Management approaches in the field of smart
Peyman Ghafari Ashtiani; Maryam Ghiasaadi Farahani
Abstract
The current research has identified the factors affecting the management and organization of businesses based on e-commerce through a meta-combination approach. The research is applied in terms of purpose and qualitative in nature with an exploratory approach. The community of this research is the articles ...
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The current research has identified the factors affecting the management and organization of businesses based on e-commerce through a meta-combination approach. The research is applied in terms of purpose and qualitative in nature with an exploratory approach. The community of this research is the articles in the field of managing and organizing e-commerce jointly or separately. The method of collecting information is the document-library method with the efficiency of the meta-combination method for extracting factors. The sampling method is also selected based on the entry and exit criteria of the prism method. In order to answer the research questions, 96 articles were examined and analyzed, which led to the extraction of 15 categories and 95 meaningful codes. The results showed that business management based on e-commerce includes the components of online sales, digital marketing, suppliers, leadership, product or service, human resources, organizational culture, customer, market, organizational structure, and organizing business based on E-commerce includes the components of technical dimension, organizational dimension, environmental dimension, economic dimension and financial dimension.
Data, information and knowledge management in the field of smart business
Nahid Entezarian; Mohammad Mehraeen
Abstract
New technologies in the field of Industry 4.0 enable companies to enhance their business processes and customize products and services through the generation of new knowledge. The creation and sharing of this new knowledge depends on both the optimal use of Industry 4.0 technologies and interactions ...
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New technologies in the field of Industry 4.0 enable companies to enhance their business processes and customize products and services through the generation of new knowledge. The creation and sharing of this new knowledge depends on both the optimal use of Industry 4.0 technologies and interactions along the value chain. However, achieving business benefits is highly dependent on human resources and their digital skills and competencies. Therefore, companies approaching the Industry 4.0 paradigm should consider these new technologies as tools that facilitate the creation and sharing of new knowledge. They should pay attention to the digital skills and competencies required to manage this technological transformation and enhance internal competencies. The purpose of this research is to combine the results and findings obtained from qualitative studies, providing new insights from previous research. In this study, a meta-composite approach was used to investigate qualitative case studies, examining the relationship between knowledge management and Industry 4.0 capabilities in organizations. The results show that knowledge management capabilities in the field of Industry 4.0 are examined in two dimensions: business models and organizational innovation. This research also emphasizes that in order to address organizational challenges, knowledge management strategies and the maturity level of Industry 4.0 technologies within organizations must be understood.IntroductionIndustry 4.0, driven by digital technologies such as smart sensors, IoT, cloud computing, big data, and AI, holds significant importance in the realm of organizational knowledge management. It enables convenient access to vast repositories of data that can be meticulously scrutinized to drive improvements in processes. Moreover, Industry 4.0 seamlessly merges the physical and virtual domains, thereby enhancing both production processes and resulting products (Wilkesmann, 2018). This study endeavors to propose a model that seamlessly integrates knowledge management and Industry 4.0 to gain a competitive advantage. The researchers will utilize the Meta-synthesis method to identify capabilities and develop a new framework, thus contributing to a deeper understanding in this field.Literature ReviewThe theoretical foundations are categorized into two components: Industry 4.0 and knowledge management.2.1. Industry 4.0Industry 4.0 emerged in 2011 as the fourth industrial revolution, focusing on fully automated and intelligent production systems. It involves the integration of production systems through real-time information exchange and flexible production. The internet and related technologies play a crucial role in connecting physical objects, machines, and processes across organizations (Ghobakhloo, 2018). Industry 4.0 relies on data-driven decision-making and recognizes the value of real-time data utilization. It disrupts