https://www.jnabm.ir/ Journal of Intelligent Marketing Management en daily 1 Sat, 21 Mar 2026 00:00:00 +0330 Sat, 21 Mar 2026 00:00:00 +0330 https://www.jnabm.ir/article_729209.html This study aimed to identify the key core, influencing, and influenced factors among the drivers and barriers of online shopping, using a mixed-methods approach (qualitative and quantitative). In the qualitative phase, through an integrative review method, 72 selected articles out of 174 from the Scopus, Web of Science, and Google Scholar databases, covering the period from 2015 to February 2025, were analyzed, resulting in the extraction of 11 main categories of drivers and 5 main categories of barriers. In the quantitative phase, the DEMATEL method was employed. For this purpose, the opinions of 10 experts—purposively sampled and experienced in online shopping on multi-category platforms—were collected and analyzed to explain the causal relationships among the categories. A hierarchical model comprising three groups of factors—strategic and core, influencing, and influenced—was developed. The results indicated that "security, trust-building, and privacy protection" constitute the core and strategic factor with the greatest impact and significance within the network structure. Additionally, influential driver factors such as user experience quality, ease of purchase, customer satisfaction and loyalty, digital marketing strategies, and perceived risk management contribute to strengthening purchase motivation. Conversely, infrastructural limitations represent the most significant psychological and practical barriers in online shopping behavior. This study offers innovative recommendations for improving security, user experience, innovation, financial facilitation, and enhancing digital literacy, providing valuable guidance for managers and policymakers. https://www.jnabm.ir/article_734169.html The present study aims to optimize the bank financing process of small and medium-sized enterprises (SMEs) using data mining algorithms and artificial intelligence. In the present era, SMEs play a vital role in the dynamics of the economy, but access to efficient financial resources is their main challenge. Traditional bank financing methods do not meet the dynamic needs of SMEs due to time-consuming processes and inadequate risk assessments. This research is of an applied type with a mixed approach (qualitative-quantitative) and an integrated strategy and aims to provide a smart and efficient model to facilitate SMEs' access to financial resources and reduce banks' credit risk. In the qualitative part, the meta-synthesis method was used to extract key features affecting SME financing, and in the quantitative part, by analyzing real data of Tejarat Bank's credit granting to 1073 SMEs over a five-year period, modeling was done with machine learning algorithms (linear regression, decision tree, k-nearest neighbor, support vector machine, and artificial neural networks). The results of the qualitative part led to the identification of four main dimensions affecting SME financing, including: business characteristics, business strategy, financial and credit status, and external factors. In the quantitative part, different algorithms were evaluated using these features and their combined categories. The findings showed that the artificial neural network (ANN) algorithm, using all extracted features, has the highest accuracy (95.75%) and stability in predicting the success of SME financing. Also, the characteristics of the financial and credit status of the business were identified as the most important categories of characteristics in the financing decision-making process. Based on these findings, the final conceptual model of the research explains the relative importance of different categories of characteristics in the decision-making of Tejarat Bank for financing SMEs. This research conclusively proves the efficiency and effectiveness of machine learning algorithms, especially artificial neural networks, in optimizing the process of bank financing of SMEs and shows their potential in improving the credit assessment processes, reducing credit risks, facilitating SMEs' access to financial resources and increasing the efficiency and reducing the costs of banks. https://www.jnabm.ir/article_734163.html Purpose: With the expansion of digital technologies and the growing volume of marketing data, artificial intelligence (AI) has become a key tool in marketing decision-making. Despite the considerable growth of research in this field, existing studies have often examined AI applications in marketing in a fragmented and isolated manner, resulting in the absence of a comprehensive and systematic perspective. Accordingly, the purpose of this study is to identify, classify, and explain the applications of artificial intelligence in marketing using a meta-synthesis approach and to propose an integrated framework of the main categories and dimensions in this domain.Method: This study is applied in terms of purpose and qualitative in nature, and it was conducted using a meta-synthesis methodology. To this end, a systematic search of reputable academic sources was performed, through which 87 selected scholarly articles published within a specified time period were identified. Following screening and quality appraisal, the articles were analyzed. Data analysis was carried out using thematic analysis, which ultimately resulted in the extraction of 309 final codes, 81 subcategories, and 18 main categories related to applications of artificial intelligence in marketing.Findings: The findings indicate that applications of artificial intelligence in marketing are multidimensional, data-driven, and integrative in nature. The most important AI-based marketing categories identified include product development, brand management, pricing, logistics, supply chain management, marketing channels, advertising, marketing campaign management, public relations, social media marketing, sustainable marketing, sales and sales forecasting, customer experience enhancement, customer relationship management, marketing strategies (STP), marketing research, consumer behavior analysis, and content creation. The results further show that artificial intelligence plays a significant role in improving the accuracy of marketing decisions, personalizing marketing activities, and optimizing marketing processes.Conclusion: Based on the results of the meta-synthesis, artificial intelligence has moved beyond a supportive analytical tool and has become an active agent within the marketing system. By transforming decision-making logic, strategy design, and customer interactions, this technology directs marketing toward intelligent, predictive, and adaptive models. The findings of this study provide a theoretical foundation for the development of intelligent marketing literature and offer practical guidance for managers seeking to effectively implement artificial intelligence in marketing activities. https://www.jnabm.ir/article_709633.html The purpose of this research is to investigate the effect of forced and non-forced social influence, social norms and observation-based learning on impulsive buying behavior through the mediating variables of perceived lack and feeling of regret in Atka store in Hamadan city. This model has been tested by analyzing the survey responses collected from 274 employees and customers of Atka store with SPSS and Smart PLS. The results showed that the variables of perceived scarcity and feeling of regret have a positive and significant effect on impulsive buying behavior and the variables (non-forced social influence, social norms and observation-based learning) have a positive and significant effect on perceived scarcity. Also, perceived lack and feeling of regret have a mediating role on the relationship between variables (non-compulsory social influence, social norms and observation-based learning) and hasty buying behavior in Atka store in Hamedan city. Finally, the forced social influence variable did not have a positive and significant effect on the perceived lack, and the perceived lack and feeling of regret did not play a mediating role on the relationship between forced social influence and hasty buying behavior in Atka store in Hamadan city. https://www.jnabm.ir/article_733631.html The fashion industry faces the challenge of producing effective digital content in an information-saturated environment, a challenge that has rendered intuitive decision-making inefficient. This research aims to design a data-driven model for predicting content effectiveness on LinkedIn, employing an explanatory sequential mixed-methods approach. Initially, through the participation of ten digital marketing experts and the application of the Analytic Hierarchy Process (AHP), a weighted index of popularity was defined, incorporating comments (0/443), reshares (0/371), and likes (0/186) with varying importance. Subsequently, 11,950 public LinkedIn posts related to the fashion industry were analyzed, adhering to ethical considerations and data anonymization. The application of Natural Language Processing techniques revealed that despite the prevalence of positive content (54/3 percent), over 91 percent of posts fall into the “weak” popularity level, a finding that exposes the paradox of “positivity without effectiveness.” Lexical