farzad asayesh

This study aims to develop an indigenous social media marketing model tailored to the banking services industry in Iran through a mixed methods approach. In the qualitative phase, grounded theory methodology was employed to analyze data collected from 16 semi-structured interviews with marketing experts, digital banking professionals, and academic specialists. The data were coded using Strauss and Corbin’s three-stage process—open, axial, and selective coding—using MAXQDA software. The findings revealed six main categories, fourteen subcategories, and seventy-four indicators influencing social media marketing strategies. Based on these, a theoretical model was proposed, identifying causal conditions (social media-related factors, managerial factors, structural factors), strategic categories (marketing and human resource actions), contextual conditions (relationship marketing and ICT), intervening conditions (customer trust, perceived risk, environmental threats), and outcomes (awareness, perceived quality, customer satisfaction and trust, environmental opportunities and threats). In the quantitative phase, a researcher-developed questionnaire was distributed to 384 customers of Bank Mellat who use social media. The instrument's validity was confirmed through content validity index (CVI) and content validity ratio (CVR), and reliability was assessed via Cronbach’s alpha, composite reliability, and Fornell-Larcker criteria. Structural equation modeling using partial least squares (PLS) indicated significant relationships among the proposed variables. The findings underscore the importance of strategic, contextual, and organizational factors in enhancing the effectiveness of social media marketing in the banking sector. The study offers a comprehensive framework for banking institutions to optimize their digital marketing strategies and improve customer engagement, satisfaction, and trust.

The aim of this research is to present a model for customer knowledge management in industrial companies affiliated with the Mostazafan Foundation.

This research is applied in purpose and descriptive-analytical in nature. The research method is qualitative. The statistical population consists of academic experts and managers of industrial companies affiliated with the Mostazafan Foundation, from which 12 individuals were selected using the snowball sampling method and theoretical saturation. The tool for collecting qualitative data is a semi-structured interview based on theoretical foundations. The analysis method for this section is grounded theory.

The results of this section of the study are presented in the form of four main categories and 19 subcategories. The identified factors include: assessment of the current state of knowledge in the organization, knowledge collection, documentation, and transfer, effective communication with customers and a complete understanding of their needs and interests, focusing on the process of knowledge creation around the customer, psychological examination of customers and customer behavior analysis, customer feedback strategy (via surveys, comments, feedback, and interviews), focusing on the company's knowledge products, reviewing the history of current customers (previous purchase behaviors), utilizing creative ideas about products and services, focusing on the education of knowledge transfer and management methods, strengthening technological infrastructures, collaboration with customers in creating shared value, comparing sales of new products with competitors' products, measuring the extent of achieving the set goals, increasing efficiency in customer service and customer orientation, digital self-service tailored to the customer (in customer support), intelligently transferring customer requests to the relevant expert, creating the maximum value from knowledge and knowledge management at a strategic level, and increasing quality and speed in decision-making and customer service.

The results of this research provide a comprehensive customer knowledge management model that can enhance communication, customer satisfaction, and the performance of industrial organizations affiliated with the Mostazafan Foundation.

Customer knowledge offers a dual-value proposition. On one hand, it helps companies better meet customer needs by identifying their requirements and desires, thereby creating value for customers. On the other hand, by identifying needs, behaviors, consumption patterns, and demands, it aids organizations in the development and improvement of products and services tailored to customer needs, thereby increasing profitability and customer loyalty. Therefore, the aim of this study is to present a model for customer knowledge management in industrial companies affiliated with the Mostazafan Foundation of the Islamic Revolution. This research is applied in purpose and descriptive-analytical in nature. The research method is qualitative. The statistical population consists of academic experts and managers of industrial companies affiliated with the Mostazafan Foundation, from which 12 individuals were selected using snowball sampling and theoretical saturation. The data collection tool for the qualitative section was semi-structured interviews based on theoretical foundations. The data analysis method used was grounded theory. The results of this section were explained in the form of 4 main categories and 19 sub-categories. The results indicated that the identified factors related to the dimensions, drivers, and outcomes of the customer knowledge management model in industrial companies affiliated with the Mostazafan Foundation in this study include: evaluating the current state of knowledge within the organization, collecting, documenting, and transferring customer knowledge, establishing effective communication with customers, and fully understanding their needs and interests, focusing on the process of creating knowledge about customers, conducting psychological assessments of customers, and analyzing customer behavior, feedback strategies from customers (through surveys, comments, feedback, and interviews with customers), focusing on the company’s knowledge-based products, reviewing the history of current customers (previous purchasing behaviors), applying creative ideas regarding products and services, emphasizing the training of knowledge transfer and management methods, strengthening technological infrastructure, collaborating with customers in creating shared value, comparing the sales of new products with competitor products, measuring the achievement of set goals, increasing efficiency in customer service and customer orientation, digital self-service tailored to the customer (in the field of customer support), intelligently transferring customer requests to relevant experts, creating the greatest value from knowledge and knowledge management at a strategic level, and improving the quality and speed of decision-making and customer service.