traditional competition and impacts various aspects of organizational strategy, business models, innovation, supply chains, production processes, and stakeholder relationships (Pozzi et al., 2023).2.2. Knowledge management strategies and approaches in Industry4.0Knowledge is essential for decision-making in implementing Industry 4.0 technologies. Industry 4.0 significantly influences knowledge management within organizations. These technologies facilitate knowledge management by enhancing existing knowledge and generating new knowledge. Knowledge sharing and storage are key components of knowledge management in the context of Industry 4.0 (Salvadorinho & Teixeira, 2021). The cost-effective and high-performance nature of Industry 4.0 technologies makes them suitable for storing and sharing knowledge. Industry 4.0 technologies enhance value creation through knowledge sharing within organizations and enable organizational innovation and competitive advantage maximization through knowledge management (Gupta et al., 2022).MethodologyThis research proposes Meta-synthesis as a suitable method for effectively combining the various factors involved in knowledge management capabilities and Industry 4.0 technologies within organizations. Meta-synthesis serves as a valuable instrument in formulating a comprehensive theory by systematically amalgamating these elements. The selection of the Hoon model (Hoon, 2013) for this research is based on its comprehensive and innovative nature in comparison to other Meta-synthesis models. It is characterized as an exploratory and inductive research design that integrates qualitative case studies to extend the findings of the original studies. Hoon's proposed Metasynthesis entails eight specific steps, which are briefly outlined below:Step 1 involves designing and framing the research question related to knowledge management capabilities in Industry 4.0. Step 2 includes searching for articles using specific keywords and selecting relevant research. Step 3 involves screening and selecting suitable texts based on inclusion criteria. Step 4 entails extracting and coding evidence from selected studies. Step 5 analyzes individual studies using a causal network technique. Step 6 synthesizes findings on an across-study level. Step 7 involves building theory from meta-synthesis.Results and DiscussionThe convergence of Industry 4.0 and knowledge management within organizational frameworks serves to amplify the influence of knowledge management on the performance of organizational innovation (Tortorella et al., 2022). This study furnishes valuable perspectives for formulating an adoption strategy and prioritizing tasks in the integration of Industry 4.0. It underscores the significance of knowledge dissemination in expediting the assimilation of Industry 4.0 and recommends a focus on cultivating affiliations with strategic counterparts. The development of internal capabilities and competencies stands as pivotal for meaningful engagement in knowledge dissemination for Industry 4.0. Effective knowledge exchange among organizations can offset the dearth of internal resources and knowledge during the adoption process. This study accentuates the cost-effectiveness of knowledge sharing as an alternative to external consultants. In sum, it furnishes invaluable insights for managers seeking to augment organizational innovation, fortify stakeholder associations, and attain a competitive edge in the landscape of Industry 4.0.ConclusionThe Meta-synthesis approach used in this study has limitations, including a smaller sample size of only 8 studies, which raises concerns about the generalizability of the findings. The reliance on a limited number of keywords for searching and identifying studies is another limitation. However, the study's analysis revealed similarities among the chosen articles, and the selection process followed the criteria set by Hoon (2013). The Meta-synthesis protocol allows for the development of causal networks, meta-causal network, and case comparison table, showing a wider context of knowledge management and Industry 4.0 capabilities in organizations. Future studies should encompass a wider scope, as organizations in the Industry 4.0 environment need to share and manage knowledge both internally and externally. The Meta causal network developed in this study can be used as a foundation for developing strategies that generate value and foster a competitive advantage in the realm of Industry 4.0.Keywords: Knowledge Management, Industry 4.0, Meta-Synthesis, Case Study.Figure 1. Meta-causal network of selected analyzed studies (research findings)
Data, information and knowledge management in the field of smart business
seyed rasoul hoseini; sahel Farokhian; Hadi Taghavi
Abstract
IntroductionCurrent global statistics indicate that 80% of startups fail within a short period, with one of the primary reasons being weak branding strategies. Startups often lack precise knowledge of branding, which increases the risk of failure. To reduce this risk, marketers need a phenomenon called ...
