In today's data-driven era, ubiquitous concern about environmental issues pushes more startups to engage in business model innovation that promotes environmentally friendly technologies. The goal of these startups is to create technology-based products and services that enhance environmental sustainability. In this context, artificial intelligence promises to be a key instrument to create, capture, and deliver value. However, the existing literature lacks a deep understanding of how startups using AI innovate their business models to achieve a positive environmental impact. Therefore, this paper investigates how green technology startups utilize AI from a business model innovation perspective for environmental sustainability. We conduct a qualitative, exploratory multiple-case study using the Eisenhardt methodology, based on interview data analyzed using qualitative content analysis. We derive five predominant manifestations for AI-driven business model innovation and identify archetypical connections between business model dimensions. Further, we establish three overarching archetypical associations among the cases. In doing so, we contribute to theory and practice by providing a deeper account of how green technology startups attempt to maximize their positive environmental impact through AI. The results of this study also highlight how business model innovation driven by AI can support society in securing a more environmentally sustainable future.

Purpose When CEOs are publicly weighing in on sociopolitical debates, this is known as CEO activism. The steadily growing number of such statements made in recent years has been subject to a flourishing academic debate. This field offers first profound findings from observational studies. However, the discussion of CEO activism lacks a thorough theoretical grounding, such as a shared concept accounting for the heterogeneity of sociopolitical incidents. Thus, the aim of this paper is to provide an archetypal framework for CEO activism. Design/methodology/approach The authors used a multiple case study approach on 145 activism cases stated by CEOs and found seven distinct statement archetypes. Findings The study identifies four main structural design elements accounting for the heterogeneity of activism, i.e. the addressed meta-category of the statement, the targeted outcome, the used tonality and the orientation of the CEOs’ positions. Further, the authors found seven distinguishable archetypes of CEO activism statements: “Climate Alerts”, “Economy Visions”, “Political Comments”, “Self-reflections and Social Concerns”, “Tech Designs”, “Unclouded Evaluations” and “Descriptive Explanations”. Research limitations/implications This typology classifies the heterogeneity of CEO activism. It will enable the analysis of interrelationships, mechanisms and motivations on a differentiated level and raise the comprehensibility of research-results. Practical implications The framework supports executives in understanding the heterogeneity of CEO activism and to analyse personality-fits. Originality/value To the authors’ knowledge, this marks the first conceptualisation of activism developed cross-thematically. The work supports further theory-building on CEO activism.

The recent surge in artificial intelligence (AI) adoption by small and medium-sized enterprises (SMEs) has garnered significant research attention. However, the existing literature reveals a fragmented landscape that hinders our understanding and application of insights about AI use in SMEs. We address this through a systematic literature review, wherein we analyze 102 peer-reviewed articles on AI adoption in SMEs and categorize states and trends into eight clusters—(1) compatibility, (2) AI readiness, (3) knowledge, (4) resources, (5) culture, (6) competition, (7) regulation, and (8) ecosystem—according to the technology–organization–environment model. Our research reveals valuable insights but also identifies significant gaps in existing literature, notably the oversight of trends identification as a pivotal driver and the neglect of legal requirements. Our study clarifies the AI implementation within SMEs, offering a holistic and theoretically grounded perspective to empower researchers and practitioners to facilitate more effective AI adoption and application within the SME sector.

Recent years have seen a surge in research on artificial intelligence (AI)-driven business model innovation (BMI), reflecting its profound impact across industries. However, the field’s current state remains fragmented due to varied conceptual lenses and units of analysis. Existing literature predominantly emphasizes the technological aspects of AI implementation in business models (BMs), treating BMI as a byproduct. Additionally, there is a lack of coherent understanding regarding the scope of BMI propelled by AI. To address these gaps, our study systematically reviews 180 articles, offering two key contributions: (1) a structured analysis of evolving research dimensions in AI-driven BMI, differentiating between static and dynamic views of BMI, and (2) a framework presenting distinct research perspectives on AI-driven BMI, each addressing specific managerial focuses. This synthesis facilitates a comprehensive understanding of the field, enabling the identification of research gaps and proposing future avenues for advancing knowledge on the management of AI-driven BMI.

Technology is assumed to be important for enhancing older adults' life quality and for ameliorating age-related problems, but older adults nevertheless typically exhibit lower technology adoption rates than young people. Gamification has the potential to address this problem by motivating older adults, but its value for the elderly has thus far been undermined through gamification design biases favoring young people. This study addressed this problem by developing a purpose-built gamified learning system, based on a popular mobile payment platform, to test the potential of employing a gamification-and-learning approach to the design of gamification systems for enhancing knowledge transfer and technology adoption by older adults. The research employed structural equation modeling, incorporating user knowledge and gamification-related constructs, drawing upon the established Technology Acceptance Model. Data were collected from older adults in Hong Kong with an appropriate demographic and market profile, following a one-group pretest–posttest research design. The results revealed notable gamification-induced improvements in the knowledge and technology adoption intentions of older adults, and significant positive relationships between gamification effectiveness and technology adoption constructs. The research demonstrates the significant positive effects which gamification may have on the acceptance and usage of technology by older adults and evokes policy implications for the silver-hair market.

