نشریه کاوش های مدیریت بازرگانی
پیاپی 37 (پاییز 1403)

The concept of affect toward brand has been widely used in marketing, advertising, and consumer behavior studies. In fact, every product should have two aspects, one aspect is the performance characteristics of the product that have been considered in the past and the second aspect, which has recently received more attention, is its sensory characteristics. Because decisions are influenced by affects, so retailers' managers and researchers try to create an affective connection with the goods in their customers. The affect that is formed under the influence of a product brand in people can create strong and lasting mental associations when using the product. Today, many companies are trying to create more affect and emotion for their brand and thus engrave it in the mind of the consumer. Due to the importance of the subject, the present study was conducted to investigate the transfer of affects from national brands to store brands through store image in the carpet industry. The effect of hedonic shopping value on affect-based competition between national and store brands, as well as the consequence of store loyalty has been investigated.

 In terms of goals, the present study is a descriptive with an application orientation that has used a survey strategy. A library approach was used to collect data within the related literature and to review the background of the subject and a questionnaire was used to collect the required field data, which was distributed both in paper based and online. Questionnaire questions were designed by adapting authentic Latin and Persian researches. The statistical population of this research is the customers of one of the large and reliable multi-brand carpet stores in Tehran. The sampling method is a targeted non-random method among people who have visited this store at least once. Due to the large number of customers in the store, the population considered unlimited and the sample size was determined by Cochran's formula of at least 384 people, and finally 404 questionnaires were fully answered. In the present study, construct validity was investigated by confirmatory factor analysis using Smart PLS 3.3 software. The content validity of the questionnaire was checked and approved by experts. Also, to set up the questionnaire, the indicators found in past valid researches related to the research subject were used, which improves the validity of the content. The face validity of the questionnaire was also confirmed from the point of view of the respondents. The reliability of the research tool was calculated by calculating the Cronbach's alpha value and the combined reliability coefficient, and based on the results, the values ​​of these two criteria are higher than 0.7, which indicates the stability and internal consistency of the questionnaire. In order to analyze the data in the descriptive statistics section of the SPSS 25 software and in the inferential section of the structural equation modeling (SEM) method with the partial least squares approach and the Smart PLS 3.3 software, it investigated the identified paths of the research according to the conceptual model.

According to the results of this research, the affect towards national brands has a positive and significant effect on the image store and the image store has a positive and significant effect on the affect towards store brand, and this indicates the transfer of positive affect from national brands to store brands through the store image. Based on the findings, the affect towards national brands has a significant positive effect on the affect towards store brand. The hedonic shopping value also modulates the relationship between the affect towards national brands and store brands. Finally, the affect towards store brands also has a significant positive effect on store loyalty. Therefore, all five hypotheses of this research were confirmed.

 The research has paid more attention to the concept of affect, especially the affect towards the brand, and the researcher's effort is to examine the affect-based competition between the national brand and the store brand in multi-brand stores, to gain a new attitude in the brand world to retail stores and managers and Specialists helped. Therefore, retailers are advised to use famous and emotionally influential brands to strengthen the affect towards store brands in order to increase customer loyalty to the store. Also, to increase the affect toward a store brand, target people who have a higher hedonic value, including women.

The current research was conducted with the aim of designing the mechanism of online businesses to prevent post purchase regret behavior of customers using a mixed exploratory method. Regret is a feeling that occurs in the purchase process or after the purchase, and this feeling can be caused by not meeting the initial expectations of the customer. The results of a research conducted in the UK show that about 82% of adults have experienced shopping aversion in the past. Also, according to a survey conducted by Slickdeals in 2022; 74% of Americans have regretted after online shopping. Regret behavior after online shopping is sometimes different and more complicated than offline shopping behavior. Post purchase Regret can be due to individual characteristics; personality traits; product compatibility with customer expectations; customer shopping experience; Confidence in online shopping; time pressure on the customer to buy; Perceived risk in online shopping or even lack of sleep. In addition, when the consumer feels that the product of competing companies is better than the purchased product in terms of price and features or when there is a difference between the previous evaluation of the product and the final purchase, a feeling of regret is created. According to what has been described, so far, various studies have been conducted to investigate the regret behavior of customers after online shopping, but research that comprehensively and systematically considers this behavior has been less investigated. Therefore, the effort of the present research is to design the mechanism of online businesses with a mixed exploratory approach to prevent post purchase regret in online shopping among Iranian customers.

