Search Results (48)

Objective: This study investigates the longitudinal reciprocal relationships among physical exercise (PE), executive function (EF), and subjective well-being (SWB) in ethnic minority college students in China, with the aim of providing theoretical and practical guidance for their psychological and cognitive development. Method: A three-wave longitudinal design was employed over a nine-month period to collect data on PE, EF, and SWB from 482 ethnic minority college students in Shaanxi Province, China (M age = 20.3 years, 63% female). Data were analyzed using a random-intercept cross-lagged panel model (RI-CLPM), and multigroup analysis (MGA) was used to examine the moderating effects of gender, family ethnic composition, and residential area. Results: The study revealed significant positive correlations among PE, EF, and SWB at the between-person level. At the within-person level, the variables exhibited temporal stability, with earlier levels significantly predicting later levels, indicating cumulative effects. Key cross-lagged analyses unveiled significant dynamic reciprocal relationships among the three variables: earlier PE positively predicted subsequent EF and SWB, earlier EF positively predicted subsequent PE and SWB, and earlier SWB positively predicted subsequent EF. Importantly, these dynamic pathways and overall relationships were consistent across gender, family structure, and residential area, indicating robustness within the studied population. Conclusion: This study highlights the dynamic, reciprocal relationships among PE, EF, and SWB. Consequently, promoting physical activity and culturally sensitive interventions for ethnic minority college students is crucial for enhancing their psychological resilience and well-being. This research offers valuable insights for policymakers and educators. Full article

This study explores residents’ perceptions of tourism development with a particular emphasis on the economic dimension of sustainability, focusing on how economic benefits, costs, and related factors shape local support in Serbia, Kazakhstan, and Hungary. By analyzing perceived advantages and disadvantages, the study aims to assess the extent of local support for tourism and the moderating effects of travel frequency and contact with tourists. In parallel, tourist arrival forecasts for 2025–2030 provide context on the anticipated dynamics of tourism growth, with Hungary showing the highest projected increase. Using advanced statistical techniques, including Multi-Group Analysis (MGA), structural equation modeling (SEM), and machine learning methods, key factors driving tourism support were identified. Positive perceptions of economic benefits and cultural identification significantly enhance support for tourism, while perceived costs act as inhibitors. The application of Random Forest and XGBoost (version 1.7.x) models improved predictive accuracy, while K-means clustering and principal component analysis (PCA) clarified relationships among constructs. The findings provide actionable insights for developing sustainable tourism strategies that prioritize economic outcomes and community engagement, particularly in culturally and economically diverse settings. Full article

With the rapid development of metaverse technology in the marketing field, it has become increasingly important to understand consumer purchase intentions for AI Brand Endorsers (AIBEs) within this digital environment. Based on cognitive–affective–behavioral (CAB) theory, this study constructs a new theoretical framework to explore the key factors influencing consumer purchase intentions for AIBE-recommended products in the context of the metaverse. We conducted an online survey with 302 Generation MZ consumers who have purchasing experience, employing Partial Least Squares Structural Equation Modeling (PLS-SEM) for in-depth data analysis and model evaluation. Additionally, we performed Multi-Group Analysis (MGA) to reveal differences among various occupations and generations. The findings indicate that attractiveness (ATT), anthropomorphism (ANT), and interactivity (INT) significantly influence hedonic motivation (HM) and social presence (SP). Furthermore, authenticity (AUT) positively affects both SP and trust in AIBEs (TAI). Consumer purchase intention (PI) is significantly impacted by SP but is not directly influenced by HM and TAI. Notably, technology readiness (optimism and innovativeness) positively and significantly influences consumer PI but does not alter the potential moderating effects of HM, SP, and TAI. This study not only broadens and deepens the application of CAB theory but also elucidates the potential development of AIBEs in future metaverse research, providing practical implications and guidance for marketers to enhance consumer purchase intentions and boost product sales. Full article

This paper examines the uptake of AI-driven fraud detection systems among financial institutions in the UAE and Qatar, with a special focus on trust, transparency, and perceptions of fairness. Despite the promise of AI operations in identifying financial anomalies, unclear decision-making processes and algorithmic bias constrain its extensive acceptance, especially in regulation-driven banking sectors. This study uses a quantitative strategy based on Partial Least Squares Structural Equation Modeling (PLS-SEM) and Multi-Group Analysis (MGA) of survey responses from 409 bank professionals, such as auditors and compliance officers. This study shows that transparency greatly enhances trust, which is the leading predictor of AI uptake. Fairness perception mediates the negative impacts of algorithmic bias, emphasizing its important role in establishing system credibility. The analysis of subgroups shows differential regional and professional variations in trust and fairness sensitivity, where internal auditors and highly AI-exposed subjects are found to exhibit higher adoption preparedness. Compliance with regulations also emerges as a positive enabler of adoption. This paper concludes with suggestions for practical implementation by banks, developers, and regulators to align AI deployment with ethical and regulatory aspirations. It recommends transparent, explainable, and fairness-sensitive AI tools as essential for promoting adoption in regulation-driven sectors. The findings provide a guide for promoting responsible, trust-driven AI implementation in fraud detection. Full article

