Management approaches in the field of smart
Mohammad Faryabi; Samad Rahimiaghdam; Zahra Ranjbar Areshtanab; Zahra Ghorbanimoaddab
Abstract
In today's complex and competitive world, startups need strong and up-to-date knowledge management to identify opportunities and create innovation. In this regard, knowledge management can help startups create effective innovations by utilizing accurate information and using it in a timely manner and ...
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In today's complex and competitive world, startups need strong and up-to-date knowledge management to identify opportunities and create innovation. In this regard, knowledge management can help startups create effective innovations by utilizing accurate information and using it in a timely manner and maintain their position in the competitive market. Therefore, the purpose of this study is to examine the impact of knowledge management on the performance of Iranian startups, focusing on the mediating role of digital innovation and the moderating role of strategic flexibility, which has not been examined in previous studies. This study is quantitative and of the type of applied studies. The statistical population includes 1321 startups nationwide. Data was collected through a standard questionnaire and through the opinions of startup managers. Data analysis was evaluated using structural equation modeling and partial least squares. The findings reveal that knowledge management has a direct and positive effect on the performance of startups. Additionally, digital innovation strengthens the relationship between knowledge management and performance as a mediator, while strategic flexibility positively moderates this relationship. This research contributes by introducing a new model to improve startup performance, demonstrating that digital innovation and strategic flexibility are critical factors in enhancing the effect of knowledge management on startup performance.
Management approaches in the field of smart
Hadi Taghavi; Mohammad Mehraeen; Mehdi ShamiZanjani; Alireza Khorakian
Abstract
The digital transformation of the banking sector is essential for survival and competitiveness in the digital age. This study aims to explain the implementation model of digital transformation in Iranian non-governmental commercial banks. As a fundamental and qualitative study, it employs an exploratory ...
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The digital transformation of the banking sector is essential for survival and competitiveness in the digital age. This study aims to explain the implementation model of digital transformation in Iranian non-governmental commercial banks. As a fundamental and qualitative study, it employs an exploratory design to achieve its objective. The research population includes managers, consultants, specialists, and experts involved in digital transformation initiatives within these banks. Using a purposive sampling method, theoretical saturation was reached with 17 participants. Data analysis was conducted using Maxqda software. The findings, based on a paradigmatic model, revealed that causal factors such as competitive pressures, customer expectations, and market dynamics significantly influence banking's digital transformation. Contextual conditions, including environmental and economic factors, employee experience, and organizational culture, provide the foundation for implementation, while regulatory and competitive challenges act as intervening variables. These factors shape strategies and actions, such as customer-centric, operational, ecosystem, and network strategies, which lead to outcomes like enhanced customer experience, improved operational efficiency, revenue growth, greater organizational agility, and innovative business models. This model, tailored to the internal challenges and unique structure of Iran’s banking industry, offers a more flexible approach to implementing digital transformation initiatives.
Management approaches in the field of smart
hossein Mohebbi; saeid Torfi
Abstract
Artificial Intelligence (AI), as one of the most transformative emerging technologies, is rapidly evolving and reshaping various sectors. For Iran, as a developing country, understanding the future trajectories of AI and implementing strategic planning for its optimal development are of critical importance. ...
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Artificial Intelligence (AI), as one of the most transformative emerging technologies, is rapidly evolving and reshaping various sectors. For Iran, as a developing country, understanding the future trajectories of AI and implementing strategic planning for its optimal development are of critical importance. This study aims to explore the future of AI development in Iran using a structural scenario planning approach with a horizon set to 2035. The research is applied in nature and employs a descriptive-survey method for data collection. The statistical population includes university professors, managers, and experts in the AI industry. Unlike previous studies that primarily focused on specific domains of AI, this research adopts a comprehensive and national-level perspective, introducing the first structural scenario framework for AI development in Iran. It identifies and analyzes four key scenarios: the AI Vacuum, the AI Renaissance, the AI Mirage, and AI Transactions. These scenarios are built upon the analysis of critical driving forces, such as governmental policies, advanced technological infrastructure, challenges of technological singularity, geopolitical dynamics, innovation accelerators, and AI applications across industries. The findings reveal that the future development of AI in Iran is highly dependent on governmental support and the advancement of appropriate infrastructure. While critical scenarios demand immediate policy intervention, the more desirable ones offer significant opportunities for sustainable AI growth. These scenarios can serve as a foundation for designing targeted policy strategies, such as a national AI roadmap and the restructuring of innovation support systems, thereby providing a structured framework for decision-making under conditions of uncertainty.
Management approaches in the field of smart
Reza Behbood; Ehsan Bagheri; Mohamad Mahdi Zolfaghari Tehrani
Abstract
The development of augmented reality (AR) and virtual reality (VR) technologies has significantly transformed smart building projects, leading to the emergence of mixed reality (MR). This concept serves as a bridge between digital and physical worlds and is considered crucial within the smart construction ...
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The development of augmented reality (AR) and virtual reality (VR) technologies has significantly transformed smart building projects, leading to the emergence of mixed reality (MR). This concept serves as a bridge between digital and physical worlds and is considered crucial within the smart construction ecosystem. However, the adoption of MR technology among Iranian specialists is limited, with few professionals familiar with its advanced capabilities. This research investigates the perspectives of construction industry experts in Iran on the convergence of AR and VR. A mixed-method approach was employed, beginning with a review of relevant literature, followed by designing a Q-methodology survey to gather expert opinions across five specific areas. The data collected through questionnaires were analyzed using content analysis and statistical methods to identify prevailing patterns and trends. Findings revealed that integrating AR and VR can significantly enhance accuracy, reduce costs, and boost productivity. However, challenges such as technical barriers and the necessity for ongoing user training were also highlighted. The research's value lies in its comprehensive analysis of expert opinions regarding MR, which can inform optimization strategies in the construction sector. Ultimately, the study concludes that acknowledging the potential of integrated technologies, along with a focus on human and economic factors, can foster success in this evolving field.
Management approaches in the field of smart
Faezeh Zamani; Ahmad Ebrahimi; Roya Soltani; Babak Farhang Moghaddam
Abstract
This research aims to investigate the effective factors in predicting lead time (LT) and create a predictive model of LT to improve sustainability and resilience for Kanban orders in the lean supply chain (LSC). The study follows the data mining (DM) method, and the dataset includes 103023 observations ...
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This research aims to investigate the effective factors in predicting lead time (LT) and create a predictive model of LT to improve sustainability and resilience for Kanban orders in the lean supply chain (LSC). The study follows the data mining (DM) method, and the dataset includes 103023 observations from the Kanban system, which were extracted in compliance with the requirements of the dataset quality indicators in the period 1402/6 to 1402/11. First, indicators affecting the LT of orders were extracted. Process mining was used to identify influential variables in high-variance processes to improve performance and accuracy. A stepwise analysis approach was used to select features for the model fitting stage. Also, tuning the parameters of non-parametric approaches was used. The predictive model uses Multiple Linear Regression, Multiple with curvature, Lasso, Elastic Net, Boosted Decision Tree, Bootstrap Random Forest, K-Nearest Neighbor, and Boosted Multi-Layer Perceptron. The performance of the fitted regression models has been confirmed using R^2, RASE, and validation of the results and model. The results showed that the logistical features are effective in LT, and the Boosted Multi-Layer Perceptron is the best for predicting orders' LT with an accuracy of 96% and an error of 5.84. Using the model's predictive capability for new data in the Kanban system, the results obtained within four months have been used. The improvements from using DM capabilities in the Kanban system all express the significant impact of combining lean and machine learning (ML) tools to empower and resilient Lean Supply Chain Management (LSCM).IntroductionThe main problem in this research is identifying the factors that effectively predict the LT of orders in the LSC, choosing the best ML algorithm for predicting the exact LT, and how process mining can effectively identify the most repeatable variables in the main variants and investigate how DM can reduce waste in LSC.Despite classification studies on risk, disruption, and delay prediction in the literature, to our knowledge, fewer articles were found regarding the use of DM to predict the accurate LT of orders in the LSC with logistical features. Also, according to researchers, DM is considered a tool to overcome the limitations of lean tools and strengthen their performance. However, the studies corresponding to the executive case did not observe the results and improvements from the ML application in predicting the LT of orders.Therefore, in this research, in terms of innovation, 1) machine learning has been used to accurately predict the LT of Kanban orders, considering logistical factors, 2) Process mining has been used in the identification stage of influential variables, 3) The results and improvements obtained from predicting the LT of orders regarding risk reduction and sustainability improvement have been examined and compared.Research Question(s)The main questions in this research are specified as follows:What factors affect LT's prediction in the lean supply chain?How do we predict the LT in the lean supply chain?How can DM effectively reduce waste in the lean supply chain?Literature ReviewRegarding the issue's importance and urgency, transparency and accurate prediction of the LT have reduced risk and improved sustainability and resilience in the LSC. These effects are significant in both theoretical and operational dimensions, such as reducing logistic costs, safety stock, working capital, stoppage, level of inventories, storage cost, energy consumption, and risk. After reviewing the literature, the most relevant articles in the field of ML are listed in Table2.MethodologyThis research is practical from the objective point of view, and from the data point of view, it is quantitative. This study includes four main processes: 1) reviewing the literature and data collection, 2) research method and pre-processing, 3) model construction, and 4) model evaluation and results (Jayanti, 2022 & Wasesa). First, influential variables were extracted by reviewing the literature. Then, the dataset was extracted from the Kanban system in compliance with the requirements of the data set quality indicators from 6/1402 to 11/1402. Then, process mining was used to identify the features with the most repeatability in the main variants, and finally, influential variables were extracted through brainstorming. An integrated stepwise analysis approach has been used to select features. The predictive model uses MLR, curvature, Lasso, Elastic Net, Boosted DT, Bootstrap RF, KNN, and Boosted Multi-Layer Perceptron. The parameters of non-parametric approaches are tuned to improve forecasting performance and accuracy. In this research, evaluation and validation are the main criteria for evaluating the model's predictive power, and error and accuracy indices have been used together. Therefore, the performance of the fitted regression models using R^2 and RASE evaluation indices and validation of the results and the model are confirmed.ResultsAfter fitting the regression models, for each row of test data, predict the LT and compare it with the actual values of the LT; then, to identify the best model, R^2, RASE, and model comparison approaches are used.The results show that the Boosted Multi-Layer Perceptron, with one hidden layer, five activation functions, and a learning rate of 0.1, has the highest accuracy at 96% and the lowest root average square error at 5.84, compared to other fitted models.Discussion and ConclusionThe obtained results show that the identified independent variables are related to customer factors (safety stock), manufacturer factors (inspection status, quality paint), logistic factors (vehicle, distance), part factors (name, part-expert), and order factors (number of holidays, Kanban issue date) are effective on the LT. As the selected model in this research, the regression model of the Boosted Multi-Layer Perceptron has the highest R^2 and the lowest RASE criteria. Process mining is practical and helpful in identifying the main variants. By using the model's predictive capability for new data in the Kanban order issuing system within four months, the improvements all express the significant impact of combining lean tools and ML to empower LSCM. The practical implications of this research can guide managers in implementing practices with lean tools, improving sustainability, eliminating waste, and being more competitive in the current challenging business environment. Academics can benefit from the present study because it provides ML practices that can be further tested and validated.This research generalizes and develops the use of DM as a decision-making support tool in predicting the LT to overcome the limitations of lean tools, and it can improve the efficiency and stability of the LSC and reduce the risk. While this research provides valuable insights, it also has limitations, including the lack of data on influential variables identified in the literature. In implementing this research, there are suggestions for future research that examine factors such as production capacity, weather, and location conditions and deep learning to fit more reliable and accurate results and investigate prescriptive analyses to optimize the LT of orders based on the fitted regression models, the design of the experiment and using the profiler's capabilities.Keywords: Machine Learning, Regression, Lean Supply Chain Management, Kanban, Lead Time.