In the qualitative part, the research strategy of Grounded theory and the systematic design of Strauss and Corbin have been used for theorizing. In this plan, the data obtained from the interviews are placed in pre-determined sections, i.e. causal conditions, core category, context, intervening conditions, strategies and consequences. The data collection tool was a semi-structured interview and its questions were designed based on the components of the paradigm model. Data triangulation strategy was used to conduct the interviews and 14 experts including university professors, online business industry activists and web businesses were interviewed through judgmental sampling. In order to check validity, research members who included 4 university professors and a Ph.D. student reviewed the coding process and their points of view were applied in the coding process. Retest method was used to calculate reliability. The reliability method of two evaluators was used to calculate the reliability. In this way, among the conducted interviews, 3 interviews were selected as samples and evaluated by another researcher. Cohen's kappa coefficient was used to calculate reliability. Kappa coefficient equal to 0.811 was obtained, which indicates almost complete agreement between two evaluators. In the quantitative part, structural equation modeling was used to evaluate and validate the designed model, and SmartPLS software was used to perform its calculations. The statistical population was the customers of the Digikala online store who made online purchases from the home appliances department from 2013 onwards and registered their complaints in the company's complaints department. Using simple random sampling, 800 emails were sent to customers and 396 analyzable questionnaires were obtained. For the validity of the quantitative part of the research, confirmatory factor analysis, convergent and divergent validity were used. For reliability, composite reliability and Cronbach's alpha were used.

In conducting the research, after implementing the interviews, their key points were determined and the primary codes of each were extracted. The interviews continued until the data reached theoretical saturation and no new points were observed in the interviews. After conducting 14 interviews, 457 codes were obtained as primary codes, which created 71 separate concepts by removing similar codes. In the axial coding stage, one of the categories obtained from open coding was identified as the category that is the basis of the research theory. Then other categories, i.e. causal conditions, context and intervening conditions, strategies and consequences were related to it. In this way, 71 obtained concepts were classified and placed in 20 categories. In the selective coding stage, the 20 extracted categories were linked to each other and the paradigm model of the research was designed using MAXQDA software.In the quantitative part, structural equations used to validate the model. First, in order to check the normality of the data, the Kolmogorov Smirnov test was used. The results showed that the data is not normal, so the PLS method was used to estimate and test the model. To evaluate the confirmatory factor analysis model, there are several fit indices that must be interpreted together. In this research, Goodness of Fit index, Normed Fit Index and Standardized Root Mean Square Residual were used to evaluate the confirmatory factor analysis model. In this research, the GOF is equal to 0.567, the NFI is equal to 0.848, and the SRMR index equal to 0.061. In general, according to all three fit indices, it can be said that the data of this research has a good fit and the questions are aligned with the theoretical framework.

The model obtained from the present research provides a comprehensive view to the companies active in the field of online business so that they can make decisions regarding the appropriate marketing and sales strategies by knowing the buying behavior of online customers. Researchers who intend to study the behavior of post purchase regret in the online environment can study regret in purchases goods that are likely to have more regret. For example, possible regret in choosing luxury and expensive goods, or cheap goods that have low quality. Also, the evaluation of post purchase regret in products that affect the environment. Investigating the effect of discounts offered on sites and putting time pressure on customer are other areas that are recommended to researchers.

Nowadays, tourism services are provided through the internet. Since customers are very important for online travel agencies and they guarantee profit for these agencies, managers of these businesses should use their power to improve the quality of tourism services in order to increase the perceived value, satisfaction and trust of customers and cause them to return and buy again. One of the important ways to satisfy customers is to improve the quality of tourists' relationship with travel agencies' websites. Therefore, if the quality of services provided by online travel agencies does not meet the demands and expectations of customers, the level of customer satisfaction will decrease and the negative feelings of customers towards the performance of travel agencies will increase, and the quality of communication between customers and travel agencies and the intention to repurchase services from them under is affected. But the point is that not all customers who suffer when receiving quality services seek revenge or retaliatory behavior. In this situation, customers may adopt non-aggressive behavior such as forgiveness. Studies show that if the feeling of forgiveness is strengthened in tourists, they will partially forget their negative experiences and even prefer to replace such experiences with pleasant memories and feelings. Stimulating customer forgiveness can strengthen the willingness to receive services again.Another solution to satisfy customers is to improve the quality of tourists' relationship with the accommodation centers. Since tourists make a part of the purchase and search process based on trusting the online travel agency, they expect to see what they expected after visiting the place. Otherwise, failure to fulfill the customer expectations leads to dissatisfaction and negative feelings in customers. These feelings cause different behaviors such as negative word-of-mouth advertising and customers turning away from repurchasing tourism services.