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IntroductionCurrent global statistics indicate that 80% of startups fail within a short period, with one of the primary reasons being weak branding strategies. Startups often lack precise knowledge of branding, which increases the risk of failure. To reduce this risk, marketers need a phenomenon called co-creation branding.Branding in startups can increase access to suppliers, customer purchases, and innovative business models (Drakoulis & Lipovsek, 2015). Despite these advantages, startups face challenges such as gaining consumer trust, creating demand for their products and services, establishing an identity, and providing unique and differentiated value to consumers (Sonja et al., 2022). Therefore, to reduce these challenges and the risk of failure, marketers need co-creation branding in startups (Bonamigo et al., 2022). Co-creation branding involves active customer and company participation and interaction to improve brand image, increase brand value and awareness, and ultimately increase customer loyalty, achieving a competitive position in the market (Dehdashti Shahrokh et al., 2022).Unfortunately, very few studies have been conducted on both co-creation branding and startups, and extensive research is needed (Wong & Merrilees, 2005; Lagerstedt & Mademlis, 2016). Therefore, this research aims to identify the factors affecting on co-creation branding in startups. The main question of this research is defined as follows: What are the factors affecting on co-creation branding in startups?Literature ReviewThe literature review of startups offers various definitions for the term. For instance, Avnimelech and Teubal (2006) define startups as young companies with advanced technology whose primary activity, from idea to initial sales, lasts between one to five years.Brand co-creation is a recent trend in branding (Hatch & Schultz, 2010), which is largely based on the dominant logic of service (Vargo & Lusch, 2008) and co-creation of value (Prahalad & Ramaswamy, 2004), starting with the identification of customer value creation processes (Juntunen, 2012). Co-creation leads to offering more suitable products and services to consumers and encouraging their participation (Nadeem et al., 2020). The theory of brand co-creation assumes that the consumer is no longer a passive brand buyer but desires and seeks active participation in creating brand experiences (Kamboj et al., 2018), and therefore, customers can play a vital role in determining the success of brands. Brand co-creation begins with the relationship between shareholders and customers (Prahalad & Ramaswamy, 2004; Snyder, 2019), where shareholders define and create their brand identity through this relationship. Finally, it can be said that brand co-creation, in addition to strengthening a company's innovation capability, is also a reliable way to enhance brand relationships (Chang & Hsieh, 2016).Broeke and Paparoidamis (2021) demonstrate in their research that the co-creation of brand value occurs when customers are more sensitive to quality and less sensitive to price, and there is high demand for the product. Under such conditions, product quality is enhanced, and the company's flexibility increases. Nadeem et al. (2020) show in their research that social support affects ethical perception, and both are effective in co-creation. Ethical understanding also has an impact on consumers' trust, satisfaction, and commitment. However, trust and commitment do not have a significant impact on the co-creation of value. Tajvidi et al. (2020) demonstrate that concerns about privacy can disrupt the effects of brand co-creation, and social support, quality of relationships, and information sharing on social media have a positive impact on consumers' intention to co-create brand value on social media. Additionally, there is a meaningful relationship between customer participation in brand communities on social media and the quality of the relationship.MethodologyThis study is objective in nature and employs a qualitative approach. Its aim is to identify the factors that affect co-creation branding in startups. To achieve this, a meta-synthesis approach is used to examine existing articles in the field and extract the relevant factors. The statistical population of the research is credible and relevant articles published between 2007 and 2022 (a 15-year time span). Meta-synthesis involves reviewing previous studies and reframing concepts through interpretive integration of previous results. In this research, the seven-stage Sandelowski & Barroso (2006) method is used to carry out the meta-synthesis, as it is the most commonly used method for meta-synthesis in recent university research studies.ResultsThis research conducted a systematic review of 41 research studies to identify the factors influencing co-branding in startups. The meta-synthesis method was used to analyze the research literature. After studying and extracting text, key codes were clustered using MAXQDA software and organized into concepts and components. Ultimately, the factors influencing co-branding in startups were extracted and classified into four themes, eight concepts, and 33 distinct codes. These themes include environmental factors (financial and social factors), strategic brand management factors (brand value