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Do good and talk about it
(2025)
This study provides robust evidence that higher investor relations (IR) quality goes in tandem with enhanced ESG ratings. Building on the extensive data from an established investor relations award in Germany, covering the largest listed firms between 2014 and 2022, we use both panel-data and two-stage least-squares regressions to analyze the effect of IR quality on ESG ratings. Our results hold true for various robustness checks. Moreover, not only do our results introduce a suitable measure for IR quality, but they also demonstrate the relevance of IR quality as an additional determinant of ESG performance measured by rating agencies. Finally, our results provide practical guidelines to firms struggling with their ESG ratings by providing reasoning that investing in higher IR quality eventually meets with success.
Earnout deals are expected to protect acquirers from overpayment as information asymmetries are reduced and the final purchase price is partly based on the future performance of the target. Various scholars have investigated the perception of earnout deals by capital markets revealing significant abnormal returns. Those studies are focused mostly on the Anglo-Saxon countries and China leveraging a pre-COVID datasets. Hence, this study aims at investigating capital market reaction to earnout deals in Continental Europe covering the timeline of 2012 to 2022. Our results indicate that earnout deals in Continental Europe outperform non-earnout deals and are especially beneficial in times of high uncertainty.
This paper investigates the emerging potential of metaverse technology and the diverse opportunities it presents for companies across industries. Although the metaverse remains in its nascent stages, its swift evolution has introduced a broad spectrum of use cases that hold significant promise for businesses. However, despite the evident potential, there remains a limited understanding of how metaverse technology can be effectively applied to benefit business operations and strategy. To address this gap, this study employs a scoping review methodology, systematically collecting and analyzing data from academic literature, publicly available sources, and company websites. The comprehensive review identified 101 distinct use cases of metaverse technology, which were subsequently categorized into three primary application fields: developing new product and service offerings, enhancing customer experience, and optimizing internal business processes. These findings not only provide a compelling rationale for companies contemplating the adoption of metaverse technology but also represent the first extensive exploration of its applications across diverse fields and industries. The study offers valuable insights that are crucial for both academic researchers and business practitioners who are keen to understand and leverage the transformative potential of the metaverse. By mapping out the current landscape of metaverse applications, this paper contributes to a deeper understanding of how companies can harness this technology to drive innovation, improve operational efficiency, and create new value propositions in an increasingly immersive and interconnected world.
The integration of legitimacy in entrepreneurial ecosystem theory is under-researched, resulting in scholarly vagueness about how entrepreneurs acquire resources. Our qualitative study with 31 (co-)founders of startups following the triple bottom line investigates entrepreneurs' daily practices for building legitimacy in entrepreneurial ecosystems. We identify that entrepreneurs follow a sequential process to build legitimacy: 1) engaging and assimilating with culture, 2) establishing and utilizing networks, 3) enhancing visibility, and 4) leveraging the sustainable mission. Following this sequential process builds different levels of legitimacy. Each level grants access to resources from the entrepreneurial ecosystem. We contribute to the scholarly conversation on legitimacy in entrepreneurial ecosystems and provide practical implications for entrepreneurs.
The concept of coopetition - simultaneous collaboration and competition between organizations to achieve mutually beneficial outcomes - plays a pivotal role in shaping business performance, particularly during periods of rapid technological advancements. This is especially evident the manufacturing sector, where innovation and competitive dynamics intersect with economic and social forces. The current academic discourse predominantly focuses on the qualitative identification and analysis of coopetition attributes, leaving a significant gap for large-scale quantitative studies to enable empirical assessment. This study aims to examine the significance of three groups of coopetition attributes for coopetition performance classified into two strategic (dynamics, paradoxicality), six relational (asymmetry, complexity, coopetition intensity, mutual dependence, strength, tensions), and five behavioral attributes (competition intensity, conflict, formality, investments, trust). Using data from 1216 manufacturing firms in Poland and employing a generalized Covariance based Structural Equation Model (CB-SEM), this study offers nuanced insights to the global discourse at the intersection of technological change and social dynamics. The results indicate that the strategic attribute paradoxicality, the relational attribute strength, and most of the behavioral attributes (trust, competition intensity, investments, formality) positively impact coopetition performance. Additionally, a significant negative impact of the strategic attribute dynamics was demonstrated, while no significant influence was identified for the remaining relational attributes (asymmetry, tensions) as well as the behavioral attribute conflict. Diverging from prior qualitative approaches, this study offers data-driven insights for decision-makers navigating societal and technological change, highlighting which attributes should be stimulated to enhance coopetition performance while minimizing the level of dynamics within coopetition strategies.
The Future Combat Air System (FCAS), a sixth-generation advanced combat aircraft, is assumed to be the largest European defence development and production programme of the 21st century and a core pillar of European cooperation in the defence sector. The 2017-initiated collaboration programme is led by Germany and France, with Spain and Belgium joining as partners, and is a who-is-who of the largest European defence companies, including Airbus Defence and Space, Thales, Safran, MBDA, and MTU. While such defence programmes have significant military, political, industrial, and economic impacts, the economic dimension in terms of economic costs and benefits is often under-represented in academic discussions. As the FCAS is still a nascent programme, only rough estimates of the total programme cost are available, and assumptions range from €100 bn to more than a trillion. With our research, we aim to contribute to the academic discussion by estimating the true economic costs and benefits of the FCAS. We use a mixed approach of data triangulation by cross-checking open source intelligence (OSINT) with expert interviews to estimate the full programme life-cycle costs. Furthermore, we estimate its economic impact on the European gross value added, employment, and tax by utilising an input – output (IO) model.