analysis highlighted the prominent importance of words related to reputable brands, career opportunities, and innovation in capturing audience attention. In the modeling phase, the Random Forest algorithm, with its capability for extracting interpretable rules, was identified as the optimal model. However, despite an apparent overall accuracy of 92 percent, deeper analysis indicated that the model struggles to predict successful content (minority classes), with a recall of only 4 percent for the “good” and “excellent” categories. Notwithstanding these limitations, the extracted rules offer a practical framework for combining brand credibility, tangible value, and a positive tone to produce effective content. By linking the qualitative knowledge of experts with the analytical power of machine learning, this study provides an operational framework for transitioning from intuitive decision-making to evidence-based decisions in fashion industry content marketing. https://www.jnabm.ir/article_710012.html The comparability of financial statements improves the information environment, increases the quality of financial reporting, reduces information asymmetry, and allows investors to more accurately assess the quality of companies through better comparison with similar companies. The research or objective of the effect of comparability on the cost of debt in companies with different ownership structures in the capital market of Iran was carried out. The research is considered to be of the accounting type in terms of applied purpose and descriptive data collection method. The investigated society is all the companies admitted to the Tehran Stock Exchange in the period from 2016 to 2016. The sample size is equal to the total number of active companies until the end of 1401, of which 264 companies were selected as samples. Descriptive and inferential statistics and SPSS software were used to analyze the research data. The results indicate that there is a negative relationship between comparability and cost of debt. Also, comparability has a greater effect on the cost of debt of non-government companies compared to government companies. https://www.jnabm.ir/article_732626.html In the era of deep globalization, companies benefit from numerous advantages but face intensified competition, environmental harm, and declining customer trust. Consequently, Corporate Social Responsibility (CSR) strategies are essential for meeting societal expectations and achieving sustainable development. CSR encompasses all value-chain activities and their societal, economic, and stakeholder impacts, serving as a critical factor in building credible brands, distinctive reputations, and lasting customer trust. Brand reputation is defined as stakeholders’ overall evaluation of a company based on past actions and future prospects (Su & Teo, 2025). CSR practices foster positive reputation and enhance brand image (Brahmi et al., 2025), representing foundational elements for reputation growth (Falk & Heblich, 2007). Despite the extensive CSR literature, significant gaps persist in specific sectors like tourism and hospitality, particularly in developing regions such as Fars Province, Iran.This applied study adopted a mixed method approach to develop a conceptual brand reputation model through a CSR lens in Fars Province’s tourism and hospitality industry. Using purposive sampling, 12 marketing and tourism experts were interviewed via semi-structured and unstructured methods. Content validity was confirmed by CVR and CVI coefficients, while reliability exceeded Cronbach’s alpha of 0.8. An innovative combination of library research and the Delphi technique identified core variables, enabling the discovery of meaningful patterns.Findings revealed a comprehensive model in which brand reputation is influenced by five key variables: brand identity, brand equity, social influence of the brand, brand visibility, and customer relationship. These dimensions collectively strengthen reputation through CSR integration.In conclusion, this developmental research successfully formulated a CSR-based brand reputation model for Fars Province’s tourism and hospitality sector. The model, grounded in identity, equity, influence, visibility, and relationships, offers a practical tool for brand differentiation in a growing market. Recommendations include embedding CSR into core operations, launching transparent sustainability initiatives, and utilizing digital platforms to boost visibility. The framework provides valuable guidance for future research and strategic marketing policies in reputation management. https://www.jnabm.ir/article_719374.html چکیده هدف: صادرات و نقش آن در اقتصاد هر کشور از اهیمت ویژه ای برخوردار است و این مسئله برای محصولات استراتژیک از جمله چای دارای اهمیت دوچندان است. صادرات چای در استان گیلان از قدیم به عنوان یک اقدام استراتژیک قلمداد می شد، از این رو هدف این پژوهش تبیین رفتار صادراتی شرکت های صادرکننده ی چای در استان گیلان با تاکید بر متغیرهای استراتژیک است. روش: این تحقیق با توجه به دسته بندی تحقیقات بر حسب هدف از نوع تحقیقات کاربردی، از نظر گردآوری داده ها تحقیقی توصیفی و از نوع پیمایشی است. جامعه آماری پژوهش شرکت های صادرکننده چای در استان گیلان است که تعداد آنها 57 شرکت است. به همین دلیل با توجه به تعداد پایین این شرکت ها از روش سرشماری استفاده گردید. پاسخ دهندگان به پرسشنامه نیز مدیران ارشد این شرکت ها بودند. ابزار گردآوری داده ها در این پژوهش پرسشنامه بوده و برای بررسی روایی آن از روایی محتوا و روایی سازه استفاده گردید. برای بررسی پایایی نیز از ضریب آلفای کرونباخ استفاده شد. برای تجزیه و تحلیل داده های حاصل از پرسشنامه از نرم افزارهای Spss و Smart PLS استفاده شده است. یافته ها : نتیجه حاصل از آزمون فرضیه ها نشان داد که کارافرینی مداری دارای بیشترین تاثیر بر رفتار صادراتی شرکت ها است و میزان آن 0.566 بدست آمده است. بعد از آن استراتژی مداری شرکت با ضریب 0.529 بر رفتار صادراتی شرکت ها تاثیر مثبت و معناداری دارد. کمترین میزان نیز مربوط به تاثیر جایگاه یابی رقابتی بر رفتار صادراتی شرکت ها بود که میزان آن برابر با 0.328 بدست آمده است. نتیجه گیری: با توجه به تایید تمامی فرضیه های پژوهش پیشنهاد می شود که شرکت های صادرکننده ی چای در حوزه ی کارآفرینی از خود واکنش بهتری نشان داده و همچنین در طراحی و تدوین استراتژی های صادراتی، چابک تر عمل نموده و استراتژی هایی متفاوت از رقبا را در نظر بگیرند. کلیدواژه ها: رفتار صادراتی، متغیرهای استراتژیک، کارآفرینی مداری، صادرات، چای، استان گیلان. https://www.jnabm.ir/article_734492.html Today the development of non-oil exports has become one of the main concerns of countries. This is so that improving export performance is also an important part of the demands of business in the private sector of each country and also in the international arena. The purpose of this research is to design a model for developing customs policies in the direction of non-oil exports growth and to develop the literature on the subject in a macro-level in the field of management and specifically in relation to the design and explanation of a model for developing customs policies in the direction of non-oil exports growth. In this article, first, using frequency tables and charts, the characteristics of the experts present in the qualitative part of the research and the experts present in the quantitative part of the research are analyzed. Then, the results of the qualitative analysis are presented and, using Delphi analysis and the agreement coefficient, the factors affecting the qualitative model of customs policies in the direction of non-oil exports are screened. In the third part of this article, based on the opinions of 40 customs experts and using the fuzzy AHP method, the identified customs policies are ranked in line with the direction of non-oil exports. Next, by analyzing the data obtained from the distribution of questionnaires among 363 customs experts and specialists and using the structural equation approach, a quantitative model of the development of customs policies in line with the direction of non-oil exports is presented and its validity and fit are evaluated. The results of this article showed that the structural model of customs policies in line with the direction of non-oil exports has a high level of validity and fit and is able to explain a significant part of the developments and challenges of non-oil exports in Iran. https://www.jnabm.ir/article_719908.html Attracting foreign investment is one of the economic priorities of sports federations, especially the volleyball federation. However the growing uncertainty in this field has pushed policy-making towards new approaches such as strategic foresight. The purpose of this research was to identify the future drivers of attracting funds for the volleyball federation. This research is descriptive-analytical in terms of practical targeting strategy and descriptive-analytical based on future research methods. The statistical population of this research was made up of sports marketing professors, federation officials and managers of sponsoring companies. The selection of these people was purposeful and their number was equal to 20 people. to order to identify the issues affecting the future of fundraising in the volleyball federation, a review of research literature and interviews with experts were used, and based on that, 25 final components were identified in connection with fundraising in the volleyball federation. The obtained results showed that 24 factors are effective components in attracting capital to the