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Mobile payment (m-payment) has existed for over 25 years; however, there is no standard framework to guide scholars and practitioners in advancing m-payment research in the digital accelerated era. With this, this study aims to develop an m-payment framework and to analyse the evolution of m-payment research from 1997 to 2021. These were achieved by identifying the motor themes, basic and transversal themes, the emerging/declining themes and the highly developed but isolated themes. In addition, the publication trends of m-payment research were also identified.

A total of 1,999 articles of m-payment were identified from the Scopus database and 8,125 keywords were grouped into 483 word groups for the co-word analysis. Thematic networks were generated based on density and centrality. Performance analysis was performed on the themes of the four quadrants in the strategic diagrams. The m-payment framework was then developed based on the evolution map and a practical guide was built from the framework.

The m-payment framework consists of four dimensions, namely behaviour, technology, risk, and context. Some themes were declining while at the same time, m-payment remains strongly relevant and can stand the test of time. Several new themes have emerged in the 2013–2021 sub-periods.

This study is limited in that the study only investigates from the context of m-payment.

This study has provided a research framework (i.e. the m-payment framework) with a practical guide for scholars and practitioners to refer to, thus enabling them to embark on future studies without any hassle. The m-payment framework was developed based on empirical data using science mapping analysis of 1,999 articles.

The proposed m-payment research framework contributes towards more understanding of m-payment ten, usage amongst consumers and thus will help to reduce the rate of COVID-19 infection because m-payment is a contactless payment. Hence, the study may help in creating a safer and healthier society amid the unprecedented pandemic.

This study developed the m-payment framework based on empirical co-word analysis. A practical guide to extending the framework is also provided to guide the scholars and practitioners. Moreover, the evolution map for m-payment was created to understand the evolution of m-payment research. Practitioners may conduct market studies to unveil the factors that contribute to consumers' behaviours in m-payment in order to gain more understanding of the reasons behind their behaviours.

Though Blockchain has been studied in numerous contexts, the understanding of the impacts of Blockchain in achieving competitive advantages remains unexplored. Many industries, organizations and firms are still in a “wait and see” mode. This study aims at examining the effects of the technological, organizational and environmental factors drawn from the TOE framework in generating competitive advantage.

A dual-staged deep learning structural equation modeling artificial neural network analysis was conducted on 211 samples of small and medium enterprises. Four neural network models were engaged to rank the normalized importance of each of the predictor variables.

The research model can expound 57.99 and 47.33% of the variance in Blockchain adoption and competitive advantage correspondingly. The study successfully identified nonlinear relationships. The theoretical and managerial contributions are useful to scholars and practitioners such as industrial players, investors, chief executive officers (CEOs), managers, decision-makers and other stakeholders that intend to use Blockchain technology.

Unlike the existing technological–organizational–environmental (TOE) framework that uses a linear model and theoretically assumes that all relationships are linear, this has been the first study, which has successfully validated that there exist nonlinear relationships in the TOE framework. Further, very little has been theorized on the impacts of Blockchain adoption on competitive advantage, especially in the context of SMEs. Therefore, this study is the first one to provide the necessary theoretical foundation that may further extend the current knowledge of Blockchain technology adoption and its impacts.

The paper intends to examine mobile taxi (m-taxi) adoption, so as to close the gap in the current literature and clarify the behaviour of users by synthesising technological factors that are related to the characteristics of m-taxi applications with non-technological factors that are associated with the psychological characteristics of customers. The moderating effects of gender were also tested.

A self-administered questionnaire was adopted for data collection with 415 useable responses. The theoretical lens was tested via partial least squares-structural equation modelling. Additionally, state-of-the-art techniques such as permutation and multigroup analysis were applied.

Results indicate that social pressure, technology anxiety, effort expectancy, performance expectancy, and service and system quality are not significantly related to behavioural intention. Also, findings show no significant differences among gender in this study, which suggests that the model is invariant across gender groups.

This study provides a novel insight by taking a broader perspective of ride-hailing terminology by considering both taxis and private vehicles.

Given the emerging nature of integrating blockchain into food traceability systems, this study aims to investigate the intention to participate in a blockchain-based Halal traceability system through a united model that consists of Halal orientation strategy, institutional theory and diffusion of innovation theory.

A sample that consists of 143 Malaysian Halal food and beverage manufacturers was drawn from Halal Malaysia Official Portal using the simple random sampling technique. The responses were collected from the key managerial personnel with experience and knowledge on the Halal supply chain using phone interviews. Subsequently, the partial least squares structural equation modelling approach was then used to analyse the theoretical model.

The manufacturers would go through a chain of the process before deciding to participate in the traceability system. Firstly, the manufacturers which practice a comprehensive Halal orientation strategy will be more perceptive towards the institutional pressures that demand them to participate in a traceability system. Secondly, in response to the pressures, the manufacturers would evaluate the technological characteristics of the system and subsequently develop their perceived desirability. Thirdly, the manufacturers with favourable perceived desirability shall decide to participate in the system.

