Journal of value creating in Business Management

Abstract The aim of this research is to design a marketing process model for customer relationship management in digital platforms of the banking industry. The research method is applied in terms of its purpose and qualitative in terms of its implementation. The statistical population of the study included 16 marketing experts, academics, and banking industry managers, selected through purposive or snowball sampling. Semi-structured interviews were used to collect data. Data analysis and coding were conducted in grounded theory. Based on the results of qualitative analysis, five categories of overarching categories were identified, including: causal factors of the customer relationship management model in digital platforms in the banking industry (technology, organizational, individual, technological factors) Phenomenon-oriented factors (electronic channels, company organization, employee empowerment) Strategic factors (electronic marketing, customer interaction, internal exchanges, learning and innovation) Contextual factors (trust-building behavior) Intervening factors (political factors, organizational factors) The outcomes (customer satisfaction and loyalty, customer trust) were identified. The results of the quantitative section, while confirming the research hypotheses, showed that the proposed model has appropriate validity.

Abstract Purpose - This study examines the impact of supply chain capabilities and knowledge management capabilities on the business performance of chain stores with a mediating role of competitive advantage. This study provides the better understanding about key constructs such as supply chain capabilities and knowledge management capabilities that influence Mashhad chain stores business performance.

Design/methodology/approach - This research is applied in terms of purpose, descriptive in nature and method, and survey-causal. Causal research design is used to identify cause-and-effect relationship among the constructs. The authors derive measures of the model from existing literature and expert opinion. Questionnaire method is used to gathering data. The statistical population of the study were managers and employees of finance, marketing, research and development, distribution and information technology, as well as suppliers of different branches of first-level chain stores in Mashhad, Iran, including Shahrema, Refah, Ofogh Kourosh, Hypermi, Bama and Etka. The author develops a conceptual model for the business performance of chain stores. This study uses a quantitative approach to test the proposed hypotheses, using Structural Equation Modeling (SEM) and SPSS and AMOS software.

Findings - Results show that supply chain capabilities significantly influence competitive advantage and business performance, and knowledge management capabilities significantly influence competitive advantage and business performance. Also, competitive advantage mediating the impact of supply chain capabilities and knowledge management capabilities on the business performance.

Originality/value – Almost, no study has examined supply chain capabilities and knowledge management capabilities constructs related to competitive advantage and business performance of Mashhad chain stores. The findings of this study imply several practical directions for them.

Abstract The main objective of this study was to present a coherent model for the role of smart technologies in improving customer relationships so that organizations can use these capabilities to create competitive advantage. This research was, in nature, fundamental-applied research with a mixed exploratory approach (qualitative-quantitative). In the qualitative part, by adopting the grounded theory method (Corbin and Strauss version), they sought to discover relationships and build a theoretical model from empirical data. The statistical population of the research was composed of managers, activists, and expert professors in the field of marketing and the banking industry with at least 5 years of relevant work experience. Data were collected through in-depth semi-structured interviews, and the purposive and theoretical sampling process continued until theoretical saturation was achieved, which ultimately led to interviews with 21 people. Data analysis was conducted in three coding stages (open, axial, and selective). The results of the selective coding showed that the improvement of customer relationships through intelligent technologies was organized around a dynamic, three-level cycle that included organizational and strategic antecedents (such as infrastructure readiness and cultural fit), implementation components (including real-time analysis of interaction data and dynamic customer engagement), and dual outcomes (such as improving the customer’s emotional experience and increasing operational efficiency). The model confirmed that to succeed in intelligent engagement, organizations must first focus on fundamental readiness so that they can achieve outcomes such as intelligent adaptation to customer needs and improved decision-making speed through analytical technologies. Overall, the developed model not only provided a comprehensive theoretical framework for researchers, but also a practical guide for managers to transform intelligent technologies into a sustainable competitive advantage in customer relationship management.

Abstract Abstract The purpose of this research was to investigate the role of Flow theory in viral promotional advergames with an emphasis on sharing personal data and forwarding the games. Using a viral marketing campaign, 393 out of 765 participants clicked on the game link sent via email, But 288 people participated in the game, 141 people answered the questions, invited their friends to the game, or shared their personal data. Poisson regression was used to investigate the role of Flow theory on game forwarding, and logistic regression was used on sharing personal data through Eviews software. Players with intrinsic enjoyment and psychological Flow (dimensions of Flow) tend to invite more people to the game and share more personal data about themselves. Perceived reward value is also positively related to game forwarding behaviors, although not related to sharing personal data. That is, players seem to communicate more about the game when they have extrinsic motivation (rewards), but are less likely to share personal data with the brand. On the other hand, extrinsically motivated players still have significant privacy concerns. In contrast, Flow is positively related to sharing personal data, suggesting that fully immersed players tend to "lose themselves" and forget about their more conscious concerns and thus appear more likely to share personal data with the brand. Companies that want to capture customers' personal data should focus more on designing game elements than rewards in such a way as to stimulate the psychological Flow of the players. Extended Abstract Introduction The implementation of viral marketing in the framework of launching a viral campaign in the form of a video or an attractive content in the form of a game is produced and then advertised online to the target audience. Basically, users are quickly attracted to this ad and share it widely. The virality of an advertisement or message in the form of a game is done randomly and is suddenly welcomed by many people, but the design and implementation of viral campaigns requires a lot of planning and creativity to be able to manage it during the campaign activity, so that it moves on the right track. In this regard, games are an important part of advertising campaigns and have attracted a lot of attention from academics and experts in this field. Previous research has been mostly about in-game advertising or advertising games and the distinction between them (Castiblanco Jimenez, I.A. et al.,2023). Viral Promotional Advergames combine a prize advertising game with an advertising game in a viral marketing campaign aimed at encouraging word of mouth to drive immediate responses and behavioral reactions from players towards goals such as; sharing personal data; forwarding the Game to friends lead to increase consumer knowledge of the brand and improve their attitude towards that brand. In this regard, Mihaly Csikszentmihalyi's Flow Theory (1975) is used, which considers Flow as a special mental state that appears when performing an action, in which the actor focuses on a task in such a way that he has a sense of adherence to, and completely Flows/immerses himself in the work and the satisfaction of the process of doing the work. In fact, he is so engrossed in doing it that he doesn't feel time, place, tiredness, hunger or unhappiness and concentrates on pursuing his work. But when they did the work, they lost that attachment and focus (Lavoie, R., & Main, K. 2019). In fact, the result of the work is not so important for these people, but it is the nature of the work they are doing is important to them. In the current research, it is investigated what factors will lead to such behavior, such as the mental state that these people experience while engaging in their profession and skills, and which is called the Flow state. It is a state in which a person is so engrossed in a task that nothing else matters to him, and this experience is so enjoyable that it is done only for its own sake. No studies have addressed the Flow experience in the context of viral advergames. Flow in the game, including enjoying and disappearing in the game, directs the responses and immediate behavioral reactions of the players towards actions such as forwarding the game and sharing personal data, and in the marketing process it plays as an important strategy for advertising or comprehensive advertising of a brand, product or service(Kim, Yoon Jeon & Ifenthaler, Dirk. 2019). Finally, the main question is how the Flow theory in Viral Promotional Advergames can lead players to forwarding games to friends and others and sharing personal data?. Theoretical framework Games have evolved over time and with the advancement of technology. An emerging form of gamification is designed as part of viral marketing campaigns, where consumers play the gambit to win sales promotions. The target consumers of such games are mostly adults rather than children. During the game, players can increase their chances of winning if they share their personal data or if they invite their friends to play the game. To distinguish this type of game, which is a combination of a promotional game for the purpose of a prize with an advertising game for the purpose of advertising in a viral marketing campaign, the term Viral Promotional Advergames is used. Due to the nature of advertising games, Viral Promotional Advergames often contain advertising messages of a brand and try to increase one's perception of the brand's status and attract positive consumer opinion (Zhao, Z., & Renard, D. 2018). Also, viral advergames are often designed as contests that allow consumers to win prizes due to luck or skill, and are intended to elicit immediate behavioral responses, with the promise of an increased chance of winning if those behaviors are performed. Previous literature describes consumers' cognitive and affective perceptions of different types of games, although it mainly focuses on children as participants. The current research examines adult gamers' behavioral reactions to Viral Promotional Advergames: namely, sharing personal data and Forwarding games. In addition, it examines how the internal and external values of adult players motivate such behaviors. Extensive empirical research confirms that Flow theory influences consumers' cognitive, emotional, and behavioral responses such as attitudes, behavioral intentions, and actual behaviors (Sarkar, J.G., Sarkar, A. and Sreejesh, S. 2023). A few researchers have applied Flow theory to advergames, but no studies have addressed experiences of Flow theory in the context of viral advergames or examined specific consumer behavioral outcomes of sharing personal data and game Forwarding. For the measurement of drowning, the existing approaches are either unidimensional or multidimensional. Multidimensionality typically includes attributes such as challenge, mastery, control, focus, enjoyment, curiosity, arousal, involvement, playfulness, telepresence, and time distortion. One popular unidimensional measure relies on perceived playfulness, as with more immersive games, enjoyment and concentration have stronger effects on player perception and behavior. Playfulness exists to some extent in any activity in which one freely engages. This structure is reflected in the two dimensions of pleasure and intellectual freedom (disappearing into work). Both dimensions indicate a state of psychological Flow. Both intrinsic and extrinsic benefits can stimulate social sharing behaviors. With regard to intrinsic benefits, emotional diffusion theory suggests that social sharing occurs when people need to share their evoked emotional experience with others (Lavoie, Raymond & Main, Kelley & Stuart-Edwards, Anastasia. 2022). According to the existing literature, intrinsic enjoyment leads to a stronger intention to participate in online word-of-mouth advertising. Perceived playfulness implies a sense of engagement that is inherently pleasurable, creating a positive emotional state. In the context of Viral Promotional Advergames, players' enjoyment of the game should lead to more positive evaluations, which increases the value of sharing personal data and Forwarding the game. Methodology This research is applicable in terms of purpose, cross-sectional survey method in terms of method, and purposeful and accessible in terms of selection of the research sample. In this study, data was collected using a pre-test-post-test method with a real viral marketing campaign. An advertising game was created for a weekly cultural magazine (at the request of magazine officials, magazine details are not reported) and data was collected during the campaign. Subscribers are people who provide their email address in exchange for promotional offers. In the pre-test stage, subject to the respondents' agreement to participate in the survey, in the first step, they received an email with a self-administered questionnaire about their attitude towards the weekly brand. In the post-test phase, participants received another email asking them to participate in a viral advertising game and to allow their behavioral data to be collected during the game for research purposes. At last, 393 out of the 765 participants clicked on the game link sent via email, but 288 participated in the game; and 141 people answered the questions, invited their friends to the game, or shared their personal data. Finally, Poisson regression was used to investigate the role of Flow theory on game forwarding and logistic regression was used on sharing personal data through Eviews software. Discussion and Results  Flow is positively related to game Forwarding and personal data sharing behaviors, such that if games elicit higher levels of enjoyment and concentration, the players may also be more willing to share personal data and Forward games. While the perceived value of prizes has a positive and significant effect on Forwarding games by players, it will not have a significant effect on sharing personal data. Also, prior attitudes towards the brand moderate the effect of perceived value of rewards on game Forwarding behavior. Also, players with inner pleasure and psychological Flow (dimensions of Flow) are more inclined to invite more people to the game and share more personal data about themselves. Perceived reward value is also positively related to game Forwarding behaviors, although not related to sharing personal data. That is, players appear to communicate more about the game when extrinsically motivated, but are less likely to share personal data with the brand. On the other hand, extrinsically motivated players still have significant privacy concerns. In contrast, perceived playfulness is positively related to personal data sharing, suggesting that fully immersed players tend to "lose themselves" and forget their more conscious concerns. As a result, they seem more likely to share personal data with the brand. Another interesting result comes from the absence of a reciprocal relationship between intrinsic and extrinsic motivation with regard to both behaviors. The reason can be the complexity of external rewards in this study. Conclusion Players with intrinsic enjoyment and psychological Flow (dimensions of Flow) tend to invite more people to the game and share more personal data about themselves, and perceived reward value is also positively related to game forwarding behaviors, although not related to sharing personal data. That is, players seem to communicate more about the game when they have extrinsic motivation (rewards), but are less likely to share personal data with the brand. Therefore, it is suggested; Companies that want to obtain customers' personal data should focus more on the design of game elements rather than prizes because the perceived value of prizes does not seem to have a significant and meaningful effect on the sharing of personal data. Games should also be designed in such a way as to induce psychological Flow/immersion in players; that is, game design elements should optimize the Flow or peak situation. On the other hand, companies that want to encourage players to submit their game should focus on both game design and prize placement, and prizes should be offered at different value levels to bias players' evaluations of more prizes. Previous research shows the importance of Flow for predicting learning, control, exploratory behaviors, positive subjective experiences, and other behavioral intentions (Lavoie & Main, 2019). Whereas, no previous studies have addressed the experience of Flowing/peaking in the context of Viral Promotional Advergames or examining Sharing Personal Data and game forwarding behaviors. With a field study of a real campaign of Viral Promotional Advergames, real data on player behavior is collected and how the intrinsic Flow/peak and extrinsic value of rewards are related to player behavior is measured. To measure intrinsic Flow/peak, players' perception of game playfulness was assessed (Chen, L.; Zhou, P.; Xiao, H. 2023). The results show that immersion in the game (enjoyment and immersion in the game) is positively related to game forwarding and Sharing Personal Data behaviors, while the external criterion related to the perceived value of rewards is positively related to game forwarding, but not to Sharing Personal Data. Furthermore, prior brand attitudes (prior to playing viral promotional games) moderate the effect of perceived value of rewards on game forwarding behavior.