volleyball federation. According to the findings of the research, the four variables of television broadcast rights, contracts with business partners, approval of copyright law, and professional club ownership are among the key drivers of attracting capital in the volleyball federation because they have both importance and high uncertainty. They had registered for themselves. For this reason, it is necessary to use them in future planning and determination of possible future scenarios. https://www.jnabm.ir/article_734139.html The aim of this study is to identify the factors affecting digital spurs (antecedents) and to identify digital spurs affecting purchase decisions (consequences). In this study, a qualitative content analysis strategy was used. Data was extracted through semi-structured interviews with 14 academic specialists and experts using purposive and snowball sampling methods and analyzed with MaxQuda software (2020). Finally, components were extracted and coded according to the interviews, and then the final model was obtained. The findings showed that the antecedents, including the choice of the type of spur, are highly dependent on the background conditions, product features, in-depth knowledge of the target audience, the stage of the purchase path (sales funnel), information content, and the technical platform. The consequences, digital spurs, were classified into eighteen conceptual macro-categories. Among them, social, cognitive, interface design, informational, and motivational triggers were identified as the most effective types. This classification provides a practical framework for digital marketing managers to better understand the impact of each trigger type, allowing them to make smarter decisions in user experience design. https://www.jnabm.ir/article_723259.html Today, the need for customer trust in banking is inevitable. This research is considered in terms of purpose in the category of applied research and in terms of the nature of a descriptive-survey research. The statistical population of this study consists of customers of electronic banking of Kosar Financial and Credit Institution. Cronbach's alpha for the whole questionnaire is 0.992, which can be evaluated as the reliability of the questionnaire. In this research, a model is presented that examines the effect of online trust of e-banking customers of Kosar Financial Institution on the market share of this institution. In order to develop this model, after conducting library studies, several factors that lead to customers' trust in e-banking were identified and their relationships were considered. Based on this, a model was proposed in which the mentioned factors were divided into two categories of public and private characteristics of online trust and finally the impact of these factors and online trust on the market share of Kowsar Institute was investigated. By collecting and analyzing the opinions of e-banking customers of Kosar Institute by means of questionnaires and data analysis and examining the relationships between variables by SPSS and Amos software and structural equation model, finally the effect of some of those factors and online trust on the market share of the institution Confirmed. https://www.jnabm.ir/article_734158.html Recent advances in Artificial Intelligence (AI) have led to fundamental changes in design processes, project management, and marketing within the Architecture, Engineering, and Construction (AEC) industry. This study aims to propose a conceptual framework based on AI to explain the synergy between marketing and project management in sustainable design and construction startups, guiding decision-making toward data-driven, intelligent, and strategic approaches. A qualitative research method with a conceptual framework development approach was employed. Data were collected through a systematic review of the scientific literature. Selected cases from sustainable startups and industry reports were then analyzed and integrated using content analysis to develop a paradigm based on predictive data-driven marketing, intelligent project management, and sustainability principles. The findings indicate four key dimensions critical to AI implementation in sustainable design and construction startups: decision-making transparency, project optimization, data synergy, and sustainable innovation. These dimensions demonstrate that AI not only enhances project accuracy and efficiency but also, as a strategic approach, guides startups toward sustainable, flexible, and innovative processes, reinforcing the role of design and construction in intelligent project management. https://www.jnabm.ir/article_726913.html The aim of the present study is accounting professionalism in Iran with a smart marketing approach. In terms of methodology, this study is a qualitative research with a grounded theory approach. The statistical population includes experts in the field of theoretical and practical foundations of accounting; including accounting professors, certified public accountants and financial managers, who were selected for interviews using the snowball sampling method according to the purpose of the study. After obtaining the opinions of the experts through 22 semi-structured interviews during the year 2025, a conceptual model of accounting professionalism has been presented, including causal conditions, context and background (structure), intervenor, central phenomenon, strategies and their consequences. The results of the study showed that, according to the determined goal, since accounting is considered as a social science, the main function of this science can be accountability and responsiveness, and as a result, according to the strategies proposed in the conceptual model, the necessary education in society, including the academic environment and the social environment, should be provided to the general public in the best possible quality in line with public needs. Transparency through the accounting system can also be considered as the main strategy for achieving accountability. In the exploratory analysis, by distributing 370 questionnaires among community experts and receiving 342 correct questionnaires, it was determined that individual and personal needs, behavioral characteristics, professional ethics and personal ethics, changing social values, socio-financial needs, social opportunities, social and political beliefs, beliefs about governance, the competitiveness of the professional environment, social needs for financial knowledge, and rapid changes in market-based accounting rules are important criteria for moving towards professionalism. https://www.jnabm.ir/article_734150.html In this study, the aim of designing a business intelligence model in international marketing with the approach of explicit knowledge was carried out. A number of 11 experts were selected as the statistical population in two departments: university and industry for interviews using the snowball method until saturation. Given the nature of the research problem, this study uses a mixed method (qualitative and quantitative). For data analysis, content coding analysis techniques were used, and in the second stage, interpretive structural modeling was used. The final order of the business intelligence model in international marketing based on the meaningful relationships between dimensions is as follows: Level 1: Structural and functional achievements of international marketing; Level 2: Dynamic capabilities and agility of the organization; Level 3: Implicit knowledge processes (extraction-Specification-integration); Level 4: Data sources for decision-making and forecasting, challenges of access and data quality, support tools and systems, Level 5: Organizational and international institutional cultural context. Based on the results obtained from the structural-interpretive model, the research themes are placed in three main areas of the influence-dependence matrix. This classification helps to identify the role of each theme in the dynamics of the business intelligence system in international marketing. https://www.jnabm.ir/article_728854.html Implementing a customer relationship management (CRM) system in many organizations is recognized as a transformative solution, it is not always successful, and statistics indicate a high rate of failure of CRM projects or failure to fully achieve the initial goals in the implementation of these projects. Understanding the factors affecting the success of implementing customer relationship management (CRM) in organizations is a fundamental prerequisite for the effective implementation of smart marketing. Because smart marketing not only requires accurate and analyzable data about customers, but also depends on the behavioral, organizational, and technological infrastructure that CRM provides.Small and medium-sized businesses have always faced many challenges, especially in competition with larger companies, due to problems such as the lack of necessary scales in various aspects of capital, production and market, fluctuations in supply and demand, purchasing raw materials on a small scale, etc. Smart marketing can, by relying on successful CRM, equip small and medium-sized businesses with data-driven power for better decision-making and competition with larger brands. Therefore, the aim of this research is to identify CRM success criteria