This study advances the current literature of Halal supply chain, information systems, operations management and blockchain through an integrated model that could explain 73.19% of the variance in intention to participate.

Under the pressure of dynamic business environments, firms in the banking and finance industry are gradually embracing Fintech, such as robo-advisors, as part of their digital transformation process. While robo-advisory services are expected to witness lucrative growth, challenges persist in the current landscape where most consumers are unready to adopt and even resist the new service. The study aims to investigate resistance to robo-advisors through the privacy and justice perspective. The human-like attributes are modeled as the antecedents to perceived justice, followed by the subsequent outcomes of privacy concerns, perceived intrusiveness and resistance.

An online survey was conducted to gather consumer responses about their perceptions of robo-advisors. Two hundred valid questionnaires were collected and analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM).

The results revealed that (1) perceived anthropomorphism and perceived autonomy are the positive determinants of perceived justice, (2) perceived justice negatively impacts privacy concerns and perceived intrusiveness and (3) privacy concerns and perceived intrusiveness positively influence resistance to robo-advisors.

The present study contributes to robo-advisory service research by applying a privacy and justice perspective to explain consumer resistance to robo-advisors, thereby complementing past studies that focused on the technology acceptance paradigm. The study also offers practical implications for mitigating resistance to robo-advisors.

The launch of ChatGPT has brought the large language model (LLM)-based generative artificial intelligence (GAI) into the spotlight, triggering the interests of various stakeholders to seize the possible opportunities implicated by it. Nevertheless, there are also challenges that the stakeholders should observe when they are considering the potential of GAI. Given this backdrop, this study presents the viewpoints gathered from various subject experts on six identified areas.

Through an expert-based approach, this paper gathers the viewpoints of various subject experts on the identified areas of tourism and hospitality, marketing, retailing, service operations, manufacturing and healthcare.

The subject experts first share an overview of the use of GAI, followed by the relevant opportunities and challenges in implementing GAI in each identified area. Afterwards, based on the opportunities and challenges, the subject experts propose several research agendas for the stakeholders to consider.

This paper serves as a frontier in exploring the opportunities and challenges implicated by the GAI in six identified areas that this emerging technology would considerably influence. It is believed that the viewpoints offered by the subject experts would enlighten the stakeholders in the identified areas.

Ever since its emergence, the metaverse has presented opportunities and disruptions to every stakeholder, including individual users and organizations. This article aims to offer valuable perspectives on six identified critical areas that the metaverse could significantly impact: marketing ethics, marketing communication, relationship marketing, retail marketing, supply chain management and transportation management.

Through a multi-perspective approach, this paper gathers valuable perspectives from various invited contributors to each of the six identified key areas that the metaverse could significantly impact.

For each key area identified, the invited contributors first share their valuable perspectives by discussing the roles of the metaverse. Subsequently, the invited contributors discuss their views on vital opportunities, challenges and research agenda concerning the metaverse.

With the widespread metaverse, it is expected that each key area identified is likely to undergo significant levels of disruption. Against this backdrop, this paper contributes to the academic literature and industry by gathering different perspectives from invited contributors on the relevance of the metaverse in marketing and logistics domains.

Considering the lack of understanding of the mobile applications (mobile apps) market and low usage rates among Malaysians, Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) was adapted to investigate the determinants of consumer behavioural intention (BI) to use mobile apps.

A total of 288 sample data was collected and analysed using partial least square equation modelling (PLS-SEM) method.

All of UTAUT2 constructs (i.e. performance expectancy, effort expectancy, facilitating conditions, hedonic motivation, and habit), except for price value and social influence, significantly relate with BI to use mobile applications. Habit was reported to have the strongest influence. Gender and educational level were found to be insignificant moderators.

Mobile application developers could have better understanding on users’ needs and intention, based on the findings.

In order to shed light on current problems, and there is a dearth in relevant studies which could resolve the issue, this paper contributes the necessary knowledge on mobile apps acceptance to developers. Educational level was added into UTAUT2 as a moderator in addition to gender.

Managing mega infrastructure projects (MIPs) is more complex because of time, size, social, environmental and financial implications. This study aims to address the management approaches, complexity and risk factors involved in MIPs. The study focuses on project success criteria and their individual effects on the success of MIPs.

To address the challenges and identify the most influencing factor for the success of MIPs, the study deployed a cross-sectional survey approach. Six hundred eighty-two usable samples were collected from the respondents to understand the impact of predetermined factors on the success of MIPs. The structural equation model and artificial neural network approach were used to derive the importance of factors affecting the success of MIPs.

The study's outcome confirms that all three influencing factors: feasibility studies, community engagements and contract selection, have a significant positive impact on the success of MIPs. Community engagement amongst all three has the most influential predictor for the success of MIPs.

The developed model will enable practitioners and policymakers from Indian construction companies and other emerging nations to concentrate on recognized risk reduction variables to enhance project success criteria and project management success, especially for MIPs.