The recent rise of big data and artificial intelligence (AI) is changing markets, politics, organizations, and societies. It also affects the domain of research. Supported by new statistical methods that rely on computational power and computer science-data science methods-we are now able to analyze data sets that can be huge, multidimensional, and unstructured and are diversely sourced. In this paper, we describe the most prominent data science methods suitable for entrepreneurship research and provide links to literature and Internet resources for self-starters. We survey how data science methods have been applied in the entrepreneurship research literature. As a showcase of data science techniques, based on a dataset of 95% of all job vacancies in the Netherlands over a 6-year period with 7.7 million data points, we provide an original analysis of the demand dynamics for entrepreneurial skills in the Netherlands. We show which entrepreneurial skills are particularly important for which type of profession. Moreover, we find that demand for both entrepreneurial and digital skills has increased for managerial positions, but not for others. We also find that entrepreneurial skills were significantly more demanded than digital skills over the entire period 2012-2017 and that the absolute importance of entrepreneurial skills has even increased more than digital skills for managers, despite the impact of datafication on the labor market. We conclude that further studies of entrepreneurial skills in the general population-outside the domain of entrepreneurs-is a rewarding subject for future research.
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Using data for a representative sample of the Dutch population with information about participants' religious background, we study the association between religion and moral behavior and attitudes. We find that religious people are less accepting of unethical economic behavior (e.g., tax evasion, bribery) and report more volunteering. They are equally likely as non-religious people to betray trust in an experimental game, where social behavior is unobservable and not directed to a self-selected group of recipients. Religious people also report lower preference for redistribution. Considering differences between denominations, Catholics betray less than non-religious people, while Protestants betray more than Catholics and are indistinguishable from the non-religious. We also explore the intergenerational transmission and the potential causality of these associations.
Highlights• Religious people are less accepting of unethical behavior and report more volunteering • Religious people are no more trustworthy in a trust game with an unknown person.• Religious people have lower preference for redistribution • Parental religion correlates with their children's moral attitudes
We study competition in data‐driven markets, where the cost of quality production decreases in the amount of machine‐generated data about user preferences or characteristics. This gives rise to data‐driven indirect network effects. We construct a dynamic model of R&D competition, where duopolists repeatedly determine innovation investments. Such markets tip under very mild conditions, moving towards monopoly. After tipping, innovation incentives both for the dominant firm and the competitor are small. We show when a dominant firm can leverage its dominance to a connected market, thereby initiating a domino effect. Market tipping can be avoided if competitors share their user information.
This paper studies the strategies employed by Catholic and Protestant nonprofit hospitals in Germany and traces them back to the theological foundations of those religions, which shape managers' values. We find that JEL Classification: L31; L21; Z12; D64; I11
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We analyze the capacities of communities (or social networks) and courts to secure cooperation among heterogeneous, impersonal transactors. We find that communities and courts are complementary in that they tend to support cooperation for different types of transactions but that the existence of courts weakens the effectiveness of community enforcement. Our findings are consistent with the emergence of the medieval Law Merchant and its subsequent supersession by state courts as changes in the costs and risks of long-distance trade, driven in part by improvement in shipbuilding methods, altered the characteristics of merchant transactions over the course of the Commercial Revolution.
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