and the relationships between them in small and medium-sized companies.This research is applied in terms of purpose and mixed with a sequential exploratory design in terms of method. First, by systematically reviewing the research literature and using the meta-synthesis method, the criteria affecting CRM success were extracted from the existing literature. Then, in the quantitative part, the DEMATEL method was used to determine the importance of the criteria and the relationships between them.Among the 43 articles selected by meta-synthesis and their review, 12 effective criteria were identified. These criteria include: implementing global standards, providing human resources, determining strategy, training human resources, changing technology principles, updating financial systems, changing organizational culture, strong management, proper assignment of tasks, appropriate IT infrastructure, customer interaction, and holding customer relationship courses. The results of the DEMATEL technique showed that the strategy determination index has the highest priority among the indicators affecting CRM success in small and medium-sized companies. After that, the indicators of human resources training and customer interaction are ranked second and third. https://www.jnabm.ir/article_734317.html Given the frequency and importance of presence in social networks in such a way that these media have almost replaced traditional media, the importance of audience reaction can be considered. Today, every positive or negative event in virtual media is met with a reaction from individuals and users, and the magnitude and extent of this reaction has complicated the issues. Therefore, the present study is trying to present a model for predicting the reaction of virtual media audiences using artificial intelligence. Based on a qualitative approach based on in-depth interviews, the desired model was designed and then analyzed using the grounded theory approach. The presented model has 41 indicators based on open coding, 17 components based on axial coding, and 8 dimensions based on selective coding. Informational, emotional, and social factors are considered as causal conditions, individual and temporal factors as intervening factors, and political and economic factors as background factors that affect the outcomes, that is, communication factors. The validity and reliability of the model using the Holstey and Cohen's Kappa indices indicate a high and desirable level of model validity. In the following, artificial intelligence algorithms were used to test the presented model, and the results showed that the support vector machine algorithm is able to predict the audience's reaction in cyberspace with an accuracy of 92 percent. https://www.jnabm.ir/article_731355.html Heritage brands, as intangible and valuable business assets, not only provide competitive advantages but also embody the history, values, and cultural identity of nations. Relying on their legacy and extensive experience, these brands have successfully garnered customer trust and loyalty; however, like any commercial entity, they follow a distinct lifecycle and may face decline or extinction if they fail to adapt to market shifts and new generations. This study aims to investigate the lifecycle of heritage brands from birth to decline and analyze indigenous strategies for Iranian businesses through a systematic review methodology. Relevant scientific articles from 2000 to 2025 were screened and analyzed from reputable international databases using appropriate inclusion and exclusion criteria. Findings reveal that heritage brands persist across four key dimensions: preserving legacy and authenticity, customer experience and emotional engagement, socio-cultural values, and economic benefits. Nonetheless, to prevent decline, the adoption of smart strategies, particularly leveraging cutting-edge technologies such as digitalization, artificial intelligence, augmented/virtual reality, and the metaverse is deemed essential. In this context, the present research introduces the theme of smart monitoring and revitalization of heritage brands using advanced technologies, proposing a three-layered framework for their analysis and evaluation. This framework is designed based on key indicators, including lifecycle monitoring, smart forecasting, intergenerational transfer, brand narrative revitalization, technology-driven localization, and cultural-economic value addition. For each dimension, measurable operational indicators are defined, which can be tracked using tools like big data analytics, machine learning algorithms, and interactive technologies. Utilizing these indicators not only enables the identification of strengths and weaknesses in Iranian brands but also assists managers in adopting data- and technology-driven strategies for revitalization and global expansion. These strategies ensure fidelity to the past while guaranteeing the continuity and intergenerational transmission of the brand's heritage. https://www.jnabm.ir/article_734141.html This article was conducted with the aim of investigating the sales strategies of industrial goods of oil refinery on sales performance. The research method was applied in terms of purpose and in terms of the method of collecting information, it was a mixed research (qualitative-quantitative). The statistical population in the qualitative part included professors, experts in the field of marketing and sales, and senior managers of Shazand Oil Refinery, who were selected using purposive sampling to a number of 10 people. And in the quantitative part of the research, all employees and managers of the marketing and sales, finance, and commercial departments of Shazand Refinery were selected as subjects using the stratified random sampling method. The data collection tool was interviews in the qualitative part and a researcher-made questionnaire in the quantitative part. The validity of the questionnaire in terms of form and content was confirmed by several experts, convergent validity was confirmed by calculating the mean of the extracted variance, and divergent validity was confirmed by calculating the AVE root. The reliability of the questionnaire was obtained through Cronbach's alpha for the entire questionnaire as 0.968 Cronbach's alpha, Kolmogorov-Smirnov tests and confirmatory factor analysis were used to analyze the data. The results showed that the oil refinery's industrial goods sales strategies included customer valuation, sales management, sales process/stages, use of multiple sales channels, customer prioritization and targeting, development of a management plan, communication goals and sales models and customer segmentation, which had a positive and significant effect on the oil refinery's industrial goods sales performance. The model fit was also examined. https://www.jnabm.ir/article_731774.html Recent developments in the international housing market, particularly in Dubai’s luxury real estate sector, have led to an increasing presence of Iranian buyers and changes in their purchasing behavior patterns. Identifying these patterns can provide a foundation for intelligent decision-making in marketing and sales. Insight-driven smart marketing is a data-based approach that analyzes customers’ behaviors and preferences to generate actionable insights for effective marketing decisions. Accordingly, this study aims to design a framework for the buying behavior of Iranian customers of luxury residential apartments in Dubai, using a qualitative approach based on the Strauss and Corbin grounded theory. A judgmental sampling method was applied to ensure that the collected information was valid and relevant to the research topic. Data were gathered through semi-structured interviews with two groups: construction industry experts in Dubai with at least 15 years of professional experience and familiarity with the Iranian community, and university professors in marketing with at least 15 years of teaching and research experience in consumer behavior. A total of 14 interviews were conducted until theoretical saturation was achieved. After transcription, 345 initial codes and 95 concepts were identified, which were refined to 288 codes and 56 concepts after validation. Open, axial, and selective coding were then performed, resulting in 15 subcategories and six main dimensions categorized into conditions, interactions, and consequences. The findings revealed that factors such as investment returns, asset protection, luxury architecture, design quality, and long-term residency opportunities had the greatest influence on purchasing decisions. The results extend previous studies and provide new insights into the behavior of Iranian buyers in luxury housing markets. https://www.jnabm.ir/article_734144.html This study was conducted with the aim of presenting a model of consumer behavior change in social networks based on brand influence. The statistical population of the qualitative part of the research was formed by experts in the field of marketing and branding, who used a purposive sampling method with a snowball approach to select the sample. In the end, 9 people formed the statistical sample after reaching theoretical saturation. In this type of sampling, first, several people who have the desired characteristics are found and after interviewing them, they are asked to introduce other