The current research is applied in terms of orientation and descriptive in nature. The statistical population includes all customers of the Alibaba tourism website in Mashhad. The researcher managed to collect 392 statistical samples using the available non-probability sampling method. The collection tool in the current research is the standard research questionnaire.

The first hypothesis test indicated that the negative feelings of customers have a significant effect on the quality of the relationship between customers and Alibaba Travel Agency. People usually expect to experience a pleasant feeling when traveling, one of these positive feelings is when things go according to their expectations and plans. It must be accepted that a large part of tourists are not interested in the challenges of travel. So any event that troubles tourists and if their expectations are not fulfilled, it will reduce the quality of the relationship between customers and the travel agency. The results of the second hypothesis test confirmed that the negative emotions of clients have a significant effect on the quality of the relationship between clients and hotel. Therefore, if a person doesn't receive suitable facilities in the reserved hotel, he considers this a kind of injustice and feels that the accommodation centers and the agency have provided him with incorrect information. The results of the third hypothesis test showed that the quality of the relationship between customers and accommodation centers has a significant effect on the quality of the relationship between customers and the agency. If tourists establish a proper relationship with accommodation centers, this positive point is strongly transferred to the relationship between the client and the agency. The results of the fourth hypothesis test indicate that if the quality of the agency's relationship with customers improves, it has a significant effect on customers' willingness to buy again. What is very important in the discussion of providing tourism services, especially online, is trust. Since tourists prefer the conditions to be in line with their expectations, the level of trust in a travel agency can greatly increase their confidence in receiving services. For this reason, if tourists find the services of an agency to be fair and attractive, and the agency can gain the trust of users in general, then tourists prefer to repeat their positive experience many times. Finally, customer forgiveness has a moderating role in the effect of relationship quality on repurchase intention.

The results show that if a company intends to be successful in the tourism sector, it cannot be indifferent to the issue of providing online services. The future of the market, at least in the tourism service reservation sector, goes through intermediary companies. This will undoubtedly increase the competition in this field, and companies will be more successful that can have more loyal customers, and loyalty is one of the consequences of the quality of the proper communication of customers with the online travel agency and accommodation centers and policies that strengthen customer forgiveness.

 In today's world, with the expansion of new technologies in the electronic arena in the last decade and the expansion of the use of web technology, facilities such as social networks have been brought, which have caused many changes in their lives. Consumers use these facilities to create, edit or share content, discuss and use it to purchase products and use services.With the development of the Internet, online shopping has increased. Therefore, online consumer attitude is very important and has attracted the attention of researchers. The observed growth in internet sales can be considered as part of the benefits of the internet by providing a large amount of information quickly and cheaply. Until this phenomenon reaches its full potential, business owners who use e-commerce as a distribution channel need to understand from online shoppers what products and services they buy online, why they shop online, and how a non-online shopper can. Can become an online shopper to increase their sales in this way, they escape the scrutiny. Once this information is available, retailers can develop a clear strategy to retain existing customers as well as attract future customers. After all, online consumer attitude is a problem that has involved many researchers. The basic question is which criteria determine the consumer's decision to buy from an electronic store, and therefore the consumer's attitude is very important to study the intention to buy online. Due to the increasing growth of companies from internet platforms and content production in different internet platforms, nowadays content generation plays a very important role in the purchase intention of consumers. The aim of the current research is to investigate the factors affecting the consumer's attitude towards the content generated by the user and the intention to online purchase in Digikala.

 This research is applied in terms of purpose and descriptive in terms of survey type. The statistical population of the research includes customers of Digikala's Instagram page, and the sample size is 384 people based on Cochran's formula due to the unlimited sample size. A non-random sampling method is available. The library method has been used to conduct primary and preliminary studies. In order to collect data, the standard electronic questionnaire of Mathur and Gangouni (2021) was used. The current research was conducted in the first half of 1401.