Digital banking generally offers lower costs compared to traditional banking systems and provides better value to society with greater speed. The present study aims to propose a value-creation model in digital banking. The research method is qualitative in nature. The statistical population in the qualitative section included 15 university professors, managers, and experts in digital banking, who were selected using a purposive sampling method. The data collection tool for the qualitative section was a semi-structured interview, and the reliability of the qualitative section was confirmed using Cohen’s Kappa coefficient. Data were analyzed using thematic analysis. The results of the thematic analysis revealed 292 codes and 64 themes, categorized into 18 basic themes and 4 organizing themes. The identified dimensions include customer digital experience management, which encompasses user-friendly design, ease of use, creating a unique experience, monitoring the digital customer experience, and utilizing technology in experience management. Digital co-creation includes direct digital feedback, indirect digital feedback, customer digital participation, and digital interaction with customers. Digital service management involves digital service customization, management of digital concerns, service delivery management, service quality improvement, diversity of digital services, customer support and training, and a value-creation digital mindset. Digital value management includes monetary value, non-monetary value, informational value, relational value, and hedonic value. Delivering digital banking services with a focus on improving accessibility, speed, and added value contributes to enhancing customer experience and strengthening digital relationships. Additionally, considering cost-value trade-offs, along with providing rewards and incentives, can further motivate customers to use digital banking services. Ultimately, creating an efficient and enjoyable customer experience plays a key role in the success of digital banking services.

In today's world, emerging technologies, especially artificial intelligence, have brought significant transformations to various industries, particularly in banking. Banks need to adopt artificial intelligence-based intelligent marketing models to maintain competitiveness and enhance customer experience. Therefore, the aim of this research is to design an artificial intelligence-based intelligent marketing model for the banking industry. The research method employed in this study is a descriptive survey, and from the perspective of its objective, the research is developmental and applied. Given the qualitative nature of the study, its credibility was evaluated and confirmed through suitability and applicability criteria. Sampling was carried out using the snowball sampling method. The research population consisted of university professors, managers, and experts in the banking industry, and the sample size was determined based on the principle of theoretical saturation. Ultimately, data for this study were collected through semi-structured interviews with 17 participants. Based on the results from qualitative analysis, 17 themes were extracted, including artificial intelligence and emerging technologies, customer needs and expectations, advancements in information and communication technology, competition in the banking industry, and changes in consumer behavior. Other identified themes were the formation of intelligent marketing, recognition of the competitive environment in the banking industry, regulatory and legislative systems, massive data volumes, organizational culture, information technology infrastructure, organizational support, investment in technology, and legal and ethical limitations. Additionally, themes such as intelligent marketing in the banking industry, implementation of artificial intelligence systems, market trend prediction, marketing automation, customer-centric service development, customer satisfaction improvement, financial performance improvement, customer experience enhancement, targeted marketing, and risk and security management were identified. Finally, to determine causal relationships and hierarchical levels among these themes, Interpretive Structural Modeling (ISM) was used, resulting in the classification of themes into 12 levels.

Marketing and sales outcomes are typically shaped based on long-term and interactive relationships between companies. These markets often involve complex and specialized products and services that require technical knowledge and a deep understanding of customer needs. The marketing and sales process in these markets comprises multiple stages, including identifying customer needs, presenting customized proposals, conducting complex negotiations, and establishing long-term contracts. In this environment, intercompany relationships are highly significant, and decision-making is primarily carried out by purchasing teams composed of managers and various experts. The objective of this study was to present a model of marketing and sales outcomes in industrial markets. This study is applied in terms of its objective and qualitative in terms of methodology, employing a grounded theory approach. Data and information were collected through a literature review and semi-structured interviews. Based on purposive sampling, 14 managers and experts from companies operating in the bitumen industry were selected in 2024. The conducted interviews were coded using ATLAS.TI software. The results identified the marketing and sales outcomes model, including increased market share, enhanced customer satisfaction, improved profitability, market differentiation, and optimized marketing performance. The marketing and sales outcome model in the bitumen market necessitates specific approaches that differ significantly from other industries. In this industry, emphasis is placed on establishing long-term customer relationships, extensive networking, and maintaining strong connections with key customers. Therefore, companies must actively engage in forming strategic relationships with major customers, such as construction contractors and road construction companies, to leverage the long-term benefits of these relationships.

