درخت حوزه‌های تخصصی

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.

The current research was conducted with the aim of providing a sustainable marketing model in the insurance industry with a focus on artificial intelligence. According to the type of data, the research method is mixed (qualitative-quantitative) of exploratory nature. In the statistical population, 12 people were selected from among the experts until the theoretical saturation was reached. The experts included professors of the faculty of business management and senior managers of Alborz insurance company, who were selected by non-probability, targeted and chain sampling. Quantitative part of 400 managers were insurance industry experts, using Cochran's formula, 196 people were selected by stratified random method. To collect data, semi-structured interviews and researcher-made questionnaires were used. The analysis method has been carried out in several consecutive steps. In the first stage, to identify the components of the model, the qualitative method and semi-structured interviews using the grounded theory have been used. In the next section, using interpretative structural modeling, the identified indicators were leveled. Finally, in order to fit the designed model in the qualitative part, a quantitative method with structural equation modeling approach was used with PLS4 software. The findings showed that 6 components were identified and there is a significant relationship between all components and sustainable marketing and the designed model has an acceptable fit. It can be concluded that AI can be incorporated as an essential component of a sustainable marketing strategy, enabling marketing professionals and businesses to make positive changes while increasing their brand reputation and profitability.

In this research, the influencing factors on the behavior of human resources in the marketing department and human resource management policies and their relationship with the strategies of this department have been examined in order to identify the factors that are related to the superior performance of this department. This research was carried out in the framework of a qualitative approach and using grounded theory. The data collection tool was semi-structured interviews, which were conducted using a combination of purposive (judgmental and quota) and theoretical sampling. The theoretical saturation criterion was used to determine the sample size and 36 interviews was conducted in 14 manufacturing companies in order to finally achieve theoretical adequacy along with document content analysis. Atlas. ti software was used to analyze the data obtained from the interviews and coding. Data analysis was done in three stages open coding, axial coding, and selective coding, and based on that, a qualitative research model was presented. The results of the research led to the extraction of 669 open codes, 160 concepts and 40 categories in the form of a paradigm model include the central category (strategic management of human resources in marketing, culture, improvement and correction, coherent and aligned systems), causal conditions (control of destructive effects) , strategic human resources and competition in the market, job type, priority dimensions, value addition and customer retention), strategies (job satisfaction, commitment, trust, perceived organizational support, motivation, justice, reward, employee participation, loyalty, empowerment, empowerment, green insight into human resources and marketing), the prevailing context (demographic characteristics, psychological characteristics, organizational structure, strategy, organizational culture and supply, technology in use) and finally outcomes (superior performance, organizational citizenship behavior, key work behaviors and production axis, the effects of human resource strategies, environmental thinking and green performance) were presented.

Nowadays, researchers and managers believe that paying attention to employees' thoughts facilitates sustainable competitive advantage in organizations. After the introduction of cognitive science into organizations, the identification of what it is, how it is formed, and the formulation of Counterfactual Thoughts (CTs) have been investigated and analyzed in the field of Human Resources (HR). In this study, a systematic review of the literature in the field of CT has been done with the aim of identifying the antecedents and key consequences of this field and analyzing them. In this research, a two-stage methodology has been considered including (i) Extraction of antecedents and consequences, (ii) Weighting of antecedents. In the first stage, using the screening of articles based on the seven-step method of Sandelowski and Barroso, the antecedents and consequences of CTs, synthesis and interpretation have also been implemented through the coding method of qualitative interpretive meta-analysis. In the second stage, the consequences extracted in the field of counterfactuals are weighted using the matrix of paired comparisons based on the opinions of experts in the field of HR and AHP, which can be used to evaluate employees' thoughts and behavior. Based on the screening of the articles, the antecedents are categorized into 4 general concepts with 12 codes, and the consequences are classified into 2 and 8 codes. The results of the AHP analysis show that the normalization of the condition related to the behavioral outcome has the greatest impact on the evaluation of employees' thoughts and behavior, while the regulation of related emotions as a result of attitude has the least impact among the codes introduced in this evaluation.