Volume 12 (2023)
Volume 11 (2022)
Volume 10 (2021)
Volume 9 (2020)
Volume 8 (2019)
Volume 7 (2018)
Volume 6 (2017/18)
Volume 5 (2017)
Volume 4 (2015)
Volume 3 (2015)
Volume 1 (2012)
Volume 2 (1392)
Main Subjects = Management approaches in the field of smart
Number of Articles: 25
Management approaches in the field of smart
The role of augmented reality technology in the evolution of marketing: a systematic review and bibliometric analysis
fahime mahavarpour; feiz davood; Morteza Maleki MinBashRazgah
Articles in Press, Accepted Manuscript, Available Online from 19 April 2024
Abstract
Augmented Reality (AR) is an emerging topic for managers across different disciplines While augmented reality technology literature is growing, there is no comprehensive analysis of augmented reality technology in marketing transformation The research aims to bridge the knowledge gap by providing a multifaceted ... Read More Augmented Reality (AR) is an emerging topic for managers across different disciplines While augmented reality technology literature is growing, there is no comprehensive analysis of augmented reality technology in marketing transformation The research aims to bridge the knowledge gap by providing a multifaceted bibliographic overview of augmented reality technology literature in marketing and reveal its trends, areas of focus and intellectual foundations. The study is based on 496 articles published on Web of Science between 1996 and 2023. According to the findings, the concept mainly revolves around seven main areas: human-machine interaction in future of digital marketing and Metaverse, advertising and customer response in online purchases, marketing challenges in industry 4 and new technologies, the effect of virtual technology on customer loyalty in retail, adoption of behavioral technology of Tourism customers, augmented reality technology marketing in the decision-making process of buyers and brands, and finally the richness of social media in e-commerce in Covid 19. While priorities and research topics have evolved over time, key concepts such as buying experience, shopper behavior, buying decision making, technology adoption have been repeated. The three influential schools of augmented reality technology in marketing are associated with integrated theory, planned behavior theory (TPB) and cognitive evaluation theory that have shaped the intellectual foundations of the discipline but we believe that a greater diversity of fields is needed to examine and describe augmented reality technology in marketing transformation.
Management approaches in the field of smart
Analyzing the Factors Affecting the Technology Scouting Based on Artificial Intelligence in technology-Oriented Companies
Shiva sadat Ghasemi; Abbas khamseh; Seyed Javad Iranban
Articles in Press, Accepted Manuscript, Available Online from 21 April 2024
Abstract
In the contemporary landscape of technology-driven industries, the integration of artificial intelligence into technology scouting is imperative for enhancing innovation and sustaining competitiveness. This research aims to forge a framework for technology scouting based on artificial intelligence, with ... Read More In the contemporary landscape of technology-driven industries, the integration of artificial intelligence into technology scouting is imperative for enhancing innovation and sustaining competitiveness. This research aims to forge a framework for technology scouting based on artificial intelligence, with a specific focus on technology-based companies. Employing a qualitative approach, data collection utilized the meta-synthesis method devised by Sandelowski and Barroso. This involved a systematic review of 28 articles relevant to the research goal out of a pool of 253 primary articles. The final selection of articles was based on predefined inclusion criteria. The research's validity was confirmed through adherence to criteria, team meetings, expert consultations, and an exhaustive audit for theoretical consensus, while reliability was ascertained through the Critical Evaluation Skills Programme. The framework spans five dimensions: technology scouting tools, technology life cycle, firm environment, firm's approach to the environment, and firm's absorptive capacity. The findings underscore the pivotal role of AI-based technology scouting tools, elucidate the nuanced dynamics of the technology life cycle, and reveal the multifaceted aspects of the enterprise environment. The research outlines strategic approaches for navigating the evolving technology landscape, underscoring the imperative of absorptive capacity for the effective utilization of artificial intelligence technologies. By delivering actionable insights and strategic counsel, this research serves to furnish technology-based companies with a robust underpinning for negotiating the intricate intersection of AI and technology surveillance. In doing so, it propels sustainable growth, fortifies competitive advantage, and fosters enduring innovation.IntroductionIn the dynamic world of technology-driven industry, the role of strategic technology management, particularly in the technology selection and acquisition phases, cannot be overemphasized if success is sought in innovation-driven companies. Focusing on technology-oriented companies that currently face a rapid industrial evolution, the present study highlights the indispensable role of technology scouting, equipped specifically with artificial intelligence (AI), in grappling with the imminent competitive environment. The study proposes a framework that anticipates a future where AI plays a central role in technology acquisition and that strives to enhance absorptive capacities by bridging the adaptation gap. Drawing upon AI, the propsoed framework not only ensures proper technology selection by firms but also drives them toward cutting-edge technological innovations. Serving as a guide for decision-makers, technology strategists, and specialists, the study is expected to contribute, both theoretically and practically, to the understanding and advancement of technology scouting in tech-driven companies. Moreover, it explores and identifies the needs of organizations navigating the intricate technology landscape to derive actionable insights that ensure sustainable innovation leadership.What is the framework for technology scouting based on artificial intelligence in technology-oriented companies? Literature ReviewIn today's rapidly evolving tech landscape, it is essential to cope with the changing business environment (Kujawa and Paetzold, 2019). Ahammad et al. (2021) linked strategic agility to search strategies. Wang and Quan (2021) studied the impact of technology selection uncertainty on firms’ absorptive capacity. Vuorio et al. (2018) explored the significance of competitive edge in tech-driven enterprises. Kerr and Phall (2018) developed a scouting process model. Nasullaev et al. (2020) reiterated the alignment of strategy and tech scouting. Xu et al. (2021) advocated patent analysis in scouting. Sikandar et al. (2021) reiterated patents' innovation measure. Tabrizi et al. (2019) observed a shift to tech-centric business models. Stute et al. (2021) noted the importance of AI in supply chain enhancement. Mariani et al. (2023) classified the motivations underlying AI adoption. Stahl et al. (2023) addressed AI ethics while D'Almeida et al. (2022) categorized AI applications. Wang et al. (2020) identified AI algorithms. Despite these efforts, scant research has been reported on tech transformation, especially AI. This study adopts the meta-synthesis method to explore the digital transformation complexities, focusing on AI's transformative potential and bridging the gaps to derive a roadmap for navigating tech-driven industries. MethodologyEmploying a qualitative approach and the meta-synthesis method, a seven-step process (including goal setting, review, selection, extraction, analysis, quality control, and model development) was meticulously followed to develop an AI-based technological scouting model for advanced tech firms. A systematic search yielded 253 articles, 28 of which met the inclusion criteria and were validated through team meetings, software analysis, and expert consultation. Reliability was ensured since 89% of the articles received excellent scores via the Critical Evaluation Skills Program, indicating high quality. ResultsThe research adopted a classified analysis perspective, utilizing inductive analysis based on Sandelowski and Barroso (2007). This involves extracting primary codes related to AI-based technology observation in high-tech companies, identifying patterns through open coding, and classifying concepts into sub-categories and main categories via axial coding. Table 1Factors Affecting AI-Based Technology ScoutingCategorySubcategoryConceptsTechnology Scouting ToolOpen Source Intelligence (OSINT) ToolsWeb scraping tools, social media monitoring, online forums, patent databases, news aggregators, competitive intelligence tools, and data analytics platforms.Machine Learning and AI ToolsNatural Language Processing (NLP), predictive analytics, pattern recognition, chatbots, sentiment analysis, machine learning, and cognitive computing tools.Collaboration and Communication PlatformsOnline collaboration tools, project management platforms, virtual team collaboration, idea management, crowdsourcing, communication apps, and workflow automation.Technology Life CycleInnovation and InventionIdea generation, R&D, concept testing, prototyping, patenting, technology transfer, proof of concept, funding, collaborative research, and feasibility studies.Technology Adoption and DiffusionTechnology readiness, market analysis, adoption theories, market penetration, standardization, compliance, user testing, and overcoming adoption barriers.Technology Evolution and ObsolescenceContinuous improvement, iterative development, versioning, obsolescence management, legacy systems, discontinuation planning, sustainability, disruptive tech, and sunset planning.Company EnvironmentCompetitive Landscape AnalysisCompetitor mapping, SWOT analysis, industry benchmarking, market share analysis, competitive intelligence, PESTLE analysis, collaboration strategies, positioning, and sustainable advantage.Regulatory and Legal EnvironmentIntellectual property management, standards compliance, regulatory impact, patent landscape analysis, legal risk, data protection, ethics, antitrust, government policies, and international regulations.Internal Organizational EnvironmentCulture, cross-functional collaboration, governance, change management, talent, agile structures, infrastructure, decision-making, metrics, and employee engagement.The Company's Approach in Facing the EnvironmentInnovation Strategy FormulationRoadmapping, open innovation, blue ocean strategy, core competency analysis, innovation ecosystems, portfolio management, ambidextrous approach, horizon scanning, lean methodologies, and design thinking.Adaptive and Resilient PracticesCrisis management, scenario planning, risk management, agile project management, supply chain resilience, continuous learning, adaptive capabilities, technology portfolio flexibility, and fostering innovation culture.Strategic Alliances and PartnershipsCollaborative innovation, joint ventures, technology ecosystems, university-industry collaborations, innovation networks, open source, licensing, technology transfer, competition, and strategic partnerships.Absorption Capacity of the CompanyLearning and Knowledge ManagementOrganizational learning, knowledge creation, sharing platforms, communities of practice, intellectual capital, training programs, technology scouting, learning culture, and tacit knowledge transfer.Resource Allocation and UtilizationTechnology budgeting, allocation models, ROI analysis, portfolio management, cross-functional sharing, resource efficiency, project prioritization, dynamic reallocation, innovation finance, and risk management.Adoption of Emerging TechnologiesScanning trends, piloting new tech, foresight methodologies, early adoption, readiness assessments, and collaborative ecosystems for adoption, mitigating risks, cross-functional teams, integration, and continuous monitoring. DiscussionTo address the crucial gap in technology scouting in technology-oriented companies involved in the joint AI and technology scouting, the study develops a framework of five dimensions. Open-source smart tools and machine learning are explored as essential components of the "Technology Scouting Tool"dimension to contribute to the development of a cohesive strategy. The "Technology Life Cycle" dimension guides the firm through the innovation, adoption, and evolution stages. The "Company Environment" dimension adopts a multifaceted approach, considering competitive analysis, regulatory factors, and internal dynamics. The strategic components of the "Firm's Approach to the Environment" underline the contributions of innovation strategy, adaptability, and alliances while "Firm's Absorptive Capacity" offers practical insights by underscoring learning, resource allocation, and technology adoption. ConclusionThe proposed framework provides a strategy tailored for tech-oriented firms incorporating AI into scouting and offers strategic insights across the five dimensions to tackle nuanced challenges in the technology landscape. Advocating advanced open-source tools and strategic approaches, it explores the technology life cycle, considers diverse aspects of firm environment, and launches an AI-driven future. Acknowledging limitations and emphasizing proper deployment of AI, the study lays the foundations for future studies to validate and expand the framework while ensuring responsive and sustainable application of AI-based surveillance technologies in corporate contexts. Keywords: Artificial intelligence, Technology scouting, Technology-oriented companies, Digital transformation.
Management approaches in the field of smart
A model for online donation intention for crowdfunding of charities in Iran
Mohammadakbar Sheikhzadeh; Mohammad Taghi Taghavifard; iman raeisivanani; Jahanyar Bamdadsoofi
Volume 12, Issue 48 , December 2024, , Pages 1-31
Abstract
Crowdfunding is an effective way to achieve the non-profit goals of the charities which can be expanded using information and communication technology. In this regard, this study was conducted with the aim of providing an online donation intention model for collective financing of charitable institutions ... Read More Crowdfunding is an effective way to achieve the non-profit goals of the charities which can be expanded using information and communication technology. In this regard, this study was conducted with the aim of providing an online donation intention model for collective financing of charitable institutions in Iran. The current research is an applied-developmental research in terms of its purpose, and it is considered a cross-sectional survey research from the data collection point of view. The statistical population in the qualitative section includes managers of charity institutions and university professors. Sampling was done using a purposeful method and theoretical saturation with 10 interviews. In the quantitative section, the views of 357 benefactors were used. The data collection tool is a semi-structured interview and a researcher-made questionnaire. To analyze the collected data, qualitative thematic analysis and partial least squares were used. The research findings showed that the technical infrastructure facilitating conditions, the quality and transparency of the website information, the security of the site and the application, and the preservation of privacy affect the perceived risk. Perceived risk affects the expectation of effort and the pleasure of helping others and leads to the expectation of performance and social influence. Finally, online donation intention is strengthened through trust.IntroductionToday, charity institutions in the country can expose to the various needs of the needy to the public using crowdfunding platforms, so that with the participation of people the necessary financial resources are provided and the problems of the needy and the deprived are solved. In this field, practical and scientific activities have also been carried out however one of the most important issues neglected from the researchers’ view point and activists in this field is the discussion of the desire or intention of online donation among benefactors. The best online donation platforms and the use of the latest technologies are not enough to attract public participation, and it is not easy to encourage and motivate people to donate online. This issue itself can be discussed from various aspects. On the one hand, the basic element of this method of financing is the maximum participation of people, and on the other hand, members of the society have little knowledge about the issue and do not have much desire to attend such calls.Therefore, in general, it can be said that the intention to donate online is a fundamental factor in the success of the efforts of the country's charities for crowdfunding. The basic question of this research is that: what is the online donation intention model for collective financing of charities in Iran?Literature ReviewCrowdfunding is an alternative way to finance a project with specific goals at a specific time through an online platform. The phenomenon of crowdfunding is emerging in the field of financing resources, goods and services in the modern digital field (Jiao and Yue, 2021). The current study focuses on the crowdfunding approach based on donations in Iranian charities. This method is mostly used in non-profit and philanthropic projects, and the participants do not expect any financial support, and are mostly used to finance charities, religious places, and civil institutions (Salido et al., 2021). In the crowdfunding method based on donation, the participants do not have any expectations for the provided financial support. The donor believes wholeheartedly in the correctness of his act and considers it to be socially beneficial. This model is usually used in financing civil institutions and charities (Van Thienbroek et al., 2023).MethodologyThis is an applied-developmental research. The population of participants in the qualitative section includes theoretical experts and experimental. Sampling was done with a purposeful method and theoretical saturation was achieved with 10 interviews. The sample size was estimated to be 357 people using Cochran's formula.The main tool for collecting research data is a semi-structured interview and a researcher-made questionnaire. And then, using ISM, the relationships between the main factors affecting the intention to donate online were determined by experts. The interview included 6 basic questions and was conducted in a semi-structured way. The research questionnaire includes 10 main constructs and 51 items with a five-point Likert scale. Thematic analysis was used to identify the categories of online donation intention for crowdfunding of charities in Iran. Data analysis was done in qualitative phase with MAXQDA software and in quantitative phase with Smart PLS software.ResultsThe results of the interviews were analyzed by the qualitative method of thematic analysis based on the six-step method of Etrid-Straling (2001). 830 open codes were identified in the first stage. After analysis and review, we reached 5 overarching themes, 10 organizing themes and 51 basic themes as below:Overarching themes: Social factors- Technical factors-Individual factors- Security factors- Consequence factors.Organizer themes: Performance expectation- Endeavour expectation- Social influence- Quality and transparency of website information- Technical infrastructure facilitating conditions- Trust- The joy of helping others- Perceived risk- Site and application security and privacy- Intention to donate online.DiscussionThe present study was conducted with the aim of presenting the online donation intention model for the collective financing of charitable organizations in Iran. Based on the results, it was determined that the facilitating conditions of the technical infrastructure, the quality and transparency of the website information, the security of the site and the application, and the protection of privacy affect the perceived risk. In the results of Zhang et al.'s (2023) and Shahidi and Kivani's (1401) studies, the technical infrastructure and website information components are also mentioned as important elements in the intention to donate online, and from this point of view, it is consistent with the results of the present study. It was also shown that the perceived risk affects the expectation of effort and the pleasure of helping others and leads to the expectation of performance and social influence. In the results of the studies of Hassanzadeh Sarostani et al. (2017) and Bass and Rushdi (2023), the importance of paying attention to the perceived risk is also mentioned, and from this point of view, it is consistent with the results of the present study. Finally, the results of the research showed that online donation intention is strengthened through trust. This importance has been confirmed in the results of Shahabi-Shojaei et al.'s study (1401).ConclusionThe present study was conducted with the aim of presenting the online donation intention model for the collective financing of charitable institutions in Iran. Based on the results, it was determined that the facilitating conditions of the technical infrastructure, the quality and transparency of the website information, the security of the site and the application, and the protection of privacy affect the perceived risk. It was also shown that the perceived risk affects the expectation of effort and the pleasure of helping others and leads to the expectation of performance and social influence. Finally, the results of the research showed that online donation intention is strengthened through trust.
Management approaches in the field of smart
Generative mechanisms of digital banking ecosystem evolution
vahid khashei varnamkhasti; Mahdi Ebrahimi; Shahram Khalil Nezhad; Fatemeh Motahari nejad
Volume 12, Issue 48 , December 2024, , Pages 33-81
Abstract
.Today, digitization is considered as a requirement for all financial and monetary institutions and markets, and the banking industry is no exception. However, moving to digital banking is not an easy task for banks, and the digital revolution has become a major challenge for this industry. In order ... Read More .Today, digitization is considered as a requirement for all financial and monetary institutions and markets, and the banking industry is no exception. However, moving to digital banking is not an easy task for banks, and the digital revolution has become a major challenge for this industry. In order to keep their business stable, banks need to launch digital platforms and create robust ecosystems around them that have the ability to evolve and adapt to the challenges caused by the chaotic and unpredictable environment in which organizations operate and the increase in internal inefficiencies. Therefore, this research was conducted with the purpose of modeling the generative mechanisms of the evolution of Iran's digital banking ecosystem. For this purpose, the qualitative content analysis method has been used. A semi-structured interview has been used to collect information using the opinions of experts in the field of digital banking. The analysis of the conducted interviews led to the identification of 674 themes, 181 codes, 59 subcategories, and 20 categories. The results of the research show that there are external factors, including cyber-attacks, political and governance obstacles, the increasing progress of communication and information technology, changes in the competitive environment, and conflicting investment relationships in the financial and banking fields, and internal factors, including the absence of strong security infrastructure in the network and weak security, weakness in digital human capital, changing needs and demands of actors, weakness in the traditional business model, and the lack of a management perspective regarding the growth of digital banking and regulatory and legal requirements, are the stimuli for the co-evolution of the elements of the digital banking ecosystem, which occurs with the activation of reinforcing and transformative generative mechanisms. The consequences of the evolution of the digital banking ecosystem can be classified into three levels: users, owner, and society.IntroductionIn the digital revolution, with the change in customer behavior and expectations and the behavior of businesses, the structure of the competition and the strategic context of the business world has changed, and the banking industry is not an exception to this rule; therefore, digitalization is considered a requirement for the banking industry. However, moving to digital banking is not an easy task for banks, and the digital revolution has become a major challenge for this industry. The previous studies have revealed that, so far, some banks have not been successful in facing the fundamental changes of the digital age and have not been able to take fundamental actions to stabilize their businesses. To this end, the first step to realizing these changes in the banking industry is a complete reconsideration of customer relations and the method of providing value to meet customer needs, business models, platforms, and ecosystems. Yet it is not enough to set up a digital platform ecosystem and just rapidly multiply it, as keeping it stable is also highly important as well. In fact, digital platform ecosystems that can be sustained over the long term are very rare. Therefore, digital platform ecosystems must have the ability to evolve and adapt to the challenges caused by the chaotic and unpredictable environment that organizations operate in as well as the increase of internal inefficiencies. Thus, besides the need for a complete rethinking of the digital banking ecosystem, the manner in which its evolutionary process has been in Iran's banking industry is important. Thus far, neither of these issues has been investigated in Iran which signifies the necessity of applied and fundamental research. The current research tries to fill this gap in the country.Research Question(s)What are the elements of the digital banking platform ecosystem and which will evolve in the future?What are the generative mechanisms of digital banking platform ecosystem evolution?What are the stimulating factors and consequences of the evolution of the digital banking platform ecosystem?Literature ReviewNowadays, digitization has become a strategic priority for the banking industry, and the establishment of digital banking requires creating a strong ecosystem around the digital banking platform and developing it. However, so far, there has not been any systematic and comprehensive approach regarding the evolution of the digital platform ecosystem. Previous studies identify digital platform ecosystems as highly evolving socio-technical arrangements that require rapid development and adaptation to ensure their long-term sustainability. Due to the lack of a clear conceptualization of the evolution of digital platform ecosystems, Stykova (2019) integrated different perspectives and proposed a novel conceptualization of the evolution of digital platform ecosystems. According to his studies, the evolution of the digital platform ecosystem delineates continuous changes in the digital platform ecosystem in relation to its actors, architecture, and governance. Through these changes, the simultaneous development of platform structures, infrastructure, functionalities, and governance regime occurs. The endogenous and exogenous events and factors emerging during the evolution of the digital platform ecosystem challenge the configuration of the ecosystem and lead to changing it. Staykova defines two types of generative mechanisms for the evolution of the digital platform ecosystem: transformative and reinforcing.MethodologyIn this research, the qualitative content analysis method is used. A group of experts in the field of digital banking in Iran's banking industry who have deep insight and the necessary knowledge about the subject of the research participated as the statistical population of this research. The purposive sampling method was employed for sampling and continued until the theoretical saturation was reached. Therefore, in this research, 21 interviews were conducted, and due to the incompleteness of some of them, in the end, by analyzing 18 interviews, the research questions were answered, and theoretical saturation was achieved.ResultsThe analysis of the interviews led to the identification of 674 themes, 181 codes, 59 subcategories, and 20 categories. Based on the results of categorization in thematic analysis and review of the theoretical foundations and the related literature, the elements of the digital banking platform ecosystem, including ecosystem actors, platform architecture, and platform governance were identified. Moreover, External factors, such as cyber-attacks, political and governance obstacles, the increasing progress of communication and information technology, changes in the competitive environment, and conflicting investment relationships in the financial and banking fields, as well as internal factors, such as the absence of strong security infrastructure in the network and weak security, weakness in digital human capital, changing needs and demands of actors, weakness in the traditional business model, and lack of management perspective regarding the growth of digital banking and regulatory and legal requirements, are the co-evolutionary stimuli of digital banking platform ecosystem elements, which appear as a result of the activation of generative, reinforcing and transformative mechanisms. Finally, the implications of the evolution of the ecosystem of the digital banking platform can be classified into three levels. The benefits of the evolution of the ecosystem for users are increasing the speed of providing and receiving services, gaining usefulness, improved security, freedom in providing and receiving services, ease of access, and co-creation of value. The implications of evolution for the owner (organization) are the Orchestrator role of the owner, dynamic capability, market size, increased revenue, increased productivity, and business sustainability. Furthermore, the outcomes of the evolution of the ecosystem at the community level include social, environmental, and economic benefits, which are indicators of reaching the maturity stage in the life cycle of the digital banking platform ecosystem.
