In this paper, we develop a theoretical framework that explains how digital technologies can help small businesses generate competitive advantages for scaling. To gain and sustain competitive advantages, small businesses traditionally had to choose between cost leadership and differentiation strategies. Digital technologies enable small businesses to reduce their costs and at the same time enhance the value of their market offerings through differentiation. The aim of this paper is to explain the role of digital technologies in such hybrid strategies for small businesses. We first identify automation, individualization and interdisciplinarity as the three dimensions of digital technologies that together enable technology-driven firms to gain and sustain competitive advantages and to scale rapidly. Second, we integrate these three dimensions into a theoretical framework. Third, we test and confirm the theoretical framework in an explanatory case study and discuss the results.

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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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Disruptive technological change can contribute to a more abundant world. However, potentially disruptive technologies often struggle to significantly influence practice. One prominent example is additive manufacturing (AM). Although AM is often regarded as the next great technological revolution in waiting, it has not yet established itself on a large scale in many fields of application. We investigate the reasons behind those challenges by looking at the various fields in which AM is applied and relating them to the specific challenges AM faces, as well as the opportunities it offers in those fields. Our findings rely on a multi-perspective technology foresight process that is based on a discourse analytic approach and that comprises data tomography covering the biggest German-language online magazine on AM and qualitative interview data collected from a range of AM stakeholders. The findings provide an empirically well-founded evaluation and explanation of the link between the challenges and opportunities offered by AM and the extent to which this disruptive technology is leveraged in specific fields. The findings prompt recommendations on how new potentially disruptive technologies can foster abundance in traditional, well established market economies based on the example of the well-developed but traditional market economy of Austria.

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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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