This study aims to present a comprehensive conceptual framework for integrating artificial intelligence into personalized marketing within the tourism industry during the era of the Fourth Industrial Revolution. It examines the role of this technology in enhancing traveler experiences and improving marketing strategies. Using a qualitative research approach and semi-structured interviews with 11 experts in the fields of marketing, artificial intelligence, and technologies related to the Fourth Industrial Revolution, data were collected and analyzed through thematic analysis. Based on the analysis, a conceptual framework was developed from 219 concepts extracted from the data. The findings of the study indicate that artificial intelligence can play a pivotal role in data management, enabling the analysis of big data and identification of traveler behavior patterns, predicting preferences and needs through machine learning algorithms, and designing precise marketing strategies to deliver personalized travel services and experiences. These capabilities significantly enhance the effectiveness of marketing strategies in the tourism industry. The proposed conceptual framework not only contributes new insights to the scientific literature on marketing and artificial intelligence but also serves as a practical guide for tourism organizations and travel service providers to effectively leverage artificial intelligence in developing personalized marketing strategies and enhancing the traveler experience.

the aim of this research is to provide a value creation model in the insurance service industry with a focus on blockchain technology (strategies and consequences).The type of research is applied and developmental in terms of purpose, in terms of execution method, exploratory in terms of qualitative data type. In the qualitative section, the information sources of scientific articles in the period from 2015 to 2022 were extracted from the advanced search of Google and Science Direct, and in the semi-structured interview section, there were 14 experts of public and private insurances who were selected by the purposeful (judgmental) sampling method.The data were also analyzed using the foundation's data analysis method with a grand theory approach, through 3 stages of open, central and selective coding. A number of 128 concepts from open codes extracted from scientific texts and interviews were categorized in the form of 22 subcategories and 13 main categories, which were placed as a research conceptual model in the form of three main classes of blockchain-based value creation (central pillar), strategies and consequences.In the qualitative part, the method of collecting information, field and library (interview method and reading texts), data collection tools included interview guide or interview card and receipt. In the analysis of qualitative data, MaxQDA 18 software was used. In the qualitative part, the method of collecting information, field and library (interview method and reading texts), data collection tools included interview cards and vouchers.The results showed that the proposed model can help managers and planners of the insurance industry in determining strategies for the development of insurance services and improving the scientific and technological management of this field

The present study aims to propose a value creation model in digital banking. This study employs a mixed-methods approach (qualitative and quantitative). The qualitative phase's statistical population consisted of 15 university professors, managers, and experts in digital banking, who were selected using purposive sampling. In the quantitative phase, the statistical population included managers and experts of Refah Bank in Tehran. The sample size for the quantitative phase was determined as 235 individuals using Cochran's formula. Data collection in the qualitative phase was conducted through semi-structured interviews based on theoretical foundations, and the reliability of this phase was confirmed using Cohen's kappa coefficient. In the quantitative phase, a questionnaire and simple random sampling method were used to collect data. The reliability of the questionnaire was assessed using Cronbach’s alpha. The qualitative data were analyzed using thematic analysis, while in the quantitative phase, descriptive statistics, exploratory factor analysis, and confirmatory factor analysis were applied. The results of thematic analysis identified 292 codes, 64 themes categorized into 18 basic themes, and 4 organizing themes. The findings indicated that the factors influencing value creation in digital banking include customer digital experience management, which encompasses user-friendly design, ease of use, creation of a unique experience, monitoring customer digital experience, and applying technology in experience management. Digital co-creation consists of direct digital feedback, indirect digital feedback, customer digital participation, and digital interaction with customers. Digital service management includes digital service customization, management of digital concerns, service delivery management, service quality improvement, digital service diversity, customer support and training, and a digital value-creating mindset. Digital value management involves monetary value, non-monetary value, informational value, relational value, and hedonic value. The results of confirmatory factor analysis further validated the model derived from the literature review.

The current research was conducted with the aim of designing a sustainable marketing model in Alborz Insurance with a focus on artificial intelligence.

According to the type of data, the research method is qualitative and exploratory in nature. In the qualitative statistical population, 15 people were selected from among the experts until the theoretical saturation limit was reached, which included university and Alborz insurance experts who were selected by targeted non-probability sampling. A semi-structured interview tool with 5W1H technique was used to collect data, and the foundation data method was used for data analysis.

In the current research, 5 components including artificial intelligence capabilities, marketing innovation, organizational capabilities, cultural capabilities and sustainable marketing performance and 13 indicators and 40 codes have been identified. Causal conditions include the capabilities of artificial intelligence (competence of artificial intelligence, quality of artificial intelligence services, experience of using artificial intelligence). The intervening condition in the current research is marketing innovation (product innovation, process innovation). Similarly, strategies include organizational capabilities (entrepreneurial competencies, strategic competencies) and the background conditions in this research include cultural capabilities (innovative culture, changeable culture). Also, the results are sustainable marketing performance (sustainable purchase intention, achieving sustainable competitive advantage, sustainable marketing activity, sustainable smart marketing).