Management approaches in the field of smart
The effect of customer interaction with the brand as an antecedent of customer loyalty: analysis of three cognitive, emotional and behavioral approaches
vahideh alipoor; Mohammadreza Saadi; atefeh mehri bazghaleh
Volume 12, Issue 48 , December 2024, , Pages 83-117
Abstract
This study aimed to investigate the effect of brand interaction through social media on brand loyalty through brand equity. The research is a descriptive research of the correlational type in terms of practical purpose and based on the method. The statistical population of this research includes the ... Read More This study aimed to investigate the effect of brand interaction through social media on brand loyalty through brand equity. The research is a descriptive research of the correlational type in terms of practical purpose and based on the method. The statistical population of this research includes the customers of three Iranian brands, My, Cinere and Callista. The size of the population is considered unlimited and the G-POWER tool was used to determine the sample size and the statistical sample size was calculated to be 199 people. A simple random sampling method was chosen for data collection and the data collection required in this research was done using a localized standard questionnaire. In order to confirm content validity, CVI and CVR and expert panel were used. In order to determine the reliability of the questionnaire, Cronbach's alpha coefficient, combined reliability and homogeneous reliability were used. Because the data do not follow normal modeling; Therefore, structural equation model and partial least squares method and PLS software were used for hypothesis testing and path analysis. The results of this study showed that customer interaction with the brand through social media can have a positive effect on brand loyalty. Also, brand equity was a positive mediating factor in the relationship between brand interaction and brand loyalty. Among the three cognitive, emotional and behavioral paths, the behavioral path with a path coefficient of 0.630 is the best path in influencing customer interaction with the brand on brand loyalty. IntroductionAccording to a Harvard Business Journal study, a 5% increase in customer loyalty can increase company profits by 25-95%. The importance of building and maintaining strong and long-term business relationships with customers is a great strength for brands (Rather, 2018). In recent years, customer interaction with the brand has become an important concept due to its promising impact on customer behavior (Rather, 2018; Rather & Sharma, 2017). By interacting with customers in virtual spaces and social networks, the brand can offer unique benefits.According to the statistics and figures announced by the Radio Communications Regulatory Organization, the number of internet users in Iran has reached more than 79 million people in 2021. This is a large number of people, each of whom may be customers of different brands and companies. Therefore, researching the impact of the customer's interaction with the brand, which usually takes place in the virtual space, on customer loyalty in Iran seems to be very necessary. Considering the importance of customer loyalty to the brand and the need for brands to promote effective communication with customers, this study investigated the impact of customer's interaction with the brand on customer loyalty. This study attempts to answer questions such as: "Can the customer's interaction with the brand lead to an increase in the customer's loyalty to the brand?" and "What type of interaction with the brand has the greatest influence on the customer's loyalty?" Literature review2.1. customer interaction with the brand via social mediaSocial media focuses on collaboration, conversation and exchange between users. Social networks are online hosts that allow members to create their own private profiles and interact with each other (Tuten & Solomon, 2017). Companies are increasingly looking to engage customers and interact with their brands. The concept of customer interaction with the brand encompasses three dimensions, namely the cognitive, emotional and behavioral dimensions, making it a multidimensional concept for study. Customer interaction with the brand emphasizes the relationship between the customer and the brand (Islam et al., 2019). Interaction with the brand may be more influential than perceived value and service quality, which are known to be important factors for brand loyalty (So et al., 2016).2.2. customer interaction with the brand via social media and brand equityCurrently, social media plays an important role in creating brand equity through interaction with customers. Therefore, customers' interaction with brands through social networks is a symbol of their greater commitment to brands, and this issue increasingly contributing to brand equity (Choedon & Lee et al., 2020). enhances the brand, which in turn creates strong, favorable and unique connections with the brand and influences their purchasing decisions and creates value (Elsharnouby et al., 2021), which means the creation of brand equity (Schivinski & Dabrowski, 2015). MethodologyAs the current research focuses on observable facts, it is part of the positivist paradigm. Due to its specific application in the field of brand management, it is considered practical research. As far as the method of data collection is concerned, it is a descriptive and survey-type study whose temporal scope lies in the area of cross-sectional research. The statistical population of this study includes all customers of Iranian cosmetics and health brands. For this purpose, the followers of the social pages of three famous Iranian brands in the field of cosmetics and health products such as My, Cinere and Callista were surveyed. Since the number of customers of these three famous Iranian brands is more than one hundred thousand people, the size of the community is considered unlimited. The G-POWER tool was used to determine the sample size. According to Cohen, reducing the alpha error leads to an increase in the generalizability and accuracy of the research results. By lowering the alpha error to a lower level, the likelihood that the researcher will incorrectly reject their hypothesis and commit a type 1 error is reduced. In addition, by increasing the power of the test, the second type error is reduced and the precision of the research results is increased (Cohen-Tannoudji et al., 1998). For this purpose, the sample size was set at an error level of 0.1 and a test power of 0.85 and with a number of 7 variables, 199 subjects.A simple random sampling method was chosen for data collection. The data collection required for this study was done using a localized standard questionnaire consisting of two parts: demographic questions and specific questions in the area of research variables. ResultsThe results obtained show that the cognitive, emotional and behavioral interactions with the brand have a positive and significant influence on the brand equity, with path coefficients of 0.330, 0.410 and 0.751, respectively. brand equity also has a positive and significant influence on customer cognitive, emotional and behavioral loyalty, with path coefficients of 0.894, 0.870 and 0.839, respectively. The Sobel test was used for the significance of the mediating effect of one variable on the relationship between two other variables. Three hypotheses - H7 cognitive path, H8 emotional path and H9 behavioral path - measure the mediating role of brand equity in the relationship between the dimensions of customer interaction and customer loyalty. The cognitive path with a path coefficient of 0.295 and a z- value of 6.183, the emotional path with a path coefficient of 0.356 and a z- value of 7.407 and the behavioral path with a path coefficient of 0.630 and a z-value of 11.18 were confirmed. DiscussionThe present study was conducted with the aim of determining the impact of customers' interaction with the brand via social media on brand loyalty, considering the mediating role of brand equity and the priority of the three cognitive, emotional and behavioral pathways in these impacts. Specifically, the impact of the dimensions of customer interaction with the brand, including cognitive interaction, emotional interaction, and behavioral interaction, on the dimensions of brand loyalty, including cognitive loyalty, emotional loyalty, and behavioral loyalty, was examined under the mediating role of brand equity. ConclusionAccording to the path coefficient, the behavioral path with a path coefficient of 0.630 is the best path to influence the customer's interaction with the brand on brand loyalty. Therefore, the said brands should communicate less emotionally on social media and be more precise so that the content presented on social media creates a sense of fit and congruence between the customer's image and the brand and a positive image of the said companies' brand remains in the customer's mind even when they compare it with other brands. Therefore, the marketing managers of the mentioned brands are recommended to share the latest and trending content and organize and engage in activities that are considered trendy and show the popular, modern and successful personality of social media users so that they can support the customers' need for self-expression.Keywords: Customer Engagement, Customer Loyalty, Brand Equity, Social Media, Beauty Brands
Management approaches in the field of smart
Designing a Digital Content Marketing Conceptual Model: A Grounded Theory Approach
Kamran Feizi; Hormoz Mehrani; Hossein Vazifehdoost; Ehsan Sadeh
Volume 12, Issue 48 , December 2024, , Pages 157-195
Abstract
The purpose of this research is to identify the main components and dimensions of digital content marketing according to the conditions of Iran and to present a model using a qualitative method based on the Grounded Theory approach. Data were collected through semi-structured in-depth interviews with ... Read More The purpose of this research is to identify the main components and dimensions of digital content marketing according to the conditions of Iran and to present a model using a qualitative method based on the Grounded Theory approach. Data were collected through semi-structured in-depth interviews with experts. These experts included university professors in the field of digital content marketing and managers and activists of advertising and digital marketing agencies. Using targeted sampling and after conducting 15 in-depth interviews, theoretical saturation was achieved after the implementation and analysis of interviews and open, axial, and selective coding. The results showed that digital content marketing is realized by these conditions. Causal conditions (Internet development, ease of use, popularity of cyberspace, ease of communication with customers, virtual network features, The appeal of Digital Content Marketing, changing customer behavior, changing current structures), contextual conditions (personal characteristics, social characteristics), intervening factors (technical limitations, increasing competitors, lack of access, unawareness, severity of the spread of Covid-19), central category (Digital Content Marketing), strategies (make it enjoyable, increasing participation, providing various services to users, using various methods to increasing audience, exchange of information, infrastructure improvement, audience-friendly style, customer orientation), and consequences (market expansion, increasing profitability, groundwork for brand creation). The results indicate that the research model is acceptable level. IntroductionThe emergence of digital networks and the wide spread of technology dramatically changed human life compared to the latest technological tools of the previous decades (Torkestani et al, 2020), so that nowadays customers have significantly changed their behavior in line with the technology and economic environment of the world (Rostami et al, 2022). Modern advertising is more cost-effective and inexpensive than traditional advertising (Abdulle, 2022). Therefore, to attract customers, trust must be gained first, and customers should feel satisfied with our brand before purchasing a product or service. These features can be found in digital content marketing (Mozaffari et al, 2023). Inflation and the prevailing economic recession have created difficult conditions for individuals and businesses (Naseri, 2017). To overcome these difficult conditions, a native model must be explained in the field of digital content marketing.Research Question (s)The main research question is as follows: What is the conceptual model for digital content marketing? What are the main components and dimensions of this model? Literature ReviewTorkestani et al. (2022) discussed the possibility of personalizing content for each audience, the emotions hidden in the content and the date of publication of the content, the way the author is a member and his identity in the online community. Tahmasebpour et al. (2022) considered digital marketing elements to include six components: technical features of digital tools, relative advantage, cost to customers, management of items and processes, promotion, service quality, and information quality. Rostami et al. (2022) also prioritized the factors affecting marketing in digital businesses in their research and did not provide a model that included all aspects of this issue. (Naseri, 2017) also only looked at content features in four categories, content inherent elements, form elements, content distribution media elements and effectiveness measurement elements. (Naseri, 2017) examined only the characteristics of the content in four categories; intrinsic content elements, form elements, content distribution media elements, and effectiveness measurement elements. (Lou & Xie, 2020) also emphasized in their research on shaping brand experience and customer loyalty of. Boban et al. (2020) only investigated the relationship between content entertainment and informational social influence and between self-expression and normative social influence and electronic word-of-mouth communication. Furr. (2019) considered digital content marketing as a branding tool for colleges and universities. Taiminen & Ranaweera, (2019) focused on support, engagement, and interaction in brand communication and perceptions. MethodologyIn terms of purpose, this research is fundamental and applied, and in terms of nature, it is in the category of qualitative research. In terms of approach, the Grounded Theory and paradigm model of Strauss and Corbin have been used as a research plan, which is based on the identification of causal conditions, contextual conditions, central category, intervening conditions, strategies and consequences, and describing the relationships between them. A semi-structured in-depth interview was conducted with 15 experts who were selected in a non-probable and purposeful manner. Sampling was performed until theoretical saturation using the snowball method. The research community includes digital experts (academic and non-academic). This group includes university professors in the field of digital content marketing, as well as activists and specialists in the field of digital content production (institutions and agencies of digital marketing and advertising). They have at least five years of scientific, research, and executive experience in DCM and at least a master's degree or doctorate in the fields of marketing management, information technology management, and other related fields. In the analysis of the data obtained from the interviews, after the full implementation of the text of the interviews, MaxQuda 2020 was used. Immediately after each interview, the interview text was extracted and typed, entered into the software, and open, axial, and selective coding procedures were performed. ResultsThe information obtained from the interviews resulted in the extraction of 135 concepts (open coding), which were placed in the form of 26 subcategories (axial coding) and 5 main categories (selective coding), as follows: Internet development, ease of use, popularity of cyberspace, ease of communication with customers, virtual network features, the appeal of Digital Content Marketing, changing customer behavior, changing current structures, technical limitations, increasing competitors, lack of access, unawareness, severity of the spread of Covid-19, personal characteristics, social characteristics, make it enjoyable, increasing participation, providing various services to users, using various methods for increasing the audience, exchange of information, infrastructure improvement, audience-friendly style, customer orientation, market expansion, increasing profitability, groundwork for brand creation.The paradigm model is presented in figure 1.Figure.1. Paradigm model of the research ConclusionThis article aims to design a digital content marketing model. Making it enjoyable in this research includes gamification in social networks, visualizing content according to people's tastes, using humorous content, and entertaining content. The obtained results showed that making it enjoyable is an effective strategy for digital content marketing. In this research, the following were discovered to increase participation in digital content: using celebrities, participating in online campaigns, holding contests, and building trust and commitment in customers. The results also show that increasing participation is an important strategy in digital content marketing. The services that can be paid in the production of digital content to attract the audience are as follows: offering discounts, bonuses to users, free training, and support. The obtained results also show that providing diverse services to users is an influential factor in digital content marketing strategies. Various methods of increasing the audience in this research include: providing outstanding and strange information, producing educational content, producing therapeutic content, producing sports content, using new ideas to produce content, producing fresh and new content, teaching new methods of producing content, increasing quality, extensive advertising, social network viral marketing, and content creation based on frequent words. The results show that the use of methods to increase the audience is the most effective strategy. Information exchange includes modeling external pages, modeling successful pages, participation in online campaigns, and content exchange. The obtained results show that information exchange has a significant impact on digital content marketing strategies. Improving the infrastructure in the field of digital content includes increasing the speed of the Internet, website design, and the production of powerful internal applications, which the results show is one of the most important strategies. Audience-friendly style also includes creating differentiation, special and unique style, being up-to-date; using one of the special effects is the mastery of body language. The results show that an audience-friendly style is one of the most effective strategies in digital content marketing. Customer orientation also includes content production based on society's problems, compliance with professional ethics, monitoring customer needs, finding customers' tastes, and honesty in content production. The obtained results show that customer orientation is an important strategy in digital content marketing.Keywords: Digital Content Marketing, Online Marketing, Brand Awareness, Grounded Theory. The purpose of this research is to identify the main components and dimensions of digital content marketing according to the conditions of Iran and to present a model using a qualitative method based on the Grounded Theory approach. Data were collected through semi-structured in-depth interviews with experts. These experts included university professors in the field of digital content marketing and managers and activists of advertising and digital marketing agencies. Using targeted sampling and after conducting 15 in-depth interviews, theoretical saturation was achieved after the implementation and analysis of interviews and open, axial, and selective coding. The results showed that digital content marketing is realized by these conditions. Causal conditions (Internet development, ease of use, popularity of cyberspace, ease of communication with customers, virtual network features, The appeal of Digital Content Marketing, changing customer behavior, changing current structures), contextual conditions (personal characteristics, social characteristics), intervening factors (technical limitations, increasing competitors, lack of access, unawareness, severity of the spread of Covid-19), central category (Digital Content Marketing), strategies (make it enjoyable, increasing participation, providing various services to users, using various methods to increasing audience, exchange of information, infrastructure improvement, audience-friendly style, customer orientation), and consequences (market expansion, increasing profitability, groundwork for brand creation). The results indicate that the research model is acceptable level. IntroductionThe emergence of digital networks and the wide spread of technology dramatically changed human life compared to the latest technological tools of the previous decades (Torkestani et al, 2020), so that nowadays customers have significantly changed their behavior in line with the technology and economic environment of the world (Rostami et al, 2022). Modern advertising is more cost-effective and inexpensive than traditional advertising (Abdulle, 2022). Therefore, to attract customers, trust must be gained first, and customers should feel satisfied with our brand before purchasing a product or service. These features can be found in digital content marketing (Mozaffari et al, 2023). Inflation and the prevailing economic recession have created difficult conditions for individuals and businesses (Naseri, 2017). To overcome these difficult conditions, a native model must be explained in the field of digital content marketing.Research Question (s)The main research question is as follows: What is the conceptual model for digital content marketing? What are the main components and dimensions of this model? Literature ReviewTorkestani et al. (2022) discussed the possibility of personalizing content for each audience, the emotions hidden in the content and the date of publication of the content, the way the author is a member and his identity in the online community. Tahmasebpour et al. (2022) considered digital marketing elements to include six components: technical features of digital tools, relative advantage, cost to customers, management of items and processes, promotion, service quality, and information quality. Rostami et al. (2022) also prioritized the factors affecting marketing in digital businesses in their research and did not provide a model that included all aspects of this issue. (Naseri, 2017) also only looked at content features in four categories, content inherent elements, form elements, content distribution media elements and effectiveness measurement elements. (Naseri, 2017) examined only the characteristics of the content in four categories; intrinsic content elements, form elements, content distribution media elements, and effectiveness measurement elements. (Lou & Xie, 2020) also emphasized in their research on shaping brand experience and customer loyalty of. Boban et al. (2020) only investigated the relationship between content entertainment and informational social influence and between self-expression and normative social influence and electronic word-of-mouth communication. Furr. (2019) considered digital content marketing as a branding tool for colleges and universities. Taiminen & Ranaweera, (2019) focused on support, engagement, and interaction in brand communication and perceptions. MethodologyIn terms of purpose, this research is fundamental and applied, and in terms of nature, it is in the category of qualitative research. In terms of approach, the Grounded Theory and paradigm model of Strauss and Corbin have been used as a research plan, which is based on the identification of causal conditions, contextual conditions, central category, intervening conditions, strategies and consequences, and describing the relationships between them. A semi-structured in-depth interview was conducted with 15 experts who were selected in a non-probable and purposeful manner. Sampling was performed until theoretical saturation using the snowball method. The research community includes digital experts (academic and non-academic). This group includes university professors in the field of digital content marketing, as well as activists and specialists in the field of digital content production (institutions and agencies of digital marketing and advertising). They have at least five years of scientific, research, and executive experience in DCM and at least a master's degree or doctorate in the fields of marketing management, information technology management, and other related fields. In the analysis of the data obtained from the interviews, after the full implementation of the text of the interviews, MaxQuda 2020 was used. Immediately after each interview, the interview text was extracted and typed, entered into the software, and open, axial, and selective coding procedures were performed. ResultsThe information obtained from the interviews resulted in the extraction of 135 concepts (open coding), which were placed in the form of 26 subcategories (axial coding) and 5 main categories (selective coding), as follows: Internet development, ease of use, popularity of cyberspace, ease of communication with customers, virtual network features, the appeal of Digital Content Marketing, changing customer behavior, changing current structures, technical limitations, increasing competitors, lack of access, unawareness, severity of the spread of Covid-19, personal characteristics, social characteristics, make it enjoyable, increasing participation, providing various services to users, using various methods for increasing the audience, exchange of information, infrastructure improvement, audience-friendly style, customer orientation, market expansion, increasing profitability, groundwork for brand creation.The paradigm model is presented in figure 1.Figure.1. Paradigm model of the research ConclusionThis article aims to design a digital content marketing model. Making it enjoyable in this research includes gamification in social networks, visualizing content according to people's tastes, using humorous content, and entertaining content. The obtained results showed that making it enjoyable is an effective strategy for digital content marketing. In this research, the following were discovered to increase participation in digital content: using celebrities, participating in online campaigns, holding contests, and building trust and commitment in customers. The results also show that increasing participation is an important strategy in digital content marketing. The services that can be paid in the production of digital content to attract the audience are as follows: offering discounts, bonuses to users, free training, and support. The obtained results also show that providing diverse services to users is an influential factor in digital content marketing strategies. Various methods of increasing the audience in this research include: providing outstanding and strange information, producing educational content, producing therapeutic content, producing sports content, using new ideas to produce content, producing fresh and new content, teaching new methods of producing content, increasing quality, extensive advertising, social network viral marketing, and content creation based on frequent words. The results show that the use of methods to increase the audience is the most effective strategy. Information exchange includes modeling external pages, modeling successful pages, participation in online campaigns, and content exchange. The obtained results show that information exchange has a significant impact on digital content marketing strategies. Improving the infrastructure in the field of digital content includes increasing the speed of the Internet, website design, and the production of powerful internal applications, which the results show is one of the most important strategies. Audience-friendly style also includes creating differentiation, special and unique style, being up-to-date; using one of the special effects is the mastery of body language. The results show that an audience-friendly style is one of the most effective strategies in digital content marketing. Customer orientation also includes content production based on society's problems, compliance with professional ethics, monitoring customer needs, finding customers' tastes, and honesty in content production. The obtained results show that customer orientation is an important strategy in digital content marketing.
