The topics of ethical conduct and governance in academic research in the business field have attracted scientific and public attention. The concern is that research misconduct in organizations such as business schools and universities might result in practitioners, policymakers, and researchers grounding their decisions on biased research results. This study addresses ethical research misconduct by investigating whether the ethical orientation of business researchers is related to the likelihood of research misconduct, such as selective reporting of research findings. We distinguish between deontological and consequentialist ethical orientations and the competition between researchers and investigate the moderating role of their perceived autonomy. Based on global data collected from 1031 business scholars, we find that researchers with a strong deontological ethical orientation are less prone to misconduct. This effect is robust against different levels of perceived autonomy and competition. In contrast, researchers having a consequentialist ethical orientation is positively associated with misconduct in business research. High levels of competition in the research environment reinforce this effect. Our results reveal a potentially toxic combination comprising researchers with a strong consequentialist orientation who are embedded in highly competitive research environments. Our research calls for the development of ethical orientations grounded on maxims rather than anticipated consequences among researchers. We conclude that measures for ethical governance in business schools should consider the ethical orientation that underlies researchers’ decision-making and the organizational and institutional environment in which business researchers are embedded.

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Social robots—such as autonomous vehicles, service robots, or healthcare robots—are designed to support tasks in a broad range of human activities. However, these robots face moral dilemmas because they must make decisions that may do good for one human but potentially inflict harm on another. We argue that Kant's categorical imperative provides a framework for algorithm-based moral decision-making. By systematically addressing ethical concerns from the outset in the development of the algorithms that steer social robots, their designers can help ensure that such robots promote the well-being of individuals, communities, and society. We conclude that those involved in the development of social robots need to embed ethics into their design and functioning. The solutions to the ethical dilemmas we advance in this paper can help improve the adoption and impact of social robots. The presented insights contribute to research, practice, and policy.@en

Corporate decision-makers form their intention to adopt new technology for their venture based on their perception of its usefulness and ease of use. However, the formation of this intention might be influenced by the fear of missing out (FOMO), making decision-makers fear losing their relatedness with fellow managers and leading to decisions based on irrational considerations. We draw on and extend the technology acceptance model to explain the potential bias caused by FOMO and expect that this bias is contingent on the level of decision makers' prior experience with the new technology in other contexts. Moderated OLS regressions on 514 observations collected from a representative sample of decision-makers of Austrian SMEs show that FOMO is positively related to the intention to adopt new technology. Moreover, we find that the relationship is mitigated by the decision maker's prior experience with that new technology. We highlight the relevance of the FOMO bias in technology acceptance, adding to the growing research stream on the role of emotions in adopting novel technologies. We further show how experience can effectively counter the FOMO bias for many decision-makers and extend the scope of technology acceptance models by illustrating their applicability to novel manufacturing technologies.

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Social media communication is attractive for non-profit organizations (NPOs); however, the channels of social media are not homogeneous; a factor not sufficiently considered by empirical research. We address this gap by looking into the moderating effect of social media channel choice on the impact of brand trust on process and outcome quality. By surveying 174 customers of an Austrian NPO, we analyze different social media channels to investigate whether (1) the established wisdom of service marketing regarding the positive impact of brand trust on service quality holds in the social-media context and (2) whether the choice of social media channel moderates these relationships. The results confirm the established model of service quality. Knowledge from traditional marketing can still be applied in a digital environment. However, the moderation analysis highlights the relevance of social media channel choice and illustrates different effects on YouTube, Facebook, and Instagram. We discuss the implications.

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Social media offers a myriad of opportunities for entrepreneurial marketing strategies that leverage the power of communities, especially when they are combined with traditional approaches such as celebrity endorsement. The reach, frequency, and speed of communication on social media offer the ideal leverage for the drivers of entrepreneurial marketing. However, the rapid rate of change may threaten the effects of investments in entrepreneurial marketing on social media and they might become only short-lived. Employing structural equation modeling, we test the long-term effect of Facebook-based celebrity endorsement on purchase intention among 234 members of a Facebook fan community in a two-wave longitudinal design. We argue that this relationship is mediated by a sponsor's brand image and moderated by brand differentiation. This study is the first to investigate the long-term effects of entrepreneurial marketing on social media. We present the contributions and implications of our findings as they affect research and practice.

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Additive manufacturing (AM) is an umbrella term for various layer-based manufacturing processes which are often portrayed as a new technological revolution. Despite impressive AM process developments the revenue of the AM industry is still a fraction of that of other manufacturing processes. This AM based revenue discrepancy raises many questions. They include: (1) What makes AM so special? and (2) How could the disruptive potential of AM be unlocked? We seek to add to the literature by providing an answer to elements of these questions through the development of a framework we call the 'Magic Cube'. We utilize the concept of vertical and horizontal innovation theory as one basis for this framework. Further we adopt a tension perspective on automation and individualisation drawn from operations research to develop a theoretical framework. The result is the 'Magic Cube', a tool that is designed to support researchers and practitioners in demonstrating the unique strengths of AM and its potential areas of application.@en

Additive manufacturing (AM) is likely to contribute considerably to key targets of innovation policy such as employment, R&D and education. The expectations of those engaged in AM, such as providers, users and policy makers, regarding the potential of this technology influence its future development and thus create opportunities for technology entrepreneurship. Therefore, these expectations need to be researched so that opportunities for technology entrepreneurship can be identified. Based on prospect theory, we employ an integrative approach to online-based technology assessment. Using the outcome of a constructive technology assessment (CTA) as a reference, a comparison with the results of a traditional technology assessments (TTA) derived from the policy makers enables us to identify the need for action regarding the allocation of public resources. Further, the comparison of the outcome of our CTA with the TTA derived from the general public shows the need to establish a public opinion on AM that legitimizes AM-related innovation policies. The approach of an integrative technology assessment proves useful, as we can deduce concrete recommendations for action on innovation policy based on our empirical findings.

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