Search results

Recent disruptions have sparked concern about building a resilient and sustainable manufacturing supply chain. While artificial intelligence (AI) strengthens resilience, research is needed to understand how cloud adoption can foster integration, collaboration, adaptation and sustainable manufacturing. Therefore, this study aimed to unleash the power of cloud adoption and AI in optimizing resilience and sustainable performance through collaboration and adaptive capabilities at manufacturing firms.

This research followed a deductive approach and employed a quantitative method with a survey technique to collect data from its target population. The study used stratified random sampling with a sample size of 1,279 participants working in diverse manufacturing industries across California, Texas and New York.

This research investigated how companies can make their manufacturing supply chains more resilient and sustainable. The findings revealed that integrating the manufacturing supply chains can foster collaboration and enhance adaptability, leading to better performance (hypotheses H1-H7, except H5). Additionally, utilizing artificial intelligence helps improve adaptability, further strengthening resilience and sustainability (H8-H11). Interestingly, the study found that internal integration alone does not significantly impact collaboration (H5). This suggests that external factors are more critical in fostering collaboration within the manufacturing supply chain during disruptions.

This study dives into the complex world of interconnected factors (formative constructs in higher order) influencing manufacturing supply chains. Using advanced modeling techniques, it highlights the powerful impact of cloud-based integration. Cloud-based integration and artificial intelligence unlock significant improvements for manufacturers and decision-makers by enabling information processes and dynamic capability theory.

The use of e-health applications has remained popular during pandemic for medical treatments. Nevertheless, adoption of e-health applications among individuals is considerably low in post-COVID-19 world. To address this issue, the current research integrates three renowned theories, namely unified theory of acceptance and use of technology model, diffusion of innovation and DeLone and McLean model and investigates individual intention to adopt e-health application.

Research design is grounded in quantitative and cross-sectional methods and uses a survey questionnaire. Survey questionnaire is administered toward smartphone users. Overall, 238 valid responses were analyzed with structural equation modeling approach.

Results indicate that altogether performance expectancy, effort expectancy, information quality, system quality, service quality, facilitating condition and social influence explained substantial variance (R² = 76.5%) in user intention to adopt e-health applications. Similarly, effect size analysis has revealed substantial impact of social influence on user intention to adopt e-health applications. Geiser and Stone’s Q² analysis discloses that research model has substantial power to predict user intention to adopt e-health applications.

This study integrates three known information system models to investigate individual behavior toward adoption of e-health applications. In practice, it suggests that managers should pay attention in improving performance expectancy, social influence, facilitating condition, system quality, service quality and information quality which develop positive behavior and encourage smartphone users to adopt e-health applications.

This study is original as it integrates three models and investigates individual intention to adopt e-health applications. To the best of the author’s knowledge, this is the first study to test the moderating impact of patient health value between user intention to adopt and actual use of e-health applications. It has established that compatibility and innovativeness are essential antecedents of performance and effort expectancy and hence make this research more unique and valuable.

The Fast Moving Consumer Goods (FMCG) sector is a critical component of the global economy, providing consumers with a wide range of products that are consumed daily. However, this sector faces vulnerability during disruptions. Therefore, this research amid to examine the effect of supplier trust and integrated technology on supply chain resilience (SCR) for sustainable supply chains in the FMCG sector.

Data was collected from 409 respondents from the FMCG sector in the United States. The hypotheses were tested using Structural Equation Modeling through SmartPLS. The study findings found that all the direct and mediating hypotheses were supported.

The findings suggest that better supplier trust and the use of integrated technology enhance the capability of an organization to better respond to disruptions. It makes the supply chain more resilient. Further, SCR brings sustainable supply chains to the FMCG sector. Similarly, SCR is a significant mediator in the relationships between independent and dependent variables, highlighting the importance of resilient supply chains.

This research contributes to the literature on study variables and the Dynamic Capability View theory, as supplier trust integrated technologies are crucial factors in building resilient supply chains. This research has several managerial implications, including managers’ need to prioritize building trust with suppliers to facilitate increased information sharing. They should invest in integrated technologies to sense, forecast and be proactive in building SCR and, eventually, a sustainable supply chain.

Based on the job demand and resource (JD–R) model, this study identifies the factors influencing fatigue among seafarers in Malaysia.

A total of 250 responses were gathered via an online survey applying a purposive sampling method. The derived data were analysed using partial least squares-structural equation modelling (PLS-SEM) via SmartPLS 4.