and brand creation), marketing factors (promotional activities and customer-related factors), and individual entrepreneurial factors (entrepreneurial personal characteristics and entrepreneurial skills).Discussion and ConclusionThe objective of this research is to identify the factors that influence co-branding in startups using a meta-synthesis method. To accomplish this objective, the scattered factors mentioned in various studies and case studies in this field were collected and classified into similar categories as concepts and themes using the meta-synthesis method and following the seven steps proposed by Sandelowski and Barroso. Startups can fulfill their responsibility and duty to society by engaging in activities that help the community, which has a significant impact on co-branding in the startup ecosystem (Kennedy & Guzman, 2016). Moreover, the social position of companies has been shown to influence co-branding (Twrsnick, 2016; Kennedy & Guzman, 2016). The availability of financial resources has a critical impact on co-branding activities in startups. Financial performance in this context refers to the extent to which the resources under the company's control generate profitability, which is vital for accepting and developing co-branding programs in the future. Therefore, it is considered one of the influential factors (Hatch & Schultz, 2010; Huang & Lai, 2011; Todor, 2014; Setiyati & Wijaya, 2015; Du Plessis et al., 2015; Tavares, 2015; Twrsnick, 2016; Kennedy & Guzman, 2016). The process of brand creation refers to a set of factors that lead to the development of a brand, encompassing brand design, brand strategy, brand identity, brand positioning, and brand objectives. These factors have been examined in most studies conducted in this area (Spence & Essoussi, 2008; Bresciani & Eppler, 2010; Bergström et al., 2010; Huang & Lai, 2011; Dai & Pietrobon, 2012; Sonja et al., 2022). Understanding the value-creating factors of a brand is a requirement for creating a strong brand. A brand's value is defined as a set of assets related to the brand name and company symbol that depend on the name or symbol of a brand and the increase in value created by the company's products or services. The value-creating factors of a brand include brand awareness, perceived brand quality, brand associations, brand image, brand experience, brand value, brand trust, brand commitment, and brand love (Boyle, 2007; Carvalho, 2007; Spence & Essoussi, 2008; Hamidi et al., 2021; Sonja et al., 2022; Bahagir et al., 2022). Promotional activities are all actions taken to raise awareness and persuade customers and the target audience to use a product or service and represent the fourth element of the marketing mix (Hagili et al., 2017; Kamboj et al., 2018; Rialti et al., 2018; Tajvidi et al., 2020; Sonja et al., 2022; Bahagir et al., 2022). To implement and execute the co-creation approach, companies create their own channels to establish connections with customers, which is essentially the fundamental aspect of co-creation, involving individuals' participation in creating valuable experiences together. By employing this approach, companies cause customers to feel a sense of belonging to the brand and develop loyalty towards the brand (France et al., 2015; Setiyati & Wijaya, 2015; Du Plessis et al., 2015; Twrsnick, 2016; Kauffman et al., 2016). Previous research has shown that the personal characteristics and traits of entrepreneurs have an impact on their success and the success of their startup companies. Therefore, knowledge and experience play a significant role in branding, and many entrepreneurs have been able to use their previous knowledge and experience to pave the way for their future (Carvalho, 2007; Juntunen, 2012; Tavares, 2015; Lagerstedt & Mademlis, 2016; Twrsnick, 2016; Giannopoulos et al., 2021). The role of entrepreneurs in guiding and integrating the branding approach in startup companies has been emphasized in previous studies, which can be achieved in line with the innovation of entrepreneurs (Spence & Essoussi, 2008; Payne et al., 2009; Tavares, 2015; Setiyati & Wijaya, 2015; Twrsnick, 2016; Giannopoulos et al., 2021). Hence, it is advisable for entrepreneurs to place significant emphasis on networking and bolstering their social networks, as well as improving communication with their customers, to foster increased and superior engagement with them, and ideally, to capitalize on enhanced brand credibility. In this regard, startup firms can enhance and expedite their brand acceptance process by encouraging customers to partake in and collaborate on the branding process through co-creation. Moreover, considering the frequent reiteration of brand identity in numerous studies, it is recommended that startup company executives devote greater attention to establishing and reinforcing brand identity in the minds of customers. : Brand, Branding, Co-Creation, Start-Up, Meta-Synthesis
Mahdi Hamidi; Seyed Soroush Ghazinoori; Mohammad Naghizadeh; Naser Bagheri Moghaddam
Abstract
vIntroductionBig data and digital technologies, such as artificial intelligence (AI), blockchain, the Internet of Things (IoT), and robotics, will transform businesses in many ways. This process of adapting to these changes is called digital transformation. Companies and policymakers in different countries ...
