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The current gap between the required and available artificial intelligence (AI) professionals poses significant challenges for organisations and academia. Organisations are challenged to identify and secure the appropriate AI competencies. Simultaneously, academia is challenged to design, offer and quickly scale academic programmes in line with industry needs and train new generations of AI professionals. Therefore, identifying and structuring AI competencies is necessary to effectively overcome the AI competence shortage.

A probabilistic topic model was applied to explore the AI competence categories empirically. The authors analysed 1159 AI-related online job ads published on LinkedIn.

The authors identified five predominant competence categories: (1) Data Science, (2) AI Software Development, (3) AI Product Development and Management, (4) AI Client Servicing, and (5) AI Research. These five competence categories were summarised under the developed AI competence framework.

The AI competence framework contributes to clarifying and structuring the diverse AI landscape. These findings have the potential to aid various stakeholders involved in the process of training, recruiting and selecting AI professionals. They may guide organisations in constructing a complementary portfolio of AI competencies by helping users match the right competence requirements with an organisation's needs and business objectives. Similarly, they can support academia in designing academic programmes aligned with industry needs. Furthermore, while focusing on AI, this study contributes to the research stream of information technology (IT) competencies.

Managerial “awareness” of supply chain management (SCM) principles is a key antecedent of SCM adoption. However, supply chain awareness (SCA) provides fertile ground for further development. The authors combine extant research with the attention-based view of the firm to further develop SCA and theorize about its effect in an understudied context.

The authors combine SCA with supply chain orientation, of which awareness is central. The authors combine qualitative and archival data for a 10-year period to test SCA in nonprofits. SCA was measured unobtrusively to avoid respondent bias; then, the authors explore how SCA relates to revenue generation from services provided.

SCA correlates positively with revenue generation. Drawing on a contingency perspective, the authors test two moderators relevant to nonprofits. The positive effect of SCA on revenue is stronger for nonprofits collocated in cities with corporate headquarters but weaker for those with larger boards.

The study further advances the notion of awareness for studying SCM phenomena and provides evidence of its relevance in the unexamined context of human services nonprofit organizations (NPOs). This work has implications for how attention to SCM principles shapes organizational outcomes, the factors that moderate these relationships and the importance of unobtrusively measuring awareness in SCM research. The authors used WayBack Machine to harvest websites. However, the quality and depth of text obtained prior to 2008 were lower than those of later years. Additionally, archival data for NPOs are limited.

Findings inform about the fit between nonprofit resources, type of board and fit with how to fund operations. This research provides an alternative way for policy makers to assess NPO capacity by focusing on the fundamental SCM concepts.

The authors contribute to the dialogue about NPOs developing financial independence through revenue generation from services sold to end customers.

NPOs are seldom studied in SCM. This is an attempt to study NPOs by combining qualitative and quantitative data.

The purpose of this study is to explore the antecedents of digital technology adoption by firms, specifically the role of strategic leader social ties such as board networks and executive academic connections in promoting digital transformation. Moreover, the authors also aim to examine the moderating effect of exploratory innovation strategy on the relationship between board networks, academic connections and digital transformation.

This study uses the panel data of Chinese A-share listed companies from 2010 to 2019. Through text analysis of data such as company annual report, media interaction, asset annotation and International Patent Classification, the authors measure degrees of digital transformation from four dimensions: management attention, media discussion, digital input and digital output. Further, this study employs social network analysis and instrumental variable method to examine the causal relationship between strategic leader social ties and digital transformation.

The study finds that an expansive board network can significantly promote the digital transformation process of companies, in which academic connection of senior executives plays a positive synergistic role with board network. Additionally, firms with exploratory innovation strategies are more likely to utilize board networks to accelerate their digital transformation process.

One limitation of this study is the use of Chinese A-share listed companies as the sample, which may limit the generalizability of the findings to other contexts. Additionally, the study focuses only on two types of strategic leader social ties and does not consider other potential antecedents of digital transformation.

This research provides insights for governments to promote digital economy and industrial upgrading. Policymakers can facilitate industrial digital transformation by creating a supportive policy environment that encourages university–industry collaboration. By fostering academic entrepreneurship and cross-border knowledge transfer, governments can create a thriving ecosystem for digital innovation, thereby enhancing industrial competitiveness and economic growth.

