Designing a Value Chain Management Model for Optimal Fulfillment of Social Responsibility in the Context of Blockchain Technology
Keywords:
Technology, Blockchain, Social Responsibility, Value ChainAbstract
The present study was conducted with the aim of designing a value chain management model for the optimal fulfillment of social responsibility in the context of blockchain technology. The research method employed was qualitative, based on the grounded theory strategy. For data collection, the tool of in-depth interviews was used. The target population consisted of academic experts, managers, and senior specialists who were involved in the processes and decision-making of value chain management in the insurance industry. Through purposive sampling and deep interviews, theoretical saturation was achieved. In the grounded theory approach used in this study, through three stages of open, axial, and selective coding, the general categories were represented within a paradigmatic framework, including causal conditions, contextual conditions, intervening conditions, core categories, strategies, and outcomes, all based on value orientation. The results indicated that all relationships among variables were significant. Specifically, the following influential relationships were confirmed: causal conditions had a significant effect on the main category of the model; contextual conditions influenced the strategies; intervening conditions also had a significant effect on the strategies; the main category had a direct impact on the strategies; and finally, the strategies had a direct and significant effect on the research outcomes. In the Importance-Performance Map Analysis (IPMA) section, the model’s indicators were evaluated in terms of importance and performance. These results can serve as a basis for strategic and managerial decision-making in various fields, especially in the evaluation and improvement of organizational processes and change management strategies. In summary, this study effectively evaluated the conceptual model and demonstrated that various factors such as causal conditions, contextual conditions, intervening conditions, and strategies influence the research outcomes. Moreover, the structural model of the study exhibited high goodness-of-fit and validity, and the relationships among its variables were confirmed.
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