Do we understand each other? Toward a simulated empathy theory for entrepreneurship

Entrepreneurs often face the daunting task of predicting consumer demand before it exists—what consumers will want if and when the entrepreneur might make it available to them. Such alertness and judgment require an entrepreneur's vicarious imagination—the supposition of what a value experience would be like for another—such as empathy. Prevailing theories of empathy, however, are ill-suited for entrepreneurship theory as they are defined as and focused on an emotion-matching process. We propose that empathy be understood instead as a vicarious mental simulation of another's experience that, when accurate, produces similar emotions but also similar experiential knowledge. According to our ‘simulated empathy theory,’ empathy is a rational imagination process, intentional and knowledge-based. We connect this empathy process to contemporary entrepreneurship theory, namely opportunity recognition and evaluation processes. We also revise the concept of empathic accuracy accordingly, and derive therefrom some practical implications regarding how entrepreneurs can increase their empathic accuracy and, thereby, their chances of success.     

A uniqueness result for extending orders; with application to collective choice as inconsistency resolution

Two axioms about extending a weak ordering of a set Ω to its power set 2^Ω uniquely determine a lexicographic weak ordering of 2^Ω. The solution is applied to collective choice to resolve majority cycle inconsistencies, and also contrasted with Condorcet.     

Marketing insights from text analysis

Language is an integral part of marketing. Consumers share word of mouth, salespeople pitch services, and advertisements try to persuade. Further, small differences in wording can have a big impact. But while it is clear that language is both frequent and important, how can we extract insight from this new form of data? This paper provides an introduction to the main approaches to automated textual analysis and how researchers can use them to extract marketing insight. We provide a brief summary of dictionaries, topic modeling, and embeddings, some examples of how each approach can be used, and some advantages and limitations inherent to each method. Further, we outline how these approaches can be used both in empirical analysis of field data as well as experiments. Finally, an appendix provides links to relevant tools and readings to help interested readers learn more. By introducing more researchers to these valuable and accessible tools, we hope to encourage their adoption in a wide variety of areas of research.