The examination of the impact of Generative AI (GenAI) on higher education, especially from the viewpoint of students, is gaining significance. Although prior research has underscored GenAI's potential advantages in higher education, there exists a discernible research gap concerning the determinants that affect its adoption. In the present study, we aim to enhance our comprehension of the factors influencing the willingness of higher education students to adopt GenAI tools. To achieve this, we have developed an extended Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) model incorporating specific GenAI constructs. Our research methodology entailed the selection of a diverse sample of 374 students through random sampling. We then analyzed their data using Structural Equation Modeling (SEM) to gain insights into the complex relationships between various variables. The study found that students are more likely to use GenAI tools when they view them as supplemental resource and effort expectancy. It also revealed that perceived costs negatively impact adoption intentions, highlighting that financial factors are a significant barrier. Interestingly, Factors like information accuracy and hedonic motivation did not significantly affect students' adoption intentions. This study offers key insights for eLearning practitioners on integrating Generative AI (GenAI) tools into educational settings. It emphasizes the significance of resource perception and effort expectancy, demonstrating GenAI's potential to personalize learning experiences. eLearning platforms can utilize GenAI to enhance active learning through engaging methods and streamline course development. Addressing cost barriers is crucial for equitable access and inclusivity. A gradual approach to integration aligned with learning objectives is recommended, along with fostering critical engagement with GenAI tools to enhance digital literacy. Lastly, the study is constrained by its specific context, potential biases in self-reported data, a narrow focus on factors influencing students' intent to use GenAI tools and a cross-sectional design. Future research should encompass a broader range of factors, employ objective measures, and integrate observational data. Longitudinal studies or experimental designs could offer more comprehensive insights into how students' perceptions and intentions develop, thus promoting a more inclusive educational environment for all students.

This study empirically investigated the drivers of port competitiveness among low-, upper-, and high-income countries in the Middle East and North Africa region. It explored the effects of country-level competitiveness, logistic performance, and ease of doing business on port competitiveness for 17 countries from the region using a 14-item scale and covering the years 2010 to 2022. Port competitiveness indicators were analyzed using confirmatory factor analysis to determine the research constructs’ validity. Structural path analysis was deployed to verify hypotheses concerning effects between conceptualized variables. The findings demonstrate that in high-income countries, an increase in country competitiveness notably enhances port sustainability and competitiveness. Conversely, in low-income countries, higher country competitiveness appears to diminish port competitiveness. For countries with average income, the association is relatively neutral, exhibiting a slight positive trend. This study explains the specific drivers and interactions that improve port sustainability and competitiveness as countries move from low- to high-income levels of development.

This study explores the impact of digital banking channels on the operational excellence of Jordanian banks. It investigates the impact of social media, chatbots, digital wallets, and mobile applications on operational excellence in Jordanian banks, focusing on the moderating role of organizational culture. The study used a quantitative research method and a stratified random sampling technique to ensure a diverse sample of the five largest banks in Jordan, including managers and IT professionals responsible for managing digital banking operations. A total of 276 completed questionnaires were analyzed using structural equation modeling. The findings show that digital banking channels significantly contribute to operational excellence. Social media banking (β = 0.155, p < 0.05) and chatbots (β = 0.212, p < 0.01) positively impact operational excellence, while digital wallets (β = 0.301, p < 0.001) and mobile banking applications (β = 0.22, p < 0.01) also exhibit significant positive effects. The structural model explained 63% of the variance in operational excellence. Additionally, organizational culture was found to positively moderate the impact of social media banking (β = 0.20, p < 0.01), chatbots (β = 0.10, p < 0.05), and digital wallets (β = 0.16, p < 0.01) on operational excellence. However, the interaction between mobile applications and organizational culture was not significant (β = 0.078, p = 0.065).

