Background: With the increasing proportion of older adults in the global population, the negative effects of cognitive aging on daily functioning and mental health have attracted growing attention from researchers. Objective: This study aimed to explore the antecedent variables of cognitive aging and to clarify their potential causal mechanisms based on previous research. Methods: A literature search was conducted in Google Scholar following the PRISMA guidelines proposed by the Joanna Briggs Institute (JBI). Two researchers independently performed study screening, data extraction, and quality assessment. The research methods, findings, and conclusions of the included studies were then systematically reviewed. Results: A total of eight studies published after 2010 were included in the final analysis. All studies adopted longitudinal designs using latent growth models (LGM). The findings suggest that cognitive aging typically begins around the age of 50–55. Factors such as social isolation, cohabitation status, depression, social participation, lifestyle, years of education, income level, leisure activities, and midlife body mass index were found to be associated with cognitive aging and may play protective roles. Conclusion: These findings highlight several potential protective factors that may help mitigate or delay the progression of cognitive aging.

This study aims to elucidate the mechanisms through which service robot anthropomorphism and employee self-efficacy influence human-robot collaborative performance in the service industry. A conceptual model was developed in which perceived usefulness, perceived ease of use, perceived competence, and collaborative intention operate as multiple mediators, clarifying how robot-assisted collaboration enhances performance. Using structural equation modeling, we analyzed data from 418 valid questionnaires collected from employees in the hospitality and catering sectors. The results indicate that both service robot anthropomorphism and employee self-efficacy significantly enhance employees' perceptions of usefulness, ease of use, and competence. These perceptions, in turn, positively affect collaborative intention, which subsequently improves collaborative performance. Moreover, perceived usefulness, ease of use, and competence jointly mediate the relationships between the antecedent variables (anthropomorphism and self-efficacy) and collaborative performance. In summary, the findings elucidate a sequential mediation pathway: robot anthropomorphism and employee self-efficacy boost key perceptions, thereby fostering collaborative intention and ultimately enhancing performance. The study provides theoretical insights into the psychological mechanisms through which anthropomorphic design features and employee self-efficacy shape effective human-robot collaboration and offers practical guidance for the successful integration of service robots into service operations.

Purpose This study investigates the relationship between artificial intelligence (AI)-related system characteristics and two interpersonal states commonly associated with effective teamwork, namely employee well-being and mutual trust. While generative AI has shown potential to improve organizational performance, its specific effects on internal team-based working relationships remain underexplored. Design/methodology/approach A theoretical model is developed to explore the influence of three antecedent variables, quality of information, system quality and generative AI use, on collaboration within teams. Collaboration is operationalized using two key constructs: employee well-being and mutual trust. The model is empirically tested using data from a large-scale survey of 208 professionals working in team-based environments. Data analysis is conducted using partial least squares structural equation modeling (PLS-SEM). Findings The results confirm that all three antecedent variables positively influence team-based collaboration dynamics. Specifically, the use of generative AI chatbots, such as ChatGPT, is shown to enhance employee well-being and foster mutual trust within teams, both of which act as interpersonal enablers of team collaboration. These outcomes suggest that the integration of high-quality AI tools can meaningfully support collaborative processes in professional settings. Originality/value This study contributes to the emerging field of generative AI research by shifting the focus from performance outcomes to collaboration mechanisms within teams. It offers practical implications for managers seeking to optimize teamwork in AI-enabled environments, including investing in system quality, redesigning workflows to integrate AI effectively and promoting a culture of trust and transparency around AI adoption.

This study analyzes the effects of Brand Attachment, Brand Characteristics, Service Quality, Servicescape, and Food and Beverage Quality on Revisit Intention, mediated by Customer Brand Attitude and Customer Satisfaction. The sample consists of 500 Generation Z consumers from five coffee shop brands in Jakarta. Data were analyzed using Structural Equation Modeling (SEM) with AMOS. The findings show that Brand Attachment and Brand Characteristics significantly influence Customer Brand Attitude, while Service Quality and Food and Beverage Quality positively affect Customer Satisfaction. Both mediating variables significantly influence Revisit Intention and mediate the relationships between antecedent variables and Revisit Intention. In contrast, Servicescape does not significantly affect Customer Satisfaction among Generation Z consumers. This study contributes to service marketing literature by integrating branding and quality perspectives. However, the cross-sectional design and geographic focus limit generalizability.