In order to analyze the data, the method of structural equation modeling with partial least squares approach and SPSS and PLS software was used. The results of the research showed that the interaction with the brand has an effect on the content generated by the user among the customers of the Digikala store; Perceived credibility affects user-generated content among Digikala store customers; Perceived profit does not affect user-generated content among Digikala store customers; The quality of information does not affect the content produced by the user among the customers of the Digikala store, and finally the content generated by the user has an effect on the intention to online purchase among the customers of the Digikala. Interaction with the brand with an impact factor of 46. The highest impact is perceived credibility with an impact factor of 309. The second place is the quality of information with an impact factor of 039. The third place and finally the perceived usefulness with an impact factor of 037. In the fourth place, the impact on the content generated by the user. have

The present research was conducted due to the high effects of the Internet and the virtual world on the business world, which itself contains complications, and in the present research, one aspect of these complications has been addressed. Companies that operate in the online field should pay special attention to the type of user-friendly content and the quality and content and always monitor the different content of users in the virtual space in order to be able to identify consumers' attitudes and online shopping behavior more accurately.

The big data revolution is underway and growing rapidly. Retail actors Internet professionals such as retail managers, retail researchers, as well as public policy investors, retail investors are looking to exploit big data to identify opportunities and challenges ahead. By reviewing the studies and previous researches, the researchers first extracted the relevant concepts, then the experts were used with the help of the interview method. The selection method of 15 experts was based on expertise and availability. Also, by using the thematic qualitative research method, concepts have been categorized. The pattern of big data opportunities and challenges in Iran's internet retailing at the store consists of 15 sub-themes which were categorized into four activity levels: store, company, customer, marke; and it showed that retail companies can gain a competitive advantage by exploiting opportunities and managing challenges, and use it to predict the needs of customers and their buying patterns. Retail actors Internet professionals such as retail managers, retail researchers, as well as public policy investors, retail investors are looking to exploit big data to identify opportunities and challenges ahead. With the expansion of the database, the need to use big data was raised in such a way that big data based on the data collected from the meetings of company managers with each other and customers improves the operational, social, financial and environmental performance of the company, the development of dynamic marketing, Identifying the faulty processes of the system, improving the level of current experiences of retail marketers and creating marketing content with the help of different information sources. Big data offers many new opportunities to create value for retailers give; some of which include price optimization, segmentation of customers, inventory management, analysis of customer expectations; Optimizing marketing processes and managing consumer behavior in the way of customers to create value; product offer; predicting the acceptance rate of the new product; Knowing customers; development of new products and services; Determining the customer's path to create value; creating interest in innovative services; Forecasting the supply chain of needs based on the analysis of expectations can be mentioned.

In this research, the qualitative research method of thematic analysis was used to collect data. In the first step, the data was coded in a systematic way in the entire data set, then the data related to each code was collected. In the second step, before drawing the network of themes, the themes should be sorted and presented in the form of a report. The statistical population of the current research are experts in the fields of marketing and business intelligence; Due to the limitation of the population, the sample size will be equal to the population size. The number of expert groups was 15 people (10 men and 5 women), of which 6 people had bachelor's degrees, 6 people had master's degrees, and 3 people had doctorate degrees in business and information technology fields. The researchers, together with the research colleague, coded the number of three interviews and the percentage of agreement within the subject, which is used as the reliability index of the analysis, which finally has a reliability value of 0.86.

After collecting and analyzing the content of the interviews from the experts and extracting the key components related to the opportunities and challenges of big data in online retail, in order to reach a consensus regarding the factors extracted from the studies and Delphi method was used to interview experts. At the end of this stage, concepts (codes) that seem to say something specific about the research questions can be organized into broader themes. The themes were mainly descriptive; That is, they described patterns in the data that are related to the research question. Most of the concepts are related to one theme, although some of them are related to more than one theme. Therefore, in the next step, the created sub-themes cover well the concepts under their inclusion, and appropriate main themes can be created with the opinion of experts. After determining the final list of concepts; They were categorized in the four activity levels of store, company, customer and market in the form of a pattern of opportunities and challenges based on big data in online retail.

Store-level online retailers use big data for cross-selling marketing, location-based marketing, in-store behavior analysis, and price comparison. ​Also, at the company level, the opportunities resulting from inventory management can include joint investment in the supply chain and sales channels, cost-effective ordering by evaluating the distribution system, feasibility of customer expectations, and creating emerging markets. Due to the maximum use of big data at the customer level, online retail stores have access to many opportunities by making customer profiles based on their demographic, geographic, and psychological characteristics can achieve a competitive advantage. Big data has been able to point to the opportunity to share knowledge with other industries, the opportunity to use local strategies, the opportunity to maximize value for customers through innovative business models and expand channels by partnering with business partners, as well as business partners through analysis And data analysis by means of big data are used for product development by adapting to customer demands through the supply chain and sharing data with business partners in order to achieve business success.

