The first essay of this dissertation explores the determinants of industry-level electronic commerce adoption by U.S. manufacturers using data from various U.S. government programs for the period of 2002 - 2019. Findings from a series of nonlinear mixed effects models reveal that the S-shaped electronic commerce adoption rate is best approximated by a Gompertz curve that assumes nonsymmetrical adoption, as opposed to the more conventional logistics curve that assumes symmetrical adoption. I further find that industries with a higher firm death rate exhibit greater adoption of electronic commerce. Third, I find that average firm size positively affects adoption more in concentrated industries. These findings shed new light on understanding industry-level patterns of technological adoption. The second essay of this dissertation examines how electronic commerce adoption affects manufacturing firms' labor productivity as well as selling, general, and administrative expenses (SG&A) utilizing a multimethod design. Specifically, labor productivity is examined using industry-level data on labor productivity from the Bureau of Labor Statistics, whereas effects on SG&A are examined using firm-level data from WRDS. The industry-level analysis reveals industries with higher rates of electronic commerce adoption see more pronounced increases in labor productivity, holding constant other inputs including capital and purchased inputs. The firm-level analyses show that firms in industries seeing higher rates of electronic commerce adoption experience lower SG&A expenses, holding constant an array of potential confounds. This essay responds to the call from productivity paradox literature for empirical research on the consequences of technology investments and provides insights for policy decision-makers and practitioners for their decision-making on new technology investment.
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