نشریه مدیریت پویا و تحلیل کسب و کار
سال چهارم شماره 6 (پیاپی 11، بهار 1404)

the present study aims to design a model for service customization in the banking industry. 

This research is applied in nature and employs qualitative methods based on grounded theory for data collection. Data were gathered through the study of documented sources and semi-structured interviews with 19 managers and banking professionals using snowball sampling and analyzed via MAXQDA18 software. In the open coding phase, 108 preliminary codes were identified from the interview analyses. In the second phase, axial coding was performed based on the constructs of axial coding models around the central phenomenon under investigation. 

According to the study's findings, the concept of service customization was identified as the central phenomenon. Causal conditions were categorized into five groups: appropriate services, optimal management, organizational structure, reliability, and trust. Five primary categories were selected as strategies, including infrastructural strategies, educational strategies, intra-organizational strategies, commercial strategies, and effective performance management. Intervening factors were identified in two categories: enhancers and inhibitors. Cultural factors, organizational capabilities, customer service evaluation, leadership style, customer-centric insights, and customer-value creation based on modern technology were determined as contextual and foundational factors for service customization. Finally, the outcomes of service customization were classified into three levels: micro, meso, and macro. 

The study concludes that service customization, through effective strategies and leveraging cultural and technological factors, enhances customer loyalty and satisfaction in the banking industry.

This study aims to identify and prioritize financial literacy indicators for children aged 10 to 12 within the framework of Islamic economic education, using the Best-Worst Method (BWM) and the combined DEMATEL-ISM approach. 

The research methodology is applied and descriptive in nature, utilizing library-based studies. The statistical population includes experts and practitioners in the field of financial literacy education, as well as university professors in accounting and finance disciplines. 

The findings indicate that among the key financial literacy indicators—spending and saving management, credit and debt management, employability and income, investment, risk management and insurance, and financial decision-making—spending and saving management, along with employability and income, hold the highest priorities. Based on the analyses conducted, employability and income have the greatest impact on other indicators and are influenced only by financial decision-making. Other financial literacy indicators, such as spending and saving management, credit and debt, investment, and risk management, are influenced and are considered dependent variables. 

The results of this study can assist policymakers and educators in designing and implementing appropriate educational programs to strengthen financial literacy in children.

The objective of this study is to propose a hybrid model based on Partial Least Squares (PLS) and Support Vector Machine (SVM) to predict corporate financial distress and enhance the accuracy and stability of the prediction process. 

This study utilized a dataset of 120 companies, consisting of 56 bankrupt and 64 non-bankrupt firms, over a two-year period. Initially, financial data were analyzed, and key features were extracted using the Partial Least Squares (PLS) method. The Support Vector Machine (SVM) algorithm was then employed, utilizing a grid search technique with 5-fold cross-validation to optimize model parameters. The performance of the proposed model was compared with traditional methods such as logistic regression and artificial neural networks. 

Empirical results indicated that the hybrid PLS-SVM model achieved an accuracy rate of 87% on the test set, outperforming traditional models and other machine learning techniques. Additionally, the model successfully identified the most relevant financial indicators for predicting financial distress and determined the role of each variable in the prediction process. 

Due to its high accuracy, interpretability, and significant stability, the proposed model can serve as an effective tool for financial institutions in risk management, credit approval, and financial planning processes. This study demonstrates that combining machine learning methods can improve financial prediction capabilities.

The purpose of this study is to investigate the impact of omnichannel integration on the application of flow theory and customer support, with the moderating role of value congruence. 

This research is applied in terms of purpose and survey-based in terms of implementation. The statistical population consists of customers of Khorasan Science and Technology Park in Mashhad during the first quarter of 2024. Based on Morgan's table, 202 participants were selected using a random sampling method. The data collection tool was a standard questionnaire on omnichannel integration, value congruence, flow theory, and customer support, adapted from Liu et al. (2023). Given the promising prospects of omnichannel marketing, it is crucial for omnichannel retailers to implement effective omnichannel strategies to support customers, reflecting customers' willingness to maintain close and lasting relationships with omnichannel retailers. 

