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Designing efficient marketplaces for the freight services industry
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Park, Arim. Designing efficient marketplaces for the freight services industry. Retrieved from https://doi.org/doi:10.7282/t3-8h1x-2j91

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TitleDesigning efficient marketplaces for the freight services industry
NamePark, Arim (author); Zhao, Yao (chair); Cho, Soohyun (co-chair); Dreyfus, David (internal member); Rodgers, Mark (internal member); Chen, Roger (outside member); Rutgers University; Graduate School - Newark
Date Created2019
Other Date2019-05 (degree)
SubjectTransportation services, Management, Shipment of goods -- South Korea
Extent1 online resource (xi, 94 pages) : illustrations
DescriptionThis dissertation composes of three essays on market design for freight services: 1) characterizing the key factors for success in a current e-commerce platform of freight services by an empirical approach, 2) designing market matching algorithms for transportation services for both short-term (market efficiency) and long-term (truckers’ equity) prosperity by a mathematical programming approach, 3) classifying compensated vs. non-compensated reviews in the context of transport services and characterize their features based on text mining techniques.
The first essay analyzes an existing freight service platform for the purpose of improving the platform’s efficacy. The process of matching shippers to truckers is central to meeting the demands of the fast-growing freight services market, and existing freight brokerage companies have begun adopting online platforms with the aim of increasing matching rates between shipper and truckers. However, the available platforms are currently plagued by low matching rates and shipper/trucker shortages. By analyzing the data from an online freight service company, we identify the primary factors affecting the matching rates with the expectation that our analysis will provide actionable and pragmatic suggestions for improving freight service online platforms.
The South Korean trucking industry has been facing the challenge of oligopolistic behavior, where most of the transportation demand is satisfied by large transportation companies, while smaller, privately-owned truckers struggle to remain profitable. Furthermore, during peak periods of demand, these larger firms are capacity constrained, causing them to subcontract a portion of their workload to the smaller, privately-owned truckers. Thus, in the second essay, we formulate and solve an augmented resource allocation model that determines the optimal tonnage assignments and trucker share allocations, while simultaneously maximizing total supply chain coordination within the network.
In recent years, online review platforms have emerged for consumers and businesses alike which may significantly affect customer buying behaviors. Smaller business may use compensated reviews to drive reputation and sales, but such reviews are often not labeled as such and can mislead customers. In the third essay, we seek to learn how compensated reviews in transportation services may differ systematically from non-compensated reviews. This study also developed classification techniques based on text mining to identify compensated vs non-compensated reviews published on online-review platforms in freight services.
NotePh.D.
NoteIncludes bibliographical references
Genretheses, ETD doctoral
Persistent URLhttps://doi.org/doi:10.7282/t3-8h1x-2j91
LanguageEnglish
CollectionGraduate School - Newark Electronic Theses and Dissertations
Organization NameRutgers, The State University of New Jersey
RightsThe author owns the copyright to this work.
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