Keng-Boon Ooi

Technological transformation has gained worldwide attention, with a significant impact on industrial development over the past few years. Several advanced technological solutions, including cloud c...

The world is shifting, and eco-friendly products are gaining increasing attention.1 As material consumption rises, people are experiencing increasingly severe pollution from product usage.2 With th...

Purpose: This study examines the intellectual evolution of marketing and logistics scholarship by analysing how themes, collaborations, and knowledge structures in the Asia Pacific Journal of Marketing and Logistics (APJML) have developed over the past decade, with particular attention to the journal's shift toward intelligence-driven and human-centred research. Design/methodology/approach: Using bibliometric and science-mapping techniques, we analyse 1,304 Web of Science-indexed APJML articles published between 2015 and 2025 with Bibliometrix / Biblioshiny. Guided by a conceptual framework and four propositions (P1-P4), the analysis integrates performance indicators, collaboration networks, and longitudinal thematic mapping, supported by three theory-informed measures capturing regionalisation dynamics, intelligence-oriented thematic inclusion, and collaboration polycentricity. Findings: The results reveal a systematic transition from efficiency-oriented research emphasising performance and satisfaction toward intelligence-driven themes centred on digital enablement, analytics, sustainability, and human-centred service ecosystems. Consistent with P1 and P3, knowledge production becomes increasingly Asia-Pacific-anchored yet polycentric, with China, Australia, and Malaysia acting as interdependent hubs rather than a single dominant centre. In line with P2, AI-related and analytics-related themes exhibit growing inclusion and acceptance over time, displacing purely efficiency-focused constructs. Supporting P4, the interaction between regional collaboration and digital enablement accelerates the diffusion of intelligence-driven and human-centred research agendas. Originality/value: Rather than offering descriptive mapping alone, this study advances bibliometric research by theorising how regionalisation, thematic drift, and collaboration structure jointly shape the evolution of marketing and logistics knowledge. By articulating a proposition-driven framework and introducing theory-informed indicators, the study positions APJML as a key conduit for regionally grounded yet globally relevant intelligence-driven scholarship.

The traditional supply chain model can adapt to changes in environmental regulations in real time through the adoption of artificial intelligence. However, empirical evidence on how GAI‐enabled gradual, multistage capabilities can be built within the framework of green supply chain management (GSCM) by extending the theoretical concept of dynamic capability theory (DCT) remains limited in the existing literature. Three hundred thirty‐eight survey data were collected using a structured questionnaire and a 5‐point Likert scale to quantify responses, which were analysed using SEM. The results have revealed direct correlations among the main study constructs, which show different layers of capabilities in a green supply chain, that is, flexible information system (FIS), responsiveness, risk mitigation competency (RMC) and the final output, GSCM performance. The study findings confirmed a significant enhancement of GSCM performance by FIS through direct and indirect serial mediation effects of responsiveness and RMC, which are consistent with the fundamental concepts of DCT. Additionally, the study has evaluated the moderating effect of GAI convenience (GAIC) and risk avoidance (RA) to establish the pivotal role of GAI in GSCM. The findings of the moderation analysis depict that higher values of GAI convenience and risk avoidance amplify the positive correlation between supply chain capabilities across multiple stages and GSCM performance. The study has significant managerial and theoretical implications that contribute to the existing literature and provide guidelines for managers to achieve high levels of GSCM performance. Additionally, the present study provides in‐depth insights into how GAI can capture environmental and market changes in real time and make quick decisions to adjust the system as early as possible.

Augmented reality (AR) technologies are a disruptive innovation that is reshaping innovation strategies in luxury retail. This study developed a framework to explain how the attributes of AR technologies, namely AR quality, haptic imagery and customisation, shape consumer outcomes in luxury retail. A mixed‐methods design was employed. In Study 1, the Delphi method was used to identify the most salient AR attributes. In Study 2, 257 consumers completed an online questionnaire. Data were analysed using a combined importance‐performance map. The findings show that AR quality, haptic imagery and customisation positively affect self‐explorative engagement. In turn, self‐explorative engagement enhances psychological ownership, which drives willingness to pay a premium. Self‐brand connection also emerged as a significant moderator. This study contributes to luxury retail research by revealing how AR technologies enhance willingness to pay a premium.

