Link to the University of Pittsburgh Homepage
Link to the University Library System Homepage Link to the Contact Us Form

Essays on Empirical Modeling of Online Assortments and Their Impact on the Consumer Decision Journey

Jha, Kumari Pallavi (2023) Essays on Empirical Modeling of Online Assortments and Their Impact on the Consumer Decision Journey. Doctoral Dissertation, University of Pittsburgh. (Unpublished)

This is the latest version of this item.

[img] PDF
Restricted to University of Pittsburgh users only until 16 May 2025.

Download (2MB) | Request a Copy

Abstract

Online retailers have the ability to present a variety of online assortments of products or services (say, apparel or hotels) in response to consumers’ search queries. Consumers can make decisions and form their own assortments based on online assortments shown by the e-tailers. In Essay 1, we examine the impact of two temporally separated sets of assortments: the available set, which is the initial assortment presented by the e-tailer (in response to the search query), and the consideration set, which is the subset of options shortlisted by the consumer for possible purchase. The results show the positive relationship between horizontal attribute heterogeneity and consideration and the negative relationship between vertical attribute heterogeneity and consideration. Organized assortments are more influential in stimulating consideration. Contingent on consideration, the time to consumption negatively influences purchase incidence.
There are multiple touch points for consumers to collect information and evaluate options in the online setting. Consumers can utilize various options such as add to cart, add to wishlist, comparison panel, one-click purchase etc. to make the process easier for themselves. In Essay 2, we examine an online assortment selected by the consumer—the wishlist. E-tailers across different countries provide the wishlist option so that consumers can search products and add them to wishlists before finally purchasing or eliminating a product. In the first phase, we examine the potential reasons for wishlisting. We examine three datasets provided by an e-tailer and find that consumers use wishlists mainly as a temporary holding area. In the second phase, we examine the antecedents and consequences of wishlisting. The results demonstrate a positive association between session depth and wishlisting incidence, as well as a negative association between session breadth and wishlisting incidence. Furthermore, wishlisting incidence in a session has a positive impact on purchase incidence


Share

Citation/Export:
Social Networking:
Share |

Details

Item Type: University of Pittsburgh ETD
Status: Unpublished
Creators/Authors:
CreatorsEmailPitt UsernameORCID
Jha, Kumari Pallavikpj7@pitt.edukpj7
ETD Committee:
TitleMemberEmail AddressPitt UsernameORCID
Committee CoChairChatterjee, Rabikarrabikar@katz.pitt.edu
Committee CoChairVenkatesh, R.rvenkat@katz.pitt.edu
Committee MemberSwaminathan, Vanithavanitha@katz.pitt.edu
Committee MemberInman, J. Jeffreyjinman@katz.pitt.edu
Committee MemberDang, Chu (Ivy)ivydang@hku.hk
Committee MemberChintagunta, Pradeeppradeep.chintagunta@chicagobooth.edu
Date: 16 May 2023
Date Type: Publication
Defense Date: 19 April 2023
Approval Date: 16 May 2023
Submission Date: 12 May 2023
Access Restriction: 2 year -- Restrict access to University of Pittsburgh for a period of 2 years.
Number of Pages: 147
Institution: University of Pittsburgh
Schools and Programs: Joseph M. Katz Graduate School of Business > Business Administration
Degree: PhD - Doctor of Philosophy
Thesis Type: Doctoral Dissertation
Refereed: Yes
Uncontrolled Keywords: Online Consumer Decision Journey; Consideration; Wishlist; Purchase; Rare Events Modeling
Date Deposited: 16 May 2023 19:24
Last Modified: 16 May 2023 19:24
URI: http://d-scholarship.pitt.edu/id/eprint/44866

Available Versions of this Item

  • Essays on Empirical Modeling of Online Assortments and Their Impact on the Consumer Decision Journey. (deposited 16 May 2023 19:24) [Currently Displayed]

Metrics

Monthly Views for the past 3 years

Plum Analytics


Actions (login required)

View Item View Item