Data analysis was conducted using structural equation modeling with Smart PLS 3 software. The results indicated that the dimensions of omnichannel integration, including customer information integration, customer transaction integration, and customer communication integration, have a significant impact on the flow experience of customers of Khorasan Science and Technology Park (with significance levels of 7.999, 3.702, and 7.024, respectively). Value congruence moderates these effects (with significance levels of 2.556, 2.066, and 3.746, respectively). Moreover, the impact of flow experience on customer support in Khorasan Science and Technology Park was found to be significant (significance level of 34.489). 

Customers enjoy and immerse themselves in the purchasing process when they receive integrated transactional services across channels. Integrating customer relationships across channels can effectively encourage customers to deeply engage in the purchasing process. Additionally, informational integration can provide relevant information aligned with customer preferences, thereby fostering customer interest. Ultimately, customers respond more positively to retailers whose value propositions align with their personal values. Customers who experience a high level of flow when interacting with an omnichannel retailer are more likely to support the retailer in the future.

This study aims to investigate the role of cloud accounting in enhancing the quality of financial reporting. 

The required data for conducting and implementing the research were collected from 18 experts with master's and doctoral degrees in accounting and a minimum of five years of experience with cloud accounting. In this study, an interpretive structural modeling (ISM) approach was employed to design a model for the role of cloud accounting in enhancing financial reporting quality. 

The results of the interpretive structural modeling using the exploratory model indicated that cloud accounting hardware factors, including process automation, advanced upgrade capabilities, cloud and virtual network servers, management and support tools, and workstations, along with cloud accounting software factors, such as flexibility and continuous improvement, scalability, information security, ease of use of cloud accounting, performance and analysis speed, data recovery capability, and remote automated reporting, contribute to the enhancement of financial reporting quality. This enhancement is reflected in dimensions such as improved transparency, increased accuracy in automated reporting, reduced errors, improved calculations, and data protection. 

The findings of this study indicate that the adoption of cloud accounting can play a significant role in enhancing financial reporting quality. Given the hardware and software advantages of cloud accounting, organizations can achieve greater transparency, higher accuracy, and reduced errors in financial reporting. These findings can serve as an effective guide for financial managers and accountants in making strategic decisions to improve financial reporting systems.

This study investigates the impact of competitive assurance elements on agile management in small and medium enterprises (SMEs).  

The research is descriptive-survey in nature, involving a sample of 41 managers and employees from Fidar Steel Company. Data were collected using the standardized agile management questionnaire by Zhang and Sharifi (2000). The data analysis was conducted using path analysis with SmartPLS software, version 4. 

The results indicate that all examined variables, including digital transformation, system alignment, agile methods, Scrum, and customer focus, have a positive and significant effect on agile management. Customer focus showed the strongest impact, with a path coefficient of 0.708 and a t-statistic of 8.997. Additionally, digital transformation and system alignment significantly contributed to enhancing organizational agility. These findings highlight the importance of leveraging modern technologies and agile practices to improve organizational performance.  

The study demonstrates that various factors, such as digital transformation, system alignment, and customer focus, can enhance agile management in SMEs. Implementing these elements can help organizations increase their flexibility and responsiveness to market changes. It is recommended that SMEs invest more in developing digital technologies and agile practices.

The present study aims to provide a model based on the factors influencing financial market indices under Iran's environmental conditions. 

This research, due to its practical recommendations, is an applied study and presents a novel exploratory model. Data collection for this study was conducted using semi-structured interviews. The research sample consisted of 15 experts from the Tehran Stock Exchange, each with over 10 years of experience working as economic and market analysts. In this study, an Interpretive Structural Modeling (ISM) approach was used to design a model. 

Through ISM analysis using the exploratory model, 18 factors were identified. These include macroeconomic indices such as economic growth, inflation rate, unemployment rate, and exchange rate, alongside electoral indices such as presidential election results, parliamentary election results, changes in economic policies, social policy changes, cultural policy changes, instability, and unpredictability. Additionally, political uncertainty indices, including a decline in trading volume, regional conflicts in the Middle East, domestic reactions and dissatisfaction, reduced investor confidence, and price fluctuations, can impact financial market indices, including secondary indices, risk indices, and price indices. 

