Search Results (1,227)

Background/Objectives: Healthcare organizations worldwide face challenges in retaining talented employees, with the phenomenon of quiet quitting increasingly recognized as a contemporary issue. Rather than leaving their jobs, employees remain at work but exert minimal effort and exhibit reduced engagement, which can ultimately undermine the performance of healthcare organizations. The aim of this research was to examine the impact of servant leadership on work engagement within healthcare organizations, to determine whether this leadership style can help mitigate the effects of quiet quitting. Methods: The study employed a quantitative approach, utilizing validated instruments to measure servant leadership and work engagement. A cross-sectional study design was utilized, employing a convenience sampling method. A total of 362 valid surveys were collected from healthcare professionals in Serbia participating in the study from January to March 2025. The partial least squares structural equation modeling (PLS-SEM) method was used to examine the relationship between servant leadership and work engagement among healthcare professionals. Results: The results indicate that servant leadership has a positive and statistically significant impact on all dimensions of engagement: vigor, dedication, and absorption. Conclusions: Based on these findings, it is concluded that servant leadership can serve as an effective strategy for enhancing work engagement and reducing negative employee behaviors, such as quiet quitting, which may, in turn, improve organizational efficiency in the healthcare industry. Full article

AI-based assistive technologies (AIATs) are increasingly recognised as essential tools to enhance accessibility, independence, and inclusion for visually impaired students in higher education. However, limited evidence exists regarding the determinants of their acceptance and use, particularly in terms of psychosocial factors. This study aimed to extend the Unified Theory of Acceptance and Use of Technology (UTAUT) by incorporating physical self-esteem (PSE) as a moderator and behavioural intention (BI) as a mediator within a single model. Data were collected through a validated questionnaire administered to 395 visually impaired undergraduates across five Saudi universities. Constructs included effort expectancy (EE), performance expectancy (PE), facilitating conditions (FCs), social influence (SI), BI, and PSE. Partial Least Squares Structural Equation Modelling (PLS-SEM) was used for analysis. Results showed that PE and SI significantly predicted both BI and adoption, while EE strongly predicted BI but not AIAT adoption; FC had no significant influence on either outcome. BI positively affected AIAT adoption and mediated the effects of PE, EE, and SI, but not FC. Moderation analysis indicated that PSE strengthened the influence of PE, EE, and SI on BI and adoption. These findings underscore the significance of psychological factors, particularly self-esteem, in promoting the adoption of AIAT and offer guidance for developing inclusive educational strategies. Full article

Mobile learning (m-learning) technologies are gaining popularity in universities but not uniformly across institutions because of cognitive, affective, and behavior obstacles. This research tested and applied an expansion of the Technology Acceptance Model (TAM) with technostress (TECH) and resistance to change (RTC) as affective obstacles, as well as the core predictors of perceived usefulness (PU), perceived ease of use (PE), and perceived risk (PR). By employing a cross-sectional survey of Greek university students (N = 608) and partial least squares structural equation modeling (PLS-SEM), we tested direct and indirect impacts on behavioral intention (BI) to apply m-learning applications. The results affirm that PU and PE are direct predictors of BI, while PR has no direct impact on BI but acts indirectly through TECH and RTC. Mediation is partial in terms of PE and PU and indirect-only (complete) in terms of PR with respect to the impact of affective states on adoption. Multi-group comparisons found differences in terms of gender, age, confidence, and years of use but not frequency of use, implying that psychological and experiential characteristics have a greater impact on intention than habitual patterns. These results offer theory-driven and segment-specific guidelines for psychologically aware, user-focused m-learning adoption in higher education. Full article

