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This study evaluates the moderating role of work-based social supports (i.e. supervisor support and co-worker support) in the relationship between job insecurity and job burnout among hospitality employees in Malaysia. Besides, the direct effect between job insecurity and job burnout is examined.

The cross-sectional data of this study were based on a total of 220 self-administered questionnaires that have been completed by hospitality employees from three different states in Malaysia. Respondents were recruited based on a snowball sampling approach. The data were collected during the COVID-19 pandemic, which was from October 2020 to January 2021.

Partial least square-structural equation modeling (PLS-SEM) was performed via SmartPLS software. The finding confirmed that job insecurity significantly intensifies employees' job burnout. Supervisor support and co-worker support were found to moderate the link between job insecurity and burnout. As anticipated, the relationship between job insecurity and job burnout increased when supervisor support is low. But high co-worker support was found to strengthen the impact of job insecurity on job burnout instead of the reverse.

This study supplements the existing literature by clarifying which sources of work-based social support (i.e. co-worker support or supervisor) is more salient in alleviating the adverse impact of job insecurity on job burnout during the COVID-19 pandemic among hospitality employees in Malaysia.

Understanding young adults’ organic food purchasing behavior in the fresh food e-commerce platforms (FFEP) is crucial for expanding the global environmental product market. The study aims to investigate how specific characteristics of platforms and organic food information impact young adults’ perceived value, leading to their subsequent purchase intention.

Around 535 valid responses were collected through an online survey and then analyzed applying a two-stage structural equation model (SEM) and artificial neural network (ANN) approach.

Results of this research show that platform characteristics (including system quality and evaluation system) and product information characteristics (including organic label, ingredient information and traceability information) significantly affect young adults’ perceived utilitarian and hedonic value. The platform’s service quality has a strong effect on their perceptions of hedonic value, while the delivery system strongly influences their utilitarian value. Moreover, the perceived value, as a crucial mediator, plays a significant role in moderating the influence of platform and product information characteristics on the purchase intentions of young consumers regarding organic food.

Previous research has overlooked the credence attributes of organic food and particularities of online purchasing, focusing instead on general platform and product characteristics. This study addresses this gap by proposing a more appropriate model that integrates the characteristics of both the platform and product information. This offers theoretical and managerial implications for effectively stimulating organic food consumption among young adults in online environments.

The purpose of this study is to explore the link between information systems (IS) capabilities, supplier integration and cost performance in the service context. Specifically, it empirically investigates how supplier integration meditates the relationship between three dimensions of IS capabilities and cost performance in service firms.

A survey of 156 UK service firms was conducted and the data analyzed to determine the role of supplier integration in mediating the effects of IS capabilities on firms' cost performance. The research model was tested using structural equation modeling (SEM), and the neural network model was used to rank the relative influence of significant predictors obtained from SEM.

The results confirmed that supplier integration fully mediates the effects of information technology (IT) for supply chain activities and flexible IT infrastructure on cost performance and partially mediates the effect of operations manager's IT knowledge on cost performance. The results showed that operations manager's IT knowledge is the strongest predictor of supplier integration.

This study takes a step toward quelling concerns about the business value of IS, contributing to the development and validation of the measurement of IS capabilities in the service operations context. Additionally, it adds to the emerging body of literature linking supplier integration to the operational performance of service firms.

The study aims to investigate factors impacting consumers’ intention to adopt collaborative consumption (CC, hereafter) services. It extends the existing knowledge of CC services by testing and validating the moderating role of coercive power and the mediating role of attitude.

Applying random sampling, the data was collected through the mall intercept method across four cities in India and was analyzed using partial least square-structural equation modeling and artificial neural network to test the proposed hypotheses. A follow-up qualitative study consisting of 15 in-depth structured interviews helped validate the results of the quantitative research.

Results of the conducted survey revealed that a sense of community, reason-based trust and enjoyment positively impact consumers’ attitudes toward CC services. Attitude positively impacts intention and shows a partial mediating influence on the relationship between motivations and intentions. Furthermore, the results revealed the moderation of the perceived coercive power of the service provider. The results of the follow-up qualitative study validated the results of the quantitative research.

Managers of CC firms must understand the relative importance of intrinsic and extrinsic motivations in formulating the attitudes of consumers and intentions toward CC services. CC managers should acknowledge the influence of the consumer’s perceived coercive power of service providers and consumer’s reason-based trust.

To the best of the authors knowledge, the current research is the first of its kind. It has justifiably and logically applied self-determination theory and a slippery slope framework in a single context. By testing the moderating impact of coercive power, the research extends the existing literature on CC and the applicability of coercive power in CC. The present study extends the knowledge regarding the consumer’s perception of reason-based trust and the perceived coercive power of service providers in CC.

This study develops a comprehensive research model and investigates the significant factors affecting positive marketing outcomes in the Metaverse through perceived social benefits and trust.

The authors propose a new research model based on social exchange theory (SET) and examine the impact of cost and reward factors. Using 327 survey samples collected from current Metaverse users in South Korea, dual-stage analysis using Partial Least Squares Structural Equation Modeling (PLS-SEM) and an artificial neural network (ANN) were employed to test the study’s hypotheses.

The results showed that perceived social benefit and trust had significant mediating effects on marketing outcomes, such as loyalty to the seller, product/service attitude, and purchase intention. All antecedents, except perceived performance risk, had a crucial impact on the two mediators. The most interesting finding of this study is the positive influence of knowledge-seeking efforts on perceived social benefits.

This study is the first empirical research to examine the effectiveness of marketing in the Metaverse. It also proposes a new theoretical model based on SET to investigate users’ behavioral intentions regarding marketing in the Metaverse, and confirms its explanatory power. Moreover, the results of this study also offer suggestions to brands on how to market to consumers in the Metaverse.