 The big data revolution is underway and growing rapidly. Retail actors Internet professionals such as retail managers, retail researchers, as well as public policy investors, retail investors are looking to exploit big data to identify opportunities and challenges ahead. By reviewing the studies and previous researches, the researchers first extracted the relevant concepts, then the experts were used with the help of the interview method. The selection method of 15 experts was based on expertise and availability. Also, by using the thematic qualitative research method, concepts have been categorized. The pattern of big data opportunities and challenges in Iran's internet retailing at the store consists of 15 sub-themes which were categorized into four activity levels: store, company, customer, marke; and it showed that retail companies can gain a competitive advantage by exploiting opportunities and managing challenges, and use it to predict the needs of customers and their buying patterns. Retail actors Internet professionals such as retail managers, retail researchers, as well as public policy investors, retail investors are looking to exploit big data to identify opportunities and challenges ahead. With the expansion of the database, the need to use big data was raised in such a way that big data based on the data collected from the meetings of company managers with each other and customers improves the operational, social, financial and environmental performance of the company, the development of dynamic marketing, Identifying the faulty processes of the system, improving the level of current experiences of retail marketers and creating marketing content with the help of different information sources. Big data offers many new opportunities to create value for retailers give; some of which include price optimization, segmentation of customers, inventory management, analysis of customer expectations; Optimizing marketing processes and managing consumer behavior in the way of customers to create value; product offer; predicting the acceptance rate of the new product; Knowing customers; development of new products and services; Determining the customer's path to create value; creating interest in innovative services; Forecasting the supply chain of needs based on the analysis of expectations can be mentioned.

 In this research, the qualitative research method of thematic analysis was used to collect data. In the first step, the data was coded in a systematic way in the entire data set, then the data related to each code was collected. In the second step, before drawing the network of themes, the themes should be sorted and presented in the form of a report. The statistical population of the current research are experts in the fields of marketing and business intelligence; Due to the limitation of the population, the sample size will be equal to the population size. The number of expert groups was 15 people (10 men and 5 women), of which 6 people had bachelor's degrees, 6 people had master's degrees, and 3 people had doctorate degrees in business and information technology fields. The researchers, together with the research colleague, coded the number of three interviews and the percentage of agreement within the subject, which is used as the reliability index of the analysis, which finally has a reliability value of 0.86.

 After collecting and analyzing the content of the interviews from the experts and extracting the key components related to the opportunities and challenges of big data in online retail, in order to reach a consensus regarding the factors extracted from the studies and Delphi method was used to interview experts. At the end of this stage, concepts (codes) that seem to say something specific about the research questions can be organized into broader themes. The themes were mainly descriptive; That is, they described patterns in the data that are related to the research question. Most of the concepts are related to one theme, although some of them are related to more than one theme. Therefore, in the next step, the created sub-themes cover well the concepts under their inclusion, and appropriate main themes can be created with the opinion of experts. After determining the final list of concepts; They were categorized in the four activity levels of store, company, customer and market in the form of a pattern of opportunities and challenges based on big data in online retail.

 Store-level online retailers use big data for cross-selling marketing, location-based marketing, in-store behavior analysis, and price comparison. ​Also, at the company level, the opportunities resulting from inventory management can include joint investment in the supply chain and sales channels, cost-effective ordering by evaluating the distribution system, feasibility of customer expectations, and creating emerging markets. Due to the maximum use of big data at the customer level, online retail stores have access to many opportunities by making customer profiles based on their demographic, geographic, and psychological characteristics can achieve a competitive advantage. Big data has been able to point to the opportunity to share knowledge with other industries, the opportunity to use local strategies, the opportunity to maximize value for customers through innovative business models and expand channels by partnering with business partners, as well as business partners through analysis And data analysis by means of big data are used for product development by adapting to customer demands through the supply chain and sharing data with business partners in order to achieve business success.