This study investigates the role of Modern Management Accounting (MMA)—which integrates Strategic Management Accounting (SMA) and Strategic Customer Knowledge (SCK)—in driving Sustainable Competitive Advantage (SCA) and Business Sustainability (BS) in Thai green hotels. Business Sustainability is conceptualized as the achievement of balanced outcomes across economic performance, social responsibility, and environmental stewardship. It addresses a theoretical debate by testing two competing SCA models: a disaggregated model (which separates SCA into Customer Experience Advantage (CEA) and Operational Efficiency Advantage (OEA)) and a holistic model (which treats SCA as a unified construct). Data from 115 certified green hotels were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The results revealed a critical distinction between the models. In the disaggregated model, SMA and SCK contributed to both CEA and OEA, but only OEA directly enhanced BS and served as a partial mediator in the relationships from both SMA and SCK to BS, whereas CEA showed no significant mediating effects. Conversely, the holistic model demonstrated that overall SCA served as a partial mediator in the relationships from both SMA and SCK to BS, while also exerting a strong direct effect on BS. The study concludes that achieving business sustainability requires a holistic SCA that integrates both operational efficiency and customer experience, offering a comprehensive framework for strategic management in the hotel industry. These findings underscore the strategic imperative for hotel managers to cultivate an integrated competitive advantage, where superior customer experiences and operational excellence are synergistically managed, to ensure long-term business sustainability. Full article

In light of escalating global environmental deterioration, studies on pro-environmental intention and behaviour with the ultimate goal of identifying contributing factors to minimise environmental issues are common. Theory of Planned Behaviour (TPB) is widely used to study environmental intentions and behaviours. However, how quality of life (QoL) influences these intentions and interactions among TPB’s own variables within a single research framework has not been thoroughly explored. Therefore, this study extends TPB by incorporating the four dimensions of QoL, as measured by the Control, Autonomy, Self-Realisation, and Pleasure (CASP-19) scale, to understand pro-environmental intentions from Malaysian viewpoints. In this study, quantitative approach was applied, and the data were collected from Malaysians aged 18 and above (N = 182) in Klang Valley, Malaysia. Using Partial Least Squares Structural Equation Modelling (PLS-SEM), a two-step approach was employed to assess the measurement and structural models. The findings confirmed Theory of Planned Behaviour (TPB) is a robust model for environmental studies showing that subjective norm and perceived behavioural control significantly influence attitudes toward pro-environmental behaviour, ultimately leading to pro-environmental intention. Interestingly, this study found no relationship between QoL dimensions and pro-environmental intention. Lastly, both theoretical and managerial implications were discussed, and research limitations and suggestions for future research directions were put forward. Full article

Customer experience is central to omnichannel marketing and is increasingly the focus of research attention. However, few studies have focused on the development of excellent omnichannel customer experiences. To fill this research gap, we examined the drivers of these experiences from a customer journey design perspective. Partial least squares structural equation modeling (PLS-SEM) and partial least squares multigroup analysis (PLS-MGA) were employed to analyze 775 valid omnichannel customers’ data, which were collected through an online survey. The findings suggest that the thematic cohesion, consistency, context sensitivity, and connectivity of touchpoints play an important role in improving omnichannel customer experience. Value co-creation behavior can be significantly increased by affective, cognitive, physical, relational, and symbolic experiences, but not by sensorial omnichannel customer experiences. These results not only contribute to the knowledge of omnichannel customer experiences, customer journeys, and value co-creation behavior, but also offer useful advice for omnichannel marketers. Full article

The purpose of this study is to examine the impact of integrity-related considerations, such as ethics, privacy, protection, security, and trust, on online consumer shopping intention within the interactive marketing environment. To achieve this, the research uses partial least squares structural equation modelling (PLS-SEM), analysing data from a sample of 260 respondents collected through an online survey. The findings reveal that protection is the most influential factor driving consumer buying intentions, followed by trust, ethics and security. Privacy, while significant, has a more moderate influence on consumer behaviour compared to other factors. The study makes a key theoretical contribution by advancing the understanding of how these constructs interact to shape consumer behaviour in the digital marketplace, particularly highlighting the importance of data protection and ethical practices. Practically, the research offers actionable recommendations for e-commerce businesses, based on building a digital integrity model, suggesting the focus on enhancing data security and ethical transparency to build consumer trust. Furthermore, the findings highlight the need for policymakers to strengthen data privacy regulations and harmonise international security standards in e-commerce. Future research should consider longitudinal studies and explore these dynamics in different regulatory environments. Full article