The use of artificial intelligence algorithms and marketing innovation will improve the recognition of customer patterns, offer the best insurance for each customer, and improve communication with customers. These types of tools can help Alborz Insurance Company to improve its marketing process and thus achieve more success and stability.

The current research was conducted with the aim of providing a sustainable marketing model in the insurance industry with a focus on artificial intelligence. According to the type of data, the research method is mixed (qualitative-quantitative) of exploratory nature. In the statistical population, 12 people were selected from among the experts until the theoretical saturation was reached. The experts included professors of the faculty of business management and senior managers of Alborz insurance company, who were selected by non-probability, targeted and chain sampling. Quantitative part of 400 managers were insurance industry experts, using Cochran's formula, 196 people were selected by stratified random method. To collect data, semi-structured interviews and researcher-made questionnaires were used. The analysis method has been carried out in several consecutive steps. In the first stage, to identify the components of the model, the qualitative method and semi-structured interviews using the grounded theory have been used. In the next section, using interpretative structural modeling, the identified indicators were leveled. Finally, in order to fit the designed model in the qualitative part, a quantitative method with structural equation modeling approach was used with PLS4 software. The findings showed that 6 components were identified and there is a significant relationship between all components and sustainable marketing and the designed model has an acceptable fit. It can be concluded that AI can be incorporated as an essential component of a sustainable marketing strategy, enabling marketing professionals and businesses to make positive changes while increasing their brand reputation and profitability.

The aim of this research was to identify and evaluate marketing and sales models in industrial markets, with a focus on the bitumen industry. The study was conducted using both exploratory and survey methods. In the qualitative section, the Delphi method was employed, while in the quantitative section, Interpretive Structural Modeling (ISM) and Structural Equation Modeling (SEM) were utilized. In the qualitative section, as well as in the Interpretive Structural Modeling method, the population consisted of managers and experts from companies active in the bitumen industry in the year 2024. A purposive sampling method was used, selecting 14 individuals. Relevant factors influencing the model were identified using library research techniques. Initially, the Delphi method was used to filter and evaluate the identified factors. Subsequently, using both the Delphi method and Interpretive Structural Modeling, the modeling process was carried out. The software tools used were EXCEL and MICMAC. The quantitative population comprised the employees and customers of the bitumen industry, with an unlimited number of individuals. Using Cochran's formula, a sample size of 384 individuals was selected. A total of 1000 questionnaires were distributed, with 669 valid responses selected for analysis. Based on the researcher-designed questionnaire and qualitative analysis, data analysis was carried out using coding and path analysis techniques. To fit the proposed model, Structural Equation Modeling (SEM) techniques were used in the SMARTPLS software. According to the Delphi technique, 17 categories were identified: optimal marketing performance, increased profitability, economic conditions, laws and regulations, political conditions, technology, product innovation, market conditions, product quality, pricing, financial strategies, brand management, production capabilities, increased customer satisfaction, market differentiation, increased market share, and improved product quality. As a result, the design of marketing and sales models in industrial markets, especially in the bitumen industry, requires a comprehensive and multifaceted approach. This model should carefully consider factors such as product quality, competitive pricing, production capabilities, and innovation at the highest level, as well as the impacts of political conditions and laws and regulations at the secondary level. On the other hand, optimizing marketing performance and increasing profitability as primary goals can only be achieved when companies utilize precise market analysis, product innovation, and the use of new technologies to improve the supply chain and enhance exports. Ultimately, this approach can help companies in the bitumen industry enhance customer satisfaction and achieve sustainable success in both domestic and international markets with high competitiveness.

This research was conducted with the aim of investigating the role of moral intelligence in the tendency to disclose (whistleblowing) in the public accountant community of Iran. The research method is a descriptive correlational type of research, and by using Morgan's Krejci table, 297 people from chartered accountants working in 1402 were selected as the sample size using a purposive sampling method and the moral intelligence questionnaire of Lenik and Keel (2005) and the questionnaire of tendency to Afshagari Alineqian et al. (2015) answered. Data analysis was done using Kolmogorov Smirnov test, Pearson correlation test and stepwise regression analysis and statistical software. The findings showed that there is a significant and positive relationship between the moral intelligence of auditors and the willingness to disclose, and moral intelligence can predict the willingness to disclose in certified accountants. In the above explanation, it can be said that according to logical approaches in moral decision-making, moral intelligence directly leads to moral judgment in people, and the core of this relationship is logical reasoning. This ability can act as a guide for the auditor's behavior and actions and provide his inner ability to recognize in critical decision-making situations.