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vIntroductionBig data and digital technologies, such as artificial intelligence (AI), blockchain, the Internet of Things (IoT), and robotics, will transform businesses in many ways. This process of adapting to these changes is called digital transformation. Companies and policymakers in different countries are implementing various programs, strategies, and policies to achieve digital transformation. However, they face many challenges and obstacles that need to be identified and addressed. This research provides a comprehensive classification of the barriers to digital transformation using the meta-synthesis method including 38 selected articles.Literature ReviewThe literature on this topic has proposed various classifications of the barriers to digital transformation. This research focuses on the barriers from the perspective of digital transformation management and excludes the studies that examine the barriers from a technical perspective. The literature on this topic can be divided into three main approaches: "examining the barriers to digital transformation across industries and companies", "innovation approach" and "barriers to organizational change".Some of the barriers mentioned in the literature are:Lack of standards, lack of legal basis for data use, integration with existing system environment, dependence on other technologies, and fear of transparency/acceptance (Vogelsang et al, 2019)Law/standards, management, and workforce (Bailie & Chinn, 2018)Strategy, business model, business processes, organizational structures, and organizational culture (Vukˇ si´, 2018)The conflict between physical and digital systems, as well as the pervasive mindsets that are ingrained in the organization's culture (Nate & Erica, 2014).Lack of guidance from the government and hence resistance to change; Changing the operating models requires replacing a large number of equipment and systems and involves significant capital; The interaction of different technologies may cause problems in a complex system; The adoption of new technologies requires a certain time for evaluation, and it takes time to adjust the strategy according to the new environment; Lack of overall planning and standardization (Lu et al, 2019).MethodologyThis research is a descriptive-applied study that uses the meta-synthesis method. In this study, the seven-stage model of Sandusky and Barroso (2006) is applied. Based on the research objectives and questions, as well as the theoretical foundations related to the barriers to digital transformation, relevant articles were searched using the keywords in the national and international scientific databases. This search resulted in finding 173 articles related to the keywords. After identifying the articles, the models and concepts presented in them were coded. In this study, open, axial, and selective coding were performed. In the next step, the internal validity and reliability of the codings were checked.ConclusionAs mentioned in the literature, the technological change in the digital field can be analyzed as a technological system and from the perspective of socio-technical transitions (Reinhardt, 2022). Different approaches for analyzing technological transitions are of interest in the literature. This study has chosen a multi-level perspective for this analysis. This perspective views the transition as a historical pattern that can be depicted in three different layers. According to this perspective, technology transition can be conceptualized as three nested levels: landscape, socio-technical regime, and niche.Using this perspective, at the landscape level, the environment of a system is examined, and the two sub-categories of government and society are identified as barriers to digital transformation. Moreover, based on the systemic approach to the topic, the socio-technical regime, which is the system that governs the industry or the field studied in this study, is proposed. The basis of companies developing digital technologies should be analyzed and investigated according to the concept of barriers to digital transformation. In this thesis, this category is explained and the dimensions related to each category are discussed in detail.Considering the scope of the study, this framework does not examine the internal relationships between the variables (sub-categories) under the categories. It seems that suggesting the relationship between sub-categories in the proposed framework can be a recommendation for future studies. Also, examining the solutions to overcome the barriers identified in a case study can be suggested as another recommendation for future studies.Keywords: Digital Transformation, Barriers, Meta-Synthesis, Multi-Level Perspective (MLP). IntroductionBig data and digital technologies, such as artificial intelligence (AI), blockchain, the Internet of Things (IoT), and robotics, will transform businesses in many ways. This process of adapting to these changes is called digital transformation. Companies and policymakers in different countries are implementing various programs, strategies, and policies to achieve digital transformation. However, they face many challenges and obstacles that need to be identified and addressed. This research provides a comprehensive classification of the barriers to digital transformation using the meta-synthesis method including 38 selected articles.Literature ReviewThe literature on this topic has proposed various classifications of the barriers to digital transformation. This research focuses on the barriers from the perspective of digital transformation management and excludes the studies that examine the barriers from a technical perspective. The literature on this topic can be divided into three main approaches: "examining the barriers to digital transformation across industries and companies", "innovation approach" and "barriers to organizational change".Some of the