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Navigating Innovative Marketplaces: Models and Data-driven Strategic Behaviors and Operations
Geng, Jingxuan
Geng, Jingxuan
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2025-08
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Business Administration/Interdisciplinary
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https://doi.org/10.34944/20x9-ge95
Abstract
In the dynamic landscape of contemporary business, the concept of innovative marketplaces has become increasingly prominent. These innovative marketplaces are characterized by rapid technological advancements, shifting consumer behaviors, and fluctuating economic conditions. This dissertation explores the intricate and multifaceted nature of strategic behaviors and operations within such innovative marketplaces, spanning diverse sectors and operational contexts. This dissertation delves into three distinct yet interconnected realms of innovative marketplaces. Specifically, the first essay explores the pricing mechanism and non-pricing interventions for a diagnosis crowdsourcing platform via analytical models and empirical analysis. The second essay shifts focus to the retail competition, particularly the intricate competition between multi-channel retailers and pure eretailers. This essay explores the multi-channel retailer’s optimal offline deployment considering consumers’ showrooming and webrooming behaviors. The last essay examines the strategic decision-making process in maintenance centers of sharing-bike platforms. Employing structural estimation modeling and harnessing the capabilities of machine learning, specifically deep neural networks, this essay illuminates the intricacies of these decisionmaking pathways. Integrating various methodologies in different innovative marketplace settings, it provides a fresh perspective on how businesses can navigate and succeed in these dynamic environments. The insights gained are valuable for business leaders, strategists, and policymakers seeking to optimize operations in the face of constant market evolution. We now elaborate on each of them in a few paragraphs below.
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