Management approaches in the field of smart
seyed Mohsen Safavi koohsareh; seyed amin hosseini sano; Amirhossein Mohajerzadeh
Abstract
The primary objective of mobile network operators is arguably to maximize their efficiency. Beyond operational and investment costs, maximizing the utilization of available resources can help them achieve this goal. To this end, operators offer discounted data plans during off-peak hours to encourage ...
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The primary objective of mobile network operators is arguably to maximize their efficiency. Beyond operational and investment costs, maximizing the utilization of available resources can help them achieve this goal. To this end, operators offer discounted data plans during off-peak hours to encourage users to utilize the network during these times. These data plans are typically based on the average traffic load across the entire network at different times of the day. However, they often overlook the fact that traffic patterns can vary significantly across different population areas within a city at various times. In this paper, different population areas are automatically identified using clustering based on traffic patterns. By identifying these areas and considering the traffic patterns specific to each area, the allocation of appropriate data plans for users, based on the regions they frequent, is analyzed and discussed. Additionally, other potential applications of this clustering method for offering various services are presented, followed by a conclusion.IntroductionThe number of cellular network users and their required bandwidth are continuously increasing (Ericsson, 2022). However, limited wireless frequency bands constrain network capacity, prompting operators to deploy dense base stations to reuse radio frequencies in smaller coverage areas, thereby enhancing capacity. Operators plan for peak usage, leading to base station layouts that often remain underutilized for extended periods, resulting in inefficient use of capital (equipment) and operational (energy and maintenance) costs (Liu et al., 2023). To address this, operators offer discounted plans during low-traffic periods but overlook the varying traffic patterns across urban areas, which could enable tailored offers for different regions. This paper proposes a hierarchical clustering-based method to identify and segment urban areas, design region-specific traffic-based plans, and target appropriate users. The main contribution is improving efficiency by maximizing the utilization of existing cellular networks without expanding capacity, benefiting both operators through increased revenue and users through enhanced satisfaction.MethodologyThe best approach to evaluate proposed solutions in cellular networks is to use real-world datasets from mobile operators. Cellular network logs are vast, contain sensitive user and network information, and require algorithms capable of handling large-scale data. In this study, we use a publicly available dataset (Barlacchi et al., 2015) containing telecommunication, weather, news, social media, and power grid data from Milan and Trentino, Italy, spanning November 1, 2013, to June 1, 2014. Our focus is on telecommunication data, specifically Call Detail Records (CDRs), to evaluate the proposed method.The dataset is processed and analyzed using Python and libraries such as NumPy, Pandas, Scikit-learn, and Matplotlib. The proposed method involves clustering base stations based on traffic patterns, designing region-specific data plans, and targeting users during low-traffic periods.3.1. Traffic Pattern-Based Region IdentificationAs mentioned earlier, traffic patterns of cellular base stations vary across urban areas. These patterns are heavily influenced by the stations' locations. For example, base stations in residential areas exhibit different traffic patterns compared to those in commercial, transportation, or recreational zones (Xu et al., 2017).Figure 1: Traffic Patterns of Base Stations in Three Different Population Zones Figure 1 illustrates the traffic patterns of base stations in three different population zones over a week. Zone 3 likely corresponds to recreational areas like amusement parks, with higher traffic on weekends. Zone 1 may represent office areas, with reduced traffic on weekends, while Zone 2 could be industrial or transit areas with consistent traffic throughout the week.To separate these zones, hierarchical clustering is employed (Abubakar et al., 2022). Instead of using Euclidean distance, which fails to distinguish adjacent zones with different traffic patterns, we use traffic time series as the clustering criterion. The chosen algorithm is agglomerative hierarchical clustering (Kassambara, 2017), as shown in Figure 2. Base stations first remove noise from their data and send average traffic data to a central node every x minutes. At the central node, Euclidean distance is used to measure traffic similarity between stations, reducing dimensionality from two dimensions (time series traffic volume) to one (distance between clusters). Over 80% of time series similarity studies use this metric, though some employ deep learning for feature extraction to improve clustering.The Euclidean distance between two base stations' traffic time series Q and C is calculated as:1 To mitigate sensitivity to variations, preprocessing steps include removing outliers, adjusting offsets, and smoothing noise using moving averages (Keogh & Pazzani, 1998).The hierarchical clustering dendrogram (Figure 2) determines the optimal number of clusters by identifying the best cut-off line. Two strategies are proposed:Predefine the number of clusters based on comprehensive traffic pattern analysis and use k-means clustering.Use silhouette scoring to dynamically determine the optimal number of clusters based on traffic similarity.We adopt the second approach, using average silhouette scores (Almeida et al., 2015) to select the optimal number of clusters. This method eliminates the need for predefined cluster counts and provides precise cluster identification.Once clusters are identified, data plans are designed for each cluster based on their traffic patterns.3.2. Designing Data PlansFor each cluster, the average traffic profile is calculated, and data plans are designed inversely proportional to traffic volume. The number of offers q in time interval t is determined by:2 where A and B are the traffic range bounds, S is the current traffic, N is the maximum number of offers, and C is the minimum (0).Alternative models, such as linear, exponential growth/decay, and logarithmic growth/decay, are also explored (Safavi et al., 2024), as shown in Figures 5 and 6.3.3. Targeting UsersUsers with higher overlap with low-traffic periods are prioritized for data plan offers. A user’s average monthly presence in low-traffic intervals is used to rank them. The longest data plans are assigned to users with the highest presence in low-traffic periods, ensuring efficient resource allocation.ResultsSimulations represents the method proposed in this paper, utilize 100% of the network's bandwidth capacity.results demonstrate the optimal utilization of existing equipment and resources, which directly correlates with increased operator profitability. Those also show that the proposed method can maximize resource efficiency by approximately 40%, representing the highest possible improvement in network resource utilizationWe can conclude, the proposed method significantly enhances resource utilization and operator profitability by fully leveraging network capacity. While other scenarios improve resource usage to some extent, only the proposed method achieves 100% utilization, highlighting its effectiveness in optimizing network performance and operational efficiency.Keywords: Mobile Network Operator, Maximizing the Utilization, Cellular Data Plan, Clustering, Traffic Pattern.
Management approaches in the field of smart
Mohammad Taghi Taghavifard; Payam Hanafizadeh; Saeedeh Mehri; Iman Raeesi Vanani
Abstract
Business model change in startups is essential for adapting to evolving market demands and increasing competitiveness, playing a critical role in their success. However, most research related to business model change has mainly focused on established firms. To address this research gap, the present study ...