barriers mentioned in the literature are:Lack of standards, lack of legal basis for data use, integration with existing system environment, dependence on other technologies, and fear of transparency/acceptance (Vogelsang et al, 2019)Law/standards, management, and workforce (Bailie & Chinn, 2018)Strategy, business model, business processes, organizational structures, and organizational culture (Vukˇ si´, 2018)The conflict between physical and digital systems, as well as the pervasive mindsets that are ingrained in the organization's culture (Nate & Erica, 2014).Lack of guidance from the government and hence resistance to change; Changing the operating models requires replacing a large number of equipment and systems and involves significant capital; The interaction of different technologies may cause problems in a complex system; The adoption of new technologies requires a certain time for evaluation, and it takes time to adjust the strategy according to the new environment; Lack of overall planning and standardization (Lu et al, 2019).MethodologyThis research is a descriptive-applied study that uses the meta-synthesis method. In this study, the seven-stage model of Sandusky and Barroso (2006) is applied. Based on the research objectives and questions, as well as the theoretical foundations related to the barriers to digital transformation, relevant articles were searched using the keywords in the national and international scientific databases. This search resulted in finding 173 articles related to the keywords. After identifying the articles, the models and concepts presented in them were coded. In this study, open, axial, and selective coding were performed. In the next step, the internal validity and reliability of the codings were checked.ConclusionAs mentioned in the literature, the technological change in the digital field can be analyzed as a technological system and from the perspective of socio-technical transitions (Reinhardt, 2022). Different approaches for analyzing technological transitions are of interest in the literature. This study has chosen a multi-level perspective for this analysis. This perspective views the transition as a historical pattern that can be depicted in three different layers. According to this perspective, technology transition can be conceptualized as three nested levels: landscape, socio-technical regime, and niche.Using this perspective, at the landscape level, the environment of a system is examined, and the two sub-categories of government and society are identified as barriers to digital transformation. Moreover, based on the systemic approach to the topic, the socio-technical regime, which is the system that governs the industry or the field studied in this study, is proposed. The basis of companies developing digital technologies should be analyzed and investigated according to the concept of barriers to digital transformation. In this thesis, this category is explained and the dimensions related to each category are discussed in detail.Considering the scope of the study, this framework does not examine the internal relationships between the variables (sub-categories) under the categories. It seems that suggesting the relationship between sub-categories in the proposed framework can be a recommendation for future studies. Also, examining the solutions to overcome the barriers identified in a case study can be suggested as another recommendation for future studies.
Maryam Sadat Mazaheri; Changiz Valmohammadi; Alireza Pourebrahimi; Mahnaz Rabeei
Abstract
IntroductionNowadays, cloud computing has attracted the attention of many organizations. So many of them tend to make their business more agile by using flexible cloud services. Currently, the number of cloud service providers is increasing. In this regard, choosing the most suitable cloud service provider ...
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IntroductionNowadays, cloud computing has attracted the attention of many organizations. So many of them tend to make their business more agile by using flexible cloud services. Currently, the number of cloud service providers is increasing. In this regard, choosing the most suitable cloud service provider based on the criteria according to the conditions of the service consumer will be considered one of the most important challenges. Relying on previous studies and using a meta-synthesis approach, this research comprehensively searches past researches and provides a comprehensive framework of factors affecting the choice of cloud service providers including 4 main categories and 10 sub-areas. Then, using the opinions of experts who were selected purposefully and using the snowball method, and using the Lawshe validation method, the framework is finalized.Research Question(s)This research aims to complete the results of previous studies and answer the following questions with a systematic review of the subject literature:-What are the components of the comprehensive framework for choosing cloud service providers?-What are the effective criteria to choose a cloud service provider?