Abstract The current research has been conducted with the aim of investigating the factors affecting the financial recovery of businesses admitted to the stock exchange. This research is an interdisciplinary study; a combination of legal and financial topics with qualitative and quantitative data. In this regard, 144 companies were studied as a statistical sample of the research in the 12-year period of 2010-2021 based on the screening process. The findings of the research showed that, in the examination of the goodness of fit indices of the model, it can be seen that, based on the McFadden coefficient of determination index, the use of predictor variables in the final model of the financial recovery of companies has been able to improve the likelihood function by 71.25%. That is, it can be concluded that the main forecasting components in the final model have been able to be effective up to 71.25% in the accuracy of detecting the financial recovery of companies. Finally, the analysis of multilayer artificial neural networks in order to evaluate the reliability of the results in diagnosing and prioritizing the financial recovery of companies shows that, therefore, considering that the tenth principal component is the most important factor in the financial recovery of companies, and citing the magnitude (absolute value) of the coefficients of each variable in the formation of this component, the order of the importance of financial variables in the financial recovery of companies and their exit from bankruptcy can be determined.
Extended Abstract                                          
Introduction
Financial helplessness refers to a situation in which the company cannot fully fulfill its obligations to financial providers, and faces difficulties in fulfilling them. Financial helplessness does not necessarily lead to bankruptcy, and a set of management measures to get out of helplessness or rehabilitation can save the company from the risk of entering the bankruptcy stage (Mherani et al, 2021). The growth and revival of the company is the result of exploiting the opportunities. In fact, a company has limited resources that it uses as necessary tools to achieve growth in facing upcoming opportunities (Hussain & Waseer, 2018). Company growth has been studied by many researchers and different terms have been used to define its stages. But most researchers agree that the growth and revitalization of the company is a process. In other words, every company is born like a child, then it starts to grow and in this way it faces various challenges and crises until it finally matures and then dissolves. In this path, there are several factors that help the company's success and allow it to move from one stage to another. Of course, there are two different thoughts among researchers in this regard; some of them believe that the company's economic growth path is linear and predictable. But some others believe that the company's growth is the result of taking advantage of opportunities and is unpredictable (Guha et al, 2013).
Manufacturing companies active in the stock market, which are considered as the main players in the economy of any country, play an important role in increasing the national income. Regardless of paying taxes to the government, companies create many job opportunities and provide them with the opportunity to pay taxes to the government by hiring and paying jobseekers. Also, companies play an important role in improving the foreign balance of the country by exporting their goods to other countries. On the other hand, bankrupt companies lose the ability to pay taxes to the government and are forced to fire their employees; which brings many social and political problems. Also, since bankrupt companies are unable to pay their loans, they create problems for lending institutions (Yan & Vedoud, 2019). Therefore, this research, referring to the concept of asset pricing models of Black and Schulz; which emphasizes on the intrinsic value of debts and assets, paying attention to the importance of bankruptcy and exit and in the continuation of rehabilitation, has examined the factors affecting financial rehabilitation of businesses accepted in the stock exchange, and in fact, the main question of the research is: what factors are effective on the financial recovery of bankrupt companies in the stock exchange?
 
Theoretical Framework
Financial rehabilitation (exit from bankruptcy)
Company rehabilitation is a process in which the weak performance status of the company changes and its performance indicators improve (Berandez & Berg, 2020). When some organizations experience a financial crisis and face challenging and deteriorating operating margins, financial revival means a significant improvement in operational margins and financial health of the organization (Ghazavi, 2018). The financial recovery of the business unit is a process based on which the weak performance status of the company is changed and the performance indicators are improved (Brandes & Brege, 2012).
 
Financial recovery strategies
The increase in the bankruptcy of business units due to the economic situation attracted the attention of researchers to this field and caused research to be found to provide a model to predict the exit from helplessness of helpless companies. With the increase in the scope of the financial crisis, managers of companies in crisis have increased their efforts to implement strategies that will save them from bankruptcy and stop their decline. In this regard, some of them use the strategy of cost reduction (Bruton & Rubanik, 2016) and asset restructuring (Sudarsanam & Lai, 2017; Hambrick & Schecter, 2014) for revival, and others consider the reorganization of the company's debts.
Dzingirai & Baporikar (2022) in a research titled "Trends and patterns in revitalization strategies" state that the most important aspect of strategic management should be the ability to respond to a world that is changing rapidly and with an increasing trend. The purpose of implementing this strategy is to take measures aimed at reducing the effects of change among organizations. As a result, it seems that the present time is the most ideal time to analyze the existing articles in this field from the perspective of bibliography. The role of revitalization strategies in strategic management articles cannot be underestimated. Three revitalization strategies, i.e. retrenchment, restructuring, and reorganization have led to the spread of articles related to the mainstream revitalization.
Ramalho & Diogo (2021) found that operational structure restructuring measures play an important role in the revitalization process of any company. In addition, this study shows that the managers of American companies during the considered time period, regardless of the effectiveness of the strategies, give more importance to financial restructuring measures.
 
Research methodology
This research is an interdisciplinary study; a combination of legal and financial topics with qualitative and quantitative data. In this regard, 144 companies were studied as a statistical sample of the research in the 12-year period of 2010-2021 based on the screening process.
 
Research findings
The findings of the research showed that, in the examination of the goodness of fit indices of the model, it can be seen that, based on the McFadden coefficient of determination index, the use of predictor variables in the final model of the financial recovery of companies has been able to improve the likelihood function by 71.25%. That is, it can be concluded that the main forecasting components in the final model have been able to be effective up to 71.25% in the accuracy of detecting the financial recovery of companies. Finally, the analysis of multilayer artificial neural networks in order to evaluate the reliability of the results in diagnosing and prioritizing the financial recovery of companies shows that, therefore, considering that the tenth principal component is the most important factor in the financial recovery of companies, and citing the magnitude (absolute value) of the coefficients of each variable in the formation of this component, the order of the importance of financial variables in the financial recovery of companies and their exit from bankruptcy can be determined.
 
Conclusion
The current research was conducted with the aim of investigating the factors affecting the financial recovery of businesses admitted to the stock exchange. The findings of the Ramalho, Diogo Miguel Pacífico (2021), Kazemzadeh & Moazami (2019), and Dzingirai & Baporikar (2022) also identified and introduced factors for the revival of companies in line with the results of this research. The artificial neural network composed of the main components in this research can correctly predict 90.9% of the bankruptcy or non-bankruptcy situations of companies, which can be confirmed by the research results of Lee (2021), Barzegar & Haedari (2017), and Wanita & Grace (2021) based on the acceptable and high power of the artificial neural network in the detection of aligned bankruptcy. Finally, for the revival of bankrupt companies in the stock exchange, suggestions for officials and legislators with regard to the research findings are presented:
- It is suggested to the Ministry of Security to make the necessary inquiries from the bankruptcy liquidation department of the provincial judiciary before issuing a license for production units that have been closed down or bankrupted, and provide the necessary background within the framework of laws and regulations for the activation of closed or semi-closed production units, with the least capital and the least cost, to activate the huge capital stagnant in them.
 