Artificial intelligence (AI) emerges as a promising technology to address burgeoning challenges resulting from shifting demographics, coupled with a shortage of qualified personnel. Thus, the adoption of AI creates especially interest within the talent acquisition (TA) domain to realize anticipated efficiency gains. However, evidence suggests that AI adoption may foster the emergence of harmful forms of practices (HFP) within TA practices. Despite the importance, respective empirical studies collecting data to generate insights remain sparse. Thus, the aim of this study is to investigate HFP and underlying drivers through a mixed-method approach. At the first stage, we conducted in-depth interviews with 42 TA experts. The resulting insights informed the development of the 'Adoption of AI in TA: Framework on Negative Consequences.' This model suggests that a confluence of technological, individual, and organizational factors can result in the emergence of HFP post-AI adoption. Such potential HFP include biased decision-making, data privacy violations, and efficiency reduction. Then, we validated our qualitative findings and confirmed our hypotheses by employing a quantitative, survey-based approach with 303 valid study participants. By shedding light on potential HFP through AI adoption in TA and respective catalysts, our research empowers both information technology and TA professionals to proactively engage in mitigation strategies. In this vein, they may successfully navigate the complex landscape of AI adoption. Hence, this study adds to research on effective AI adoption in TA.
Artificial intelligence (AI) is increasingly being recognized as a critical tool when it comes to addressing the most pressing challenges facing modern industries, including the pursuit of sustainability. The use of AI is aiding businesses in navigating corporate sustainability challenges, but existing research lacks a comprehensive exploration of how corporations leverage AI to boost their sustainability. By exploiting an inductive concept-development approach and incorporating data from 24 companies, this study provides valuable insights into the role that AI plays in shaping organizational sustainability strategies, identifying operational enablement and technical capacity as key drivers of AI adoption for corporate sustainability. These drivers are incorporated into the technology, organization, and environment (TOE) framework alongside the strategic steps and capabilities necessary for organizations to effectively adopt and implement AI in the development of their sustainability strategies. Ultimately, this study proposes an integrative model for sustainability-oriented AI adoption that emphasizes the importance of aligning AI initiatives with organizations’ sustainability objectives in order to maintain a competitive advantage and drive progress. Correspondingly, it underscores the need for robust data management, system integration, and continual performance monitoring to reduce resistance to AI adoption allowing for the potential of AI to be fully harnessed in pursuit of sustainability. Furthermore, this study offers practical guidance by exploring the direct and indirect use cases of AI in corporate sustainability. The study concludes by highlighting potential avenues for future research in this evolving field.
The has been an upsurge in the significance of sustainability in the business landscape, leading corporations to adopt strategies that extend beyond implementing social responsibility initiatives. While start-ups and social entrepreneurs have excelled in integrating sustainability into their business models, balancing financial goals with the growing demand for sustainability has been far more challenging for large corporations. This study considers the potential of corporate entrepreneurship to foster sustainability within established companies. Sustainable corporate entrepreneurship (SCE) allows companies to leverage innovation for sustainability as a value-creating opportunity rather than a restrictive constraint. This study addresses a critical gap in the literature—the lack of a comprehensive framework for SCE––through a meticulous, systematic literature review of 95 recent publications. Our proposed SCE framework has three dimensions: focus, approach, and evaluation. We provide insights to deepen understanding and guide future research in this evolving field. Specifically, we introduce a model that illustrates how SCE can be cultivated as a dynamic capability for generating value through sustainability-focused innovation. This model captures individual and organisational factors and encompasses factors that enable and limit SCE.
In light of the energy crisis following the Russian invasion of Ukraine, policymakers postulated to lower fossil fuel consumption. Focusing on Europe, we analyze whether domestic energy consumption was reduced in the past because of increased geopolitical risk (GPR) in fossil fuel supplier countries. For this purpose, we adopt an aggregate GPR measure that combines information on GPR in supplier countries with rich bilateral trade data for oil, natural gas, and coal. We estimate the impact of GPR related to fossil fuel imports utilizing an instrumental variable approach and a growth-energy use model. Our results indicate that during the period 2000–2019, increased GPR in coal supplier countries entailed reductions in both coal and total energy consumption. Moreover, economic growth effects on fossil fuel consumption were partly reduced by risks related to coal and natural gas imports. Similarly, if mediated by a high domestic import dependency or government effectiveness, GPR partly lowered the consumption of coal and natural gas. Regarding the energy transition, we find indications of a partial shift from fossil fuels to renewable energy in response to GPR abroad. That is, concurrent to the partial reduction in fossil fuel consumption, GPR in coal supplier countries increased renewable energy consumption.