Green energy has received extensive attention worldwide for its outstanding contributions to fighting environmental damage. However, in recent years, there have been indications that the outlook for social acceptance of green energy adoption (GEA) is not optimistic, and potential difficulties and challenges from various aspects are possible in the future. To this end, a growing body of literature explores the determinants of GEA that will push towards greater social acceptance. Taking into account the current lack of an accessible holistic overview of the knowledge structure of GEA research and its determinants, high-level insights urgently needs to be provided. Therefore, the objective of this paper is to conduct a comprehensible bibliometric review of GEA research and the determinants of GEA. First, with the help of different bibliometric analyses, an in-depth view of GEA publications, looking at active authors, highly productive countries/regions, the most relevant journals, citation structures, and GEA's thematic evolution, is visually presented. Second, further supported by a content analysis, this work sorts out and identifies the key determinants of GEA in terms of technical matters, adopter levels, corporate promotions, and environmental challenges. Finally, the existing knowledge gaps, as well as possible future research directions, are summarized based on the above findings. The work presented in this paper will help scholars to obtain systematic knowledge and a structured understanding of GEA research and its determinants.

Green energy adoption and its determinants: A bibliometric analysis

Green energy has received extensive attention worldwide for its outstanding contributions to fighting environmental damage. However, in recent years, there have been indications that the outlook for social acceptance of green energy adoption (GEA) is not optimistic, and potential difficulties and challenges from various aspects are possible in the future. To this end, a growing body of literature explores the determinants of GEA that will push towards greater social acceptance. Taking into account the current lack of an accessible holistic overview of the knowledge structure of GEA research and its determinants, high-level insights urgently needs to be provided. Therefore, the objective of this paper is to conduct a comprehensible bibliometric review of GEA research and the determinants of GEA. First, with the help of different bibliometric analyses, an in-depth view of GEA publications, looking at active authors, highly productive countries/regions, the most relevant journals, citation structures, and GEA's thematic evolution, is visually presented. Second, further supported by a content analysis, this work sorts out and identifies the key determinants of GEA in terms of technical matters, adopter levels, corporate promotions, and environmental challenges. Finally, the existing knowledge gaps, as well as possible future research directions, are summarized based on the above findings. The work presented in this paper will help scholars to obtain systematic knowledge and a structured understanding of GEA research and its determinants. • Presenting a holistic evaluation of green energy adoption. • Key determinants of green energy adoption are highlighted from multiple perspectives. • Thematic evolution of the green energy adoption literature is identified. • The existing knowledge gaps and future possible research agendas for green energy adoption determinants are provided. 

A bibliometric analysis of creative industries: Current trends and future directions

Literature notes that firms are keen to develop big data analytics capability (BDAC, e.g. big data analytics (BDA) management and technology capability) to improve their competitive performance (e.g. financial performance and growth performance). Unfortunately, the extant literature has limited understanding of the mechanisms by which firms' BDAC affects their competitive performance, especially in the context of small and medium-sized enterprises (SMEs). Using resource capability as the theoretical lens, this paper specifically examines how BDAC influences SMEs' competitive performance via the mediating role of business models (BMs). Also, this study explores the moderating effect of COVID-19 on the relationship between BDAC and BMs. Supported by Partial Least Squares-Structural Equation Modelling (PLS-SEM) and data from 242 SMEs in China, this study finds the mediating roles of infrastructure and value attributes of BMs in enhancing the relationship of BDAC on competitive performance. Furthermore, the improvement of financial performance comes from the matching of BDA management capability with infrastructure attributes of BMs, while the improvements in growth come from the matching of BDA management capability and BDA technology capability with value attributes of BMs. The result also confirms the positive moderating effects of COVID-19 on the relationship of BDA management capability and value attributes of BMs. This study enriches the integration of BDAC and BMs literature by showing that the match between BDAC and BMs is vital to achieve competitive performance, and it is helpful for managers to adopt an informed BDA strategy to promote widespread use of BDAs and BMs. 

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The Source of SMEs’ Competitive Performance in COVID-19: Matching Big Data Analytics Capability to Business Models

Recent high-profile antitrust cases and policy proposals have put a spotlight on the relationship between firms’ access to big data and sustained competitive advantages in digital markets. In Europe, concerns about data-driven market power have led policy makers to propose far-reaching regulations of information technology (IT) in these markets. Despite the global policy relevance, the regulation of big data and its competitive effects has so far received little attention in information systems (IS) research. This article addresses this research gap by developing an overarching framework for future IS research on the role of IT for the regulation of data-driven market power. The proposed research framework builds upon a three-part analysis: First, we review the academic literature and show that there is extensive, although nuanced, empirical evidence for business value creation from big (user) data. Second, we draw on the resource-based view of the firm and recent policy reports to derive six facilitating factors that enable firms to establish market power based on sustained data-driven competitive advantages. Third, we characterize three regulatory approaches to govern market power and competition in data-driven digital markets: (i) empowering consumers, (ii) data openness and (iii) limiting data scale. For each of these approaches, we highlight the key role of IT artifacts in mediating the effect of regulatory rules on actual practice.

Siqi Liu

Papers

A bibliometric review of a decade of research: Big data in business research – Setting a research agenda