people for the interview, and the number of respondents is gradually increased in this order. The statistical population of the quantitative part of the research also includes customers of Digikala Company who have purchased at least twice and at least one year has passed since their first order. Due to their unlimited size, 200 people are selected purposefully and nonprobably. The sampling method in this study was purposeful, so that initially a certain number (about 1000 people) of real Digikala customers nationwide (by applying a filter that had purchased at least twice and at least one year had passed since the date of their first order) were selected. Since quantitative analysis in this study is based on confirmatory factor analysis with the structural equation modeling method, it is performed according to the rules for determining sample size in multivariate statistical analyses. In this study, due to the use of a mixed research method, both qualitative and quantitative research data collection tools are used, in other words, a semistructured interview tool is used for the qualitative part and a questionnaire tool is used for the quantitative part. MaxQDA software is used for qualitative analysis. After forming the overarching themes and organizing them, which somehow explains the main components of the research, in the next stage, quantitative questionnaire questions were prepared and, using the opinions of academic experts (professors and doctoral students in marketing management) and digital marketing experts, the content validity was calculated using the content validity ratio or CVR method and unnecessary questions were eliminated according to the Lavish formula. Finally, the questionnaire with questions confirmed in terms of content validity was distributed among the statistical sample of the quantitative section (digital goods customers) and, with the help of AMOS software and using the fit indices of confirmatory path analysis, the model scale validation was evaluated in terms of reliability and convergent and divergent validity. https://www.jnabm.ir/article_732283.html The present study was conducted with the main qualitative objective of developing a model for developing simultaneous multisensory advertising in the café-restaurant industry (components, antecedents, and consequences) and with the main quantitative objective of identifying the relationships between the components, antecedents, and consequences of the simultaneous multisensory advertising design model in the café-restaurant industry in Tehran. The research method was a mixed-type exploratory design, and in the qualitative section, the statistical population included academic experts, marketing managers, brand consultants, and key informants with at least 5 years of research experience in the field of sensory marketing. The sampling method in this section was purposeful and data collection continued until theoretical saturation was reached, with a total of 14 in-depth interviews conducted based on the interview protocol. In the quantitative stage, the statistical population included active customers in selected café-restaurants in Tehran. Considering the total number of the statistical population (unlimited) and based on the Morgan table, 384 people were randomly selected (two-stage cluster). In the qualitative part, the data collection tool was a semi-structured in-depth interview, and in the quantitative part, a researcher-made questionnaire was used. Three-stage coding (open, axial, and selective) was used to analyze the data in the qualitative stage, and descriptive and inferential statistical methods were used in the quantitative part. The results of the qualitative stage led to the development of a paradigmatic model of simultaneous multisensory advertising in the café-restaurant industry, in which the background factors included the consumer's perceptual background, product information transparency, environmental hygiene sense, and ordering system personalization, and the causal conditions included olfactory perception management, enhanced tactile experience, dynamic visual design, personalized flavor engineering, and adaptive audio design, the pivotal phenomenon included simultaneous multisensory advertising, action and interaction strategies included the holistic management of intelligent multisensory stimuli, and the consequences included creating synergy in sensory perception, consumer comfort and pleasure, and effective interaction and sensory connection with the consumer. This research presents a new model for simultaneous multisensory advertising, and its findings can help marketing policymakers, experiential brand managers, and café-restaurant industry activists to design more effective multisensory advertising, enhance experience, https://www.jnabm.ir/article_734149.html Rapid digital transformations and changes in customer behavior have imposed new requirements on marketing in the insurance industry. Digital marketing, as a strategic and data-driven approach, plays a critical role in improving organizational performance and creating competitive advantage for insurance companies; however, there is a noticeable lack of a comprehensive and localized developmental model tailored to the specific conditions of Iran’s insurance industry.The purpose of this study is to develop a digital marketing development model for insurance companies in Iran. The research is applied in terms of purpose and adopts a mixed-methods (qualitative–quantitative) approach. In the qualitative phase, data were collected through interviews with experts in the insurance industry and digital marketing and analyzed using three-stage coding, leading to the extraction of an initial conceptual framework. In the quantitative phase, the proposed model was tested using a questionnaire and structural equation modeling.The findings indicate that factors such as digital marketing strategy, content marketing, target audience identification, organizational factors, managerial attitudes, digital security, and information technology infrastructure have a significant impact on the development of digital marketing. The final model provides a practical framework to support managerial decision-making in the effective implementation of digital marketing within insurance companies. https://www.jnabm.ir/article_734048.html The primary objective of this study is to present a model for the effectiveness of spiritual and religious tourism marketing in influencing tourists' visit intentions in the digital age, employing a meta-synthesis approach. This research is developmental in nature, qualitative concerning data type, and utilizes a documentary-meta-synthesis methodology for data collection. The Critical Appraisal Skills Programme (CASP) can be employed for evaluating the articles. Based on 60 selected articles from reputable scientific databases, covering domestic sources from 2011 to 2025 and international sources from 2000 to 2026, information extraction was conducted from the results and analyses of these articles. After individually assessing each article, 24 were ultimately approved and screened. Subsequently, a new conceptual model was designed by reviewing the backgrounds and models of the approved articles. For the category of religious tourism, three indicators were extracted: sustainable development (economic development, community development, local development); infrastructure (destination image, destination appeal, perceived quality, perceived value); and motivation indicators (cultural, social, religious, personal). Additionally, for the category of spiritual tourism, two indicators were identified: spirituality in tourism (achieving meaning, attaining transcendence, achieving mutual understanding) and tourism marketing (political marketing strategy, religious marketing strategy, commercial marketing strategy). The extracted indicators within the framework of the proposed conceptual model can influence tourists' visit intentions. It is recommended that future research further examines the proposed model. https://www.jnabm.ir/article_734165.html Today, health is widely considered as a basic need for the development of societies. Therefore, it is essential to determine valid criteria for measuring the effectiveness of programs by system analysts. The present study was conducted with the aim of designing and validating the public policy model in the health sector (case study: Chaharmahal and Bakhtiari University of Medical Sciences). The qualitative part of this study was conducted using a data-based approach and interviews with experts and specialists of the University of Medical Sciences, and the design of the research theme pattern was based on the content analysis method. The statistical population of the study in the quantitative part is all administrative and human resources experts and senior managers of Chaharmahal and Bakhtiari University of Medical Sciences. The research data collection tool is a researcher-made questionnaire. Also, the structural equations approach with PLS software was used to validate the research model. The results of the quantitative part of the study showed a relatively strong fit of the structural model (0.060) and a strong predictive power of the research model. The proposed model is presented below and was observed to have good validity using the structural equation