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Despite the burgeoning popularity of virtual gifting in live streaming, research lacks an in-depth understanding of the drivers behind this behavior. Using para-social relationship (PSR), this study aims to capture viewers’ lively social feelings toward the streamer as the key factor leading to the purchase behavior of virtual gifts. It also aims to establish a theoretical link between PSR and viewers’ holistic experience in live streaming as captured by cognitive absorption and aims to investigates the role of technological features (i.e. viewer–streamer and viewer–viewer interactivity, streamer-level and viewer-level deep profiling and design aesthetics) in shaping viewers’ experience.

Based on 433 survey responses, this study employs a combination of structural equation modeling and neural networks to offer valuable insights into the relationships between the technological environment, viewer experience and viewer behavior.

Our results highlight the salience of PSR in promoting the purchase of virtual gifts through cognitive absorption and the importance of the technological environment in eliciting the viewer experience. This study sheds light on the development of PSR in a technological environment and its relationship with cognitive absorption.

By applying PSR to conceptualize viewers’ perceived connection with the streamer, this study extends the research on purchase behavior in the non-shopping context by providing an enlightened understanding of virtual gift purchase behavior in live streaming. Moreover, by theoretically linking PSR with cognitive absorption, virtual gift purchase and technological features of live streaming, it enriches the theory of PSR and bridges the gap between the design practice of supporting the IT infrastructure of live streaming and research.

Motivated by empirical features that characterize cryptocurrency volatility data, the authors develop a forecasting strategy that can account for both model uncertainty and heteroskedasticity of unknown form. The theoretical investigation establishes the asymptotic optimality of the proposed heteroskedastic model averaging heterogeneous autoregressive (H-MAHAR) estimator under mild conditions. The authors additionally examine the convergence rate of the estimated weights of the proposed H-MAHAR estimator. This analysis sheds new light on the asymptotic properties of the least squares model averaging estimator under alternative complicated data generating processes (DGPs). To examine the performance of the H-MAHAR estimator, the authors conduct an out-of-sample forecasting application involving 22 different cryptocurrency assets. The results emphasize the importance of accounting for both model uncertainty and heteroskedasticity in practice.

Given the cryptocurrency market boom in recent years, this study aims to identify the factors influencing cryptocurrency pricing and the major gaps for future research.

A systematic literature review was undertaken. Three databases, Scopus, Web of Science and EBSCOhost, were used for this review. The final analysis comprised 88 articles that met the eligibility criteria.

The influential factors were identified and categorized as supply and demand, technology, economics, market volatility, investors’ attributes and social media. This review provides a comprehensive and consolidated view of cryptocurrency pricing and maps the significant influential factors.

This paper is the first to systematically and comprehensively review the relevant literature on cryptocurrency to identify the factors of pricing fluctuation. This research contributes to cryptocurrency research as well as to consumer behaviors and marketing discipline in broad.

This article aims to clarify the impact of stock market liberalization on corporate green technology innovation, analyze its mechanism from the perspectives of financing constraints and environmental management level and explore heterogeneity.

Using the panel data of Chinese enterprises from 2010 to 2020, this article adopts the multi-point difference-in-difference (DID) method to test the impact of stock market liberalization on enterprise green technology innovation and its conduction pathway.

The outcomes demonstrate that stock market liberalization contributes to the furthering of green technology innovation. The heterogeneity test reveals that this promotion is more pronounced for private companies, small-scale companies and companies with high information transparency. The mediating effect test shows that stock market liberalization boosts green technology innovation by alleviating corporate financing constraints and improving corporate environmental management.

This article elucidates the impact path of stock market liberalization on corporate green innovation based on alleviating corporate financing constraints and improving corporate environmental management levels. From the perspective of corporate green technology innovation, this article provides evidence from emerging market countries for the economic effects of capital market opening, which helps to further improve the level of green innovation.

This paper aims to present the vertical integration state-of-the-art and propose an expansion of the operations and supply chain management (OSCM) field by identifying gaps and bottlenecks.