Management approaches in the field of smart
Designing a model of the consequences of the application of artificial intelligence and machine learning in advertising and sales
Hosein Rahimi kolour; Rahim Mohammad khani
Volume 12, Issue 48 , December 2024, , Pages 223-270
Abstract
The digital world provides many opportunities for marketers to reach customers. However, in the fast-paced world, finding new and innovative ways to advertise and sell products and services is very important. Due to the advancement of artificial intelligence and its development in the field of advertising ... Read More The digital world provides many opportunities for marketers to reach customers. However, in the fast-paced world, finding new and innovative ways to advertise and sell products and services is very important. Due to the advancement of artificial intelligence and its development in the field of advertising and sales, professionals now have the tools to completely redefine the current understanding of branding, marketing, advertising and sales. The growing popularity of the Internet and the increased use of mobile devices are generating massive amounts of consumer data that feed artificial intelligence-based systems. This research is a type of mixed research with a qualitative and quantitative approach, which is a survey descriptive study in terms of its purpose, application, and in terms of data collection. The statistical population of the research was managers and experts in the field of digital marketing and IT in the field of advertising and sales, who were selected using the snowball sampling method. In the qualitative part, the tools for collecting information were library and articles review, interviews, and in the quantitative part, questionnaires. In the qualitative part of the data analysis method, using the theme analysis that was compiled with MAXQDA software and using the coding method, and in the quantitative part, the analysis method was based on Kendall's correlation test. According to the results of the research, 7 main themes, 22 sub-themes and 44 codes were discovered, which included the consequences of using artificial intelligence and machine learning in advertising and sales. The findings of the research can have important results for marketers and activists in the field of advertising and sales. Among the consequences of the application of artificial intelligence and machine learning, we can mention things such as understanding, recognizing and revealing consumer needs and desires, classifying target advertisements, intelligent evolution of commercial advertisements, innovation in sales, development of sales channels, and optimization of the fields of using artificial intelligence in advertising agencies Keywords:: artificial intelligence, machine learning, big data, advertising and salesIntroductionMost of the research on the use of artificial intelligence and machine learning in advertising and sales has been done in the last four years. The gap between AI research, the application of AI and machine learning in advertising and sales is still significant. Theoretical findings still need to be supported by real tools and software solutions. In the academic context, most researchers either focus on describing one or two of the newest solutions available on the market or mention very generalized application areas and focus on AI as a phenomenon and the main object of study. There is little research on the results of the general implementation of artificial intelligence in advertising and sales and the results of the implementation of specific artificial intelligence tools. Studies have been conducted on the applications and challenges of the application of artificial intelligence and machine learning in marketing, international marketing and marketing strategies. The innovation of the current study is that despite the exponential development of artificial intelligence and related technologies, its emerging application in various production environments, none of the previous studies have addressed the consequences and results of the application of artificial intelligence and machine learning in a qualitative manner in advertising and sales; Therefore, to cover the issues raised above, we intend to answer the following research question. What areas of artificial intelligence and machine learning are used in advertising and sales? What are the existing solutions based on artificial intelligence and related technologies such as machine learning in the field of advertising and sales development and optimization? Literature ReviewArtificial intelligence is a computer science technology that teaches computers to understand and imitate human communication and behavior. Today, around the world, artificial intelligence has become a hot topic in many sciences and public discussions in society; Because it seems to expand and challenge human cognitive capacity. It is obvious that artificial intelligence will become an integral part of every business organization worldwide in the long run. One of the definitions of artificial intelligence is to teach computers to learn, reason and adapt (Bardo Eritav et al., 2020). Artificial intelligence is supposed to simulate human intelligence in order to support or even expand human abilities (Ote, 2019). In other definitions, the possession of machines with rational and human thinking and action has been emphasized (Berry Hill et al., 2019; Zahouri et al. Moghadam, 2020). Machine learning (ML) is a process that uses observations or data, such as direct experience or instruction, to recognize patterns in data without human intervention, allowing you to make better decisions in the future. The goal of ML is to enable computers to learn automatically "on their own," without human intervention or assistance, so that systems can adjust their actions accordingly. Today, most AI applications use ML in marketing activities, from personalizing product offers to helping discover the most successful advertising channels, estimating churn rates or customer lifetime value, and creating superior customer groups (Tiwari et al., 2021; Shissel et al., 2020). Compared to traditional advertising production, artificial intelligence technology has increased the effectiveness of advertising production and marketing, and has made brand marketing more humane, accurate and effective, and has improved the effectiveness of advertising communications and information call rates. Advertising production using artificial intelligence technology can categorize, combine information sources, quickly generate new ideas, and implement intelligent marketing (Deng et al., 2019). MethodologyThis research is a type of mixed research with a qualitative and quantitative approach, which is a survey descriptive study in terms of its purpose, application, and in terms of data collection. The tools of data collection in the qualitative part of the library review were articles and semi-structured interviews with 18 managers and experts in the field of digital marketing and IT in the field of advertising and sales, who were selected using the snowball sampling method. The method of data analysis in the qualitative section, using theme analysis, which was compiled with MAXQDA software and using the coding method. In the quantitative part, purposeful sampling with 35 digital marketing experts and information gathering through a questionnaire, the analysis method was based on Kendall's correlation test. ResultsAccording to the results of the research, 7 main themes, 22 sub-themes and 44 codes were discovered, which included the consequences of using artificial intelligence and machine learning in advertising and sales. The findings of the research can have important results for marketers and activists in the field of advertising and sales. Among the consequences of the application of artificial intelligence and machine learning, we can mention things such as understanding, recognizing and revealing consumer needs and desires, classifying target advertisements, intelligent evolution of commercial advertisements, innovation in sales, development of sales channels and optimization of the fields of using artificial intelligence in advertising agencies. Discussion and ConclusionThe rapid development of modern technology, especially artificial intelligence, has led to the creation of powerful solutions to take advertising and sales to a whole new level. With the increased use of social media and the Internet, the amount of data available on customer behavior and customer communication is immense. Although research on the use of artificial intelligence and related technologies is still limited due to the novelty of the topic, this paper reviews existing research on innovation, the use of social media with AI, machine learning, and big data capabilities to provide opportunities to increase advertising effectiveness and Sales have been linked. Using artificial intelligence, it is possible to gain a clearer view of consumer behavior on social media that leads to brand preferences. Artificial intelligence-based systems that work in digital marketing environments focus on machine learning and big data techniques and use data-driven marketing strategies to guide and collect customer knowledge data and evaluate activity performance; Therefore, by using systems based on artificial intelligence and machine learning, facilitate decision-making processes, understanding user behavior and responses, innovation strategies, sales forecasting, understanding social network strategies, customer orientation and optimization of activities and strategic advertising planning in digital environments.Advertising and sales systems based on artificial intelligence can add value to the business, as well as turn the application of artificial intelligence and machine learning in advertising and sales into a sustainable strategy that can guide the steps a company takes to succeed in its marketing strategies, such as content analysis and optimization. social; performance analysis and media selection; Budget analysis and optimization; Identifying and evaluating target groups; Predicting reactions; monitoring the competition, it needs to realize; Therefore, the application and new uses of advertising and sales system based on artificial intelligence seem necessary for companies
Management approaches in the field of smart
Designing a model to improve digital marketing capability with an emphasis on digital marketing use indicators in industrial companies
Ghasem Zarei; Rahim Mohammad khani
Volume 12, Issue 47 , November 2024, , Pages 111-151
Abstract
AbstractThe convergence of information technology, media and communication has changed consumer behavior in terms of searching, obtaining, processing and responding to company information or services. A company's ability to plan, implement and manage digital marketing to increase its competitiveness ... Read More AbstractThe convergence of information technology, media and communication has changed consumer behavior in terms of searching, obtaining, processing and responding to company information or services. A company's ability to plan, implement and manage digital marketing to increase its competitiveness in the eyes of consumers is called digital marketing capability. The purpose of this research is to design a model for improving marketing capabilities by emphasizing the indicators of using digital marketing in industrial companies. This research is a type of mixed research with a qualitative and quantitative approach, which is a survey study in terms of its purpose, application, and in terms of data collection. The statistical population of the research was managers and experts in the field of digital marketing of industrial companies and university professors who were selected using the snowball sampling method. In the qualitative part, the data collection tool was an interview, and in the quantitative part, a questionnaire was used to identify the categories, and a semi-structured interview was used, and a questionnaire was used to validate the model. In the qualitative part of the data analysis method, the Grounded theory approach was based on the Strauss and Corbin method, which was compiled using MAXQDA software and using the coding method, and in the quantitative part, the analysis method was based on Kendall's correlation test.IntroductionThe availability of digital technologies for a growing number of companies offers new opportunities in terms of market and consumer research and analysis, as well as communicating with customers throughout the consumer life cycle and building brand awareness and loyalty. On the other hand, changes in consumer preferences and lifestyles, including the increase in time spent by consumers worldwide on digital media and their expectation of a highly personalized approach, make manufacturers' shift to digital tools a necessary condition for survival. Digital marketing strategies have been studied, however, research focused on the understanding and application of digital marketing usage indicators in digital marketing has not been analyzed and the novelty of the current study is that despite the exponential development of digital technologies and its emerging application in Unlike marketing, none of the previous studies have addressed the indicators of using digital marketing. The purpose of this study is to identify the factors influencing the improvement of digital marketing capability and to analyze a company's digital marketing usage index (DMUI) and to plan strategies derived from these indicators, as well as to identify the motivating, contextual and intervening factors to improve the digital marketing capability of industrial companies. Literature ReviewThe term digital marketing refers to almost all marketing activities that take place online. It is a collective term that includes all digital communication and advertising channels that businesses can use to communicate with existing and potential customers (Alexander, 2017) A company's ability to plan, implement and manage digital marketing is known as its digital marketing capability. It refers to a company's ability to use the Internet and other information technologies to facilitate deep customer interactions. Through these interactions, customers have access to the company's resources and information, and the company learns more about its customers. The processes, structures and skills that a company needs to succeed in the digital age are also defined as digital marketing capabilities (Chaffey, 2016). Digital transformation is a process of change that leverages technology and digital capabilities to create added value through business models, operational processes and customer experiences (Markanian, 2020). Therefore, digital transformation aims to improve entities by making significant changes in their characteristics through a combination of It is from information technology, computing, communication and connection (Viyal, 2019). Innovation Ecosystem Readiness is a measure of ecosystem readiness to accept innovation. Ecosystem interactions affect the adoption rate of organizational innovations (Wang, 2020).Adoption of digital marketing: shows the extent of use of digital marketing technology in the organization. Companies that are able to use digital marketing technology effectively tend to have higher levels of digital marketing capabilities (Wang, 2020). MethodologyThis research is a type of mixed exploratory research with a qualitative and quantitative approach, which is practical in terms of its goal. The method of data collection is, in the qualitative part, interviews, review of library documents, articles, and in the quantitative part, a questionnaire (survey). The statistical population of the research was managers and experts in the field of digital marketing of industrial companies and university professors who were selected using the snowball sampling method. In the qualitative part, the data collection tool was an interview, and in the quantitative part, a questionnaire was used to identify the categories, and a semi-structured interview was used, and a questionnaire was used to validate the model. In the qualitative part of the data analysis method, the grounded theory approach was based on the Strauss and Corbin method, which was compiled using MAXQDA software and using the coding method, and in the quantitative part, the analysis method was based on Kendall's correlation test. Results In this research, in order to meaningfully interpret the effective factors in improving digital marketing capabilities, personal views and personal experiences of experts, senior marketing managers in the digital field of industrial companies and university professors have been examined. Data collection was done through in-depth and semi-structured interviews with 18 people from the mentioned statistical community. It should be noted that the interview with the 13th person led to theoretical saturation and after that almost all the information and data were repeated, but for more certainty and the possibility of obtaining new data, we continued the interview until the 18th person. The interviews started in a semi-structured way by asking questions about the effective factors in improving the digital marketing capability, and the subsequent questions were designed based on the answers of the interviewees during the interview session, although certain frameworks were considered before the interview. The interview lasted approximately 40 minutes to an hour. The method of sampling in this research is judgmental (theoretical) and the interviewees were selected randomly during the research. Discussion and ConclusionThe results of the research showed that management factors in industrial companies can influence the promotion of digital marketing capability. The knowledge and expertise of the manager about the up-to-date science of marketing, the manager's belief in customer orientation, good thinking and risk-taking, creativity, management's confidence in the existence of expert human resources, financial and time resources for electronic marketing, management's enthusiastic desire to use existing and up-to-date technologies, use And having successful and related experiences in this field and ensuring the intention and decision of the management to invest in the development of digital marketing, can be considered as very important factors in the field of management. The company's strategies in terms of being customer-oriented, having clear visions for digital marketing and using communication and information technologies are very important for development in this field. Although a company's digital marketing capabilities can be achieved through one of the channels of digital marketing adoption, digital transformation, or innovation ecosystem readiness, digital marketing is about more than technology adoption. It is also about strategies for integrating technology into business processes. Digital transformation is the main driver of increasing digital marketing capabilities. Companies can enhance the role of managerial innovation, organizational readiness and perceived usefulness to improve their innovation ecosystem readiness. In addition, businesses must master changing and re-engineering new business models to accomplish digital transformation. Finally, in addition to implementing digital marketing through websites, social media, mobile marketing, and content marketing, the company should emphasize the importance of digital analytics, digital CRM, digital advertising, and display advertising.Although a company's digital marketing capabilities can be achieved through one of the channels of digital marketing adoption, digital transformation, or innovation ecosystem readiness, digital marketing is about more than technology adoption. It is also about strategies for integrating technology into business processes. Digital transformation is the main driver of increasing digital marketing capabilities. Companies can enhance the role of managerial innovation, organizational readiness and perceived usefulness to improve their innovation ecosystem readiness. In addition, businesses must master changing and re-engineering new business models to accomplish digital transformation. Finally, in addition to implementing digital marketing through websites, social media, mobile marketing, and content marketing, the company should emphasize the importance of digital analytics, digital CRM, digital advertising, and display advertising.Keywords: digital marketing, digital market capability, digital marketing index, industrial companies.
Management approaches in the field of smart
Causal Model of Networking in Science and Technology Parks
Manuchehr Karbasi; Ghanbar Abbaspour Esfeden; Seyedeh Sedigheh Jalalpour; Peyman HajiZadeh
Volume 12, Issue 47 , November 2024, , Pages 185-221
https://doi.org/https://doi.org/10.22054/IMS.2023.74392.2351
Abstract
AbstractNowadays, the development of science and technology parks and improving their performance depends on cooperation with industry and university and communication with the environment and related centers. Hence, it is important to identify cooperation network and networking indicators in science ... Read More AbstractNowadays, the development of science and technology parks and improving their performance depends on cooperation with industry and university and communication with the environment and related centers. Hence, it is important to identify cooperation network and networking indicators in science and technology parks. The purpose of this research is to identify the indicators of networking in science and technology parks. The method of the current research is qualitative and in it three methods of metacomposition, fuzzy Delphi and Dimetal were used. A search was made in Persian and English databases and 10 related studies were identified and analyzed. In order to verify the networking indicators extracted from the theoretical literature, 13 experts and managers of Pardis Technology Park were surveyed and the indicators were confirmed by the experts using the fuzzy Delphi method. In order to draw the causal model of the relationships between the indicators, DEMATEL method was used. The data was analyzed using Excel software. The results showed that networking in science and technology parks has 15 indicators, such as improving the level of products, information, increasing market share, goals and creating value. According to experts, the market share increase index is the first priority and organizational learning is the last. Drawing the causal model of networking showed that indicators such as management, organizational learning, information and knowledge are effective indicators. Indicators such as new product development, market opportunity creation, relationships and opportunity exploitation are also effective indicators in the networking of science and technology parks.IntroductionNowadays, the development of science and technology parks and improving their performance depends on cooperation with industry and universities and communication with the environment and related centers. Hence, it is important to identify cooperation network and networking indicators in science and technology parks. The ultimate mission of technology parks is to be able to coordinate the results obtained from academic research with the needs of the industry and thus fill the gap between the industry and the university, and this will ultimately lead to the commercialization of knowledge. One of the major influential factors in changing the approach of science and technology parks and creating new structures and mechanisms is the birth of new concepts such as networking in the field of business. The purpose of business networking is to increase competition, cooperation and organizational expansion. Considering the importance of these centers and the impact of networking on their performance, it is essential to identify the indicators of networking in science and technology parks. So far, many researchers have investigated the relationship between science and technology parks and other actors in the innovation ecosystem, but few researchers have focused only on the indicators of park networking. In this regard, this research aims to identify the factors influencing the networking of science and technology parks and to evaluate the cause-and-effect relationships between these factors by using the method of a systematic review of previous studies (super combination) and a survey of experts. This question should answer what are the indicators of networking in science and technology parks.Literature ReviewPaztto and Burin's research (2022) indicates that management control systems are effective in inter-organizational cooperation and identification of companies. This system promotes collaborative behaviors among companies related to science and technology parks. Networking and inter-organizational partnership ultimately lead to knowledge and information sharing, increasing flexibility, improving problem-solving strategies and limiting the use of power. The research of Glitova et al. (2022) showed that for cooperation and networking between industry, university and the public sector, attention should be paid to indicators such as knowledge creation by universities, research and development centers and businesses, technology transfer, creation of new businesses, industrial clusters, Business support services, customization, building the necessary infrastructure and equipment, and legal requirements at the local level are required. The research of Khan-Mirzaei et al. (2021) showed that networking and emphasizing cooperation and communication between science and technology parks and growth centers can lead to gaining a competitive advantage for the national economy. Communication with universities and research and development centers, cooperation with companies that have a similar field of work, access to the information flow and access to the information needed in the market, or in other words, the market situation, are among the factors that create a cooperation network between Science and technology, industry, university parks are important. In confirmation of this issue, Cadorin et al. (2019) stated that talent resources and the government play an important role in promoting cooperation between science and technology parks and universities. Managers of science and technology parks should strengthen their relationship with local universities and the student community (as sources of talent) and pay attention to their relations with government representatives to receive the necessary support for the development of the park.MethodologyThe method of the current research is qualitative and in it, three methods of Meta-synthesis, Fuzzy Delphi and DEMATEL were used. A search was conducted in Persian and English databases and 10 related studies were identified and analyzed. To verify the networking indicators extracted from the theoretical literature, 13 experts and managers of Pardis Technology Park were surveyed and the indicators were confirmed by the experts using the Fuzzy Delphi method. To draw the causal model of the relationships between the indicators, DEMATEL method was used. The data was analyzed using Excel software.ResultsIn this research, a set of 62 codes and 15 indicators was obtained by extracting concepts effective on park networking from previous qualitative research. The main indicators include improving the level of products, and information, increasing market share, goals (park goals, socio-economic and environmental goals), creating value, exploiting the opportunities available in the park, optimizing resources, and developing new products, Knowledge includes the knowledge of the market-partners and co-creation of knowledge, the international and commercial performance of the park, creating opportunities through the market, management, the need for resources and operational resources, creating and developing relationships and organizational learning. According to experts, the market share increase index is the priority and organizational learning is the last. The indicators of relationships, value creation, resources, market opportunities, goals, management, knowledge, exploiting opportunities, resource optimization, performance, upgrading products, information and new product development are ranked second to fourteenth respectively. Indicators of management, organizational learning, information, knowledge, goals, resources, and upgrading of products are effective indicators. New product development, creating market opportunities, and relationships, exploiting opportunities, optimizing resources, creating value, and increasing market share and performance are also influential indicators in the networking of science and technology parks.ConclusionThe review of the subject literature showed that paying attention to the indicators obtained in this research can lead to networking in science and technology parks. For example, the implementation of the indicators of improving the level of products, increasing market share, park goals, creating value, exploiting opportunities, knowledge, creating market opportunities, relations between actors, organizational learning and technical and human resources in Nihu Technology Park and Nankang Software Park in Taipei City. Networked. Researchers have pointed out various actors in the cooperation network of science and technology parks. The review of the texts in the meta-synthesis stage showed that each of the sources identified one to three actors based on their purpose. What was tried to be considered in this research was the gathering and consensus of all actors and their placement in the form of networking indicators such as increasing market share, resources and management. Among the new findings of this research, we can mention the type of causal relationships that are established between the indicators of networking in science and technology parks. Most researchers have not paid attention to these relationships and have focused more on the relationship between the park and variables such as innovation, performance, development, etc. However, the identification of networking behavior and the type of communication between the elements of this ecosystem can lead to the improvement of performance and optimization of activities and actions, and in this research, we tried to consider more and more comprehensive indicators in the cooperation network. be placed Finally, the purpose of the formation and development of science and technology parks is to increase the capacity of innovation and the growth of the knowledge-based economy through knowledge management (creation, sharing and access to knowledge and technology) among the members of the cooperation network of parks and to develop and commercialize the product, it becomes possible by them.Keywords: Networking Indicators, Science and Technology Parks, Meta-synthesis, Fuzzy Delphi, DEMATEL.
Management approaches in the field of smart
Dimensions of Alignment between Digital Capability and Innovation Strategy in Petrochemical Industry
Soroush Ghazinoori; Sohrab Aghazade Masroor; Mohamad Naghizadeh; Mojtaba Hajian Heidary
Volume 12, Issue 47 , November 2024, , Pages 223-269
Abstract
AbstractThe reduction of profit margins and the disappearance of past competitive advantages have pushed companies in Petrochemical industries toward innovation by utilizing digital capabilities. This necessitates the establishment of a strategic alignment between digital capabilities and innovation ... Read More AbstractThe reduction of profit margins and the disappearance of past competitive advantages have pushed companies in Petrochemical industries toward innovation by utilizing digital capabilities. This necessitates the establishment of a strategic alignment between digital capabilities and innovation strategies and decisions. This research aims to examine the dimensions of alignment between digital capability variables and innovation strategies and create a framework for its assessment. Initially, by reviewing the background of studies, a framework for assessing each of the variables was developed. Subsequently, a questionnaire for confirmatory structural analysis of the identified concepts and dimensions was formulated. This questionnaire was completed by 99 experts in innovation management, digital technologies in the industry, and academia. As a result, it was determined that to assess the level of alignment between digital capabilities and innovation strategies, creating digital value and digital innovation processes for innovation strategies, digital innovation infrastructure and digital innovation capabilities for digital capabilities, and complementarity, balance, and coordination for alignment were considered as assessment dimensions of the variables.IntroductionToday, the advantages of the past in the petrochemical industry are diminishing, and the competitive landscape is changing. It can be noted that one of the main challenges encompassing the petrochemical industry today is enhancing competitiveness and reducing operational costs, which require innovation in the use of new technologies (O. V. Zhdaneev, V. Korenev, and A. S. Lyadov, 2020).Most organizations in this industry use structures and organizational procedures that are not well-suited for utilizing innovative capabilities, including digital capabilities (Alexey Shinkevich, Naira Barsegyan, Vladimir Petrov, and Tatyana Klimenko, 2021). On the other hand, organizations are striving to create complementarity between their different capabilities to strengthen potential innovation capacity (Rogier van de Wetering, Patrick Mikalef, 2017).Therefore, one of the crucial questions for companies in the petrochemical industry can be how to assess the alignment between digital capabilities and innovation strategy. Consequently, the goal of this research is to identify appropriate dimensions and components for assessing the alignment of digital capabilities and innovation strategy in the petrochemical industry. To achieve this, the relevant concepts related to the main variables are identified and examined, and based on this, the dimensions and components under these variables will be confirmed through a validation process to create an assessment tool. Literature ReviewIn the examination of digital capabilities in the petrochemical industry, it can be noted that new processes and patterns are emerging due to adaptation to new technologies, (Amankwah-Amoah, J., Khan, Z., Wood, G., & Knight, G., 2021). Studies conducted on dynamic capabilities (Loureiro, R., Ferreira, J. J., & Simoes, J., 2021) claim that the proper combination of resources and capabilities allows organizations to gain a competitive advantage and improve their performance. (Torres, R., Sidorova, A., & Jones, M. C, 2018). From automating data movement to leveraging processes, all of these have a significant impact on creating added value and generating income (Oztemel, 2018). Based on this, to assess the digital capability variable, one can consider the effective use of digital innovation resources, the management of digital innovation networks, the capacity for absorbing and accepting digital innovation, predicting trends and technologies, managing digital innovation risks, access, transparency, and information security, advanced analysis, and artificial intelligence, as primary components.Pisano introduces three key questions as the pillars of innovation strategy: The first question is how the organization's innovation creates value for potential customers. The second is how the company gains a share of the value it creates due to its innovation. The third question returns to the type of innovations that enable the company to create and gain value, and what resources each innovation requires (Pisano, 2015). The role and position of digital technologies in addressing these key questions seem crucial. Since digital technologies have significantly influenced technical and social changes for individuals and societies, including organizations, they have caused products, services, processes, and business models to have a more substantial impact (Ciriello RF, Richter A, Schwabe G, 2018).The concept of alignment implies the existing collaboration between different organizational units based on environmental needs. Organizations with greater alignment perform better in various performance standards, and an aligned organization has internalized directions (Labovitz, G. H., & Rosansky, V., 1997). Growth and profitability are ultimately the results of alignment between employees, customers, strategies, and processes (Labovitz, G. H., & Rosansky, V., 1997). It is necessary for organizations to prepare for changes by creating structures and processes that can easily be adjusted and realigned (Galbraith, 2002). Alignment should exist at all levels of the organization (individuals, projects, systems, and the company). In recent studies, digital platforms and the ecosystem around the company have been added to the scope (Coltman, T., P. Tallon, R. Sharma, and M. Queiroz, 2015). MethodologyThis research was conducted with an applied approach using quantitative methods and confirmatory factor analysis. The main question in this study relates to the components and dimensions of assessing the alignment between two variables: digital capability and innovation strategy. Therefore, it was necessary to identify and categorize concepts, indicators, and main dimensions of each of the three variables (alignment, digital capability, and innovation strategy) based on previous studies, and this formed the basis for analysis in the confirmatory factor analysis. Based on the identified concepts and indicators for the variables, a questionnaire was developed. A total of 120 individuals were identified. A purposive sampling method was used to collect their opinions, and questionnaires were distributed. In the end, 110 responses were received, of which 99 were usable. The reliability of the questionnaire was calculated for each of the variables, and all of them had values above 0.7 (as reported in the findings). Then, using the smart PLS software and the confirmatory method, the sub-structures of each of the variables were modeled. ConclusionBased on a review of the literature and relevant concepts and topics related to the research question, a comprehensive understanding was developed. Previous alignment models in organizations have mostly focused on information technology and high-level business strategies.Regarding the assessment of the innovation strategy variable, it's important to note that, given the decreasing profit margins and the increasing operational costs of companies, a shift toward value-oriented strategies (economic, social, etc.) is becoming more prominent. The realization of value can be achieved through customizing products, improving industrial processes, automating decision-making, and increasing the speed of decision-making in innovation. On the other hand, digital technology has brought fundamental changes to innovation management processes, requiring companies to be attentive to new tools and approaches when formulating innovation strategies. Artificial intelligence aids in identifying new opportunities, while big data analysis helps organizations make decisions based on their past records and experiences.Furthermore, as companies in the petrochemical industry need to create digital capabilities for success in the field of digital innovation, some of these capabilities will be focused on changing historical business routines. In this context, businesses strive to continuously evaluate the returns on their digital projects and optimize resource allocation. Additionally, the enhancement of digital literacy, thinking, and human capital competencies, often referred to as digital talent, is essential.In the context of digital capability and innovation strategy, there are three main dimensions. The first is coordination. If the path to digital innovation is pursued in a fragmented and uncoordinated manner within the organization, it is unlikely to enhance organizational performance and alignment. Therefore, organizational goals and needs in the digital innovation and digital capability domains should be coordinated, and the organization should be able to establish new processes to create dynamism in the problem-solution and digital innovation processes. Moreover, stronger attention and balancing are required, as unbalanced attention to digital capability or innovation strategy can disrupt alignment and equilibrium between organizational capabilities. This indicates the importance of flexibility and transparency regarding resource allocation. The illustration of model is showed in figure 1.Figure 1. Dimensions of alignment of digital capability and innovation strategy Keywords: Digital Capabilities, Innovation Strategy, Alignment, Digital Innovation. v
