Cornell University
Library
Cornell UniversityLibrary

eCommons

Help
Log In(current)
  1. Home
  2. Cornell University Graduate School
  3. Cornell Theses and Dissertations
  4. Essays on Firm and Platform Operations: Information, Marketplace Design and Data-driven Decision Making

Essays on Firm and Platform Operations: Information, Marketplace Design and Data-driven Decision Making

File(s)
Liu_cornellgrad_0058F_12646.pdf (1.66 MB)
Permanent Link(s)
https://doi.org/10.7298/9pq7-tk27
https://hdl.handle.net/1813/110600
Collections
Cornell Theses and Dissertations
Author
Liu, Xiaoyan
Abstract

The recent years have seen the emergence and proliferation of online platforms that serve as an intermediation to connect demand and supply, ranging from business-to-business (B2B) platforms connecting buyers and sellers to peer-to-peer labor platforms connecting customers and service providers in the gig economy. With the advancement of digital technologies, online platforms are superior in their capability to match demand and supply more accurately, economically, and timely. In this dissertation, I study the design of such platforms with a focus on data-driven decision making, operational efficiency, and economics in Chapter 1 and 2. The evolution of the financial market has placed a profound influence on firms. Information asymmetry exists between firms and the investors in the financial market, and managerial short-termism has reported become more phenomenal in firms today. In Chapter 3, I study the impact of managerial short-termism on firms' operational decisions and long-term value. The titles of the three chapters of this dissertation are: (1) Chapter 1: Personalized Recommendation System Design for an Online B2B Platform; (2) Chapter 2: Bonus Competition in the Gig Economy; (3) Chapter 3: Operational Distortion: Compound Effects of Short-termism and Competition. Chapter 1 is joint work with Professor Vishal Gaur. Chapter 2 is joint work with Professor Li Chen and Professor Yao Cui. Chapter 3 is joint work with Professor William Schmidt. This dissertation explores a suite of methodologies including data-driven predictive models, econometrics, and game theory.Chapter 1 develops a data-driven algorithm to design a recommendation system for an online B2B platform and tests its performance in a field experiment. Chapter 2 adopts a Hotelling framework to investigate the pricing strategies of competing labor platforms in the gig economy and their impact on market shares, platform profits, and social welfare. Chapter 3 constructs a signaling game model to examine the impact of managerial short-termism on firms' operational distortion and long-term profits in a competitive environment.

Description
227 pages
Date Issued
2021-08
Keywords
Data-driven Algorithm
•
Gig Economy
•
Platform Operations
•
Recommendation System
•
Short-termism
•
Two-sided Marketplace
Committee Chair
Gaur, Vishal
Committee Member
Schmidt, William
Cui, Yao
Gavirneni, Nagesh
Degree Discipline
Management
Degree Name
Ph. D., Management
Degree Level
Doctor of Philosophy
Rights
Attribution-NonCommercial-NoDerivatives 4.0 International
Rights URI
https://creativecommons.org/licenses/by-nc-nd/4.0/
Type
dissertation or thesis
Link(s) to Catalog Record
https://newcatalog.library.cornell.edu/catalog/15160230

Site Statistics | Help

About eCommons | Policies | Terms of use | Contact Us

copyright © 2002-2026 Cornell University Library | Privacy | Web Accessibility Assistance