Abstract Abstract
The purpose of this research is to design a model of artificial intelligence competencies on organizational performance, taking into account business-to-business marketing capabilities. The research method is exploratory (qualitative-quantitative). In the qualitative part, it is considered with the Shannon entropy approach, and in the quantitative part, it is descriptive-survey. The participants of the present research in the qualitative part are faculty members and elites of artificial intelligence and marketing and management, which was conducted with 14 people based on the theoretical saturation rule, and in the quantitative part, the 540number of executive directors of industrial towns in northern Iran, of which 190 were selected as statistics sample. The data collection tool was semi-structured interview in the qualitative part, and researcher made questionnaire in the quantitative part. The method of data analysis was selected in the quantitative part of confirmatory factor analysis tests using SmartPLS software. The results showed that the mechanisms of artificial intelligence competencies have an effect on business-to-business marketing capabilities and organizational performance, and also the model of artificial intelligence competencies on organizational performance is confirmed considering the aspect of business-to-business marketing capabilities.
Extended Abstract
Introduction
The huge increase in the amount of data along with access to processing power capabilities and storage space on digital devices, have attracted new attention in the last few years to artificial intelligence in several fields and scientific courses (Enholm et al., 2021). The intense competition among organizations around the world has also accelerated the need to use artificial intelligence to achieve a competitive advantage over competitors (Ransbotham et al., 2018). Most C-level executives do not see AI as a core competency that organizations must employ to remain competitive in the long term (Kietzmann & Pitt, 2020). One of the key areas of using artificial intelligence in organizational activities has been business-to-business marketing (Mikalef et al., 2021). Smart solutions are needed to enhance business-to-business marketing capabilities in a complex business environment, because business-to-business operations are often associated with enormous information complexity and the need to make quick decisions. In this sense, artificial intelligence has the potential to revolutionize the way of performing common activities due to the ability to process increasing amounts of data and provide rich insights about key business partners and customers (Bag et al., 2021). In addition, it has been stated that artificial intelligence applications enable the automation of many manual processes, and this can help eliminate bottlenecks and increase operational efficiency in business-to-business activities (Paschen et al., 2020). In fact, a recent survey study on corporate executives conducted by Garner showed that the majority believe that artificial intelligence is likely to become a key development in their organization in the next few years (Shin & Kang, 2022).
Therefore, the main questions of this research are: What effect does artificial intelligence competencies have on organizational performance considering the B2B variable? Through what mechanism, the effects of artificial intelligence competencies on organizational performance are realized? And finally, what is the model of artificial intelligence competencies on organizational performance considering the aspect of B2B marketing capabilities?
Theoretical framework
Until now, there is not a complete understanding of how organizations should plan the development of artificial intelligence and turn it into a strategic asset applicable to achieve a competitive advantage. This issue is very evident and prominent in the field of business-to-business marketing, because there is still very little knowledge about the impact of artificial intelligence and the potential mechanisms of value generation from such technologies (Huang et al., 2019). Understanding the value of AI in business-to-business marketing and how to achieve it is critical to reducing the number of failed initiatives within organizations, as well as accelerating the development of AI in these types of operations. Similarly, recent survey studies of industry professionals show that there are still a number of significant bottlenecks preventing the adoption and use of AI that go beyond technical challenges. In addition, from the point of view of many managers, the value of adopting artificial intelligence is still not clear and certain, which prevents its further application in key organizational operations (Bhalerao et al., 2022). A recent study by McKinsey noted that the most popular use cases for AI in organizations relate to optimizing business-to-business marketing and service processes, and this is where respondents placed the most value. However, there are still several challenges associated with realizing such value by investing in AI and specifically with creating an AI competency that can always support business needs (McKinsey, 2022). To address this gap, this study uses the core competence theory (Prahalad, 1993) and provides a definition of the use of artificial intelligence within organizational boundaries, following the key followers of this theory. Especially, we express the concept of artificial intelligence competence as a central competence of organizations, which indicates the need for creative and coordinated use of artificial intelligence. The stated theories explain that organizations able to develop an artificial intelligence competency are organizations that are able to realize a competitive advantage over their competitors; because the application of artificial intelligence is unique in nature and requires comprehensive efforts from various organizational entities to produce artificial intelligence applications difficult to imitate and add value.
Methodology
In the current research, a systematic approach is used. This approach inductively uses a systematic set of procedures to formulate a theory in relation to a phenomenon. Content analysis is one of the documentary methods that deal with the systematic, objective, quantitative and generalizable examination of communication messages. This method is considered a concealer in the classification of methods, and it is used to check the obvious content of the messages in a text, and as a result, it does not enter into the interpretation and semiotics of the message content. The Delphi method is a structured communication method or technique that was originally invented and developed for the purpose of systematic and interactive forecasting by relying on the deliberation of experts. This method used in future research mainly pursues goals such as discovering innovative and reliable ideas or providing appropriate information for decision making. The Delphi method is a structured process for collecting and classifying the knowledge available to a group of experts, which is done through the distribution of questionnaires among these people and the controlled feedback of the answers and opinions received. Research method is fundamental-applied according to the goal; mixed (qualitative-quantitative) of sequential exploratory type according to the type of data; cross-sectional according to the time of data collection; and descriptive-survey according to the method of data collection or the nature and method of the research.
Discussion and Results
According to the results of Shannon's entropy technique for evaluating the capabilities of artificial intelligence, it can be seen that all the dimensions and indicators were higher than the average level of the group's weight, and remain in the model. Therefore, using the results of semi-structured interviews and inspired by the theoretical and empirical literature of the research, the identified categories will be categorized as described in the table below. As mentioned in the previous discussions, the sample size in the qualitative part of the research follows the principle of theoretical saturation, which is reflected in the next table on how to reach theoretical saturation.
Conclusion
The main goal of this research was to design a model of artificial intelligence competencies on organizational performance, considering the aspect of business-to-business marketing capabilities. The research method was exploratory (qualitative-quantitative). It was taken into account with the Delphi technique approach in the qualitative part, and descriptive-survey in the quantitative part. The participants of the present research in the qualitative part were academic faculty members and elites of artificial intelligence and marketing and management, which was conducted with 14 people based on the theoretical saturation rule; and in the quantitative part, 540 people of the industrial managers of the industrial towns in northern Iran, of which 190 people were selected a statistical sample. The data collection tool was a semi-structured interview in the qualitative part, and a researcher-made questionnaire in the quantitative part. The method of data analysis was carried out in the quantitative part of confirmatory factor analysis tests using SmartPLS software. One of the goals of this research was to try to understand whether, and under what conditions, artificial intelligence can lead to organizational value for companies. In order to answer this question, we grounded artificial intelligence based on the theory of core competencies. Therefore, the competencies of artificial intelligence were considered from the aspect of one of the key organizational capabilities that has the potential to create a competitive advantage for organizations. Therefore, the competencies of artificial intelligence are not only understood from the technical aspect, but also include management's ability to creatively anticipate applications that add value to the organization and include the ability to experience and test new methods of using artificial intelligence. Also, based on this approach, AI competency is considered as a core competency that organizations should strive to enhance, rather than just an ancillary and auxiliary set of capabilities that can support certain operations.
 

Abstract The aim of the research is to the effect of electronic satisfaction and trust on the intention to repurchase online by mediating the ease of use and moderating the online experience of customers in the digital store. In terms of purpose, the research method is practical; and based on the method of data collection, it is descriptive of causal type. The statistical population of the research is the customers of the digital goods store, which according to Cochran's formula for the unknown population size, the sample number was 384 people. The data was collected through a standard questionnaire and then analyzed by structural equation modeling method and using smart pls 3 software. The findings show that electronic trust and satisfaction variables had a significant effect on ease of use, and electronic trust and satisfaction and ease of use had a significant effect on online repurchase intention. Also, electronic trust and satisfaction have a significant effect on the intention to repurchase online with the mediating role of ease of use, which was confirmed by the Sobel test with a z-value of 2.374 for electronic satisfaction and 2.805 for electronic trust. Online customer experience moderates the relationship between customer satisfaction and online repurchase intention, and online experience moderates the relationship between online trust and online repurchase intention. Extended Abstract Introduction Today, online shopping has grown tremendously, and technological advancements have made shopping experiences significantly more efficient, transparent, and easy; and customers have become more aware of the value of online shopping with the growth and availability of e-commerce platforms worldwide, more price transparency, and faster delivery time (Delgosha & Hajiheydari, 2020). Increasing competition in the market has forced businesses to create stronger relationships with their customers, which has a positive effect on their repurchase decisions (Antwi, 2021). Repurchase intention is a situation in which consumers decide to buy products or services from the same company for the second time (Naghdi, 2021). To maintain a market presence, customer needs must be accurately understood; which helps the market to improve customer trust by improving service quality, and increase customer satisfaction and encourage the desire to buy (Putri et al, 2023). A study is needed to understand how e-commerce creates trust and satisfaction in its consumers. The main issue of the current research is whether electronic satisfaction and trust affect online repurchase intention through the mediation of ease of use and moderation of the online experience of customers. Theoretical Framework Nabila et al., (2023) showed in a study that ease of use and trust have a positive and significant effect on the intention to repurchase online. Also, customer trust has a positive and significant effect on electronic satisfaction. Abdulmaleki & et al, (2023), shows that satisfaction and enjoyable electronic experience play a mediating role in the relationship between electronic service quality and purchase intention. Wijaya & Nurcaya (2017) argue that satisfaction is a consumer feeling in which customers feel the best that a company offers. The effect of satisfaction certainly leads to repurchase intention for certain companies or products. Methodology Due to the use of a new approach, the current research is considered applicable, which was carried out using a causal survey-descriptive method. The statistical population of the Digikala store customer research, which was obtained to determine the number of samples according to Cochran's formula for the size of the unknown population, was 384 numbers of people. It has been analyzed by SPSS and SMART PLS3 software. To collect and measure data, a 20-item questionnaire with a five-point Likert scale was used as follows: The questionnaire of Ginting et al., (2023) with 5 items in the repurchase part, the questionnaire of Barbu et al., (2021) with 3 items for ease of use of, the questionnaire of Nabila et al., (2023) with 4 items for electronic trust, the questionnaire of Barbu et al., (2021) with 5 items for customer experience, and the questionnaire of Ginting et al., (2023) with 3 items in the electronic satisfaction section were used. Also, its validity has been confirmed by professors and experts, and its reliability by Cronbach's alpha coefficient. Discussion and Results First hypothesis: there is a significant relationship between electronic trust and ease of use. It was observed that the T-statistic between the two variables is equal to 7.608, since this value is higher than the borderline value of 1.96, it can be concluded that with at least 95% confidence, electronic trust has a significant effect on ease of use. Second hypothesis: there is a significant relationship between electric trust and online repurchase intention. It was observed that the t-statistic between two variables is equal to 2.043, and since this value is higher than the borderline value of 1.96, it can be concluded that with at least 95% confidence, electronic trust has a significant effect on the intention to buy online. Third hypothesis: There is a significant relationship between electronic satisfaction and ease of use. The t-statistic values between the two variables are equal to 3.566, and since this value is higher than the borderline value of 1.96, it can be concluded that with at least 95% confidence, electronic satisfaction has a significant effect on the ease of use. Fourth hypothesis: There is a significant relationship between electronic satisfaction and online repurchase intention. Also, the t-statistic between the two variables was observed as 5.994 and since this value is higher than the borderline value of 1.96, it can be concluded that with at least 95% confidence, the hypothesis of electronic satisfaction has a significant effect on online purchase intention. Fifth hypothesis: There is a significant relationship between ease of use and repurchase intention. The t-statistic between the two variables is equal to 3.001. And since this value is greater than the borderline value of 1.96, it can be concluded that with at least 95% confidence, ease of use positively and significantly affects the intention to buy online. Sixth hypothesis: there is a significant relationship between electronic trust in online purchase intention and the mediating role of ease of use. The T-statistic between the two variables was found to be 2.842, and since this value is higher than the borderline value of 1.96, it can be concluded that with at least 95% confidence, electronic trust has a positive and significant effect on the intention to buy online with the mediating role of ease of use. Seventh hypothesis: There is a significant relationship between electronic satisfaction on online purchase intention and the mediating role of ease of use. Also, the t-statistic between the two variables was observed as 2.152, and since this value is higher than the borderline value of 1.96, it can be concluded that with at least 95% confidence, electronic satisfaction has an effect on on-line purchase intention with the mediating role of ease of use, and ease of use can be a mediator for on-line purchase intention, which indicates the customers' satisfaction. Hypothesis 8: Online customer experience moderates the relationship between e-trust and on-line repurchase intention. The t-statistic between the two variables is equal to 2.002, and since this value is higher than the borderline value of 1.96, it can be concluded that with at least 95% confidence, online customer experience moderates the relationship between customer trust and online repurchase intention. Hypothesis 9: Online customer experience moderates the relationship between e-satisfaction and online repurchase intention. The value of the t-statistic between the two variables is equal to 2.666, and is higher than the borderline value of 1.96, as a result, with at least 95% confidence, online customer experience moderates the relationship between customer satisfaction and online repurchase intention. Conclusion The results of the first hypothesis are consistent with the researches of Wilson et al, (2021) and Anifa (2022). Therefore, increasing the trust of customers makes it possible for them to pay less attention to the problems related to the purchase with a mental set and practical plan suitable for a successful trading experience, which increases the ease of use.
The results of the second hypothesis are in line with the researches of Puti et al, (2023) and Ikhsan & Lestari (2021). If the managers of the marketing department can promote trust in electronic environments among their customers during the purchase process and try to create transparency about the process of carrying out activities in the store, they can believe that the purchase process be repeated The results of the third hypothesis show that the higher the level of consumer satisfaction, the easier the use of the products. Consumers provide a good evaluation of service and product performance for the satisfaction they feel from purchasing a product or service. The results of the fourth phase are consistent with the researches of Ginting et al, (2023) and Anifa (2022). Marketing stimuli that look different in augmented reality can give a distinct impression to consumers, creating a sense of satisfaction in the shopping experience and encouraging repeat purchases. The results of the fifth hypothesis are consistent with the researches of Nabila et al, (2023) and Anifa (2022). Ease of use can make customers repurchase existing products because of ease of use. The results of the sixth hypothesis are in line with the researches of Wilson (2019) and Subagio et al, (2018). It shows that the user's perceived ease of trial feature of the virtual product can mediate the repurchase intention relationship that is used with trust. The results of the seventh hypothesis are in line with the research of Nabila et al, (2023) and Diyanti, Syarifa Yulindar (2021). The results of the eighth hypothesis are in line with Miao et al., (2022). Internet stores should take a creative approach to meet the needs of customers and increase customer trust by creating appropriate platforms. The results in the ninth hypothesis were in line with the research Miao et al, (2022). The more positive experiences received from the product from a store, the more satisfied the customer will be with the store, and as a result, he will consider the positive experience as a suitable frame in his mind, and the more likely he is to repeat the purchase of the products.

