درخت حوزه‌های تخصصی

Objective: “In the digital age, anthropomorphism—attributing human characteristics to non-human entities in digital environments—plays a pivotal role in improving user experience (UX) and fostering customer loyalty. With the increasing adoption of artificial intelligence (AI) and intelligent interfaces, simulating human interactions such as digital platforms has emerged as a powerful mechanism for creating emotional connections and facilitating interactions. This study seeks to identify the antecedents and consequences of anthropomorphism in digital user environments and assess its impact on user experience and customer loyalty. Methods: Using a qualitative and exploratory approach, this research examines data collected from semi-structured interviews with 16 academic and industry experts using thematic analysis. Sampling was conducted through a snowball technique, and theoretical saturation was considered as the criterion for determining sample size. Results: The findings show that the antecedents of anthropomorphism include six main factors: personalization and optimization of user interactions (including personalized user experiences and emulation of human emotions), human-like interactions and natural communication in digital spaces, social and emotional experiences of users, intelligent responsiveness and optimal interactions, emulation of human and psychological behaviors, and user loyalty and trust enhanced through human-centered interactions. The implications of anthropomorphism include increased social interactions, intelligent responsiveness, personalized experiences, and enhanced customer trust and loyalty. Conclusions: The results indicate that anthropomorphism helps increase user satisfaction and strengthen customer loyalty by personalizing interactions and creating emotional bonds. These insights offer valuable implications for designers and marketers of digital systems who aim to optimize user experiences and develop effective customer retention strategies.

The absence of a comprehensive and localized model for the effective management of the cost of money in the country’s banking system, considering the cultural, economic, and structural complexities inherent in the banking industry, constitutes a fundamental challenge. Therefore, the present study aims to articulate a model for managing the cost of money in Iran’s banking industry through a grounded theory approach. This research is applied in purpose and conducted with a qualitative methodology based on grounded theory. The statistical population consists of distinguished professors in the fields of finance, accounting, and management, as well as senior banking executives including bank presidents and faculty members of reputable universities in the country, selected during the years 2023 and 2024. Sampling was carried out purposefully and through the snowball method until theoretical saturation was achieved. Data were collected through library studies and 11 semi-structured interviews with banking and academic experts possessing sufficient expertise and professional experience. The data were analyzed using Strauss and Corbin’s three-stage coding process with MAXQDA software, which resulted in the extraction of 95 basic concepts categorized into four main themes: socio-cultural-political factors, technical-structural factors, environmental and contextual factors, and factors related to the improvement of economic indicators. The findings indicate that comprehensive management of the cost of money requires simultaneous consideration of technological, structural, interactive, and policy-making components. The proposed conceptual model, by clarifying the relationships influencing resource mobilization and cost control in Iran’s banking industry, provides practical strategies for enhancing efficiency, strengthening economic governance, and developing banking services. Furthermore, factors such as interbank interest rates, economic risks, operational costs, inflation, and exchange rates were identified as decisive variables. Ultimately, the finalized model, informed by expert insights, delineates a pathway for reducing costs and improving the efficiency of the banking system.