approach. https://www.jnabm.ir/article_735206.html In today’s competitive markets, the increasing complexity of products and services has led to significant levels of perceived ambiguity in consumer decision-making processes. In this context, visual communication tools—particularly illustration styles—play a crucial role in simplifying information, enhancing comprehension, and reducing cognitive uncertainty. This study aims to analyze the role of different illustration styles in reducing perceived ambiguity in the purchase of complex products. The research examines illustration styles as key mechanisms for effectively conveying product features and functionalities, and investigates their impact on various dimensions of perceived ambiguity, including cognitive confusion, uncertainty, and difficulty in evaluating alternatives. A quantitative research design was employed, with data collected through structured questionnaires distributed among consumers of complex products. The data were analyzed using appropriate statistical techniques. The findings indicate that illustration styles significantly contribute to reducing perceived ambiguity. Simplified and structured illustration styles enhance clarity and reduce cognitive load, whereas realistic styles improve functional understanding and increase trust in the product. Furthermore, alignment between the type of illustration and the level of product complexity plays a critical role in improving consumers’ perceptual experience. Overall, the study underscores the strategic importance of employing appropriate illustration styles in marketing communications and provides practical implications for smart marketing managers aiming to reduce perceived ambiguity and facilitate more effective consumer decision-making. https://www.jnabm.ir/article_734167.html Servantship refers to the management of services and resources to optimize performance and enhance service quality within organizations. It plays a key role in increasing client satisfaction, reducing costs, and improving productivity. The present study aims to design a servantship model in Iranian governmental organizations from a behavioral perspective. This research is applied in terms of objective and descriptive-developmental in terms of methodology. Qualitative data were extracted through meta-synthesis of documents and validated using the Delphi and fuzzy DEMATEL methods with the participation of experts employed in four selected ministries; in this phase, 15 usable questionnaires were returned. In the quantitative phase, the model was tested using structural equation modeling on a sample of 480 employees from the four ministries. The convergent and discriminant validity and the reliability of the measurement instruments were confirmed using Cronbach’s alpha and composite reliability. Analyses indicated that external factors, including servantship culture, leadership behavior, motivational environment, and legal accountability; internal factors, including commitment, altruism, social responsibility, and organizational citizenship behavior; and Iranian–Islamic factors, including service based on divine duty, service-oriented behavior, and self-constructive behavior, significantly influence servantship behavior. The findings present a behavioral model of servantship in Iranian governmental organizations using Delphi, fuzzy DEMATEL, and structural equation modeling, providing practical insights for improving service delivery and developing organizational servantship. https://www.jnabm.ir/article_734346.html This study is designed to examine the impact of innovative resources comprising internal innovative resources and collaborative innovation networks on the tendency to use artificial intelligence (AI) within organizations. The present research proposes an integrated theoretical framework grounded in the synthesis of the Resource-Based View (RBV) and Strategic Choice Theory. Within this framework, innovative resources are positioned as the primary and central drivers, while organizational factors including organizational digital culture and the “Not-Invented-Here” syndrome and environmental factors particularly environmental instability serve as moderating variables. The research adopts a descriptive-correlational design with a quantitative approach. Data were collected from 390 employees and managers of insurance branches in East Azerbaijan Province, Iran, in the year 1404 (2025). The data collection instrument consists of standardized questionnaires based on validated measurement scales drawn from the existing literature. Data analysis was performed using Structural Equation Modeling (SEM) in SmartPLS 4 software, and model reliability and validity indices were confirmed as satisfactory. Findings indicate that both types of innovative resources internal and network-based exert a positive and significant influence on the tendency to adopt AI. Environmental instability negatively moderates these relationships, whereas organizational digital culture positively strengthens them. Furthermore, the NIH syndrome demonstrates a dual effect: on one hand, it enhances the relationship between internal innovative resources and AI tendency by reinforcing organizational self-reliance; on the other hand, it weakens the link between collaborative innovation networks and AI tendency due to resistance against external ideas. The novelty of this research lies in the development and empirical validation of a conceptual model that prioritizes innovative resources as the foundational basis of AI orientation, while simultaneously examining within a unified framework the moderating roles of environmental, cultural, and cognitive factors in a data-sensitive industry: insurance. These findings not only enrich the theoretical literature on digital strategy, innovation, and technology adoption but also provide practical, evidence-based guidance for the effective design and implementation of AI strategies in service-oriented organizations. https://www.jnabm.ir/article_734273.html This study focused on leveling and analyzing the factors affecting the knowledge-based organization model for Homa Airlines using the interpretive structural equation method. The research approach was based on a combination of qualitative and quantitative methods, in which in the first stage, data-driven theory played the main role in identifying and discovering key concepts of knowledge management. In-depth interviews with fifteen industry experts, senior managers, and experts at various organizational levels with at least ten years of work experience in the aviation industry collected rich and comprehensive data. The open, axial, and selective coding process extracted the main and secondary categories affecting the organization's transformation towards knowledge-based, and the inductive approach of data-driven theory enabled the creation of a local theory that was adapted to the specific conditions of Homa Company. In the second stage, interpretive structural equations were used as a tool for analyzing hierarchical relationships and determining the levels of influence of the identified factors. The structural self-interaction matrix was formed based on the opinions of experts and the variables were leveled by converting the relationship symbols into an accessibility matrix. The results showed that the seven-level pyramidal structure explained the causal and influential relationships between factors in a logical way. At the first level, knowledge-based economy, knowledge-based organization, knowledge-based development, and information factors were placed as the fundamental foundations that formed the overall infrastructure of the transformation. The second level included knowledge-based strategy, competitive requirements, human factors, empowerment, knowledge-based organization, and organizational sustainability, which provided overall direction to the transformation process. The third to sixth levels included strategic plan, management factors, human resources, executive and structural factors, environmental factors, cultural and motivational factors, infrastructure factors, agility, strategic orientation, and organizational profitability, respectively, which were directly dependent on lower levels. The Mi'kmaq analysis divided the variables into four categories based on the degree of dependence and influence. Strategic orientation and profitability of the organization were identified with very low dependence and high influence in the driving variables area. Knowledge-based economy, knowledge-based organization, knowledge-based development and information factors were identified with the highest degree of dependence and low to medium influence in the dependent variables category. Knowledge-based strategy, competitive requirements, human factors, empowerment and knowledge-based organization were identified in the linked variables category and played the role of a connecting link between drivers and results. The validity and reliability of the research were ensured through member review, data triangulation, expert panel evaluation and stability test of pairwise comparison matrices. https://www.jnabm.ir/article_734402.html The main objective of this study is to examine the role of business cycles in moderating the impact of marketing on firms’ financial performance. Specifically, the present research aims to determine