Abstract Abstract The main purpose of the current study is to investigate the impact of green transformational leadership on green behavior with the mediating role of green organizational culture and environmental concerns of employees in industrial units of Shahrekord. This study is applicable in terms of purpose, and descriptive-survey in terms of data collection. Green transformational leadership was measured using the six-item scale developed by Singh (2020), environmental concern was measured using the five-item scale developed by Frang and Martens (2006), green behavior was measured using the sixteen-item scale developed by Hassanpour (2020), and also green organizational culture was measured using the nineteen-item scale developed by Stanstie et al (2021). The statistical population of this study was 510 employees, among which a sample including 219 employees in industrial units of Shahrekord was selected by Morgan table, and the questionnaires were distributed among them by simple random sampling. SPSS and Smart PLS softwares were used to analyze the data as well as hypotheses testing. The results showed that green transformational leadership has a positive effect on green behavior with the mediating role of green organizational culture. The results also indicated that green transformational leadership had a positive effect on green behavior with the mediating role of environmental concerns. Extended Abstract Introduction The first way to have a sustainable environment is to identify the factors that threaten it and take action to reduce the impact of these factors. Therefore, the environment is currently considered a global issue for everyone, including organizations (Adriana et al, 2020), so that stopping destruction and efforts to increase the quality of the environment are among the challenges considered as the front line of organizations. Recently, the green behavior of employees at the workplace has been in the focus of organizational researchers because the evidence indicates that the individual behavior of employees can play an important role in the environmental performance of the organization and improve it. Behaviors that strengthen or weaken environmental sustainability by employees, which occur voluntarily or involuntarily and are also measurable, are called green employee behavior (Xiao et al, 2020). Past studies show that when leaders implement green transformational leadership, they positively affect corporate environmental responsibility and green behavior. Green transformational leadership is a style of leadership that inspires its followers to achieve environmental goals and motivates them to perform and behave green beyond expectations. One of the categories that seems to be able to facilitate the effect of green transformational leadership on the green behaviors of employees is the attitude of employees. Attitude is defined as a person's emotional tendency when he evaluates something positively or negatively (Farhadinejad et al, 2019). According to the mentioned materials, the main problem of the research is whether green transformational leadership has a positive and significant effect on green behavior with the mediating role of green organizational culture and environmental concerns in the industrial units of Shahrekord city. Theoretical Framework Green transformational leadership, theory-based evidence and experience-based evidence indicate that personal and situational factors are among the factors that can influence the tendency of employees to have environmentally friendly behavior at work. In this regard, researchers name an important factor in the formation of green behavior at work under the title of transformational leadership (Hadi & Rasool, 2017). When employees go beyond the goals, in order to minimize the positive impact of organizational activities on the environment (Raskooi, 2019), in fact, it is better to say, green management refers to the integrity of the organization's behavior; and the environmental awareness of green management demands that a company adopt tangible and integrated operations to prevent the pollution created in the organization's activity process (Mazarezadeh et al. 2015). Considering serious environmental problems, such as pollution and resource depletion and increasing polluting gases, companies should change their traditional business model to a sustainable model (Takaudo et al, 2019). However, few companies have the ability to deal with environmental issues using their limited resources (Zhang et al, 2019). The behavior that positively affects the environment is called green behavior or environmentally friendly behavior (Iqbal et al, 2018). In fact, behaviors that contribute to the sustainability of the environment indicate green behavior, such as saving resources, transforming and turning waste into valuable items, and protecting the environment (Jian et al, 2020). Singh et al, (2020) in a study investigated the effect of green innovation on organizational performance through the mediation of green transformation leadership and green human resource management. The findings showed that the actions of green human resources management have a positive and significant effect on the green innovation leadership and then on the environmental performance of organizations. Lee (2020) investigated the effect of green human resource management on environmentally friendly behavior of hotel employees and environmental performance in a study. The findings showed that paying attention to green human resource management measures increases the organizational commitment of employees, behavior compatible with their environment, and sustainable performance. Methodology The current research is an applicable research in terms of the goal, and a descriptive-survey research in terms of the method used. The statistical population of this research is 510 employees of the industrial units of Shahrekord city, 219 people were selected as a sample using Morgan's table, and the questionnaire was distributed among them using simple random sampling. The questionnaire of Kumar Singh, (2020) for the green transformational leadership variable, and the questionnaire of Frang, & Martens (2006) for the environmental concern variable, and the questionnaire of Hassanpour (2020) for the green behavior variable, and the questionnaire of Stanstie et al. (2021) for the green organizational culture variable were used to collect related data. Discussion and Results In order to investigate research hypotheses and analyze data, PLS software was used. The results showed that the significance level for the effect of green transformational leadership on green organizational culture is less than 0.05 (p≤/05); it can be said that green transformational leadership has a significant impact on green organizational culture. Considering that the coefficient of influence of green transformational leadership on green organizational culture is positive and equal to 0.735, it is concluded that green transformational leadership has a positive effect on green organizational culture. The value of the significance level for the effect of green organizational culture on green behavior, which is less than 0.05 (p≤/05), can be said that green organizational culture has a significant effect on green behavior. Considering that the coefficient of influence of green organizational culture on green behavior is positive and equal to 0.496, it is concluded that green organizational culture has a positive effect on green behavior. The significance level value for the effect of green transformational leadership on environmental concerns, which is less than 0.05 (p≤/05), can be said that green transformational leadership has a significant effect on environmental concerns. Considering that the coefficient of influence of green transformational leadership on environmental concerns is positive and equal to 0.804, it is concluded that green transformational leadership has a positive effect on environmental concerns. The value of the significance level for the effect of environmental concerns on green behavior, which is less than 0.05 (p≤/05), can be said that environmental concerns have a significant effect on green behavior. Considering that the coefficient of influence of environmental concerns on green behavior is positive and equal to 0.377, it is concluded that environmental concerns have a positive effect on green behavior. Considering that all 4 sub-hypotheses were accepted, as a result, the main hypothesis is also accepted and green transformational leadership has a significant effect on green behavior with the mediating role of green organizational culture and environmental concerns. Conclusion The current research was conducted with the aim of the effect of green transformational leadership on green behavior with the mediating role of green organizational culture and environmental concerns. The results of this research are consistent with the results of Kumar Singh et al, (2019) and Goldberg et al, (2018); environmental challenges put considerable pressure on organizations to behave more environmentally sustainable. A large number of organizations have started to adopt green policies and methods to increase economic benefits and better environmental performance (Ardito & Dangelico, 2018). Nevertheless, the environmental performance of organizations not only depends on strict laws and regulations, but it also requires employees' positive responses to environmental concerns with employees' environmental behaviors (Kim et al, 2017). The success of a company's environmental management depends on the employees' environmental behavior, because their behavior improves the company's environmental performance as a whole (Lu et al, 2017). The environmental behaviors of employees contribute to the optional actions of employees in the environmental sustainability of the organization and the employer, but are not under the control of any policy or formal environmental management system. Environmental behaviors include recycling and reuse, finding sustainable ways of working, developing and applying ideas to reduce the company's negative environmental effects, developing green processes and products, and questioning harmful practices. According to the results of the research, it is suggested that in order to develop a green transformational leadership style, organizations can formulate regulations that encourage managers to display a green leadership style (such as designing special reward programs). In the government domain, policy makers should try to adopt policies in the framework of which the managers of the organizations will be trained in green leadership style and in this way influence the green attitude and behavior of the employees. Organizations may conduct environment-related training to empower employees to achieve environmental goals. Organizations should conduct environmental audits to assess whether suppliers' practices are consistent with the companies' environmental goals or not.

Abstract Extended Abstract
Abstract
The purpose of this study is to analyze the impact of ethical marketing on consumer repurchase intention with emphasis on the mediating role of brand identity and brand equity. The research method is descriptive-survey in terms of nature, and applicable in terms of purpose. The statistical population of the research is the customers of Digi Kala online store. The sample size was determined using Cochran's formula of 375 people, and the samples were selected by available sampling method. Ethical marketing questionnaires (Safari.et al.2017), brand equity (Aaker.1991), brand identity (Mael & Ashforth, 1992) and repurchase intention (Hong.et al.2012) were used to collect data. The data validity was determined by the academic experts, and the reliability was confirmed by Cronbach's alpha coefficient test. In order to analyze the data, the structural equation technique was used using Lisrel statistical software and SPSS statistical software. The results showed that marketing Ethics has a positive and significant effect on brand identity, customer repurchase intention and brand equity. Brand identity has a positive and significant effect on customers' intention to repurchase. Brand equity has a positive and significant effect on customers' intention to repurchase. Finally, ethical marketing has a significant effect on consumer's intention to repurchase by emphasizing the mediating role of brand identity and brand equity.
Introduction
Rapid change in today's world has faced organizations with various challenges, but in the meantime, successful organizations are those which, with the help of management tools and new technologies, take advantage of the opportunities created to their benefit. The e-commerce environment is one of these tools. Internet-based e-commerce environment allows customers to search for information and purchase goods and services through direct contact with online stores (Feyznia.2017) .Today, shopping intention reflects the predictable behavior of the consumer in future purchasing decisions that significantly helps in the formation of consumer attitudes (Xiao, & Liu.2018). Identity is one of the factors that keeps the brand stable and directs it to new markets and products (Muhonen.et al.2017) Brands identify themselves to customers and differentiate themselves from other competitors. The process of creating a brand identity is to formulate the mindsets that the brand intends to create and ensure that the brand is identified by the customer and associated with a particular category of needs (Khodavardikhani, 2018). The customers prefer one tbrand to other based on the factors important to them (Ebrahim, 2020). Brand equity is one of the assets that maintains the value of the company and, by creating a competitive advantage over competitors, will attract customers' attention and loyalty (Zollo.et.al.2020). The intention to repeat the purchase is the process of referring and repeatedly purchasing goods and services from a store in the long run, the main reason for which is positive experiences after the purchase (Birjandi.et.al.2019). Ethical marketing is a domain of applicable ethics which is related to hidden ethical principles in behavior, advertising and regulation in marketing (Purwanto.etal.2019). This issue, which is widely discussed in management and market science today, is called ethical marketing (Pittz.et.al.2020). Digi Kala online store is one of the most reputable virtual stores in our country which many people buy from around the clock to provide the products and services they need. Considering that a suitable platform for online sales and purchases has not yet become popular in our country, the researcher intends to analyze the relationship between consumer intention to repurchase, brand identity and brand equity while analyzing the aspects of ethical marketing. This study tries to answer the question whether ethical marketing has a significant effect on the consumer's intention to repurchase, by emphasizing the mediating role of brand identity and brand equity in the Digikala online store.
Theoretical literature
Using the definition of Taylor (2000), Till (2009) defines marketing ethics as follows: Research into the nature and levels of belief, beliefs, standards, and rules of ethical behavior in relation to business decisions and sales conditions (Safari, et.al.) 2017). Intention to buy is a pattern of attitude towards the product for future purchases (Shaghlani, 2017). Su (1990) states that the intention to buy refers to some exchange behaviors that occur after consumers evaluate the product and reflect an emotional response in their behavior to an issue (Safari, et al. 2017). Brand identity expresses the ideal characteristics that the brand intends to offer to customers. In other words, brand identity is what the brand commits to the market (Essamri, et. al.2019). Whatever is supposed to be portrayed in the future and engraved in the mind of the customer is the essence of the brand. Adorned appearance and what is seen is the expression of a brand identity (Ahmadian.2017). According to Acker (1991), brand equity has three basic components: brand awareness, brand loyalty and brand association. Brand awareness is the level of awareness and cognition by which the customer recognizes, remembers and can identify brand-related products and services (bordbar, et al.2018).
Chae.et al. (2020) in a study concentrated on the effect of product features on perceived value, brand trust and repurchase intention. The results showed that product features have a positive and significant effect on perceived value, brand trust and repurchase intention. Ghaffari (2018) also stated in his research that there is a positive and significant relationship between ethical marketing and customer loyalty. Izadian (2019) also concluded in his research that there is a positive and significant relationship between brand personality with brand trust and brand loyalty.
Methodology
The present research is applicable in terms of purpose, and descriptive-survey in nature. The statistical population of the research consists of customers of Digi Kala online store, 375 of whom were selected as the research sample using Cochran's formula and available sampling method. ethical marketing questionnaires (Safari.et al 2017), brand equity (Aaker.1991), brand identity (Mael, & Ashforth, 1992) and repurchase intention (Hong.et al.2012) were used to collect data.
Discussion and Results
In order to investigate the mediating effect of brand identity in the hypothesis under discussion, the direct effect of the two structures with the indirect effect in the case of involving mediating variables should be examined so that if the effect increases, the mediating effect can be considered acceptable. In the present hypothesis, the direct effect is equal to 0.49. If there is a mediating variable of brand identity, the indirect effect is:
 (0.69) × (0.73) = (0.507)
Due to the fact that the direct path effect is less than the indirect path, therefore, the existence of a mediating variable increases the brand identity and the mediating role in the present hypothesis is confirmed.
In order to investigate the mediating effect of brand personality in the hypothesis under discussion, the direct effect of two structures with indirect effect in the case of involving mediating variables should be examined so that if the effect increases, the mediating effect can be considered acceptable. In the present hypothesis, the direct effect is equal to 0.49. Indirect effect in the presence of a mediator variable of brand equity is:
(0.72) × (0.78) = (0.561)
Due to the fact that the effect of direct path is less than indirect paths, therefore, the existence of a mediator variable increases the equity of the brand, and the mediating role in the present hypothesis is confirmed.
Conclusion
Considering the confirmation of the first main hypothesis; the effect of ethical marketing on repurchase intention with emphasis on the mediating role of brand identity, the result is explained in such a way that providing the desired services to customers creates trust among customers and persuades them to refer to this site in different situations. Therefore, the idea is imprinted in the minds of customers that if they want quality services, they will always trust this online store and keep it in mind, and if the services required by customers are available on this site, they will not be willing to use services and products of other stores. As a result, the management of this store fulfills its obligations to customers correctly and honestly, and customers are assured about the goodness of the products they receive from this site, compared to other online stores. The degree of easy access of customers to the services or products listed on the Internet sites can affect their satisfaction with the perceived usefulness of these facilities and goods. When the customer can easily make online purchases and buy the desired product, he acts with more interest in understanding the usefulness and the purchase process. These results match with research findings of Demirgüneş.(2015); Rezaei, (2018); Izadian, (2019) and supported by them.
The result of testing the second hypothesis based on the positive and significant effect of ethical marketing on repurchase intention by emphasizing the mediating role of brand equity is explained in such a way that considering the intangibility of goods and services received by customers through the Internet and their purchase from virtual stores has reasonably high perceived risk. When buying online from store sites, customers pay special attention to the details of the purchase and the products offered on this site. Paying attention to the characteristics of the offered products and the amount of site commitment about the returning of impaired goods can be considered as a significant aspect in this case. On one hand, online stores should explain precisely the details and application of their products with high clarification so that customers can make the right choice to meet and satisfy their needs. On the other hand, these stores must be committed to selling their goods and provide after-sales service satisfy the customers. In this way, site managements can stimulate the customer's sense of trust to their virtual store and encourage them to buy online. These results match with research findings of Bavarsad, et al. (2015); Vazifehdust & Memarian. (2014); Chen & Quester, (2015) and supported by them.