Job demand positively influences sleep problems and occupational stress, while job resources positively impact job autonomy. The research analysis also confirms the positive effect of sleep problems and occupational stress on fatigue. Furthermore, the study reveals the negative effect of job autonomy on fatigue. In-depth analysis confirms the mediation and sequential mediation effects as the determinants of fatigue among seafarers in Malaysia.

Besides enriching the literature on fatigue, the findings provide practical insights to maritime agencies to develop an effective policy to reduce fatigue among seafarers.

The study develops a new model for seafarers’ fatigue via the JD–R model by introducing work pressure, sleep problems, occupational stress and autonomy as sequential mediators.

This paper aims to investigate the motivating factors for Malaysian governmental agencies (MGAs) to embrace chatbot technology.

Based on the technology-organisation-environment (TOE) framework, using purposive and snowball sampling techniques, 262 online data from the MGA top management were gathered. Smart PLS4 was employed to test the hypotheses of the study.

The findings demonstrated positive relationships between technological readiness (TR), big data analytics (BDA), organisational readiness (OR), organisational learning capabilities (OLC) and governmental policies (GP) concerning chatbot adoption intention and also the relationship GP with OR. A mediating effect was also observed, which indicated the OLC role in positively mediating BDA, the OR role in positively mediating OLC and the OR role in positively mediating GP with OR and OLC as sequential mediators in the relationship between BDA and chatbot adoption intention. Furthermore, the presence of citizen demand (CD) strengthened the relationship between TR, OR and chatbot adoption intention.

This study was limited to Malaysian federal government agencies who still not adopting Chatbots.

The findings offer valuable insight into factors affect the adoption of chatbots among Malaysian government agencies. Stakeholders, including department heads, can use these findings to strategically enhance counter service by promoting chatbot adoption.

The study demonstrated that the TOE framework was effective in identifying the factors contributing to the decision-making process for adopting chatbots across MGAs. Organisational readiness and organisation learning capability was found to sequentially mediate the relationship between big data analytic and intention to adopt chatbot. Citizen demand was found to have moderation effect on the relationship between organisational readiness and technological readiness towards the intention to adopt a chatbot.

There is paucity of research on the significant criteria that non-Muslims consider when purchasing halal cosmetics. Consequently, this paper aims to apply the theory of planned behaviour (TPB) and the health belief model (HBM) to investigate the effects of subjective norms (SN), perceived behavioural control (PBC), halal certification and health consciousness on attitude; as well as the impact of attitude on promoting the intention to purchase halal cosmetic products among non-Muslims.

Data collection involved the use of a web-based survey of 238 non-Muslim respondents that are resident in Malaysia, a south east Asian country reputed for being the global hub for halal products. The proposed model was evaluated using Smart PLS 3.3.5.

According to the structural model results, halal certification, health consciousness and SN have significant relationships with attitude. In addition, there are significant relationships between attitude, health consciousness, SN and the intention to purchase halal cosmetic products. In contrast, there is no correlation between halal certification, PBC and intention to purchase halal cosmetics. Furthermore, attitude significantly mediates the relationships between halal certification, SN, health consciousness and intention to purchase halal cosmetics. However, attitude did not significantly fulfil the role of a mediator in the relationship between PBC and intention to purchase halal cosmetic products.

The study findings provide valuable insights to companies targeting non-Muslim markets. The study findings contend how halal cosmetic production/marketing companies may customize their marketing activities based on social and health perspectives, thereby increasing the consumers’ social expectations and confidence in halal cosmetics production standards and guaranteeing safety to influence their attitudes and quickly penetrate the new market for non-Muslim consumers who make a relatively unexplored population.

The current study investigates the factors influencing graduates’ perceived employability by utilizing the stimulus-organism-response theory, in the post pandemic era.

A quantitative approach was employed to examine the hypotheses of the research framework through partial least squares structural equation modelling (PLS-SEM) on the SmartPLS software.

The result indicates that course structure has a positive effect on students’ grit and community of inquiry (CoI). Also, students’ grit and CoI have a positive relationship with students’ performance, while students’ performance has a positive relationship with perceived employability. Moreover, students’ grit, CoI and students’ performance sequentially mediated course structure and perceived employability, whereas readiness and self-directed learning strengthen the relationship between students’ performance and perceived employability.

The findings will benefit university management, government and potential employers on how confident the student is in the chances of a future career after graduating from a higher institution.

Drones will become part of daily lives similar to smartphones becoming a staple of modern living. Nonetheless, only several past studies investigated the intention to utilise drones for parcel delivery however, the intention to use drones among online shoppers was not fully explored. The study attempts to investigate the factors influencing the intention to use drones for last-mile delivery.

