درخت حوزه‌های تخصصی

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.

The present study aims to investigate the association between political connections and related-party transactions for the firms listed on the Tehran Stock Exchange (TSE). Sample includes the 485 firm-year observations from companies listed on the Tehran Stock Exchange during the years 2013 to 2017 and research hypothesis was tested using multivariate regression model based on panel data.We find that political connections are negatively associated with related-party transactions. In other words, politically connected firms are less inclined to exercise opportunistic behaviours by related-party transactions in comparison to other firms. Moreover, additional analysis reveals that the negative relationship between political connections and related-party transactions is more pronounced in larger firms.Our findings not only extend the extant theoretical literature concerning the stock political economy in developing countries including emerging capital market of Iran, but also help investors, managers, capital market regulators, policy makers and accounting standard setters to make informed decisions.

The present research examines the benefits of implementing knowledge management (KM) principles in the Jordanian banking sector to enhance performance. The study emphasizes the significance of Artificial Intelligence (AI) and how Jordanian banks utilize it to improve the quality of customer service they provide. This study targets managers at all levels and focuses on the Jordanian banking sector as its research environment. A questionnaire is created to gather information from a random sample to achieve the research's objectives. The study involves a sample of 250 managers. Additionally, the research adopts a descriptive methodology, and SPSS is used to analyze the data. The statistical findings provide robust evidence for the importance of performance expectations, social influence, and perceived risk in influencing consumer intentions. Marketers and decision-makers within the banking industry can leverage these insights to shape their long-term strategies for effectively utilizing and maximizing AI technology in the banking sector. Furthermore, by providing policymakers and practitioners of Jordanian commercial banks with insight into the variables influencing user satisfaction, the findings will help these complex institutions operate more effectively.