Essays on firm strategies in online digital platforms

Deng, Chaoqun
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Ravichandran, T.
Langer, Nishtha
Yu, Shan
Wattal, Sunil
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This dissertation consists of three distinct but related essays about firm strategies in online digital platforms. The first essay explores under what conditions managers will be more likely to respond to electronic word of mouth in online review forums. Using Elaboration Likelihood Model (ELM) as a persuasion theory, we explained how online review information influences managers’ attitudes and subsequently their behavior through the central and peripheral routes. We used data from and applied natural language processing algorithms to capture information embedded in online reviews. The second essay examines the influence of managerial responses to online compliments (i.e. positive reviews) on subsequent customers’ attitudes. It is unclear if managers should respond to positive reviews and if so does such actions help or hurt the firm. In order to understand the effective managerial response strategies to handle online customer compliments, we have to dig deep into online customer compliments and managerial responses. Using natural language processing algorithms and deep learning algorithms, we extracted information presented in customer compliments and managerial responses. In the third essay, we applied social presence theory and the literature links trust and purchase intention to examine how the face disclosure and facial expressions of a provider influence the demand for services or products provided by a sharing economy platform. We used data from to investigate the effect of the face disclosure and facial expressions from a host’s profile picture on the property demand at Airbnb.
August 2018
School of Management
Lally School of Management
Rensselaer Polytechnic Institute, Troy, NY
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