This study explores the impact of metaverse technology on business models (BMs). Despite increasing academic and practical interest, the adoption and seamless integration of this technology poses substantial challenges for businesses. This study adopts a grounded-theory approach to explore how firms can incorporate this technological innovation within their existing BMs. Drawing upon insights from 20 interviews, the data were structured using the Gioia methodology, uncovering 5 dimensions that elucidate how companies can leverage metaverse technology to augment value creation, capture, and delivery, both internally and externally, within their BMs. These dimensions serve as a roadmap for firms seeking to embrace the metaverse, offering insights into potential adaptations to their existing BMs. This study contributes to the theoretical discourse surrounding the metaverse by delineating specific components within BMs that can be tailored to accommodate metaverse integration. Furthermore, our findings offer invaluable guidance and recommendations to firms and ventures, highlighting the diverse areas within the value creation process where metaverse integration can be strategically applied. This research lays the foundation for a more comprehensive understanding of metaverse technology's role in shaping the business landscape.

Purpose The purpose of the study is to understand the relationship between family-driven innovation and the incorporation of corporate sustainability in German family firms. Design/methodology/approach The study conducted 26 interviews with 22 German family firms. Thematic analysis was undertaken on the collected data resulting in five major themes. Findings The study identified five main themes of corporate sustainability-oriented innovation in family firms, which include measuring corporate sustainability performances, building corporate sustainability-oriented infrastructure, stabilizing/optimizing operations, enhancing operational flexibility/independence and knowledge management and development. The study also provides an activity-based guide for family firms to use innovation to achieve corporate sustainability goals and present the findings’ implications for policymakers. Originality/value The present study is the first study to empirically investigate the relationship between family-driven innovation and the incorporation of corporate sustainability at each of the corporate sustainability maturity levels.

This article explores how entrepreneurial small- and medium-sized enterprises (SMEs) manage coopetition strategies to innovate with large firms. While coopetition offers opportunities for innovation and growth, asymmetries between SMEs and large firms can provoke unilateral actions, opportunistic tactics, and knowledge theft which can undermine SME innovation power and jeopardise coopetition success. Based on a qualitative multiple-case study of 25 coopetitive innovation projects, each involving an SME and a large firm, we find that SMEs manage these risks by pursuing a synergistic mix of three distinct coopetition strategies: (1) Co-distribution, (2) Technology licensing, and (3) R&D co-development. In each strategy, SMEs navigate different coopetition intensities by dynamically combining the principles of separation, integration, co-management and co-ownership to achieve specific innovation outcomes. Our findings suggest that SMEs shift between cooperation- and competition-dominant strategies and employ a mix of management principles to offset asymmetrical risks and maximise their innovation benefits from coopetition with large firms.

Bibliometric analysis has recently become a popular and rigorous technique used for exploring and analyzing the literature in business and management. Prior studies principally focused on ‘how to do bibliometric analysis’, presenting an overview of the bibliometric methodology along with various techniques and step-by-step guidelines that can be relied on to rigorously conduct bibliometric analysis. However, the current body of evidence is limited in its ability to provide practical knowledge that can enhance the design and performance of bibliometric research. This claim is supported even by the fact that relevant studies refer to their work as ‘bibliometric analysis’ rather than ‘bibliometric research’. Accordingly, we endeavor to offer a more functional framework for researchers who wish to design/conduct bibliometric research on any field of research, especially business and management. To do this, we followed a twofold way. We first outlined the main stages and steps of typical bibliometric research. Then, we proposed a comprehensive framework for specifying how to design/conduct the research and under what headings the relevant stages (step-by-step) will be used and/or presented. Thus, the current paper is expected to be a useful source to gain insights into the available techniques and guide researchers in designing/conducting bibliometric research.

Green influencers are crucial in promoting sustainable lifestyles, but their impact may vary depending on their audience. Their behavioral effect might be limited if they were mainly “preaching to the choir” of like-minded green followers who likely already consume sustainably. The purpose of this research is to (1) investigate the communication practices of green influencers and their followers as an indicator of their green attitudes (and a potential influencer-follower attitude fit) and (2) understand the effect of consumer green attitudes on their response to green influencer messages. Field data reveal the high influencer-follower fit in green attitudes in that they mostly talk about green topics. Two experiments with real and fictional influencers show the negative implications of this attitude fit: the effect of green influencer posts on consumers’ usage intention is weaker when these consumers have similar green attitudes as the influencers (fit), whereas the effect is stronger when these posts reach a non-green audience (non-fit). This implies that green influencers should focus on reaching a non-green audience when promoting green consumption; alternatively, green behavioral intentions might increase through sustainable messages from non-green (e.g., beauty) influencers.