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This book focuses on traditional fields of business studies and economics and how digitalization has affected them. It provides an overview about the lessons learned from academic research and highlights implications for practitioners. Digitalization has not only changed the ways business administration and economics are taught, but also the substance at the core of the two disciplines. Chapters from expert contributors define and carefully evaluate the developments that have occurred over the last decades. The authors further provide an assessment of how industry branches have adapted and in which form regulators have engaged. Attention is given to the theoretical and empirical findings from recent scholarly literature. Furthermore, the authors provide some novel insights from their own research at the University of Bremen. This book appeals to business administration, economics, and entrepreneurship scholars and practitioners alike. Hornuf has put together a fascinating collection of research on new digital technologies in the service of business and the economy. The chapters address topics that are of interest to managers as well as policy makers, from digital transformations in supply chains to virtual business incubators. - Vili Lehdonvirta, Professor of Economic Sociology and Digital Social Research at University of Oxford I am impressed by the depth and breadth of knowledge in the new book edited by Professor Lars Hornuf. It provides a holistic view of the role of technology with a focus on digitalization for Business and Society. This book is a must for researchers and practitioners who would like to learn more on research and practice of digitalisation and its related benefits for businesses and the society. - Thanos Papadopoulos, Professor of Management at Kent Business School The digital transformation challenge is daunting for academics and practitioners alike. Research in this area is constantly changing as the underlying technical opportunities shift. This collection offers a valuable overview of digital transformation challenges covering various technologies, such as chatbots, virtual incubators, AI, social media, and crypto-assets. Each chapter forwards the debate on a particular digital technology or field, such as marketing, logistics, or human resource management. The result is a multifaceted contribution to the ongoing interdisciplinary debate on digitalisation. The focus on emerging technologies with the potential for radical impact makes this a highly relevant and important contribution to the academic debate. - Carsten Sorensen, Associate Professor of Information Systems and Innovation at London School of Economics and Political Science.

The European Court of Justice (ECJ) is a very powerful court compared to other international courts and even national courts of last resort. Observers almost unanimously agree that it is the preliminary references procedure that made the ECJ the powerful court it is today. In this paper, we analyze the determinants that lead national courts to use the procedure. We add to previous studies by constructing a comprehensive panel dataset (1982-2008), including more potentially relevant explanatory variables and by testing for the robustness of previous results. In addition to confirming the relevance of variables previously found significant, we identify a number of additional determinants, including the relevance of agriculture to a country, corporate tax rate, familiarity with EU law, and tenure of democracy.

In this study, we investigate whether and to what extent community managers in online collaborative communities can stimulate crowd activities through their engagement. Using a novel data set of 22 large online idea crowdsourcing campaigns, we find that active engagement of community managers positively affects crowd activities in an inverted U-shaped manner. Moreover, we evidence that intellectual stimulation by managers increases community participation, while individual consideration of users has no impact on user activities. Finally, the data reveal that community manager activities that require more effort, such as media file uploads instead of simple written comments, have a larger effect on crowd participation.

In the past decade, crowdworking on online labor market platforms has become the main source of income for a growing number of people worldwide. This development has led to increasing political and scientific interest in the wages that people can earn on such platforms. In this article, we extend the literature based on a single platform, region, or category of crowdworking by conducting a meta-analysis of the prevalent hourly wages. After a systematic and rigorous literature search, we consider 20 primary empirical studies, including 104 wages and 76,282 data points from 22 platforms, eight different countries, and a time span of 12 years. We find that, on average, microwork results in an hourly wage of less than $6. This wage is significantly lower than the mean wage of online freelancers, which is roughly three times higher. We find that hourly wages accounting for unpaid work, such as searching for tasks and communicating with requesters, tend to be significantly lower than wages not considering unpaid work. Legislators and researchers evaluating wages in crowdworking should be aware of this bias when assessing hourly wages, given that the majority of the literature does not account for the effect of unpaid work time on crowdworking wages. To foster the comparability of different research results, we suggest that scholars consider a wage malus to account for unpaid work. Finally, we find that hourly wages collected through surveys tend to be lower than wages collected via browser plugins or other technical data collection methods.

In the past decade, crowdworking on online labor market platforms has become the main source of income for a growing number of people worldwide. This development has led to increasing political and scientific interest in the wages that people can earn on such platforms. In this article, we extend the literature based on a single platform, region, or category of crowdworking by conducting a meta-analysis of the prevalent hourly wages. After a systematic and rigorous literature search, we consider 20 primary empirical studies, including 104 wages and 76,282 data points from 22 platforms, eight different countries, and a time span of 12 years. We find that, on average, microwork results in an hourly wage of less than $6. This wage is significantly lower than the mean wage of online freelancers, which is roughly three times higher. We find that hourly wages accounting for unpaid work, such as searching for tasks and communicating with requesters, tend to be significantly lower than wages not considering unpaid work. Legislators and researchers evaluating wages in crowdworking should be aware of this bias when assessing hourly wages, given that the majority of the literature does not account for the effect of unpaid work time on crowdworking wages. To foster the comparability of different research results, we suggest that scholars consider a wage malus to account for unpaid work. Finally, we find that hourly wages collected through surveys tend to be lower than wages collected via browser plugins or other technical data collection methods. ; 0007

When using digital devices and services, individuals provide their personal data to organizations in exchange for gains in various domains of life. Organizations use these data to run technologies such as smart assistants, augmented reality, and robotics. Most often, these organizations seek to make a profit. Individuals can, however, also provide personal data to public databases that enable nonprofit organizations to promote social welfare if sufficient data are contributed. Regulators have therefore called for efficient ways to help the public collectively benefit from its own data. By implementing an online experiment among 1,696 US citizens, we find that individuals would donate their data even when at risk of getting leaked. The willingness to provide personal data depends on the risk level of a data leak but not on a realistic impact of the data on social welfare. Individuals are less willing to donate their data to the private industry than to academia or the government. Finally, individuals are not sensitive to whether the data are processed by a human-supervised or a self-learning smart assistant.