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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.

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.

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.

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.

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.

Manufacturing capability is a crucial component of every nation’s economy and pharmaceuticals are frequently a significant part of the manufacturing sector. Pharmaceutical supply chains are essential to health-care systems, contributing to living quality and shorter hospital stays. This study aims to examine the role of multiple integrations on business performance (BP) through supply chain flexibility (SCF) and supply chain agility (SCA).

Data was collected from 198 supply chain professionals in the pharmaceutical sector of the developing economy of Pakistan. The sample was collected based on a nonprobability purposive sampling approach. A five-point Likert-scale survey was used and analyzed with the PLS-SEM technique using SmartPLS 4.

This study found that process integration (PI) does not affect SCA, whereas relationship integration and measurement integration positively affect SCA. SCA positively impacts BP. In contrast, all integrations significantly influenced supply flexibility and BP except for PI. Finally, SCF significantly mediates the relationship between all integrations and BP.

This study examined the relationships of multiple integrations on BP, directly and indirectly, through SCF and agility. The theory of dynamic capabilities has been applied and extended to increase the comprehensiveness of the findings. A developing economy’s pharmaceutical industry supply chain was examined, producing empirical evidence of the results.