Journal of Business and Management Trends in Asia

The Second Curve in Digital Transformation: A Study on Business Model Innovation through Highway Maintenance Data Assetization

2026-06-30T11:49:14+07:00

Against the backdrop of deep integration between digital economy and transportation infrastructure, highway maintenance data are evolving from internal management tools into tradable and financeable strategic assets. However, existing research lacks systematic explanations of how highway transportation enterprises cultivate the second curve through maintenance data assetization. This study integrates resource-based theory, data lifecycle theory, and business model innovation theory to construct a “resource foundation—technical transformation—model reconstruction” three-dimensional analytical framework, and proposes a three-stage evolution model: internal empowerment, external transaction, and capitalization operation. Through a dualcase study of Gansu Provincial Highway Construction Group and Jilin Provincial Highway Group, findings reveal that: (1) Highway maintenance data meet VRIO criteria, with organizational support serving as the key prerequisite; (2) The critical transition condition from internal empowerment to external transaction is scenario definition and productization capability, while the transition to capitalization operation requires market validation and financial instrument embedding; (3) Data assetization drives business model innovation by reshaping value proposition, value creation and delivery, and value capture; (4) Maintenance data and traffic data exhibit two differentiated assetization pathways: “depth mining” and “breadth coverage.” This study operationalizes the second curve theory into an analyzable three-stage evolution model, extending the application of resource-based view in the context of data assets.

The Relationship Between Health Behaviors and Psychological Resilience Among College Students: The Mediating Role of Self-Efficacy in the Context of the “Healthy China 2030” Initiative

2026-06-30T23:56:52+07:00

Within the policy framework of the “Healthy China 2030” initiative, promoting healthy lifestyles and psychological well-being among college students has become an important public health objective. This study aimed to examine the relationship between health behaviors and psychological resilience among college students and to explore the potential psychological role of self-efficacy in this relationship.

A cross-sectional survey was conducted among 1,324 college students recruited from Chinese universities. Participants completed standardized questionnaires measuring health behaviors (including sleep, diet, and exercise), psychological resilience, and self-efficacy. Descriptive statistics, correlation analysis, and regression analyses were performed to examine the relationships among the variables.

The results indicated that health behaviors were significantly and positively associated with psychological resilience (r = .543, p < .001). Regression analysis further showed that health behaviors significantly predicted psychological resilience (β = .543, p < .001). In the multiple regression model, self-efficacy emerged as the strongest predictor of psychological resilience (β = .567, p < .001), followed by health behaviors (β = .273, p < .001). Gender showed a small but significant effect, whereas health status was not a significant predictor.

These findings suggest that healthy behavioral patterns may play an important role in promoting psychological resilience among college students, and that self-efficacy may function as a key psychological resource in this process. The study provides empirical support for health promotion strategies that integrate lifestyle interventions with psychological resource development in the context of the “Healthy China 2030” initiative.

Ai-Empowered Finance Discipline Construction in Private Universities:An empirical Study on Perceived Value, Organizational Trust and Adoption Intention

2026-06-30T23:35:19+07:00

Against the backdrop of accelerating digital transformation in higher education, the enabling pathways and adoption mechanisms of artificial intelligence (AI) technologies for finance discipline construction in private universities warrant in-depth investigation. Grounded in the Value-based Adoption Model (VAM) and organizational trust theory, this study constructs a triadic analytical framework comprising perceived value, organizational trust, and adoption intention. Drawing on 387 valid questionnaires collected from faculty, administrators, and students across 17 private universities in China, and employing multiple linear regression analysis, this research systematically examines the influence mechanisms of core variables on AI tool adoption intention. Results indicate that perceived value (β = 0.412, p < 0.01) is the strongest predictor of AI adoption intention, while organizational trust (β = 0.287, p < 0.01) also exerts a significantly positive effect. Together, these two variables account for 63.4% of the variance in adoption intention (adjusted R² = 0.634). Further analysis reveals that organizational trust partially mediates the relationship between perceived value and adoption intention. The findings illuminate the adoption dynamics in private university contexts: in environments with relatively limited institutional safeguards, organizational trust serves as a critical boundary condition shaping adoption decisions. The generalizability of these findings across different university types warrants future investigation through comparative samples including public universities. This study offers both theoretical foundations and practical guidance for private universities advancing AI integration in finance discipline construction.

Social Embeddedness and Behavioral Habit in WeChat Pay Adoption Among Guangxi University Students

2026-06-30T23:29:21+07:00

This study investigates the determinants of WeChat Pay usage intention among university students in Guangxi, China, focusing on three core constructs: social influence, price value, and habit. Using survey data from 412 valid responses and multiple linear regression analysis, the results demonstrate that habitual use (β = 0.536, *p* < 0.01) is the strongest predictor of usage intention, confirming the dominance of automated behavioral patterns in payment decisions. Price value (β = 0.108, *p* < 0.05) and social influence (β = 0.103, *p* < 0.01) also exhibit significant but comparatively weaker effects. Contrary to conventional technology adoption models, performance expectancy and effort expectancy show no statistically significant impact, suggesting that mobile payment has transitioned from an "innovative technology" to a "daily utility" among this demographic. These findings provide empirical evidence for understanding payment behaviors in academic settings and offer practical implications for optimizing campus payment services.

Keywords: WeChat Pay, Social Influence, Price Value, Habit, Usage Intention.

The Impact Mechanism of Short Video Usage Intensity on Cognitive Function of College Students in Shanghai: Based on the Moderating Effect of Media Literacy

2026-06-30T23:18:37+07:00

This study focuses on college students in Shanghai,aiming to explore the impact mechanisms of short video usage intensity on their cognitive functions(attentional stability,memory processing,and cognitive depth),reveal the moderating effect of knowledge-acquisition-oriented content preferences,and construct a multi-level collaborative management strategy.The findings provide theoretical basis and practical references for guiding college students to use short videos rationally and promote healthy cognitive development.Using questionnaire surveys,data from students at multiple universities in Shanghai were collected.SPSS 26.0 was employed for correlation analysis and regression testing to systematically verify the relationships and moderating effects among variables.The results show that short video usage intensity is significantly negatively correlated with college students'cognitive functions(p<0.01),with high-intensity usage exacerbating attentional dispersion.Knowledge-acquisition-oriented content preferences can effectively buffer these negative effects.Based on these findings,a"university-family-society"collaborative management framework was constructed to optimize college students'short video usage behaviors and cognitive development.