This paper uses a systematic literature review based on a sample of 173 OSCM field articles, collected from Scopus and Web of Science databases.

There are no single factors, such as future costs, structures or skills development, in the decision to vertically integrate operations. It is necessary to combine the vision of production costs with the perspective of governance and transaction costs. In addition, it is essential to consider the competency perspective and its impact on capability building.

Few studies have attempted to understand how vertical integration is used in terms of OSCM research themes and theories. Vertical integration can help companies face challenges and serve as a potential solution for achieving better prices, demand control and quality management.

The significant role of vertical integration mechanisms in supply chains is crucial for managers evaluating a firm's reconfiguration with more vertical operations. Policymakers interested in supporting the smoothness of vertical integration decisions in regulatory agencies play a key role as contingencies.

In times of global challenges, vertical integration is a strategy known to be more effective for firms to obtain a competitive advantage, making them more resilient.

This paper addresses gaps in the vertical integration theme and provides insights for future research development.

Building information modelling (BIM) has transformed the traditional practices of the Architecture, Engineering and Construction (AEC) industry. BIM creates a collaborative digital representation of built environment data. Competitive advantage can be achieved with collaborative project delivery and rich information modelling. Despite the abundant benefits, BIM’s adoption in the AEC is susceptible to confrontation. A substantial impediment to BIM adoption often cited is data interoperability. Other facets of interoperability got limited attention. Other academic areas, including information systems, discuss the interoperability construct ahead of data interoperability. These interoperability factors have yet to be surveyed in the AEC industry. This study aims to investigate the effect of interoperability factors on BIM adoption and develop a comprehensive BIM adoption model.

The theoretical foundations of the proposed model are based on the European interoperability framework (EIF) and technology, organization, environment framework (TOE). Quantitative data collection from construction firms is gathered. The model has been thoroughly examined and validated using partial least squares structural equation modelling in SmartPLS software.

The study’s findings indicate that relative advantage, top management support, government support, organizational readiness and regulation support are determinants of BIM adoption. Financial constraints, complexity, lack of technical interoperability, semantic interoperability, organizational interoperability and uncertainty are barriers to BIM adoption. However, compatibility, competitive pressure and legal interoperability do not affect BIM adoption.

Finally, this study provides recommendations containing the essential technological, organizational, environmental and interoperability factors that AEC stakeholders can address to enhance BIM adoption.

To the best of the authors’ knowledge, this paper is one of the first studies to combine TOE and EIF in a single research model. This research provides empirical evidence for using the proposed model as a guide to promoting BIM adoption. As a result, the highlighted determinants can assist organizations in developing and executing successful policies that support BIM adoption in the AEC industry.

This paper aims to explore how open innovation communities contribute to the adoption of building information modelling (BIM) in the construction industry.

The paper presents a cross-case analysis of two construction communities, buildingSMART Norway and the BIM Vietnam Community. Data were collected based on 21 semi-structured interviews conducted with industry experts actively engaged in these two communities. The theoretical basis for the study was open innovation and the institutional intervention model, which delineates institutional actions related to the adoption of new information technology.

The findings show both similarities and differences in the way in which the communities contribute to industrial practice. Both communities use similar knowledge channels and repositories but apply different approaches to innovation creation and diffusion. In addition, trust can support BIM innovation in the community context.

The comparison of buildingSMART Norway and the BIM Vietnam Community in accelerating BIM innovation allows for exploring how open innovation communities support BIM adoption in the construction industry. The findings provide insights for construction communities into creating and diffusing BIM innovation. In addition, the examples of gaining benefits from community innovation activities are useful for construction firms and practitioners.

The construction business is widely recognised for its inherent complexity and dynamic nature, which stems from the nature of the job involved. The industry is often regarded as one of the most challenging industries globally in terms of implementing environmental, health and safety (EHS) practices. However, in the absence of EHS, the construction industry cannot be considered sustainable. Therefore, this study aims to identify the trends, knowledge gaps and implications of EHS research to enhance construction activities and knowledge.