-What is the selected framework of effective factors? Literature ReviewMany researchers have looked at the problem of choosing the best CSP from different aspects and have tried to provide a solution in this field. In this regard, we can refer to "Tang and Liu" (2015) who proposed a model called "FAGI" which defines the choice of a trusted CSP through four dimensions: security functions, auditability, management capability, and Interactivity helps. "Kong et al." (2013) presented an optimization algorithm based on graph theory to facilitate CSP selection. Some researchers have also provided a framework for CSP selection, such as "Gash" (2015) who provides a framework called "SelCSP" with the combination of trustworthiness and competence to estimate the risk of interaction. "Brendvall and Vidyarthi" (2014) suggest that in order to choose the best cloud service provider, a customer must first identify the indicators related to the level of service quality related to him and then evaluate different providers. Some researchers have focused on using different techniques for selection. For example: "Supraya et al." (2016) use the MCDM method to rank based on infrastructure parameters (agility, financial, efficiency, security, and ease of use). They investigate the mechanisms of cloud service recommender systems and divide them into four main categories and their techniques in four features of scalability, accessibility, accuracy, and trustIn this research, it has been tried to use the models and variables of the subject literature in developing a comprehensive framework. The codes, concepts, and categories related to the choice of cloud service providers are extracted from previous studies, and a comprehensive framework of the factors influencing the choice of cloud service providers is presented using the meta-composite method. MethodologyIn this research, based on the "Sandusky and Barroso" meta-composite qualitative research method, which is more general, a systematic review of the research literature was conducted, and the codes in the research literature were extracted. Then the codes, categories, and finally the proposed model are formed. The seven-step method of "Sandusky and Barroso" consists of: formulation of the research question, systematic review of the subject literature, search and selection of suitable articles, extraction of article information, analysis and synthesis of qualitative findings, quality control, and presentation of findings. Lawshe validation method has been used to validate the research findings. ResultsIn the meta-synthesis method, all the factors extracted from previous studies are considered as codes and concepts are obtained from the collection of these codes. Using the opinion of experts and considering the concept of each of these codes, codes with similar concepts were placed next to each other and new concepts were formed. This procedure was repeated in converting the concepts into categories and the proposed framework was identified. This framework consists of 27 codes, 10 concepts, and 4 categories (Table 1).Table 1: Codes, concepts, and categories extracted from the sourcescategoryConceptCodeNo.TrustSecurityHardware Security1Network Security2Software Security3Confidentiality4Control5Guarantee and AssuranceAccessibility6Stability7Facing ThreatsTechnical Risk8Center for Security Measures9TechnologyEfficiencyService Delivery Efficiency10Interactivity11Hardware and Network InfrastructureConfiguration and Change12Capacity (Memory, CPU, Disk)13Functionality Flexibility14Usability15Accuracy16Service Response Time17Ease of use18ManagerialMaintenanceEducation and Awareness19Customer Communication Channels20StrategicLegal Issues21Data Analysis22Service Level Agreement23CommercialCustomer SatisfactionResponsiveness24Customer Feedback25CostSubscription Fee26Implementation Cost27The lack of a common framework for evaluating cloud service providers is compounded by the fact that no two providers are the same, so that this issue complicates the process of choosing the right provider for each organization. Figure 1 shows the proposed comprehensive framework including 4 categories and 10 concepts covering the issue of choosing cloud service providers. These factors are useful in determining the provider that best matches the personal and organizational needs of the service recipient. The main categories are: trust building, technology, management, and business, which will be explained in the following.Figure 1: Cloud service provider selection framework 5- ConclusionBy comprehensively examining the factors affecting the choice, this research introduces specific areas such as trust building, technology, management, and business as the main areas of cloud service provider selection and add to the previous areas. The category of building trust between the customer, and the cloud service provider is of particular importance. In this research, the concepts related to trust building are: security (including hardware security, network security, software security, confidentiality and control), (availability, stability and stability), and facing threats (technical risk). In 36% of the articles, the concept of trust is mentioned, but in each study, only a limited number of factors affecting this category are discussed. This research takes a comprehensive look at the category of technology, the concepts of productivity (including service delivery efficiency, interactivity), hardware and network infrastructure (including configuration and repair, capacity (memory, processor, disk)), and performance (including flexibility, usability, accuracy of operation, service response time, ease of use). Considering the variety of services on different cloud platforms, service recipients must ensure that the provision of services is managed easily and in the shortest possible time by the cloud provider. The commercial aspect of service delivery deals with the two concepts of customer satisfaction (including responsiveness, customer feedback) and service rates (including: subscription cost and implementation cost), which are of interest to many businesses. The results of this research will help the decision makers of using the cloud space (both organizational managers and cloud customers) in choosing the best cloud service provider to have a comprehensive view of the effective factors before choosing and plan according to their needs.
Mohammad Saleh Torkestani; Zohreh Dehdashti Shahrokh; Iman Raeesi Vanan; Fatemeh Golshan
Abstract
Providing valuable information in the form of attractive content and interaction with customers is one of the most important elements of content marketing. The most important factor in the success of content marketing is answering to the question of what causes the audience to engage in content. Despite ...