This study investigates the effects of consistency, perceived value, customer service, and personalization on customer loyalty through omnichannel customer experience in the context of Garuda Indonesia, a leading full-service airline in Southeast Asia. A quantitative explanatory research design was employed using a structured questionnaire distributed to 150 passengers who had interacted with at least two service channels within the past 12 months. Data were analyzed using SPSS through validity and reliability testing, multiple linear regression, and mediation analysis. The findings reveal that all four antecedent variables—consistency, perceived value, customer service, and personalization—significantly enhance omnichannel customer experience. Furthermore, omnichannel customer experience is found to positively influence customer loyalty and mediate the relationship between each antecedent variable and loyalty. These results highlight the critical role of integrated, consistent, and personalized service delivery across digital and physical channels in shaping passengers’ loyalty toward full-service airlines. The study contributes to the growing body of omnichannel service research and offers strategic implications for airline managers seeking to strengthen customer engagement in an increasingly digitalized travel environment.

Psychological perception of water scarcity, despite its strong correlation with water-saving behavior, has not been explored within major behavioral theoretical frameworks. This study develops an extended Theory of Planned Behavior (TPB) model incorporating psychological perception of water scarcity as an antecedent variable. This research paper investigates how scarcity perception impacts water-saving behavior by examining three mediating mechanisms: attitude, subjective norm, and perceived behavioral control. Additionally, it assesses the extended model's incremental explanatory power over the original model. Using data taken from China General Social Survey, this study uses structural equation model for path analysis and Bootstrap methods to test mediating effects. According to the findings, perceived scarcity is a significant predictor of all three main constructs of the Theory of Planned Behavior. The attitude path makes the biggest contribution as all three chained mediating paths are significant. The extended model demonstrates superior fit and predictive accuracy. This study establishes four specific objectives which include clarifying the theoretical positioning of perceived scarcity as a precursor variable within the behavioral model; outlining its specific psychological pathways to stimulate water-saving behavior; and providing targeted evidence for water-saving interventions. Policymakers must focus on effort on developing strategies that shape attitudes and enhance people’s self-efficacy to promote an overall shift residential water-saving behaviors.

Intangible cultural heritage products (ICHPs) function as an important medium through which regional cultural values are communicated within tourism consumption, thereby supporting the sustainability of cultural heritage practices. However, existing research provides limited insight into the psychological mechanisms underlying region-specific purchase intentions. To address this gap, this study extends the Theory of Planned Behavior (TPB) by incorporating cultural identity and consumer knowledge as antecedent variables and product scarcity as a moderating factor, with the aim of explaining tourists’ purchase intention toward Bashu ICHPs in China. Data were collected from 429 tourists and analyzed using structural equation modeling and hierarchical regression techniques. The results indicate that cultural identity and consumer knowledge indirectly influence purchase intention through attitudes and subjective norms, whereas perceived behavioral control emerges as the strongest direct predictor of purchase intention. In addition, product scarcity significantly strengthens several relationships between the antecedent variables and the core TPB components, thereby amplifying culturally and cognitively driven decision-making processes. Overall, this study deepens theoretical understanding of consumer behavior within regional cultural heritage systems and provides practical insights for the sustainable development and marketing of Bashu ICHPs.

Employee engagement has become a central concept in Human Resource Management (HRM) research due to its role in enhancing employee performance and organizational sustainability. This study employed a content analysis approach to review research trends related to employee engagement, particularly those examining work-life balance and leadership perspectives. A total of 50 peer-reviewed studies published between 2014 and 2025 were analyzed based on research design, antecedent variables, organizational context, theoretical frameworks, and methodological approaches. The findings indicate a significant increase in employee engagement research in recent years, with quantitative cross-sectional designs dominating the literature. Work-life balance and servant leadership emerged as the most frequently examined antecedents of employee engagement, while employee performance remained the primary outcome variable. Job Demands–Resources (JD–R) Theory was identified as the dominant theoretical framework. Based on the findings, this study proposes methodological and contextual recommendations for future employee engagement research.

