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Two Essays on Industrial Organization.

Qiu, Zichen.

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Two Essays on Industrial Organization.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Two Essays on Industrial Organization./
作者:	Qiu, Zichen.
出版者:	Ann Arbor : ProQuest Dissertations & Theses, : 2017,
面頁冊數:	93 p.
附註:	Source: Dissertation Abstracts International, Volume: 78-11(E), Section: A.
Contained By:	Dissertation Abstracts International78-11A(E).
標題:	Economic theory. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10288750
ISBN:	9780355036978

Two Essays on Industrial Organization.
Qiu, Zichen.

Two Essays on Industrial Organization. - Ann Arbor : ProQuest Dissertations & Theses, 2017 - 93 p.

Source: Dissertation Abstracts International, Volume: 78-11(E), Section: A.

Thesis (Ph.D.)--The University of Wisconsin - Madison, 2017.

This thesis is about consumer search and consideration sets generation. It looks at a tradeoff between sampling more products and the cost of evaluation from the perspective of consumers. The ability to collect massive amounts of individual-level data has significantly transformed our society. Large-scale micro-data had fundamentally improved our understandings about consumers' shopping behaviors. A thesis I put forth introduces search time and develops a joint model of optimal search and purchase. To be more specific, it considers both across-stores and within-store search intensities when explaining the heterogeneities observed in consumer consideration sets. I further support this thesis by empirically estimating the model using a disaggregate data set which captured detailed web browsing and buying history for a massive number of Internet users across the United States.

ISBN: 9780355036978Subjects--Topical Terms:

1556984
Economic theory.

Two Essays on Industrial Organization.
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500 $a Source: Dissertation Abstracts International, Volume: 78-11(E), Section: A.
500 $a Adviser: Alan Sorensen.
502 $a Thesis (Ph.D.)--The University of Wisconsin - Madison, 2017.
520 $a This thesis is about consumer search and consideration sets generation. It looks at a tradeoff between sampling more products and the cost of evaluation from the perspective of consumers. The ability to collect massive amounts of individual-level data has significantly transformed our society. Large-scale micro-data had fundamentally improved our understandings about consumers' shopping behaviors. A thesis I put forth introduces search time and develops a joint model of optimal search and purchase. To be more specific, it considers both across-stores and within-store search intensities when explaining the heterogeneities observed in consumer consideration sets. I further support this thesis by empirically estimating the model using a disaggregate data set which captured detailed web browsing and buying history for a massive number of Internet users across the United States.
520 $a In the first part, I apply the DHW model to study consumers' shopping behavior in the online market for jeans. De Los Santos, Hortacsu and Wildenbeest (2012) tests various search paradigms and shows that fixed sample size search model explains the observed search behaviors in online book market more accurately. Different than De Los Santos et al. (2012), this chapter considers the online jeans market where consumer search are much more aggressive. Using a detailed data on consumer web browsing and purchasing histories, this chapter estimates the distribution of search costs and store-preferences across consumers. In addition, this chapter also quantifies the significance of search costs in affecting consumer's choices.
520 $a The second chapter extends the DHW model to incorporate consumers' within-store search. This chapter focuses on differentiated products markets consisting of multi-products stores. Examples of such markets are apparel, auto insurance, electronics and many others. In contrast with previous costly search models, this chapter introduces consumer within-store search time and demonstrates the significance of within-store search in affecting consumers' choice. I develop a joint model of optimal search and purchase and further characterize a closed-form solution of consumers' consideration sets. Using the same individual-level data on web browsing and purchasing histories, I estimate the distributions of search costs and store-preferences across consumers. I also estimate the frequency of ex-post loss of utilities from search. In addition, this chapter compares to the DHW model results and shows the significance of using both across-store and within-store search in explaining observed heterogeneities in consumers' consideration sets and purchases. This study unveils intriguing questions and has a wide range of applicable markets.
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