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Business model change in startups is essential for adapting to evolving market demands and increasing competitiveness, playing a critical role in their success. However, most research related to business model change has mainly focused on established firms. To address this research gap, the present study provides a framework that contributes to understanding the role of design themes in startup business model changes. In this study, a systematic literature review was used to analyze theoretical foundations and prior researches. After defining the research question, designing a search strategy, and applying screening criteria, 95 articles published between 2000 and 2024 were reviewed. In the first stage, a conceptual model was developed to analyze the dimensions of business model change by reviewing theoretical foundations and prior researches. This model was then refined through inductive-deductive thematic analysis, using evidence from empirical articles and case studies. The identified themes—novelty, efficiency, lock-in, complementarity, and adaptability—were examined across four main dimensions of business model change: content, structure, governance, and stream. The findings showed these themes interact synergistically and contribute to competitive advantage and business sustainability. The research results suggest that these five overarching themes provide a suitable framework for understanding and managing business model change in startups.IntroductionIn recent years, the topic of entrepreneurship and startups has attracted significant attention and has emerged as a key driver of economic growth. The business model of startups plays a fundamental role in this process, serving as a mechanism for exploiting entrepreneurial opportunities and creating value (Amit & Zott, 2001; George & Bock, 2011; Guo et al., 2020). However, one of the key characteristics of the startup and entrepreneurial environment is high uncertainty, which static business models are unable to effectively adress (Demil & Lecocq, 2010). Accordingly, the main objective of this research is to develop a framework for changing the business models of digital startups and to offer practical insights for entrepreneurs. To explore the dynamics of startup business model change, this study addresses the following key research question:Research QuestionHow do startup business models evolve, and which business model themes drive this change?To answer this question, a conceptual framework was developed based on the business model structure proposed by Amit and Zott (2001) and the business model innovation framework proposed by Spieth and Schneider (2016). Literature ReviewThe existing literature on business model change follows two major approaches: the evolutionary approach and the theme-based approach (Guo et al., 2020).2.1. Evolutionary Approach to Business ModelsFrom an evolutionary approach, the business model of the startup changes and evolves in a dynamic manner through flexibility (Bock et al., 2012), experimentation (Andries et al., 2013), and trial-and-error learning (Chesbrough, 2010; Sosna et al., 2010). This approach draws upon methodologies such as the Lean Startup (Ries, 2011) and Customer Development (Blank, 2013), which suggest that business models evolve through iterative testing and customer feedback. Studies based on this approach show that incremental and continuous changes in business models require careful attention to the firm's internal resources and competencies, as explained by the resource-based view (RBV) and dynamic capabilities theory (Schneider & Spieth, 2013).2.2. Theme-Based Approach to Business ModelsThe theme-based approach focuses on using specific themes to structure business models and value creation. The four conventional themes are novelty, efficiency, lock-in, and complementarity (Amit & Zott, 2001, 2012; Kulins et al., 2016; Pati et al., 2018):Novelty: Refers to innovation in products or services or underlying resources and capabilities.Efficiency: Focuses on cost optimization and resource utilization.Lock-in: Helps strengthen long-term relationships with customers and partners.Complementarity: Enhances synergies among different value propositions.Recent studies (Zott & Amit, 2007; Ojala, 2016; Costa & Haftor, 2021) have demonstrated the effectiveness of this approach in fostering strategic entrepreneurship, allowing startups to integrate external opportunities with internal capabilities for sustained growth.2.3. Research Gap and Initial Conceptual ModelBusiness model change research has primarily focused on established firms (Achtenhagen et al., 2013; Bohnsack et al., 2014), while business model change in startups - a broadly defined type of organization with limited resources, high uncertainty, flexibility, and differences in value creation sources - has been less examined in the academic literature (Kesting & Günzel-Jensen, 2015; Guckenbiehl & Corral de Zubielqui, 2022). Amit and Zott (2001) recommend more research on the dynamics of business model themes, a gap reiterated by Randhawa et al. (2020). In this study, based on the business model structure by Amit and Zott (2001) and the stream dimension of Spieth and Schneider (2016), we analyze startup business model change themes across four dimensions: content, structure, governance, and stream.MethodologyThis study adopts an inductive–deductive approach and conducts a systematic literature review on startup business model change. The review process adhered to Tranfield et al.'s (2003) framework: planning the review; conducting the review; analyzing the findings. The articles included in the literature review were from articles published between 2000–2024 and they were retrieved from the Scopus and Web of Science databases. Initial output of 197 articles were ultimately reduced to 95 articles for in-depth review after duplicates and irrelevant articles were removed. To identify core concepts and themes related to business model change, the data were coded and analyzed using ATLAS.ti software.ResultsThematic analysis using the theme network tool led to the identification of five primary themes: novelty, efficiency, lock-in, complementarity, and adaptability. Each of these themes represents business model change in four dimensions: content, structure, governance, and stream (see Table 1) Table 1. Final Framework of Startup Business Model Change Based on Business Model Design ThemesDimensions NoveltyEfficiencyLock-InComplementarityAdaptabilityContent Products, services, information, or value propositionsüüüüüResources and assetsüü üüCapabilities and competenciesü üüStructure Customer segments and their relationsü üParticipants and their relationsü üüCommunication mechanismsüüüüüGovernance Controllersü ü Formal and legal structure üIncentivesü ü Stream Revenue streamsü üüCost structuresüü üInvestment structuresü üDiscussionThe framework proposed in this study introduces an additional dimension—stream—which extends the three-dimensional concep outlined by Amit and Zott (2001): content, structure, and governance. Furthermore, the inclusion of adaptability, which is not present in Amit and Zott’s model, is a significant innovation. Supported by Sharma et al.'s (2016) model, this framework integrates adaptability into a unified business model design, addressing dynamic environments and emerging market challenges beyond operational management.ConclusionThis study offers two important contributions to the literature by providing a new conceptual framework for startup business model change (Table 1). First, in addition to the four conventional business model themes (novelty, efficiency, lock-in, complementarity), the adaptability theme is introduced to demonstrate the importance of adaptability in changing and evolving business models. Second, this study provides new insights into how business models change by adding the stream alongside the content, structure, and governance dimensions.Keywords: Startup, Business Model Change, Business Model Design Themes.
Management approaches in the field of smart
Fahime Mahavarpour; Feiz Davood; Morteza Maleki Min Bash Razgah
Abstract
Augmented reality technology has emerged as one of the main trends in the digital market in recent years. This new technology has been successively used in innovative businesses due to its attractiveness and potential. The aim of the current research was a systematic and comprehensive review ...
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Augmented reality technology has emerged as one of the main trends in the digital market in recent years. This new technology has been successively used in innovative businesses due to its attractiveness and potential. The aim of the current research was a systematic and comprehensive review in the form of a bibliometric approach on the citation data of the purchase decision-making literature based on augmented reality technology. A pragmatic paradigm allowed the researcher to collect citation data from the Scopus database in a systematic strategy and preprocess it in the form of the standard Prism protocol. Finally, 239 studies were included in the bibliometric analysis basket by R Studio and Vosviewer software. The final results in the functional section identified the most influential documents, authors, journals, organizations, and countries, and then added highlights to buyer behavior and purchase decision-making with augmented reality technology in virtual businesses in the form of interaction patterns between elements and data content analysis.. It is also worth noting that this concept mainly revolves around five main areas: the virtual and psychological experiences of shoppers in online shopping with augmented reality; The effects of artificial intelligence on new technologies in the behavior of buyers; virtual and psychological experiences of buyers in online shopping with augmented reality; Interactions of technology, perceived value and cognition on shoppers' experience in retail using mobile augmented reality; The role of augmented reality technology in purchasing decisions and smart purchases in virtual space. The influential school of augmented reality technology in buyers' decision-making is related to the stimulus-organism-response theory, which formed the intellectual foundation of this field.
Introduction
Try to conduct marketing without using augmented reality technology; you will not succeed. Try to create an inspiring marketing strategy without augmented reality technology; this will not be effective either. While traditional marketing is effective, it involves high costs and difficulties in engaging and providing personalized services to customers, as it cannot adjust services to recognize customers' needs or expectations. Marketing with this novel technology (AR) represents a new and potentially impactful subfield that has transformed how buyers experience goods and services. Augmented reality aids in the development of marketing, offering benefits that enhance the company's image, strengthen customer interaction, and increase sales. These advanced new technologies have already positively boosted marketing. AR technology is in its early stages and there are ample opportunities for its improvement. This innovative technology (AR) provides an excellent option for enriching perceptual and interactive desires. While many established consumer behavior theories may extend naturally into virtual spaces, many of them may require significant updates to align with buyers' search, selection, and usage practices. During purchase decision-making, whether interacting with physical or online stores, buyers encounter various touchpoints that determine the shopping experience. Academic knowledge is expanding exponentially. This has made it challenging to keep up with the latest innovations in research and evaluate the collective evidence in a particular field of study. One such database is Scopus, created in 2004 and published by Elsevier. Managing such knowledge using traditional tools and techniques is difficult, if not unlikely, due to the rapid growth. This is why literature review as a research method has become more popular than ever in various natural and social science disciplines. The purpose of a systematic review is to identify all empirical evidence that meets pre-specified criteria to answer a specific research question or hypothesis. Bibliometrics is a new style of theoretical literature review and a type of systematic review that has created related theories and bibliometric analysis in various fields of knowledge, including management sciences. The value of bibliometric methods lies in their ability to analyze the evolution of scientific literature over time and reveal intellectual relationships in this field. Therefore, based on the present research problem, which seeks to describe performance indicators, examine the interactive patterns of these indicators, and analyze the content of citation information in the field of augmented reality technology in the academic space, the researcher aims to demonstrate the study gap in this field and contribute to filling the knowledge gap. In the introduction section, a systematic methodology is first defined to specify the steps for collecting, preprocessing, and analyzing information. Then, in the results section, an objective and tangible interpretation is provided using tables and charts from professional bibliometric software. Finally, the obtained results are discussed and concluded within the context of expanding the present literature.
Methodology
Systematic reviews indicate a precise approach to integrating and evaluating scientific evidence literature reviews are no exception and are guided by a systematic process. This process aids researchers in systematically and comprehensively gathering, analyzing, and evaluating existing studies, providing an overall picture of the state and trends within a scientific field. Compared to systematic literature reviews, this method helps prevent author bias. The present bibliometric methodology emerges from a pragmatic paradigm that designs various stages of research based on common assumptions and beliefs among review researchers Based on the outputs of scientific research, the researcher has the freedom to use various quantitative and qualitative approaches within this philosophical framework. According to bibliometric studies, the methodology of bibliometric research consists of five steps, which are detailed below.
Chart 3: The Methodological Process of Bibliometric Studies (Moradi & Miralmasi, 2020b, p. 570)
Results
In this study, the focus is on the topic of augmented reality technology and its evolution up to the year 2024. While augmented reality technology saw erratic growth in buyer behavior and purchase decision-making during its nascent stage up to 2015, this was largely due to the limited understanding of its long-term effects owing to the lack of metrics, measurable elements, and research studies at that time.
There is a 50-year span of articles, indicating over half a century of discussion surrounding augmented reality technology. However, from 2015 onwards, it has experienced an annual growth rate of 25.92%, showing an upward trend.
Approximately 36.46% of the research has been authored through international collaborations, as this field requires expertise from various research disciplines.