Abstract Abstract The purpose of the present research is to investigate the impact of social media marketing on brand loyalty with the mediating role of trust and equity of the brand in Isfahan Bank Mellat branches. This research is applicable in terms of purpose, and correlative in terms of research method, and required data have been collected by using questionnaire and survey method. The statistical population of this research is the clients of Isfahan Bank Mellat branches. 384 acceptable samples were collected by simple random sampling method. Four social media marketing questionnaires with 11 questions, brand trust with 10 questions, brand special value with 16 questions, and brand loyalty with 15 questions were used as data collection tools. Data analysis was done using structural equation modeling and PLS software, and the research results show that social media marketing has an effect on brand loyalty with the mediating role of trust and brand equity. That is, if the bank tries to create content in the virtual space through which attracts the attention on those platforms and encourage the readers to share it among social media,, the loyalty of the bank's customers will improve. The bank should spread its advertisements through the virtual space and attract the attention of the audience, as a result, trust in the brand will improve. Extended Abstract Introduction Today, a large number of users with different goals have joined virtual social networks and engage in various activities (Barreto, 2014). Organizations, either small or large, have entered social media and are slowly trying to discover its benefits (Bakeri, 2020). They have used Twitter, created fan pages on Facebook, posted videos on YouTube, and perhaps even created websites in the late 20th century (Zhang & Liu, 2021). Organizations today feel that the Social media are and will be a means of business (Naeem, 2021). The main goal of social media marketing is to create a business based on customer orientation and the credibility of a company in order to develop and manage work (Kim, 2012). No one can claim that there are only advantages and benefits in the field of social media marketing. Rather, in social media marketing, like all aspects of life, there are advantages and disadvantages together and side by side (Rosen, 2013). However, in our country, social networks have not been able to find their desired place in people's lives, and after all, culture creating in this field has not been done, and producers of products and services cannot make proper use of these networks. This issue has become the main problem in creating trust and loyalty of customers to the brand in social networks. In e-commerce, trust is considered the most important success factor. It should be said that according to previous studies, the recommendations of acquaintances and online opinions of consumers (word of mouth advertising) are the most reliable type of advertising in the world and the most important source of information for purchasing decisions. Many researchers consider the power of the internet as a social structure in creating and increasing brand trust and loyalty. It is argued that brand community in social networks increases brand loyalty through increasing brand trust. By increasing the capabilities of social networks, trust in the brand and then loyalty to the brand increases; therefore, brand trust plays a mediating role. According to the mentioned materials, the main problem of the research is whether social media marketing has an effect on brand loyalty with the mediating role of trust and special value of the brand in Bank Mellat branches of Isfahan. Theoretical framework A social network is a social structure made up of groups - generally individual or organizational - which are connected by one or more types of dependencies. Social networks in the context of a complex information society depict the effective functioning of the network (convergence) and with a more detailed look, society is a combination of multiple networks: inter-organizational networks, intra-organizational networks, personal networks, computer networks, and furthermore, cross-border networks and information flows through these highways (Zhang & Liu, 2021). Brand equity has been defined in different ways for different purposes. But so far, no common consensus has been reached. The concept of brand equity has been the subject of a large number of studies, has been examined from different perspectives, and is often described as the value that a brand gives to a product (Rezaeian, M., Asgar, 2021; Shams Lahroudi, 2018) According to Aker, brand loyalty is one of the foundations of brand equity, and many factors play a role in creating this loyalty, one of the main of which is the experience of using the brand (Song, 2012). Oliver defines brand loyalty as a consumer's strong commitment to purchase or reuse a brand regularly in the future. Fukuyama (1995) defines brand trust as: an expectation that arises from inside of an orderly, honest community with cooperative behaviors based on commonly shared norms, on the part of community members. He believes that the industrial revolution has played a significant role in the importance of trusting the brand to recognize and understand business behaviors such as marketing. Mirzaee Azandariani and Arya (2022) conducted a research titled investigating the impact of the characteristics of second-hand goods platforms on brand loyalty intentions with the mediating role of customer satisfaction (the study of Divar and Sheipour platform in Iran). Research findings showed that ease of use has a positive and indirect effect on brand loyalty intentions with a mediating role of customer satisfaction, perceived usefulness has a positive and indirect effect on brand loyalty intentions with a mediating role of customer satisfaction, and the entertainment aspect has a positive and indirect effect on Brand loyalty intentions with the mediating role of customer satisfaction, and the sense of belonging to a community has a positive and indirect effect on the intention of brand loyalty with the mediating role of customer satisfaction, and seller credibility has a positive and indirect effect on the intention of loyalty to the brand whit a mediating role of customer satisfaction, and the recognition of a third party has a positive and indirect effect on the intentions of brand loyalty with the mediating role of customer satisfaction. Farzin et al. (2020) conducted a study with the aim of investigating the effect of brand equity from the consumer's point of view on brand satisfaction and loyalty in the wood and paper industries of Mazandaran province. The results of the research showed that there is a positive and significant effect between the dimensions of brand equity and consumer satisfaction (except for employee behavior and brand awareness) and brand loyalty (except for ideal self-concept and brand identity) and also between consumer satisfaction and brand loyalty is a positive and significant effect. Research methodology The research method is descriptive-correlative in nature and applicable in terms of purpose. The statistical population of this research is the clients of Isfahan Bank Mellat branches and simple random sampling method was used and 384 acceptable samples were collected. In order to collect data related to the variables, four social media marketing questionnaires were used with 11 questions, brand trust with 10 questions, brand equity with 16 questions, and brand loyalty with 15 questions; and based on a 5-point Likert scale (completely agree to completely disagree).   Research findings Structural equations and PLS were used to investigate the research hypothesis and data analysis, and the results showed that social media marketing has an effect on brand loyalty with the mediating role of trust and brand equity in Isfahan Bank Mellat branches. Social media marketing has an effect on brand loyalty in Isfahan Bank Mellat branches. Social media marketing has an effect on brand trust in Isfahan Bank Mellat branches. Social media marketing has an effect on brand equity in Isfahan Bank Mellat branches. Brand trust has an effect on brand loyalty in Isfahan Bank Mellat branches. Brand equity has an effect on brand loyalty in Isfahan Bank Mellat branches. Social media marketing has an effect on brand loyalty with the mediating role of brand trust in Isfahan Bank Mellat branches. Social media marketing has an effect on brand loyalty with the mediating role of brand value in Isfahan Bank Mellat branches. All factor loading coefficients are greater than 0.4, which shows that this model is suitable. Conclusion The present study was conducted with the aim of investigating the impact of social media marketing on brand loyalty with the mediating role of trust and brand value in Isfahan Mellat Bank branches. The results of this research corresponds with the results of research findings of Frzin et al. (2020); Shirkhodaei (2017); Imran Khan et al. (2017). If the bank tries to create content in cyber space through which can attract the attention of the audience on those platforms and encourage readers to share it among social media, the loyalty of the bank's customers as a result, will improve. The bank should spread its advertisements through the virtual space and attract the attention of the audience, as a result, trust in the brand will improve. According to the present research, it is suggested that the bank employees have sufficient knowledge and information about the services to provide to the customers. The employees solve the problems faced by the customers regarding the services in the best way; follow up and respond to the requests of the customers regarding the services quickly and in different ways such as phone, email, etc.; provide a platform so that customers can fully use the bank's services anywhere and at any time of the day or night; and by improving the level of value and the mental image of the brand of services and the quality level of relations with customers, provide the possibility of strengthening customer satisfaction, which ultimately leads to customer loyalty.