Management approaches in the field of smart
Immersion in VR News Pieces Focusing on Cognitive Factors Based on Grounded Theory
Atieh Moghaddam Monfared; Abbas Toloie Eshlaghy; Reza Ehtesham Rasi
Volume 12, Issue 47 , November 2024, , Pages 367-411
Abstract
AbstractConsidering that the users are the main focus of immersive journalism, any study in this field without understanding and recognizing them is incomplete. The quality of the VR news experience depends on many parameters, the most important of which are related to the cognitive and behavioral science ... Read More AbstractConsidering that the users are the main focus of immersive journalism, any study in this field without understanding and recognizing them is incomplete. The quality of the VR news experience depends on many parameters, the most important of which are related to the cognitive and behavioral science of the users, apart from the technological factors that are prerequisites for making VR. In this regard, through interviews with experts in journalism and cognitive sciences, this research identified the categories that influence the depth of user’s immersion based on the Grounded Theory methodology and finally presented a conceptual model. The phenomenon of the model is “user involvement”. This category is affected by contextual factors such as "user’s demographic characteristics" and "type of news", as well as the intervening factors of "trauma" and "preventing factors of using virtual reality". In addition, the three categories of "cognition", "narrative" and "crafting pieces" provided the causal conditions that are the basis for the immersion in the news narrative. Finally, "focusing on user’s cognitive factors" in creating VR pieces is the interaction strategy that brought two consequences of "increasing immersion" and "changing norms and behaviors". IntroductionIn an era characterized by rapid technological advancement and digital transformation, journalism stands at the precipice of a profound evolution. The fusion of virtual reality (VR) with journalism has emerged as a pioneering innovation, propelling the field into a new dimension – the metaverse. This dynamic convergence is reshaping how news is both reported and consumed, presenting a paradigm shift that warrants a closer examination. Traditional journalism has long been the cornerstone of information dissemination, serving as society’s watchdog and providing a lens through which we view the world. However, with the advent of VR and its integration into news reporting, we find ourselves on the cusp of a revolution that promises to redefine the very essence of journalism. The immersive nature of VR enables audiences to step inside the stories they consume, transcending the limitations of two-dimensional screens and forging a connection that goes beyond words and images. At the heart of this transformation is the metaverse –a digital universe where virtual and real-world experiences coalesce seamlessly. Within this expansive virtual realm, the potential for immersive, interactive journalism knows no bounds (Uskali & Sirkkunen, 2020, P. 6).In an ever-evolving landscape of journalism, Virtual Reality (VR) journalism stands as a transformative force, not merely conveying information to audiences, but immersing them in the stories with a dynamic and active role. One of the intriguing aspects of this evolution is the dynamic role played by the audience, who, in the realm of Virtual Reality and the metaverse, are no longer passive news consumers but active participants in the storytelling process. Traditionally, audiences in journalism assumed the role of static observers and receivers of news (Shin, 2018, P. 65). However, with the emergence of Virtual Reality and its integration with the metaverse, audiences are no longer mere spectators; they become active participants deeply embedded in situations and places beyond their physical reality. This transcends the conventional viewing of news reports and empowers audiences to actively contribute to news production (McMahan, 2016, P. 68).Secondly, within the metaverse, audiences interact with characters and other audience members, express their opinions, and directly engage in news creation. These active interactions provide a powerful tool for fostering increased engagement and a deeper understanding of news topics (Shin, 2016, P. 141). In this article, we delve into the exploration of the dynamic role of audiences in Virtual Reality journalism and examine the impacts of this role on the reporting process and media communications. From shifting public opinions to experiencing active audience engagement in the metaverse, we delve deep into these transformations, highlighting the formation of a two-way and dynamic relationship between media outlets and their audiences.Research QuestionHow can we enhance audience immersion in virtual reality news content by strategically addressing their perceptual systems and cognitive factors? Literature ReviewVirtual reality (VR) in storytelling, exemplified by De la Peña et al.'s (2010) "Immersive Journalism," demonstrates its popularity. The study explores user participation in simulated news events, highlighting heightened presence through avatars and virtual scenario reconstruction. It advocates for a fundamental shift in journalism perspectives, aligning with embodied cognition theory. Immersive journalism aims to provide empathetic, simulated experiences, potentially influencing real-world actions. VR's impact on perceptual experiences is acknowledged, with powerful illusions forming the foundation of these experiences.It discusses the unique potential of virtual reality (VR) in journalism, emphasizing its ability for deep behavioral influence. Research, like that of Yee & Bailenson (2007), indicates that avatars in VR can alter user behavior. Recent studies focus on VR’s positive role in creating empathy. For example, Ma (2020) suggests immersive storytelling enhances social engagement. Breves (2021) explores how spatial presence in VR persuasively impacts cognitive processes. The text touches on the emergence of the metaverse and highlights the need for further research in the evolving field of VR journalism. MethodologyIn this article, the research process follows an inductive approach due to the absence of specific laws for identifying cognitive factors influencing the quality of user immersion in virtual reality (VR) experiences. The study aims to explore these cognitive factors affecting immersion by engaging targeted experts in journalism, VR, cognitive sciences, and VR content creators. Data collection involves document analysis and in-depth interviews using Skype. The data is analyzed using the Strauss and Corbin method with a focus on cognitive factors impacting user immersion in VR storytelling.The research participants were selected purposefully, and key themes in the interviews include defining cognition, main stimuli for cognitive factors, factors inducing immersion, cognitive factors affecting user engagement, and interaction with simulated environments. The research process spans over four years, and to enhance credibility, the researcher consulted participants and another expert coded four interviews for inter-coder reliability, yielding a reliability coefficient of 73.0%. The study’s reliability is confirmed as the coefficient is above 70%. ResultsIn the Grounded theory approach, interview texts underwent open coding, extracting initial codes that were then compared to identify related phenomena. Concepts like “attention” emerged, involving cognitive focus, intentional neglect of irrelevant details, and concentrating energy on essential information to avoid distractions and complete specific tasks.All concepts were extracted through this process. The identification of concepts and categories continued until the researcher did not discover any new concepts, essentially reaching saturation. In total, 100 codes, 29 concepts, and 14 categories were identified. Figure 1. Conceptual Model of cognitive factors affecting audience immersionCasual Conditions CognitionNarrativeCrafting the pieceCentral Phenomenon User Engagement and Immersive PerceptionStrategies Focusing on the user's cognitive factors in creating virtual reality news piecesOutcomes Increasing perceived immersionChanging norms and beliefs Intervening Conditions Demographic User FeaturesNature of News Contextual Conditions TraumaInhibiting Factors of Virtual Reality Usage Discussion5.1. Central phenomenonThis article focuses on “User Engagement and Immersive Perception,” highlighting the significance of “Interaction” as a cornerstone for user immersion. Seamless alignment of virtual events with user expectations fosters a profound sense of immersion. Quotes emphasize the impact of substituting real-world stimuli, physically adjusting viewpoints, and empowering users to explore beyond scripted narratives. The provided quotes shed light on identified codes:“The substitution of real-world stimuli with virtual counterparts elicits a profound sense of complete immersion.”“Empowering users to explore the environment beyond scripted narratives results in an unmistakable enhancement of immersion.”The concept of the “First-Person Experience” plays a crucial role in immersive journalism. The objective is to immerse users in a first-person perspective during events, allowing them to undergo news stories firsthand. Quotes highlight the experiential context of stepping into a story, encountering it through a first-person lens, and the critical role of three-dimensional graphics in creating an interactive first-person perspective. The immersive experience transforms into knowledge unattainable through traditional journalism, showcasing the potency of both conventional and immersive storytelling. The following quotes further underscore this concept:“In an experiential context, individuals step into a story, encountering it through a first-person lens, moving within and interacting realistically.” “These theoretical discussions share striking similarities, emphasizing the critical role of three-dimensional graphics in crafting the illusion of a fully interactive first-person perspective, transcending mere camera positions.”5.2. Casual conditionsFocusing on enhancing immersive quality, three pillars shape the experience: “Cognition”, “narrative” and “ crafting the piece”.Cognition:Schema: Users’ knowledge structures impact immersion. If experiences don’t align with existing schemas or create new ones, cognitive dissonance disrupts harmony.Orientatin: Recognizing individuals and self-awareness are vital for enjoyment and immersion.Past Experience: Similar past experiences significantly influence users’ perception and immersive depth.Narrative:Realism: Theplace illusion and plausibility in virtual environments are crucial for perceptual stability and creating a tangible experience.Interactive Scenario: Active user participation enhances the illusion of presence, blurring the line between observer and participant.Crafting the Piece:Audio Quality: Sound is the backbone of storytelling, playing a crucial role in immersive journalism.Visual Quality: Initial immersion relies on visual display, creating a sensation unique to immersive journalism.These elements converge to craft an engaging and immersive virtual reality journalism experience.5.3. Contextual conditionsThe categories of “Demographic User Features” and the “Nature of News” chosen for virtual reality creation acts as the linchpin determining the augmentation or hindrance of immersive quality. These elements, encompassing age, gender, education, and social standing, prove pivotal. Emotional variances, persuasiveness, age, and the overall well-being shaping users’ lives are initial influencers, possibly steering the audience’s propensity for virtual reality engagement and, on a broader scale, molding their conduct and viewpoint. Noteworthy quotes include:“Attitudes cultivated through profound cognitive engagement or transformative shifts compared to those grounded in superficial cognitive processes cultivate more enduring and favorable behaviors.”“The behavior and mindset of an individual hinge on their literacy and knowledge levels. Consequently, this can significantly impact the user’s ability to connect with the narrative.”Conversely, the selection of news types for virtual reality production holds significance. Not all news is inherently suitable for virtual reality journalism, with only specific themes demonstrating aptness for this platform. If the chosen news type is incongruous, it risks diminishing the level of immersive experience. Conversely, judicious selection of news types can yield superior outcomes in captivating the audience with the subject matter. Exemplary quotes comprise:“While immersed in crime journalism, theft, and media coverage of racism, gender discrimination, and the like, we navigate these realms. Yet, I contend that only select topics within this spectrum prove beneficial and practical for virtual reality journalism.”“News conducive to immersive journalism are those that enrich the user’s comprehension of the event, actively involving them in the unfolding narrative.”5.4. Intervening conditionsTwo significant factors, ‘Trauma’ related to users and ‘Inhibiting Factors of Virtual Reality Usage’ tied to technology, exert substantial negative influence, undermining the core subject’s quality. The combination of ‘Disorder’ and ‘Claustrophobia’ shapes the ‘Trauma’ issue, with virtual reality equipment intensifying anxiety and inducing discomfort, impacting the immersive experience. The narrative space acts as an amplifier, heightening anxiety, particularly for users with real-world trauma, posing risks for producers. Additionally, barriers like high costs and limited accessibility hinder widespread virtual reality adoption, creating a challenging landscape. Noteworthy quotes emphasize caution in deploying tools for trauma survivors and address potential medical or psychological consequences, highlighting the obstacles in virtual reality’s emerging technology adoption.5.5. StrategiesThe primary goal of immersive journalism is to foster empathy by enabling the audience to connect with narrated stories, placing themselves in similar situations. Immersion is achieved when the news storyline aligns with the audience’s cognitive factors, enhancing their inclination and motivation. Focusing on cognitive elements plays a significant role in immersing the audience in the virtual narrative.5.6. Outcomes The presented strategy of “increasing perceived immersion” among audiences leads to broader outcomes, such as “changing norms and beliefs.” Immersion involves concepts like “suspension of disbelief,” “acceptance,” and “transference,” emphasizing user interaction with news narratives and a more realistic understanding of the virtual world. Norman Holland suggests that when individuals engage with a narrative, their brains immerse in perception, delaying critical evaluation until disengagement. This immersion is crucial for empathy and unbiased judgment. Additionally, focusing on cognitive factors can intensify audience immersion.On the other hand, the shift in norms and beliefs is the second outcome of immersive journalism’s cognitive focus, encompassing “catharsis” and “creating new knowledge.” The virtual space enables individuals to explore events without real-world consequences, aiding emotional release and achieving catharsis. Moreover, immersive news, addressing issues like climate change, can evoke empathy and drive societal change. The impact extends to individual, social, and global levels, showcasing the potential of this industry to influence behavior and reshape global societal norms. Conclusionimmersive journalism, utilizing virtual reality (VR), transforms storytelling by immersing users in news events. Dolapena’s 2010 study emphasizes a shift in journalism perspectives, focusing on cognitive factors like perception and psychology. The proposed model, derived from expert interviews, identifies six key elements, emphasizing user engagement, environmental interaction, and immersion perception. Strategic attention to cognitive factors enhances user involvement, increasing empathy and immersion. The primary outcome is heightened user empathy, while the secondary outcome positively impacts global norms and beliefs. Challenges in VR storytelling revolve around the dynamic relationship between immersion and user cognition, emphasizing the pivotal role of individual characteristics.Keywords: Virtual Reality, Immersion, Narrative, Immersive Journalism, Cognition.
Management approaches in the field of smart
The framework of factors affecting the maturity of business intelligence
Javad Nazarian-Jashnabadi; MohammadHossein Ronaghi; moslem alimohammadlu; Abolghasem Ebrahimi
Volume 12, Issue 46 , November 2023, , Pages 1-39
Abstract
AbstractThe maturity of business intelligence is a result of the evolution and advancement of technology and management approaches that help to provide accurate information, predictive analyzes and improve decisions in organizations using advanced technologies such as artificial intelligence and data ... Read More AbstractThe maturity of business intelligence is a result of the evolution and advancement of technology and management approaches that help to provide accurate information, predictive analyzes and improve decisions in organizations using advanced technologies such as artificial intelligence and data analysis. Despite technological maturity that improves the efficiency and performance of organizations over time, business intelligence is far from becoming a mainstream trend in organizations. According to numerous researches in the field of business intelligence, the aim of this research was to present the framework of factors affecting the maturity of business intelligence using a meta-composite approach. In order to reach a comprehensive framework that includes all the maturity factors of business intelligence, 221 scientific studies were reviewed. Relevant codes were extracted using content analysis in metacomposite method. The categories were leveled using the comprehensive interpretive structural modeling method and the most influential ones were determined. The findings show that a total of 93 codes were extracted and divided into 6 categories. These categories include organization and management factors, environment, technology infrastructure, human resources - knowledge, data management and data analysis. The categories of technology infrastructure, data management and data analysis were placed at level three and have the greatest impact on the maturity of business intelligence.IntroductionIn today's world, digital transformation has become one of the prominent and fundamental phenomena in the field of technology and business. This transformation has placed organizations in a process of change and evolution, significantly altering their approaches and operational methods (Hilbert, 2022). One of the concepts that has emerged as a result of these developments is business intelligence (Ragazou et al., 2023). The primary objective of business intelligence is to convert scattered, raw, and unstructured data into usable and valuable information. By integrating internal and external data and utilizing advanced analytics methods such as data mining and artificial intelligence, business intelligence facilitates more effective and precise decision-making for organizations (Sinarasri & Chariri, 2023). However, given the multifaceted nature of business intelligence, companies must operate more intelligently and strive for maturity by identifying critical factors in the successful implementation of business intelligence. This plays a crucial role in reducing the likelihood of business failures. In general, the shortage of appropriate knowledge resources for companies operating in this field, coupled with a lack of proper understanding among managers, has resulted in minimalist views on business intelligence, limiting its scope to basic services and reports.Given the extensive use of business intelligence, addressing the topic of business intelligence and its influencing factors is crucial. On the other hand, the existence of numerous domestic and international research studies in various aspects of business intelligence necessitates the creation of a comprehensive and coherent framework to connect these research efforts. Considering the current concern, the main question of this research is to provide a comprehensive and coherent framework of the factors affecting business intelligence maturity. The results of this research play a role in advancing theoretical discussions on the maturity of business intelligence and provide suitable indicators for companies seeking to optimize their use of business intelligence. The use of quantitative approaches alongside systematic review can add significant value; therefore, the "Total Interpretive Structural Modeling" (TISM) approach is used to determine the levels of concepts. The research questions are as follows:(1) What are the influential factors on business intelligence maturity?(2) What is the classification of factors affecting the maturity of business intelligence?(3) What are the most important concepts influencing business intelligence maturity?(4) Among researchers, which factors influencing business intelligence maturity are most commonly used?Literature ReviewThe concept of business intelligence maturity refers to an organizational growth stage in which organizations and businesses harness intelligent technologies and leverage their most powerful features. This stage signifies that achieving maturity in business intelligence is considered a strategic goal for organizations in the digital age. Business intelligence maturity offers several advantages, as highlighted in various studies: improved decision-making (Aparicio et al., 2023), enhanced customer satisfaction (Ramos, 2022), increased flexibility (Aparicio et al., 2023), and reduced costs and time required for work (Niazi, 2019).The research conducted in the field of business intelligence across various domains has highlighted several advantages. These include data analytics and dashboards (Sinarasri & Chariri, 2023), security and privacy (Halper & Stodder, 2014), as well as forecasting and advanced analytics (Darwiesh et al., 2022). However, it's important to note that the topics and benefits mentioned here represent only a fraction of the research conducted in the field of business intelligence maturity. Most of these studies are domain-specific, focusing on industries such as banking (Rezaei et al., 2017; Monshy, 2021; Najmi et al., 2010), insurance, small businesses (Ragazou et al., 2023; Sinarasri & Chariri, 2023), e-commerce (Ramos, 2022), the manufacturing industry (Ahmad et al., 2020), and supply chain management (Arunachalam et al., 2018).Some of these research studies have adopted a quantitative approach (Rangriz and Afshari, 2015). This type of research often focuses on the maturity of business intelligence using structural equations (Monshy, 2021; Poti et al., 2017; Khrisat et al., 2023; Golestanizadeh et al., 2023; Mbima & Tetteh, 2023) and examines the relationships between various latent variables and the maturity of business intelligence. However, these studies have not employed a systematic review approach to comprehensively explore the underlying concepts. Business intelligence encompasses diverse dimensions and extends beyond a few latent variables.Another part of the researches has dealt with the modeling of business intelligence with a qualitative method; However, their investigation has reached limited variables and does not include all aspects of business intelligence (Fallah and Kazemi, 2019; Adineh et al., 2022). On the other hand, it should be clear what level of the organization the model is for (readiness, growth, maturity and decline). Because every organization with the conditions it lives in needs a certain level of business intelligence to progress and it is not possible to prescribe the advanced use of business intelligence to a newly established organization, which has not been observed in various researches (Ahmadizad et al., 2015; Srivastava & Venkataraman, 2022).MethodologyThis study is objective in nature and employs a qualitative approach. Its aim is to identify the factors that affect the maturity of business intelligence. To achieve this, a meta-synthesis approach is used to examine existing articles in the field and extract the relevant factors. The statistical population for this research includes credible and relevant articles published until 2023. Meta-synthesis entails reviewing prior studies and reinterpreting concepts by integrating previous results. In this research, the seven-stage Sandelowski & Barroso (2003) method is employed to conduct the meta-synthesis, as it is widely recognized as the most commonly used method for meta-synthesis in recent university research studies. The seventh and final step of the meta-synthesis method involves presenting the findings. In this phase, the TISM is utilized to categorize the meta-synthesis outputs into two categories: "impactful" or "influenced." Eventually, a comprehensive framework for understanding the factors that influence the maturity of business intelligence is established by employing TISM.ResultsThe aim of this research was to provide a framework for understanding the factors that influence business intelligence maturity using a meta-synthesis approach. To develop a comprehensive framework encompassing all aspects of business intelligence maturity, 221 scientific studies were reviewed. Relevant codes were extracted through content analysis using the meta-synthesis method. The categories were stratified using the Total Interpretive Structural Modeling method, and the most influential ones were determined. The findings indicate that a total of 93 codes were extracted, which were categorized into 6 groups. These categories encompass organizational and managerial factors, the environment, technological infrastructure, Human resources - knowledge, data management, and data analysis. The categories of technological infrastructure, data management, and data analysis were placed at level three and exhibited the greatest impact on business intelligence maturity.Discussion and ConclusionThis research investigates the factors influencing the maturity of business intelligence with the aim of establishing a comprehensive framework. The results obtained through the meta-synthesis method reveal six categories crucial to business intelligence maturity. These categories are categorized using the TISM method. Technology infrastructure, data management, and data analysis are placed at the third level and exhibit the most significant impact on other levels. Human resources - knowledge and organization and management factors were placed at the second level. This level is influenced by the third level and, in turn, influences the first level. The environment is categorized at the first level.Among the factors affecting business intelligence maturity, the power of analysis, decision-making quality, and quick and easy access to data exhibit the highest recurrence rate in previous research. The ability to analyze data accurately and with a focus on data-centricity extracts comprehensive insights from the data (Lilly & Renjberfred, 2018), enabling precise predictions of trends, patterns, and behaviors both within and outside the organization (Hernández-Julio et al., 2021). The power of analysis empowers organizations to make strategic decisions based on accurate and reliable information and data (Batra, 2022). Most researchers assert that the quality of decision-making is one of the key advantages of implementing business intelligence in organizations (Fu et al., 2022). Regarding the aspect of fast and easy data access, scholars argue that it is a prerequisite for achieving business intelligence maturity (Sinarasri & Chariri, 2023).
Management approaches in the field of smart
Identifying the Research Trends and Subfields of the social manufacturing paradigm
vahid sharifi; Gholamreza hashemzadeh Khorasgani; Seyed Alireza Derakhshan; Ashraf Shahmansouri; Abotorab Alirezaee
Volume 12, Issue 46 , November 2023, , Pages 81-120
Abstract
AbstractIn recent years, studies on the paradigm of social Manufacturing and its applications have been developed as a new production paradigm and have led to the production of diverse and scattered knowledge in this field. Knowing the sub-fields, new topics and the research process of the social production ... Read More AbstractIn recent years, studies on the paradigm of social Manufacturing and its applications have been developed as a new production paradigm and have led to the production of diverse and scattered knowledge in this field. Knowing the sub-fields, new topics and the research process of the social production paradigm can be of great help to researchers in this field. The current research has been carried out with the aim of identifying and categorizing research in the field of social Manufacturing, recognizing sub-fields and achieving a coherent view of its research process.This research has investigated the research field of social Manufacturing using bibliometric analysis. The data of this research was collected from 200 articles of the Scopus database and an analysis of the co-occurrence analysis of key words and bibliographic pairs was performed on them, and in this way the sub-fields and the research process of this field were identified.Based on the findings of this study, the research in the field of social Manufacturing has been categorized into 5 clusters and it has also been determined that in recent years, topics such as cloud computing, smart production, blockchain, Internet of Things, social physical cyber systems, innovation systems, society 5.0 and Digital twins have received more attention in research in this field. This research provides a framework of concepts and main topics of interest in the research field of social production, which provides a comprehensive perspective for researchers in this field that can help in choosing their research path.1.IntroductionThe paradigm of social manufacturing can provide suitable solutions for problems of traditional manufacturing such as (non-demand production, high cost production, non-creative production, etc.), However, considering the freshness of this paradigm and the partial studies around it, currently, there is no clear understanding of it in the manufacturing. the present research has been done for manufacturers, organizations and manufacturing companies in case of confronting the market changes so that they can take safe steps to face environmental changes. The main problem is the lack of recognizing theparameters that should be taken into account in order to use all the possible capabilities of social manufacturing. However, no specific research has been done in this field so far. In fact, this research seeks out to answer the following questions:What are the main areas of social manufacturing?What are new topics and emerging trends associated with research in the field of social manufacturing? Literature Reviewever since the last ten years now, researchers have given attention to the concept of social manufacturing. Many researchers have studied the technology and applications of social manufacturing (Pingyu Jiang & Ding, 2012). Similarly, an organizational communication network model has been developed by some based on the social manufacturing. (P. Jiang et al., 2015) in a research, Hamalainen and his colleagues have proposed the basic characteristics of social manufacturing as well (Hamalainen, 2018) also Shang and his colleagues, have designed a social manufacturing model for producing shoes and clothes. (Xiong, Helo, 2022).Correspondingly, Xiang and colleagues (2022) in an investigation have explored the key factors of the transition from mass production to social manufacturing. The outcome of this research is that expanding the concept of Internet of Things, deploying multiple sensors and the usage of data mining with the purpose of managing production data with a large volume, variety and speed in the physical system, will lead to the continuous growth of the industry of manufacturing.3.Methodologythe present research seeks out to identify the playing field of social manufacturing, its subfields and research trends by examining 200 articles from the Scopus database using bibliometric analysis. "VOS Viewer" software is used for bibliometric as well. the software has been using for providing bibliometric maps, visualization of the coinciding of keywords, citation, analysis of bibliographic pairs, co-citation map and other things, through distance-based maps. In order to analyze the new topics, two different parts have been used. the first part is the usage of a cover map and the second part is the analysis of the average lifetime of words. Building a cover map is one of the methods to identify the changes in scientific fields and examine their developments. Cover maps are things that are the outcome of combining two maps with each other. For instance, we use these maps when we need to display the role of time on a science map (Mousavi and colleagues, 1400, quoted by Rafols et al., 2010).4.ResultsBased on the result of the clustering of the keywords co-occurrence map (Figure 5), the five identified research clusters are as follow:Cluster 1: This cluster deals with social manufacturing and correlated technologies such as 3D printing, 3D modeling, social sensors, social cyber-physical systems, RFID and social computing. This indicates that research efforts are dedicated to explaine the infrastructure technologies of social manufacturing.Considering the average publication year of 7/2016 for keywords in the cluster, these topics are more developed in social manufacturing than the others.Cluster 2: The researches of the second cluster are associated with industry 4 and various new production methods with social manufacturing.Industry 4 is a concept which attempts industries become smart, dynamic and flexible. This industry seeks to overcome new challenges such as global competition, market fluctuations, development of customization, establishment of innovation and product life cycle management (Ostadi and Nasiri, 1401). Cloud manufacturing, intelligent manufacturing, digital manufacturing, crowdsourcing, outsourcing, and mass customization. As revealed in figure 5, the most frequent words of this cluster are: industry 4, crowdsourcing and cloud manufacturing, which include a significant number of associated researches with social manufacturing. The age of the keywords in this cluster illustrates the consideration to industry 4 in social manufacturing initiated roughly from 2014 and then the cluster has been inclined towards crowdsourcing and mass customization with an average of 2016.5.Cluster 3: As illustrated in figure 5, a significant number of researches connected with social manufacturing have been carried out in applying new technologies. the most frequent keywords of this cluster include: Internet of Things, cloud computing, deep learning, big data, blockchain, 5thG internet and digital twin.The average year of publishing the keywords of the field is 7/2018, which indicates the researches, especially Blockchain and Internet of Things, can be considered as a research field which has been recently examined.Cluster 4: Researches of this cluster refers to the effect of consumer demand and participation. keywords such as manufacturing platforms, personalized production, personalized products, social media, and the role of the consumer are among the keywords of this cluster.Cluster5: Social sustainability is one of the notions connected with sustainable development, which was counted in the developing programs of different countries from the 1960s onwards. nevertheless, due to the lack of consensus on its components and its place among other apparatuses, it has been treated in many different ways practically.Social sustainability refers to the capability of a society to preserve the necessary means of producing wealth, prosperity and social contribution in order to expand integration and cohesion. As a concept, it also seeks to preserve the social and cultural components of an integrated society with the environmental and economic dimensions. the role of social sustainability is precisely significant in sustainable development (Vaezzadeh and others, 2015). ConclusionThe present study identifies five research clusters as follow:Social manufacturing and its infrastructural technologiesResearches correlated with the connection between new methods of production and industry 4 with social manufacturingResearches related to new technologies such as blockchain and Internet of Things with social manufacturingResearch connected to the concepts of consumer participation in manufacturing (the role of supply and demand) such as mass customization and crowdsourcingStudies in social sustainability, sustainable development, collaborative economy and the fifth generation of societyMoreover, by means of a cover map the present research has achieved the newest topics in social manufacturing such as cloud computing, intelligent production, social computing, blockchain, Internet of Things, cyber- physical social systems, innovative systems, digital twins, the fifth generation of society, and machine learning by using the analysis of the average life of words.discoveries of the present research will help manufacturers and manufacturing companies, to know the emerging areas and components of social manufacturing, and equipped in case of changes and use all the capabilities of social manufacturing. what's more, the analysis of keywords identifies the intellectual bases of discourse in social manufacturing. Furthermore, the findings of bibliographic pair analysis identify influential articles in this field as well, so that researchers can benefit from them as the theoretical foundations of this field.
