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The purpose of this paper is to add to the small but growing body of research examining the influence of founder gender on new venture access to venture development programs.

Hypotheses were tested utilizing a sample of 482 nascent technology ventures which applied for admittance into a venture development organization headquartered in the southern region of the United States from March 2004 through February 2016.

Findings suggest that female-founded applicant ventures experience a higher likelihood of acceptance into venture development programs than male-founded applicant ventures. Results further suggest that social attention to gender equality reduces this effect for female-founded applicant ventures. Findings extend the understanding of the gendered nature of high-technology venturing and venture development organizations.

The findings of this study may not generalize to new ventures operating in other contexts (e.g., non-U.S., low-tech, and other venture development programs). Additionally, this study's design and data limitations do not allow for the establishment of causality or address founder motivations to apply for acceptance into venture development programs.

This study adds to empirical findings regarding the influence of founder gender on new venture acceptance into venture development programs by developing and testing competing hypotheses. This study also extends extant research by examining the moderating effect of social attention to gender equality on the hypothesized relationships between founder gender and acceptance into venture development programs.

The purpose of this study is to understand the profit implications of analytics-driven centralized discriminatory pricing at the headquarter level compared with sales force price delegation in the purchase of an aftermarket good through an indirect retail channel with symmetric information.

Using individual-level loan application and approval data from a North American financial institution and segment-level customer risk as the price discrimination criterion for the firm, the authors develop a three-stage model that accounts for the salesperson’s price decision within the limits of the latitude provided by the firm; the firm’s decision to approve or not approve a sales application; and the customer’s decision to accept or reject a sales offer conditional on the firm’s approval. Next, the authors compare the profitability of this sales force price delegation model to that of a segment-level centralized pricing model where agent incentives and consumer prices are simultaneously optimized using a quasi-Newton nonlinear optimization algorithm (i.e. Broyden–Fletcher–Goldfarb–Shanno algorithm).

The results suggest that implementation of analytics-driven centralized discriminatory pricing and optimal sales force incentives leads to double-digit lifts in firm profits. Moreover, the authors find that the high-risk customer segment is less price-sensitive and firms, upon leveraging this segment’s willingness to pay, not only improve their bottom-line but also allow these marginalized customers with traditionally low approval rates access to loans. This points out the important customer welfare implications of the findings.

Substantively, to the best of the authors’ knowledge, this paper is the first to empirically investigate the profitability of analytics-driven segment-level (i.e. discriminatory) centralized pricing compared with sales force price delegation in indirect retail channels (i.e. where agents are external to the firm and have access to competitor products), taking into account the decisions of the three key stakeholders of the process, namely, the consumer, the salesperson and the firm and simultaneously optimizing sales commission and centralized consumer price.