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Optimizing Incentives For Systems With Heterogeneous Agents, Chen Chen
Optimizing Incentives For Systems With Heterogeneous Agents, Chen Chen
Dissertations
This dissertation explores new models and applications based on the game theory of incentives. This exploration starts with controlling an invasive insect problem to address one of the most significant challenges facing our forests, the invasion of the Emerald ash borer (EAB), a non-native, wood-boring insect that threatens to kill most ash trees in North America, through designing two new cost-sharing programs between the landowners and local governments. Ash trees are one of North America’s most widely distributed tree genera and a vital part of the green infrastructure of cities, where they provide residents with numerous social, economic, and ecological …
Entrepreneurship And Heterogeneity Among Firms' Strategies: Three Essays, Xi Zhang
Entrepreneurship And Heterogeneity Among Firms' Strategies: Three Essays, Xi Zhang
Dissertations
The first essay of this dissertation focuses on the entrepreneurship survival in the early stage, during which time an entrepreneur plays the game at the "edge of chaos" and improvises in real-time to learn the strategic playing field. It examines the social networks of entrepreneurs and the impact on new venture survival. Specifically, it explores how the entrepreneurs' social connections with other entrepreneurs and their types of employment differentially affect survival during the different stages of the entrepreneurial journey in the United States and India. Using the Global Entrepreneurship Monitor (GEM) dataset, this study documents not only how the social …
Graph Enabled Cross-Domain Knowledge Transfer, Shibo Yao
Graph Enabled Cross-Domain Knowledge Transfer, Shibo Yao
Dissertations
The world has never been more connected, led by the information technology revolution in the past decades that has fundamentally changed the way people interact with each other using social networks. Consequently, enormous human activity data are collected from the business world and machine learning techniques are widely adopted to aid our decision processes. Despite of the success of machine learning in various application scenarios, there are still many questions that need to be well answered, such as optimizing machine learning outcomes when desired knowledge cannot be extracted from the available data. This naturally drives us to ponder if one …