Creative Destruction? Impact of E-Commerce on the Retail Sector

Abstract

Using an administrative payroll dataset for 2.6 million retail workers, we find that the staggered rollout of a major e-commerce firm's fulfillment centers reduces traditional retail workers' income in geographically proximate counties by 2.4%. Wages of hourly workers, especially part-time hourly workers, decrease significantly, driven by a drop in the number of hours worked. We observe a U-shaped pattern in which both young and old workers experience a sharper decrease in wage income. Consequently, some workers experience an increase in credit card delinquency. Using data for 3.2 million stores, we find that sales (employment) at proximate stores decrease by 4% (2.1%). Exits, especially of young and small stores, increase, and entry decreases. In aggregate, the retail sector loses 938 jobs per county per quarter, and the transportationwarehousing sector (food services sector) gains 256 (143) jobs. Our results highlight how creative destruction led by e-commerce impacts local labor markets.

Location and Price Competition On A Uniform Path with Different Pricing Policies

“…While this might appear at first glance to be a simplistic approximation of the real world, given the inherent analytical complexity of the problem as discussed above, making this assumption allows us to develop closed form solutions that, in turn, yield several key insights (presented as needed in the paper and summarized in the concluding Section 5) which closely approximate real-world instances of competition between online and brick-and-mortar retailers. For example, our model provides a theoretical basis for the adverse impact of online retailing on brick-and-mortar stores in USA over the past two decades, as substantiated in the empirical study by Chava et. al.…”

“…In practice this would imply that the brick-and-mortar retailer would have to ensure that its optimal profit, which is invariant to the size of the total market, always stays sufficiently larger than its own production and/or operational costs to ensure that its net profit meets benchmarks to stay in business. An interesting instance of the adverse impact of this competitive pressure has been documented in the recent empirical study conducted in Chava et. al.…”

“…In doing so, first note that by (15), RU(pU|M*) = 𝑝 U (𝑁 − 2  (2𝑝 U − 3)/4  − 1) = 𝑝 U (𝑁 − 1) − 2𝑝 U  (2𝑝 U − 3)/4  when pU  3.5 and N  4. Once again, as was the case in (5) for M, due to the floor function (2pU-3)/4 present in (15), RU(pU|M*) is also step function of pU, eliminating the possibility of using first order derivative directly on RU(pU|M*) to find 𝑝 U * . Therefore, assume that (2pU -3)/4 is denoted by a non-negative integer k.…”

“…By reapplying (5), we obtain that when pM = pU -(k+1) = pU -k-1, where pU -k-1  0, with M still located at a -interior node, it captures (2k+3) nodes and…”