The adoption of Accounting Information Systems (AIS) in Indonesia remains uneven between urban and rural areas, reflecting disparities in digital competence, social conditions, and infrastructural readiness. Addressing this gap, this study extends the Technology Acceptance Model (TAM) by incorporating digital literacy, trust, and social influence, while explicitly examining the moderating role of geographical context (urban versus rural). A quantitative survey method was employed, collecting data from 300 AIS users, comprising 150 respondents from urban areas and 150 from rural areas. The data were analyzed using partial least squares structural equation modeling (PLS-SEM) and multi-group analysis. The research model positions digital literacy, trust, and social influence as antecedent variables; perceived ease of use and perceived usefulness as mediators; behavioral intention as an intervening variable; and actual system usage as the outcome variable. The findings indicate that behavioral intention is a strong predictor of actual AIS usage in both urban and rural contexts. However, significant contextual differences emerge: digital literacy and trust positively influence perceived usefulness in urban areas, while these relationships are not significant in rural settings. This result highlights the moderating role of geographical context in shaping AIS acceptance patterns. This study contributes theoretically by extending TAM through a contextualized urban–rural perspective and empirically demonstrating the heterogeneous effects of key antecedents across geographical settings. From a policy perspective, the findings suggest that strategies to promote AIS adoption should be context-sensitive, with greater emphasis on digital capability development and trust-building mechanisms in rural areas.

This study investigates how Word of Mouth, service quality, and brand image influence B2B customer loyalty at As-Syifaa Pharmacy in Majalengka, with customer satisfaction acting as a mediating variable. A quantitative approach was applied using the SEM-PLS method, drawing on data from 300 purposively selected customers. The analysis included measurement of validity and reliability, followed by structural model testing to identify both direct and indirect relationships among variables. The findings reveal that Word of Mouth, service quality, and brand image each play a meaningful role in enhancing customer satisfaction, which in turn becomes the strongest predictor of customer loyalty. Satisfaction was also found to mediate the effects of the three antecedent variables, either fully or partially, highlighting its central role in shaping long-term business relationships. These results indicate that building B2B customer loyalty requires more than consistent operational performance; it also depends on maintaining a credible brand reputation and fostering positive relational communication within the business network. Based on these insights, the study recommends strengthening service standards, reinforcing brand consistency, and managing interpersonal communication to support sustainable loyalty among B2B partners.

Abstract Although refugees are often perceived as a burden to the socioeconomic fabric in some places, entrepreneurship offers a promising avenue for refugees to participate in the economy, secure decent work, and achieve self-reliance. However, refugee entrepreneurship is largely seen as necessity-driven and thus limited personal agency in refugees’ entrepreneurial behavior, which has negative connotations for persistence and success. This paper demonstrates the role of prior entrepreneurial experience in boosting refugees’ personal entrepreneurial agency (represented by entrepreneurial intentions and implementation intentions) through its effects on the antecedents specified in the theory of planned behavior (TPB). The study uses survey data from 404 refugees in Uganda. The participants were drawn from three large refugee settlements. A serial mediation analysis was conducted using PROCESS Macro in SPSS. The results indicate prior entrepreneurial experience positively predicts the TPB antecedent variables, suggesting that entrepreneurial experience is essential for a positive entrepreneurial attitude, subjective norm, and a strong perceived behavioral control (PBC) among refugees. These TPB antecedent variables mediated the effects of prior entrepreneurial experience on entrepreneurial intentions and implementation intentions. Significant double mediation paths were mainly observed via entrepreneurial attitudes and intentions, as well as via perceived behavioral control and entrepreneurial intentions. The results indicate that prior experience is a vital resource that can be a foundation for successful refugee entrepreneurship promotion. Thus, active learning approaches that boost experience acquisition can be useful in entrepreneurship training and education interventions. Arrangements such as innovation hubs, apprenticeships, and internships for refugees can be vehicles for active and experiential learning. The study extends the TPB by integrating prior experience as an antecedent of entrepreneurial attitudes, subjective norm, PBC, and implementation intention.

