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Social commerce (SC) is a new genre in electronic commerce (e-commerce) that has great potential. This study proposes a new research framework to address deficiencies in existing social commerce research frameworks (e.g. the information model).

In the era of Industrial Revolution 4.0 technologies and new social commerce (s-commerce) models, the authors believe that there is an immediate need for a new research framework. The authors analysed the progress of the s-commerce paradigm between 2003 and 2023 by applying longitudinal science mapping. The authors then developed a research framework based on the themes in the strategic diagrams and evolution map.

From 2003 to 2010, studies on s-commerce mainly focused on social networking sites, virtual communities, social shopping and analytic approaches. From 2011 to 2015, it shifted to s-commerce, consumer behaviour, Web 2.0, artificial intelligence, social technologies, online shopping, user studies, data gathering methods, applications, service-based social commerce constructs, e-commerce and cognitive factors. Social commerce remained the primary research paradigm from 2017 to 2023.

The SC framework may be analogous to popular research frameworks such as technology-organisation-environment (T-O-E) and stimulus-organism-response (S-O-R). Based on this SC framework, researchers may gain a better understanding by determining the factors of the social, commercial, technological and behavioural dimensions.

The authors redefined s-commerce and developed an SC framework. Practical guidelines for the SC framework and an exemplary research model are presented. Overall, this study offers a new research agenda for the extant understanding of s-commerce, with the SC framework as the next frontier of the theoretical advancements and applications of s-commerce.

The main aim of this study is to examine the effect of virtual store atmospheric factors on impulsive purchasing in the metaverse context.

Grounded in purposive sampling, 451 individuals with previous metaverse experience were recruited to accomplish the objectives of this research. Next, to identify both linear and nonlinear relationships, the data were analyzed using partial least squares structural equation modeling (PLS-SEM) and artificial neural network (ANN) approaches.

The findings underscore the significance of the virtual store environment and online trust in shaping impulsive buying behaviors within the metaverse retailing setting. Theoretically, this study elucidates the impact of virtual store atmosphere and trust on impulsive buying within a metaverse retail setting.

From the findings of the study, because of the importance of virtual shop content, practitioners must address its role in impulse purchases via affective online trust. The study’s findings are likely to help retailers strategize and improve their virtual store presentations in the metaverse.

The discovery adds to the understanding of consumer behavior in the metaverse by probing the roles of virtual store atmosphere, online trust and impulsive buying.

Since its inception, ChatGPT has been disruptively transforming how businesses operate along the whole value chain. The service sector is no exception from these technological advances. Given its potential and significance, five major areas whereby ChatGPT has great potential in services management are identified and discussed in terms of opportunities, challenges and research agendas: service marketing, customer experience, digital services, cost-effective service excellence, and ethical and corporate digital responsibility.

By adopting an expert-oriented perspective approach, the study leverages the expertise of 11 knowledgeable contributors from the fields of service and information systems to foresee the implications of ChatGPT in services. The article comprehensively examines the current body of literature and practices in ChatGPT and services and proposes a forward-thinking research agenda for service scholars and practitioners.

The contributors recognize that ChatGPT has the potential to transform service offerings significantly, enrich customer experiences, optimize service costs, and contribute to societal advantages through improved digital services. However, they also acknowledge the disruption ChatGPT may cause to traditional service practices, including the potential loss of human touch in services, challenges to privacy and security, and the potential negative outcomes affecting service consumers and employees in terms of inequality, biases, and misuse of ChatGPT.

This article introduces a groundbreaking investigation into the use of ChatGPT in services management. The originality is demonstrated by examining the potential and obstacles to applying ChatGPT in different service domains. In addition, this research serves as a guiding light for subsequent studies by suggesting an in-depth research agenda, including understanding the design and optimization of ChatGPT in the customer service journey, the role of ChatGPT in assisting service organizations to promote responsible services, and implications of ChatGPT on service stakeholders.

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.

This paper aims to investigate the triangular interconnections among supply chain finance (SCF), supply chain risk management (SCRM) and supply chain sustainability (SCS) within the context of small and medium-sized enterprises (SMEs) under the theoretical foundation of dynamic capabilities view.

A total of 319 valid data sets were gathered from SMEs in China to evaluate the research model. This study uses partial least square structural equation modelling and necessary condition analysis as the two statistical methodologies for the assessment.

The findings indicate that SCF positively impacts on both SCRM and SCS, whereas SCRM also positively influences SCS. Furthermore, it has been observed that SCRM partially mediates the connection between SCF and SCS.

The findings contribute to the literature of SCS by empirically validating the direct and mediating impacts of SCRM on SCS.

The results provide valuable insights that can assist SME stakeholders, owners and managers in developing strategies to effectively incorporate SCF and SCRM practices, thereby enhancing SCS performance.

This study expands the existing research on SCF and SCRM in the context of promoting SCS, specifically from the viewpoint of an Asian developing country.

The study aims to investigate the relationship between transformational, transactional leadership and employee retention with the mediating effect of employee engagement.

Using judgemental sampling, data were collected from 650 employees serving at different levels in the pharmaceutical industry of Bangladesh. Structural equation modeling was employed to test the hypothesized relationships using AMOS.

