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  4. Essays on Information Technology Adoption among Commercial Firms

Essays on Information Technology Adoption among Commercial Firms

File(s)
Chen_cornellgrad_0058F_12868.pdf (3.73 MB)
Permanent Link(s)
https://doi.org/10.7298/zzka-ty38
https://hdl.handle.net/1813/110835
Collections
Cornell Theses and Dissertations
Applied Economics and Management PhD Dissertations
Author
Chen, Ruyu
Abstract

The diffusion of information technologies (IT) in the business sector has the potential to transform industries and affect the performance of firms. My dissertation explores factors that influence business process innovation in IT, and analyze the implications of the use of IT for inventive activities. Chapter 1 provides a research overview. Chapter 2 investigates how worker mobility influences the adoption of a new general-purpose technology (GPT) that requires significant complementary investments. I use the state-level changes to the enforceability of noncompete agreements as a plausible exogenous shock to labor mobility, and observe the adoption of machine learning (ML) from over 153,000 establishments between 2010 and 2018; the results suggest that changes that facilitate worker movements are associated with a significant decline in the likelihood of the adoption of ML. Moreover, the magnitude of establishment response depends upon establishment size, number of large establishments in the same industry-location, and the level of experimentation with analytics technology. Chapter 3 examines how the Internet affects the likelihood that firms cite scientific publications in their patent inventions. I compiled a dataset that contains 541,568 patent citations to scientific papers from 3,651 public firm locations (firm sites in a given metropolitan statistical area) between 1992 and 2000, and identified the staggered adoption of basic Internet at these firms. I show that the Internet enables firms to discover “hidden gems”– commercializable yet under-recognized scientific findings published by early-career scientists, and/or in less prestigious journals, with fewer forward academic citations but with more forward patent citations.

Description
136 pages
Date Issued
2021-12
Keywords
GPT
•
Information technology
•
Innovation
•
Noncompete agreement
•
Patent-to-paper citation
•
Worker mobility
Committee Chair
Forman, Chris
Committee Member
Marx, Matt
Leiponen, Aija E.
Leyden, Benjamin
Selman, Bart
Degree Discipline
Applied Economics and Management
Degree Name
Ph. D., Applied Economics and Management
Degree Level
Doctor of Philosophy
Type
dissertation or thesis
Link(s) to Catalog Record
https://newcatalog.library.cornell.edu/catalog/15312692

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