whether the effect of marketing expenditures on return on assets (ROA) varies across different phases of the business cycle, namely recession and expansion, or is influenced by macroeconomic conditions. This study utilizes quarterly data from 96 manufacturing firms listed on the Tehran Stock Exchange over the period 2018–2024. The dependent variable is ROA, considered as an indicator of firms’ financial performance, while the main independent variable is marketing expenditure. Business cycles are categorized into recession and expansion periods, and to investigate their moderating role, an interaction term between marketing expenditure and business cycle phases is included. In addition, control variables such as financial leverage, inflation rate, and exchange rate are incorporated into the model. Panel data analysis with a fixed-effects estimator is employed, allowing for the control of unobserved heterogeneity across firms. The results indicate that marketing expenditures have a negative impact on ROA in both recession and expansion periods. However, this effect is not statistically significant at the 95% confidence level during expansion, whereas it is significant and negative during recession. The interaction effect of marketing expenditures and business cycles is found to be negative and significant during recession, but positive and significant during expansion. Furthermore, financial leverage and inflation exert a significant negative effect on ROA, whereas the exchange rate has a significant positive impact on firms’ financial performance. Based on these findings, it can be concluded that the impact of marketing on firms’ financial performance is not static or independent of economic conditions; rather, it is significantly influenced by business cycle phases. Specifically, during economic recessions, increased marketing expenditures may impose additional pressure on ROA, whereas in expansion periods, these expenditures can play a reinforcing role in enhancing financial performance through their interaction with favorable economic conditions. https://www.jnabm.ir/article_709959.html In the banking system, customers are the main focus and in fact all the work is to seek their satisfaction, attention and attraction. Customer goals must be realized in customer relationship management strategy. Customer relationship management and knowledge management are key and strategic tools for all companies, especially in the current competitive environment. Due to the importance of the topic in this research, the role of knowledge management system on customer-oriented management was examined. The statistical population of the research is the employees of Sepah Bank in Shahrekord, 160 of whom were used as a statistical sample according to the Karjesi-Morgan table. The research collection tool was the standard questionnaire of knowledge establishment and customer-centered management. The validity of the instrument was based on form and content validity, and Cronbach's alpha was used for reliability. The results showed that knowledge management and customer-oriented management have a significant relationship. Also, the components of establishing knowledge management system showed a significant positive relationship with customer-oriented management. This means that customer-oriented management will increase with the increase in the establishment of knowledge management system. https://www.jnabm.ir/article_734490.html The aim of this research is to model the “smart innovation of Islamic brand identity” and explain its consequences on the performance of the Iranian youth clothing market, because despite the theoretical emphasis on Islamic identity in the branding literature, the operational, data-based, and smart mechanisms of this identity and its role in improving market performance—especially in the dynamic, digital, and sensitive adolescent market—have not been systematically explained. The present research was conducted with a qualitative approach and using data-based theory. Data were collected through 15 in-depth semi-structured interviews with key experts in the youth clothing industry, including brand managers and founders, designers, marketing and branding specialists, innovation managers, and cultural identity consultants, and the sampling process continued until theoretical saturation was achieved. Data analysis was conducted using open, axial, and selective coding. The findings led to the extraction of an integrated paradigmatic model in which “data-based smart Islamic brand identity” was identified as the central phenomenon. Causal conditions include dynamic and generation-oriented redefinition of Islamic identity, value flexibility, and utilization of learning and data analysis infrastructures; contextual conditions are influenced by socio-cultural developments of adolescents, digital space, and intense competition in the apparel market; and intervening conditions include digital trust, behavioral transparency, identity coherence, and perceived brand credibility. The extracted core strategies include intelligent personalization of the shopping experience, two-way and data-driven interaction with the adolescent market, intelligent design of the Islamic identity message and narrative, and predictive analysis of consumer behavior. The consequences of these strategies were explained in the form of significant improvement in market performance, increased sustainable loyalty, promotion of competitive resilience, and agility of brand decision-making. The main innovation of the research is to present a native, contextual, and data-driven model that places Islamic identity at the heart of brand innovation, not as a symbol or slogan, but as an intelligent, learning, and decision-making process, and shows that truly intelligentizing Islamic identity can lead to sustainable competitive advantage in the Iranian youth clothing market. https://www.jnabm.ir/article_734152.html The aim of this research is to present a cultural management model of the Sacred Defense with a cultural marketing approach. The statistical population of the research in the qualitative section was initially a study of documents, then interviews were conducted with the commanders of the imposed war. The sampling is snowball or chain. To conduct a semi-structured interview, 12 commanders of the imposed war who were experts and had sufficient education and experience related to the subject were used. Thematic analysis method was used to analyze the data in the qualitative section. In the qualitative stage, 180 conceptual codes were identified and extracted, and by merging and combining the concepts extracted from document analysis and expert interviews, 105 concepts were extracted and coded using thematic analysis method at three levels of basic, organizing, and comprehensive themes. Then, to validate the factors identified from two rounds, the fuzzy Delphi approach was used in the form of a questionnaire from the perspective of 10 university experts. Data analysis resulted in the identification of 99 basic themes, 35 organizing themes, and 9 comprehensive themes, and the final model of the Holy Defense management culture model was drawn. Next, the identified factors were ranked using the Friedman test. Finally, the identified dimensions are, in order of priority: 1- Modeling of the heroes of the Holy Defense (4.499); 2- Symbols and values of management culture (4.410); 3- Deep understanding of the nature of culture (3.921); 4- Intelligence and scientific awareness (3/646); 5- Foresightful measures and policy-making (2/99); 6- Risk-taking, innovation and transformation (2/760); 7- Ethics and sincerity (2/841); 8- Rule of law (2/666); 9- Resilience and adaptability (2/448). https://www.jnabm.ir/article_734500.html In the era of smart marketing and big data, the ability of banks to accurately identify customers and optimally allocate financial resources is a key factor for increasing organizational confidence and productivity. This research focuses on designing an intelligent big data-based banking facility allocation model that aims to go beyond simply reducing risk and move towards maximizing the value of eligible customers. Using existing financial and credit records, K-Means clustering was first used to separate customers into three distinct risk-taking groups (low, medium, high risk). Then, a Random Forest model with a prediction accuracy of 96% was used to accurately assess the risk profile of each cluster. The main innovation of the research lies in the allocation stage, where a hybrid optimization method including Analytic Hierarchy Process (AHP) and Particle Swarm Algorithm (PSO) was used to optimize the loan allocation parameters. The results show that this hybrid approach not only significantly reduces credit risk, but also improves the overall efficiency of the bank by intelligently directing resources towards profitable sectors. This model provides a powerful tool for making accurate credit decisions, based on customer value, and in line with the strategic marketing goals of banks. https://www.jnabm.ir/article_731684.html In today’s dynamic and competitive environment, organizations are compelled to adopt modern marketing approaches to enhance their competitive capabilities. The purpose of this study is to examine the effect of marketing orientation on competitive advantage, with