In the first part of the dissertation, we empirically examine the impact of expanded product variety due to the adoption of the Internet on demand concentration, taking endogeneity into consideration. We analyze two large data sets from the movie rental industry at both movie-level and consumer-level. We find that product variety diversifies the demand for niches more significantly than for hits in absolute terms (e.g., the top/bottom 1,000 titles). However, using relative terms (e.g., the top/bottom 10% of titles) to dynamically adjust for the changing product variety, we find that product variety increases the demand for the hits and reduces the demand for the niches. We further find that product variety increases monthly Gini Coefficients, a measure of demand concentration. We propose that new products appear much faster than consumers discover them. Finally, we find no evidence that niche titles satisfy consumer tastes any better than popular titles and that a small number of heavy users are more likely to venture into niches than light users. In the second part of the dissertation, we analyze a large, detailed operational data set from a restaurant chain to shed new light on how workload (defined as the hourly average number of diners assigned to a server) affects servers' performance (measured as hourly sales). We use an exogenous shock - implementation of a labor scheduling software - to disentangle the endogeneity between demand and supply in this setting. We find that when the overall workload is low, an increase in the workload leads to higher server performance. However, there is a saturation point after which any further increase in the workload leads to degradation of performance. In the focal restaurant chain we find that this saturation point is generally not reached and, counter-intuitively, the chain can reduce the staffing level and achieve both significantly higher sales (an estimated 35% increase) and lower labor costs (an estimated 20% decrease).