Description
TitleThree essays on data-driven problems
Date Created2018
Other Date2018-10 (degree)
Extent1 online resource (135 pages : illustrations)
DescriptionThis dissertation comprises three essays on data-driven problems. The first essay addresses the dynamic, evolving academic social network through co-authorship. A descriptive analysis of the research publications appearing in Management Science (MS) and Operations Research (OR) from 1995 to 2014 is visualized to throw light on the basic collaboration patterns. The second part of the analysis examines the similarities and differences between MS and OR. The social network characteristics are studied and a clique analysis by size, structure, density, and diversity is performed to understand the factors that drive productivity. Finally, new metrics are introduced to assess the
journals on their openness to new authors, and on the influence of the status of the editorial board on the chance of publishing a submitted article. The second essay focuses on healthcare analytics. It provides a general macro-level review of the healthcare industry. First, the essay includes an analysis of population health (inpatients) in the New York State, disease mapping associated with the gender, age, and race, and the trend over time is also studied. Second, the relationships are explored between hospital charges or costs and service quality ratings, and between hospital charges or costs and
local demographics indicators. Third, hospital profitability and drivers for the profits are investigated. Finally, an optimization model is built to determine the locations and services provided for hospital network expansion. The model is based on the parameters estimated on the New York State inpatient data. The third essay examines the Chinese housing bubble, or, more specifically, on the relationships among housing prices, macroeconomic policies, and physical properties. The aim is to determine the validity, if any, of the many popular conjectures circulated in the media. Based on real-time trading
data of the second-hand housing market in Beijing and macro-economic indicators, a valuation model is developed to establish the housing market trend in China in order to help investors in choosing the appropriate investment strategy, and the policy makers in regulating the market.
NotePh.D.
NoteIncludes bibliographical references
NoteIncludes vita
Noteby He Zhang
Genretheses, ETD doctoral
Languageeng
CollectionGraduate School - Newark Electronic Theses and Dissertations
Organization NameRutgers, The State University of New Jersey
RightsThe author owns the copyright to this work.