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In this study, we examine how gender stereotype biases affect the social support given to entrepreneurs by members of the digital entrepreneurial community. While entrepreneurship is a socially embedded activity, extant social support research in entrepreneurship remains scant. We hypothesize that in the digital entrepreneurial community, when entrepreneurs' conversation topics match their gender role (i.e., being a male and struggling with work-life balance or being a female and struggling with business difficulties), social media commenters' perceived gender role congruity tends to be higher, which in turn leads to a higher likelihood of providing social support. We also hypothesize that social media commenters' gender will moderate the relationship between entrepreneurs' gender and social media commenters' perceived gender role congruity. The results from three studies confirm our hypotheses. [ABSTRACT FROM AUTHOR]

At least three challenges hinder the analysis of online WOM. First, the process of transform unstructured online WOM data can generate many variables, increasing the need for dimension reduction. Second, the volume and valence of online WOM may dramatically change in a short period before and after an incident. Third, important events might trigger symmetric or asymmetric reactions in online WOM across rival products or services. We introduce a new method--multi-view sequential canonical covariance analysis to solve the myriad WOM conversational dimensions, detect WOM dynamic trends, and examine its concurrent effects across multiple firms. This new method also provides greater computational efficiency, and thus can be referred as a more advanced manifold optimization approach. We illustrate the advantages of this new method through an empirical example--the 2017 United Express Flight 3411 incident. We find that United Airlines and its rivals all experienced a sudden increase of negative emotions and a sudden decrease of positive emotions because of the Incident, yet the magnitudes of the changes were more dramatic for United Airlines. This new method provides a novel insight into the online WOM dynamics and can contribute to a wide range of fields. [ABSTRACT FROM AUTHOR]

We argue that the standard statistical models commonly used by management scholars to investigate the relationship between prior entrepreneurial experience and the probability of switching into entrepreneurship from wage employment are less capable of unveiling the true relationship, especially in the context of big data. In particular, because the immense volume of data means that almost everything can be significant, the statistical significance relying on p-values may not imply economic significance. In addition, in the context of big data, more flexible relationships than simple linear relationships (linear, curvilinear, cubic, etc.) are possible, yet the standard statistical models that pre-specify the linear relationships between the independent and dependent variables lack the capability of detecting such relationships. To illuminate these concerns, we re-visit this important relationship using two different models: logistic regression - a standard statistical model commonly used by management scholars, and random forests - a powerful machine learning tool for analyzing big data. Through comparing the discrepant findings of these two models, we assert the benefits of using contemporary approaches to handle big data in re- visiting fundamental questions in management. [ABSTRACT FROM AUTHOR]

While prior studies have explored the impact of CEO share ownership on IPO firm survival, the mixed findings imply that the association is far more complicated than a simple, direct relationship. We use the lens of agency theory to propose an important underlying mechanism - at-IPO discretionary earnings management and evaluate whether it channels the association between CEO share ownership and IPO firm survival. We also suggest that board members representing different principal groups may have varying motivation to monitor at the IPO stage. The levels of director monitoring supported by respective shareholdings therefore will affect the magnitude of CEOs' share ownership impact. Using a sample of 269 entrepreneurial firms that completed an IPO from 2001 to 2007, our results reveal that: (1) CEO share ownership has a U-shaped relationship with at-IPO discretionary earnings management; (2) CVC/BA/Founder directors share ownership moderates this association while VC director share ownership does not; and (3) at-IPO discretionary earnings management mediates the effects of CEO share ownership on IPO firm survival. These findings provide a more complete view of the impact of CEO share ownership on IPO firm survival and also have important implications for understanding entrepreneurial corporate governance. [ABSTRACT FROM AUTHOR]