Our research investigates the role of social media communication in amplifying high-quality information and its impact on the success of ICOs in achieving their soft cap. We analyzed data from 3,644 ICOs and the demographics of 1,987 CEOs, CFOs, and CTOs to compare their quality attributes against their number of social media followers. Our findings reveal that the most significant factors for reaching the soft cap are the number of followers and team size, while the competencies (education and skills) of the management team have a very marginal effect, even when enhanced through social media. This indicates that widespread social media signals can positively influence investor behavior without necessarily reducing information asymmetries regarding the quality of the team. We propose that this effect arises from the combination of minimal investment amounts and stimulated herding behavior among investors.

The manuscript investigates whether the individual personality trait, Fear of Missing Out (FOMO)—typically considered negative—influences the willingness of individuals to contribute to Initial Coin Offerings (ICOs), a phenomenon that emerged after the blockchain revolution. We conducted both qualitative and quantitative work in this space and present the results of an international survey, including a conjoint experiment. Theoretically, we anchor our study in signaling theory and propose that signal valence (the positive or negative interpretation of a signal) can diverge from signal intent. Specifically, we find that candidate ICO funders with strong FOMO behave predictably irrationally. They are more likely to invest in financially irresponsible projects and are less likely to invest in projects that have received recognition from established media sources or multinationals. While both financial responsibility and stakeholder recognition are ostensibly positive signals of team and project quality, we find that for ICO funders with high FOMO, the valence of these signals changes.

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.

This research contributes to the Management of Technology (MOT) literature by scrutinizing the interrelation between education, experience, and the scaling aptitudes of high-tech companies. The study hinges on a comprehensive analysis of data collected from 1987 C-level executives and 3644 born-digital firms that pursued funding via blockchain-based Initial Coin Offerings (ICOs). Employing structural equation modeling, we systematically tested our hypotheses, contrasting the scaling trajectories of companies that successfully procured funding against those that fell short. Our findings reveal that amongst the diverse managerial competencies, only the leadership acumen of CEOs plays an important role in fostering the scaling of tech-companies across the spectrum, leaving the proficiencies of CFOs and CTOs with negligible impact. More crucially, the competencies of a CEO magnify in importance in relation to a tech-company's scaling potential post the securing of funds. The insights gained from this study not only enrich the existing body of knowledge on scaling and ICOs within the MOT literature but also hold considerable practical value for crafting effective scaling strategies in the high-tech industry.

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.

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.

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.

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.

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.

This article examines how a firm's willingness to make trade-offs that favour sustainability over commercial goals attenuates the relationship between firm-level sustainability orientation and subsequent performance. The hypothesis development draws on stakeholder theory and the literature on mission and revenue drifts, while the empirical analysis is based on two waves of original survey data on Finnish manufacturing SMEs. We find that sustainability orientation is positively associated with performance only when the willingness to make sustainability trade-offs is low, whereas the relationship becomes negative when the willingness to make such trade-offs is high. Our findings thus suggest that the popular adage of doing well by doing good might only hold if doing good does not conflict with business interests. The results add to stakeholder theory by showing how conforming to stakeholder expectations can be good for business – but only if doing so does not seriously compromise the pursuit of profits.

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.

Commissioning studies of the CMS hadron calorimeter have identified sporadic uncharacteristic noise and a small number of malfunctioning calorimeter channels. Algorithms have been developed to identify and address these problems in the data. The methods have been tested on cosmic ray muon data, calorimeter noise data, and single beam data collected with CMS in 2008. The noise rejection algorithms can be applied to LHC collision data at the trigger level or in the offline analysis. The application of the algorithms at the trigger level is shown to remove 90% of noise events with fake missing transverse energy above 100 GeV, which is sufficient for the CMS physics trigger operation.

The CMS Hadron Calorimeter in the barrel, endcap and forward regions is fully commissioned. Cosmic ray data were taken with and without magnetic field at the surface hall and after installation in the experimental hall, hundred meters underground. Various measurements were also performed during the few days of beam in the LHC in September 2008. Calibration parameters were extracted, and the energy response of the HCAL determined from test beam data has been checked.