Technological developments such as the Internet and smartphones have created structural changes in company strategies and changed business paradigms. In the era of big data and the increasing importance of information in this era, intelligence marketing is an important and unique way through which businesses can significantly expand their information channels. Intelligence marketing can improve the company's performance through competitive advantage in market information management, organizational learning, and intellectual capital. The ability of market intelligence has increased the competence of businesses to identify and exploit foreign opportunities, and as a result, it can prepare them to be present in the global arena. Many advantages of intelligence marketing for businesses have made it inevitable for them to enter this field. Before entering the field of intelligence marketing, which requires the use of new technologies, one should be aware of its challenges. Identifying these challenges can act as a predictive monitoring tool and reduce the risks of failure due to the use of intelligence marketing. Based on this, the current research seeks to answer the question from the point of view of food industry managers, what challenges do these industries face in applying intelligence marketing?

The current research is practical in terms of its purpose and it belongs to the category of qualitative methods with inductive approach. The statistical population of the research is all managers active in the food industry of the country, and research data was collected from 15 of them until reaching theoretical saturation. The sampling method was the targeted method and the data collection tool was semi-structured interviews. Data analysis was done with the thematic analysis method and using the analytical method of the thematic network, presented by Atride-Stirling (2001). Based on this method, first, the texts of the interviews were implemented and by reflecting on them, the basic themes (key codes of the text), then, the organizing themes (themes obtained from the basic themes), and finally, the overarching themes were extracted. became Then, these themes were drawn as a web network by Maxqda 2020 software, and the prominent themes of these three levels were shown along with the relationships between them.

The study identified seven general challenges related to the adoption of intelligence marketing in the food industry. In order of importance, these challenges include issues related to cost, time, and technology (time constraints, financial challenges, infrastructure issues, and selecting appropriate tools); the availability of skilled and efficient human resources (lack of specialized personnel in intelligence  marketing and marketing in general); macro and industry-level challenges (lack of experience in intelligence marketing, competition-related challenges, legal and regulatory challenges, and social media filtering); managerial challenges (managers' commitment to traditional systems, resistance to change, lack of knowledge and awareness among managers, limitations in using social media, and leadership challenges); cultural challenges for adopting new technologies (building trust among customers and fostering internal organizational trust); data collection and analysis (collecting accurate and sufficient data, analyzing marketing data); and the execution of strategic intelligence marketing (challenges related to products and services, appropriate customer segmentation, intelligence marketing strategies, establishing effective communication with customers, producing relevant content, smart advertising, and improving SEO).

The results of this research have practical suggestions for managers active in the food industry. Since the adoption and application of intelligence marketing is an undeniable necessity for active businesses in all industries, senior managers should be aware of the challenges of using new technologies before entering this field. Based on the results of this research, some of the challenges facing the food industry depend on macro measures and policies, but in the case of proper exposure to other challenges, it can be properly planned. Therefore, the practical suggestion of this research is to consider the controllable challenges of using intelligence marketing and to formulate appropriate strategies and tactics to face these challenges. Conducting this research has faced limitations. Here are some of the most important ones. Since the current research data was collected from managers active in the food industry researchers have limited access to these people and have faced difficulties in interviewing key people in this industry. Also, the lack of familiarity of some managers with the topic of intelligence marketing had caused problems in data collection. Since this research was conducted with a qualitative approach to identify the challenges of using intelligence marketing in the food industry, it is suggested that the identified challenges be further evaluated with quantitative methods. Also, conducting similar research in other industries is one of the suggestions of this research for future researchers.

In today's highly competitive environment, to guarantee their financial position and maintain their market share, institutions, and organizations should strengthen their ability to respond to the environmental changes of customers and, according to Sergio Ziman, provide more reasons to customers than that. encourage them to buy and create a long-term relationship with the company. Competitive advantage is one of the important issues that have been emphasized in the management literature in recent years and is one of the components that guarantee organizational sustainability. Also, companies need to design and adopt strategies that can help them improve their performance. In such a competitive environment, companies can survive by synchronizing themselves with the changing dynamic competitive conditions; In other words, company managers will see the results of their decisions in the form of strategy selection in the mirror of their performance criteria, and a company with distinctive capabilities and advantages has a higher probability of creating superior value. for the customer and achieving a competitive advantage.

 In this research, two documentary and field methods were used to identify these issues. The statistical population consists of managers and experts from eight city development and construction cooperative companies and the Ministry of Cooperation, Labor, and Social Welfare of Gilan province. The data analysis method is more complex. Meta-synthesis is a type of qualitative study that uses the findings of other qualitative research in the field of a subject as data.