The findings of this study indicate that Iran's financial market indices are influenced by various economic, political, and social factors, and accurately identifying these factors can contribute to the development of more effective predictive models.

The objective of this study is to present a model for the financial oversight of the country's public sector budget with an internal oversight approach within the executive branch.  

This research is qualitative in nature and was conducted using the fuzzy Delphi method. The statistical population consists of 131 experts and specialists in the field of financial oversight of the public sector budget, who were selected as research experts using the non-probabilistic chain sampling method. 

Based on the results, 8 dimensions, 27 components, and 86 indicators for the financial oversight of the country's public sector budget with an internal oversight approach were identified. Through the fuzzy Delphi process and confirmatory factor analysis using the Smart PLS software, 2 components and 6 indicators were ultimately removed, resulting in a final set of 82 indicators. The research findings indicate that all 8 identified dimensions—financial oversight pillars, training and human resources, organizational culture and ethical values, oversight strategies and tactics, forecasting of oversight laws and regulations, oversight infrastructures, financial oversight tools, and the design of financial oversight and control procedures and methods—have positive and significant relationships with the performance of financial oversight of the public sector budget with an internal oversight approach. 

This model can assist supervisory bodies that are effective in overseeing the public sector budget and serve as a pathway for efficient and effective financial oversight for executive bodies in the country's public sector.

The primary objective of this study is to identify and analyze effective digital marketing tools and methods for attracting tourists and enhancing awareness of the importance of sustainable tourism.

This study employs a quantitative approach to data collection, which includes the distribution of online questionnaires to tourists and local stakeholders. The statistical population comprises experts, tourists, and local stakeholders, from whom 50 individuals were selected using purposive and convenience sampling methods. Additionally, relevant documents and reports on sustainable tourism and digital marketing strategies were reviewed as complementary information sources. The SOAR and ARAS techniques were utilized for data analysis. In the SOAR approach, strengths, opportunities, aspirations, and expected results are identified, whereas ARAS assists in data analysis and the planning of practical measures to improve strategies. This combined approach facilitates the effective examination and analysis of digital marketing strategies in managing sustainable tourism destinations, yielding valuable insights for decision-makers and stakeholders.

The findings indicate that creating engaging and informative content on social media platforms, particularly Instagram and Telegram, can significantly impact tourist attraction and awareness of sustainable destinations. Additionally, targeted advertising and collaboration with local influencers were identified as effective strategies for enhancing Noor’s brand image and promoting sustainable tourism. Furthermore, interactive websites and online tools for booking and travel planning contribute to improving the tourist experience.

The use of digital marketing strategies can play a crucial role in managing sustainable tourism destinations. Noor coastal city, by leveraging these tools and methods, can continue to develop its sustainable tourism sector and be recognized as a model tourism destination in Iran. It is recommended that educational programs on digital marketing be conducted for local tourism stakeholders to enable them to make the best use of these opportunities.

Dynamics and complexity are important and prominent features of today's organizations and examining the factors affecting on divisiveness in them is of great importance. As a result, the present study was conducted an interpretive structural modeling of the divisiveness antecedents in government organizations. 

This study in terms of purpose was applied and in terms of implementation method was cross-sectional. The population of the present research was managers with high experience in government organizations and experts familiar with the research field, which according to the principle of theoretical saturation number of 12 people of them were selected as samples with using purposive and snowball sampling methods. The instrument of the present study was semi-structured interview with managers and experts and the completion of a questionnaire based on them by managers and experts, which whose psychometric indicators were reviewed and confirmed. The data were analyzed with using content analysis and interpretive structural modeling methods in PLS software. 