the mediating roles of market innovation and global strategy and the moderating role of market turbulence in the tile and ceramic industry of Yazd Province. This applied research utilized a descriptive–survey approach. The statistical population comprised all managers and experts of tile and ceramic manufacturing units in Yazd Province, from whom 368 valid questionnaires were collected using a convenience sampling method. Data were analyzed using structural equation modeling (PLS SEM) through SmartPLS software. the results indicated that marketing orientation has a positive and significant impact on competitive advantage (β=0.261, t=8.171). Moreover, marketing orientation improves competitive advantage through both market innovation (β=0.151, t=7.644) and global strategy (β=0.213, t=10.940). The moderating effect of market turbulence on the relationships between market innovation–competitive advantage (t=3.064) and global strategy–competitive advantage (t=2.849) was also confirmed, suggesting that environmental dynamism strengthens these effects. Model fit indices (SRMR=0.04, NFI=0.94) indicated a good fit between the conceptual model and the empirical data. Ultimately, marketing orientation positively and significantly influences competitiveness, while market innovation and global strategy play crucial mediating roles in this relationship. Additionally, market turbulence acts as a moderating factor that intensifies these relationships. This research, by confirming the pivotal role of marketing orientation in enhancing competitive performance, contributes to the theoretical enrichment of dynamic capability literature and provides practical strategies for achieving sustainable development in the national and international tile and ceramic industry. https://www.jnabm.ir/article_735083.html This study aims to model virtual customer development within the corporate banking sector. It is an applied, descriptive research project conducted using an exploratory approach based on the interpretivist paradigm. The study population includes theoretical experts (marketing management professors) and practical experts (senior managers and marketing directors of Bank Maskan), all possessing sufficient experience in corporate banking and digital marketing. Purposive sampling was employed, and theoretical saturation was achieved after 12 interviews. Data were collected using semi-structured interviews and questionnaires. Qualitative analysis of the expert interviews was conducted using thematic analysis in MAXQDA software. Finally, the relationships between constructs were identified using Interpretive Structural Modeling (ISM) in MICMAC software, resulting in the design of a virtual customer development model for corporate banking. The findings reveal that the constructs are organized into a six-level hierarchical structure, elucidating the path for virtual customer development in corporate banking. At Level 6, two foundational constructs—development of digital banking infrastructure and human resource training and development—play a foundational role in shaping the other levels. At Level 5, digital marketing strategy acts as a key mediating variable, guiding the effective utilization of infrastructure and human resource capabilities. At Level 4, marketing strategies exert their influence through two critical constructs: first, the bank's corporate social responsibility, and second, customer relationship management. At Level 3, the synergy and combination of these two factors pave the way for strengthening corporate banking. At Level 2, results indicate that corporate banking plays an effective mediating role in improving risk management and information/data security. Finally, at Level 1, virtual customer development is positioned as the ultimate outcome and the primary objective of the model. https://www.jnabm.ir/article_734322.html This study aims to present a phygital customer experience framework for chain stores in Iran. Given the ongoing shifts in consumer behavior and customers’ continuous movement between physical and digital channels, Iranian chain retailers are increasingly required to design an integrated customer experience aligned with the country’s local retail context in order to sustain competitiveness. The present research adopted a qualitative approach and, in terms of purpose, is classified as developmental–applied. Data were collected through 12 semi-structured interviews with experienced chain store managers and academic experts and the interview process continued until theoretical saturation was reached. The collected data were analyzed using Braun and Clarke’s thematic analysis procedure. The findings demonstrate that phygital customer experience in Iranian chain stores constitutes a multidimensional phenomenon that can be conceptualized through five domains, namely antecedents, the phygital customer journey, dimensions of phygital customer experience, barriers to phygital customer experience, and outcomes. The results further indicate that implementing an effective phygital experience in chain retailing requires not only the adoption of emerging technologies but also organizational alignment, consistency in service provision and systematic management of the challenges inherent in Iran’s chain retail industry. Furthermore, the appropriate implementation of the proposed framework can lead to substantial benefits for retailers, including enhancing customers’ perceived value, fostering positive word of mouth, strengthening brand equity, reducing operational costs and ultimately improving profitability in Iranian chain stores. Overall, the proposed framework offers a coherent and practical foundation for understanding and advancing phygital customer experience in the Iranian chain stores industry. https://www.jnabm.ir/article_735084.html In the housing construction sector , " balanced financing " leads to simultaneous and intelligent use of a number of financial sources ( i.e. , constructive , pre - selling , loan repayment , participation with investors and … ) in such a way that the construction supply chain and its investments in all sectors are of the appropriate financial security and the financial risk of it is controlled and liquidity pressure on the manufacturer or buyer is not exceeded .so financing is the growth engine of the macroeconomics .. In this regard, this research aimed to design a housing construction supply chain financing model with a balancing approach in listed construction investment companies. The method of this research is mixed (qualitative-quantitative). In the qualitative part of the research, 86 reputable scientific and research articles were first examined using a meta-synthesis approach, and finally 32 articles were selected to extract the components of housing construction supply chain financing with a balancing approach. After detailed analysis, 19 components were identified and extracted for housing construction supply chain financing with a balancing approach. In the quantitative part, first using the opinions of 18 experts on the identity of cause and effect using the DEMATEL method, and then modeling was carried out with the help of interpretive structural modeling (ISM), and a four-level model was obtained, which shows that the use of validation models for the actual progress of housing construction projects in the entire chain is the most influential component. https://www.jnabm.ir/article_734544.html The purpose of this research is to empirically analyze the efficient market hypothesis in the Iranian capital market: An analysis of behavioral idiosyncrasies. This research is applied and conducted with a quantitative method. The information in this research is based on collecting secondary data from the Tehran Stock Exchange, including panel data from 112 companies over the 10-year period of 2014-2015. The sampling method of this research is non-random and based on the criteria of the company's financial stability, the existence of complete price and return data, and representation of different market segments. To analyze the data, first the variables under study were described in the study period, then the obtained data were analyzed using modeling with a multilayer perceptron neural network (MLP) and optimization with the water cycle algorithm (WCA). According to the results, the average closing price (65,351 Tomans) and daily return (0.0495%, equivalent to an annual growth of about 12.8%) indicate a stable market growth, while the high standard deviation of prices (47,728) and the range of returns (-4.15% to 4.85%) confirm the diversity and volatility of the market. The trading volume with an average of 2.54 million and technical indicators such as RSI (average 52.74) and Volatility (0.9831) indicate high investor activity and the impact of their behavior on stock value changes. Calendar variables such as January_Effect (8.3% occurrence) provide the basis for examining behavioral anomalies. The presence of fluctuations and potential patterns in RSI (third quartile 64.68) and Momentum (range -9.78% to 11.14%) indicate that the market may not be completely random (EMH) and support adaptive patterns (AMH). Fundamental variables such as P/E (average 12.4) and Book_to_Market (1.002) indicate the diversity of companies, which is crucial for classifying return behavior (question 2) and suggesting investment strategies.