The increasing global emphasis on sustainability necessitates the integration of environmentally responsible practices within supply chains. This study explores the impact of green supply chain management practices (GSCMPs) on firm sustainable performance in Pakistan’s manufacturing and service industries. Unlike prior research, which primarily focuses on the direct impact of GSCMPs, this study advances knowledge by incorporating green technological innovation (GTI) and green managerial innovation (GMI) as mediators and green organizational culture (GOC) as a moderator. The study looks at survey data from 480 industry professionals and uses partial least squares structural equation modeling (PLS-SEM) and multi-group analysis (MGA). It discovers that GSCMPs greatly enhance sustainability outcomes, especially when green innovations are used. Furthermore, the impact of GSCMPs is more pronounced in the manufacturing sector, emphasizing the role of regulatory pressures and technological advancements. This study makes a significant contribution to the literature by integrating post-pandemic sustainability challenges, highlighting industry-specific dynamics, and providing actionable strategies to enhance green supply chain adoption in emerging markets. The study provides applicable strategies for managers and policymakers to embed sustainability deeper into corporate strategies, ensuring resilience and competitive advantages in evolving global markets. Full article

Generative AI, particularly tools like ChatGPT, is reshaping higher education by enhancing academic engagement, streamlining processes, and fostering innovation. This study investigates the determinants of ChatGPT adoption intentions (CGPTAIs) by extending the Technology Acceptance Model (TAM) to include the mediating roles of perceived trust (PT) and perceived risk (PR). Using a quantitative cross-sectional design, the data from 435 participants were analyzed using structural equation modeling (SEM) to explore the relationships among the perceived ease of use (PE), perceived intelligence (PI), perceived usefulness (PUSE), PT, and PR. Τhe findings reveal that the perceived ease of use (PE) and perceived intelligence (PI) significantly drive adoption intentions, while perceived usefulness (PUSE) plays a limited role. PR fully mediates the relationship between PUSE and CGPTAI and partially mediates PE and PI, while PT fully mediates PUSE and partially mediates PE, but not PI. Multi-group analysis highlights demographic differences, such as age and prior AI experience, in adoption pathways. These results challenge traditional TAM assumptions, advancing the model to account for the interplay of usability, intelligence, trust, and risk. Practical insights are provided for fostering ethical and responsible ChatGPT integration, safeguarding academic integrity, and promoting equitable access in higher education. Full article

Rice is an important agricultural product in Vietnam; however, the rice industry faces several challenges, particularly weak linkages between farmers and enterprises. The Vietnamese government has introduced the Large Field Model (LFM) program to improve cooperation between farmers and agribusiness companies. Despite these efforts, its implementation remains limited, and contract violations are common. This study investigated the factors affecting relationship quality (RQ) and loyalty (LO) between farmers and agricultural companies in the LFM, focusing on comparing cooperative and non-cooperative participating farmers. Using the Partial Least Squares–Multi-Group Analysis (PLS-MGA) method, this study assessed the different effects of factors such as price satisfaction (PS), payment terms (PTs), and support policies (SPs) on RQ and LO among two groups. The findings indicated that RQ has a stronger influence on LO in farmers with cooperative participation than those who exhibit non-cooperative participation. PS was the most significant factor influencing RQ in both groups, whereas PT was influential only for cooperative participating farmers. SP did not significantly affect RQ in either group. Finally, agricultural companies and policymakers should strengthen partnership management in agricultural supply chains by addressing gaps in support policies, developing appropriate pricing strategies, being flexible in negotiating payment terms, and improving the legal framework related to contract enforcement. Full article