This study aims to elucidate the pathways through which behavioral intention for pickleball participation is formed among the general public (i.e., individuals excluding professional or competitive athletes) and to analyze the decision-making mechanisms underlying participation. Grounded in the Theory of Planned Behavior (TPB), this research introduces exercise motivation as an antecedent variable. Based on a survey of 315 pickleball participants, it employs a mixed-methods approach combining Structural Equation Modeling (SEM) and fuzzy-set Qualitative Comparative Analysis (fsQCA) to empirically examine the influencing factors, pathways, and causal configurations of participation intention. (1) Exercise motivation significantly and positively influences behavioral intention; (2) Attitude and perceived behavioral control fully mediate the relationship between exercise motivation and behavioral intention, whereas the mediating role of subjective norm is not significant; (3) The inclusion of exercise motivation effectively enhances the explanatory power of the extended TPB model in predicting behavioral intention; (4) fsQCA identifies two distinct configurations sufficient for triggering high behavioral intention, with a positive attitude serving as a core condition in both. This study broadens the application boundaries of TPB in the context of sports participation and enriches the research on the psychological mechanisms of public participation in pickleball. Using the case of China, it provides theoretical support and practical guidance for promoting and popularizing pickleball in regions where the sport is in its early stages of development.

Abstract Understanding how snowmelt is partitioned into different hydrologic flowpaths/storages—and how this partitioning varies over time—is essential for predicting water availability and quality under climate variability. In this study, we examine the time‐variance of snowmelt partitioning patterns (SPP) in response to interannual variations in antecedent (Fall) rainfall before snowmelt seasons, across two snow‐dominated catchments in Canada and Sweden with contrasting geologic and topographic features. Using integrated subsurface–surface flow and transport modeling, combined with observational data, we simulate the partitioning of snowmelt into shallow flowpath, deep flowpath, evapotranspiration, and long‐term storage. To generalize our findings beyond the two case studies, we design a suite of virtual experiments that systematically vary catchment slope and the extent of the hydraulic conductivity's vertical and lateral heterogeneity. Results show that lateral heterogeneity in conductivity mediates the sensitivity of snowmelt partitioning to interannual variations in antecedent rainfall. While laterally homogeneous catchments display minimal sensitivity of snowmelt partitioning pattern to wet or dry Fall rainfall conditions, catchments with heterogeneous lateral structure store a significantly larger portion of snowmelt and reduce snow‐sourced shallow flow contributions in years with high pre‐snow rainfall than years with low pre‐snow rainfall. In contrast, while slope and vertical conductivity architecture govern SPP, they play a limited role in mediating SPP's temporal sensitivity to antecedent rainfall variability. These findings reveal that subsurface structure—including the extent of lateral subsurface heterogeneity—modulates the influence of climate variability on snowmelt partitioning and catchment hydrologic function. This has implications for predicting streamflow responses, groundwater recharge, and solute transport under changing climate regimes, and highlights the importance of representing time‐variable hydrologic behavior in hydrologic models.

This study reveals the relationship among emotional intelligence, internal and external motivations, and creative behavior to cultivate creative behavior of college students majoring in fine art in Jiangsu Province, China, and explores the mediating effect of internal and external motivations in the influence of emotional intelligence to predict creative behavior. The subjects of the study are 847 people. To find out mediating effect of internal and external motivations between emotional intelligence and creative behavior, simple regression analysis and multiple regression analysis are performed. There is a positive(+) correlation among emotional intelligence, internal and external motivations, and creative behavior. For college students majoring in fine art, each internal and external motivation partially mediate the influence of emotional intelligence to predict creative behavior. In order to improve the creative behavior of college students majoring in fine art, it is necessary to increase emotional intelligence, internal and external motivations by each student. In future studies, searching for variables such as personality traits, diffuse thinking levels, risk sensitivity levels, and self-efficacy as antecedent variables that affect creative behavior will also help cultivate creative behavior.