This study helps to improve social welfare. By reducing production costs and enhancing customer experience, digital transformation increases economic surplus for both consumers and manufacturers, enabling society as a whole to benefit from the digital dividend. By promoting collaboration across borders and embracing a digital-friendly culture, businesses and governments can achieve long-term success in the digital age and contribute to building more prosperous and sustainable societies.

This research makes several contributions to the literature on digital transformation and leadership. Firstly, this paper empirically examines the role of board network and executive academic connection in promoting the adoption of digital technology, filling the research gap of leadership antecedents of digital transformation. Secondly, the authors put forward a relatively comprehensive measure for digital transformation, which could help to advance the literature on digital transformation and provide a more nuanced perspective on this topic. Finally, the paper enriches the theoretical understanding of board network and executive academic connection from the perspective of social capital theory and organizational learning theory.

Tracking trends in new technology funding patterns is essential for venture scaling. The emerging advanced digital technologies (ADT) such as virtual reality (VR), artificial intelligence (AI), blockchain and Internet-of-things (IoT) promote business innovation adaptations, and in turn, reshape the industrial landscape. To attract nascent funding for such prospective projects among the public, well-articulated project pitches that are equipped with effective marketing communication convey the projects' importance and marketability. Specifically, when the entrepreneurs and the crowdfunding platform users interact via different types of crowdfunding platforms, pitch framing, including the signaling of ADT terms, project location and fundraising goal, becomes imperative to help facilitate crowdfunding success.

Drawing on data collected from six leading US-based equity and reward-based crowdfunding platforms in 2020, an empirical study was performed. Using the text analysis approach, the authors examined the positive effects of incorporating technology orientation on crowdfunding success. While the effect between the project description's signaling of geographic location, fundraising goal and articulation style on fundraising success, while controlling for project and platform characteristics.

The results suggested that the technology-orientated projects are more likely to achieve better fundraising outcomes. Taking crowdfunding platform types, project locations, minimum fundraising goals and articulation with analytical and authentic into consideration, the results still hold.

Building on the theoretical framework of signaling theory, the authors consider the crowdfunding-specific contextual factors to enhance the understanding of the positivity impact of technology orientation. By such addition, it facilitates more effective strategic composition of entrepreneurs' fundraising conversations.

This paper aims to examine how and why consumers respond to chief executive officer (CEO) activism on social media. The authors developed a conceptual model that proposes impression management as a mechanism for consumer response to CEO activism.

In Study 1a, the authors examined 83,259 tweets from 90 CEOs and compared consumer responses between controversial and noncontroversial tweets. In Study 1b, the authors replicated the analysis, using a machine-learning topic modeling approach. In Studies 2 and 3, the authors used experimental designs to test the theoretical mechanism.

On average, consumers tend to respond more to CEO posts dealing with noncontroversial issues. Consumers’ relative reluctance to like and share controversial posts is motivated by fear of rejection. However, CEO fame reverses this effect. Consumers are more likely to engage in controversial activist threads by popular CEOs. This effect holds for consumers high (vs low) in public self-consciousness. CEO fame serves as a “shield” behind which consumers protect their online image.

The study focused on Twitter (aka “X”) in the USA. Future research may replicate the study in other social media platforms and countries. The authors introduce “shielding” – liking and sharing content authored by a recognizable source – as a tactic for impression management on social media.

Famous CEOs should speak up about controversial issues on social media because their voice helps consumers engage more in such conversations.

This paper offers a theoretical framework to understand consumer reactions to CEO activism.

The purpose of this study is to examine how crowdfunding backer perceptions of market orientation and foreignness impact crowdfunding performance in emerging economies.

Using content analysis software, the authors analyzed 756 Kickstarter campaign narratives from the emerging economies of Brazil, Russia, India, China, and South Africa for the period between 2009 and 2019.

The authors’ results show that behavioral market orientation signals are positively related to amounts raised while decision criteria signals are negatively related. The authors also find that foreign entrepreneur status interacts with the two market orientations to impact funding amounts.

When creating crowdfunding campaigns in emerging economies, domestic entrepreneurs should use high levels of behavioral market orientation rhetoric but low levels of decision criteria rhetoric within their campaign narratives.

This study unpacks the components of market orientation and examines their positive and negative effects on crowdfunding success in the context of emerging economies.