This study examines the impact of Customer-based Brand Equity (CBBE) on passengers’ Willingness to Pay Premium (WPP) for airline tickets, comparing low-cost and flag airlines. The research is prompted by the competitive nature of the industry and the need to comprehend passenger preferences, focusing on brand image, brand awareness, and service attributes as key variables influencing CBBE. The survey data collected from 489 recent travelers were analyzed through Partial Least Squares Structural Equation Modelling (PLS-SEM) and Multigroup Analysis (MGA), generating two quantitative analyses: first, the model was analyzed for airlines in general, and second, a multi-group analysis was performed to understand how the model behaves through price tiers. The findings indicate the significant influence of the chosen variables on both CBBE and WPP. A distinguishing factor lies in the differentiation between low-cost and flag airlines, revealing differing impacts on CBBE and WPP. This research contributes to the branding literature by expanding CBBE’s application to services, especially in the airline sector. It also builds on existing knowledge of WPP’s importance in service industries. Segmenting airline price tiers offers actionable insights for management strategies. In conclusion, this study augments the knowledge of CBBE, providing valuable managerial implications, guiding brand-tailored strategies to increase passengers’ willingness to pay premium. Full article

In many European countries the consumption of tropical fruit is constantly growing, and people are increasingly turning to diets rich in fruit and vegetables. In this context, mango is considered a super-food for its nutritional medium-high energy value. Produced mainly in developing countries, tropical fruits animate an interesting international market. Production in Mediterranean countries is also growing and is increasingly requested in European markets. The aim of this work is to investigate the factors that drive the inclination to purchase fresh mango and mango food and drinks in Italy and Brazil in order to observe consumer preferences in the two countries. The personal experiences, motivations and choices of consumers regarding fresh mango and mango-based products were taken into consideration. Through an online survey, a semi-structured questionnaire was administered in Italy and Brazil which led to a total sample of 453 participants. The data were statistically analyzed, and a PLS-SEM model was used to empirically examine the factors influencing the consumption of fresh mango and mango food and drinks. The research hypotheses are all supported. For a comparison between the two countries, a multigroup analysis (PLS-MGA) was performed. In Italy, consumers are attentive to the quality and safety of the fruit; they choose the point of sale where they buy fresh mango or mango foods because they trust the seller to guarantee the fruit’s origin and transformation. In Brazil, new consumer trends are emerging especially in gastronomy; since they are local foods, they are considered safe, sustainable and healthy by consumers. The study addresses a little-explored topic and aims to enrich the debate on consumer orientations, preferences and reasons for buying mango and mango products. Full article

Tax compliance and avoidance are critical issues for governments and businesses worldwide, especially as businesses often use legal methods to minimize taxes, which can impact public revenue and equity within the tax system. This study focuses on understanding the factors influencing tax avoidance behaviors among SMEs in Greece’s tourism sector, a sector that has received limited research attention. To this end, a quantitative cross-sectional design was employed, using a structured questionnaire to explore potential factors influencing tax avoidance behavior. Data were collected from 534 SME managers and analyzed using Structural Equation Modeling (SEM) to assess the impact of key factors and their interrelationships, including coercive power, digital transformation, tax knowledge, firm performance, and perceived fairness, on tax avoidance. In addition, corporate social responsibility (CSR) was included as a moderator variable, while coercive power and digital transformation were assessed as mediators. Furthermore, Multi-Group Analysis (MGA) was conducted to explore the differences between small and medium enterprises, as well as different ownership structures. The results indicate that all key determinants, except perceived fairness, are significantly and positively related to tax avoidance intention. Additionally, it was revealed that coercive power increases tax avoidance through firm performance and tax knowledge, while digital transformation mediates the influence of firm performance on tax avoidance by curtailing avoidance intentions. While CSR mitigates the negative influence of coercive power, digital transformation has a dual role: that of promoting transparency and strategic efforts to reduce the tax burden. These findings have important policy implications, as policymakers seek to promote digital adoption and enhance CSR engagement while formulating specific regulatory strategies to reduce tax avoidance among SMEs. Full article

The COVID-19 pandemic has severely impacted global tourism, raising the need for sustainable recovery strategies. This study examines how tourists’ confidence in tourism recovery (CTR) influences travel intentions across different pandemic phases—outbreak, stabilization, and conclusion. Positioned within the Theory of Planned Behavior (TPB), the research explores the mediating role of CTR in the relationships between attitude, subjective norms, perceived behavioral control, and travel intention. Using structural equation modeling (SEM), multi-group analysis (MGA), and Importance–Performance Matrix Analysis (IPMA), this study assesses changes in travel behavior during each pandemic phase. Data were collected through three surveys conducted in major Chinese cities between late 2022 and early 2023. The findings reveal that CTR significantly mediates the influence of behavioral factors on travel intention, especially during the stabilization and conclusion phases. The IPMA results highlight key areas for intervention, with CTR, perceived behavioral control, and subjective norms varying in importance across phases. This research underscores the need for adaptive and sustainable strategies to strengthen traveler confidence, offering practical insights for supporting long-term resilience and growth in the tourism industry during and beyond health-related crises. Full article