The findings of the present research showed that divisiveness antecedents in government organizations had 15 main concepts in 4 categories of centralized structure (with four concepts of profit-seeking personality, extreme complexity, power concentration and heterogeneous policies and strategies), secretive personality (with three concepts of deceptive personality, laxity towards beliefs and values and flattering personality), duplicitous managers and leaders (with four concepts of sessional managers, passive managers, unreasonable self-confidence and autocratic managers) and politicized culture (with four concepts of perceived injustice, non-responsive managers, evasion of responsibility and nepotism). Also, the concepts of profit-seeking personality, deceitful personality, flattering personality, unreasonable self-confidence, autocratic managers, perceived injustice, evasion of responsibility and nepotism were at the first level, the concepts of extreme complexity, sessional managers, passive managers and non-responsive managers were at the second level and the concepts of power concentration, heterogeneous policies and strategies and laxity towards beliefs and values ​​were at the third level. Finally, an interpretive structural model of the divisiveness antecedents in government organizations was drawn. 

According to the results of the present research, organizational experts and planners can exploit the results of this study and use the identified concepts and categories to reduce divisiveness.

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.

The aim of this study is to examine the impact of personalization and trust on customer empowerment and the subsequent success of e-government in knowledge-based companies in Tehran Province.

This descriptive-analytical study used a structured questionnaire distributed among senior, middle, and operational managers in knowledge-based companies. A total of 350 questionnaires were completed. Face and content validity were assessed using expert judgment (CVR and CVI), and reliability was confirmed via Cronbach's alpha. Data were analyzed using SPSS-25 and AMOS-24 through covariance-based structural equation modeling (CB-SEM).

Results indicated that personalization significantly and positively affects both trust and customer empowerment. Trust also has a significant positive impact on empowerment. Empowerment, in turn, directly and significantly contributes to e-government success. Indirect effects of personalization and trust on success, mediated by empowerment, were also confirmed. The conceptual model showed good fit based on multiple goodness-of-fit indices.

Customer empowerment driven by personalized services and strengthened trust plays a crucial role in the success of e-government initiatives. By fostering customer-centered strategies and trust-building environments, organizations can enhance innovation, satisfaction, and operational effectiveness in public service delivery.

The objective of this study is to validation of the model of improving symbolic capital in managers.

This research employs a quantitative approach using survey instruments and statistical analyses to collect data and test the hypotheses. Data were gathered from managers and leaders of various organizations across different industries, and statistical techniques such as Structural Equation Modeling (SEM) were used to assess the relationships between variables and test the research hypotheses.

The results revealed that symbolic capital acts as a significant source of power and legitimacy within organizations, influencing strategic decisions and resource acquisition. Furthermore, the conversion of cultural, social, and economic capitals into symbolic capital plays a crucial role in creating competitive positions and expanding the influence of managers and organizations. These findings align with previous studies, which emphasize that symbolic capital can serve as a tool for gaining legitimacy and power in various markets.

Symbolic capital plays a fundamental role in individual and collective success within organizations, and managers should actively leverage this form of capital to strengthen their public image and legitimacy. This study highlights the importance of converting social and cultural capitals into symbolic capital for strategic decision-making and marketing.

This study aims to design and explain the digital entrepreneurship ecosystem model using the grounded theory method.

In this qualitative study, data collection in this study was conducted through in-depth and semi-structured interviews with key informants, senior managers of online businesses, and academic experts with significant knowledge in the field of entrepreneurial ecosystems. These interviews were conducted iteratively until theoretical saturation was achieved. The analysis in this research was based on Strauss and Corbin's systematic design, including open coding, axial coding, and selective coding.

In total, from the 163 initial codes identified during open coding, 124 codes were classified into 25 main categories and five groups: causal factors, contextual factors, intervening factors, strategies, and outcomes. These were then presented as part of the research model.

Therefore, it can be asserted that the development of digital ecosystems and online entrepreneurship in Iran requires collaborative efforts among governmental, private, educational, and technological sectors. Such synergy can address challenges, leverage existing opportunities, and ultimately improve various economic, social, and technological aspects.

 The aim of the present study is to examine the mechanism of trust formation and its impact on satisfaction, behavioral intention, and actual behavior of mobile banking customers of Shahr Bank in Iran.

 This research is applied in terms of objective, causal in terms of method, and survey-based in nature. The data collection tool was a closed-ended questionnaire using a 5-point Likert scale. The sample consisted of 384 customers of Shahr Bank in Isfahan who used mobile banking services between March and May 2024. The sampling method was convenience sampling, and Cochran's formula was used to determine the sample size. Furthermore, structural equation modeling was employed to examine the relationships between variables using PLS software, and descriptive statistics were analyzed using SPSS software.