Developing countries, despite having fewer scientific outputs, publish their articles as international collaborative studies to ensure publication in reputable journals and to increase citations to their studies.
Keywords: Augmented Reality Technology, Marketing, Buyer Decision Making, Buyer Behavior, Virtual Businesses.
Management approaches in the field of smart
Homa Soufi; Habib Roodsaz; Davoud Hosseinpour; Hosein Aslipour
Abstract
Digital transformation in the banking sector is recognized as a critical driver of growth and change. This study investigates the anticipated outcomes (both outputs and impacts) following the implementation of digital banking policies, utilizing an exploratory and applied-developmental approach. The ...
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Digital transformation in the banking sector is recognized as a critical driver of growth and change. This study investigates the anticipated outcomes (both outputs and impacts) following the implementation of digital banking policies, utilizing an exploratory and applied-developmental approach. The research adopts a mixed-method design, incorporating both qualitative and quantitative phases. In the qualitative phase, experts in banking and policymaking were interviewed using purposive sampling, reaching theoretical saturation after 25 interviews. In the quantitative phase, data was collected from 354 bank managers and professionals through a researcher-developed questionnaire. The data was analyzed using thematic analysis for the qualitative part and the Partial Least Squares (PLS) method for the quantitative part. The results indicate that the initial outcomes of digital banking policy implementation include improvements in revenue and market positioning, cost efficiency, customer acquisition and satisfaction, bank infrastructure, data management, banking products and services, banking technologies and channels, and risk management. Additionally, the long-term and sustainable impacts of digital transformation in the banking system encompass transparency and justice, the creation of new opportunities, the future outlook of banking and the economy, digital leadership and mindset, social and environmental impacts, long-term policymaking and planning, as well as internal and external networking.
Introduction
Digital transformation is a crucial driver of development, particularly in the banking sector, where it reshapes traditional business models and operational processes, enabling efficient online financial services. Despite these advancements, Iranian banks face infrastructural and regulatory challenges, such as weak IT systems and traditional organizational cultures, which hinder the full adoption of digital solutions. To address these issues and align with global standards, comprehensive digital banking policies are necessary. This study explores the effects of these policies, focusing on the changes they bring about in both the short and long term. In this context, the fundamental research question is: What are the expected dimensions and components of the outputs and long-term impacts following the implementation of digital banking policies during the evaluation period?
Literature Review
Digital transformation in banking refers to the use of digital technologies to fundamentally improve and change the processes and structures of traditional banking. This transformation includes the application of technologies such as artificial intelligence, blockchain, big data, and cloud computing, which enable banks to offer innovative and customized services to customers (Vial, 2014). The emergence of fintech companies and the provision of digital financial services have pressured traditional banks to digitalize their structures. As a result, banks have developed digital transformation policies to remain competitive and align with market changes (Salamatitaba et al., 2017). In digital banking policy-making, evaluation is recognized as one of the most critical stages in the policy cycle. According to various literature and definitions, outputs are the immediate results obtained in the short term following the implementation of the policy, including direct improvements in digital banking services and processes. These results are typically observable within 1 to 3 years after the policy is implemented. In contrast, impacts refer to the long-term outcomes that emerge between 5 to 10 years post-implementation, encompassing the lasting effects and consequences of the policy. Research indicates that digital transformation in banking leads to improved customer satisfaction, enhanced transaction security, and optimized processes.
Methodology
This applied-developmental study employs a mixed-method approach. In the qualitative phase, 31 banking and policy experts were selected through purposive and snowball sampling, with saturation reached after 25 interviews. Data were analyzed using thematic analysis with MAXQDA software. In the quantitative phase, a survey was administered to 354 bank managers and experts, with the sample size calculated using Cochran's formula. The researcher-developed questionnaire included 36 items based on a five-point Likert scale. Reliability was evaluated using Cronbach’s alpha, yielding a score above 0.7. Data analysis was conducted using the Partial Least Squares (PLS) method with SmartPLS software to validate the findings.
Results
The thematic analysis of the qualitative data identified 88 descriptive codes, 21 interpretative codes, and 8 overarching themes for the outputs, as well as 54 descriptive codes, 15 interpretative codes, and 7 overarching themes for the impacts following the implementation of digital banking policies. The outputs were categorized into areas such as revenue and market positioning, cost efficiency, customer acquisition and satisfaction, bank infrastructure, data management, products and services, banking technologies and channels, and risk management. The long-term impacts included dimensions such as transparency and justice, the creation of new opportunities, the outlook for banking and the economy, digital thinking and leadership, social and environmental impacts, long-term policymaking and planning, and internal and external networking. Quantitative data analysis was conducted using the Partial Least Squares (PLS) method with SmartPLS software. The model was validated through relevant statistical tests, demonstrating a satisfactory fit and reliability.
Discussion & Conclusion
The findings align with key studies. Czerwińska et al. (2021) confirmed that investment in digital technologies enhances banks' competitive positions, which this study supports. Similarly, Lydiana et al. (2022) highlighted the role of digital transformation in fostering innovation, with this study further expanding the focus to service development. Consistent with Agboola et al. (2019), this research shows that digital transformation improves cost efficiency and operational performance. The impact on customer satisfaction and acquisition aligns with Aydin & Onayli (2020), emphasizing the role of digital experiences in customer growth. The analysis of organizational transformation matches Mirković et al. (2019), and the emphasis on data management is consistent with Sadigh et al (2022).
This study differentiates between the short-term outputs and long-term impacts of digital transformation in banks, providing a unique perspective compared to previous studies. It offers localized insights tailored to the Iranian market, making the findings particularly relevant for policymakers. It emphasizes that policymakers and regulatory bodies, such as the Central Bank, should prioritize strengthening IT infrastructure, developing comprehensive data security and privacy regulations, and focusing on new technologies like open banking and big data. The results indicate that the long-term effects of digital transformation on economic indicators and customer behavior require further investigation. Future studies could explore these effects over different time periods and examine how technologies such as AI and blockchain influence customer psychology, including decision-making, trust, and satisfaction, as well as social factors like access to banking services and the distribution of opportunities.
Keywords: Digital Transformation, Digital Banking, Policy Evaluation, Policy Outcomes.
پسآیندهای خطمشی بانکداری دیجیتال
Management approaches in the field of smart
Aryan Setareh Tabrizi; Ali Mohtashami
Abstract
Shipping industries in ports, as one of the main and strategic industries, have always performed an important role in the optimized management of the transportation business in a country. Moreover, it has an impact on the country's economy. The future status of port’s business management can be ...
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Shipping industries in ports, as one of the main and strategic industries, have always performed an important role in the optimized management of the transportation business in a country. Moreover, it has an impact on the country's economy. The future status of port’s business management can be seen in planning and forecasting, access to new technology in order to smartness, access to logistics, increase in specialized human resources and the impact of ports globalization. For this reason, the ports have to provide their services in a sutaible way in order to plan for their business development and supply demands. Also, the process of these changes in the future will be more than that, it will have a direct impact on the technology and facilities of the port. According to the mentioned points, in this article, in order to promote the ports and shipping industry, in the first step, the main indicators of green and smart ports are identified by library study, and then interviews are conducted with thematic analysis system approach. Next, the conceptual model of the research was drawn.Consequently, each index in the drawn pattern and the final index are evaluated in MATLAB software by Fuzzy Inference. As result of that, it is possible to determine the smartness and environmental indicators in the ports of the country for the first time. In this regard, Anzali port, one of the country's most important ports, will be implemented and concluded as a real example.
Introduction
Ports and harbors face serious competition to deliver a more efficient and safer flow of goods around the world. In this context, a new concept has emerged, which is called a smart port (2019, Molavi). Targeted smart port initiatives seek to remove specific barriers at ports. These initiatives are largely focused on specific applications of information and communication technology and regulation-based approaches in smart ports. These rules are aimed at improving port sustainability, the implementation of new technologies and providing port performance evaluation standards. In this part, the generalities of the research are presented in the form of stating the problem and the necessity of conducting the research, and in the next part, the goals and assumptions of the research are presented. Finally, the executive structure of research and innovation is presented.
Research Methodology
In this article, two library and field methods have been used to collect information. We reviewed educational theses, foreign and Iranian published books, Persian and English publications and some textbooks. Then, the basis the questions for the interview was designed. In this research, the snowball method was used and the number of experts in this field reached fifty people. Then, the subject method is used to obtain the data and information needed to identify the indicators. Semi-structured interviews were used based on the interview protocol. (2019, Yarahmad Ghasemi)
Innovation and novelty of the research:
Background and up-to-date information on research innovation:
Research Port 360 has recently prepared a comprehensive report in collaboration with the World Ports Association which report aims to examine the activities related to the management of smart port markets in the period 2023-2028 and is intended to be used in the agenda of all ports in the world.
Through the analysis and research conducted in this report, the dynamic chain of the global smart ports industry market during the period 2023-2028 has been well studied and an overview of how ports are becoming smart has been provided.
In the regulation of technology, it can be said that a digital port describes a connected port that uses broadband communication infrastructure, flexible and service-oriented computing infrastructure, and innovative services to meet demands. On the other hand, intelligence, along with international laws and regulations in the field of environment, results in a developed port.
Some of the things that distinguish this research from other research in terms of innovation are as follows:
In this research, services in the field of ports are considered in both implementation forms combined with a strategy and which have been thoroughly examined in research interviews, which has not been seen in the articles in this way as it has been accurately displayed in the maximum research table.
In this research, all four service levels that should be considered in ports, such as traffic management, safety, environment and ship management, have been examined in the research to extract concepts and ultimately the main indicators.
The managerial and executive application of this research is ultimately the implementation of environmental and smart components in the country's ports, which leads to the sustainable development of ports.
