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Essays on the digital consumer: Mode...

Lee, Clarence.

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Essays on the digital consumer: Models of engagement, upgrade, and referral behaviors.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Essays on the digital consumer: Models of engagement, upgrade, and referral behaviors./
Author:	Lee, Clarence.
Description:	142 p.
Notes:	Source: Dissertation Abstracts International, Volume: 75-10(E), Section: A.
Contained By:	Dissertation Abstracts International75-10A(E).
Subject:	Marketing. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3624380
ISBN:	9781303976834

Essays on the digital consumer: Models of engagement, upgrade, and referral behaviors.
Lee, Clarence.

Essays on the digital consumer: Models of engagement, upgrade, and referral behaviors. - 142 p.

Source: Dissertation Abstracts International, Volume: 75-10(E), Section: A.

Thesis (D.B.A.)--Harvard University, 2014.

This item is not available from ProQuest Dissertations & Theses.

In this dissertation, I present three essays on two empirical models of consumers using Web services. Business-to-consumer (B2C) Web services, such as Facebook, Dropbox and Pandora, have become a major part of the economy. Due to the low cost of digital distribution, these firms can provide their services for free, with the goal to attract a large customer base, while earning revenue by relying on advertisements or charging a small subset of customers for premium features. My goal is to characterize the various stages that a consumer faces when using a Web service: from adopting the service, to using it for personal and social needs, and to paying for the service. In addition, I also model the customer referral process, where the customer becomes a marketing instrument to encourage other customers to adopt. In the first essay, I explore the relationship between how customers find out about a service and how active they are when using the service. I estimate a hidden Markov model (HMM) of consumer behavior, and I characterize how the firms' social media efforts may encourage customers to be more active. In the second essay, I examine the relationships among usage, payment (upgrades), and referrals. I estimate a single agent dynamic structural model to capture these consumer decisions. Lastly, I conclude with an essay that presents the computational challenges in estimating the HMM and the dynamic structural model in a Bayesian fashion, and I also discuss how I use various estimation techniques, parallelization, and Amazon Elastic Compute Cloud to address these issues.

ISBN: 9781303976834Subjects--Topical Terms:

536353
Marketing.

Essays on the digital consumer: Models of engagement, upgrade, and referral behaviors.
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500 $a Source: Dissertation Abstracts International, Volume: 75-10(E), Section: A.
500 $a Advisers: Sunil Gupta; Vineet Kumar.
502 $a Thesis (D.B.A.)--Harvard University, 2014.
506 $a This item is not available from ProQuest Dissertations & Theses.
520 $a In this dissertation, I present three essays on two empirical models of consumers using Web services. Business-to-consumer (B2C) Web services, such as Facebook, Dropbox and Pandora, have become a major part of the economy. Due to the low cost of digital distribution, these firms can provide their services for free, with the goal to attract a large customer base, while earning revenue by relying on advertisements or charging a small subset of customers for premium features. My goal is to characterize the various stages that a consumer faces when using a Web service: from adopting the service, to using it for personal and social needs, and to paying for the service. In addition, I also model the customer referral process, where the customer becomes a marketing instrument to encourage other customers to adopt. In the first essay, I explore the relationship between how customers find out about a service and how active they are when using the service. I estimate a hidden Markov model (HMM) of consumer behavior, and I characterize how the firms' social media efforts may encourage customers to be more active. In the second essay, I examine the relationships among usage, payment (upgrades), and referrals. I estimate a single agent dynamic structural model to capture these consumer decisions. Lastly, I conclude with an essay that presents the computational challenges in estimating the HMM and the dynamic structural model in a Bayesian fashion, and I also discuss how I use various estimation techniques, parallelization, and Amazon Elastic Compute Cloud to address these issues.
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