The present study aims to design and provide a well-founded and reliable framework for content marketing in the banking industry of Iran, with the objective of enhancing the effectiveness of this approach and contributing to increased market share and profitability of banks. 

This mixed-method research was conducted in two phases: qualitative and quantitative. In the qualitative phase, grounded theory was used to design the model. A purposive sampling method was employed, selecting a group of academic experts and banking industry specialists, and in-depth interviews were conducted until theoretical saturation, which was reached after 15 interviews. The collected data were analyzed systematically and continuously in three stages: open coding, axial coding, and selective coding. In the quantitative phase, the designed model was validated using confirmatory factor analysis based on a covariance approach, and path analysis was used to finalize the model. 

During the open coding stage, 188 concepts were extracted, which were grouped into 41 categories through axial coding. Finally, 10 main categories were identified: understanding the business and planning, establishing a content management and strategy unit, defining content marketing goals, understanding the audience, identifying audience needs, generating content ideas and topics, managing content production, managing content dissemination, managing customer expectations and experiences, and gathering feedback for process improvement. The final model was developed based on these categories and validated in the quantitative phase. 

This study presented a comprehensive and clear model for content marketing in the banking industry, outlining specific stages and processes for implementation. The model has the potential to enhance the effectiveness of content marketing strategies and contribute to the improvement of market share and profitability for banks.

This study aims to develop a fitted model for marketing decision-making based on the risks faced by entrepreneurs in small and medium-sized enterprises (SMEs) while considering the controlling effect of various marketing strategies on risk reduction. It is a descriptive-applied research that employs a mixed-methods approach, integrating both quantitative and qualitative methods. A conceptual model, comprising various variable factors and their interrelations, was designed, and the prioritization of risks was conducted through structural analysis. Data were collected using a semi-structured questionnaire with a five-point Likert scale through expert interviews. Subsequently, structural equation modeling (SEM) was employed using PLS3 and SPSS software to analyze the relationships among the variables from a marketing perspective to inform risk-related decision-making. In the present study, 11 marketing strategies influencing decision-making were identified. Their impact on the risk indicators faced by entrepreneurs was assessed based on the theory of realization. According to the statistical analysis results, after eliminating certain reflective indicators, all the aforementioned strategies were deemed essential in the model's design. Their effects on credit, operational, market, and liquidity risks were analyzed. Out of the 48 tested hypotheses, 27 were confirmed, while 21 were rejected and subsequently removed from the conceptual research model.

The final goal of the research is to provide a model for co- branding according to the modern banking structure of our country so that it can cover the growing needs in the field of banking.

In this research, to achieve the co- branding model, the qualitative method of foundation data theory has been used, and the main basis for collecting information in this method is to conduct semi-structured interviews with knowledgeable people and experts in the sampling used in this article was theoretical sampling. After conducting interviews and collecting information, the codes obtained in different sections were analyzed and after three steps of open, central and selective coding, the final model was obtained by the researchers of this article

The final model consists of the sum of the central category, causal conditions, intervening conditions, strategies and finally, the consequences and results of co- branding. Each of these conditions and factors that make up the model have variables and categories that pay attention to them to achieve the final goal of co- branding. Originality: Tis article is taken from thesis of Phd.Masoumeh Ghaffari charati

 A large part of the sustainable marketing literature is devoted to the concept of “green”, which implies the environmental aspect of sustainable development, and it seems that the social aspect of sustainable development is less considered. Meanwhile, the company's social actions are very important, not only in terms of achieving sustainable development goals (this can be seen by referring to the 17 goals of the sustainable development program); they also have a positive impact on the image of the company and can attract customers' trust to social brands. However, in domestic literature, not much research has been done in relation to social branding. On the other hand, in many cases, the two concepts of social media branding and societal branding are confused with each other. The first refers to the use of social networks in branding activities, while the second basically refers to the social responsibility considerations of the company in branding operations, which is the subject of the present research. This research has been done with the aim of providing a branding model for Iran's dairy industry. 