Research findings
According to the thematic analysis, the smartness and greenness of ports is drawn in Figure 4. We should evaluate all the indicators obtained from the evaluation model with the Mamdani logic in FIS with MATLAB software in order to determine the level of implementation of the intelligence and environmental model of ports. The inputs are: 1) port intelligence 2) greenhouse gas production 3) smart infrastructure 4) water and waste management 5) renewable resources utilization 6) environmental management 7) cultural support 8) energy consumption 9) safety management 10) greenness of the ports. Considering the average value for all the inputs, we will see that the result for the output is equal to the average. For instance, according to Figure 9, the environmental model and intelligence in the areas where the value of the smart technology is very high and high, and the amount of the greenhouse gas production is low and very low, the result for the environmental and intelligence model is high. After that, Anzali port, was considered as a real model and the results is obtained as Figure 12. It indicates that the organization of this port is not ready to implement the designed model.
Conclusions and Discussion
Evaluating the efficiency of ports in terms of compliance with green and intelligence indicators is very important and strategic. (Tabrizi, 2023) In this study, first the main indicators for evaluating green and smart ports were identified through a library study and a thematic analysis system, and then the conceptual model of the research was drawn. Each indicator was evaluated based on the fuzzy inference, and finally all indicators were embedded in the form of a final model in FIS, which can be implemented for the first time in the country's port business. In this regard, it was implemented in Anzali Port as a real example and conclusions were drawn. It is necessary that the issue of greenness or the environment of ports be given priority attention by ports of countries, because for international communications especially European ports, the greenness of ports is of great importance. The issue of greenness of ports is put on the agenda, and the need to implement smart indicators in ports requires more attention, because in analyzing the indicators by fuzzy inference and also implementing the model on the real example, it shows that the smartness component is given little importance in the country's port business, which is hoped to be resolved separately. Therefore, evaluating the efficiency of ports in terms of compliance with green and intelligence indicators is very important and strategic.
Keywords: Transit Ports, Intelligent Factors of Port Business Management, Green Factor, Thematic Analysis, Fuzzy Inference.
Management approaches in the field of smart
Elnaz Valizadeh Hamzekolaei; Ameneh khadivar; Fatemeh Abbasi
Abstract
Abstract
Social networks have become vital for sharing opinions and feelings through user-generated content. Many organizations leverage analytics to enhance decision-making, yet most sentiment analysis studies focus on commercial businesses, neglecting non-profits despite their significant social media ...
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Abstract
Social networks have become vital for sharing opinions and feelings through user-generated content. Many organizations leverage analytics to enhance decision-making, yet most sentiment analysis studies focus on commercial businesses, neglecting non-profits despite their significant social media presence. This research investigates the impact of user-generated content on the financial performance of non-profit organizations using a dataset of 26,714 tweets from 23 accounts. Results indicate that while positive emotions do not affect financial performance, negative emotions and retweets harm it, whereas likes positively influence revenue. Future research should explore additional social networks and broader data collection methods.
Introduction
Free market societies comprise three main sectors: the public sector, the private business sector, and private non-profit organizations, collectively known as the "three-sector economy" (Weisbrod, 1975). Non-profit organizations are characterized by being organized, private, self-managed, non-profit distributing, and voluntary (Salamon et al., 1996). This research focuses on non-profits dedicated to animal welfare, which aims to prevent animal abuse and ensure proper care (Navigator Charity, n.d.). Recently, these organizations have gained prominence and significantly influenced societal modernization (Lee & Nowell, 2014). Evaluating their performance is crucial for enhancing efficiency amid increasing competition for funding. Given the challenges of measuring performance in non-profits, this study employs sentiment analysis of user-generated content on Twitter to assess organizational effectiveness.
Research Question(s)
How is the performance of non-profit organizations evaluated using user opinion analysis?
Literature Review
This literature review examines existing studies relevant to the research topic and identifies gaps that necessitate this investigation. Non-profit organizations generate revenue and publish annual financial statements (Rathi et al., 2016). They increasingly use social networks to engage with stakeholders (Lai et al., 2017), producing content that can yield valuable insights through user opinion analysis (Miller, 2011). Social networks enable these organizations to gather stakeholder feedback, enhancing decision-making (Waters & Lo, 2012). Non-profits typically focus on measuring performance through donor revenue and budget progress, emphasizing the importance of both financial and non-financial metrics (Epstein & McFarlan, 2011; Kaplan, 2001).
Research has explored the effects of user-generated content on the performance of both non-profit and for-profit organizations. For instance, studies have shown that Twitter content can predict sales for commercial enterprises (Liu et al., 2016) and that negative user messages elicit more responses, prompting businesses to adapt their communication strategies (Hewett et al., 2016). Additionally, analysis of user content has identified key factors influencing millennial engagement online (Saura et al., 2019). Another study linked customer feedback on Twitter to satisfaction and dissatisfaction factors in the hotel industry (Xu et al., 2017), while research demonstrated that emotions in text comments significantly affect product sales performance (Li, 2018).
In non-profit contexts, stakeholder-generated content can enhance participation strategies (Saxton & Waters, 2014), and increased social campaign popularity correlates with heightened discussion (Tayal & Yadav, 2016). However, most existing research focuses on emotional impacts on specific campaigns rather than overall organizational performance, revealing a significant gap. This study aims to fill this gap by evaluating non-profit performance through sentiment analysis of social media content, presenting an innovative model that incorporates econometric methods. Thus, this research represents a novel contribution to understanding non-profit performance evaluation.
Methodology
This study examines selected non-profit organizations evaluated through "Charity Navigator," a prominent charity evaluator in the United States. To refine our sample and focus on larger, more active organizations on social media, we began with a pool of 9,000 non-profits and used advanced search filters (see Table 1) to identify 60 organizations. From this group, five organizations were randomly chosen for further analysis.
Table 1. Title of filters for advanced search of non-profit organizations on charitynavigator website
The title of the characteristics of non-profit organizations
Characteristics of non-profit organizations
Social network
Twitter
Select category-type
Place
Income
Site ranking
Work area
Animals - rights, welfare and services to animals
The entire United States of America
No restrictions
No restrictions
international
Data collection involved manually extracting financial reports detailing total income for each organization from 2010 to 2020 via the "ProPublica" website. We also identified 23 English-language Twitter accounts related to these organizations, from which we gathered tweet data using a Python-based web crawler.
Data preprocessing included removing non-English texts, hashtags, mentions, URLs, punctuation, and stop words, as well as performing tokenization and lemmatization. This resulted in a dataset of 22,829 tweets from the five selected non-profits.
Data Visualization
Word Cloud: We generated a word cloud using the hyperwords package in Python, displaying the 50 most frequently used words, with their size reflecting usage frequency.
Topic Modeling: To explore underlying topics in the tweets, we applied Dirichlet’s hidden allocation algorithm, identifying five main themes:
Vegetarian education
Addressing cruelty and rescuing animals
Animal protection
Monitoring organizational actions
Supporting organizational activities
Results showed vegetarian education was the most discussed topic, while support for non-profits was the least frequent, indicating users prioritize other issues.
Sentiment Analysis
We conducted sentiment analysis using a vocabulary-based approach. Texts were standardized to lowercase, and stop words and punctuation were removed. A dataset of 1,000 tagged examples was used to evaluate sentiment accuracy.
Econometric Analysis
This research assesses how user-generated content on Twitter impacts the annual income of non-profits. After necessary tests and model estimation using Evioz 10 software, we evaluated the effects of independent variables on total revenue, summarized in Table 2.
Table 2. Variables used in the model
Mathematical symbol
English symbol
Mean
1
y
Total Revenue
Total Revenue
X1
X2
X3
X4
X5
Volume
Neg
Positive
Retweet
Favorite
Volume of tweets
Negative sentiments
Positive sentiments
Number of retweets
Number of favorits
The regression model is expressed as:Total Revenue = αi + β1X1it + β2X2it + β3X3it + β4X4it + β5X5it + eit
We conducted Chow or Flimer tests to determine data structure and used Fisher’s test for the unit root test, confirming stationarity at a 95% confidence level.
Model Estimation
Using the OLS method, we found the model significant at the 95% confidence level, with a coefficient of determination of 0.512638, indicating that over half of the variability in total revenue is explained by the model. The Durbin-Watson statistic indicated no autocorrelation among residuals.
Results showed a significant relationship between Twitter content and financial performance. Negative sentiments and retweets inversely affected financial outcomes, while likes positively correlated with revenue, indicating active support from followers. No significant relationship was found between tweet volume or positive sentiments and financial performance.
Results
The results show that users' opinions have a significant impact on the financial performance of these organizations. Therefore, non-profit organizations should pay special attention to their users and donors to increase their satisfaction. Otherwise, the lack of proper management of the organization's actions can damage its credibility. Also, there is a need for further investigation to determine the cause of the negative relationship between the number of retweets and financial performance of organizations. Modeling of topics discussed by users shows that managers of non-profit organizations should focus more on building trust among their users, because the results of topic modeling show that support for the organization is the least frequent.
Keywords: Sentiment Analysis, Nonprofit Organizations, Topic Modeling, Social Network, Panel Data.
Management approaches in the field of smart
Mohammadakbar Sheikhzadeh; Mohammad Taghi Taghavifard; iman raeisivanani; Jahanyar Bamdadsoofi
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 ...
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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
vahid khashei varnamkhasti; Mahdi Ebrahimi; Shahram Khalil Nezhad; Fatemeh Motahari nejad
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 ...
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.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
vahideh alipoor; Mohammadreza Saadi; atefeh mehri bazghaleh
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 ...
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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.
Management approaches in the field of smart
Kamran Feizi; Hormoz Mehrani; Hossein Vazifehdoost; Ehsan Sadeh
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 ...
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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
Hosein Rahimi kolour; Rahim Mohammad khani
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 ...
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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 sales
Introduction
Most 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 Review
Artificial 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).
Methodology
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 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.
Results
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.
Discussion and Conclusion
The 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
Ghasem Zarei; Rahim Mohammad khani
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 ...
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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
Manuchehr Karbasi; Ghanbar Abbaspour Esfeden; Seyedeh Sedigheh Jalalpour; Peyman HajiZadeh
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 ...