Tourist loyalty is vital for destination success, fostering repeat visits and positive word-of-mouth. This study explores the psychological and safety-related factors driving tourist loyalty to natural attractions in Oman, a rising destination known for its stability and safety. Using Social Cognitive Theory as a foundation, the research incorporates perceived risk and novelty seeking as key moderating variables. Data were collected via an online survey of 165 international tourists and analyzed through Partial Least Squares Structural Equation Modeling (PLS-SEM). Findings show that attachment, satisfaction, and novelty seeking significantly affect both attitudinal and behavioral loyalty. While perceived value strongly influences behavioral loyalty, its impact on attitudinal loyalty appears more complex, suggesting possible unobserved mediators. Additionally, risk perception and novelty seeking moderate the link between destination familiarity and loyalty, underscoring the role of tourists’ internal evaluations of safety and desire for new experiences. This study advances the limited literature on tourist loyalty in developing countries by integrating psychological and risk-related dimensions. It offers actionable insights for tourism planners and marketers in Oman: emphasizing the country’s safety reputation, improving satisfaction levels, and crafting experiences that blend familiarity with novelty can enhance tourist loyalty and ensure sustained competitiveness in the global tourism market. Full article

As Generation Z increasingly dominates the consumer market, understanding their purchasing behaviour in online marketplaces has become crucial for businesses aiming to engage this digitally native and environmentally conscious demographic. The present study aims to explore Generation Z′s purchasing behaviour in e-commerce platforms through the lens of the Technology Acceptance Model (TAM), while incorporating additional factors such as sustainability and environmental awareness. A partial least squares structural equation modelling (PLS-SEM) analysis using WarpPLS 8.0 was conducted on a sample of 636 Generation Z respondents from Romania. The results suggest that online marketplaces can enhance consumer engagement by integrating eco-friendly practices and emphasizing sustainable product offerings. This research contributes to the e-commerce literature by extending the TAM framework and by providing valuable insights for businesses targeting environmentally conscious digital consumers. Full article

Cultural heritage sites play a crucial role in safeguarding identity, fostering cultural exchange, and generating sustainable tourism. Within this context, the Palace Museum in Beijing, which attracts 19 million annual visitors, offers a compelling case for examining the dynamics that shape revisit intention. This study explores the relationships among perceived authenticity, place attachment, destination satisfaction, visitor engagement, and revisit intention within the context of heritage tourism. Using Partial Least Squares–Structural Equation Modeling (PLS-SEM), data were collected from local visitors to the Palace Museum to analyze both the direct and mediating effects of these constructs. Findings indicate that perceived authenticity significantly enhances both destination satisfaction and visitor engagement, while place attachment makes a strong contribution to visitor engagement. Moreover, visitor engagement emerged as a more influential mediator than destination satisfaction in linking perceived authenticity to revisit intention, showing the importance of immersive and meaningful participation in shaping tourists’ behavioral intentions. These results suggest that while satisfaction remains a relevant concept, strategies that emphasize authenticity-driven experiences and fostering of deeper emotional and participatory bonds are more effective in sustaining revisits. This study advances the understanding of heritage tourism and provides practical insights for managing iconic heritage sites such as the Palace Museum. Full article

In the rapid digital era, artificial intelligence (AI) tools have progressively arisen to shape the education environment. In this context, large language models (LLMs) (i.e., ChatGPT vs. 4.0 and Gemini vs. 2.5) have emerged as powerful applications for academic inclusion. This paper investigated how using and trusting LLMs can impact the academic success and quality of life (QoL) of visually impaired university students. Quantitative research was conducted, obtaining data from 385 visually impaired university students through a structured survey design. Partial Least Squares Structural Equation Modelling (PLS-SEM) was implemented to test the study hypotheses. The findings revealed that trust in LLMs can significantly predict LLM usage, which in turn can improve QoL. While LLM usage failed to directly support the academic success of disabled students, but its impact was mediated through QoL, suggesting that enhancements in well-being can contribute to higher academic success. The results highlighted the importance of promoting trust in AI applications, along with developing an accessible, inclusive, and student-centred digital environment. The study offers practical contributions for educators and policymakers, shedding light on the importance of LLM applications for both the QoL and academic success of visually impaired university students. Full article

