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Sustainability performance (SP) has emerged as a central topic on both corporate and political agendas worldwide. This study investigated the relationship between SP and financial distress risk (FDR) among European listed firms, addressing the growing importance of SP in financial decision-making. Utilising a panel dataset from LSEG Data & Analytics (formerly Refinitiv) for STOXX Europe 600 firms between 2016 and 2022, we performed regression analyses to examine the impact of SP on FDR, measured through alternating scores. In contrast to most existing research, we found SP to increase FDR for most analyses performed, with the effect varying by SP dimension. Because we found environmental and governance SP to increase FDR, we did not find an association between social SP and FDR in most analyses performed. Our findings provide practical and theoretical implications for firms, investors and policymakers concerning the influence of SP investments on FDR and potential SP overinvestments in Europe's latest sustainability regulatory setting.
Rapid scaling amidst resource constraints is crucial for established firms and startups in today’s business landscape. Despite its increasing popularity and research interest, little is understood about dynamic capabilities in the context of growth hacking. This study explores how growth hacking activities contribute to developing dynamic capabilities by employing a flexible pattern matching approach based on 29 qualitative interviews with growth hacking experts. By filling the gap in understanding dynamic capabilities in the context of growth hacking, the research enriches growth hacking’s theoretical foundations and provides practical insights. The results emphasize effectively managing capability dimensions dualities, distinguishing between startup and corporate challenges, and prioritizing rapid experimentation with big data. The study also examines artificial intelligence’s (AI) potential for automating growth hacking processes, while highlighting data privacy risks. This paper suggests future research avenues for further exploring the interplay of dynamic capabilities and growth hacking.
Purpose
This study explores the negotiation behaviors and strategies employed by experienced entrepreneurs to secure venture capital (VC) funding.
Design/methodology/approach
Using a qualitative approach, we conducted interviews with 32 accomplished founders with track records in securing VC funding. Our conceptual underpinning rests upon an existing negotiation competency model. This study employed a systematic and iterative data analysis method, following an inductive approach grounded in Gioia et al.’s (2013) methodology to conceptualize the unprocessed interview data.
Findings
We identified three dimensions characterizing entrepreneurial negotiation behavior in VC negotiations: negotiation competencies, power tactics, and negotiation style. Furthermore, we identified specific behaviors in these dimensions and explored how entrepreneurs apply these skills in the VC context.
Research limitations/implications
This study contributes a nuanced understanding of entrepreneurs’ negotiation behaviors, opening avenues for further research on effective strategies in entrepreneurial finance.
Practical implications
Entrepreneurs can leverage the identified negotiation strategies to enhance their skills and navigate VC negotiations more effectively, potentially leading to better funding outcomes. Furthermore, training programs can be crafted to encourage the cultivation of these behaviors.
Originality/value
This study is the first to systematically examine the negotiation behaviors and strategies employed by experienced entrepreneurs in VC negotiations, revealing entrepreneurs’ specific behaviors and elucidating how these behaviors are employed within negotiations to provide practical insights.
This research explores the characteristics of green influencer messages on follower engagement by examining the interplay between message framing (gain vs. loss), construal level (high vs. low), and post timing (weekdays vs. weekends). Green influencers (also: greenfluencers or sustainable influencers) are considered a key agent for a change to more sustainable consumption. A pilot field study of 1000 green influencers, however, indicates that the current communication practices of green influencers (which strongly focus on gain frames, low construal, and posts during the week) are not ideal for maximizing engagement and sustainable behavioral intentions. Two experiments replicate this finding and establish the process through which green influencer posts affect engagement: gain frames increase fluency, which increases engagement; low construal levels decrease psychological distance, which increases engagement. Timing moderates these processes in that weekend posts increase the engagement with gain frames and week posts increase the engagement with low-construal frames. These findings highlight that there is no silver bullet in green influencer messages, but that green influencers need to adapt the framing and construal of their messages to the posts' timing to increase their contribution to more sustainable lifestyles and the greater good.
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.
The Shapley value equals a player's contribution to the potential of a game. The potential is a most natural one-number summary of a game, which can be computed as the expected accumulated worth of a random partition of the players. This computation integrates the coalition formation of all players and readily extends to games with externalities. We investigate those potential functions for games with externalities that can be computed this way. It turns out that the potential that corresponds to the MPW solution introduced by Macho-Stadler et al. (2007, J. Econ. Theory 135, 339-356) is unique in the following sense. It is obtained as the expected accumulated worth of a random partition, it generalizes the potential for games without externalities, and it induces a solution that satisfies the null player property even in the presence of externalities.
The new normal
(2024)
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.
Climate-related issues have become increasingly relevant, as reflected in current political and academic discourse. This development is also reflected in investors' capital allocation decisions and their demand for climate-related information. Considering the recommendations of the Task Force on Climate-related Financial Disclosures (TCFD), we first investigate the climate-related disclosure quality of listed German firms. We use self-constructed scoring models based on the TCFD recommendations to measure disclosure quality. Second, we use regression analysis to investigate whether corporate governance can explain climate-related disclosure quality. The results indicate that disclosure quality is heavily dispersed across firms, with risk disclosure being better than disclosure of opportunities. Corporate governance factors exert distinct but mostly weak influence on climate-related disclosure quality and that institutional ownership promotes climate-related disclosure quality. We show several implications for research and practice and highlight the relevance for firms to implement a comprehensive approach to communicating climate-related issues.
A gamification approach for enhancing older adults' technology adoption and knowledge transfer
(2024)
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.