Emerging competitive dynamics demand small and medium-sized enterprises (SMEs) to continuously comprehend and respond to changing market conditions by implementing effective soft total quality management (STQM) practices. Firstly, the study intends to identify the key STQM practices perceived to foster knowledge sharing (KS). Secondly, this study aims to investigate the impact of market turbulence (MT) on the interaction between STQM practices and KS among SMEs.

A total of 215 valid samples were analysed. Incorporating a two-hidden-layer deep artificial neural network (ANN) into SEM approaches allows for more in-depth testing and high prediction power. This study employs a two-stage PLS-SEM-ANN predictive-analytical technique to provide a more comprehensive analysis and significant statistical contribution.

The PLS-SEM-ANN analysis reveals that STQM practices including employee involvement (EI), employee training (ET), top management commitment (TMC) and employee teamwork (EM) are critical to boosting KS. MT, interestingly, moderates the relationship between EM and KS while negatively moderating the relationship between TMC and KS.

The study contributes to the knowledge-based view theory by demonstrating the importance of integrating STQM and KS among SMEs to thrive in today's dynamic market environment.

This paper presents a new surface reconstruction method based on complex form functions, genetic algorithms and neural networks. Surfaces can be reconstructed in an analytical representation format. This representation is optimal in the sense of least‐square fitting by predefined subsets of data points. The surface representations are achieved by evolution via repetitive application of crossover and mutation operations together with a back‐propagation algorithm until a termination condition is met. The expression is finally classified into specific combinations of basic functions. The proposed method can be used for CAD model reconstruction of 3D objects and free smooth shape modelling. We have implemented the system demonstration with Visual C++ and MatLab to enable real time surface visualisation in the process of design.

Mobile taxi booking apps (MTB) have revolutionalized the transportation industry. As taxis can be hired via smartphones, irrespective of any time or place, the business platform for taxi service has completely changed. Now customers are saved from the hassle of going to the designated taxi stands or waiting along the roadside. But, the long-term sustainability of this service depends on its continued use. Therefore, this study aims to explore factors that hedonically incline people toward continuance of MTB. To achieve the purpose, the unified theory of acceptance and use of technology (UTAUT) was extended with mediation effects of hedonic motivation.

The data were collected from existing users of MTB and analyzed through structural equation modeling and revalidated via artificial neural networks.

The statistical results show that the main factors of UTAUT substantially create hedonic motivation to use the apps and significantly mediate their effects on behavioral intention to continue using MTB. However, mediation between social influence and continuity intent was not statistically supported. The findings represent important contributions to the extended UTAUT.

This study adds value to the theoretical horizon and also presents M-taxi companies with useful and pertinent plans for efficient designing and effective implementation of MTB. Moreover, limitations and suggestions for future researchers are also discussed.

This study extends UTAUT with the mediating role of hedonic motivation to predict continued use of MTB, which further initiates the applicability of UTAUT in a new setting and a new perspective (post adoption). This, in turn, significantly expands theory by using hedonic motivation as an important attribute that could mediate impact of all main antecedents to shape customers loyalty toward system use.

In today’s globalized and heavily industrialized economy, sustainability issues that negatively affect the human population and external environment are on the rise. This study aims to investigate a synergistic combination of supply chain management and quality management practices in strengthening the sustainability performance of Malaysian manufacturing firms.

A total sample of 177 usable surveys was collected. Given the contributions and acceptability of the artificial neural network (ANN) approach in evaluating the findings of this study, this study uses ANN to measure the relationship between each predictor (i.e. supply chain integration [SCI], quality leadership [QL], supplier focus [SF], customer focus (CF) and information sharing [IS]) and the dependent variable (i.e. sustainability performance). Via sensitivity analysis, the relative significance of each predictor variable is ranked based on the normalized importance value.

The sensitivity analysis indicates that CF has the greatest effect on sustainability performance (SP) with 100% normalized relative importance, followed by QL (75%), IS (61.5%), SF (57.3%) and SCI (46.7%).

The findings of this study have the potential to provide valuable guidance and insights that can help all manufacturing firms enhance their SP from the optimum combination of the selected SCQM practices with a focus on sustainability.

While there is an abundant amount of literature studies on mobile payment adoption, there is a scarce of knowledge concerning the sustainable use of mobile payment contactless technologies. As those technologies are mainly concerned with security and users' trust, the question of how security factors and trust can influence the sustainable use of those technologies within and beyond the COVID-19 pandemic is still unanswered. This research thus develops a theoretical model based on integrating the protection motivation theory (PMT) and the expectation-confirmation model (ECM), extended with perceived trust (PT) to explore the sustainable use of mobile payment contactless technologies.

The developed model is evaluated based on data collected through a web-based survey from 523 users who used contactless payment technologies. Unlike the existing literature, the collected data were analyzed using a hybrid structural equation modeling-artificial neural network (SEM-ANN) technique.

The data analysis results reinforced all the proposed relationships in the developed model. The sensitivity analysis results showed that PT has the largest impact on the sustainable use of mobile payment contactless technologies with 97.2% normalized importance, followed by self-efficacy (SE) (77%), satisfaction (72.1%), perceived vulnerability (PV) (48.9%), perceived usefulness (PU) (48.2%), perceived severity (PS) (40.7%), response efficacy (RE) (28.7%) and response costs (RCs) (24.1%).

The originality of this research lies behind the development of an integrated model based on PMT and ECM to understand the sustainable use of mobile payment contactless technologies. The study provides several managerial implications for decision-makers, policy-makers and service providers to ensure the sustainability of those contactless technologies within and beyond the COVID-19 pandemic.