Management approaches in the field of smart
Identifying the qualitative components of gamification in the working environment of knowledge-based companies
Mohammad Bashokouh; golsum akbari arbatan; mehdi ebrahimzade
Volume 12, Issue 46 , November 2023, , Pages 121-152
Abstract
Although digitization brings important possibilities, implementing its technologies in practice can be challenging. One of the current major developments in this field is to discover the potential of gamification for the empowerment of knowledge-based companies. Based on this, the current research was ... Read More Although digitization brings important possibilities, implementing its technologies in practice can be challenging. One of the current major developments in this field is to discover the potential of gamification for the empowerment of knowledge-based companies. Based on this, the current research was conducted with the aim of identifying the qualitative components of gamification implementation in the working environment of knowledge-based companies. This research has a qualitative approach, through in-depth semi-structured interviews, it has compiled and validated the conceptual framework with thematic analysis method. The statistical population includes experts and experts of knowledge-based companies, among whom 12 people were selected by purposeful sampling and participated in this study. The number of samples follows the rule of saturation. The findings of the research show that concepts were identified in the form of 4 main themes, including the acceptance process with 2 organizing themes, promotion strategies with 4 organizing themes, development and design strategies with 4 organizing themes, evaluation and implementation platforms with 3 organizing themes Gamification actually provides various possibilities to increase the motivation of employees for knowledge-based activities. But to reveal its potential, it needs a suitable environment. Introduction In the last decade, a growing trend towards gamification activities and information systems has been observed to motivate positive behaviors to adapt to users' needs. The growing process of gamification of fields such as education and marketing has become powerful and has opened its way to the environment of companies, especially knowledge-based companies. Therefore, this study examines the impact of gamification on the different roles of employees of knowledge-based companies and their behavioral patterns and "visualizes" different communities that have appeared in a company but have not been noticed before. These observations, in turn, can show the adjustment of the working methods of knowledge-based companies. Research Question(s) How can gamification become an innovation in the knowledge-based field? What consequences will the adopted solutions have for improving the performance of knowledge-based companies? Literature Review Gamification is a way to enhance knowledge management with game design elements to increase user interaction, content creation and satisfaction (Duriník, 2014). Understanding the fundamental characteristics of the impact of gamification on knowledge work may be important for the future development of expert and intelligent systems, which are increasingly used to support knowledge work in a variety of ways. First, embedding gamification in the design of expert and intelligent systems may help to organically implement such a system in work practices, for example by addressing issues of inappropriate use (Spanellis et al, 2020). Secondly, the implementation of expert and intelligent systems can be supported by using gamification, and this potential advantage can be enhanced by knowledge-based workers who are generally accustomed to gamification (González et al., 2016). Since in knowledge-based companies, managers are considered as one of the main decision-making factors, having their innovative features and capabilities has an impact on the improvement and success of the knowledge-based company's efficiency. Therefore, it can be said that innovation is considered to be the most key and important factors of companies' profitability (Lopez-Nicilas & Merono-Cerdan, 2011). Methodology This research is based on the purpose of applied research and based on the approach of qualitative research. The statistical population studied in this research is managers, experts and experts of knowledge-based companies. Therefore, the selection of people was made based on the purposeful sampling of 12 people and the respondents are familiar with gamification technology and have records in this field. Sampling adequacy follows the rule of theoretical saturation. Brown and Clark's (2006) 6-step thematic analysis method was used to analyze the interview text. Results Analyzing the research data in three stages of basic themes, organizing themes, and overarching themes finally led to 71 basic themes, 10 organizing themes, and 4 overarching themes, which include all the emerging themes, which are shown in the table below. mentioned. Discussion This research has been conducted with the aim of identifying the components of gamification implementation in the working environment of knowledge-based companies. In this context, it can be stated that knowledge-based companies can, based on the extracted factors, establish the necessary conditions. To accept, promote, design and develop and evaluate and implement their activities based on gamification. Also, according to the factors extracted in this research, using the correct implementation method of gamification in the environment of knowledge-based companies is completely different from other information technology environments. The results showed that design and training are among the most important factors identified in the implementation of gamification in the working environment of knowledge-based companies; Therefore, knowledge-based companies should plan that the systems should have an appropriate training stage for learning, identifying and modifying patterns and act accordingly.
Management approaches in the field of smart
Modeling and Scenario Analysis of Critical Success Factors for the Implementation of Industry 4.0 in Healthcare
Esmaeil Mazroui Nasrabadi; Zahra Sadeqi Arani; Mostafa Salmannejad
Volume 12, Issue 46 , November 2023, , Pages 153-183
Abstract
AbstractThe implementation of Industry 4.0 in the healthcare sector to improve community health is of great importance. Therefore, it is crucial to identify the critical success factors for implementing Industry 4.0 in the healthcare sector, model them, and analyze scenarios for targeted interventions. ... Read More AbstractThe implementation of Industry 4.0 in the healthcare sector to improve community health is of great importance. Therefore, it is crucial to identify the critical success factors for implementing Industry 4.0 in the healthcare sector, model them, and analyze scenarios for targeted interventions. This issue has not been investigated in previous studies, and this research aims to fill this research gap. This research was conducted in two qualitative and quantitative stages. The statistical population was experts in both stages, and the judgmental and snowball sampling methods were used. The first stage had a population size of 17, determined based on theoretical saturation, while the second stage had a population size of 10. Thematic analysis was used as the data analysis method in the first stage, and fuzzy cognitive mapping was used in the second stage. The results showed that "competent managers," "support and cooperation," and "competent human resources" have the most significant impact, while "project management," "appropriate planning," and "support and cooperation" are the most susceptible. Furthermore, "support and cooperation," "appropriate planning," and "project management" are the most central. Three forward and three backward scenarios were designed for more effective interventions. It is recommended to improve the organization's educational system, strengthen the succession system, implement transparent contracts, and improve the quality of human resource management to achieve independent variables. IntroductionThe health sector is of great importance to governments. Recent developments in technology (especially industry 4.0) have led to a transformation in the health sector, and if the health sector fails to adapt to these developments, it will face serious damage. These developments have led to widespread benefits such as reduced costs, increased productivity, and increased quantity and quality of service. Failure to pay attention to this transformation can lead to the loss of competitive advantage and lack of proper control of the disease, so the factors that can lead to successful implementation of Industry 4.0 must be identified. This research has three steps. The first step is to identify critical success factors in the implementation of Industry 4.0 in health care.In the second step, the modeling of these factors is discussed to determine the role of each CSF and their relationships. Finally, by identifying the backward and forward scenarios, it is possible to apply targeted interventions. Literature ReviewThe 4th Generation Industrial Revolution has transformed healthcare into healthcare 4.0. Like the industry that has gone through different generations, healthcare has also had different generations: Healthcare 1.0, Healthcare 2.0, Healthcare 3.0, and Healthcare 4.0 (Oduncu, 2022). Health 4.0 is a continuous and transformative process for converting the entire healthcare supply chain. With the help of health care 4.0 patients get rid of negative conditions such as the progression of their disease, and new inventions in the field of health that reduce human death, and prevent the prevalence of diseases. The patient's records are also safe and used if necessary (Oduncu, 2022). In this generation of health, IOT, intelligent measurement, cloud computing, big data analysis, artificial intelligence, automatic control, and automatic and robotic implementation are combined, to create not only digital health products and technologies but also digital health services. (Pang et al., 2018). MethodologyTo answer the research questions, two qualitative and quantitative steps have been performed. In the qualitative stage, the CSFs for the implementation of Industry 4.0 in the healthcare sector were identified. The method of sampling is purposeful, and the sample size was determined by theoretical saturation. Semi-structured interviews and thematic analysis method has been used to gather and analyze the data. In the second stage, the conceptual model of the CSFs of Industry 4.0 implementation was extracted. Using a researcher-made questionnaire data was collected and modeling CSFs was carried out using the fuzzy cognitive map method and Pajek and FCMapper software. ResultsIn the first stage, based on interviews, 32 CSFs were identified in the healthcare sector and categorized into 11 groups that is:Future study and gaining experienceProject ManagementCompetent managersCompetent human resourceThe rule of lawProper hardware and softwareOrganizational readiness analysisComplete ecosystemProper planningFinancingSupport and cooperationPublic education (for the community)The fuzzy cognitive map method was used to identify CSFs model. Out of the 12 CSFs studied, 2 variable is drivers, "competent managers" and "organizational readiness analysis"; and two receivers are "project management" and "public education" factors. The remaining 8 factors have ordinary status, meaning that they have both effective and effective roles. In the first backward scenario, the "project management" factor was considered as the target factor to create a scenario path. During the process of drawing this scenario, the "proper hardware and software" factor was determined as the starting point of the scenario. The path of this scenario shows the high importance of the "proper hardware and software" factor in improving the current state of project management. The second and third scenario pathways are part of the first scenario, which indicates the high importance of "proper hardware and software" and "support and cooperation" in Healthcare 4.0.The first forward scenario path shows that as the "competent managers" factor improves, the maximum improvement in the "competent human resource" will be formed because competent managers are unable to work with ordinary human resources and feel more damaged. The second and third scenarios as part of the first scenario also emphasize its double importance. Overall, it can be claimed that the existence of competent managers and competent human resources and their support and cooperation with each other are considered to be the most important factors that will strengthen the success of the health sector in the implementation of the fourth-generation industry. Discussion and ConclusionThe research findings include important suggestions for healthcare managers in the implementation of the fourth-generation industry. According to the findings from the backward scenario, it is suggested that the most priority for the “proper hardware and software” factor is considered as the essential starting point in this project; because if it is ignored, the human resources involved will not take this project seriously and therefore will not take action for other factors. But the presence of this factor, as can be seen in all three paths, can have the most important impact on the support and cooperation of the organization's managers and human resources. These factors will also activate management activities such as project management and planning. It is also recommended to use competent and specialist managers at the starting point of the project. Experienced and expert managers will be able to make the most of the organization's human resources capacity and provide the best possible way to provide the required hardware and software.
Management approaches in the field of smart
Identifying and ranking the antecedents of digital marketing development based on blockchain technology (case: aviation industry)
Amir Valafar; Morteza Maleki MinBashRazgah; Azim Zarei; feiz davood
Volume 12, Issue 46 , November 2023, , Pages 219-257
Abstract
AbstractBlockchain technology is one of the most promising technologies of this century that has the potential to bring about fundamental changes in business models in a wide range of industries. The current research seeks to identify the antecedents of the development of digital marketing ... Read More AbstractBlockchain technology is one of the most promising technologies of this century that has the potential to bring about fundamental changes in business models in a wide range of industries. The current research seeks to identify the antecedents of the development of digital marketing based on blockchain technology from the point of view of marketing experts in the aviation industry.This research is practical in terms of orientation and positivist from a philosophical point of view, which was carried out using a mixed method.,In this study, the antecedents of the development of digital marketing based on blockchain technology were first extracted by literature review and semi-structured interviews, and with the help of experts, the final factors were identified;Then, these factors in the form of Q cards were provided to 22 marketing experts in the aviation industry who were selected purposefully and finally their views were analyzed using exploratory factor analysis.The participants in this research have 6 different views and their mental patterns are categorized based on market variables, internal, content, technological, human and environmental factors.The results of this research have given useful insight to managers and decision makers in the aviation industry, so that by knowing these factors, they can strengthen and develop digital marketing in airline companies.IntroductionThe transformation arising from the fourth industrial revolution is based on the integration of digital technologies. This transformation is effective in all dimensions of business activities and causes fundamental changes in the way organizations function and provide value to consumers. Blockchain technology is one of the most promising technologies of this century that has the potential to bring about fundamental changes in business models in a wide range of industries. In the current competitive environment, marketing managers know that forming and maintaining relationships in the digital space is essential(Hussain Zahid,2021). The benefits of digital marketing in the aviation industry include making the user more active, providing rich content to the customer, providing airport services to the customer digitally, increasing the speed and convenience of transactions, increasing customer satisfaction, reducing workload and increasing the utilization of airlines(Keke, 2022).Today, blockchain has strongly influenced business models(Jain et al,2022)Blockchain has also changed the way digital marketing works(Nilsson&Ali,2018). The most important requirements in the aviation industry are high data security, protection against unauthorized access and privacy. Blockchain technology can help digitize the aviation industry and create new business models(Kehoe&Hallahan,2017). One of the capabilities of blockchain technology is providing a customer loyalty program. Blockchain technology can help passengers to buy tickets using digital currency and eliminate the chance of selling and buying duplicate tickets) Ahmad et al, 2021 (. Blockchain creates complete transparency and brand traceability in digital marketing (Stone&Woodcock,2014). The purpose of this study is to identify and classify the antecedents of the development of digital marketing based on blockchain technology from the point of view of airline marketing experts. Literature ReviewMarketing is a social and managerial process through which people and organizations get what they need by creating and exchanging value with others) Kotler et al,2017(Many companies invest in digital marketing as a factor in the development and sustainability of future business(Al-bawaia,2022). Blockchain is a peer-to-peer digital ledger of transactions that may exist publicly or privately between users(Rennock et al,2018). Blockchain features are decentralization, immutability, transparency and auditability of transactions(Monrat et al,2019). Due to the need to develop air transportation in the country, 18 airlines are engaged in air transportation activities. The airline industry is part of a highly interconnected ecosystem of various players including aircraft and aircraft component manufacturers, lessors, airports, freight forwarders, global distribution system providers and online travel agencies. Airlines are at the heart of this ecosystem. Today, the airline industry must include the use of modern technologies in its plan to provide better services to passengers(Riechmann,2020) MethodologyThe current research seeks to identify the antecedents of the development of digital marketing based on blockchain technology from the perspective of marketing experts in the aviation industry, which was conducted in a combined method, in this research, first by reviewing the literature and semi-structured interviews, the factors affecting the development of digital marketing based on blockchain technology China was extracted and finalized with the help of experts. Then these factors were given to 22 aviation industry marketing experts in the form of Q cards. These people were selected purposefully and finally their opinions were analyzed using exploratory factor analysis. ResultsThe participants in this research have 6 different views and their mental patterns are categorized based on market variables, internal, content, technological, human and environmental factors. According to the views of the participants, 6 identified mental patterns explain 75.194% of the total variance. The first mental pattern is 19.283%, the second mental pattern is 13.459%, the third mental pattern is 11.585%, the fourth mental pattern is 11.375%, the fifth pattern is 10.080% and the sixth pattern is 9.142%.Discussion and ConclusionInvestigations show that no such research has been done in this organization and similar organizations. The results were also compared with previous researches. Although the method used in this research has not been used in previous researches; But some of the results obtained are similar to the researches (Lopes et al, 2021), (Antoniadis et al, 2019) and(Hosseinpouli Mamaghani et al, 2021) and the effect of variables The development of digital marketing based on blockchain technology is confirmed in this research. Market variable, existing competition, competitors' strategy and increasing demand in digital marketing in the aviation industry have been the most important from the point of view of marketing experts in the aviation industry. It seems that the focus on market factors is due to the fierce competition between airlines, which shows that managers in this industry should pay more attention to these categories. The results of this research can help decision makers and policy makers in adopting a suitable strategy for the development of digital marketing and strengthen digital marketing in airlines.
Management approaches in the field of smart
The impact of gamification elements on customer engagement
Mahsa Akbari; mostafa bigdeli; Parvaneh Charestad
Volume 12, Issue 46 , November 2023, , Pages 297-326
Abstract
AbstractGamification is a relatively new concept that has seen a significant increase in its use in recent years. Gamification involves the application of game elements in a non-gaming environment to create a gaming experience related to a product or service. The aim of this research is to investigate ... Read More AbstractGamification is a relatively new concept that has seen a significant increase in its use in recent years. Gamification involves the application of game elements in a non-gaming environment to create a gaming experience related to a product or service. The aim of this research is to investigate the impact of different aspects of gamification (immersion, achievement, social) on customer engagement (emotional, cognitive, social) in the online store of Digikala. The research population consists of consumers and users of the Digikala website who have made at least one purchase on this site. In this regard, 222 questionnaires obtained from Digikala website users' data were analyzed. The research model was designed by reviewing the literature related to the research topic and previous studies, and it was analyzed using structural equation modeling. Finally, it was determined that the aspects of gamification have a positive and significant effect on customer engagement. The immersion aspects of gamification have a positive impact on emotional aspects of customer engagement, the achievement aspects affect the cognitive aspects of customer engagement, and the social aspects of gamification also have a stronger positive impact on the social aspects of customer engagement.IntroductionGamification has gained recognition as a powerful tool for establishing customer engagement in recent years, garnering significant attention both in industry and academia (Huotari, 2017), (Hamari et al., 2014), (Hamari et al., 2014b). This is because the inherent nature of play and the potential for possible achievement evoke positive emotions in people. In marketing, gamification is a means to elicit positive emotions in customers for the sale of a product or service. The use of gamification helps consumers spend more time on your website, increasing the likelihood of them making a purchase. In this context, gamification can be described as the use of game design in a non-gaming environment (Deterding et al., 2011). In other words, gamification seeks to replicate the effects of games, including motivation, excitement, and repetition, in a real-world context. Therefore, gamification technologies have the capability to manipulate social and individual factors to motivate customers and influence their intentions (Shang & Lin, 2013), (Jackson, 2009).As online games and social software continue to advance and become integrated into e-commerce businesses, they create new patterns that enhance user experiences and encourage active participation (Hsu & Chen, 2018).With the expansion of online businesses, the use of effective marketing techniques to attract customers has become crucial. In this regard, Digikala, the largest online retailer in Iran, has been no exception. Therefore, the use of gamification has great importance in branding and improving customer experiences.Literature ReviewGamification is an innovative concept that has not only impacted the gaming industry but has also opened avenues in management sciences to provide maximum effectiveness for organizations in competitive conditions. Initial studies on gamification were conducted in 2008 by Brett Terrill. However, its scientific popularity and extensive research began around 2010 (Alhamed & Morano, 2018).In terms of the effectiveness and the impact of gamification on marketing concepts, particularly in customer engagement, extensive research has not been conducted. However, most studies indicate a positive impact of gamification on customer engagement. In this regard, we will review some important research studies.In a study that examined the effects of gamification aspects on customer engagement dimensions and brand value among customers of Huawei and Xiaomi in social networks, it was found that gamification aspects have a significant impact on customer engagement dimensions and brand value (Xi & Hamari, 2019). In another study that investigated the impact of gamification on customer engagement and online sales, it was revealed that gamification aspects such as social interactions, goal orientation, and rewards lead to increased customer engagement and online sales (Eisingerich et al., 2019). In a study that focused on the impact of gamification on participation in online programs, the results indicated that gamification significantly affects participation (Looyestyn et al., 2017).MethodologyThis study is descriptive & applied in nature and employs a quantitative approach. Data collection was done through questionnaire. In this study, the statistical population consists of customers of the Digikala website who have made at least one purchase from this site. Since this website is the most well-known online shopping site in Iran, a structured questionnaire was distributed to 300 Digikala users using convenience sampling method. After filtering out incomplete and problematic questionnaires, a total of 222 questionnaires were gathered. Data analysis was conducted using Structural Equation Modeling (SEM) through the Lisrel Software.ResultsBased on the results obtained from the hypothetical model, we conclude that:The influence of immersion aspects of gamification on the emotional dimension of customer engagement was confirmed (Hypothesis 1).The influence of immersion aspects of gamification on the social and cognitive dimensions of customer engagement was not confirmed (Hypotheses 2 and 3).The influence of achievement aspects of gamification on the emotional and cognitive dimensions of customer engagement was confirmed (Hypotheses 4 and 5).The influence of achievement aspects of gamification on the social dimension of customer engagement was not confirmed (Hypothesis 6).The influence of achievement aspects of gamification on the emotional, cognitive, and social dimensions of customer engagement was confirmed (Hypotheses 7, 8, and 9).The immersion aspects of gamification have a stronger and more significant impact on the emotional dimension of customer engagement compared to other dimensions (Hypothesis 10).The achievement aspects of gamification have a stronger and more significant impact on the cognitive dimension of customer engagement compared to other dimensions (Hypothesis 11).The social aspects of gamification have a stronger and more significant impact on the social dimension of customer engagement compared to other dimensions (Hypothesis 12).Discussion & ConclusionIn general, the findings of the present research indicate that immersion aspects of gamification (such as creating avatars, customizing applications and web pages, storytelling, and narrative) have a greater impact on the emotional dimensions of customer engagement.When compared to immersion aspects, achievement aspects of gamification, such as giving prizes, medals, digital currency, coins, points, and gift cards, have a greater influence on the cognitive dimensions of customer engagement. They also affect the emotional aspect. Providing rewards and medals leads to customers forming a better rational and cognitive perception of our brand.Moreover, social aspects of gamification, like organizing competitions and teamwork activities and using social networks, have a more significant impact on the social dimension of customer engagement. However, they also have an effect on the emotional and cognitive dimensions.The findings of this research are consistent with the results of previous studies, including Madura (2015), Zhi and Hamari (2019), Harwood and Garry (2015), Yin et al. (2017), and Eisingerich et al. (2019).Based on the results obtained, it is recommended that online stores and smart businesses employ various gamification elements to increase customer engagement
Management approaches in the field of smart
The Evolution Path of Business Intelligence & social media Capabilities
maryam mirsharif; akbar alemtabriz; alireza motameni
Volume 12, Issue 45 , September 2023, , Pages 1-38
Abstract
The evolution of information technology, artificial intelligence, and large volumes of data in web2, led to the formation of a new approach from the convergence of two scientific fields of business intelligence (BI) and social media analysis (SMA), which is called social business intelligence (SBI) ... Read More The evolution of information technology, artificial intelligence, and large volumes of data in web2, led to the formation of a new approach from the convergence of two scientific fields of business intelligence (BI) and social media analysis (SMA), which is called social business intelligence (SBI) with some researchers. Growing the number of studies in BI and SMA and the explosion of information, required coherence, integration and summary to knowledge extraction. The purpose of this paper is to recognize the capabilities that are the result of the two scientific field convergence. The bibliometric methods have been used to analyze publications tile 2022 and map the topics trend, historical graph, co-occurrence network and knowledge map of social business intelligence capabilities. The results indicate that the nature of business intelligence studies changes toward the analysis of big social media data and integration of analytical and managerial capabilities in BI with the power of marketing, communication and networking in SM. Also, five clusters of social marketing capability, data analytic capability, knowledge capability, communication capability, and transformational capability have been identified for SBI. About the role of SBI in empowering organizations in the digital era, especially in business related to marketing and innovation goals, it is recommended to equip organizations with this technology and its capabilities.IntroductionThe evolution of information technology, artificial intelligence, and large volumes of data in web2, led to the formation of a new approach from the convergence of two scientific fields of business intelligence (BI) and social media analysis (SMA), which is called social business intelligence (SBI) with some researchers. Growing the number of studies in BI and SMA and the explosion of information, required coherence, integration and summary to knowledge extraction. One of the main topics of interest for business intelligence researchers is big social media data analysis, which brings many capabilities for organizations in the information age. This research has been used the bibliometric analysis method to recognize the capabilities of social business intelligence. Therefore, the social academic network of social business intelligence capabilities has been analyzed in order to gain knowledge about the research field, main topics, evolution path of concepts and a comprehensive view in the expansion of the current limited knowledges.Research Question(s)RQ: What are the capabilities of social business intelligence (SBI)?To answer this question, the following points are followed:1) How are the growth and development of studies in social business intelligence capabilities?2) In what scientific groups have these abilities been used?3) What are the most productive countries, publications, and most cited articles?4) Who are the influential authors in the research field?5) What is the evolution of citations and time trends of concepts in social business intelligence capabilities?6) What are the most important concepts in social business intelligence capabilities?Literature ReviewAlthough business intelligence has developed and grown over the years, the concept of social media-based business intelligence has gained a lot of attention in recent years. First, Studies focus on business intelligence capabilities and dynamic capabilities and the resource base view has been discussed a lot. In some studies, the organizational, technological, and innovational capabilities of business intelligence and the impact of the environment on the success of business intelligence have been explained (Işık et al., 2013), (Ramakrishnan et al., 2016), in group of studies, the positive relationship between dynamic capabilities, managerial capabilities in business intelligence and analysis (BI&A) has been investigated (Torres et al., 2018), in other group of studies, innovative infrastructure capabilities, process capabilities have been addressed to help decision making (Ramakrishnan et al., 2018).In recent years, the nature of studies in business intelligence capabilities has changed towards emerging technologies such as big data analysis, digital businesses, and social media big data. This group of studies focuses on the ability of social media analysis, the impact of social media capabilities in achieving knowledge management; sharing information, communication, facilitating business marketing, achieving competitive intelligence, and the strategic capability of social media in the organization's achievement of innovation. Various researchers have described the analytical aspect of SBI in knowledge extraction, decision making and marketing capabilities of social media base BI that can influence market intelligence, customer needs, and satisfaction (Ghofrani et al., 2018; Hameed et al., 2022; Pourkhani et al., 2019). Nevertheless, Social media data is recognized as the best source of data for business intelligence research (Choi et al., 2020; Tunowski, 2020) that can be used to achieve various goals such as data collection and perception, analytical results, and market goals. However, this research area is still in the early stages of development and needs more studies to mature.MethodologyIn this research, the five-step bibliographic analysis method (Zupic & Čater, 2015) has been developed to achieve the research objectives and extract knowledge about SBI capabilities. despite various studies on social media in business intelligence, there is little understanding of the synergy power of business intelligence and social media and SBI capabilities. thus, to achieve a comprehensive view of the convergence of two scientific fields and their capabilities, the bibliographic analysis has been used to extract the most cited articles, influential authors, most important publications, growth trends, and Thematic evolution. the co-occurrence network analysis of keywords has been used to extract topics' trends. to collect the required metadata, the Web of Science (WOS), the most comprehensive scientific database has been used, and approved by the Scientific Information Society (ISI). Also, the research chain explained by Chio (2020), related to business intelligence and social media analysis, has been used to extract and collect the required data and summarize part of the research literature.ConclusionThe results of the research indicate that in line with the growth of studies in the convergence of the two fields of business intelligence and social media analysis, the upward growth of studies in the capabilities of business intelligence centered on social media analysis is also evident and the increase in the number of studies with the expansion of the use of social media in businesses and big data analysis. The most important clusters identified in the word co-occurrence network are the concepts of social marketing capability, data analysis capability, communication capability, knowledge capability, and strategic capability. In other words, Business intelligence based on social media analysis or social business intelligence includes both capabilities and positive points of using business intelligence inside social media analysis capabilities, in other words, business intelligence capabilities in strategic fields, management, and analysis, are combined with the ability of marketing, expansion of communications and networking in social media. As a result, social business intelligence improves company performance by using artificial intelligence algorithms and big social media data analysis.Acknowledgmentshave been very grateful for the spiritual support of Dr. Eslam Nazemi.Keywords: Business Intelligence, social media, Social Business Intelligence, Bibliometrics, Capabilities.