In the rapidly evolving global business landscape, servitization and digitalization have emerged as key strategies for enhancing firm competitiveness and performance. This study examines their impact, along with the moderating role of government support, in the Indonesian shipping industry. Drawing on the resource-based view (RBV), servitization and digitalization are conceptualized as internal drivers of performance, while Resource Dependence Theory (RDT) positions government support as an external factor that reduces environmental uncertainty and strengthens these relationships. Using data from 345 shipping companies, analyzed through Partial Least Squares Structural Equation Modeling (PLS-SEM), the results show that both servitization and digitalization positively affect competitiveness and performance. Furthermore, government support significantly enhances these effects by providing resources such as infrastructure and financial incentives, facilitating the adoption of digital strategies and service-based models. Beyond firm outcomes, these transformations align with broader sustainability objectives by improving resource efficiency, reducing waste and delays, and potentially lowering the environmental footprint of logistics activities. This study advances theoretical understanding by demonstrating the central role of external resources—particularly government support—in enabling successful digital and service transformations. For policymakers, the findings emphasize the need for targeted incentives and infrastructure to accelerate industry-specific innovation and sustainability goals. For practitioners, they highlight the importance of aligning strategic initiatives with government policies to maximize the benefits of servitization and digitalization. Full article

While integrated Artificial Intelligence and Business Analytics (AI-BA) represents a significant advancement in marketing analytics and greatly influences firms’ innovations, there is a considerable gap in current research regarding its impact on technological innovation. This study addresses this gap by exploring how AI-BA affects data-driven and technological innovation, considering the mediating roles of integration capabilities and digital platforms. A theoretical model has been developed based on the dynamic capability view (DCV) and organizational information processing theory (OIPT). The model has been validated using data from enterprises in Saudi Arabia, and Partial Least Squares Structural Equation Modeling (PLS-SEM) has been employed for analysis. The findings demonstrate that AI-BA directly enhances both technological and data-driven innovation. Additionally, it was discovered that data-driven innovation, integration capabilities, and digital platforms mediate these effects, thereby enhancing technological innovation within the respective industries. These findings provide both theoretical and practical insights into the relationship between AI-BA, data-driven innovation, and technological innovation. They enrich the existing literature and provide actionable guidance for practitioners aiming to align their AI-BA with improved technological innovation outcomes. Full article

Student trust plays a pivotal role in shaping the future integration of artificial intelligence (AI) in higher education. This study investigates how AI Facilitating Conditions (FCs), Performance Expectancy (PE), and task type influence students’ System-like Trust (AST) and Human-like Trust (AHT) in AI and further examines the mediating role of human-like trust in fostering the willingness to continue AI-assisted learning. Drawing on valid data collected from 466 Chinese university students, we employed partial least squares structural equation modeling (PLS-SEM) in combination with artificial neural networks (ANN) to test the hypothesized relationships, mediating mechanisms and the relative importance of influencing factors. The findings indicate that AI facilitating conditions significantly enhance both system-like trust and usage intention; performance expectancy exerts a positive effect on both forms of trust, with particularly strong effects observed in subjective tasks. Moreover, system-like trust positively promotes human-like trust, and together, these dimensions jointly strengthen students’ intention to engage in AI-assisted learning. Results from the ANN analysis further highlight that performance expectancy, system-like trust, and facilitating conditions are the primary determinants of system-like trust, human-like trust, and usage intention, respectively. This study extends the application of interpersonal trust theory to the AI domain and offers theoretical insights for fostering more positive and effective patterns of AI adoption in higher education. Full article

This study scrutinizes the effects of generative artificial intelligence (GenAI) on sustainable performance (SP) in Chinese manufacturing firms through the mediating role of novelty-centered and efficiency-centered business model innovations (BMIs). It also explores the moderating effect of AI regulation on the GenAI–BMIs and GenAI–SP relationships. Data were collected from 1192 middle-level managers across 500 Chinese manufacturing firms using a two-wave survey design. Partial least squares structural equation modeling (PLS-SEM) was employed to test direct, mediating, and moderating relationships. The findings show that GenAI adoption has a significant positive effect on novelty-centered BMI, efficiency-centered BMI and sustainability performance. The GenAI–SP relationship is mediated by both BMIs, indicating that GenAI contributes to sustainability both directly and through innovative business practices. Moreover, AI regulation significantly strengthens the effects of GenAI on both BMI and SP, emphasizing the importance of regulatory alignment in maximizing technological benefits. This research shows that firms should emphasis AI tools and strategies to innovate their business model for better sustainable outcomes. Firms need to follow regulations and rules embedded into digitalization to ensure a sustainable competitive position in the market. Full article