Purpose: This study aims to examine the effect of data-driven supply chain (DDSC) on artificial intelligence (AI) and supply chain sustainability (SCSU) including supplier sustainable development, environmental sustainability and social sustainability. The scanning, interpretation, action and performance (SIAP) model is used in this study to explain the research model. Design/methodology/approach: Using a sample of 216 responses, collected from managers of manufacturing small and medium-sized enterprises (SMEs) via purposive sampling, this study applied partial least squares structural equation modeling (PLS-SEM), necessary condition analysis (NCA) and importance performance map analysis (IPMA) to test the impact of DDSC on AI and SCSU in the context of Malaysia. Findings: The findings from multiple statistical techniques indicate that DDSC is positively associated with AI and SCSU. Besides, AI plays a mediating role between DDSC and SCSU. These findings argue that DDSC and AI are the important factors that enhance SCSU outcomes, thus prioritizing DDSC in achieving excellence in SCSU and reaching sustainable development goals. Practical implications: The findings indicate that managers should strategically implement DDSC aligned with sustainability goals to improve real-time data utilization, reduce waste and optimize resource allocation. Integrating AI-driven analytics improves SC responsiveness and decision-making. Hence, firms should invest in digital capabilities to maximize these benefits and foster inclusive and effective SCSU outcomes. Originality/value: To the best of the authors' knowledge, this article extends the sensing, interpretation, action and performance pillars of the SIAP model by integrating DDSC and AI to comprehend SCSU in manufacturing SMEs in the emerging economy of Malaysia. It conceptualizes AI as a mediator capability inherent within DDSC using PLS-SEM, NCA and IPMA to reveal both sufficiency and necessity conditions for SCSU outcomes.

Purpose: Given the cultural diversity of live commerce audiences and the intensifying competition that makes retaining existing consumers ever more difficult, this study investigates how streamers' cultural intelligence shapes consumers' relationships with these platforms and, by extension, their continued, extended use of live commerce. Design/methodology/approach: A total of 599 valid responses were gathered through a cross-sectional, online questionnaire survey and analyzed using Partial Least Squares Structural Equation Modelling. Findings: The results indicate that streamers' behavioural cultural intelligence positively influences consumer engagement, which in turn promotes key platform outcomes, namely satisfaction, love and loyalty. These attitudes stimulate usage intention, ultimately prompting continued and extended use of live commerce, reflected in usage behaviour, experience response and cross-category usage. Practical implications: This study yields valuable insights for practitioners. It stresses the need to account for cultural diversity within even national borders. Recognizing streamers as key human touchpoints in live commerce, this study underscores the need for platforms to develop and train streamers' cultural intelligence, which is found critical for retaining existing consumers and ensuring platform sustainability and, by extension, sectoral growth. Originality/value: By examining how streamers' cultural intelligence affects consumers' continued and extended use of live commerce, this study advances existing knowledge of the streamer's role in consumer retention. This cultural lens also adds new insight to source characteristics, extending beyond those typically featured in conventional source-effect models (e.g. credibility).

This study examines the influence of ecological responsibility, legitimation, and competitiveness on the intention of Taiwanese SMEs to adopt carbon reduction practices. It further investigates whether these intentions translate into actual implementation and explores the moderating role of employee green efficacy in this relationship. Data were collected through a questionnaire survey of Taiwanese SMEs. A total of 326 valid responses were analyzed using regression analysis to test the proposed hypotheses. Findings reveal that ecological responsibility is the most significant predictor of adoption intention, followed by competitiveness, while legitimation exerts the weakest effect. Employee green efficacy significantly moderates the relationship between intention and implementation, increasing the likelihood of action. These findings advance the literature on SME environmental strategy by extending Bansal and Roth's ecological responsiveness model through the integration of the theory of planned behavior alongside institutional and social cognitive perspectives. By highlighting the role of employee green efficacy in strengthening the translation of intentions into action, the study offers a theoretically enriched understanding of how cognitive and institutional mechanisms jointly drive SME carbon reduction. Practically, the results provide actionable insights for policymakers and SME managers seeking to facilitate effective transitions toward reduced carbon emissions.

Purpose: This study aims to examine the impact of data governance (DG) on supply chain (SC) resilience, focusing on the mediating effect of IR4.0 and the moderating impact of environmental uncertainty in the context of Malaysia. Design/methodology/approach: In this study, data were collected from managers of the Electrical and Electronics industry in Malaysia using a questionnaire survey approach. Researchers applied Partial Least Squares Structural Equation Modelling (PLS-SEM) to analyze 204 valid responses. Findings: The findings from PLS-SEM indicate that DG significantly improve both IR4.0 and SC resilience in Malaysia. Besides, IR4.0 has a mediating effect on the relationship between DG and SC resilience, whereas environmental uncertainty has no moderating impact on the relationship between DG and SC resilience in Malaysia. Research limitations/implications: The policymakers and practitioners should focus on data management in terms of structural, procedural and relational practices to align organizational resources with SC networks. Managers in IR4.0 should also prioritize the integration of robust DG frameworks into IR4.0 technologies to ensure the improvement in organizational resilience and enhancement in response to disruptions. Originality/value: The originality of this research lies on the significance of DG framework and SC resilience, applying technological aspects and using analytical models. Moreover, this is the early study that examined the underexplored impact of DG on enhancing SC resilience. Moreover, this research adds the originality by identifying DG practices and the mediating role of IR4.0 that assist in achieving SC resilience in Malaysia.