The main purpose of this research is to model social branding in the direction of sustainable development, so the current research is in the scope of developmental research. Since in this research we arrive at a general pattern from the data obtained from interviews and questionnaires, therefore, the approach of this research is inductive. Qualitative data analysis was done with the methods of exploratory and interview-based data theory, and quantitative data analysis was based on the nature and method of descriptive survey research, which is a questionnaire for data collection. The statistical population of this research in the qualitative part included university professors and managers of dairy companies. The selection of the statistical sample was continued using the purposeful snowball sampling method until the level of theoretical saturation and data sufficiency. A total of 19 experts were selected as samples in the qualitative section. The population studied in the quantitative research are the managers, supervisors, and employees of the livestock company (N = 730). To calculate the sample size, Cochran's formula for limited communities was used, and the statistical sample size reached 252 samples, which we distributed 300 questionnaires among them for more certainty. The main tool of data collection in the qualitative part is a semi-structured, in-depth interview. In the quantitative part, to test these research hypotheses, a researcher-made questionnaire containing 47 items was used to collect information. The items of the questionnaire have been formulated exactly based on the indicators identified in the qualitative phase of the research. In order to evaluate the reliability of the questionnaire, Cronbach's alpha coefficient was calculated, and two methods of form-content validity (CVR-CVI) and construct validity (convergent validity and divergent validity) were used to check the validity. In order to determine the validity and reliability of the interviews, two methods of re-testing and double-coder agreement were used. Qualitative data was analyzed using the foundation data method. Data analysis has been done in the qualitative section using Maxqda software. Inferential statistics and the partial least squares technique (PLS) were used to analyze the data and test the research hypotheses. 

A questionnaire was provided to the statistical sample based on the results of the qualitative analysis of six categories of factors, including causal factors, mental paradigms of managers, optimization, organizational culture, and social responsibility. The results obtained by calculating Cronbach's alpha, combined reliability, shared reliability, and AVE showed that the questionnaire has good validity and reliability, and finally, the model has a good fit. 

In relation to the causal conditions of social marketing categories, the mental paradigms of managers, social responsibility, optimal mining, and organizational culture were identified. The statistics of the “social marketing” category as one of the causal conditions of social branding are quite expected, because one cannot expect success in social branding without social marketing activities. An important category that was identified under the causal factors is the mental paradigms of the managers. Social branding is not just a category of communication and directives, and it is realized when the company managers (especially the senior managers of the company) are really concerned about society mentally and intellectually. This result is consistent with the findings of Al-Hosseini et al. (2014), Amiboor et al. (2021), and Kaur et al. (2020). The microenvironment and competitive environment were identified as contextual categories. This finding shows that even if the managers of an organization do not have much desire for social affairs, it is the general trend of society that leads organizations towards public benefit and social responsibility actions. For example, changes in consumer income levels can affect their purchasing habits and preferences for certain brands. This result is consistent with the findings of Al-Hosseini et al. (2014), Amiboor et al. (2021), and Kaur et al. (2020). Regarding the intervening conditions, the categories of employee participation and sustainable competitive advantage were identified. Sustainable competitive advantage refers to the unique strengths and resources that a dairy company has that allow it to outperform its competitors in the long run. In the dairy industry, sustainable competitive advantage can be obtained from various factors such as product quality, production efficiency, distribution channels, brand reputation, etc. Dairy companies rely on employees to ensure that their products meet high quality standards. When employees work together and communicate effectively, they can quickly identify and address production issues and challenges, resulting in better-quality products. These findings are consistent with the results of previous researchers (Rojas et al., 2023; Zahedi et al., 2020). Based on the results obtained in relation to the central category of the research, the category of social branding management was identified. Social branding management refers to the process of creating and maintaining a “community-oriented” or “community-friendly” brand image for a company's products or services. The role of social branding management is vital to the branding model of dairy companies. Social branding management can help to create a unique and convincing brand “social identity” that connects with consumers. The results are in line with the findings of Shafiq et al. (2023) and Wu et al. (2024). Charitable marketing, cooperative branding, and target market selection were identified as strategic categories. Brand development through joint branding and the formation of economic clusters can also be a suitable solution for small domestic dairy companies. On the path of progress, many small and start-up businesses face challenges that larger businesses usually do not face. This can lead to higher conversion rates, increased customer loyalty, and higher profits. These findings are consistent with those of Christiansen (1922), Dumont and Oates (2020), Dhaka et al. (2022), and Iskanderpour et al. (2023).

This study has been conducted with the aim of providing a local model of increasing market share in Iranian dairy industries with a qualitative approach. The present research is considered to be a qualitative research method in terms of its purpose, applied research type, and in terms of data collection method. The statistical population includes 12 experts, including professors of Islamic Azad University in marketing fields, including marketing managers in dairy companies who are familiar with market share issues. The sample size was determined based on reaching theoretical saturation in the interviews. The main tool of data collection in the field section includes semi-structured interviews. Data base theory approach using MAXQDA software was used to analyze qualitative data and provide a paradigm model. Based on the results of the qualitative analysis of six categories of factors including causal conditions (internal marketing, product life cycle management, market attractiveness, marketing mix, competitive strategy and planning and targeting), background factors (characteristics of customers, competitive environment and market turbulence), central phenomenon (market share development strategy), strategies and measures (market share management, sales promotion, advertising, competition, special brand value and market segmentation), intervening factors (risk management and sustainable competitive advantage) and The consequences (establishment of brand position, profitability, bargaining power and increase in market share) were identified. As a result, the paradigmatic model of the native pattern of increasing the market share in Iran's dairy industries has been fully drawn with a qualitative approach according to six conditions (contextual, causal, intervening, central phenomenon, strategies and actions, and consequences).