 The results showed that service quality (t-statistic = 2.20), information quality (4.55), system quality (2.85), structural assurance (7.12), and task-related features (3.22) significantly influence the trust variable. Additionally, there is a significant relationship between trust and user satisfaction with mobile banking (t-statistic = 21.29). User satisfaction with mobile banking leads to behavioral intention (t-statistic = 20.13), which in turn drives customers toward actual usage of mobile banking services (t-statistic = 12.75). Finally, the data fit indices such as composite reliability and Cronbach’s alpha were above the standard threshold of 0.7. 

 This study emphasizes the importance of trust and user satisfaction in influencing actual behavior in mobile banking and contributes to the existing body of knowledge on behavioral intention by offering a better understanding of how these factors affect intentions and preferences in developing countries such as Iran.

 The main objective of this research is to examine the impact of firm size and ownership structure on sustained innovation capability in companies listed on the Tehran Stock Exchange. 

 Given the structure of the data studied in this research, a ten-year period (from 2014 to 2023) was analyzed using the panel data method. The research data is a screened sample from the companies listed on the Tehran Stock Exchange, covering a total of 133 companies. To conduct the statistical analysis and model analysis, the EViews version 12 software was used. 

 The findings revealed that the estimated coefficient for ownership structure, at 0.0869 with a significance level of 0.0078, indicates a direct and significant relationship between this variable and the firm’s innovation capability. Additionally, the estimated coefficient for firm size, at 0.0674 with a significance level of 0.0021, shows a direct and significant relationship between this variable and the firm’s innovation capability. 

 It can be concluded that the larger the firm size and the more transparent the ownership structure, the greater the firm's innovation capability. Therefore, financial and economic planners should seriously consider these factors and take effective actions to promote innovation in companies and financial-economic institutions.

 This study aims to design a professional ethics charter for managers, emphasizing the values of Generation Z employees, with a focus on the National Iranian Oilfields Company in Ahvaz. 

 The research employs a mixed-methods approach, beginning with content analysis of professional ethics laws and related articles to identify key components and indicators. In the second phase, the Delphi method was used to refine and validate the discovered components. The final phase involved designing the ethics charter using a focus group technique, gathering insights from experts in the field. 

 The study identified 17 key components, encompassing 81 indicators for the creation of a professional ethics charter. These components included the values related to work, such as individual ethics, organizational commitment, employee satisfaction, and respect for Islamic principles. The Delphi method was employed to refine these components, ensuring their alignment with the needs and challenges of Generation Z employees in the workplace. 

 This research underscores the significance of integrating ethical values into organizational frameworks, especially in managing Generation Z employees. It provides a comprehensive approach to enhancing the ethical conduct of managers and employees, which in turn contributes to organizational success, employee retention, and competitive advantage in the workforce.

 The aim of this research is to examine the impact of disclosing sustainability reporting dimensions on the financial and non-financial performance of manufacturing and non-manufacturing companies. 

 This research is a descriptive-correlational study. The statistical population includes all managers of manufacturing and non-manufacturing companies listed on the Stock Exchange, from which 240 individuals were purposefully selected. To collect data, a researcher-designed and standardized questionnaire was used (Cronbach's alpha coefficient: 0.78). Structural equation modeling and AMOS software version 22 were employed to test the research hypotheses. 

 The results showed that the disclosure of sustainability reporting dimensions has a positive and significant impact on the financial and non-financial performance of both manufacturing and non-manufacturing companies (p < 0.001). 

 It can be concluded that the disclosure of sustainability dimensions positively influences financial indicators such as return on assets, market share growth, and sales revenue, while also enhancing non-financial benefits such as customer satisfaction, internal process efficiency, and organizational learning. These results emphasize the value of integrating sustainability practices into corporate strategies to achieve long-term competitive advantages. The implications of this study underscore the necessity for regulatory bodies to develop integrated sustainability reporting standards to ensure transparency and accountability in corporate activities.