The study found that transformational and transactional leadership significantly impact employee retention. The direct effects of transformational leadership (TFL) on employee engagement were found to be significant, while transactional leadership (TSL) has no significant direct influence on employee engagement. The output of the mediation analysis revealed that employee engagement significantly mediates the relationship between TFL and employee retention, whereas it showed an insignificant relationship between TSL and employee retention.

Based on the findings and the literature support, it can be postulated that an appropriate leadership style, especially TFL, that drives employee engagement can influence employees to stay with the organization longer. The study recommends that managers and leaders comprehend the importance of leadership and its appropriateness to retain valued employees by ensuring high workplace engagement.

The study would provide a unique insight into TFL and TSL practices and their impact on the pharmaceutical industry’s employee retention. This study also extends the research on employee engagement as a mediator between TFL and TSL and employee retention.

Unlike previous research that primarily utilized structural equation modelling (SEM) to evaluate safety hazards in subway projects, this research aims to utilize a hybrid approach to investigate and scrutinize the key indicators of safety hazards leading to accidents, thereby hindering the progress of subway projects in China, taking into cognizance the multiple stakeholder’s perspective.

By administering a survey questionnaire to 373 highly involved stakeholders in subway projects spanning Changsha, Beijing and Qingdao, China, our approach incorporated a four-staged composite amalgamation of exploratory factor analysis (EFA), confirmatory factor analysis (CFA), covariance-based structural equation modelling (CB-SEM) and artificial neural network (ANN) to develop an optimized model that determines the causal relationships and interactions among safety hazards in subway construction projects.

The optimized model delineated the influence of individual safety hazards on subway projects. The feasibility and applicability of the model developed was demonstrated on an actual subway project under construction in Changsha city. The outcomes revealed that the progress of subway projects is significantly influenced by risks associated with project management, environmental factors, subterranean conditions and technical hazards. In contrast, risks related to construction and human factors did not exhibit a significant impact on subway construction progress.

While our study provides valuable insights, it is important to acknowledge the limitation of relying on theoretical approaches without empirical validation from experiments or the field. In future research, we plan to address this limitation by assessing the SEM using empirical data. This will involve a comprehensive comparison of outcomes derived from CB-SEM with those obtained through SEM-ANN methods. Such an empirical validation process is crucial for enhancing the overall efficiency and robustness of the proposed methodologies.

The established hybrid model revealed complex non-linear connections among indicators in the intricate project, enabling the recognition of primary hazards and offering direction to improve management of safety in the construction of subways.

The overarching goal of the study was to formulate an integrated research model to empirically demonstrate the complex interplay between heuristics, project characteristics, information system usage quality, empathy, and mindfulness in predicting users'/donors' donation behaviour and well-being in the context of donation-based crowdfunding (DBC) mobile apps.

The data were collected from 786 respondents and analysed using the multi-stage SEM-ANN-NCA (Structural equation modelling-artificial neural network-necessary condition analysis) method.

Increased perceived aesthetics, narrative structure, self-referencing, project popularity, project content quality, and initiator reputation would foster empathy. Empathy and mindfulness lead to donation behaviour, and, ultimately emotional well-being.

This study offers a clear framework by ranking the key contextual predictors and assessing the model’s necessity logic to facilitate crowdfunders' donation behaviour and well-being on DBC platforms. This research provides practical insights for bank marketers and further aids financial service providers in formulating an optimal DBC mobile app strategy.

This research investigates the factors that drive affluent customers to engage in sustainable behaviours, particularly their choice to stay in green hotels. The study aims to understand how green purchase intentions (GPI) translate into green purchase behaviours (GPB), focusing on how the scarcity of green hotels may influence this relationship.

Using a quantitative research method, the study examines several key predictors – such as ecological concern, perceived behavioural control, social norms and green attitudes – and their impact on GPI and GPB. Data were gathered from 418 affluent consumers through a structured survey, capturing their views on ecological concern, perceived control, social norms, green attitudes and related purchasing intentions and behaviours. The data were then analysed using SPSS and AMOS, with additional validation through artificial neural networks (ANN).

The findings indicate that ecological concern, perceived behavioural control, social norms and green attitudes significantly affect GPI among affluent consumers, and there is a strong positive correlation between GPI and GPB. Additionally, the study highlights that the unavailability of green hotels weakens the intention–behaviour link.

One limitation of this study is its reliance on self-reported data, which may be subject to social desirability bias and may not accurately reflect actual behaviour. Additionally, the study focuses on a specific context, green hotel purchases, which may limit the generalizability of the findings to other green consumer behaviours or industries. The cross-sectional nature of the study also prevents the establishment of causality between the constructs. Furthermore, the study may not account for other potential moderating variables, such as price sensitivity, brand loyalty or individual differences in environmental knowledge, which could also influence the relationship between green purchase intention and behaviour.

The research emphasizes the importance of perceived behavioural control and the detrimental impact of limited green hotel availability on the intention–behaviour relationship. The study provides practical insights for hotel managers, recommending clear communication strategies, deeper integration of sustainability practices and collaboration with policymakers to encourage sustainable consumer behaviours.

This study stands out by focusing on affluent consumers and their green purchasing habits, contributing valuable knowledge to the field of sustainable behaviour.