The escalating need for sustainable urban mobility solutions amid concerns over climate change and fuel emissions makes the adoption of E-Bikes a critical area of study. This research investigates the psychological and cognitive factors that drive consumer Intention to Purchase E-Bikes (IPTEB), specifically examining how Environmental Awareness (EA), Consumer STEM Literacy (SL), and Perceived Technological Innovativeness (PTI) influence the perception of functional utility, operationalized as Perceived Technical Benefits (PTB). A quantitative study employing a cross-sectional design utilized Structural Equation Modeling (PLS-SEM) on data collected from 273 prospective E-Bike consumers in Multan, Pakistan. The structural model demonstrated high predictive power, explaining over 67% of the variance in the key endogenous constructs. All four hypothesized paths were supported, confirming that PTB is the overwhelming predictor of IPTEB (β= 0.820). Crucially, the antecedent variables influencing PTB ranked as follows: PTI (β= 0.373) was the strongest, closely followed by SL (β= 0.319), with EA exerting the weakest influence (β= 0.207). These findings suggest that while environmental concern provides motivation, the purchasing decision is fundamentally driven by rational, technology-based evaluations of product superiority, necessitating that manufacturers shift marketing strategy to focus on technical education and functional performance to maximize perceived value and accelerate adoption.

This study evaluates the performance of a proposed model based on the Technology Acceptance Model (TAM) to forecast students' opinions of statistics education improved by advanced technology. Using a sample of 379 undergraduate students from Malaysia's East Coast, chosen by simple random sampling, this study examined six main constructs: social influence, self-efficacy, perceived usefulness, perceived ease of use, attitude toward using, and behavioral intention. The measurement model was validated using confirmatory factor analysis (CFA), which found that each construct satisfied the necessary thresholds for model fit, dependability, and validity. Students' attitudes toward using technology were found to be influenced by perceived usefulness, social influence, self-efficacy, and perceived ease of use, according to a structural model examined using Covariance-Based Structural Equation Modeling (CB-SEM). Attitude, perceived ease of use, social influence, and self-efficacy significantly affected behavioral intention; the direct path from perceived usefulness to behavioral intention was not statistically significant. Four major mediation effects were also found, which emphasizes the importance of attitude in connecting the antecedent variables to behavioral intention. Thus, by using the digital education for statistics course, the model under test is also sufficient to match the present development and will be helpful for future studies.

ABSTRACT The aim was to explore the relationship between moral injury symptoms, individual and military potential antecedent variables, and mental health scales. Responses were obtained from 504 Swedish military veterans. Findings showed that moral injury symptoms were modestly related to emotional stability and combat exposure. Moral injury symptoms were moderately strongly related to stress-related physical and psychological symptoms and strongly related to PTSD indication. The results suggest a strong conceptual overlap between moral injury symptoms and PTSD indication. The association between moral injury symptoms and stress-related physical and psychological symptoms was discussed from an intervention perspective. The study also adds to previous research in that the sample had more favorable mental health, when measured by stress-related symptoms and PTSD indication. Possible reasons for this are strict selection criteria and a lower frequency and intensity of combat exposure.