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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
Soroush Ghazinoori; Sohrab Aghazade Masroor; Mohamad Naghizadeh; Mojtaba Hajian Heidary
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 ...
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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.
Management approaches in the field of smart
Atieh Moghaddam Monfared; Abbas Toloie Eshlaghy; Reza Ehtesham Rasi
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 ...
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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
Mojtaba Ahmadi; Alireza pourebrahimi; Ladan Riazi; Seyed Abdollah Amin Mousavi
Abstract
In this paper, the challenges to the implementation of the IT audit process in Iran's banking network have been identified through a number of case studies in four large Iranian banks. The data has been collected through conducting 20 interviews with experts in both IT management and IT audit fields ...
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In this paper, the challenges to the implementation of the IT audit process in Iran's banking network have been identified through a number of case studies in four large Iranian banks. The data has been collected through conducting 20 interviews with experts in both IT management and IT audit fields of the mentioned credit institutions, and reviewing some of their internal documents. In this research, 20 cases of the main challenges and problems in the implementation of the IT audit process were identified. The findings of the research showed the existance of "Lack of independence and existence of common financial interests", "Inability to establishing communication between IT audit unit and IT unit", "Inappropriate organization and administrative structure of the entity under audit", "Lack of specialized information technology knowledge and necessary capabilities" information technology audit", "insufficient experience and inappropriate records of information technology auditors", "lack of valid training courses and lack of auditors having valid international certificates and documents of information technology audit" and "insufficient self-confidence of auditors", are among the main challenges to the implementation of the audit process that is considered information technology.
Introduction
In this paper, the challenges to the implementation of the IT audit process in Iran's banking network have been identified through a number of case studies in four large Iranian banks. The data has been collected through conducting 20 interviews with experts in both IT management and IT audit fields of the mentioned credit institutions, and reviewing some of their internal documents. In this research, 20 cases of the main challenges and problems in the implementation of the IT audit process were identified. The findings of the research showed the existance of "Lack of independence and existence of common financial interests", "Inability to establishing communication between IT audit unit and IT unit", "Inappropriate organization and administrative structure of the entity under audit", "Lack of specialized information technology knowledge and necessary capabilities" information technology audit", "insufficient experience and inappropriate records of information technology auditors", "lack of valid training courses and lack of auditors having valid international certificates and documents of information technology audit" and "insufficient self-confidence of auditors", are among the main challenges to the implementation of the audit process that is considered information technology.
Among the most effective ways of evaluating and crediting the financial and management reports calculated with the help of information technology tools is information technology audit. Today, information technology control and audit have become an important mechanism to ensure integrated information systems and financial reports of organizations to prevent heavy financial failures in the future.
According to the Central Bank regulations, Iranian banks have been required to perform the information technology audit process and provide related reports in accordance with the ISACA ITAF. The evaluation shows unfavorable results. According to the issues raised, this research tries to use Stoll and Havelka's model (Stoll and Havelka, 2021), which lead to the successful implementation and improvement of information technology audit quality, including "organizational factors", "control factors" and "Individual factors of the auditor" has been devoted to the detailed analysis of problems, challenges and enabling and inhibiting factors in the field of challenges of implementing the IT audit process in the banking network of Iran.
Literature Review
"Information technology audit" is the inspection of the organization's IT systems and infrastructure to ensure that standards and guidelines are followed, documented, have the necessary efficiency, and operate effectively in line with business goals (ISACA, 2015a). The need for optimal implementation of the IT audit process has been recognized by many researchers as the main concern of many organizations today. Studies have mainly focused on IT audit concepts, dimensions, patterns and frameworks that can be used to properly implement the IT audit process. In this paper, considering that our focus is on reviewing IT audit challenges, articles have been reviewed and evaluated that mostly deal with the main challenges that most organizations face in this field. Information technology audit in banks is different from other organizations due to the sensitivity of business, complexity of operations, unique regulations, different characteristics and security needs, high-risk environment, the importance of maintaining customers' financial information and data confidentiality, and auditors should pay attention to General frameworks should be used to review and evaluate the information technology field of banks using the specific security standards and regulations of this industry.
Methodology
In the first stage, it has been helped to review the theoretical foundations and extract categories, concepts and key codes of the challenges of implementing the information technology audit process, and then in the second stage, each of the mentioned categories, concepts and key codes, according to the information obtained from the face-to-face interviews It has been analyzed with the participants and experts' opinions of both information technology and information technology audit. In order to accurately assess the problems, challenges and enabling and inhibiting factors in the optimal implementation of information technology audit, the information technology area of 4 Iranian banks (as a representative of four types of banks in the country including: government commercial, specialized government, semi-private and fully private), to conduct a case study has been selected. The current research is fundamental-applied in terms of research directions and a case study in terms of research strategy. The main tool for collecting information and data is through interview, observation and review of collected documents and documents, and therefore its approach is qualitative.
Results
The categories, concepts and the number of 20 key codes regarding the challenges of implementing the IT audit process were extracted based on the research literature and Stoll and Havalka's model (2021) and according to the information obtained from the interviews with the participants and the opinions of experts in both IT fields and Information technology audits were analyzed. The results indicate that "Lack of independence and existence of common financial interests", "Inability to establish communication between the information technology audit unit and the information technology unit", "Inappropriate organization and administrative structure of the entity under audit", "Lack of specialized information technology knowledge and capabilities" The necessity of information technology audit", "Insufficient experience and inappropriate records of information technology auditors", "Lack of valid training courses and lack of auditors having international valid information technology audit certificates and documents" and "Insufficient self-confidence of auditors", are among the main challenges of implementing the process. It is an information technology audit.
Discussion and Conclusion
Information technology audit is the main way to measure the effectiveness of information technology services, guarantee its efficiency and avoid threats and risks. In this paper, the challenges of implementing the IT audit process in Iran's banking network were identified through a case study in four large Iranian banks. The data has been collected by conducting twenty 45-minute interviews with experts in both IT management and IT audit fields of the mentioned credit institutions and reviewing some of their internal documents. In this research, 20 cases of the main challenges and problems of implementing the IT audit process were identified. Recognizing these challenges, while providing the background for future studies regarding the formulation of IT audit implementation frameworks and models for researchers, helps credit institutions to identify these challenges and take effective measures to implement the IT audit process. The study of this research included only four Iranian banks, which of course are among the large and complex organizations; However, it limits the generalizability of the results to other organizations and businesses, which is one of the limitations of this research.
Keywords: Information Technology Audit, Information Technology Inspection, Iranian Banking Industry, Audit Implementation Challenges, Internal Audit.
Management approaches in the field of smart
maryam ahmadi; Mehran Ziaeian; Hajar Soleymanizadeh
Abstract
Nowadays, intelligence and industry 4.0 has been the focus of many industries due to its various benefits such as tracking raw materials and manufactured products, reducing costs, etc. One of the most important factors in facilitating the implementation of Industry 4.0 is human resources. The purpose ...
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Nowadays, intelligence and industry 4.0 has been the focus of many industries due to its various benefits such as tracking raw materials and manufactured products, reducing costs, etc. One of the most important factors in facilitating the implementation of Industry 4.0 is human resources. The purpose of this research is to investigate the role of human resources on the implementation of Industry 4.0 in the steel industry of Yazd. Using research literature, 13 factors related to human resources affecting the implementation of Industry 4.0 have been identified. In the following, by using the fuzzy Delphi approach and selecting 17 university professors and managers of Yazd steel industry by snowball sampling and asking for their opinions, three factors of continuous learning ability, data analysis and business intelligence, and security and privacy protection weren’t confirmed. Also, based on the request of the authors of the research from the related experts, by adding factors related to the implementation of Industry 4.0, three factors of freedom of action in doing work, sufficient time to do work, and innovation and creativity were introduced. Finally, the cause-and-effect relationships between the factors were investigated using the fuzzy DEMATEL approach. The results showed that cooperation and interaction are the most important factors for the implementation of Industry 4.0 in Yazd steel industry. Perceived usefulness and recruitment of skilled labor are known as the most effective factors, and innovation, creativity, learning, and empowerment are known as the most effective factors on the implementation of Industry 4.0.
Introduction
The steel industry is known as one of the vital and very important industries in the world and especially in Iran. Despite the importance of the steel industry in the country, this industry faces many challenges and problems such as the supply of resources and raw materials (Soltanzadeh, Rahmani, & Majidpour, 2024), high production costs and the increase in the price of raw materials (Morshedi, Nezafati, & Shokouhyar, 2023), lack of global standards in the quality of manufactured products (Pourmehdi, Paydar, Ghadimi, & Azadnia, 2022) and...
To answer these challenges, the country's steel industries, including the Yazd steel industry, seek to provide effective solutions for survival, entering global markets and surpassing competitors. One of the most accepted approaches among manufacturing companies in recent years to face the mentioned challenges is Industry 4.0. The use of Industry 4.0 technologies brings various advantages such as predicting errors, minimizing environmentally destructive activities, tracking raw materials and manufactured products, etc. Despite the benefits of Industry 4.0 and the increasing interest in it from researchers and managers of various industries, there are vague perceptions regarding the adoption and deployment of Industry 4.0 (Morovati Sharifabadi, Ziaeian, Mirfakhradini, & Zanjirchi, 2024). Many authors state that the implementation of Industry 4.0 is a difficult task and faces various problems and challenges, including scientific, technical, economic, social, human resources, and even political issues (Wankhede & Vinodh, 2021). Among the mentioned factors, one of the most important factors for establishing Industry 4.0 is human power (Ziaei Nafchi & Mohelská, 2021). The purpose of the current research is to investigate the role of human resources in the establishment of Industry 4.0 technologies and the intelligentization of Yazd steel industry.