Abstract Abstract This study, based on the MARA methodology and the concept of systems fragility, introduced the fragility analysis approach to the problem of strategy selection. In turbulent and unpredictable environments, decision-making (especially regarding key and influential decisions such as strategy selection) is challenging. In changing and variable conditions, classical approaches to strategy selection as well as multi-attribute decision-making approaches lose their effectiveness. Classical scenario planning approaches are also unable to cope with turbulent environments due to their inherent limitations and simplification. In response to the shortcomings of the aforementioned approaches, the Matrix Approach to Robustness Analysis (MARA) was introduced, which is able to solve the problem of strategy selection without computational constraints. However, this approach is suitable when a conservative decision-maker wants to choose a strategy with the lowest risk. Therefore, this approach does not provide a desirable outcome when the decision maker seeks to exploit opportunities. In this approach, after listing the decision options and defining scenarios based on the most important environmental indicators, the performance of the strategies in each of the different states of the indicators was determined and the total performance of each strategy in each scenario was compared with the performance of that strategy in the base scenario (status quo). The proposed approach was described in the form of a case study. In practice, this analysis shows which strategy (decision) can bring more benefits to the organization (decision maker) in the event of a change in each of the environmental impact indicators (scenario change). This concept is in contrast to robust analysis, which considers the option that has less risk in the event of a change to be superior. Using this tool in turbulent environments can help managers in the business management process. Introduction The complexity we face in today's modern and rapidly changing world requires a better understanding of how to make decisions that effectively deal with this complexity; otherwise, we may develop strategies that have unintended and irreversible consequences. Accordingly, decision-makers must first equip themselves with appropriate decision-making tools. Choosing a method or approach to decision-making is, in turn, a decision-making problem (Sorourkhah, 2024). In the decision-making literature, there are various methods, models, and approaches to decision-making, each of which is suitable for a specific situation. Based on a) the type of problem, b) the quality of the data, c) the number of indicators and d) the goal of solving the problem, decision makers can choose the most appropriate option (Bartolini, 2021). Given that the problem of choosing a strategy is a) a key decision with long-term consequences, b) the data is uncertain and unpredictable, and c) the indicators are numerous and often contradictory; we know that classical approaches such as QSPM and multi-criteria decision-making techniques are not suitable. In these circumstances, the use of scenario-based approaches seems more logical (Joorbonyan et al., 2024). Although the modern world is increasing in knowledge, paradoxically, this makes it more difficult to predict things. Due to the emphasis of the inductive learning process on narrative and causality, the impression is formed that the only way to deal with uncertainty is to identify the causal chains that have been constructed early; for example, by identifying early “trigger events”, “weak signals”, or “early warnings”, and then implementing precautionary measures to mitigate the consequences of an undesirable future or to take early advantage of a desirable future. This view is prominent in the recent scenario planning literature. In contrast, the existential view of uncertainty sees outcomes as the result of random processes that are not causally related. The increasing complexity of the challenges faced by modern organizations far exceeds the ability to discover causality, and causal speculation is therefore temporary, unstable, and error-prone. Therefore, the ability of methods to prepare for the future (the ability to cope with uncertainty arising from complexity) is becoming increasingly important, without relying solely on identifying causes (Bahrami et al., 2025). In such a situation, the Matrix Approach to Robustness Analysis (MARA) can simultaneously deal with complexity and uncertainty (Amiri et al., 2024). However, the MARA method is conservative and tries to choose the option that brings the least loss. Therefore, if the goal of decision-making is to maximize the exploitation of an opportunity, a new approach is needed. This concept has been known as antifragility in recent years. So far, the concept of antifragility has been actively applied in several fields, including molecular biology, physics, computer science, transportation planning, risk analysis, and engineering; however, a practical criterion for antifragility has not been developed yet (Pineda et al., 2019). According to the resilience literature, organizations can be fragile or antifragile to shocks; researchers believe that decisions (strategies) can also be fragile or antifragile to shocks (Kokkinos et al., 2023). When an unexpected event occurs, many previously selected strategies lose their effectiveness and, in some cases, may even lead to negative results. Accordingly, in this study, the researcher seeks to answer the question: what is antifragile analysis: a tool for managing business in a turbulent environment? Theoretical foundations Antifragility The phenomenon of antifragility has been proposed as a new theoretical framework in management and organizational sciences in recent years. This concept was first introduced by Nasim Nicholas Taleb and showed its fundamental difference from concepts such as fragility and antifragility. In Taleb's definition, antifragile systems not only resist shocks and disturbances, but also benefit from these instabilities and rise to a higher level of performance. In this view, unlike fragile systems that are damaged in the face of disturbances and antifragile systems that only return to their original state, antifragile systems adapt to and benefit from disturbances (kianirad et al., 2022. ( Faryadras et al., (2026) studied "The relationship between antifragility and financial performance and business continuity in banks listed on the Tehran Stock Exchange". 10 eligible banks were selected for the sample and the data were analyzed using panel data regression. The results showed that antifragility has a positive and significant effect on business continuity and also on the financial performance of banks listed on the Stock Exchange. In addition, financial performance has a positive effect on business continuity. Gaadim ghobadi et al., (2024) studied "Providing a model of antifragility in Iranian financial organizations through thematic analysis". The results of the study led to the identification of 79 codes and 19 themes in the form of four main categories such as 1- the random and environmental category, which includes the components of flexibility, financial crisis, antifragile performance, agility and adaptability, and 2- the financial performance category, which includes the components of cost control, financial performance of institutions, central bank independence, inflation volatility, cash flow management, 3- the management category, which includes the components of risk management, improving economic growth, capital management, financial policies, relationship with the government, and 4- the organizational category, which includes the components of innovation and creativity, adaptability, resistance and coping, integration and service empowerment. Research Method This study was designed to present and test the approach to analyzing the antifragility of strategies in turbulent environments and is considered an applicable and analytical-modeling study. The data in this study were collected secondary and computationally, and the analyses were based on matrix modeling of scenarios and strategy performance. In this study, first, the environmental impact indicators for strategic decision-making were identified and structured based on the MARA method. Then, possible future scenarios were eliminated according to the different states of each production indicator and impossible or contradictory scenarios. The performance of each strategy in each scenario was evaluated by experts and specialists in the relevant field and recorded in the form of a strategy performance matrix. In the next step, the total performance of each strategy in the scenarios was compared with the baseline to calculate the antifragility score of each option. Research Findings The results showed that different strategies experience different degrees of antifragility to environmental changes. The examination of future scenarios revealed that some strategies are not only unvulnerable to shocks, but also perform better than the baseline in many alternative scenarios. The aggressive strategy scored the highest antifragility score and has a high ability to transform environmental changes into opportunities. These findings emphasize the importance of choosing opportunistic rather than conservative options in turbulent environments. Furthermore, using the antifragility framework allows managers to make structured and flexible decisions. Conclusion In the agitated, turbulent, and unpredictable environments that characterize many industries today, strategy selection becomes doubly important. The findings of this paper indicate that a antifragility -based approach, especially in situations where nonlinear changes and environmental shocks occur, can provide a more efficient tool for strategic decision-making than conservative approaches. Relying on environmental scenarios and comparing the performance of strategies against the baseline allows for the identification of options that perform better across a wide range of possible futures. This finding is consistent with previous studies. For example, Kokkinos et al. (2023) has shown that organizations that are able to exploit shocks and fluctuations are not only more antifragile to change but can also use these conditions to improve performance and innovation. Also, recent research in the field of innovation management and organizational performance shows that measuring antifragility components, such as diversity of responses, capacity for emergent behaviors, and nonlinear response to shocks, can increase the productivity and adaptability of organizations (Branicki, Sullivan, & Worrall, 2018). Studies that have examined antifragility in the context of supply chains and dynamic systems also emphasize that systems that are not only antifragile but also benefit from environmental shocks perform better in the long run (Santos & Eisenhardt, 2020(. Numerical implementation of the proposed approach showed that different strategies experience different degrees of antifragility, and some of them are not only not vulnerable to changes but also outperform the baseline in a significant part of alternative scenarios. In the present case study, the aggressive strategy obtained the highest antifragility score and was able to turn environmental changes into opportunities. This finding suggests that in conditions of fluctuating, unstable, and complex environments, choosing strategies that have the capacity to exploit change (rather than simply resist it) can promote decision-making from a conservative to an opportunity-oriented mode. Overall, the results of this study indicate that the antifragility approach can provide a structured and numerical framework for strategy selection in turbulent environments. This approach, in line with previous literature that emphasizes the exploitation of volatility and the capacity for innovation, guides managers' decision-making path from a focus solely on risk reduction towards opportunity-based decision-making and enhancing competitive advantage (Sorourkhah, 2024). Therefore, antifragility can be recognized as an important practical and theoretical concept in strategic management in the era of uncertainty and provides new research horizons for the development of more data-driven and generalized models.

Abstract Abstract The aim of this study is to investigate sales drivers in assessing the authenticity of emerging brands through measuring deep neural networks (DNN). The present study is applicable in terms of purpose, and mixed (qualitative-quantitative) in terms of implementation, and is an exploratory research type. The statistical population of the study in the qualitative section included 10 experts and academic experts proficient and familiar with the fields of marketing and branding. The research collection tool was a semi-structured interview. Data analysis in the qualitative section was carried out through coding and using MAXQDA software, and in the quantitative section using neural net and MATLAB software. The results of the study showed that 8 research criteria were identified, including brand continuity, brand credibility, brand coherence, brand symbolism, market homogeneity, market competition, market infrastructure, and political decisions. Also, all predictions of the proposed artificial neural network are made correctly, and the network is able to correctly identify and classify all outputs based on the defined inputs. Introduction In today's business world, brands play an important role in creating differentiation and attracting customers. Brand authenticity is one of the key concepts in modern marketing that refers to the extent to which customers perceive the credibility, honesty, and true values ​​of a brand (Morhart et al, 2015). Brand authenticity is especially important for emerging brands that are in the early stages of their development. This concept is especially important for emerging brands that do not yet have a strong and established position in the minds of customers (Beverland, 2021). Investigating the interaction between sales drivers and the authenticity of emerging brands is important due to the challenges in this field, especially in competitive markets. On one hand, the use of sales incentives can help increase brand awareness and accelerate customers’ decision-making process. On the other hand, if these incentives are not designed properly, they may lead to a decrease in the perception of brand authenticity (Steenkamp & Geyskens, 2014). For example, excessive discounts or excessive use of promotional tools may send contradictory messages about the true value of the brand (Dwivedi & McDonald, 2018). On the other hand, sales incentives can have a positive impact on brand authenticity in certain situations. For example, offering targeted and temporary discounts or using incentives consistent with the brand’s values ​​and message may strengthen customers’ emotional connection with the brand and improve their perception of brand authenticity (Holt, 2020). A review of the literature on the impact of sales incentives on consumer behavior and brand authenticity reveals that although there are studies on the impact of sales incentives on consumer behavior and brand authenticity, a limited number of studies have focused specifically on emerging brands and their specific challenges. In particular, fewer studies have examined how sales incentives can be used in a way that both helps increase short-term sales and reinforces the image of brand authenticity. Therefore, the main research question is: What is the role of sales incentives on the authenticity of emerging brands?  Theoretical Framework Sales Incentives Sales incentives are one of the most effective marketing tools that are widely used to stimulate consumer buying behavior, increase sales, and create competitive advantage. These incentives are usually designed as short-term strategies that aim to immediately increase demand (Chandon et al, 2000). Sales incentives can have significant effects on consumer purchasing behavior, and can encourage consumers to make immediate purchases by creating a sense of urgency and greater value. Price discounts, especially on high-priced products or price-sensitive categories, often lead to increased sales volume (Liao et al, 2021). Brand Authenticity Brand authenticity refers to the alignment of a brand’s actions with its values, history, and promises, and refers to a brand’s ability to demonstrate honesty and align with customer expectations. This concept encompasses several dimensions, including authenticity, coherence, and transparency (Napoli et al, 2016). This concept is particularly important for emerging and developing brands, as consumers often seek real values ​​and meaningful connections when choosing brands (Bruhn et al, 2017). Mousavi et al, (2023) investigated the effect of brand authenticity on the self-concept of domestic brand customers by explaining the mediating role of brand social power. The research findings show that brand authenticity has a positive and significant effect on customer self-concept. Also; brand social power has a positive and significant effect on customer self-concept. As a general conclusion, it should be added that products similar to the characteristics of authentic brands in terms of customer self-image are more likely to be selected for use by the target customer community due to the social power of the brand. Nurani Kutenaee et al, (2021) in a study titled "Modeling Store Brand Competitiveness Based on the Environmental Stimuli Pattern in Chain Stores: A Mixed Approach" concluded that managing external and internal environmental stimuli in the store through an enjoyable shopping experience can create authenticity, attachment, and store brand image, which results in increasing market share, creating a powerful brand and competitive advantage, and ultimately making the store brand competitive.  Research Methodology The present study is applicable in terms of purpose, and mixed (qualitative-quantitative) in terms of implementation, and is an exploratory research type. The statistical population of the study in the qualitative section included 10 experts and academic experts proficient and familiar with the fields of marketing and branding. The research collection tool was a semi-structured interview. Research findings Data analysis in the qualitative section was carried out through coding and using MAXQDA software, and in the quantitative section using neural net and MATLAB software. The results of the study showed that 8 research criteria were identified, including brand continuity, brand credibility, brand coherence, brand symbolism, market homogeneity, market competition, market infrastructure, and political decisions. Also, all predictions of the proposed artificial neural network are made correctly, and the network is able to correctly identify and classify all outputs based on the defined inputs. Conclusion The present study was conducted with the aim of investigating sales drivers in evaluating the authenticity of emerging brands through measuring deep neural networks (DNN). The results of this study are in line with the results of Mousavi et al, (2023), Nurani Kutenaee et al, (2021), Mohammadi et al, (2021), Grewal et al, (2020), Holt (2020), Yavarigohar & Koraghli (2019), Van-Dat (2018), Dwivedi & McDonald (2018), Chen et al, (2017), Napoli et al, (2014), and Steenkamp & Geyskens (2014). Holt (2020) concluded in their study that emerging brands should use sales stimuli that reflect real values ​​and cultures. In this study, brand symbolism, which has a cultural context, has been pointed out in a relatively similar way, which can play a role as one of the criteria related to sales stimuli. According to the research results, the following suggestions are made: Commercialization of knowledge-based goods in the Iranian pharmaceutical industry can help develop research and innovation in this industry. It is suggested that by producing and supplying innovative drugs, research should be conducted to gain more knowledge about diseases and their treatment methods. This research can lead to scientific and medical advances in the country and improve treatment methods.