The average size of the global online market for supermarket goods is about 9 times larger than Iran. Therefore, with the aim of finding effective factors and providing implementation solutions to the country's online supermarkets, this research has investigated the impact of decision-making structure & characteristics of supermarket goods on the change of consumer purchasing behavior from offline to online with the mediating roles of technology & e-commerce acceptance & consumer innovativeness. The objective of this research is practical, and the method used is descriptive-survey and to test the hypotheses, a researcher-made questionnaire was used. The statistical population consists of all online buyers of supermarket goods, 384 people were randomly selected for the sample by the simple random method using Morgan's table. Construct validity and questionnaire structure were confirmed by confirmatory factor analysis, reliability with Cronbach's alpha coefficient, and composite reliability in SmartPLS and SPSS software. In data analysis, the Kolmogorov-Smirnov test for normality of variables, the Friedman test for prioritizing variables and indicators, and the Structural Equation Modeling (SEM) were utilized to test research hypotheses. The findings indicated that the decision-making structure & characteristics of supermarket goods have a positive and significant impact on the mediating variables of technology & e-commerce acceptance & consumer innovativeness, and ultimately lead to a change in consumer buying behavior from offline to online. As a result, to expand the online market for supermarket products in Iran, major players in this industry such as Digikala, Snapp, and Okala, In addition to understanding consumer decision-making models, particularly when purchasing supermarket goods, they should consider the effective role of technology & e-commerce acceptance & consumer innovativeness in their marketing and advertising strategies to encourage customers to make online shopping.

Today, higher education is considered one of the most important bases for the development of societies. Today, higher education is considered one of the most important bases for the development of societies. Blockchain technology affects many areas, one of these areas is education and universities. Therefore, the current research seeks to identify and analyze the effective drivers of the future of higher education with a focus on blockchain technology.

The current research is applied in terms of orientation and is post- positivism in terms of philosophical foundations. Fuzzy-Delphi and Marcus methods were used in this research. The theoretical community of the research, the educational managers of the large public universities of Iran, and the judgmental sampling method and the samples were selected based on the expertise and experience of experts in the fields of higher education and blockchain technology and the sample size was equal to 10 people. Data collection tools are interviews and questionnaires.

At first, through background review and interviews with experts, 18 drivers were extracted, 14 of which were from the background and 4 through interviews. In the following, they were screened by distributing expert questionnaires and fuzzy Delphi method. 9 drivers were considered as final drivers. The final drivers were prioritized by the Marcus method.

3 drivers, the approach of universities towards new technologies, the coordination of the educational system with the systems and infrastructures of other universities, and the support of the senior managers of the universities were the highest priority respectively.

The objective of this study is to design a gamification model for digital marketing using the grounded theory method.

This qualitative study utilized the grounded theory approach. Data were collected through semi-structured interviews with 15 experts in the field of digital marketing and gamification. Participants were selected using purposive sampling, and the interview data were analyzed through open, axial, and selective coding stages.

The findings revealed that causal factors such as understanding customer behavior and fostering user interaction play a critical role in the success of gamification. Additionally, contextual factors like organizational culture and specialization, as well as intervening conditions such as environmental limitations and digital platform capabilities, affect the implementation of gamification. Key strategies identified included game design quality and customer experience management, which led to outcomes like marketing success and increased profitability.

The results suggest that gamification can be an effective tool for increasing user engagement, improving customer experience, and fostering brand loyalty in digital marketing. Proper design of gamification elements and effective management of customer experience are essential for success. Organizations should focus on understanding customer behavior, enhancing organizational culture, and promoting specialization to fully benefit from gamification.

The banking industry is one of the most important and influencing industries in today’s world and highly relies on identifying customer needs besides planning and providing solutions for proper response to their needs. Emphasis on exclusivity and strong competitive power within the banking network can significantly impact the performance and portfolios of banks. To prevent crises and future risks in banking networks, more attention should be paid to managing banks' exclusive power. Foreign currency services form a major part of banks' services and generate substantial income in both rials and foreign currencies. Therefore, the main purpose of this research is to provide a pattern for promoting the capability of competitiveness of customer foreign currency services in the banking industry.

This study is applied research in which a mixed research method has been used. Resources and articles were studied using documentary analysis. The Delphi test was applied to determine dimensions, elements, and indices. Structural equations analysis test, exploratory factor analysis, and Lisrel software were used to determine the current status and influencing elements. The statistical population in the quantitative phase comprised managers and employees engaged in banking marketing and foreign currency operations. The participants in the qualitative section consisted of experts specializing in the same field. The sample size consisted of 166 individuals, including experts and knowledgeable individuals, selected using a random sampling method.