Objective: The main objective of this study is to develop an eHealth adoption model based on patients’ perceptions of public value dimensions and empirically apply the model to understand the adoption of a governmental health app by Jordanian patients. The study attempts to contribute to overcoming the narrow focus of contemporary theories such as UTAUT and, ultimately, to designing more effective implementation strategies in order to address the current delays in global eHealth adoption. Methods: We conducted a quantitative survey of 430 Jordanian patients, utilizing structural equation modeling (SEM) to process the empirical data. Specifically, we applied an SEM two-step approach that involved (a) evaluating the model-data fit through a review of the measurement model(s) and common method bias; and (b) analyzing the structural model. Results: Our findings confirm that the proposed patients’ value scale is valid and reliable. Its five dimensions (hedonistic motivation, utilitarian motivation, social value, ethical public value, and public trust value) significantly correlate with patients’ public value, and the latter directly affects their use of eHealth apps, with habits mediating this relationship. Among the dimensions, hedonistic motivations tend to be prioritized over utilitarian ones. Ethical and trust values also play an essential role, particularly in how health technology handles patients’ data and upholds their dignity and self-esteem. Conclusions: This study highlights the holistic nature of eHealth adoption by patients and the crucial role of public values in their use behavior. It provides useful insights for policymakers and developers.

Behavioral science confronts the issue of how people’s behaviors differ from what they intend to do. However, current models, such as the theory of planned behavior, are insufficient to account for contextual influences and interdisciplinary effects, especially in the case of modern social phenomena. The majority of studies concentrate on single domains (e.g., health and consumer behavior) and employ manual coding schemes, overlooking essential thematic relationships. This research highlights the necessity for integrative frameworks that attempt to analyze why intentions fail to be realized in complex settings such as climate change and digitalization. The primary objectives of this research are to identify and operate dominant and emerging thematic trends in intention–behavior literature in a time series from 1979 to 2025 and to analyze and investigate the effects of publication index status and citation patterns on scholarly impact. This study uses structural topic modeling (STM) alongside bibliometric analyses to identify themes and correlations in intention–behavior research. STM employs generalized linear models to include document‐level metadata, allowing for the discovery of related topics and the key factors influencing the development of the literature. Data collection was initially performed on February 20, 2025, through the Web of Science database, using studies that were identified following PRISMA guidelines, reviewed, and considered relevant. The initial records numbered 5350. Significant thematic trends were found to define, and key psychological mechanisms to explain the intention–behavior gap were identified. The study also found that the determinants of publication index status and citation trends play important roles in establishing the discipline’s fate and the impact of intention–behavior literature. Based on these findings, the study highlights how strong thematic links in intention–behavior research can inform cross‐domain interventions—such as integrating physical activity and organic food campaigns or leveraging sustainable tourism to promote ethical consumption—by targeting shared psychological drivers like health identity and self‐image. In future research, the intention–behavior gap should be investigated across different disciplines and contexts and with longitudinal and experimental designs to take advantage of the psychological and contextual factors that affect behavior.

Type of the article: Research Article AbstractIn an era of persistent economic uncertainty and supply chain disruptions, organizational resilience has emerged as a critical determinant of long-term sustainability, particularly in rapidly evolving industries such as food manufacturing. Emotional intelligence (EI) has been identified as a key driver of resilience, enabling individuals and organizations to better adapt, recover, and grow in the face of challenges. This study aims to investigate the impact of EI on organizational resilience and to assess the moderating role of transformational leadership in this relationship within the context of Jordan’s yogurt industry. A quantitative research design was employed, and data were collected in 2024 from 768 employees working across three leading yogurt manufacturing companies in Jordan. Structural Equation Modeling (SEM) using Smart PLS was applied to analyze the relationships among the variables. The results demonstrate that all four dimensions of EI, self-awareness, self-regulation, social awareness, and relationship management, exert a statistically significant positive effect on organizational resilience (p < 0.001). Furthermore, transformational leadership was found to moderate these relationships significantly, enhancing the strength of EI’s influence on resilience outcomes. These findings offer robust empirical support for the integration of EI and leadership development in resilience-building strategies. The study provides sector-specific insights that contribute to the theoretical advancement of resilience frameworks and offers actionable guidance for organizational leaders seeking to enhance adaptability in dynamic and uncertain environments.