Literature Review
The term Industry 4.0 was first introduced in November 2011 by the German government at the Hanover Trade Fair (Frank, Dalenogare, & Ayala, 2019). Industry 4.0 aims to connect the physical and digital worlds, decentralize business processes, intelligentize product production processes and provide services using advanced technologies such as the Internet of Things, blockchain, cyber-physical systems (Entezirian)., & Mehraeen, 2024) and ... in order to simplify production processes, monitor production at any place and time, increase productivity, efficiency and profitability (Javaid, Haleem, Singh, Suman, & Gonzalez, 2022) ). Saniuk et al. (2023) investigated the knowledge and skills of industrial and managerial employees for the implementation of Industry 4.0. The results of this research showed that employees' knowledge and skills, creativity and innovation, employees' resistance to changes are among the most important factors affecting the establishment of Industry 4.0 (Saniuk, Caganova, & Saniuk, 2023). In a study, Verma and Venkatsan (2022) investigated human resource factors for the successful implementation of Industry 4.0. The results of this research showed that training, recruitment, job design, performance evaluation and health and safety of employees are among the most important factors in the establishment of Industry 4.0.
Methodology
The present research is practical in terms of its purpose, because its results can be used in various industries and organizations to demand the establishment of Industry 4.0. Also, this research is descriptive-causal in terms of nature and method, and survey in terms of data collection. In this research, in order to identify the final influencing factors related to human resources on the establishment of Industry 4.0 technologies and the intelligentization of industries, the fuzzy Delphi approach has been used. In the following, in order to present the cause-and-effect relationship between the identified factors, the fuzzy DEMATEL approach has been used.
Results
In this research, by studying the literature, work motivation factors, work commitment, technical and engineering knowledge, cooperation and interaction, learning and empowerment, system thinking, continuous learning ability, data analysis and business intelligence, security and privacy protection, receiving salaries according to Activity, perceived usefulness and perceived ease were identified as factors related to human resources affecting the establishment of Industry 4.0. In order to verify the identified factors, university experts and Yazd steel industry managers were consulted using the fuzzy Delphi approach. Based on the results obtained from the fuzzy Delphi approach, three factors of continuous learning ability, data analysis and business intelligence, and security and privacy preservation were not confirmed due to the de-fuzzified value lower than the threshold (0.6). In addition, the three variables of freedom of action in the work, sufficient time to do the work and innovation and creativity were introduced by the experts and confirmed in the second stage of asking their opinions. Based on the results of the fuzzy DEMATEL approach and considering the highest value of R+J for cooperation and interaction, this factor was recognized as the most important factor related to human resources in the establishment of Industry 4.0 in Yazd steel industry.
Keywords: Fourth Industrial Revolution, Industry 4.0, Human Resource Management, Fuzzy Delphi, Fuzzy DEMATEL.
Management approaches in the field of smart
Pegah Ghasemi Ghonchehnazi; Ali Atashsooz
Abstract
Technology-based reforms with an emphasis on digital society (especially in the public sector) have been placed on the agenda of most countries and have become a major challenge for governments. One of the most important strategic tools of organizations in this field is "digital leadership". The main ...
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Technology-based reforms with an emphasis on digital society (especially in the public sector) have been placed on the agenda of most countries and have become a major challenge for governments. One of the most important strategic tools of organizations in this field is "digital leadership". The main purpose of the current research is to explain the role of digital leadership and its impact in creating digital transformation in Telecomunication Infrastracture Company. The statistical population of this research includes experts and senior experts of the studied organization, who were selected by a judgmental method. First, the dimensions and elements of digital transformation leadership were examined, and in order to examine the components of digital transformation leadership, as well as to set research questions and create a review protocol. The guiding principles of Xiao and Watson (2017) were used. Data collection was done through a questionnaire. Cronbach's test was used to measure the reliability of the questionnaire and Kendall's coefficient was used as an index of coordination and agreement. The results showed that the constructive dimensions of the concept of digital transformation leadership have a significant impact on creating digital transformation, and among them, Leader's digital expertise and giving importance to customer experience have the most impact.
Introduction
In the digital age, due to the emergence of new technologies and technologies, the traditional beliefs of business have fundamentally changed. Chaotic conditions caused by fundamental changes in the organization, uncertainty, lack of transparency of investment consequences and high cost of investment have prevented many organizations from entering this field (Osterrider et al., 2020). Organizations have undergone changes as one of the economic and social ecosystem elements. Therefore, in order to respond to these expectations, organizations must put fundamental changes in their agenda, which is the strategic tool of organizations in this field, "digital leadership" (Enak & Dharma, 2020). This research aims to identify the dimensions of digital transformation leadership and in order to better understand this iss Anak ue from a managerial point of view, to show the components of each factor in the form of the organization's digital transformation leadership framework.
Literature Review
Digital transformation is the application of new technologies in the three internal, external and overall dimensions of an organization. Three stages for digital transformation, which include the transition to digitalization, the digitization stage, and the digital transformation stage, are proposed, and each stage shapes specific requirements for digital resources, organizational structure, growth strategies, and performance standards (Verhoef et al., 2021).
Digital leadership includes two important dimensions of digital maturity, including what technology is (as digital capabilities) and how to lead change (as leadership capabilities). Digital capabilities include creating a pleasant digital experience for customers, improving internal processes and reinventing the business model, and leadership capabilities that include the ability to create a digital vision, engage all employees enthusiastically, focus on digital governance, and technology leadership capabilities (Westerman et al., 2014). Combining the three factors of vision, engagement and management creates a strong prescription for digital leadership. These three factors create synergy with each other and each reinforces the other over time. The fourth powerful leadership factor is technology. Four dimensions of digital transformation achievements and indicators that are evaluated in these dimensions in order to explain the role of digital leadership in the organization can be evaluated in the cases of business model (ecosystem), processes, customer experience and employee experience (Nadeem et al., 2018).
Muller et al. (2024) described the competencies that business leaders need to facilitate digital transformation. Based on a literature review, they identified four distinct sets of competencies that leaders need under different circumstances in a portfolio model labeled challenger, executive, organizer, and challenger. Yao et al. (2024) in research entitled the influence of digital leadership on digital transformation showed that digital leadership has a positive effect on digital transformation and digital strategic consensus plays a mediating role in this relationship. In research conducted by Tigre et al. (2023) based on bibliometrics and network analysis, they stated that few retrospective studies have been conducted in this field and this topic continues to attract more research because it has not yet entered its maturity stage. is in another study, Bonnet and Nandan (2021) believe that today's leaders are constantly facing new challenges so that they must adapt their organization and leadership style to the new environment. In addition, the key role of leaders in shaping the identity of the organization in the digital age and the need for forward-looking design and its active movement are felt today more than ever.
Methodology
A literature review and Delphi method were used in a mixed design. In order to identify the components of digital transformation leadership, as well as to set research questions and create a review protocol, Xiao and Watson (2017) guiding principles have been used. The eight-step systematic review process was implemented, leading to the execution phase. Ninety-two studies related to the research were selected, and conceptual elements were identified. Using Shannon’s entropy, the support from previous studies for the conceptual elements of digital transformation leadership and their importance were calculated. The synthesized findings were used in the initial framework, which informed the Delphi study. Quality assessment, as a screening factor for refining articles, employed the Okoli and Pawlowski method in the current research. Fourteen experts in digital transformation-related domains were selected for participation in the Delphi panel. The initial research framework was developed based on panel opinions, and Kendall’s coefficient was used to assess consensus. Questionnaires were prepared, and three rounds of question distribution were conducted, incorporating feedback to apply new indicators and remove redundant ones. Kendall’s coefficient determined the level of agreement among opinions.
Results
To analyze the data, the Delphi method was implemented in three rounds. The first round of Delphi questionnaire, which includes one section, was given to 14 panel members. Adopting digital technologies, focusing on the impact of digital technologies on customer behavior, strategic use of the organization's digital resources, new capabilities and competencies for leadership, the ability to establish governance in the digital age, analysis and having experience in management layers. Organization, technology leadership ability, etc. are among the results of the first round of the Delphi method.
In the second round, the final indicators of the research, which were designed in the form of a questionnaire, were sent to the experts for evaluation and a summary of the experts' opinions was reported. Kendall's coefficient in the second round is equal to 0.765, which shows the agreement of the experts on the indicators. At this stage, the questionnaire was sent again to the experts for preliminary approval. The third-round questionnaire also included two sections, the survey section and the effective factors section on digital leadership, and its results are shown in below table.
factors
Mean
Standard Err.
Kendall
Acceptance of digital technologies
4.79
0.58
31.32
Changing business models
4.43
0.51
22.39
….
…
…
…
Changing leadership paradigms in the digital arena
4.43
0.65
23.07
…
…
…
…
Focus on digital governance
4.71
0.61
30.40
Technology leadership
4.43
0.51
21.89
Kendall Coeff.
0.599
Discussion
The results showed that the constructive dimensions of the concept of digital transformation leadership include the adoption of digital technologies, changing business models, focusing on the impact of digital technologies on customer behavior, digital attitude and behavior, using digital technology to facilitate transformation and changes. Alignment between technology, process and employees, strategic use of the organization's digital resources, changing leadership paradigms in the digital arena, alignment of the organization with digital transformations, deep understanding of customers, ability to understand technology and business, new capabilities and competencies for leadership, management and supervision Digital transformation is the ability to establish governance dimensions in the digital age. Although the expansion of communication and technology can be a threat to some businesses.
Conclusion
It is clear that leading and keeping up with the digital age depends on the capacity and potential capabilities of organizations. Therefore, each of the indicators identified in this research can play an important role in creating digital transformation in the organization. According to the results of the research it is suggested to the organizations that in order to achieve the goals of digital transformation programs, they employ leaders and managers who have digital leadership abilities like what was identified in this research.
Keywords: digital leadership, digital transformation, digital maturity, digital governance
Management approaches in the field of smart
Mehrdad Mehrkam; zakieh nasimi
Abstract
Taxation is one of the vital aspects of development in countries and plays an essential role in advancing the economic progress of countries. For this reason, different countries of the world implement comprehensive plans to improve and transform their tax systems. This study was conducted ...