To explore the formation mechanism of college students' adoption intention of generative artificial intelligence (GAI)—i.e., the dynamic paths of direct/indirect effects of antecedent variables and interaction effects of moderating variables—this study integrates and extends the traditional Technology Acceptance Model (TAM) and Unified Theory of Acceptance and Use of Technology 2 (UTAUT2). The integration is necessary because traditional TAM focuses on rational cognition, while UTAUT2 lacks the emotional dimension in educational scenarios and the integration of multi-level contexts. A theoretical framework incorporating the “individual-family- institution-region” four-dimensional moderating and collaborative perspective was constructed, and an empirical analysis was conducted using Partial Least Squares Structural Equation Modeling (PLS-SEM). A multi-stage stratified sampling method was adopted, with a sample of 842 college students from five universities in eastern and western China. The scales for UTAUT2 core variables and extended TAM variables in the questionnaire were adapted from previous studies that had undergone reliability and validity verification. Reliability was tested using Cronbach's α and Composite Reliability, while validity was tested using Average Variance Extracted, the Fornell-Larcker criterion, and Heterotrait-Monotrait Ratio. Results showed that the measurement model had acceptable reliability and validity, with good explanatory power (R 2 = 0.743) and predictive validity of the structural model. Specifically, perceived comfort (β = 0.112, p < 0.005), perceived security (β = 0.109, p < 0.05), and emotional dependence (β = 0.497, p < 0.005) all exerted positive effects on perceived usefulness and perceived ease of use. Performance expectancy (β = 0.216, p < 0.005), social influence (β = −0.064, p < 0.05), facilitating conditions (β = 0.143, p < 0.005), and perceived ease of use (β = 0.469, p < 0.005) directly drove adoption intention, whereas the direct effect of perceived usefulness was not significant (β = −0.031, p = 0.523). This result challenges the core assumption of TAM—which emphasizes “priority of rational utility” and confirms the “de- instrumentalization” characteristic of generative AI adoption, meaning user decisions rely more on emotional experience and interactive fluency.Regarding moderating effects: gender negatively moderated the relationship between performance expectancy and adoption intention (β = −0.207, p < 0.05); family structure negatively moderated the relationship between habit and adoption intention (β = −0.228, p < 0.05); university type positively moderated the relationship between performance expectancy and adoption intention (β = 0.251, p < 0.05); and regional differences negatively moderated this relationship (β = −0.251, p < 0.05).In practice, it is suggested that educational authorities strengthen the construction of digital infrastructure in western universities, universities develop differentiated guidance strategies for students majoring in humanities/social sciences and science/engineering, and developers optimize emotional interaction design. This study provides theoretical support for context-adapted strategies for the educational application of generative AI.

The concept of fear of cancer recurrence (FCR) is defined and analyzed. Methods: A systematic search was conducted for relevant literature on fear of cancer recurrence in Chinese databases, including CNKI, WanFang, Weipu, and the China Biomedical Literature Service System, as well as in English databases such as PubMed and Web of Science. Rodgers’ evolutionary concept analysis method was employed to analyze the selected literature. Results: Rodgers’ evolutionary concept analysis revealed that the concept of FCR encompassed psychological distress characteristics that dynamically evolved with disease manifestations. Antecedent variables included demographic factors, disease and treatment-related factors, psychological factors, and family and social influences. The consequences of this fear involved an exacerbation of negative emotional burdens among cancer patients, a detrimental impact on their health-related quality of life, and the emergence of maladaptive negative behaviors. Conclusion: FCR is a multidimensional and dynamic concept. Healthcare staff needs to incorporate FCR into clinical screening processes to improve the early identification of fear of cancer recurrence in cancer patients.

County-wide distributed rooftop photovoltaic (DRPV) systems, as an emerging form of renewable energy development, constitute a critical component for the low-carbon energy transition and carbon reduction. However, the pilot implementation in China has faced many challenges, with resistance from rural residents being a key issue requiring urgent resolution. This study aimed to investigate the underlying factors influencing their participation in DRPV and identify the key determinants. The topic modeling and evolutionary analysis were first conducted based on the multi-platform online textual data. The theoretical model was constructed combining the antecedent variables identified by the online textual analysis and the classic Unified Theory of Acceptance and Use of Technology (UTAUT) framework. This model was validated through questionnaire surveys and structural equation modeling. The results revealed that facilitating conditions were the core determinant of rural residents’ participation in DRPV systems. Government-led safeguard mechanisms served as the primary enhancer of perceived convenience. Additionally, effort expectancy (0.301), performance expectancy (0.253), and social influence (0.424) all positively correlated with participation intention, with social influence exhibiting the strongest impact. Notably, rural residents equally prioritize environmental benefits and economic returns from DRPV systems. These findings provided policy insights for promoting DRPV projects in the future.