A total of 292 data were gathered via an online survey among online shoppers applying a snowball sampling method. Since the study operationalised the measures as composites, a combination of reflective and formative measurement, and the study focusses on predictive purposes, partial least squares structural equation modelling with SmartPLS 4 was applied to test the model developed based on the stimulus-organism-response model.

The analysis found that all the direct hypotheses were found supported. Moreover, Green support, green desire and pro-environmental behaviour positively and sequentially mediated future orientation and intention, whereas technology anxiety and perceived safety moderated the relationship between pro-environmental behaviour and intention.

The respondents only limit to the online shoppers in Malaysia which based on purposive sampling method, thus the findings cannot be generalized to another countries.

Besides enriching the literature on drone studies, the findings provided practical insights to online platforms and drone operators to develop an effective strategy to encourage online shoppers to shift from conventional delivery to drone delivery.

The study developed a new model for drone delivery studies using the S-O-R model in introducing orientation towards the future and green support as the stimulus, green desire as an organism and pro-environmental behaviour and usage intention as a response. The study introduced multiple sequential mediators, also contributing to the S-O-R model to predict online shoppers' behaviour towards drones as a tool for last-mile delivery. Another important contribution, technology anxiety and perceived safety were confirmed to have a moderation effect for the relationship between pro-environmental behaviour and intention to use drones for last-mile delivery.

Over the last few decades, electronic banking has been used widely to manage financial transactions worldwide. More recently electronic wallet (e-wallet) banking has been identified as an innovative mode of e-payment and enhances e-banking customer experience. Although e-wallet banking service is more secure, fast, convenient and cost effective, compared to conventional web-based banking, adoption of e-wallet application is limited among e-banking consumers. To address this issue, the current study has conceptualized task technology fit (TTF) model, diffusion of innovation (DOI) theory and protection motivation theory towards adoption of e-wallet service. Moreover, pandemic risk is studied as moderating factor between the relationship of e-wallet and use of e-wallet banking among banking consumers.

The research design of this study is based on positivism research paradigm. This study is cross-sectional and used deductive level of theory to formulate hypotheses. Research survey was conducted towards e-banking users. For statistical findings research framework is tested with 280 numerical responses. Data are estimated through partial least square structural equation modeling (PLS-SEM) approach.

Statistical results demonstrates that collectively factors underpinned protection motivation theory, TTF and DOI have shown large variance R² 65.7% in adoption of e-wallet. The effect size f² analysis has revealed that compatibility is one of the most influential factors in determining individual behavior to adopt e-wallet. Similarly, Geisser and Stone Q² analysis has disclosed substantial predictive power to predict adoption and use of e-wallet service.

Theoretically, this study integrates protection motivation theory, DOI theory and TTF model toward adoption of e-wallet service and hence contributes to information system literature. To practice this, research has suggested that factors such as pandemic risk, perceived severity and compatibility are most influential factors and hence need policy makers' attention to boost e-wallet adoption.

This study is original as the study develops an integrative research model to investigate e-banking user behavior to adopt of e-wallet service. Moreover, pandemic risk is tested as moderating factor between adoption and use of e-wallet which, in turn, enhance the value of this study and directs how to deal with existing and future pandemic crisis.

Due to the environmental concerns in our society, governments are moving towards green purchasing. However, public sector organizations have substantial internal problems. By using a theory of natural resource-based view, this study aimed to analyse the influence of leadership styles and innovation capabilities on green purchasing in the public sector organizations of a developing economy.

Data was collected from 199 purchasing professionals of public sector organizations, and hypotheses were tested through a quantitative method using partial least square-structural equation modelling with the help of SmartPLS version 4 to validate the measurement model.

This study identified that transformational leadership and delegation style of leadership have a significant and positive effect on innovation capability and green purchasing. Similarly, innovation capability mediates the relationship between leadership styles and green purchasing. However, transformational leadership found a more substantial effect on innovation capability and green purchasing than the delegation leadership style.

Results provide insight into the role of leadership styles in green purchasing and innovation capabilities in public sector organizations. Thus, addressing the important issues of how leadership styles and innovative capabilities (IC) can improve green culture, specifically green purchasing, to enhance ecological sustainability.

Results provide insight into the role of leadership styles in green purchasing and innovation capabilities in public sector organizations. Thus, it addresses how leadership styles and IC can improve green culture, specifically green purchasing, to enhance ecological sustainability.