Management approaches in the field of smart
Exploring the lived Experience of the Concept of Touch in Purchasing Product Categories from Physical and Online Stores
meisam Aminzadeh vahedi; seyyed hamid khodadad Hosseini; Beit Allah Akbari Moghadam
Volume 12, Issue 45 , September 2023, , Pages 39-69
Abstract
The touch of the product plays an important role in the final decision of the customer when purchasing from physical and online retail, and the sensations that come to be enjoyed through touch enable them to experience the product from all angles. Therefore, considering the importance of touch, ... Read More The touch of the product plays an important role in the final decision of the customer when purchasing from physical and online retail, and the sensations that come to be enjoyed through touch enable them to experience the product from all angles. Therefore, considering the importance of touch, this research has investigated the lived experience of touching the product from the point of view of customers of physical and online stores. The following article is done with qualitative method and phenomenological paradigm. The research community is made up of electronic and clothing buyers from online and physical stores: Technolife, Adak, Havadar and Happyland in Tehran, and through semi-structured interviews, evidence was collected based on the purposeful sampling method. The interviews continued until reaching the theoretical saturation, and in this research, the interviews reached saturation with 15 people. Based on the extracted results, the main themes include; Product perception is physical touch, virtual touch, touch experiences, need for touch and touch perceptions. According to the results, managers of physical and online stores should provide conditions (such as the use of modern technologies) that touch and contact with the product happen to both groups of online and physical buyers so that they can buy products based on their needs and wants, and also this research can pave the way for the development of touch literature for researchers. IntroductionThe touch of the product plays an important role in the final decision of the customer when purchasing from physical and online retail, and the sensations that come to be enjoyed through touch enable them to experience the product from all angles. Therefore, considering the importance of touch, this research has investigated the lived experience of touching the product from the point of view of customers of physical and online stores.Considering the importance of touch, this research seeks to answer this question: What are the themes of customers' lived experiences of understanding the concept of touch in physical and online shopping?Literature ReviewThere is a lot of research in the field of sensory marketing, some of which have focused on the importance of touch and the use of technologies (which create a multi-sensory experience for consumers).)Labrecque, 2020,p:1013؛ Mishra et al, 2020,p:1(.Many researchers have shown that the decision to buy will be positive after specific and positive emotional reactions that occur after touching the product (Hultén, 2020; Krishna, 2013,p:56).Retail companies recognize that product touch is an essential component of in-store experiences and explicitly encourage consumers to touch their products (Williams & Ackerman, 2011). On the other hand, online stores may use special features (for example, image magnification) to create a sense of tactile contact with products and create a so-called mental simulation with tactile products and create a favorable desire for their products (Overmars & Poels, 2015, p: 17). Meanwhile, touch interfaces may engage consumers with online shopping and influence their purchasing decisions (Chung et al, 2018, p: 795). Analyzed the main drivers for product purchase decisions and the differences between online and offline retailing. She confirmed that most of the consumers search about the product and check it mostly online, but when buying, they tend to go to physical stores (Gligorijevic, 2011). Touch in consumer behavior is a new research area (Jansson-Boyd, 2011a, p: 219), and considering the importance of touch in theoretical literature and its importance in customer decisions, this research has been conducted in this field. MethodologyThe current research is applied-developmental in terms of its purpose and was carried out based on the descriptive phenomenological approach, also practical and practical solutions for solving problems and improving processes were presented. This type of research is done to answer practical questions and meet practical needs (Maxwell et al, 2009, p: 198).The following article is done with qualitative method and phenomenological paradigm. The research community is made up of electronic and clothing buyers from online and physical stores: Technolife, Adak, Havadar and Happyland in Tehran, and through semi-structured interviews, evidence was collected based on the purposeful sampling method. The interviews continued until reaching the theoretical saturation, and in this research, the interviews reached saturation with 15 people. ResultsThe purpose of this research is to discuss how to understand the concept of touch in the process of purchasing product classes from physical (face-to-face) and online stores and to conduct a topical analysis based on descriptive phenomenology. Based on the extracted results, the main themes include; Product perception is physical touch, virtual touch, touches experiences, need for touch and touch perceptions. According to the results, managers of physical and online stores should provide conditions (such as the use of modern technologies) that touch and contact with the product happen to both groups of online and physical buyers so that they can buy products based on their needs and wants, and also this research can pave the way for the development of touch literature for researchers. DiscussionThe present study discusses how to understand the concept of touch in the process of purchasing product classes from physical (face-to-face) and online stores and conducts thematic analysis based on descriptive phenomenology. Based on this, the main theme of understanding the product includes sub-themes: understanding the personality of the product, ease of use of the product, emotional function and cognitive function, the main theme of physical touch of the product, including sub-themes: evaluation of inherent properties by hand touch and evaluation of geometric properties by hand touch, the main theme Touch and tactile perceptions include sub-topics: visual and audio virtual information and textual virtual information combined with sound and image, the content of touch experiences including sub-topics: product knowledge and familiarity with the brand; The theme of customer's need for touch includes sub-themes: instrumental touch and automatic touch, and the theme of tactile perceptions includes sub-themes: trust-seeking measures and compensatory return policy. ConclusionThe results have shown that people for whom the need to touch is important because of reducing the risk in purchasing, to better recognize the product features, to ensure the usefulness and ease of use of the product, to acquire skills and better process product information by hand before purchasing, touched so that they can have a better evaluation of the product.AcknowledgmentsWe are grateful to all the stores and buyers who helped us in conducting the interviews. Keywords: live Experience, product Touch, product Categories, physical and Online Store.
Management approaches in the field of smart
A Business Intelligence Maturity Model in Healthcare Based on the Combination of Delphi and DEMATEL-ANP Methods
Mahnaz Saeedi Mamaghani; Mohammad Javad Ershadi; Arman Sajedinejad
Volume 12, Issue 45 , September 2023, , Pages 117-156
Abstract
The maturity of business intelligence, which is the main goal of this research, plays an important role in intelligent decision-making, planning, control and monitoring in the field of health care. In order to identify the effective factors, the Delphi method was used and experts' opinions were, and ... Read More The maturity of business intelligence, which is the main goal of this research, plays an important role in intelligent decision-making, planning, control and monitoring in the field of health care. In order to identify the effective factors, the Delphi method was used and experts' opinions were, and in order to determine the effectiveness and effectiveness of the indicators and finally to prioritize them, used the DANP method. The statistical sample includes 20 targeted academic experts and health care experts. According to the results of the Delphi section, 26 main indicators finalized in the research were identified, which are divided into three main categories including organizational, process and judgment criteria. According to the results of the DANP process, flexible and expandable technical infrastructure criteria, data and system quality and the correct definition of business intelligence problems and processes were prioritized as the three criteria with the highest ranking in the maturity of business intelligence. The business intelligence maturity model proposed by the research can be a road map for the successful implementation of business intelligence in the field of health care.IntroductionBusiness intelligence is one of the most important issues in recent decades as a decision-making system for managers of organizations in order to plan, control and intelligently monitor companies and their subordinate units and measure the achievement of organizational goals. Business intelligence includes a comprehensive set of tools, technologies and products designed to collect, aggregate, analyze and present usable data (Reinschmidt J. & Francoise A., 2000) Introduction of new and complex medical technologies, the global trend of increasing length Longevity, the unexpected development of chronic diseases and emerging diseases (such as Covid-19) can lead to an increase in health care costs to unsustainable levels (Janssen & Moors, 2013; Qaseem et al., 2012). Public or private medical care organizations have focused their efforts on achieving new, cost-effective and efficient levels of care (Romanow et al., 2012). For this purpose, information technologies play a fundamental role by transforming data into knowledge that can improve patient care, medical care facilities, and process management (Behkami & U. Daim, 2012; Li & Mao, 2015; Pai & Huang, 2011). Considering the very important role of data in supporting the improvement of the organizational level, business intelligence is one of the important areas of research for researchers and activists in the treated field (Chen et al., 2012).The field of business intelligence has improved significantly over the past decade and has promising applications in the health field (El-Gayar & Timsina, 2014; Gandomi & Haider, 2015). Indeed, business intelligence can not only improve outcomes in healthcare organizations but also help them achieve continuous improvement and precision in medicine (Christensen et al., 2008; Gastaldi et al., 2015; Tremblay et al., 2012).Investigating the process of information production and transmission in the field of healthcare is of great importance. Today, organizations active in this field need correct information at the right time, in order to make the best decision by the right person. But many of the systems used by users do not have appropriate and expected performance, and health care organizations need to act smarter, but despite the potential, business intelligence has not been widespread in the field of medical care (Hanson, 2011) and research There are limited studies on how to successfully implement a sample business intelligence solution in the field of medical care (Foshay & Kuziemsky, 2014). This research tries to fill this gap by developing a model that provides maturity levels for evaluating and improving business intelligence solutions in healthcare. Therefore, considering the explanations and issues raised in the field of business intelligence, the present research seeks to answer a main question, what is the maturity model of business intelligence in the field of health care providers? In this regard, two sub-questions are also raised, which are: What are the indicators affecting the maturity model of business intelligence in the field of health care providers, and what is the prioritization of these factors?Literature ReviewAccording to the studies of Foshay and Kuziemsky, healthcare organizations are under constant pressure to not only achieve more results with fewer resources, but also to gradually transform into information-based systems (Foshay & Kuziemsky, 2014). Considering that the amount of information recorded by electronic health records and medical record centers is growing rapidly, healthcare organizations are trying to use tools such as business intelligence to improve the efficiency and effectiveness of their operations (Kuiler, 2014; Wang et al., 2018).According to the research conducted by Naqash, business intelligence solutions help decision-makers by providing practical information in the right format, at the right time and in the right place (Negash, 2004). The business intelligence market has grown significantly and has become the first investment priority for CIOs (Gartner, 2015). Also, the awareness of the potential benefits of business intelligence is increasing (Chuah & Wong, 2011), however, the implementation of business intelligence in health and treatment organizations is progressing relatively slowly and in a case-by-case manner (Foshay & Kuziemsky, 2014).Some studies show the benefits of business intelligence to improve patient care, treatment outcomes, effective use of human resources, lower costs (Borzekowski, 2009), higher revenue (Ayal & Seidman, 2009) and improved productivity (Lucas et al., 2010). have reported As reported in other studies, the successful implementation of business intelligence in healthcare depends on understanding and analyzing the characteristics of this field (Avison & Young, 2007; Mettler & Vimarlund, 2009). Therefore, one of the most important goals of this research is to provide a maturity model for the continuous development and improvement of business intelligence solutions to healthcare professionals. In Table (1), some business intelligence maturity models in the field of health care that have been implemented in the past are reviewed. Table 1. Some business intelligence maturity models in healthcareResearch resultsResearch researchersA framework for defining and prioritizing decision support information needs in the context of specific health care processes is presented.Foshay & Kuziemsky (2014)In this study, the subject of comprehensive business intelligence in special care and understanding the basic concepts of business intelligence solutions with comprehensive features have been discussed.Pereira et al. (2016)A way to identify the capabilities and weaknesses of the intelligent information system in the hospital has been presented.Carvalho et al. (2018)The methodology of implementing the model of hospital information systems is presented.Carvalho, Rocha, & Abreu (2019)This article identifies a wide range of maturity models in the health sector and its characteristics and strengthens the belief that the maturity of the hospital information system can contribute to the quality of information and knowledge management in this field.Gomes & Romão (2018)The result of this research is the maturity model of the hospital information system based on 6 stages of maturity. The hospital information system maturity model has the feature of collecting a set of key and effective factors of maturity and related characteristics and not only enables the evaluation of the overall maturity of a hospital information system, but also the individual maturity of its different dimensions.Carvalho, Rocha, Vasconcelos, et al. (2019)The purpose of this research is to determine how the existing business continuity maturity models conform to the ISO 22301 standard and to map the existing health care model with the business continuity maturity model.Haidzir et al. (2018)In this research, while determining organizational maturity levels, effective factors in improving maturity have been identified and prioritized, and a road map for applying business intelligence in this field has been presented.(Gastaldi et al. (2018)The result of this research is to present a maturity model including six stages of the growth and maturity sequence of the hospital information system.Carvalho, Rocha, Vasconcelos, et al. (2019)The importance of scientific research on business intelligence with a focus on patients has been investigated.Zheng et al. (2018)In this research, by providing a maturity assessment framework and infrastructure development based on results, information and digital transformation in health care has been encouraged and guided.Williams et al. (2019)In this research, it has been determined that organizational business intelligence application screens at all management levels have a positive and significant effect on measurable performance indicators. In this context, when businesses monitor their operational activities through business intelligence, they have come to the conclusion that performance indicators provide less time wastage, high reliability, integrated data, quality and accurate valuation benefits in the evaluation process.Işık et al. (2021)The relevant factors for the adoption of business intelligence system have been established using a systematic literature review and a theoretical structure based on technology, organization, environment and determinants and theories of CEOs. This research deepens the literature of business intelligence system and promotes the understanding of the important decision-making elements of business intelligence system.Salisu et al. (2021)The co-creation approach will optimize the currency, accuracy and appropriateness of information in the digital health profile, understanding and use of the digital health profile and the maturity assessment tool to facilitate informed iterative discussions by Pacific Island countries on digital health maturity in order to use digital tools to strengthen use the country's health systems. Digital health profile and maturity assessment tool can rationalize the selection and use of existing tools and reduce cognitive overload.Liaw et al. (2021)In this research, an alternative solution with the benefits and possible costs of its implementation in the hospital has been shown, and the proposed initial evaluation method can be used in different health and treatment units after confirming the weight of the criteria based on the adopted strategy.Wielki & Jurczyk (2019)The results of the study enrich the recent literature of business intelligence system and improve the understanding of the decision-making processes of practitioners to obtain the maximum value from the adoption of business intelligence system.Ahmad et al., (2020)The findings support the argument that the organizational learning culture plays an important role in the business intelligence system and also affects the business performance.Arefin et al., (2021)MethodologyTo implement business intelligence in the field of health care, the characteristics of this field must be understood and analyzed; This task has been carried out in three stages. First, the subject literature was analyzed with the "systematic review" method, and in addition to the field of health care, all sectors in which the maturity of business intelligence was evaluated were also considered. In the following, a series of key success factors of business intelligence and maturity components were extracted by examining more than 23 articles in the fields related to business intelligence and further, the steps of implementing the proposed method are also described.3.1. First stage - knowledge acquisitionAt this stage, previous studies in the field of business intelligence maturity model, evaluating the value of key success factors in business intelligence and identifying maturity components were reviewed. In this study, the structured search strategy method was used as data sources from Emerald, Sage, Elsevier, IEEE, Taylor & Francis, and Springer databases in the period from 2000 to the beginning of 2022. At first, this study used the following keywords and search terms, combined and separate: "business intelligence", "factors affecting business intelligence system", "business intelligence maturity", "maturity measurement" and "business intelligence system in health care". The collection of articles presented in this research was consistent with the topic of this research in terms of questions, objectives, adopted frameworks and findings. The definitions used and their alignment with the measurement adopted were evaluated, to ensure that the factors of business intelligence investigated by different researchers are largely similar. Finally, by advancing the previous steps, an initial version of the business intelligence maturity model was adopted, which is significantly different from the final business intelligence maturity model.3.2. The second stage - identifying and categorizing the criteriaAfter extracting the main criteria influencing the success of business intelligence in three areas of organization, process and technology, using the Delphi decision-making technique, the key factors and important criteria of business intelligence maturity in health care organizations were determined and categorized, and finally the maturity model of business intelligence in the field of health care, it was confirmed by a survey of experts.3.3. The third step - determining the criteriaAfter finalizing the dimensions and criteria of the research with the Delphi method, using pairwise comparisons and the Dimtel method based on the network analysis process method, the internal and external connections of the factors were determined and each of the factors were weighted and prioritized. In this step, a committee evaluation method was used to evaluate the validity of the questionnaire (Harkness & Schoua-Glusberg, 1998). In addition, ANP-DEMATEL combined method was used to evaluate how and how much the components affect each other. Various researchers such as (Đurek et al., 2019; Rasouli et al., 2021) have used this approach in the field of maturity model.ResultsIn this research, business intelligence was investigated in three basic areas of organization, process and technology, and each of these areas has criteria. First, articles were comprehensively reviewed in the field of business intelligence maturity in order to determine the dimensions of the goal and criteria. The criteria of the designed research maturity model were finalized using the Delphi method and with the opinion of experts, and then decision-making methods with multiple criteria were used to measure the optimality. The effects of goals, dimensions, and criteria on each other were investigated with the Dimtel method, then the dimensions and criteria were weighted in terms of importance with the network analysis process method. According to the results of Dimtel, the two dimensions of technology and process are effective, and the organizational dimension is effective. The organizational field has a higher relative importance than process and technology and has more interaction with other factors of the system and is affected by two dimensions of technology and process. The results of the analysis of the questionnaires of the network analysis process method answered by the experts show that the organizational factor is the most preferred and heaviest factor in the maturity of business intelligence, and then the process factor has a higher weight and the technology factor has a lower weight than the other two areas. In line with the results of William et al. (2019) and Gastaldi et al. (2018), who have encouraged and guided information and digital transformation in health care by providing a maturity assessment framework and infrastructure development based on results, respectively, two technical infrastructure criteria Flexible and expandable (hardware and software) and data and system quality were obtained from the highest importance compared to other criteria. And in the same way, the criterion of the correct definition of business intelligence problems and processes was prioritized with the third rank compared to other criteria in the maturity of business intelligence, and the rest of the criteria were also ranked in the article. Jayanthi Ranjan (2008) has also achieved this. In this way, a comprehensive and complete business intelligence maturity model was obtained in the field of health care, which can make the path of business intelligence maturity smoother in health care and be a road map for the successful implementation of business intelligence maturity in health care. It is suggested that in future researches, the proposed maturity model should be practically implemented in health care organizations and the maturity level of business intelligence should be evaluated. Figure 1. The final research model (source: researcher's findings)Organizational field• Cooperation between the employees of the organization and the information technology department• Alignment of business strategies with business intelligence strategies• Senior management support for the business intelligence project• Clear goals and vision for business intelligence• Development of business intelligence strategy• The ability of the organization to provide sufficient resources and funds needed for business intelligence projects• Risk-taking of senior managers in investing in new information technologies• Capabilities of the team/employees/managers• Monitor information through the Business Intelligence Assessment Center• Continuous improvement of organizational processes (improvement of competence)Technology field· Flexible and expandable technical infrastructure (hardware and software)· Data and system quality· Appropriate technology/tools or the use of appropriate technology and tools for hospital conditions· Business intelligence system architecture· Integration of business intelligence systems with other systems· Quality of data analysis· ConnectorBusiness intelligence in the field of health careProcess area• Correct definition of business intelligence problems and processes• Using patterns and repeatable methods in designing business intelligence projects• Aligning business intelligence solutions with user expectations• User training and support• Effective change management• Balanced and strong composition of the business intelligence project group• Project planning and management in the implementation of business intelligence• Measuring business intelligence• Decision makingKeywords: Business Intelligence, Healthcare, DEMATEL, ANP. The maturity of business intelligence, which is the main goal of this research, plays an important role in intelligent decision-making, planning, control and monitoring in the field of health care. In order to identify the effective factors, the Delphi method was used and experts' opinions were, and in order to determine the effectiveness and effectiveness of the indicators and finally to prioritize them, used the DANP method. The statistical sample includes 20 targeted academic experts and health care experts. According to the results of the Delphi section, 26 main indicators finalized in the research were identified, which are divided into three main categories including organizational, process and judgment criteria. According to the results of the DANP process, flexible and expandable technical infrastructure criteria, data and system quality and the correct definition of business intelligence problems and processes were prioritized as the three criteria with the highest ranking in the maturity of business intelligence. The business intelligence maturity model proposed by the research can be a road map for the successful implementation of business intelligence in the field of health care.IntroductionBusiness intelligence is one of the most important issues in recent decades as a decision-making system for managers of organizations in order to plan, control and intelligently monitor companies and their subordinate units and measure the achievement of organizational goals. Business intelligence includes a comprehensive set of tools, technologies and products designed to collect, aggregate, analyze and present usable data (Reinschmidt J. & Francoise A., 2000) Introduction of new and complex medical technologies, the global trend of increasing length Longevity, the unexpected development of chronic diseases and emerging diseases (such as Covid-19) can lead to an increase in health care costs to unsustainable levels (Janssen & Moors, 2013; Qaseem et al., 2012). Public or private medical care organizations have focused their efforts on achieving new, cost-effective and efficient levels of care (Romanow et al., 2012). For this purpose, information technologies play a fundamental role by transforming data into knowledge that can improve patient care, medical care facilities, and process management (Behkami & U. Daim, 2012; Li & Mao, 2015; Pai & Huang, 2011). Considering the very important role of data in supporting the improvement of the organizational level, business intelligence is one of the important areas of research for researchers and activists in the treated field (Chen et al., 2012).The field of business intelligence has improved significantly over the past decade and has promising applications in the health field (El-Gayar & Timsina, 2014; Gandomi & Haider, 2015). Indeed, business intelligence can not only improve outcomes in healthcare organizations but also help them achieve continuous improvement and precision in medicine (Christensen et al., 2008; Gastaldi et al., 2015; Tremblay et al., 2012).Investigating the process of information production and transmission in the field of healthcare is of great importance. Today, organizations active in this field need correct information at the right time, in order to make the best decision by the right person. But many of the systems used by users do not have appropriate and expected performance, and health care organizations need to act smarter, but despite the potential, business intelligence has not been widespread in the field of medical care (Hanson, 2011) and research There are limited studies on how to successfully implement a sample business intelligence solution in the field of medical care (Foshay & Kuziemsky, 2014). This research tries to fill this gap by developing a model that provides maturity levels for evaluating and improving business intelligence solutions in healthcare. Therefore, considering the explanations and issues raised in the field of business intelligence, the present research seeks to answer a main question, what is the maturity model of business intelligence in the field of health care providers? In this regard, two sub-questions are also raised, which are: What are the indicators affecting the maturity model of business intelligence in the field of health care providers, and what is the prioritization of these factors?Literature ReviewAccording to the studies of Foshay and Kuziemsky, healthcare organizations are under constant pressure to not only achieve more results with fewer resources, but also to gradually transform into information-based systems (Foshay & Kuziemsky, 2014). Considering that the amount of information recorded by electronic health records and medical record centers is growing rapidly, healthcare organizations are trying to use tools such as business intelligence to improve the efficiency and effectiveness of their operations (Kuiler, 2014; Wang et al., 2018).According to the research conducted by Naqash, business intelligence solutions help decision-makers by providing practical information in the right format, at the right time and in the right place (Negash, 2004). The business intelligence market has grown significantly and has become the first investment priority for CIOs (Gartner, 2015). Also, the awareness of the potential benefits of business intelligence is increasing (Chuah & Wong, 2011), however, the implementation of business intelligence in health and treatment organizations is progressing relatively slowly and in a case-by-case manner (Foshay & Kuziemsky, 2014).Some studies show the benefits of business intelligence to improve patient care, treatment outcomes, effective use of human resources, lower costs (Borzekowski, 2009), higher revenue (Ayal & Seidman, 2009) and improved productivity (Lucas et al., 2010). have reported As reported in other studies, the successful implementation of business intelligence in healthcare depends on understanding and analyzing the characteristics of this field (Avison & Young, 2007; Mettler & Vimarlund, 2009). Therefore, one of the most important goals of this research is to provide a maturity model for the continuous development and improvement of business intelligence solutions to healthcare professionals. In Table (1), some business intelligence maturity models in the field of health care that have been implemented in the past are reviewed. Table 1. Some business intelligence maturity models in healthcareResearch resultsResearch researchersA framework for defining and prioritizing decision support information needs in the context of specific health care processes is presented.Foshay & Kuziemsky (2014)In this study, the subject of comprehensive business intelligence in special care and understanding the basic concepts of business intelligence solutions with comprehensive features have been discussed.Pereira et al. (2016)A way to identify the capabilities and weaknesses of the intelligent information system in the hospital has been presented.Carvalho et al. (2018)The methodology of implementing the model of hospital information systems is presented.Carvalho, Rocha, & Abreu (2019)This article identifies a wide range of maturity models in the health sector and its characteristics and strengthens the belief that the maturity of the hospital information system can contribute to the quality of information and knowledge management in this field.Gomes & Romão (2018)The result of this research is the maturity model of the hospital information system based on 6 stages of maturity. The hospital information system maturity model has the feature of collecting a set of key and effective factors of maturity and related characteristics and not only enables the evaluation of the overall maturity of a hospital information system, but also the individual maturity of its different dimensions.Carvalho, Rocha, Vasconcelos, et al. (2019)The purpose of this research is to determine how the existing business continuity maturity models conform to the ISO 22301 standard and to map the existing health care model with the business continuity maturity model.Haidzir et al. (2018)In this research, while determining organizational maturity levels, effective factors in improving maturity have been identified and prioritized, and a road map for applying business intelligence in this field has been presented.