We know that organizations are the systematic coordination and cooperation of several people, systems, and methods that work continuously through the division of tasks and the establishment of regular and logical relationships to achieve a common goal or purpose. Cooperation is the process of involvement of employees in the strategic and tactical decisions of the organization, which happens formally or informally at a certain level and limits. Every organization is created with an existential philosophy, and to realize this existential philosophy, it must turn it into a goal and plan. To clarify the goals of the organization, it needs to coordinate with the environment. According to Barnard, the task of management is to shape maintain, and apply the benefits of management to achieve the desired goals. By being together, some people establish a relationship and become purposeful, and finally create harmony and continue by creating a cooperation system.

The total findings show that the competitive advantages of city development and construction cooperative companies in Gilan province include the following subcategories: common goal, communication, and willingness to serve. The results of this research and similar research can help the managers of newly established companies to successfully start their work, and on the other hand, it can open the way for managers of long-standing cooperatives to respond. to new obligations and requirements and to be by the requirements of the time.

Digital marketing as a key tool in today's world, especially in the era of information and communication technology, is rapidly growing and developing. This type of marketing allows companies to communicate more effectively with their audiences, consequently increasing conversion rates. Additionally, digital marketing enables businesses to access new markets at a lower cost compared to traditional methods. Various tools such as SEO, content marketing and digital advertising help brands stand out in a competitive space. Furthermore, the use of analytics data in digital marketing assists companies in better understanding customer behavior and optimizing their strategies. Considering the ongoing trends globally, digital marketing is continually evolving and companies must stay updated to leverage these changes. For this reason, investing in digital marketing has become a strategic necessity for business success. Ultimately, the ability to measure and analyze results accurately is one of the distinguishing features of digital marketing allowing brands to make more informed decisions. Additionally, digital marketing serves as an innovative framework, playing a significant role in the transformation and development of businesses. In today's fast-changing technological landscape, brands must adhere to digital marketing strategies to maintain competitiveness and meet customer needs. In this regard, distinguishing digital marketing from traditional methods and creating innovative approaches enables businesses to get closer to their target audiences. Digital platforms, such as social networks allow brands to interact directly and instantly with their customers. These interactions help increase customer loyalty and brand awareness making customers feel more valued. Digital marketing enables businesses to quickly adapt to market trends and changes; for example, the emergence of new technologies such as artificial intelligence and machine learning can enhance customer experiences and personalize services.

The present research is applied in terms of purpose, quantitative in research method, and classified as descriptive-correlational based on the method of data collection. The statistical population of this study includes managers and academic experts with experience and expertise in the fields of digital banking, commercial banking, and digital marketing excellence. Data were collected through a 16-item questionnaire using a 5-point Likert scale, resulting in the receipt and analysis of 167 completed questionnaires. This research examined the relationships between variables using the Smart PLS 3 software and the structural equation modeling method.

One of the fundamental factors for success in digital marketing is paying attention to the needs and preferences of customers. Banks need to analyze data and customer behavior to communicate effectively with them and provide relevant content. Utilizing modern technologies such as artificial intelligence, machine learning and data analytics can help banks gain a better understanding of customer needs and optimize their marketing strategies. A key feature of digital marketing is the ability to engage in direct and immediate interactions with customers. Banks should take advantage of this opportunity and engage in conversation with customers through social media and interactive websites. One of the advantages of digital platforms is the ability to evaluate and analyze results accurately. Additionally, banks should continuously monitor the performance of their campaigns and adjust their strategies based on the data obtained and market changes. Ultimately, excellence in digital marketing requires a multifaceted approach that includes paying attention to customer needs leveraging modern technologies, creating valuable content and establishing effective interactions with customers. Banks must continuously strive to adapt to changes in the market and consumer behavior and capitalize on digital opportunities to create a positive experience for customers. These efforts not only help improve brand recognition but can also lead to increased sales and customer loyalty.

Excellence in digital marketing presents a golden opportunity for banks to achieve success in a competitive and ever-changing environment. By thoroughly understanding its various elements and implementing effective strategies businesses can enhance their competitive advantage. Furthermore, achieving excellence in digital marketing indicates that financial institutions must seriously focus on implementing innovative digital strategies. Given the increasing competition and high customer expectations utilizing digital tools can significantly improve customer experience and increase their loyalty. Offering suitable online services personalizing customer experiences and leveraging data analytics to better understand customer needs are among the key elements in this regard. Additionally, banks should focus on expanding their interactions with customers through social media and educational content. By establishing effective communication and building trust banks can strengthen their position in the market. Ultimately, success in digital marketing depends on adapting to rapid market changes and emerging technologies which can lead to reduced costs and increased customer satisfaction. Engaging customers through informative content and responsive communication channels not only enhances customer relationships but also fosters loyalty and improves overall service quality.

