مجله مدیریت کسب و کار
پیاپی 64 (زمستان 1403)

Risk management is a key tool for improving customs performance and positively impacting businesses. Iran Customs, responsible for overseeing imports and exports and combating illegal trade, requires the design and implementation of effective risk management models. This study presents a comprehensive model for import risk management based on the principles of the resistance economy. The research methodology is mixed-methods, including both qualitative and quantitative analyses. In the qualitative phase, the Delphi method and interviews with 14 experts, including the Head of Customs and senior managers, were conducted. In the quantitative phase, data collected from 165 customs managers were analyzed using statistical methods. The findings indicate that the lack of electronic equipment, absence of meritocracy, and sudden changes in customs duties are the most significant import risks. The proposed model identifies, prioritizes, and formulates management strategies that can improve customs processes, reduce import risks, and facilitate legal trade, ultimately supporting business growth and economic development.

The main purpose of this research is to investigate the effect of effective factors on improving the quality of electronic services of public service organizations, according to the conceptual model extracted through the ground theory method, a questionnaire was prepared and after checking its reliability and validity, it was distributed and collected in the statistical population. The hypothesis test was performed through the partial least squares method of the structural equations technique of SmartPLS software and the results according to the standard coefficients charts and the significance level showed that the value of the T statistic obtained for the paths drawn in the model of improving the quality of electronic services of public service organizations based on The foundation data method is more than 1.96. The value of the T statistic for the path of causal conditions to the central category is equal to 6.606, for the path of the central category to strategies is equal to 5.395, for the path of intervening conditions to strategies is equal to 4.983, and for the path of background conditions to strategies is equal to 2/417 and strategies on consequences is equal to 21/040. 

Digital transformation, as a macro-organizational process, includes the integration of digital technologies in different departments of the organization, which leads to improved transparency, speed in responding, and increasing the quality of information. As a result of these changes, companies can increase their business credibility with suppliers and lenders. Business credibility means the trust that stakeholders have in companies and is one of the key factors for attracting facilities and financial resources. Trade credit plays an important role in financing activities of companies. Therefore, this study has investigated the relationship between digital transformation and attracting commercial credit in companies active in the Tehran Stock Exchange. This research is quantitative, descriptive, semi-experimental and library. The research method is correlational in terms of content and nature. Based on this, the analysis was performed on a sample of 128 active companies in the Tehran Stock Exchange for 10 years from 2014 to 2023. Multivariate regression with year and industry fixed effects has been used to test research hypotheses. The results of data analysis show that digital transformation has a positive and significant effect on the attraction of commercial credit of companies.

The aim of this research is to design a comprehensive model for strategic market-oriented management of Saipa Company, with a focus on export strategies. This research is applied and developmental in terms of its objective, and exploratory with a qualitative approach in terms of its nature. The statistical population of the study includes specialists, senior managers, and experts in the automotive industry and sectors related to automotive product exports. Using purposeful sampling, the sample consisted of 18 academic members (university professors), managers, and experts from the automotive industry. Data collection was carried out through semi-structured interviews and library research. Data analysis was performed using a grounded theory approach, assisted by MAXQDA v10 software, and the coding process took place in three stages: open, axial, and selective coding. The results of the qualitative data analysis led to the design of a paradigmatic model for market-oriented strategic management with an emphasis on exports at Saipa Company. This model includes six main dimensions.

Credit scoring models have evolved significantly over time, incorporating various techniques to assess the creditworthiness of individuals and businesses. Credit scoring is an important process for credit providers because it determines the probability of default or non-default of applicants and plays an important role in determining people's ability to receive facilities and credit. Traditional credit scoring models, such as those that incorporate the credit history and repayment behavior of borrowers, have been of interest in credit risk management for decades. These models help decision-making processes by evaluating credit, influencing loan approvals, and shaping preventive measures in case of default. Using emerging machine learning frameworks and approaches and alternative data sources, credit scoring methods will become more successful over time in optimizing risk management, improving loan approval processes, reducing investment risk for lenders, and effectively addressing the financial needs of borrowers. In this research, a comprehensive classification of credit scoring models has been presented using bibliometric citation analysis and includes more than 100 cited articles.