Abstract Abstract
The main goal of this research is to design the maturity model of the fourth industrial revolution in the supply chain of banking services and the development of digital banking with the data-based approach. The current research is, qualitative type based on strategy, and it is in the basic research categories in terms of goal. The data collection method is field research, and the data collection tool is a semi-structured interview. The participants of the current research are the senior managers of the country's banks, experts and activists in the field of digital banking, and using the sampling method, 10 people were selected as participants in the research. It should be noted that the interview has progressed to theoretical saturation. Qualitative data obtained through interviews were analyzed using the data-based theorizing method. Qualitative data analysis was done using Max Kyoda software version 2020. According to the results obtained, the categories identified in this research include ten categories in the causal conditions section, seven categories as components of the central phenomenon, four categories related to contextual conditions, eleven categories in the strategies section, and seven categories for intervening conditions. And finally, there are eight categories for the consequent part of the model.
Introduction
In the last few years, technology has been developing rapidly and big data or mega data, computing or cloud computing, smartphones and high bandwidth are now commonplace. Examining and comparing the effects of technology in other industries shows that digital has created great changes in the status and value of the industry (Barazideh et al., 2024). There is much pressure to change and transform the banking industry. Customer experiences and expectations, technological capabilities, legal requirements, demographic and lifestyle issues, and economics all create an inevitable necessity for change. It is obvious that the digital age has had a pervasive impact on every industry and organization (Ramzanpour Osmavandani et al., 2024). Digital transformation management is the determining factor of the survival or destruction of organizations in this era, and now it is the era of transition from traditional models to technology-oriented and value-creating business models. In recent years, the new generation of banking under the name of digital banking has been operationalized in the world and the main attention of leading banks has been focused around the axis of digital transformation (Karimi et al., 2023. (
Over the years, the development of new services in the banking and financial sector has been driven by telephone banking, online banking and other forms of fintech (Hasan et al., 2020). These developments enabled the banking sector to overcome the global challenges associated with facilitating transactions across industries, thanks to improvements in accessibility, speed, efficiency, effectiveness and transparency. However, the introduction of digital banking, focusing on technologies such as blockchain, has been announced as the next evolutionary step that will transform not only the banking and financial industry, but also the nature and execution of corporate transactions (Osmain et al., 2021).
Therefore, the use of new mechanisms such as blockchain with all kinds of monetary services brings the possibility of causing widespread disruption in the banking industry. As a result, it includes activities such as facilitating international money transfers, smart contracts, digital banking, office automation and digital assets. Thus, it provides an opportunity for relevant stakeholders to contribute to the improvement of openness, trust and privacy issues. However, although blockchain technology has provided many opportunities for businesses, it is necessary to realize that there will be many problems and complexities in the areas of adoption as well as in the areas of technology and regulation. For example, the numerous risks caused by the loss of digital money and cyber security breaches are examples of recent incidents that have revealed a high level of risks associated with the use of blockchain technologies in banking and finance (Demirhan et al., 2021). According to the items mentioned above, the main question of the current research is:
How to fully recognize, evaluate and design the maturity dimensions of the fourth industrial revolution in the supply chain of banking services and the development of digital banking using a data-base approach, so that banks can use modern optimizing technologies to provide their services, improve financial performance and customer experience?
Theoretical framework
In the fourth industrial revolution, the emergence of major technologies such as artificial intelligence and the Internet of Objects has led to extensive changes in business models, among which banks have had a greater share of these developments. Despite the research conducted in the field of business model change in the fourth industrial revolution, the issue of transformation in the supply chain of banking services in the fourth industrial revolution has been almost neglected (Shahabi et al., 2021). The competition between banks and financial institutions, the emergence of digital technologies, the problems caused by sanctions, the continuous change of customer requests and the needs of society have made planning for the development of digital banking an undeniable necessity for banks. Digital technologies (such as social media, mobile, cloud computing, Internet of Objects and other digital technologies) offer great opportunities for organizations to provide new value propositions, especially by combining their existing capabilities with new digital capabilities. In addition, digital technologies will increase user experience and create new revenue streams (Asqari et al., 2018).
Chaidar et al., (2023) in their paper investigated the dynamic relationship between fintech investments and financial performance and showed whether the size of the bank can affect its performance in the field of digital transformation (digitalization) or not. The fully modified ordinary least squares model is estimated for 23 European banks in the whole period from 2010 to 2019 and for two sub-periods from 2010 to 2014 and from 2015 to 2019. Econometric results show that fintech is positively and significantly related to bank profitability, in the sense that the more digital interaction banks have, the higher the profitability.
 In their research, Avianto et al., (2024) analyzed the differences in book prices of banks based on the level of digitalization and investigated the effect of digitization and financial factors on the value of book prices of banks with digital services. The analysis of the results of this study shows that higher levels of digitalization are associated with improvements in the share of fee income, return on equity and price to book value of the bank. Additionally, the level of digitization enhances equity returns, improves non-performing loans and increases capital utilization, all of which significantly impact book value.
Zhao et al., (2024) in their study investigate the effects of corporate digitization on green transformation in listed resource-based companies in China from 2009 to 2021. The data analysis of this research shows that digital transformation significantly increases the sustainability of these companies.
Ayinaddis et al., (2024) in their study analyzed the perceived effects of digital transformation in the banking industry and identified the factors that most affect banking performance and business volume. Based on the obtained results, the strengthening of the impact of digital transformation in banking and the vital importance of employees' skills and the digital experience of shareholders have been highlighted.
Research methodology
Based on the type of data, this research is considered as a qualitative research and according to the purpose of the research, it is considered as a basic and exploratory research, which seeks to design a model for the maturity of the fourth industrial revolution in the supply chain of banking services and the development of digital banking.. The participants of the research are senior managers of the country's banks and experts and activists in the field of digital banking, 10 of whom were selected by theoretical sampling and interviewed. In selecting the samples, an effort was made to select the most knowledgeable and well-known managers. The interviews have been repeated in order to share the preliminary findings, complete, correct, revise and adjust the data.
Research findings
In the current research, according to the purpose of the research to design a model for the maturity dimensions of the fourth industrial revolution in the supply chain of banking services and the development of digital banking, the researcher has used the data-based theorizing method in the style of Strauss and Corbin. In this research, the researcher started the interviews with targeted sampling of the desired samples and questions about the maturity dimensions of the fourth industrial revolution in the supply chain of banking services and the development of digital banking. In the central coding step, while the interviews were progressing, the relationship of the categories in the relative sampling of the codes of the interviews was determined to some extent. In the last step of selective coding, a selective sampling of the categories was carried out and according to the causal conditions raised in connection with the maturity of the fourth industrial revolution in the supply chain of banking services and the development of digital banking from the samples in connection with Phenomenon-oriented, strategies, contextual conditions, intervening conditions, and finally, the consequences of questions were asked and finally, in the supplementary stage, according to the literature of this field and theoretical foundations, the final form of the model was completed.
Conclusion
In the era of technological advancement and innovative disruption, digital banking with artificial intelligence has emerged as an alternative technology for channel management, services and online banking solutions. Although the emergence of artificial intelligence in digital banking has enriched digital banking services, the adoption of digital banking with artificial intelligence and meeting the expectations of digital banking users is still an important issue. According to the results obtained from the model presented in this article, and according to the strategies identified in this model, the country's banks can create value for customers and improve their financial performance. Also, other consequences include personalized services, structural improvement, creation of new institutions and organizations, re-engineering of processes, creation of a suitable banking business model and finally improvement of customer performance.

