Visiting Assistant Professor of Business Administration
Tomomichi Amano is a Visiting Assistant Professor of Business Administration in the Marketing Unit at HBS. He teaches the Marketing course in the MBA required curriculum.
Tomomichi Amano is a Visiting Assistant Professor of Business Administration in the Marketing Unit at HBS. He teaches the Marketing course in the MBA required curriculum.
Professor Amano's research agenda is twofold. First, he is interested in uncovering ways to merge economics and marketing with rich datasets in order to deepen the understanding of consumer behavior in online markets. The second strand of his research focuses on understanding product line decisions and the diffusion of innovation, particularly in the contexts of markets or products that have substantial environmental consequences.
Professor Amano received a B.A. in economics from Harvard College, as well as a M.A. in economics and Ph.D. in business administration from Stanford University. He has previously taught at Columbia Business School.
My research
agenda
is twofold
.
First,
I am interested in
uncovering
ways
to
merge economics and
marketing
with “big data” and
new methods
,
in order
to deepen
our
understanding of consumer behavior
and marketing.
The second strand
of my research is driven by the question of how marketing influence
In differentiated goods markets with societal implications, quality standards are commonly implemented to avoid the under-provision of innovation. Firms have clear incentives to engage in strategic behavior because policymakers use market outcomes as a benchmark in designing regulation. This study examines a unique energy efficiency standard for television sets, under which future minimum efficiency standards are explicitly a function of current product offerings. The setting illustrates firms' dual incentives at work: A firm better differentiates products under a looser standard but may want to induce a tighter standard if it can benefit from raising rivals' costs. These incentives drive firms to ratchet quality. We develop a structural model of product entry that illustrates how the regulator's standard setting rule affects a firm's product quality decision. Counterfactual simulations illustrate that ratcheting down was prevalent in this market and that incentives to ratchet up did not exist. The results suggest that in many commonly regulated markets in which firms share similar cost structures, firms are likely to experience incentives to ratchet down and delay the introduction of innovative products. The study highlights the importance of understanding supply side incentives, such as ratcheting, in designing and assessing policy.
Many online markets are characterized by sellers that stock large numbers of products and sell each product infrequently. At the same time, consumer browsing information is typically tracked by online retailers and is much more abundant than purchase data. We propose a demand model that caters to this type of setting. Our approach, which is based on search and purchase data, is computationally light and allows for flexible substitution patterns. We apply the model to a data set containing browsing and purchase information from a retailer stocking over 500 products, recover the elasticity matrix, and solve for optimal prices for the entire assortment.
Amano, Tomomichi, Andrew Rhodes, and Stephan Seiler. "Large-Scale Demand Estimation with Search Data." Harvard Business School Working Paper, No. 19-022, September 2018. (Stanford University Research Paper, No. 18-36, August 2018.)
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