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Providing valuable information in the form of attractive content and interaction with customers is one of the most important elements of content marketing. The most important factor in the success of content marketing is answering to the question of what causes the audience to engage in content. Despite numerous researches in the field of identifying the dimensions of engagement and motivators of audiences to engage with content, the audience engagement is still one of the most important concerns of actors in the field of content marketing and they are looking for effective ways to identify factors affecting the promotion of audiences' engagement. The present study, using Meta - synthesis method based on the Sandelowski and Barros (2007) model, identifies influential indicators of content marketing on promoting the audience engagement. For this purpose, studies according to years 2003 – 2019 were collected and the papers that did not obtain the intended criteria were excluded from the study. Finally, the findings of 45 papers were selected. By classification of identified codes, 23 categories were identified in 4 dimensions including engagement, categories related to content features, categories related to content writer and other user's reactions. Among all identified categories, the possibility of content personalization for each audience, the sentiment embedded in content and the history of content, the membership level of writer and his/her identity in the online community made the highest priority.
Abbas Moayya; Ali Otarkhani; Ali Rezaeian; Bahman Hajipour
Abstract
Business Model Innovation (BMI) is an innovation process which is associated with radical change (i.e., designed, novel, nontrivial changes) in the configuration of an existing BM, aimed at building and maintaining competitive advantages. One of the important subjects regarding this concept is the drivers ...
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Business Model Innovation (BMI) is an innovation process which is associated with radical change (i.e., designed, novel, nontrivial changes) in the configuration of an existing BM, aimed at building and maintaining competitive advantages. One of the important subjects regarding this concept is the drivers of this level of innovation in businesses. However, despite the interest of many researchers in BMI in recent years, few articles have studied its antecedents directly and comprehensively, and most of existing articles are case studies. Therefore, in this study, an attempt has been made to integrate the antecedents reported in scattered case studies with the Meta-Synthesis method, and combining them with the Thematic Analysis method to provide a comprehensive list of Business Model Innovation drivers. For this purpose, after searching related articles in Scopus database and refining the results, 140 case studies reported in selected articles were analyzed. Extraction of instances of drivers, coding, searching for themes and naming them during the recursive steps of the content analysis method, led to identification of 10 main themes including 30 sub-themes. Eventually, the research report is presented along with the researcher's definition of all 10 main drivers and 30 sub-drivers.
MohammadHossein Ronaghi
Abstract
The rapid depletion of natural resources and growing awareness of the environmental deterioration have made sustainability one of the key elements enabling contemporary businesses to thrive. Among the most crucial sustainable practices is the application of Green IT due to the wide use of IT in various ...
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The rapid depletion of natural resources and growing awareness of the environmental deterioration have made sustainability one of the key elements enabling contemporary businesses to thrive. Among the most crucial sustainable practices is the application of Green IT due to the wide use of IT in various business sectors to enhance the performance of businesses. Green Information Technology (IT) has emerged as a vital IT governance concern to promote environmentally-friendly IT use and ecologically responsible business processes. according to various researches in green information technology, this research aims to design a green information technology using Meta-synthesis method. In order to design and explain a comprehensive model, all factors of green information technology have been identified through systematic literature review using 189 papers and content analysis. Then the importance and priority of each proposed factor was determined using Shannon quantitative method. The results reveal cost reduction, data center layout, employee stewardship and participation are the major factors in green information technology. At the end the research results demonstrate a comprehensive framework for green information technology factors.
zahra vazife; Mohammad Mahdi; Nadia Vakili
Abstract
Today, information plays the role of capital of the organization and the protection of corporate information is one of the important pillars of its survival. On the other hand, security issues and barriers are one of the most important issues in the field of information systems. For a long time, security ...
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Today, information plays the role of capital of the organization and the protection of corporate information is one of the important pillars of its survival. On the other hand, security issues and barriers are one of the most important issues in the field of information systems. For a long time, security was considered as one of the main components of information technology infrastructure. This study is an applied research in which meta-synthesis approach has been used for analysis. This research has been carried out using a meta-synthesis approach with a thorough and in-depth review of the subject and combines the findings of qualitative and quantitative research. In this regard, 118 articles on information security and information systems management were evaluated and 55 articles were selected. Then, by analyzing content analysis the relevant dimensions and codes were extracted and the importance and priority of each dimension was determined using Shannon entropy. Based on the findings of the research, knowledge about the value of information, the ability to retrieve information, the correct use of resources, and the coexistence of information and software has the highest importance among the 10 dimensions. Finally, following the research steps, a model for determining and deploying an effective information security management system was presented in three layers of identification, implementation structure, and design of the support system of the information security management system.