(Gastaldi et al. (2018)The result of this research is to present a maturity model including six stages of the growth and maturity sequence of the hospital information system.Carvalho, Rocha, Vasconcelos, et al. (2019)The importance of scientific research on business intelligence with a focus on patients has been investigated.Zheng et al. (2018)In this research, by providing a maturity assessment framework and infrastructure development based on results, information and digital transformation in health care has been encouraged and guided.Williams et al. (2019)In this research, it has been determined that organizational business intelligence application screens at all management levels have a positive and significant effect on measurable performance indicators. In this context, when businesses monitor their operational activities through business intelligence, they have come to the conclusion that performance indicators provide less time wastage, high reliability, integrated data, quality and accurate valuation benefits in the evaluation process.Işık et al. (2021)The relevant factors for the adoption of business intelligence system have been established using a systematic literature review and a theoretical structure based on technology, organization, environment and determinants and theories of CEOs. This research deepens the literature of business intelligence system and promotes the understanding of the important decision-making elements of business intelligence system.Salisu et al. (2021)The co-creation approach will optimize the currency, accuracy and appropriateness of information in the digital health profile, understanding and use of the digital health profile and the maturity assessment tool to facilitate informed iterative discussions by Pacific Island countries on digital health maturity in order to use digital tools to strengthen use the country's health systems. Digital health profile and maturity assessment tool can rationalize the selection and use of existing tools and reduce cognitive overload.Liaw et al. (2021)In this research, an alternative solution with the benefits and possible costs of its implementation in the hospital has been shown, and the proposed initial evaluation method can be used in different health and treatment units after confirming the weight of the criteria based on the adopted strategy.Wielki & Jurczyk (2019)The results of the study enrich the recent literature of business intelligence system and improve the understanding of the decision-making processes of practitioners to obtain the maximum value from the adoption of business intelligence system.Ahmad et al., (2020)The findings support the argument that the organizational learning culture plays an important role in the business intelligence system and also affects the business performance.Arefin et al., (2021)MethodologyTo implement business intelligence in the field of health care, the characteristics of this field must be understood and analyzed; This task has been carried out in three stages. First, the subject literature was analyzed with the "systematic review" method, and in addition to the field of health care, all sectors in which the maturity of business intelligence was evaluated were also considered. In the following, a series of key success factors of business intelligence and maturity components were extracted by examining more than 23 articles in the fields related to business intelligence and further, the steps of implementing the proposed method are also described.3.1. First stage - knowledge acquisitionAt this stage, previous studies in the field of business intelligence maturity model, evaluating the value of key success factors in business intelligence and identifying maturity components were reviewed. In this study, the structured search strategy method was used as data sources from Emerald, Sage, Elsevier, IEEE, Taylor & Francis, and Springer databases in the period from 2000 to the beginning of 2022. At first, this study used the following keywords and search terms, combined and separate: "business intelligence", "factors affecting business intelligence system", "business intelligence maturity", "maturity measurement" and "business intelligence system in health care". The collection of articles presented in this research was consistent with the topic of this research in terms of questions, objectives, adopted frameworks and findings. The definitions used and their alignment with the measurement adopted were evaluated, to ensure that the factors of business intelligence investigated by different researchers are largely similar. Finally, by advancing the previous steps, an initial version of the business intelligence maturity model was adopted, which is significantly different from the final business intelligence maturity model.3.2. The second stage - identifying and categorizing the criteriaAfter extracting the main criteria influencing the success of business intelligence in three areas of organization, process and technology, using the Delphi decision-making technique, the key factors and important criteria of business intelligence maturity in health care organizations were determined and categorized, and finally the maturity model of business intelligence in the field of health care, it was confirmed by a survey of experts.3.3. The third step - determining the criteriaAfter finalizing the dimensions and criteria of the research with the Delphi method, using pairwise comparisons and the Dimtel method based on the network analysis process method, the internal and external connections of the factors were determined and each of the factors were weighted and prioritized. In this step, a committee evaluation method was used to evaluate the validity of the questionnaire (Harkness & Schoua-Glusberg, 1998). In addition, ANP-DEMATEL combined method was used to evaluate how and how much the components affect each other. Various researchers such as (Đurek et al., 2019; Rasouli et al., 2021) have used this approach in the field of maturity model.ResultsIn this research, business intelligence was investigated in three basic areas of organization, process and technology, and each of these areas has criteria. First, articles were comprehensively reviewed in the field of business intelligence maturity in order to determine the dimensions of the goal and criteria. The criteria of the designed research maturity model were finalized using the Delphi method and with the opinion of experts, and then decision-making methods with multiple criteria were used to measure the optimality. The effects of goals, dimensions, and criteria on each other were investigated with the Dimtel method, then the dimensions and criteria were weighted in terms of importance with the network analysis process method. According to the results of Dimtel, the two dimensions of technology and process are effective, and the organizational dimension is effective. The organizational field has a higher relative importance than process and technology and has more interaction with other factors of the system and is affected by two dimensions of technology and process. The results of the analysis of the questionnaires of the network analysis process method answered by the experts show that the organizational factor is the most preferred and heaviest factor in the maturity of business intelligence, and then the process factor has a higher weight and the technology factor has a lower weight than the other two areas. In line with the results of William et al. (2019) and Gastaldi et al. (2018), who have encouraged and guided information and digital transformation in health care by providing a maturity assessment framework and infrastructure development based on results, respectively, two technical infrastructure criteria Flexible and expandable (hardware and software) and data and system quality were obtained from the highest importance compared to other criteria. And in the same way, the criterion of the correct definition of business intelligence problems and processes was prioritized with the third rank compared to other criteria in the maturity of business intelligence, and the rest of the criteria were also ranked in the article. Jayanthi Ranjan (2008) has also achieved this. In this way, a comprehensive and complete business intelligence maturity model was obtained in the field of health care, which can make the path of business intelligence maturity smoother in health care and be a road map for the successful implementation of business intelligence maturity in health care. It is suggested that in future researches, the proposed maturity model should be practically implemented in health care organizations and the maturity level of business intelligence should be evaluated. Figure 1. The final research model (source: researcher's findings)Organizational field• Cooperation between the employees of the organization and the information technology department• Alignment of business strategies with business intelligence strategies• Senior management support for the business intelligence project• Clear goals and vision for business intelligence• Development of business intelligence strategy• The ability of the organization to provide sufficient resources and funds needed for business intelligence projects• Risk-taking of senior managers in investing in new information technologies• Capabilities of the team/employees/managers• Monitor information through the Business Intelligence Assessment Center• Continuous improvement of organizational processes (improvement of competence)Technology field· Flexible and expandable technical infrastructure (hardware and software)· Data and system quality· Appropriate technology/tools or the use of appropriate technology and tools for hospital conditions· Business intelligence system architecture· Integration of business intelligence systems with other systems· Quality of data analysis· ConnectorBusiness intelligence in the field of health careProcess area• Correct definition of business intelligence problems and processes• Using patterns and repeatable methods in designing business intelligence projects• Aligning business intelligence solutions with user expectations• User training and support• Effective change management• Balanced and strong composition of the business intelligence project group• Project planning and management in the implementation of business intelligence• Measuring business intelligence• Decision makingKeywords: Business Intelligence, Healthcare, DEMATEL, ANP.
Management approaches in the field of smart
Developing a Framework for Evaluating the Digital Platform Economy
Mehdi Elyasi; Maghsoud Amiri; Seyed Soroush Ghazinoori; Neda Jomehri
Volume 12, Issue 45 , September 2023, , Pages 157-201
Abstract
The current digital revolution has given rise to a new organizational form, the Platform company. Today, the most valuable companies in the world and the first ones with a market value of more than a trillion dollars are platform companies. The Platform Economy is developing at an exponential rate and ... Read More The current digital revolution has given rise to a new organizational form, the Platform company. Today, the most valuable companies in the world and the first ones with a market value of more than a trillion dollars are platform companies. The Platform Economy is developing at an exponential rate and has become a top priority for governments across the world. The present study aims to provide a framework for evaluating the Digital Platform Economy at the international level. Utilizing a systematic review and meta-synthesis approach, the Platform Economy dimensions are identified as Digital Users, Digital Entrepreneurs, Digital Platforms, Digital Infrastructure, Innovation Capacity, and Institutional Environment and by extracting relevant indicators from international reports, the Platform Economy Composite Index is developed. Using the Partial Least Squares-Path Modelling (PLS-PM) method and specifically the Higher-Order Construct model, the measurement model is validated, and by employing a non-compensatory aggregation method, the Platform Economy Composite Index ranks 128 countries. The study is concluded by scrutinizing Iran’s current status regarding the enabling factors of the platform economy and identifying its strengths and weaknesses and providing recommendations for improvement. The results indicate that although Iran’s current status in terms of demand-side enablers is relatively good, it faces serious issues in terms of supply-side enablers.IntroductionThe emergence and proliferation of the application of big data, cloud computing and new algorithms have led to the formation of a platform economy built around platform companies. This new generation of digital businesses has disrupted several industries and often are startups that have become new market leaders (Acs et al., 2021).Companies like Apple, Microsoft, Google, Amazon, and Meta are examples of such businesses. The market value of these five companies was close to 9 trillion dollars in December 2021 (Companiesmarketcap, 2021), equivalent to 9.5% of the global GDP (O'Neill, 2021).The immense value creation power of the platform economy has made its the key to inclusive economic growth for both advanced and developing economies, and a catalyst for economic and social leapfrogging opportunities in developing countries (Chakravorti et al., 2019). However, platform economy literature has neglected the assessment of the national factors that have given rise to the platforms and therefore, it is necessary to identify the national factors that enable the emergence and growth of digital platforms (Hermes et al., 2020).However, a review of the research literature indicates that the evaluation of platform economy at the national level has not made much progress and the few studies that have attempted this (Chakravorti et al., 2019; Morvan et al., 2016), have been primarily focused on the developed countries and therefore are more compatible with the conditions of these countries. Consequently, policymakers in developing countries, despite having different conditions, must refer to the experiences of developed countries for the development of platform economy policies. Since there is a limited understanding of the effectiveness of such policies on enhancing the efficiency of the platform economy, this approach can be challenging (Szerb et al., 2022).Against this background, this study aims to develop a comprehensive framework for evaluating the platform economy of countries at different levels of development. Utilizing a systematic review and meta-synthesis approach, the enabling dimensions of the platform economy are identified as Digital Users, Digital Entrepreneurs, Digital Platforms, Digital Infrastructure, Innovation Capacity, and Institutional Environment. Based on this framework and by extracting relevant indicators from international reports, the Platform Economy Composite Index is constructed. The study concludes by closely examining Iran's current situation in terms of the enabling factors of the platform economy. It identifies the country's strengths and weaknesses and offers recommendations for improvement. Research Question(s)The main question of this research is defined as follows:What are the dimensions and components of a comprehensive framework for evaluating the platform economy and how can a composite index be developed using this framework?Literature ReviewDigital platforms serve as intermediaries that facilitate interactions and exchange of values between at least two different and interdependent user groups in platform ecosystems (Drewel et al., 2021).There is no consensus on the definition of the platform economy, and different terms such as Sharing Economy, Collaborative Economy, Access Economy, and Gig Economy have been used to refer to this phenomenon in academic and policy research (Riso, 2019). However, the term Platform Economy has gained more prevalence due to its more inclusive connotations. Kenney and Zysman (2016) consider the term Platform Economy a “more neutral term as they believe it encompasses a growing number of digitally enabled activities in business, politics, and social interaction”. Here, the platform economy is defined as a value creation system consisting of platforms and platform ecosystems (Dufva et al., 2017).A review of the research literature indicates that the evaluation of platform economy at the national level has not made much progress (Szerb et al., 2022), and the few studies that have evaluated the platform economy at the national level, have been primarily focused on developed economies e.g., Morvan et al. (2016) developed Platform Readiness Index to evaluate readiness level of 16 countries of G20 countries in the development of platforms. Furthermore, to the best of our knowledge there is no systematic review focused on the identification of platform economy enablers at the national level. Therefore, utilizing a systematic review and meta-synthesis approach, this study aims to develop a comprehensive framework for evaluating the platform economy of countries at different levels of development.MethodologyThe main steps for developing a composite index include developing a conceptual framework, selecting individual indicators, imputation of missing data, multivariate analysis, normalization, aggregation, and composite index validation (OECD, 2008).The first step of constructing a composite index is the development of a conceptual framework that encompasses the dimensions and components of the phenomenon being measured. To this end, based on a meta-synthesis approach, a systematic review was conducted. The meta-synthesis approach was implemented using the Noblit and Hare (1988) seven-step method: 1. getting started; 2. deciding what is relevant; 3. reading the studies; 4. determining how the studies are related; 5. translating the studies into one another; 6. synthesizing translations; 7. expressing the synthesis. This resulted in the extraction of 6 dimensions and 16 components as platform economy enablers which are presented in the proposed conceptual framework for the platform economy evaluation.Based on this framework and by extracting relevant indicators from international reports, the Platform Economy Composite Index is constructed. Using the Partial Least Squares-Path Modelling (PLS-PM) method and specifically the Higher-Order Construct model, the measurement model is validated, and by employing a non-compensatory aggregation method, the Platform Economy Composite Index ranks 128 countries.ConclusionThis study attempted to develop a comprehensive framework for evaluating the efficiency of the platform economy of countries at different levels of development. Using a systematic review and meta-synthesis approach, Digital Users, Digital Entrepreneurs, Digital Platforms, Digital Infrastructure, Innovation Capacity, and Institutional Environment were identified as the evaluating dimensions of the platform economy.Furthermore, Iran's current situation in terms of the enabling factors of the platform economy was closely examined and country's strengths and weaknesses were identified. The results from the Platform Economy Composite Index indicate that while Iran is in a relatively good position regarding demand-side enablers, it is facing significant challenges with supply-side enablers.Keywords: Digital Platform, Platform Economy, Composite Index, International Ranking.
Management approaches in the field of smart
Strategic Factors Affecting Banks' Cooperation with FinTechs
alireza rezanezhad kookhdan; peyman ghafari ashtiani; Mohammad Hasan Maleki; Majid Zanjirdar
Volume 12, Issue 45 , September 2023, , Pages 265-311
Abstract
Traditional banking needs new fintech innovations and technologies to improve its processes and services. Various factors affect the cooperation of banks and fintechs, some of which are related to banks and others to the banking environment.The purpose of this study is to identify and analyze the strategic ... Read More Traditional banking needs new fintech innovations and technologies to improve its processes and services. Various factors affect the cooperation of banks and fintechs, some of which are related to banks and others to the banking environment.The purpose of this study is to identify and analyze the strategic factors affecting the cooperation of banks and fintechs in Bank.The present study is applied in terms of orientation and has a quantitative nature in terms of methodology. Two methods of fuzzy Delphi and fuzzy dematel were used to analyze the data. The fuzzy Delphi method was used to screen the strategic factors of the research and the fuzzy dematel technique was used to identify the most effective factors. Two tools of interview and questionnaire were used to collect data. The research questionnaires were:Fuzzy Screening Questionnaire and effect analysis Questionnaire. Initially, through literature review and interviews with experts, 28 strategic factors were identified.These factors were screened by fuzzy Delphi technique.10 internal factors and eight external factors had a defuzzy number greater than 0.7 and were selected for analysis with fuzzy dematel.Analysis of internal factors with fuzzy dematel showed that the factors of the nature of the needs of the bank's customers,the future thinking of the bank's senior managers, the culture of risk-taking between managers and senior experts and the agility of the bank's structure and processes have the most net effect In relation to external factors, the factors of intensity of competition between banks, effective factors on the cooperation between banks and fintechs. IntroductionThe relationship with banks is not only beneficial for them but also brings threats and challenges. So, banks have resorted to using different strategies to deal with the possible threats of FinTechs, the most important of which is the formation of strategic partnerships. A strategic partnership is a cooperative arrangement between organizations, contributing to the competitive advantage of the parties. Some advantages of the strategic partnership between the banking system and FinTech are efficiency in speed, agility, cost, and attracting new customers. Some of the challenges faced by traditional banks are having complex structures, high level of formality, increasing operating costs, providing expensive and time-consuming banking services, lack of service innovation, and failure to meet customer expectations (Soltani and Tahmasebi Aghbolaghi, 2020). Through strategic partnerships with FinTechs, banks can overcome many of their inefficiencies.Most of the studies on banks and FinTechs have investigated the effects of financial innovations on the operational variables of banks, such as costs and performance. The challenges and opportunities of bank and FinTech partnerships have been evaluated by some studies. Moreover, some studies have extracted the patterns of bank and FinTech partnerships from the point of view of bank and fintech managers. Factors affecting the partnership between banks and FinTechs have been examined by a few studies. They obtained limited factors from the perspective of a few stakeholders. The strategic partnership between banks and FinTechs is affected by various factors, some of which are intra-organizational and some are extra-organizational. Accordingly, the study questions are as follows:What are the strategic factors affecting the partnership between banks and FinTechs?Which strategic factors have the most impact on the partnership between banks and FinTechs? Literature ReviewBy providing customer-oriented services, using Internet-based technologies, and facilitating the use of financial services, FinTechs have competed with traditional financial services (Suryono et al., 2021). FiTtechs offer more innovative, faster, and cheaper services than banks. On the other hand, banks have slower structures and processes than FinTechs. Many traditional institutions, such as banks, do not have a positive view of Fintechs (Romānova & Kudinska, 2016; Temelkov, 2018). However, the trend towards bank-FinTech partnerships has increased significantly recently (Buchak et al., 2018; Iman, 2019; Ky et al., 2019; Cole et al., 2019; Ya, 2020; Cheng & Qu, 2020; Saphyra & Zahra, 2021; Hoang et al., 2021). Banks and their managers have two important approaches to FinTechs. The first approach does not have a positive view of FinTechs, arguing that the risk of partnering with and investing in them is very high and that partnering with them can lead to various threats such as security risks. The second approach suggests that partnering with them, especially in research and development, can lead to the agility of banking structures and processes. Partnerships between banks and FinTechs can have various reasons, the main of which are reducing costs, increasing profitability, growing revenues, developing market share, reducing each other's risks, and providing optimal and unique services (Tahmasebi Aghbolaghi et al., 2021). Many studies have investigated the effects of FinTechs on banking indicators. Th These studies, which form an important part of the literature, aim to explain the effects and functions of FinTechs and their innovations in the banking sector. This relationship is accompanied by challenges such as regulatory (Buchak et al., 2018; Omarova, 2020), customer management (Suryono et al., 2020), security (Lee & Shin, 2018), integration and partnership (Phan et al., 2020), fee system (Koshesh Kordsholi et al., 2019), receiving international licenses (Payandeh et al., 2014; Koshesh Kordsholi et al., 2019), authentication and validation systems (Suryono et al., 2020), wallets (Agarwal & Zhang, 2020), and low financial literacy of users (Suryono et al., 2020). One of the most important challenges faced by FinTechs is the lack of effective and supportive laws. The laws enacted are mainly for the benefit of traditional institutions. They are mostly ambiguous and unpredictable. Banks and large financial institutions are reluctant to partner with FinTechs due to the ambiguity of laws and regulations. Materials and MethodsThis study was conducted to provide a framework for identifying and analyzing strategic factors affecting the partnership between banks and FinTechs. For this purpose, fuzzy Delphi and fuzzy DEMATEL techniques were used. These are quantitative techniques and use quantitative data for analysis. The fuzzy Delphi technique was used to screen the strategic factors of partnership between banks and FinTechs and the fuzzy DEMATEL technique was used to analyze the effectiveness of these factors. Since these techniques are quantitative, the study has multiple quantitative methodologies. Moreover, it is an applied study because of the benefit of its findings for the banking industry and FinTechs.The study was conducted in three steps. In the first step, the factors affecting the partnership between banks and FinTechs were extracted through a literature review and interviews with FinTech experts. In the next step, these factors were screened using the fuzzy Delphi technique. In the third step, the effectiveness of the screened factors was determined through the fuzzy DEMATEL technique. ConclusionThis study was conducted to identify and analyze the strategic factors affecting the partnership between banks and FinTechs. 28 factors were extracted through a literature review and expert interviews. 14 of the extracted factors were intra-organizational and the rest were extra-organizational. They were screened using the fuzzy Delphi technique, and 10 factors were eliminated. The intra-organizational and extra-organizational strategic factors were then analyzed separately through the fuzzy DEMATEL technique. Among the intra-organizational strategic factors, the nature of the needs of the bank's customers, the forward-thinking of the bank's senior managers, the culture of risk-taking among managers and senior experts, and the agility of the bank's structure and processes were the most effective, respectively. Among the extra-organizational strategic factors, the intensity of competition between banks, the fee system, the performance of the regulator in legislation, and the risks and security considerations concerning FinTechs, had a greater effect on the partnership between banks and FinTechs, respectively.Keywords: Financial Technology, FinTech, Banking Industry, Banking FinTechs, Fuzzy Approach.Traditional banking needs new fintech innovations and technologies to improve its processes and services. Various factors affect the cooperation of banks and fintechs, some of which are related to banks and others to the banking environment.The purpose of this study is to identify and analyze the strategic factors affecting the cooperation of banks and fintechs in Bank.The present study is applied in terms of orientation and has a quantitative nature in terms of methodology. Two methods of fuzzy Delphi and fuzzy dematel were used to analyze the data. The fuzzy Delphi method was used to screen the strategic factors of the research and the fuzzy dematel technique was used to identify the most effective factors. Two tools of interview and questionnaire were used to collect data. The research questionnaires were:Fuzzy Screening Questionnaire and effect analysis Questionnaire. Initially, through literature review and interviews with experts, 28 strategic factors were identified.These factors were screened by fuzzy Delphi technique.10 internal factors and eight external factors had a defuzzy number greater than 0.7 and were selected for analysis with fuzzy dematel.Analysis of internal factors with fuzzy dematel showed that the factors of the nature of the needs of the bank's customers,the future thinking of the bank's senior managers, the culture of risk-taking between managers and senior experts and the agility of the bank's structure and processes have the most net effect In relation to external factors, the factors of intensity of competition between banks, effective factors on the cooperation between banks and fintechs. IntroductionThe relationship with banks is not only beneficial for them but also brings threats and challenges. So, banks have resorted to using different strategies to deal with the possible threats of FinTechs, the most important of which is the formation of strategic partnerships. A strategic partnership is a cooperative arrangement between organizations, contributing to the competitive advantage of the parties. Some advantages of the strategic partnership between the banking system and FinTech are efficiency in speed, agility, cost, and attracting new customers. Some of the challenges faced by traditional banks are having complex structures, high level of formality, increasing operating costs, providing expensive and time-consuming banking services, lack of service innovation, and failure to meet customer expectations (Soltani and Tahmasebi Aghbolaghi, 2020). Through strategic partnerships with FinTechs, banks can overcome many of their inefficiencies.Most of the studies on banks and FinTechs have investigated the effects of financial innovations on the operational variables of banks, such as costs and performance. The challenges and opportunities of bank and FinTech partnerships have been evaluated by some studies. Moreover, some studies have extracted the patterns of bank and FinTech partnerships from the point of view of bank and fintech managers. Factors affecting the partnership between banks and FinTechs have been examined by a few studies. They obtained limited factors from the perspective of a few stakeholders. The strategic partnership between banks and FinTechs is affected by various factors, some of which are intra-organizational and some are extra-organizational. Accordingly, the study questions are as follows:What are the strategic factors affecting the partnership between banks and FinTechs?Which strategic factors have the most impact on the partnership between banks and FinTechs? Literature ReviewBy providing customer-oriented services, using Internet-based technologies, and facilitating the use of financial services, FinTechs have competed with traditional financial services (Suryono et al., 2021). FiTtechs offer more innovative, faster, and cheaper services than banks. On the other hand, banks have slower structures and processes than FinTechs. Many traditional institutions, such as banks, do not have a positive view of Fintechs (Romānova & Kudinska, 2016; Temelkov, 2018). However, the trend towards bank-FinTech partnerships has increased significantly recently (Buchak et al., 2018; Iman, 2019; Ky et al., 2019; Cole et al., 2019; Ya, 2020; Cheng & Qu, 2020; Saphyra & Zahra, 2021; Hoang et al., 2021). Banks and their managers have two important approaches to FinTechs. The first approach does not have a positive view of FinTechs, arguing that the risk of partnering with and investing in them is very high and that partnering with them can lead to various threats such as security risks. The second approach suggests that partnering with them, especially in research and development, can lead to the agility of banking structures and processes. Partnerships between banks and FinTechs can have various reasons, the main of which are reducing costs, increasing profitability, growing revenues, developing market share, reducing each other's risks, and providing optimal and unique services (Tahmasebi Aghbolaghi et al., 2021). Many studies have investigated the effects of FinTechs on banking indicators. Th These studies, which form an important part of the literature, aim to explain the effects and functions of FinTechs and their innovations in the banking sector. This relationship is accompanied by challenges such as regulatory (Buchak et al., 2018; Omarova, 2020), customer management (Suryono et al., 2020), security (Lee & Shin, 2018), integration and partnership (Phan et al., 2020), fee system (Koshesh Kordsholi et al., 2019), receiving international licenses (Payandeh et al., 2014; Koshesh Kordsholi et al., 2019), authentication and validation systems (Suryono et al., 2020), wallets (Agarwal & Zhang, 2020), and low financial literacy of users (Suryono et al., 2020). One of the most important challenges faced by FinTechs is the lack of effective and supportive laws. The laws enacted are mainly for the benefit of traditional institutions. They are mostly ambiguous and unpredictable. Banks and large financial institutions are reluctant to partner with FinTechs due to the ambiguity of laws and regulations. Materials and MethodsThis study was conducted to provide a framework for identifying and analyzing strategic factors affecting the partnership between banks and FinTechs. For this purpose, fuzzy Delphi and fuzzy DEMATEL techniques were used. These are quantitative techniques and use quantitative data for analysis. The fuzzy Delphi technique was used to screen the strategic factors of partnership between banks and FinTechs and the fuzzy DEMATEL technique was used to analyze the effectiveness of these factors. Since these techniques are quantitative, the study has multiple quantitative methodologies. Moreover, it is an applied study because of the benefit of its findings for the banking industry and FinTechs.The study was conducted in three steps. In the first step, the factors affecting the partnership between banks and FinTechs were extracted through a literature review and interviews with FinTech experts. In the next step, these factors were screened using the fuzzy Delphi technique. In the third step, the effectiveness of the screened factors was determined through the fuzzy DEMATEL technique. ConclusionThis study was conducted to identify and analyze the strategic factors affecting the partnership between banks and FinTechs. 28 factors were extracted through a literature review and expert interviews. 14 of the extracted factors were intra-organizational and the rest were extra-organizational. They were screened using the fuzzy Delphi technique, and 10 factors were eliminated. The intra-organizational and extra-organizational strategic factors were then analyzed separately through the fuzzy DEMATEL technique. Among the intra-organizational strategic factors, the nature of the needs of the bank's customers, the forward-thinking of the bank's senior managers, the culture of risk-taking among managers and senior experts, and the agility of the bank's structure and processes were the most effective, respectively. Among the extra-organizational strategic factors, the intensity of competition between banks, the fee system, the performance of the regulator in legislation, and the risks and security considerations concerning FinTechs, had a greater effect on the partnership between banks and FinTechs, respectively.Keywords: Financial Technology, FinTech, Banking Industry, Banking FinTechs, Fuzzy Approach.
