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The author presents new estimates of the probability weighting functions found in rank-dependent theories of choice under risk. These estimates are unusual in two senses. First, they are free of functional form assumptions about both utility and weighting functions, and they are entirely based on binary discrete choices and not on matching or valuation tasks, though they depend on assumptions concerning the nature of probabilistic choice under risk. Second, estimated weighting functions contradict widely held priors of an inverse-s shape with fixed point well in the interior of the (0,1) interval: Instead the author usually finds populations dominated by “optimists” who uniformly overweight best outcomes in risky options. The choice pairs used here mostly do not provoke similarity-based simplifications. In a third experiment, the author shows that the presence of choice pairs that provoke similarity-based computational shortcuts does indeed flatten estimated probability weighting functions.

This chapter examines whether professional auditors’ affect toward client management influences fraud likelihood judgments and whether accountability and experience with fraud risk judgments moderate this effect. This research also explores the process by which affect influences fraud judgments by examining affect’s influence on the evaluation of fraud evidence cues. Results indicate that more positive affect toward the client results in lower fraud likelihood judgments. Accountability is found to moderate this effect, but only for experienced auditors. These findings have implications for fraud brainstorming sessions where all staff levels provide input into fraud risk assessments and because client characteristics are especially salient during these assessments. Importantly, results also support the proposition that affect impacts inexperienced auditors’ fraud assessments through errant attribution of client likability to evidence cues that refer to management, rather than biasing all client-related evaluations. Together, these findings suggest that education and training can be improved to better differentiate relevant and irrelevant cues in fraud judgment.

Bitcoin is difficult to categorize and indeed has been associated with 112 different labels in the British media (e.g., “private money,” “commodity”) – most of which poorly describe bitcoin. Specifically, our analyses of 674 media articles, focusing on the relationship between labeling and categorization, identify classification inconsistencies at three levels: within clusters of labels, between labels and categories, and between category attributes. These inconsistencies hamper categorization based on attribute similarity, audience goals, and causal models, respectively. We identify four factors that nurture this categorical anarchy and conclude with a call for research on the socioeconomic revolution heralded by blockchain technology.

Homophily, or the tendency for individuals to be attracted to those who resemble them, is significantly influential in the formation of startup founding and top management teams. But its role in subsequent stages of startup growth remains largely unclear. We consider the impact of homophily on matching of early workers to startups. We propose that, in the case of underrepresented minority groups, the tendency toward homophily plays an important role in this matching process, albeit in an asymmetric way. In particular, homophily exerts a stronger influence on the supply than the demand side: job candidates are more inclined to favor startups with demographically similar founders than startup founders are inclined to favor demographically similar job-seekers. Focusing on an important group of historically disadvantaged workers – women – we examine these arguments using unique data on the online recruiting of high-tech startups concentrated in the Silicon Valley. We find evidence suggesting that female candidates' propensity to apply to a job at a given startup increases with the proportion of female founders. However, startups with a higher proportion of female founders are not more likely than other startups to favor female candidates in personnel selection.

Institutional theory and organizational ecology have long proposed alternative (albeit not always contradictory) processes to interpret founding and creation of a novel organizational form. Much of the debate has dealt with the issue of how legitimation processes shape such important events or acts. Empirical research on both sides is rich with interesting results, while much of the controversy regards how legitimation is empirically captured and the ways it unfolds over time.

Recently, within organization ecology this specific issue has received increasing attention in the search for a theory of forms and identities. A central piece of the proposed theory links identities to specific audiences or constituencies, both internal and external, which act by attributing legitimation to novel constructions. The new formulation has originated different efforts aimed at better understanding how audiences develop and how they are shaped by wider social movements. Existing research has mainly been dealing with organizations (and forms), which appear to be legitimate (albeit not legitimated) from their inception, benefiting from the generalized acceptance of business organizations in modern societies. Limited attention has been devoted to analyzing contrasted forms, i.e. organized forms of action which act at the border or outside the border of established economic and social action. I contend that it is by analyzing these extreme cases that a clearer interpretation of legitimacy and legitimation processes can be achieved. By analyzing the evolution and the principal dynamics of three populations that are operating in gray and black market, I propose a critique to existing theories of legitimacy.

In today's knowledge-based economy, the ability to produce highly novel and practical ideas is critical to an organization's survival. This paper draws upon social perspectives of creativity (Perry-Smith & Shalley, 2003) and the vital role of recombinant information in creative development (Barron & Harrington, 1981; Hargadon, 2003) to explore information exchange probabilities; exchanges among group members who are deep-level similar fosters incremental creative potential while information exchanges among group members who are deep-level dissimilar fosters radical creative potential. The dynamics of attraction suggest group members are most likely to interact with people who are least likely to facilitate radical creativity. Using a computer simulation we examine how proximity may be used to facilitate information exchanges among deep-level diverse group members to increase the potential for radical creativity. Results suggest the use of proximity to create strong ties among deep-level dissimilar group members may facilitate radical creativity in groups.

Purpose – As researchers need partners to collaborate with, this study aims to provide author recommendation for academic researchers for potential collaboration, conference planning, and compilation of scientific working groups with the help of social information. Hereby the chapter analyzes and compares different similarity metrics in information and computer science.

Methodology/approach – The study uses data from the multidiscipline information services Web of Science and Scopus as well as the social bookmarking service CiteULike to measure author similarity and recommend researchers to unique target researchers. The similarity approach is based on author co-citation, bibliographic coupling of authors and collaborative filtering methods. The developed clusters and graphs are then evaluated by these target researchers.

Findings – The analysis shows, for example, that different methods for social recommendation complement each other and that the researchers evaluated user- and tag-based data from a social bookmarking system positively.

Research limitations/implications – The present study, providing author recommendation for six target physicists, is supposed to be a starting point for further approaches on social academic author recommendation.

Practical implications – The chapter investigates in recommendation methods and similarity algorithm models as basis for an implementation of a social recommendation system for researchers in academics and knowledge-intensive organizations.

Originality/value of chapter – The comparison of different similarity measurements and the user evaluation provide new insights into the construction of social data mining and the investigation of personalized recommendation.

This article explores the effect of technological similarity in acquisitions on invention quantity and quality. In doing so, we confirm previous findings in the literature suggesting that technological similarity exhibits an inverted U-shaped relationship with innovative output and a negative relationship with average invention quality. However, we identify the nature of the technology as an important moderating factor for both relationships. We distinguish between two types of technologies, complex and discrete, and suggest that at high levels of technological similarity, invention quantity and average quality increase more in complex technology industries as compared to discrete technology industries. These effects are attributed to innovation cumulativeness and the interdependencies developed between patent rights in complex technology settings. A study of acquisition and patenting activity in two industries over a sixteen-year period provides empirical support to our claims.