In this Insights paper, we examine the continued decrease in the numbers of female coaches of high-profile sports teams. The decline in number of female coaches of high-profile teams is alarming, especially considering the increase in athletic participation among women. Because of this, it is important to examine possible explanations for this issue as a starting point for action and reform. We first detail several relevant examples of recent hires and firings of high-profile coaches in different countries around the world. Then, we briefly examine the relevant literature on gender representation of those working in sport. Using recent women’s basketball coaching changes in the National Collegiate Athletic Association (NCAA) as a case in point, we aim to demonstrate that the trend of decreasing numbers of female coaches continues. We believe the specific setting of college coaches represents the moral global issue of gender inequity in regards to high-performance coaching settings. Specifically, we argue that a three-pronged conceptual approach—cultural capital, role congruity theory, and homologous reproduction—can provide insights into the hiring practices of female coaches in comparison with their male coaching counterparts.
The growth and popularity of eSports cannot be understated. The domain has become so mainstream that colleges and universities are rapidly beginning to launch eSports programs within their athletics departments. In this study, the authors interviewed 33 student-athletes receiving scholarships for participating in eSports at one institution. In all, the identity and social capital of athletes in this "new" athletic arena were explored and compared with previous studies examining "traditional" athletes. The implications of the similarities and differences are discussed and ideas for future research into this emerging field are presented.
We study an inventory placement optimization problem where demand is sensitive to service response time, under the online retailing setting. The main challenge is to achieve the optimal trade‐off between revenue benefits from shorter delivery time and the increase in inventory cost associated with placing inventory closer to market demand. To predict the effects of modified demand under service response time variations, we introduce a demand prediction and elasticity model to quantify the sensitivity in demand for particular product categories. Of course, shortening response time by positioning products close to market demand may increase inventory costs. Hence, the team developed a novel data‐driven two‐stage stochastic programming approach complementing the demand prediction and elasticity model, which optimally trades safety stock with service response time and hence revenue increase. We then illustrate the impact of our approach through data provided by an e‐commerce retailer in North America. Our approach offers supply chain managers a general‐purpose decision support tool that optimizes the inventory network to generate recommended stocking levels for stores, distribution centers, and warehouses on a daily basis.
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