Using the Delphi method, a pattern for promoting the capability of competitiveness of customer foreign currency services in the banking industry was extracted. The method was applied three times to reach an agreement between the experts. Moreover, the level and extreme effectiveness were confirmed using structural equations tests and exploratory factor analysis. Based on the obtained results, it can be concluded that the coefficient of all factors had a significant effect on the final model, confirming the effectiveness of each factor in promoting the competitiveness of customer foreign currency services within the banking industry.

Foreign currency services constitute one the most important parts of banking services. They result in high incomes for banks, therefore, banks need to undertake requisite measures to establish a competitive edge in attracting, retaining, and servicing customers, while also evaluating the prevailing conditions in the banking sector. For each foreign currency service, banks adopt various procedures simultaneously when handling requests for foreign currency services, including submission, documentation completion, and customer file creation. Banks can possess a greater share of the foreign currency market by adopting proper strategies and determining elements for the capability of competitiveness. This study shows that major elements such as “banking activity”, “credit portfolio”, “monetary and financial”, “market share” and “extra-organizational” shape patterns for promoting the capability of competitiveness of customers’ foreign currency services in the banking industry.

Today, maintaining effective employees is one of the most important factors in achieving the goals of any organization. As much as the judiciary can attract more qualified personnel and if he maintains and uses it more effectively, he will be more successful in achieving his goals. The purpose of the research was to evaluate the strategic factors affecting employee retention policies in government organizations. The research method is practical in terms of purpose and descriptive of correlation type according to the method of data collection. The statistical population of the research includes employees of the judiciary in Tehran in 2023. Using Cochran's formula, 384 people were selected as a sample and 425 questionnaires were distributed and 415 questionnaires were collected. The reliability of the questionnaire was measured by calculating Cronbach's alpha coefficient, which was 0.810. Data were analyzed using structural equation modeling and Smart-PLS software. The findings indicate that organizational commitment, job satisfaction, internal learning ability, and job commitment have a significant effect on the administrative innovation of the judicial branch organization. Finally, administrative innovation has an effect on the retention of employees of the judicial branch.

The purpose of this research is to identify the factors influencing the creation of brand identity in the banking industry of Iran. According to its purpose, the research method is applicable, and in terms of implementation, it is qualitative and based on the case study approach. The statistical population of this research includes Iranian banking industry experts who were senior managers of Bank Mellat in Tehran. The number of 23 experts who had sufficient knowledge and expertise in the field of brand was selected by judgmental sampling and snowball method, and data collection was done using semi-structured interview tool. The interviews were continued until theoretical saturation was reached, and the text of the interviews were analyzed and coded using the MAXQDA 2018 software. Data analysis led to the identification and extraction of research findings including 130 primary codes, 33 concepts, and 10 categories. Based on the results of this research, the categories of goals and strategies, structure and processes, human resource management, organizational culture, internal branding, communication, banking services, financial power, visual identity, and verbal identity are identified as the important factors affecting the creation of identity in the banking industry of Iran.

The current research aimed at designing a paradigmatic model for social media marketing in the Iranian banking services.

This study employs an exploratory qualitative research method. The population of this research consisted of a group of experts, including professors in the field of marketing management and a group of banking industry experts in the marketing sector, who were deeply interviewed. In this study, sampling was conducted purposively until theoretical saturation was reached in the interviews, which continued until theoretical saturation was achieved with 16 experts interviewed. In this research, the main tool for data collection in the field section was semi-structured interviews, and the grounded theory approach was utilized using MAXQDA software version 2020 for analyzing collected data and presenting the paradigmatic model.

Consequently, after conducting open, axial, and selective coding, 18 categories and 70 indicators were identified within six main sections including causal conditions (factors related to social media, management factors, structural factors, electronic word-of-mouth advertising), contextual conditions (relationship marketing, information and communication technology), intervening conditions (customer trust, perceived risk), the core phenomenon of social media marketing (the role of communications, the role of advertising), strategies (human resources actions, marketing actions), and outcomes (customer satisfaction, environmental opportunities, environmental threats, awareness, perceived quality, customer trust). As a result, the paradigmatic model of a native social media marketing pattern in the Iranian banking services industry has been fully delineated with a qualitative approach considering six conditions (causal, contextual, intervening, the core phenomenon of social media marketing, strategies, and outcomes).

Banks can segment their target market and plan and act more for awareness raising for each segment of society as appropriate. The research and development department of banks should study hidden needs or sometimes define new needs for audiences and customers and introduce them in an attractive manner.