درخت حوزه‌های تخصصی

Purpose: The purpose of this research was to provide a model for choosing the best content for the activity of service guilds.Method: In inferential statistics, the K-S test is used for the normality of research hypotheses. For this purpose, Pearson's correlation coefficient and linear regression tests have been used through SPSS 21 software, and the best content generated using genetic algorithms and forbidden search were introduced.Findings: Analysis of research and implementation results with two collective intelligence algorithms shows that Instagram has a positive and significant effect on all four dimensions and thus leads to the success of the service classes that have used Instagram.Conclusion: In this article, a combination model of genetic algorithm and forbidden search algorithm was chosen for users so that the best content, which of course does not contain malicious ads and cookies, etc., is introduced for the continuation of the service industry.

Purpose: This research aimed at presenting the consumers’ compulsive buying pattern through internet advertisements of digital content in Iran's TV shopping industry.Method: Research Methodology was practical in terms of purpose and conducted using mixed method (qualitative-quantitative). The research community was based on the purposeful sampling method, and consisted of ten marketing experts. The research tool was interview. MAXQDA software was used to analyze data through database theory. The statistical population in the quantitative section included TV buyers in Mashhad. Based on Morgan table and random sampling, 384 samples were selected. The research tool was a researcher-made questionnaire, and the Structural Equation Method (SEM) in SmartPLS software was used for data analysis. The validity of the questionnaire was confirmed by using face, content, divergent and convergent validities, and its reliability was also confirmed using Cronbach's alpha. Both of Composite and homogeneous reliability were evaluated.Findings: "appropriate digital marketing mix design for TV sales, digital marketing capabilities, individual demographic characteristics, lifestyle, family " constitute the causal conditions in the consumer’s compulsive buying pattern in the TV shopping. According to the findings, “quick and transient purchase and irrational and emotional purchase” were identified as a central phenomenon. “TV's attractiveness from the audience's point of view, broadcasting policies, sales companies' policies, national TV belief and trust, individual awareness and knowledge about buying products and society's culture” acted as intervening conditions. In the field of buying, “intellectual structures of society and executive structures of society” identified as background conditions. Human strategies and structural and organizational strategies” acted as strategies and “Consumers outcomes; families and society outcomes” were identified as outcomes. According to the results of structural modeling, the relationships of the identified pattern were significant.Conclusion: The issue of compulsive buying is one of the most important and common issues, and buying from TV has fueled this issue, and has become the basis for its expansion and, following that, its negative consequences. In this scientific research, efforts were made to reduce the consequences of this phenomenon. The results of this study showed that although the phenomenon of compulsive purchase from TV is negative, but with proper management, useful results can be obtained from it.

In this paper, we present a comprehensive approach for evaluating efficiency in complex networks by integrating network data envelopment analysis (NDEA) with the Malmquist productivity index. The proposed method addresses the inherent challenge of accommodating negative data within the network efficiency evaluation framework, which is a common occurrence in real-world network operations. Through the introduction of a two-stage structure, the model not only effectively manages the presence of negative values, but also provides a robust and insightful assessment of network efficiency. A case study from banking sector is employed to demonstrate the efficacy of the proposed approach, showcasing its capacity to offer valuable and actionable insights for decision-making in complex network environments. The results highlight the practical applicability and importance of the extended approach in addressing the complexities associated with evaluating efficiency in diverse network settings.