درخت حوزه‌های تخصصی

Objective : This study examines the impacts of Extended Producer Responsibility (EPR) on product life extension and market dynamics. It investigates the relationship between the physical and emotional durability of products in the apparel supply chain, highlighting the importance of the secondary market in prolonging product life and value. By understanding the connections among producers, consumers, and the secondhand market, the study aims to develop a practical approach that helps planners derive optimal synergistic solutions, considering the needs of consumers, ecological considerations, and the economic factors within the apparel market. Methods : The interactions among consumers, producers, and the government are demonstrated through agent-based simulations across five scenarios. The market includes various groups of consumers to represent its heterogeneous nature. The simulation, conducted in NetLogo, models the behavior of both producers and buyers in the context of government intervention. Results : Simulation results indicate that EPR policies, combined with government interventions such as incentives, penalties, and regulations, can effectively promote the management of products at the end of their life cycle. In scenarios that utilized incentives, producers were more likely to buy and sell secondhand products, reducing the production of new items and increasing recycling rates. These results underscore the critical importance of collaboration among the government, the public, and producers to implement EPR policies successfully. Conclusion : Effective implementation of EPR policies requires government market intervention calibration. When the government applies a reward-and-penalty system to enforce EPR, product waste is reduced, and producer profitability surpasses other scenarios.

Purpose : This research aims to develop a digital marketing model for the business-to-business (B2B) commerce sector. Method : This applied research, which used a mixed-methods approach, started with a qualitative phase to create initial model. This was followed by thematic Subsequently, an interpretive structural modeling at the thematic interpretive structural modeling. A quantitative validation of the model was then conducted. The qualitative sample included 15 experts, selected based on theoretical saturation. In the quantitative phase, a random sample of 384 managers from industrial companies was drawn from an effectively infinite population. Thematic analysis was used for qualitative phase, while partial least squares technique was employed in the quantitative analysis. Findings : The qualitative phase identified key themes: infrastructure, training and learning, organizational culture, regulations, relation channels, social network, customer orientation, cost and income, investment and competitive advantages. Based on these, thirteen hypotheses were developed and tested. The results indicated that infrastructure has a significant impact on regulations, organizational culture, and training and learning; regulations have a significant impact on social networks; organizational culture has a significant impact on social networks and communication channels; training and learning have a significant impact on communication channels; social networks have a significant impact on customer orientation; communication channels have a significant impact on customer orientation; customer orientation has a significant impact on capital attraction, cost performance, and revenue; capital attraction has a significant impact on competitive advantage; cost performance has a significant impact on competitive advantage. Conclusion : The study concluded that B2B digital marketing is a complex topic and B2B businesses should carefully consider the subtleties of this form of marketing.

Financial resilience in businesses refers to their ability to withstand economic shocks and challenges while maintaining financial stability under difficult conditions. This study adopts an applied research approach with both descriptive and prescriptive future-oriented methods. It is qualitative research that uses Causal Layered Analysis (CLA) to identify financial resilience in entrepreneurial businesses. To achieve a deep understanding of causal layers, scenarios are developed based on the global business network perspective. Two rounds of interviews were conducted with 35 experts, both structured and unstructured, to extract financial resilience indicators in Iranian entrepreneurial businesses. From the literature review and expert interviews, 35 factors were identified. Two factors, enthusiasm and fear of failure, were eliminated, resulting in 33 final factors. The matrix of financial resilience scenarios for entrepreneurial businesses was presented in four scenarios: economic crisis, economic boom, old technology, and new technology. Subsequently, SWOT analysis was used to analyze and propose strategies aimed at directing towards the third scenario. The findings indicate that utilizing the CLA approach aims to offer a plan in the field of financial resilience for entrepreneurial businesses. This helps planners to set aside current thinking and consider possible and probable futures, which may not necessarily be a continuation of past trends, to achieve a long-term plan to enhance financial resilience in entrepreneurial businesses.

This study aims to analyze 45 definitions of digital transformation (DT) to identify key drivers and propose a conceptual framework to outline their impact on business performance. Through content analysis, 24 key drivers were identified, focusing on the frequency of occurrence across the definitions. The analysis highlights drivers such as IT technologies & innovation, business model, business performance, customer experience, and operational processes. The results show a significant emphasis placed on various drivers of DT, reflecting its multidimensional nature. Key drivers include technological innovation, organizational adaptation, customer-centric strategies, and change management practices. By conceptualizing the relationships between key drivers and performance outcomes, the proposed conceptual framework provides theoretical insights into the mechanisms underlying digital transformation and its impact on business performance. The proposed framework integrates technological, strategic, organizational, and cultural dimensions. The analysis underscores the complexity and multidimensional nature of DT as a strategic phenomenon and offers drivers on which the organizations should focus to face the challenges of digital disruption. This paper's original theoretical contribution lies in synthesizing various definitions of digital transformation from the past two decades to propose a comprehensive definition of Corporate Digital Transformation.

Taxes serve as a vital source of funding for governments and significantly influence economic growth and income distribution, which varies based on a country's level of development and economic framework. Recently, researchers have introduced methods to identify effective factors in preventing tax evasion. Most of these methods rely on basic techniques such as regression, structural equations, and non-intelligent methods that cannot effectively analyze the relationship between the values of the variables involved in this field. Therefore, in this study, we introduce a method that leverages artificial intelligence techniques, specifically a meta-heuristic optimization approach and a perceptron neural network. This method effectively analyzes the nonlinear relationships within the data while addressing both the intrinsic and extrinsic aspects of the data dimensions simultaneously. The research sample consists of 25 experts from the Tax Affairs Organization, and the study was conducted in the year 2022. The results indicate a high prediction accuracy of approximately 98%. Additionally, it highlights the significant role of various factors contributing to tax evasion, including income concealment, money laundering, economic crises, political trust, the weaknesses, and complexities of tax laws and regulations, inadequate clarification of tax laws, contradictions in legal tax articles, administrative bureaucracy, and an inefficient tax structure.