The literature on knowledge management in sustainable supply chain (KMSSC) has witnessed significant growth in the past two decades. However, a scientometric review that consolidates the primary trends and clusters within this topic has been notably absent. This paper aims to scrutinize recent advancements and identify the intellectual underpinnings of KMSSC research conducted between 2002 and 2022.

The present review employs a scientometric analysis approach via visualization maps of prolific contributions, co-citation, co-occurrence and thematic networks to examine a total of 114 articles and conference papers on KMSSC.

Emerging research frontiers and hotspots are revealed and a state-of-the-art framework of KMSSC research structure is developed.

The review provides significant implications that guide KMSSC research and better inform sustainability decisions in the supply chain context.

To the best of the authors' knowledge, this is the first review to thoroughly synthesize the intersected domain of KMSSC using scientometric analysis.

Leveraging signalling theory and institutional environment theory, this study aims to examine how the entrepreneurial orientation of emerging market firms impacts initial public offering (IPO) performance.

The authors conduct regression analysis based on archival data from 312 firms’ IPOs in India.

The results in the Indian context suggest it differs from IPO performance in developed markets. In an emerging market context, the findings suggest that only competitive aggressiveness is valued by investors in IPOs. The findings further show that proactiveness and autonomy negatively influence IPO underpricing.

The research propositions imply that, owing to institutional voids in emerging markets, investors’ risk propensity and, hence, rewarding a firm’s entrepreneurial orientation differ from those in developed markets.

Extant literature has given limited attention to the dynamics of entrepreneurial orientation and the effect of each dimension of entrepreneurial orientation on IPO performance in emerging markets.

The purpose of this study is to explore and present a clear overview of innovation topics during the first year of the COVID-19 pandemic, and then organise these topics into various analyses.

The authors use multiple language analysis methods, such as text mining and latent Dirichlet allocation topic modelling, to address the research questions. A total of 440 news articles are analysed using Python and Google Colaboratory tools.

The analysis identified 20 innovation topics, highlighted sector-specific analyses and proposed phases of innovation. The authors suggest that each sector develops unique patterns and forms of innovation for long-term benefits and further research. This study expands upon existing literature on innovation and crisis at a theoretical level by incorporating an actor as the agency.

Based on the findings, the authors conclude that the COVID-19 pandemic has prompted businesses to adopt dynamic capabilities. Furthermore, the authors provide several strategic recommendations for addressing the pandemic in the developing context. The study discusses the roles of policymakers, business practitioners and academia in this context as well.

Very few studies specifically explore and identify forced innovation topics in emerging countries during the pandemic. There has been no review of forced innovations implemented in Indonesia using news media as a source. Additionally, this study presents the trajectory of innovation during the time of crises.

In the rapidly evolving digital economy, businesses face formidable pressures to maintain their competitive standing, prompting a surge of interest in the intersection of artificial intelligence (AI) and digital transformation (DT). This study aims to assess the impact of AI technologies on corporate DT by scrutinizing 3,602 firm-year observations listed on the Shanghai and Shenzhen stock exchanges. The research delves into the extent to which investments in AI drive DT, while also investigating how this relationship varies based on firms' ownership structure.

To explore the influence of AI technologies on corporate DT, the research employs robust quantitative methodologies. Notably, the study employs multiple validation techniques, including two-stage least squares (2SLS), propensity score matching and an instrumental variable approach, to ensure the credibility of its primary findings.

The investigation provides clear evidence that AI technologies can accelerate the pace of corporate DT. Firms strategically investing in AI technologies experience faster DT enabled by the automation of operational processes and enhanced data-driven decision-making abilities conferred by AI. Our findings confirm that AI integration has a significant positive impact in propelling DT across the firms studied. Interestingly, the study uncovers a significant divergence in the impact of AI on DT, contingent upon firms' ownership structure. State-owned enterprises (SOEs) exhibit a lesser degree of DT following AI integration compared to privately owned non-SOEs.

This study contributes to the burgeoning literature at the nexus of AI and DT by offering empirical evidence of the nexus between AI technologies and corporate DT. The investigation’s examination of the nuanced relationship between AI implementation, ownership structure and DT outcomes provides novel insights into the implications of AI in the diverse business contexts. Moreover, the research underscores the policy significance of supporting SOEs in their DT endeavors to prevent their potential lag in the digital economy. Overall, this study accentuates the imperative for businesses to strategically embrace AI technologies as a means to bolster their competitive edge in the contemporary digital landscape.