Management approaches in the field of smart
Providing Agent-based Conceptual Model for the Hospital Evaluation and Accreditation System
Javad Keshvari Kamran; Mohammad ali Keramati; Abbas Toloie Eshlaghy; Seyed Abdollah Amin Mousavi
Volume 12, Issue 45 , September 2023, , Pages 347-389
Abstract
The aims of this study is to provide a conceptual model of hospital accreditation in Iran through qualitative research. The grounded theory model was compiled using the results of the analysis of the interviews. Then, with the help of the grounded theory model and the results of qualitative analysis, ... Read More The aims of this study is to provide a conceptual model of hospital accreditation in Iran through qualitative research. The grounded theory model was compiled using the results of the analysis of the interviews. Then, with the help of the grounded theory model and the results of qualitative analysis, a state diagram was obtained. Using the state diagram, initial sampling, systematic review of sources and results of interviews, 9 conceptual agents "governance organizations, management and leadership, clinical personnel, support personnel, hospital infrastructure, assessor, standards, assessment method and service recipient" were identified. Finally, the conceptual model of agent-based, environment, behavioral rules of agents and their input and output interactions was presented. In future researches, reinforcement learning models can be designed according to the conceptual model of this study, so that by using it, software developers can develop a suitable framework for solving complex problems in the field of hospital accreditation. Because the field of hospital management systems is one of the desirable types of socio-technical systems that have high capacities.IntroductionThe ecosystem of hospital accreditation is a triangle with “standard, accreditation method, and accreditation assessors” sides (Mosadeghrad et al.,2017). Hospital accreditation in Iran has faced challenges, the most important of which are: “a large number of standards and measures, lack of transparency and ambiguity in the measures, incompleteness and defects in the standards and high emphasis on structure and documentation, lack of systemic thinking and following that, a lot of focus on the sectoral approach” (Mosadeghrad & Ghazanfari, 2020). The results of a systematic review of sources and documents indicate that as a result of the lack of new approaches to solving “social-technical” problems such as “use of agent-based systems”, the above-mentioned challenges have become more prominent and ultimately cause the credibility and ranking of hospitals to become unrealistic (Ghazanfari et al., 2021). This study aims to present new models such as the agent-based conceptual model in Iran's hospital accreditation system. This model will create a study foundation for the environmental simulation process and the creation of a multi-agent hospital accreditation system to provide useful guidelines to the relevant policymakers.Therefore, it seems that the result of the current research covers the research gap in this field to some extent. Also, this study aims to answer the main research question; “What are the rules, position, behavior, and relationships of each of the agents in the multi-agent hospital accreditation system and how are they formulated?” It has started working.Literature ReviewHospital accreditationHospital accreditation is the process of systematic evaluation and determination of hospital credit by an external organization using the desired structural, process, and outcome standards (Chehrzad et al., 2019).Figure 1. The main elements of the hospital accreditation system, Source: (Mosadeghrad & Ghazanfari, 2021) Figure 1 shows the main elements of the hospital accreditation system. The hospital accreditation system is a triangle that includes the sides of “standard, accreditation method, and accreditation assessors”. The governance element is the regulator and controller of the sides of this triangle.Agent-based systemsThe agent-based system can be used to solve problems that are difficult or impossible to solve for a “single agent” or an integrated system. Agent-based systems provide new methods for solving complex computing problems and implementing social-technical software projects (Dorri et al.., 2018). The elements of agent-based systems are: “environment, objects, a set of agents, a set of relationships, and a set of agent behaviors” (Bonabeau, 2002).Research backgroundTable 1 shows the summary report of the background of the most important research conducted in the fields of hospital accreditation and agent-based models.Table 1. Summary report of the background of the researchSummary of study resultsResearcherA comprehensive hospital accreditation model was developed and validated. Paying attention to structures, processes, outcomes, and systemic thinking during model development is one of the advantages of this study.(Mosadeghrad & Ghazanfari, 2021)The challenges of hospital accreditation standards were categorized into two groups: standards development process and standards content.(Ghazanfari et al., 2021)The identified agents describe the consumer's impulse buying behavior as an economic analysis based on the relationship between the customer and the product.(Abbasi Siar et al., 2022)The multi-agent model and process simulations provide useful information for generating strategies to reduce the risks of COVID-19 transmission inside the facility.(Cuevas, 2020)The results of the agent-based simulation show the advantages of the proposed model for reducing the response time to requests compared to the current maintenance system.(Yousefli et al., 2020)The proposed model of pre-hospital management operation was presented. The identified agents are: “Management Center, Ambulance, Traffic Station, Medical Service Provider, Patient, Counseling Center, National Medical Record System, and Service Quality Monitoring”.(Safdari et al., 2017)MethodologyTo collect data, library and field methods have been used. Using qualitative analysis and obtained results, conceptual models were created. Therefore, the approach of this research is of a hybrid type. Also, the snowball sampling method was used to collect the required information. By using primary sampling, agents, the environment, and their relationships were extracted. By conducting six interviews, theoretical saturation was achieved regarding the conceptual model. To collect the information needed to know the elements and processes, a systematic review of sources and semi-structured interviews were used. The interviewees were selected from among the professors, managers, and employees of the hospitals. Finally, the interviews were summarized using grounded-theory-based methods, approaches, and systematic approaches. To calculate the reliability of the interviews, the method of two inter-coder agreements was used. Finally, the fuzzy Delphi method with triangular fuzzy numbers was used to validate the extracted conceptual model. ResultsConceptual model of the agent-basedUsing the results obtained from qualitative data analysis and the grounded theory model, examples and independent agents of each agent group were identified. All the interactions of the agents are included in the final model in the form of input and output. Figure 2 shows the agent-based conceptual model of the hospital accreditation system.Figure 2. Conceptual model of the agent-based hospital accreditation system (source: findings of the present research) DiscussionThis study aimed to provide a conceptual model of the agent-based system in Iran's hospital accreditation system. Also, agents, the environment, general behavioral rules, and their interactions with the environment were obtained. Because, so far, a lot of research has been conducted to provide an optimal model in the hospital accreditation ecosystem, there have been no studies that have new methods such as agent-based design. Therefore, it seems that the findings of the current research have covered some research gaps in this field because agent-based design is one of the newest and most efficient solutions available for solving distributed problems and complex human processes and environments. The agent-based conceptual model of the current research can create a suitable study base for the environmental simulation process and the creation of a multi-agent hospital accreditation system. Also, future researchers are suggested to carry out relevant research in this field, considering the wide application of agent-based modeling in the field of social-technical hospital systems and the importance of using reinforcement learning algorithms in them.ConclusionThe background analysis of the research was done with the method of systematic review of sources. Using experts' opinions, broad and general questions were asked about the results of the research, and then their description and analysis were addressed through grounded theory-based tools (MAXQDA), and a conceptual model of the grounded theory was obtained. Then, to the main research question; “What are the rules, position, behavior, and relationships of each of the agents in the multi-agent hospital accreditation system and how are they formulated?” The appropriate answer was given so that by using qualitative analysis, the dimensions of the problem were fully understood and the obtained results were converted into the final conceptual model. Also, agents, the environment, and their relationships were obtained. Then their general rules of conduct were compiled. All interactions of the agents with the environment were included in the model as input and output.Keywords: Agent-Based Conceptual Model, Hospital Accreditation, Multi-Agent System, Simulation.The aims of this study is to provide a conceptual model of hospital accreditation in Iran through qualitative research. The grounded theory model was compiled using the results of the analysis of the interviews. Then, with the help of the grounded theory model and the results of qualitative analysis, a state diagram was obtained. Using the state diagram, initial sampling, systematic review of sources and results of interviews, 9 conceptual agents "governance organizations, management and leadership, clinical personnel, support personnel, hospital infrastructure, assessor, standards, assessment method and service recipient" were identified. Finally, the conceptual model of agent-based, environment, behavioral rules of agents and their input and output interactions was presented. In future researches, reinforcement learning models can be designed according to the conceptual model of this study, so that by using it, software developers can develop a suitable framework for solving complex problems in the field of hospital accreditation. Because the field of hospital management systems is one of the desirable types of socio-technical systems that have high capacities.IntroductionThe ecosystem of hospital accreditation is a triangle with “standard, accreditation method, and accreditation assessors” sides (Mosadeghrad et al.,2017). Hospital accreditation in Iran has faced challenges, the most important of which are: “a large number of standards and measures, lack of transparency and ambiguity in the measures, incompleteness and defects in the standards and high emphasis on structure and documentation, lack of systemic thinking and following that, a lot of focus on the sectoral approach” (Mosadeghrad & Ghazanfari, 2020). The results of a systematic review of sources and documents indicate that as a result of the lack of new approaches to solving “social-technical” problems such as “use of agent-based systems”, the above-mentioned challenges have become more prominent and ultimately cause the credibility and ranking of hospitals to become unrealistic (Ghazanfari et al., 2021). This study aims to present new models such as the agent-based conceptual model in Iran's hospital accreditation system. This model will create a study foundation for the environmental simulation process and the creation of a multi-agent hospital accreditation system to provide useful guidelines to the relevant policymakers.Therefore, it seems that the result of the current research covers the research gap in this field to some extent. Also, this study aims to answer the main research question; “What are the rules, position, behavior, and relationships of each of the agents in the multi-agent hospital accreditation system and how are they formulated?” It has started working.Literature ReviewHospital accreditationHospital accreditation is the process of systematic evaluation and determination of hospital credit by an external organization using the desired structural, process, and outcome standards (Chehrzad et al., 2019).Figure 1. The main elements of the hospital accreditation system, Source: (Mosadeghrad & Ghazanfari, 2021) Figure 1 shows the main elements of the hospital accreditation system. The hospital accreditation system is a triangle that includes the sides of “standard, accreditation method, and accreditation assessors”. The governance element is the regulator and controller of the sides of this triangle.Agent-based systemsThe agent-based system can be used to solve problems that are difficult or impossible to solve for a “single agent” or an integrated system. Agent-based systems provide new methods for solving complex computing problems and implementing social-technical software projects (Dorri et al.., 2018). The elements of agent-based systems are: “environment, objects, a set of agents, a set of relationships, and a set of agent behaviors” (Bonabeau, 2002).Research backgroundTable 1 shows the summary report of the background of the most important research conducted in the fields of hospital accreditation and agent-based models.Table 1. Summary report of the background of the researchSummary of study resultsResearcherA comprehensive hospital accreditation model was developed and validated. Paying attention to structures, processes, outcomes, and systemic thinking during model development is one of the advantages of this study.(Mosadeghrad & Ghazanfari, 2021)The challenges of hospital accreditation standards were categorized into two groups: standards development process and standards content.(Ghazanfari et al., 2021)The identified agents describe the consumer's impulse buying behavior as an economic analysis based on the relationship between the customer and the product.(Abbasi Siar et al., 2022)The multi-agent model and process simulations provide useful information for generating strategies to reduce the risks of COVID-19 transmission inside the facility.(Cuevas, 2020)The results of the agent-based simulation show the advantages of the proposed model for reducing the response time to requests compared to the current maintenance system.(Yousefli et al., 2020)The proposed model of pre-hospital management operation was presented. The identified agents are: “Management Center, Ambulance, Traffic Station, Medical Service Provider, Patient, Counseling Center, National Medical Record System, and Service Quality Monitoring”.(Safdari et al., 2017)MethodologyTo collect data, library and field methods have been used. Using qualitative analysis and obtained results, conceptual models were created. Therefore, the approach of this research is of a hybrid type. Also, the snowball sampling method was used to collect the required information. By using primary sampling, agents, the environment, and their relationships were extracted. By conducting six interviews, theoretical saturation was achieved regarding the conceptual model. To collect the information needed to know the elements and processes, a systematic review of sources and semi-structured interviews were used. The interviewees were selected from among the professors, managers, and employees of the hospitals. Finally, the interviews were summarized using grounded-theory-based methods, approaches, and systematic approaches. To calculate the reliability of the interviews, the method of two inter-coder agreements was used. Finally, the fuzzy Delphi method with triangular fuzzy numbers was used to validate the extracted conceptual model. ResultsConceptual model of the agent-basedUsing the results obtained from qualitative data analysis and the grounded theory model, examples and independent agents of each agent group were identified. All the interactions of the agents are included in the final model in the form of input and output. Figure 2 shows the agent-based conceptual model of the hospital accreditation system.Figure 2. Conceptual model of the agent-based hospital accreditation system (source: findings of the present research) DiscussionThis study aimed to provide a conceptual model of the agent-based system in Iran's hospital accreditation system. Also, agents, the environment, general behavioral rules, and their interactions with the environment were obtained. Because, so far, a lot of research has been conducted to provide an optimal model in the hospital accreditation ecosystem, there have been no studies that have new methods such as agent-based design. Therefore, it seems that the findings of the current research have covered some research gaps in this field because agent-based design is one of the newest and most efficient solutions available for solving distributed problems and complex human processes and environments. The agent-based conceptual model of the current research can create a suitable study base for the environmental simulation process and the creation of a multi-agent hospital accreditation system. Also, future researchers are suggested to carry out relevant research in this field, considering the wide application of agent-based modeling in the field of social-technical hospital systems and the importance of using reinforcement learning algorithms in them.ConclusionThe background analysis of the research was done with the method of systematic review of sources. Using experts' opinions, broad and general questions were asked about the results of the research, and then their description and analysis were addressed through grounded theory-based tools (MAXQDA), and a conceptual model of the grounded theory was obtained. Then, to the main research question; “What are the rules, position, behavior, and relationships of each of the agents in the multi-agent hospital accreditation system and how are they formulated?” The appropriate answer was given so that by using qualitative analysis, the dimensions of the problem were fully understood and the obtained results were converted into the final conceptual model. Also, agents, the environment, and their relationships were obtained. Then their general rules of conduct were compiled. All interactions of the agents with the environment were included in the model as input and output.Keywords: Agent-Based Conceptual Model, Hospital Accreditation, Multi-Agent System, Simulation.vv
Management approaches in the field of smart
Development of the archetype for data marketplace platforms' business model
Fatemeh Mohammadnezhad Chari; Jahanyar Bamdadsoofi; Iman Raeisi Vanani; Maghsoud Amiri
Volume 11, Issue 44 , March 2023, , Pages 145-189
Abstract
The present paper is conducted through exploratory and inductive approach in order to achieve a business model for data marketplaces. The research paper could be considered as a first attempt in the field of data marketplaces and their business models in Iran. The paper is based on two iterative taxonomy ... Read More The present paper is conducted through exploratory and inductive approach in order to achieve a business model for data marketplaces. The research paper could be considered as a first attempt in the field of data marketplaces and their business models in Iran. The paper is based on two iterative taxonomy approach that is first introduced by Nickerson et al.(2013).Mixing of a systematic way on current literatures along with structured interviews by some experts who are involved in this area is applied to gain the main objectives.Our results provide the main bloc of the presented archetype with three sub blocs ،attributes and specifications that is titled value proposition. The sub blocs are named value creation، value capture and value delivery. Introduction Recently many online data trading platforms have emerged as a new business paradigm to respond to society’s fundamental needs and rights for specific data. On these data marketplaces, service providers buy raw data from device and application owners or collect it from contributors to offer enriched and value-added data to data consumers such as scientists, businesses, etc. The aim of this study is to develop an architecture of business model for data marketplaces in order to get better a understanding of their business logic. Hence, the research questions are as follows: 1-What are the attributes of construct blocs of the data marketplace business model? 2- What are the specifications of each attribute in any construct bloc of data marketplace business model? Literature Review The concept of business model has evolved during recent years by refining its components. There are different types of business model constructs across the literature, from 9 blocs of Osterwalder and Pigneur (2010) to the business model with 3 blocs proposed by “Hautes Etudes Commerciales de Paris” called Odyssey 3.14. The most famous business model construct includes four components (blocs) with “value proposition” as a core component which refers to the benefits that customers receive and why the company is the best choice for them. (Magretta, 2002; Casadesus et al.,2010). The three sub-constructs include “value creation”, “value delivery”, and “value capture” (Teece, 2010). “Value creation” reflects the products and services offered by the company and also the key activities, resources and processes, and partners. “Value delivery” refers to the corporate interactions with the market and “Value capture” concerns the revenue streams and cost structures which make the profit equation. Methodology: The present study is conducted through exploratory and inductive approach to achieve an archetype of a business model for data marketplaces. To the best of our knowledge, this research paper could be considered a first attempt in the field of data marketplaces business model design in Iran. The methodological orientation of this research is based on two iterative taxonomy approaches that is first introduced by Nickerson et., al (2013). Mixing of a systematic way on current works of literature along with structured interviews by some experts who are involved in this area is applied to gain the main objective and answer the research questions. Through this approach, three following steps are taken in a systematic and repetitive manner. Systematic literature review of 43 scientific documents and their content analysis Conducting structured interviews with 5 experts Visiting 4 online data platforms and data marketplaces websites Results and discussion: Findings indicate that the data marketplace business model archetype consists of “value proposition” as a main component with 8 attributes including data goods, technological products, infrastructural services, brokery and curation services, operating services, supporting services, the domain of activities, and proprietary forms. The three sub-components’ attributes concerning the data marketplace business model are figured out as follows: “Value creation” as a sub-construct with six attributes including key partners, key activities, key processes, key products and services, transaction orientations, data sourcing and data origin, and data time -frame. “Value delivery” as a second sub-component includes five attributes such as data accessibility, output frames, target audiences, trustworthy mechanisms, and privacy preservation mechanisms. “Value capture” with five attributes including price discovery mechanisms, payment mechanisms, revenue streams, costing mechanisms, and pricing models. To sum up, these 24 attributes include more than 100 specifications. All of these specifications are profoundly described in detail across the article. Some attributes have more than 8 specifications such as key partners, key activities, or key processes while others have fewer. Most of the specifications are not exclusive, since a particular platform’s attributes may include one or multiple specifications. For example, a particular data platform could have multiple pricing models such as “pay-per-use”, “freemium” or “flat rate”. Conclusion Our taxonomy of the data marketplace business model could be extended by four major concerns of data platforms which are data quality evaluation, data pricing mechanisms, secure data trading and truthfulness, and privacy protection mechanisms. Some aspects of the data marketplace business model are inherently contradictory and a trade-off has to be applied between them. For example, European General Data Protection Regulation (GDPR) tries to make a trade-off between data trading transparency and individual privacy protection. Furthermore, participants’ conflicting interests in order to gain a win-win result have to be considered in all online data platform business models. We suggest future researchers in computer science and IT management science, and data scientists extend our archetype by using methods such as text mining techniques and web crawling. Keywords: Data Marketplace, Business Model, Archetype, Taxonomy.
Management approaches in the field of smart
Designing a Model for the Impact of Innovation on the Market Performance of Online Shopping Websites with a Narrative Analysis Approach
Sahar Masah Choolabi; Kambiz Shahroodi; Narges Delafrooz; Yalda Rahmati
Volume 11, Issue 44 , March 2023, , Pages 259-287