Abstract Abstract This research systematically reviews the literature on ambidexterity strategies in the development of the digital economy. The main questions addressed are: What is the current state of knowledge in this field and related studies? What research proposals can advance the understanding of ambidexterity in the context of digital economy development? The philosophy of this research is interpretive, aligning with the application of ambidexterity in industries and companies focusing on the development of the digital economy. An inductive, qualitative approach is adopted, analyzing research articles from the Web of Science database using a systematic literature review method. The bibliometric analysis follows the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA 2020) guidelines, covering 114 articles and employing VOSviewer software for analysis. The findings indicate that, given the upward trend in the number of studies in recent years, this field is experiencing scientific growth. Based on the results, five clusters emerge in the word analysis diagram: (1) organizational ambidexterity, dynamic capabilities, market orientation, digital economy, big data, and absorptive capacity; (2) ambidexterity, Industry 4.0, information technology, innovation, organizational agility, strategic alignment; (3) competitive advantage, digital transformation, resource-based view; (4) exploration, exploitation; and (5) sustainability. Introduction The turbulence and complexity of today's business environment have increased significantly. The number of influencing factors has grown, and their rate of change has accelerated. Under such conditions, the future becomes ambiguous and unpredictable, with environmental trends and opportunities remaining unstable. This increasing turbulence reduces the stability and predictability of the future. Consequently, traditional approaches to strategic planning, in a world where key variables are constantly changing and difficult to predict, have low validity and reliability. In this environment, organizations require new mental models to make dynamic strategic decisions and translate them into strategic changes. Preparedness, responsiveness, and strategic flexibility are crucial components for dealing with turbulence and complexity. Organizations must generate and test ideas, learning from their decisions and the environment, to carve a path to competitive advantage. Possessing an adaptive advantage, in addition to a competitive one, is essential. Economic enterprises must continuously analyze the environment, identify drivers of change, and examine the macro and micro trends these drivers create in the broader environment and industry. They should develop related scenarios and subsequently analyze their key capabilities and competencies. Identifying resource and capability gaps to face the future is essential. Through strategic planning, they can move toward adaptability to the evolving environment (Harandi et al., 2024). An organization's ability to maintain a competitive advantage by leveraging existing capabilities while simultaneously innovating and acquiring new competencies is crucial for survival. The concept that organizations must continuously explore new opportunities and exploit existing assets to remain resilient in complex and turbulent environments is significant in organizational literature. Achieving a balance between exploration and exploitation is a prerequisite for resilience and sustainability in modern organizations. The capacity to manage and balance creative destruction and innovation with the exploitation of existing resources is essential for businesses in the digital domain (Harandi et al., 2024). This article addresses the depth and body of knowledge regarding ambidextrous strategy in the context of these discontinuities. By reviewing the literature on ambidextrous strategy within these discontinuities, we clarify future research areas. Therefore, this article's contribution lies in explaining the knowledge structure of this field and proposing areas for future research. Given the above points and the growth of studies in ambidexterity, the theoretical gap addressed by this research is the lack of a systematic and coherent study of the body of knowledge in this field within the context of the digital economy. Accordingly, the main objective of this research is to systematically review the literature on ambidextrous strategy in the development of the digital economy. This involves a systematic review of existing literature on the use of ambidextrous strategy in addressing environmental discontinuities caused by digital transformation, the Fourth Industrial Revolution, and the development of the digital economy. This study is centered around the following questions: What is the configuration and body of knowledge regarding ambidextrous strategy in the context of the digital economy? What research proposals can advance the body of knowledge in ambidexterity within digital economy development? Which aspects of ambidexterity have received more attention, and which could be subjects for further research? Subsequently, we have endeavored to extract suggestions for future research. Theoretical Framework Digital Economy The development of the digital economy has led to significant transformations in the economic structure of society, bringing about fundamental changes. One notable example is the shift in financing methods for businesses and ideas. Most traditional companies heavily rely on personal financing from their owners and sometimes meet financial needs through bank loans. Except for a few exceptions, these companies experience low growth rates and take decades to reach their peak. However, in the digital age, the widespread use of the Internet has provided two important tools for startups: crowdfunding and collective creativity. These tools, along with financing through joint venture capital investments, increase the likelihood of success for new companies aiming to leverage emerging technologies such as artificial intelligence in competition with giants like Google, Amazon, or Facebook. Additionally, changes in the competitive structure are observable. Companies have accumulated competitive advantages to stay at the top of the competition, but significant technological advancements can fundamentally change the competitive landscape and eliminate such advantages. Another fundamental change is that innovative ideas no longer only emerge from expensive laboratories with heavy investments. Instead, garages, small offices in incubators, and accelerators are generating new ideas and disruptive businesses just as effectively as academic settings. Today, many advanced countries recognize the importance of these workspaces and are making significant efforts to stimulate and encourage technological innovation (Makridakis, 2017). Ambidexterity Tushman first introduced the concept of ambidexterity in the context of organizational structures for innovation. March, Tushman, and O'Reilly expanded on this in the field of organizational learning, proposing two methods—exploration and exploitation—for optimal resource utilization. Ambidexterity refers to an organization's ability to exploit current capabilities while simultaneously exploring future opportunities (Alghamdi, 2018). As environmental changes occur, the relative fit of business subunits within a company fluctuates, prompting senior managers to reconfigure and reallocate resources to adapt. This approach, known as dynamic capabilities, emphasizes the key role of strategic leadership in appropriately adapting, integrating, and reconfiguring organizational skills and resources to match changing environments (O'Reilly III et al., 2009). A company's ability to be ambidextrous is at the core of dynamic capabilities. Ambidexterity requires senior managers to perform two critical tasks: first, to accurately understand changes in their competitive environment, including potential shifts in technology, competition, customers, and regulations; second, to respond to these opportunities and threats by reconfiguring tangible and intangible assets to address new challenges (O'Reilly III & Tushman, 2011). Methodology The philosophy of this research is interpretive, aiming to develop the application of ambidexterity in industries and companies within the theme of developing the digital economy. The research adopts an inductive, qualitative approach, utilizing research articles from the Web of Science database. It employs a systematic literature review method using bibliometric techniques, following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA 2020) guidelines, and is analyzed with VOS viewer software. The PRISMA statement, first published in 2009, was designed to help systematic review authors transparently report why the review was conducted, what was done, and what was found. Over the past decade, advancements in systematic review methodology and terminology have necessitated an update to the guidelines. The PRISMA 2020 statement replaces the 2009 statement and includes new reporting guidance reflecting advances in methods for identifying, selecting, evaluating, and synthesizing studies. The structure and presentation of items have been revised to facilitate implementation (Page et al., 2021). Discussion and Results The Web of Science database was used to extract relevant studies. Initially, only research articles published with the two keywords "ambidexterity" and "digital economy" were retrieved, totaling only 16 articles. This small number indicates that this area requires more scholarly attention. The figure below shows the output of the keyword frequency analysis in these articles. Subsequently, the search results were input into VOSviewer software to visualize the connections. Out of 642 keywords, 64 were repeated at least four times. To make a more informed selection, 18 keywords with significant semantic relevance to the content of the articles and the existing literature were chosen for relational analysis. The remaining keywords, based on the literature review and article analysis, were not necessarily relevant to the field under study. Since the time range of the published articles was not limited, this research included the most up-to-date studies available in the Web of Science database. The publication trend also shows an upward trajectory. The chart below illustrates the keyword frequency analysis from the search using the keywords "ambidexterity" in conjunction with "digital transformation," "digital economy," and "Industry 4.0" from the Web of Science database. Discussion and Conclusion In addition to the keywords, five clusters are observed in the keyword analysis chart: (1) organizational ambidexterity, dynamic capabilities, market orientation, digital economy, big data, and absorptive capacity; (2) ambidexterity, Industry 4.0, information technology, innovation, organizational agility, and strategic alignment; (3) competitive advantage, digital transformation, resource-based view; (4) exploration, exploitation; and (5) sustainability. Although other keywords could have appeared in this analysis based on their frequency, the items shown were filtered to highlight their importance and to indicate their frequency and relationships for future discussions. These clusters have revealed important keywords that seem to require separate studies on their connections with the three main topics of "digital transformation," "Industry 4.0," and "digital economy." It is suggested that these areas be the subjects of future 

Abstract Abstract The present study aims to provide a recurring marketing strategy with a customer credibility determination approach using neural network data mining. The method of this research is applicable in terms of purpose, and is of a mixed type (qualitative-quantitative) in terms of implementation. First, by using the content analysis method, the key components of recurring marketing were identified and the initial optimization framework was designed. Then, the Delphi method and structured interviews with experts in the field of marketing and customer management were used to validate the indicators. In this study, a combination of the K-Means++ clustering algorithm and the RFM model was used to segment customers and identify groups in need of marketing interventions. Also, by using decision trees and artificial neural networks, the rules for validating customers and the accuracy of predicting their behavior have been improved. The research findings show that this combined framework not only improves the accuracy of clustering, but also allows designing personalized strategies for each group of customers. The results indicate that the recency index has the greatest impact in determining customer value, and the integration of transactional data with demographic and behavioral characteristics provides more comprehensive insights for marketing decisions. By filling the gaps in previous research, especially in the area of ​​interpretability and generalizability of models, this research has taken an effective step towards developing theoretical and applicable knowledge of return marketing. Introduction Customer value is defined as the perception of what a product or service can be useful to the customer, compared to possible alternatives. By benefit, we mean whether the customer feels that he or she receives certain benefits by purchasing a product in exchange for a certain amount of money. Lifetime value shows the profit from the customer relationship for the entire period from the moment he saw the first advertisement or registered on the site to the last purchase. Lifetime value affects the amount of revenue: the more regular customers a company has, the higher its revenue. How can you calculate lifetime value? To calculate lifetime value, you can multiply the average purchase size by the number of purchases and the retention period. Or divide the total revenue by the total number of users for a given period. In this regard, customer credit is one of the crucial issues and is very important for maintaining the financial security and sustainability of the organization. One of the fundamental challenges in this area is identifying the appropriate indicators for crediting and scoring customers. Therefore, determining correct and reliable indicators is very challenging. Segmenting customers into different prominent groups and designing personalized activities for each cluster is a vital technique for determining marketing tactics (Rajesh et al., 2024). Also, to score customers, there must be an appropriate and fair scoring system. This system must be able to place customers in different categories by considering credit and behavioral criteria and assign them appropriate points based on their performance (Wulansari & Heikal, 2024). In addition, there is a need to develop methods to evaluate and monitor customers over time. The aim of this research is to present a return marketing strategy with a customer credit determination approach using data mining. However, so far, the inability to discover valuable information contained in the collected data has prevented this data from being converted into valuable and usable knowledge in the organization, and data mining tools can help organizations discover hidden knowledge in a large amount of data (Calisir et al., 2016). Therefore, this research seeks to answer the question: what does a return marketing strategy with a customer credit determination approach using data mining look like? Theoretical Framework Return Marketing Return marketing is a suitable method for retaining current customers and increasing their loyalty. Using retention marketing techniques, customers can be encouraged to buy again and even share the brand with others (East et al., 2006). Customer Loyalty Loyalty is defined as an emotional and attractive connection to a brand and a practical action over time. In this definition, an individual prefers a particular brand to other brands and makes decisions as a psychological commitment to it. (Cardinale et al., 2016). Moula et al. (2024) in a study on customer type discovery and its impact on increasing hotel revenue: a data mining approach, reached the following results. Demand estimation is a fundamental component of revenue management systems. The demand for a product can be determined from the customers who purchase it. Identifying customer types in this field is a challenging endeavor that has recently been solved using metaheuristic and mathematical techniques. The metaheuristic method takes advantage of the lack of data in the business ecosystem, starts with random samples, and uses a fit function as a guide throughout the operation. The approach proposed in this study builds the ecosystem by combining complementary data to identify valuable customer types. The researchers use a new periodic table with additional data to achieve this goal. Subsequently, the relevant data is reduced through a data mining clustering method, and finally an algorithm and fit function are used to identify valuable customer types. To validate this approach, the proposed solution was compared with the latest research in the field, including genetic, memetic, and mathematical approaches. The researchers’ results showed that the model has lower error, with a maximum reduction of 34% and an improvement in value of up to 7%. Singh et al. (2024) examined customer churn in banking: A machine learning approach and a coherent program leveraging data science and management. According to this paper, customer churn in the banking industry occurs when consumers stop using the goods and services offered by the bank for a period of time and then discontinue their relationship with the bank. Therefore, customer retention is essential in today’s highly competitive banking market. In addition, having a strong customer club helps in attracting new consumers by strengthening the trust and referrals of existing customers. These factors make reducing customer churn an important step that banks should follow. In their study, Singh et al. examined banking data and predicted which users were most likely to stop using bank services. The researchers used various machine learning algorithms to analyze the data and show a comparative analysis on different evaluation criteria. Research Methodology The method of this study is applicable in terms of purpose, and mixed (qualitative-quantitative) in terms of implementation. First, by using the content analysis method, the key components of remarketing were identified and the initial optimization framework was designed. Then, the Delphi method and structured interviews with experts in the field of marketing and customer management were used to validate the indicators. Research Findings In this study, a combination of the K-Means++ clustering algorithm and the RFM model was used to segment customers and identify groups in need of marketing interventions. Also, by using decision trees and artificial neural networks, the rules for validating customers and the accuracy of predicting their behavior were improved. The findings of the study show that this combined framework not only improves the accuracy of clustering, but also allows designing personalized strategies for each group of customers. The results indicate that the recency index has the greatest impact in determining customer value, and the integration of transactional data with demographic and behavioral characteristics provides more comprehensive insights for marketing decisions. By filling the gaps in previous research, especially in the area of ​​interpretability and generalizability of models, this study has taken an effective step towards developing theoretical and practical knowledge of return marketing. Conclusion The present study was conducted with the aim of presenting a return marketing strategy with the approach of determining customer credibility using neural network data mining. The results of this study are in line with the results of Moula et al. (2024), Singh et al. (2024), Egorenkov (2024), Dwivedi et al. (2024), Haghi & Hamidi (2024), Khadivar & Mehmannavazan (2023), and Sharifi Esfahani et al. (2023). Dwivedi et al. (2024) showed that service quality and employee behavior have a positive and significant effect on customer satisfaction. To satisfy customers and retain them, customer relationship management must be strong and reliable. Therefore, customer relationship management plays a vital role in increasing market share, productivity, improving in-depth knowledge of the customer and his satisfaction to increase loyalty to the organization. Based on the research results, the following recommendations were made: Offering products tailored to age, occupation, or geographic region (e.g., student facilities for young customers). Offering digital services (e.g., e-wallets) to customers who transact online.