The prevalence of endowment culture in Islam is an important and widespread discussion. Also, the role of endowment as a civil matter arising from Islamic knowledge and high culture in economic, cultural, and social development and organizing the issues and problems of society is not hidden from anyone. The purpose of the present study is to present an applied model of participatory endowment using the Delphi method. The research method is descriptive-analytical in nature and in terms of method, and it was conducted using the Delphi method and using books, magazines, articles, and documents with a qualitative approach. Qualitative content analysis was used to analyze the data and structural-interpretive modeling was used to validate the components of the model. This study has an interpretive approach in terms of philosophy and is developmental in terms of orientation. The research findings showed that the most effective motivations of endowments are religious motivations (God's pleasure, reward in the hereafter), serving others, building hospitals, and spreading science and knowledge in society.

Predicting the income and costs of transportation in transit, can help shipping companies for better planning to attract transit and increase foreign revenue for the country. The purpose of research is to predict the cost and income of shipping companies in transit using dynamic system. The research method is descriptive and the method of data collection are data base and field study. The samples include two groups, the first group are experts in the field of financial and transportation has been used to determine the dimensions and variables of model and the second group are data for model which composed of three transport companies in the bandar abbas-Sarakhs corridor. To obtain and validate the behavior of the system We considered cost of the time from 2011 to 2024 year, and run VENSIM software for prediction cost and income from 2024 to 2030. By introducing and adding new variable of trade velocity to the model, the results showed that income, cost of each trip and total cost of transportation will increase significantly. Also, by changing in the exogenous variable, income and cost will be changed, therefore, it is suggested that the government pay special attention to improvement of trade speed.

The purpose of this research is to investigate the impact of social and environmental factors on the purchase of fixed phone services on improving customer experience (fixed phone customers in Tehran). this research is an applied developmental research based on the result, and mixed method research combining two qualitative and quantitative research. The qualitative research method is the grounded theory and exploratory and confirmatory factor analysis. The participants in the qualitative part of the research are experts and marketing experts and managers of communication companies. By conducting in-depth interviews, data analysis was carried out through three stages of open, axial and selective coding, and quantitative research was conducted using a questionnaire tool and a statistical population of fixed phone service customers in Tehran. As a result of the interview and the use of the contextual method, 8 main indicators and 25 sub-criteria for improving the customer experience were identified and the final model was presented. The results of the research show that social factors (social perception, social support, social environment) have a more significant impact on improving the customer experience compared to environmental factors at a confidence level of 0.95, which can be taken into account by managers.

This research has been done with the aim of designing a model for leveling organizational resilience factors in knowledge-based companies in the plastic industry. The study is applied in terms of purpose and survey in terms of library method. This research has been done in a qualitative-quantitative way. In the qualitative part, the theme method and in the quantitative part, the Structural-Interpretive Equations (ISM) method has been used. The research tool was used in the qualitative part of the semi-structured interview and in the quantitative part of the researcher-made questionnaire. The results of the research indicate that 4 dimensions (environmental, organizational, managerial, individual) have been identified in the qualitative section, and each dimension includes a component. In the quantitative section, the leveling of dimensions and components has been discussed. In the leveling section, the dimensions are placed in 3 levels. It is located on the third level of the environmental dimension. The environmental dimension is the most influential component. The third level affects the second level, i.e., individual, managerial and organizational components. The components of the second level, i.e., the individual, managerial and organizational components, influence the first level, i.e., the organizational resilience component.

Accurate identification of factors affecting product quality can lead to improved production processes, reduced waste, increased productivity, and ultimately improved customer satisfaction. This study aimed to identify factors affecting the quality of industrial products and analyze the relationships between these factors using data mining and clustering techniques. Data related to the industrial production process, including variables such as raw material purity, machine error rate, temperature, pressure, production speed, and human experience, were simulated and preprocessed. K-Means, hierarchical clustering, and DBSCAN algorithms were used to analyze the data. The results showed that raw material purity, machine error rate, and temperature are among the most important factors affecting product quality. Also, clusters with high raw material purity (>95%) and machine error rate less than 2% showed the best quality, while clusters with low purity and high production speed had poor quality. This research provides a comprehensive model for analyzing and optimizing the quality of industrial products that can be used in various industries such as automotive, pharmaceutical, and food industries