Social customer relationship management (SCRM) is a new concept that combines social media and social networks with standard customer relationship management (CRM) tools, processes, and practices to improve customer engagement, especially customer service. The goal of SCRM is to create a personal relationship with customers by tracking communications and interactions, following leads, analyzing customer views, and responding appropriately by reviewing the data received in the form of customer feedback. Many organizations have recognized the potential of SCRM capabilities in their businesses and have made significant investments in this area. However, the success rate of companies in integrating social media with CRM systems has varied greatly, and various studies report high failure rates of SCRM implementation. As social customer relationship management (SCRM) is considered an emerging phenomenon, most companies are still in the early stages of adoption. To exploit the true potential of SCRM, companies must be aware of the factors that drive its adoption. However, the existing literature on SCRM has largely focused on the characteristics, opportunities, and benefits that SCRM offers, but provides little insight into the factors that influence its adoption. Today, the service industry plays a vital role in the development and economic growth of countries. The insurance industry, as a supporting service industry, contributes to this development and plays a significant role in the economy. The Iran's insurance industry, despite its long history, has not had a very good position compared to other economic sectors of the country and compared to the world insurance markets, and has lagged behind in terms of growth. The low insurance penetration rate and low demand for insurance services in Iran confirm this. In a competitive and volatile sector like insurance, one of the profitable ways to outperform competitors and at the same time develop insurance penetration is to enable online interaction with customers through the use of social CRM. Social CRM provides opportunities for insurance companies that can increase their effectiveness. Given the benefits discussed, the purpose of this research is to identify the critical factors affecting the adoption of social CRM in the insurance industry and to prioritize these factors based on their importance and impact.

 This research is applied in terms of its purpose and descriptive-survey in terms of its method. In order to collect data and information, library and field methods were used. After identifying the criteria and sub-criteria based on a review of the research literature and a survey of managers and experts familiar with the research topic in the insurance industry, a field study and distribution of a pairwise comparison questionnaire were used to prioritize each of the criteria. The statistical population of this research includes experts familiar with the topic, including customer relationship management experts in insurance companies in Tehran, of whom 29 were selected using the snowball sampling method. The questionnaire included three main criteria and 18 sub-criteria, which the experts were asked to prioritize. The network analysis process technique in Super Decision software was used to weight and prioritize the research criteria and sub-criteria. The insurance experts confirmed the validity of the pairwise comparison questionnaire and it has the necessary validity and its reliability was calculated by calculating the inconsistency rate.

In this research, the factors affecting the adoption of social customer relationship management (SCRM) in the insurance industry were identified, with a review of past research, in three main criteria and 18 sub-criteria. Then, these factors were examined and prioritized by experts using a questionnaire. The results of the network analysis process technique showed that among the 3 main criteria (technology, organizational, and environmental), technology factors were identified as the most important main indicator in the adoption of SCRM in insurance companies. Organizational factors ranked second, and environmental factors ranked third. After the final prioritization, the highest rank in the sub-criteria was observed for the sub-criterion "the existence of reliable customer information in social media". This was followed by "senior management support" in second place and "the ability to integrate customer-related systems" in third place, which indicates the importance of paying attention to these sub-criteria in the insurance industry.

 In recent years, social customer relationship management (SCRM) has emerged as a powerful tool for businesses to engage with customers on social media platforms and build strong relationships with them. This trend has also had a significant impact on the insurance industry, prompting insurance companies to adopt SCRM strategies to better connect with their customers. SCRM enables insurance companies to effectively target and engage with a diverse range of customers. While technologies such as SCRM can offer better alternatives and solutions for communicating with customers, effectively integrating them into the existing insurance system can be challenging. Therefore, there is a need to identify the factors that influence insurance companies' intention to participate in SCRM programs, which can be the key to successful implementation of this technology. In general, based on the results of the research conducted, it can be stated that the adoption of SCRM is not only considered a technological project, but should also be considered as a comprehensive integrated business strategy in which organizational, environmental and technological factors must all be integrated and help the company to make an informed decision about the implementation of this strategy. By taking a comprehensive approach to SCRM, insurance companies can build stronger customer relationships, drive business growth, and gain a competitive advantage in today's digital age.