This study addresses the impact of urban parks on the self-rated health of office workers under 40, a demographic experiencing significant increases in depressive symptoms during the pandemic. This study in Baise City, China, aims to fill this gap by exploring the relationships between landscape quality, leisure time spent in parks, place attachment, and self-rated health among 411 office workers aged 18 to 40. Structural equation modeling was used to assess these relationships, and multigroup analysis (MGA) in SmartPLS evaluated differences between subgroups. The findings reveal a strong link between urban park landscape quality and leisure time spent in parks, place attachment, and self-rated health. Although the old-fashioned park showed lower overall performance in the study variables compared to the modern park, it had a stronger relationship between landscape quality and place attachment. Leisure time spent in parks did not directly impact self-rated health but was mediated by place attachment. MGA results indicated that while leisure time in parks positively affected self-rated health for single participants, it had a negative effect for married participants. These results underscore the importance of tailoring urban park design and management to accommodate the varying needs of different demographics. This research provides new insights into enhancing office workers’ self-rated health through environmental design and supports the objectives of the Healthy China strategy and Sustainable Development Goal 11. Full article

The aspiration of this paper is to examine the impact of corporate social responsibility (CSR) and service quality on customer loyalty and their relationship in the Indian telecommunication industry. A model was proposed and a total of 377 responses were collected using a structured questionnaire. Data were assessed and analyzed using PLS SEM. Multi-group analysis (MGA) was carried out to comprehend the moderating effect of gender, age, education, and income within the model. The results suggest that CSR does not have a direct impact on customer loyalty (CL), but there is an indirect effect when it is mediated through customer satisfaction (CS) and trust (Tr). Service quality (SQ) was found to have a direct impact on CL and while it is also mediated through CS. The results of the MGA revealed that customer satisfaction increases commitment towards customer loyalty and trust among male users. This study highlights that the modern customers are knowledgeable, more aware, and value companies which are focused on CSR activities. Full article

Financial technology (Fintech) and sustainability are two of the main drivers in the transformation of many organizations. New innovative technologies create new services for consumers. The focus on sustainability is a necessary reaction to the many challenges faced by organizations and, more broadly, society. The motivation to support these is, therefore, clear, but not all organizations move forward on both with the same enthusiasm. Leaders in Fintech do not always prioritize operating in a sustainable way. It is, therefore, important to explore and identify the synergies between Fintech and sustainability. One important aspect of this transformation is the consumers’ perspective, particularly the trust they have, their personal information privacy concerns, and the vulnerability they feel. It is important to clarify whether leadership in Fintech, with sustainability leadership, is more beneficial than leadership in Fintech on its own. This research evaluates consumers’ trust, privacy concerns, and vulnerability in the two scenarios separately and then compares them. Survey data is analyzed using Partial-Least Squares Structural Equation Modeling (PLS-SEM) and Multi-group Analysis (MGA). The findings show that leadership in both Fintech and sustainability builds trust more, which in turn reduces vulnerability more. Privacy concerns are lower when sustainability leadership and Fintech leadership come together; however, their combined impact was not found to be sufficiently statistically significant in this study. Full article

Food waste is an issue throughout the food supply chain from production to consumption, especially in the later stages, such as retailing and final consumption. For the future of the developing world, changes in farming and retail practices are crucial. This study introduces a digital system for managing agricultural waste in Thailand that aims to encourage farmers and food retailers to sell their excess agricultural materials. The study’s objectives are as follows: (1) to explore factors that affect users’ behavioral intention to utilize an agriculture waste trading platform; (2) to compare the behavioral differences between farmers and retailers regarding their intention to use a digital platform for sustainable agriculture. Data were gathered from 570 fruit and vegetable sellers and farmers across five provinces in the northeastern region of Thailand. Structural equation modeling (SEM) was used to analyze the relationships between constructs based on the modified Unified Theory of Acceptance and Use of Technology (UTAUT2), and multigroup analysis (MGA) was employed to analyze differences in path coefficients across groups. The key findings revealed that social influence (SI) had a more significant impact on retailers compared to farmers, while facilitating conditions (FC), habits (HB), and privacy (PR) were necessary for both groups. Unlike retailers, farmers were also motivated by hedonic motivation (HM) from using the platform. Explicitly, retailers’ behavioral intentions were influenced by a more significant number of factors than those of farmers. This research suggests that policymakers should develop targeted marketing campaigns leveraging social influence for retailers, improve platform usability and security, and create incentives for habitual use to enhance platform adoption. Additionally, policymakers should promote engaging features for farmers, provide comprehensive education and training, and advocate for supportive policies and financial incentives. Strategic actions to facilitate the transition toward a circular economy will improve the environmental sustainability and economic resilience of the agri-food sector. Full article