The emerging growth digital application has driven ecosystems integrating digital banks and e-commerce platforms, enabling seamless, efficient transactions. This study examines the impact of user experience and satisfaction on reuse intention in this integrated environment. Using a mixed-method approach, data were collected through surveys of 471 respondents and interviews with 30 participants. Quantitative data were analyzed using structural equation modeling, while qualitative data were processed through content analysis. Results show that perceived ease of use, usefulness, reliability, value, and risk significantly affect user experience, while perceived security does not. These findings aim to help digital banks and e-commerce platforms design effective CRM strategies to enhance satisfaction and reuse intention.

This study aims to explore the connotation of “Guanxi” within contemporary Chinese marketing channels and to construct and verify a global management model. The objective is to examine how instrumental and emotional dimensions of Guanxi influence enterprise operations and management processes. A hybrid research methodology combining qualitative and quantitative approaches was employed. In-depth interviews with 30 dealer executives provided qualitative insights, while a large-scale survey with 305 valid responses facilitated quantitative analysis. SPSS22.0 and LISREL8.8 were utilized for data analysis, including reliability, validity, hypothesis testing, and structural equation modeling (SEM). The findings reveal that Guanxi is multi-dimensional, comprising both instrumental and emotional components. Instrumental Guanxi includes factors such as status, prestige, credibility, and decision-making power, while emotional Guanxi encompasses trust, emotional connection, and mutual respect. Both dimensions significantly affect professionalism, shared values, contact frequency, and popularity within marketing channels. Hypothesis testing confirmed the significant relationships between these variables, except for the non-significant impact of popularity on instrumental Guanxi. The mediating effects of flexibility and supervision on the relationship between Guanxi and corporate performance were also significant, highlighting the mechanisms through which Guanxi influences organizational outcomes. Moderating effects of perceived internal incentive fairness and digital collaboration capabilities further amplify these relationships. Finaly, the study underscores the dual importance of strategic utility and emotional resonance in Guanxi, providing a robust model for understanding its impact on business management. These insights are valuable for both researchers and practitioners aiming to leverage Guanxi in enhancing organizational performance and relational strategies.

The scientific discourse on university towns (UT) has progressed for a long time, with a surge of interest in recent years. However, a global overview of the research conducted on this topic have yet to exist. This paper aims to re-examine the relationship between UT and urbanization in literature. Built environment and people are often the most talked aspects in UT literatures. The variety of definitions remains largely uncharted. Policies behind UT development are also rarely studied. This article used an R studio-based bibliometric literature review to synthesize findings from various scientific literature. Keywords related to university towns and urban were used in digital search engines to examine and analyse the literature. Results revealed a significant gap in scientific research on critical theoretical concepts that planners can use as a guide in creating, formulating, and evaluating UT, especially in developing countries. This study promotes simplification of existing literature by examining the impact of UT on the stakeholders involved.

The present research focuses on researching the impact of the diverse communication media that facilitate or develop Student Motivation and Engagement in the educational systems of the states in the Gulf, especially Oman. The main goal of this work is to determine which type of method is most effective in encouraging students in view of cultural and technological factors present in the region. Comparisons using hypothesis testing and structural models which provided higher T value for Technology-Based Communication Methods (TBCM) and Human Face-to-Face Communication Methods (HFtFCM). Next, the research hypothesis H2 that TBCM has a direct positive relationship with SMaE was supported by the following regression coefficients: β = 0.177, t = 4.493; p = 0.000. On the other hand, there was no effect of HFtFCM on SMaE as indicated by a regression coefficient of 0.056 (p < 0.124) for this hypothesis and therefore, this hypothesis was rejected. The analysis using the mediator of Student Perception of Communication Effectiveness (SPoCE) only partly mediates TBCM and SMaE (β = 0.047, t = 3.737, p = 0.000). However, SPoCE was found not to moderate the relationship between HFtFCM and SMaE (β = −0.01, t = 1.125, p = 0.005). The present study underlines the efficiency of TBCM in the area of student engagement, while face-to-face conversation does not play significant part in this process. The obtain results conclude that, the traditional and technological evolution in the Gulf region supports the adoption of TBCM in educational systems. Such approaches support with the technological learning and likings of students, offering greater flexibility and engagement. Educational systems must highlight TBCM to better meet the growing needs of their student, while identifying that face-to-face remains important, though secondary, in energetic motivation.

The proposed research work encompasses implications for infrastructure particularly the cybersecurity as an essential in soft infrastructure, and policy making particularly on secure access management of infrastructure governance. In this study, we introduce a novel parameter focusing on the timestamp duration of password entry, enhancing the algorithm titled EPSBalgorithmv01 with seven parameters. The proposed parameter incorporates an analysis of the historical time spent by users entering their passwords, employing ARIMA for processing. To assess the efficacy of the updated algorithm, we developed a simulator and employed a multi-experimental approach. The evaluation utilized a test dataset comprising 617 authentic records from 111 individuals within a selected company spanning from 2017 to 2022. Our findings reveal significant advancements in EPSBalgorithmv01 compared to its predecessor namely EPSBalgorithmv00. While EPSBalgorithmv00 struggled with a recognition rate of 28.00% and a precision of 71.171, EPSBalgorithmv01 exhibited a recognition rate of 17% with a precision of 82.882%. Despite a decrease in recognition rate, EPSBalgorithmv01 demonstrates a notable improvement of approximately 14% over EPSBalgorithmv00.

This study employed a deductive approach to examine external HRM factors influencing job satisfaction in the post-pandemic hybrid work environment. Explores the intermediary functions of age, gender, and work experience in this particular environment. The data-gathering procedure consisted of conducting semi-structured interviews with carefully chosen 50 managers representing various sectors, industries, organizations, and professions. The applied approach was adopted to allow a systematic and unbiased investigation of the mediating variables. The study used SPSS 25 and Smart PLS 4 to analyze the model, enhancing understanding of HRM challenges in a constantly evolving workplace. The findings offer valuable insights for HR experts and businesses, highlighting the value of comprehending what methods HRM components influence job satisfaction to optimize employee well-being and productivity. The study provides applied recommendations designed for enhancing employee contentment in the AI-evolving professional atmosphere, shedding light on the importance of supportive leadership strategies, particularly during AI-triggered downsizing. Additionally, we welcome a new era to push forward in integrating and managing AI tools and technologies to automate decision-making and data processing. Results propose that Exogenous influences of human resource management (HRM) influence manager job satisfaction considerably. Specifically, downsizing caused by AI was found to have negative consequences, whereas diversity and restructuring have favorable effects. Gender was recognized as a crucial factor that influences outcomes, then age and years of experience have the most visible effect.