The study adopted a science mapping approach involving bibliometric and scientometric analysis of 407 construction EHS publications from the Scopus database with the VOSviewer software. The study is based on journal articles from the Scopus database without restriction to any time range.

The main focus of construction EHS research identified in the study includes sustainability-related studies, risk-related, environmental issues, EHS management, integrated management systems studies, health and safety related and EHS in the construction process. Some emerging areas also identified include productivity, design, culture, social sustainability and machine learning. The most influential and productive publication sources, countries/regions and EHS publications with the highest impact were also determined.

Documents published in the Scopus database were considered for analysis because of the wider coverage of the database. Journal articles written in English language represent the inclusion criteria, whereas other documents were excluded from the analysis. The study also limited the search to articles with the engineering subject area.

The research findings will enlighten stakeholders and practitioners on the focal knowledge areas in the EHS research domain, which are vital for enhancing EHS in the industry.

To the best of the authors’ knowledge, this review-based study is the first attempt to internationally conduct a science mapping on extant literature in the EHS research domain through bibliometric and scientometric assessments.

COVID-19 has made businesses increasingly dependent on technology to be competitive and efficient. Small and medium enterprises (SME) digitalisation and innovation research are widespread. SME digital transformation and innovation require government policies, initiatives and assistance. How the government can help SMEs achieve these goals is unclear. So, this paper aims to investigate how government policy may assist Vietnamese SMEs to boost innovation performance and digital transformation.

The study will take a quantitative approach, with questionnaires distributed to 659 respondents from SMEs in Vietnam through snowball and convenience sampling procedures. The structural equational modelling method is used for data analysis.

The study indicated that government policies supported Vietnamese SMEs’ innovation and information technology (IT) capabilities. Government policy assistance also boosted IT capabilities and innovation. Furthermore, mediation effects show that digital transformation fully mediates the relationship between innovativeness and firm performance, whereas IT capabilities partially mediate this relationship.

Further research that replicates the findings and analyses contextual heterogeneities between nations is advised because Vietnam’s pandemic setting was both similar and dissimilar.

The study demonstrated government-company interactions through supportive policy. It investigated whether SMEs seeking digital transformation and innovativeness might gain competitive benefits by implementing effective knowledge management and enhancing their IT capabilities.

A resource-based theoretical framework is extended to study how innovation, public policy and digital transformation for SMEs interact. The study confirms government policy strongly influences enterprises’ digital development. Specifically, the new mediating effects of IT capabilities and digital transformation are explored and provide new insights into the existing literature.

Aim to the limitations of grey relational analysis of interval grey number, based on the generalized greyness of interval grey number, this paper tries to construct a grey angle cosine relational degree model from the perspective of proximity and similarity.

Firstly, the algorithms of the generalized greyness of interval grey number and interval grey number vector are given, and its properties are analyzed. Then, based on the grey relational theory, the grey angle cosine relational model is proposed based on the generalized greyness of interval grey number, and the relationship between the classical cosine similarity model and the grey angle cosine relational model is analyzed. Finally, the validity of the model in this paper is illustrated by the calculation examples and an application example of related factor analysis of maize yield.

The results show that the grey angle cosine relational degree model has strict theoretical basis, convenient calculation and is easy to program, which can not only fully utilize the information of interval grey numbers but also overcome the shortcomings of greyness relational degree model. The grey angle cosine relational degree is an extended form of cosine similarity degree of real numbers. The calculation examples and the related factor analysis of maize yield show that the model proposed in this paper is feasible and valid.

The research results not only further enrich the grey system theory and method but also provide a basis for the grey relational analysis of the sequences in which the interval grey numbers coexist with the real numbers.

The paper succeeds in realizing the algorithms of the generalized greyness of interval grey number and interval grey number vector, and the grey angle cosine relational degree, which provide a new method for grey relational analysis.