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Taxation is one of the vital aspects of development in countries and plays an essential role in advancing the economic progress of countries. For this reason, different countries of the world implement comprehensive plans to improve and transform their tax systems. This study was conducted with the aim of evaluating the leadership style of managers on digital transformation among senior and middle managers of the country's tax affairs organization.A random sample of 44 expert managers was selected. This study used Smart-PLS software for data analysis and was conducted in the summer of 1402. The findings of the study showed that the leadership style of the managers and the digital transformation strategy have an impact on the digital transformation of the tax organization. In other words, it was found that the digital transformation strategy significantly mediates the relationship between managers' leadership style and digital transformation, not a moderating role. In addition, the results showed that managers' leadership style and digital transformation strategy have the greatest impact on digital transformation. have The obtained findings have shown that the proposed hypotheses are acceptable.
Introduction
In today's global landscape, digital transformation is paramount for organizational success. Even government bodies are revamping their tax systems to adapt to evolving environments. However, challenges like skill shortages and resource constraints impede progress. Nonetheless, integrating digital transformation technologies offers numerous benefits, such as enhanced transparency and innovation. Failing to keep up with technological advancements can lead to organizational obsolescence. Thus, thriving in competitive markets requires adeptness in digital transformation, innovation, and emerging technologies, supported by robust implementation strategies.
Literature Review
Digital transformation, as a managerial strategy, revolutionizes organizational operations and processes through the integration of digital technologies. These changes encompass the overhaul of products, business procedures, sales avenues, value chains, and business models. Beyond internal and external organizational shifts, digital transformation extends to establishing a distinct market presence both presently and in the future. Embracing this transformation necessitates the organization's agility in adopting new technologies and implementing comprehensive measures. However, digital transformation initiatives must transcend mere technological integration and instead prioritize process re-engineering and alignment among technology, processes, and personnel. Effective leadership and adept change management capabilities are also crucial components in this transformative journey.
2-1- The relationship between digital transformation and the leadership style of managers:
Digital transformation, as an organizational shift towards digital institutional frameworks, hinges on the legitimacy of the organization's belief system. Managers are pivotal in driving the success of this transformation; through strategic programs and effective leadership, they steer organizations toward digital evolution. The leadership style adopted by managers holds significant sway in this process, with studies indicating that a transformational leadership approach yields positive impacts on both organizational innovation and performance. Consequently, the text proposes a hypothesis asserting that managers' leadership style exerts a positive and noteworthy influence on digital transformation.
2-2- The relationship between digital transformation and digital transformation strategy:
Amidst the era of digital transformation, the significance of a well-crafted strategy for managing institutional change is underscored. Digital transformation is characterized as a dynamic and ongoing process necessitating a thorough reassessment of operations, strategy, leadership capabilities, innovation, and business models. In this context, the formulation of a digital strategy, encompassing both corporate and business strategies, emerges as a primary driver of success in digital transformation endeavors. Consequently, a hypothesis is posited, asserting that the digital transformation strategy exerts a positive and substantial impact on digital transformation outcomes.
2-3- The relationship between managers' leadership style and digital transformation strategy:
This text emphasizes the crucial role of the Chief Digital Officer (CDO) in operationalizing digital strategy and ensuring its alignment with the company's mission and goals. Ineffective implementation of digital strategy by senior managers and employees hinders reaping benefits from digital transformation. Successful utilization of digital transformation requires organizations to develop robust digital strategies and drive digital transformation efforts under senior executives' leadership. The text presents a hypothesis asserting that managers' leadership style significantly and positively affects digital transformation strategy.
2-4- Digital transformation strategy mediation:
The text highlights the significance of a well-designed and efficiently executed digital transformation strategy in guiding organizational digital transformations. Additionally, it proposes a hypothesis suggesting that the digital transformation strategy serves as a mediator in the relationship between managers' leadership style and the organization's digital transformation.
2-5- Moderation of digital transformation strategy:
The text defines digital strategy as a series of strategic IT and information systems actions directed by managerial decisions regarding the utilization of current infrastructure. It suggests that even if managers excel in handling risk and uncertainty, if their actions don't align with existing strategies, digital transformation might not yield desired outcomes. Consequently, the text hypothesizes that the digital transformation strategy moderates the relationship between managers' leadership style and the organization's digital transformation.
Methodology
Type of Research: This research is applied and descriptive-survey in nature, aimed at examining the relationship between managers' leadership style and digital transformation.
Population and Sample: The statistical population includes 50 middle and senior managers of the country's tax affairs organization. Based on Morgan's table, 44 managers with sufficient knowledge of digital transformation processes were selected as the sample. Simple random sampling was used to select the managers.
Data Collection Tools: Data were collected through semi-structured interviews and questionnaires. The interviews aimed to identify the managers' level of knowledge about digital transformation and the existing challenges. The questionnaires included both closed and open-ended questions and assessed various aspects of leadership style and digital transformation strategy.
Findings: The results indicated that the level of familiarity of managers with digital transformation concepts varies, and this difference depends on factors such as work experience and managerial role.
Data Analysis Method: For data analysis, structural equation modeling using Partial Least Squares (PLS) was employed. This method includes two models: the measurement model (examining the relationship between observable and latent variables) and the structural model (investigating the relationships among latent variables).
Results
This study emphasizes the dual nature of digital transformation, presenting both challenges and opportunities for organizations, including government bodies like tax authorities. The implementation of the taxpayer system serves as a successful example of digitalizing tax processes, demonstrating how technology can improve efficiency and transparency while minimizing redundancy. The role of managers in driving digitalization is crucial, requiring adept leadership and strategic approaches. Furthermore, the study highlights the digital transformation strategy's pivotal role as a mediator between managers' leadership style and organizational digital transformation. However, the finding that the strategy does not moderate this relationship suggests a nuanced perspective influenced by research context and environmental factors. Overall, the text underscores the importance of digital transformation for organizational success, advocating for strategic planning, effective leadership, and prudent technological adoption.
Figure 1. Conceptual model
H3
H4
H1
H2
Leadership style of managers
Digital transformation
Digital transformation strategy
5.conclsion
According to the statistical results, one of the factors that influence the digital transformation is the leadership style of managers. Organizational managers directly influence digital transformation; Therefore, managers should provide the necessary platform for moving towards digitalization for the employees and the organization so that the organization can move in this direction.
As the statistical results showed, digital transformation strategy has an impact on digital transformation. When organizations are going to move towards digitalization, they must abandon their traditional processes and change them to modern ones; Therefore, in order to do this correctly, the strategy of the organization needs to be changed and designed according to the new goals of the organization, which is digitization, so that the organization can move in the right direction. In the absence of a suitable strategy, the organization will deviate from its path and digitization will not happen.
Finally, we used a cross-sectional research design while the discussion of digital transformation and digitalization happens over time; Therefore, it is suggested to use a time study to examine the growth of digital transformation implementation and capture the lessons learned over time.
Keywords: Managers' Leadership Style, Digital Transformation, Digital Transformation Strategy, Tax Affairs Organization.
Management approaches in the field of smart
Shiva sadat Ghasemi; Abbas khamseh; Seyed Javad Iranban
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 ...
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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.
Introduction
In 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 Review
In 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.
Methodology
Employing 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.
Results
The 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 1. Factors Affecting AI-Based Technology Scouting
Category
Subcategory
Concepts
Technology Scouting Tool
Open Source Intelligence (OSINT) Tools
Web scraping tools, social media monitoring, online forums, patent databases, news aggregators, competitive intelligence tools, and data analytics platforms.
Machine Learning and AI Tools
Natural Language Processing (NLP), predictive analytics, pattern recognition, chatbots, sentiment analysis, machine learning, and cognitive computing tools.
Collaboration and Communication Platforms
Online collaboration tools, project management platforms, virtual team collaboration, idea management, crowdsourcing, communication apps, and workflow automation.
Technology Life Cycle
Innovation and Invention
Idea generation, R&D, concept testing, prototyping, patenting, technology transfer, proof of concept, funding, collaborative research, and feasibility studies.
Technology Adoption and Diffusion
Technology readiness, market analysis, adoption theories, market penetration, standardization, compliance, user testing, and overcoming adoption barriers.
Technology Evolution and Obsolescence
Continuous improvement, iterative development, versioning, obsolescence management, legacy systems, discontinuation planning, sustainability, disruptive tech, and sunset planning.
Company Environment
Competitive Landscape Analysis
Competitor mapping, SWOT analysis, industry benchmarking, market share analysis, competitive intelligence, PESTLE analysis, collaboration strategies, positioning, and sustainable advantage.
Regulatory and Legal Environment
Intellectual property management, standards compliance, regulatory impact, patent landscape analysis, legal risk, data protection, ethics, antitrust, government policies, and international regulations.
Internal Organizational Environment
Culture, cross-functional collaboration, governance, change management, talent, agile structures, infrastructure, decision-making, metrics, and employee engagement.
The Company's Approach in Facing the Environment
Innovation Strategy Formulation
Roadmapping, open innovation, blue ocean strategy, core competency analysis, innovation ecosystems, portfolio management, ambidextrous approach, horizon scanning, lean methodologies, and design thinking.
Adaptive and Resilient Practices
Crisis 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 Partnerships
Collaborative innovation, joint ventures, technology ecosystems, university-industry collaborations, innovation networks, open source, licensing, technology transfer, competition, and strategic partnerships.
Absorption Capacity of the Company
Learning and Knowledge Management
Organizational learning, knowledge creation, sharing platforms, communities of practice, intellectual capital, training programs, technology scouting, learning culture, and tacit knowledge transfer.
Resource Allocation and Utilization
Technology budgeting, allocation models, ROI analysis, portfolio management, cross-functional sharing, resource efficiency, project prioritization, dynamic reallocation, innovation finance, and risk management.
Adoption of Emerging Technologies
Scanning trends, piloting new tech, foresight methodologies, early adoption, readiness assessments, and collaborative ecosystems for adoption, mitigating risks, cross-functional teams, integration, and continuous monitoring.
Discussion
To 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.
Conclusion
The 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.
