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Blockchain adoption and design for supply chain management
Descriptive
TitleInfo
Title
Blockchain adoption and design for supply chain management
Name
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Chang
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Ai-Chih
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Ai-Chih Chang
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author
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Benjamin
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Benjamin Melamed
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Advisory Committee
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chair
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Katehakis
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Michael
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Michael Katehakis
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Advisory Committee
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co-chair
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(type = family)
Rodgers
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Mark
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Mark Rodgers
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Advisory Committee
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internal member
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Babich
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Volodymyr O
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Volodymyr O Babich
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Advisory Committee
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outside member
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Rutgers University
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Graduate School - Newark
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theses
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2019
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2019-10
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2019
Language
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English
Abstract
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In the current business environment, firms are eager to adopt new technologies as they observe more and more successful business applications thereof. One of the disruptive technologies, Blockchain technology (BCT), is currently drawing public attention owing to the cryptocurrency phenomenon for which BCT serves as the backbone technology. In view of certain innovative features, BCT holds out the promise of impacting Supply Chain Management (SCM), both operationally and financially.
This Blockchain-centered research investigates the impact of BCT on SCM operations as well as its strategic adoption. It provides a holistic treatment and analysis in terms of: (1) Reviewing BCT and comparing it with peer technologies; (2) investigating existing and potential applications of BCT; and (3) identifying business benefits and the impact of BCT, including safety, cost savings, demand
growth and yield improvement. Finally, we extract and explore useful managerial insights via rigorous modeling and analysis, and extensive numerical studies.
Combining the strategic decisions on BCT adoption and operational decisions pertaining to supply chains, we develop two mathematical models: (1) a Blockchain-enabled Newsvendor model, and (2) a Dynamic Programming (DP) model. With the objective of optimizing total expected profit, a Newsvendor model is developed to study how BCT adoption impacts optimal inventory decisions
and ultimately how to determine optimal BCT adoption. The model is illustrated with closed-form solutions for selected demand distributions, specifically, Uniform and Normal distributions.
We construct a DP model underlain by a generic stochastic model, where the firm seeks to maximize the total expected discounted profit by jointly managing (1) Blockchain design, (2) production or ordering decisions, and (3) dynamic pricing and selling. We first show that the deployment of BCT can assist firms in reducing order quantities, lowering selling prices and reducing target-inventory levels. It is also shown that higher volatility in either supply or demand lowers the expected profit as compared to lower-volatility counterparts. Our numerical study produces useful managerial insights. For example, some types of goods (e.g., credence goods and experience goods) greatly benefit from the adoption of BCT, but it may not prove beneficial to leverage BCT for certain other types of goods (e.g., search goods). Finally, considering the lifecycle of typical experience goods, it is recommended to adopt BCT as early as possible.
This Blockchain-centered research investigates the impact of BCT on SCM operations as well as its strategic adoption. It provides a holistic treatment and analysis in terms of: (1) Reviewing BCT and comparing it with peer technologies; (2) investigating existing and potential applications of BCT; and (3) identifying business benefits and the impact of BCT, including safety, cost savings, demand
growth and yield improvement. Finally, we extract and explore useful managerial insights via rigorous modeling and analysis, and extensive numerical studies.
Combining the strategic decisions on BCT adoption and operational decisions pertaining to supply chains, we develop two mathematical models: (1) a Blockchain-enabled Newsvendor model, and (2) a Dynamic Programming (DP) model. With the objective of optimizing total expected profit, a Newsvendor model is developed to study how BCT adoption impacts optimal inventory decisions
and ultimately how to determine optimal BCT adoption. The model is illustrated with closed-form solutions for selected demand distributions, specifically, Uniform and Normal distributions.
We construct a DP model underlain by a generic stochastic model, where the firm seeks to maximize the total expected discounted profit by jointly managing (1) Blockchain design, (2) production or ordering decisions, and (3) dynamic pricing and selling. We first show that the deployment of BCT can assist firms in reducing order quantities, lowering selling prices and reducing target-inventory levels. It is also shown that higher volatility in either supply or demand lowers the expected profit as compared to lower-volatility counterparts. Our numerical study produces useful managerial insights. For example, some types of goods (e.g., credence goods and experience goods) greatly benefit from the adoption of BCT, but it may not prove beneficial to leverage BCT for certain other types of goods (e.g., search goods). Finally, considering the lifecycle of typical experience goods, it is recommended to adopt BCT as early as possible.
Subject
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Topic
Blockchain technology
Subject
(authority = RUETD)
Topic
Management
Subject
(authority = LCSH)
Topic
Blockchains (Databases)
Subject
(authority = LCSH)
Topic
Business logistics
RelatedItem
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Title
Rutgers University Electronic Theses and Dissertations
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ETD_10243
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1 online resource (xi, 172 pages) : illustrations
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Ph.D.
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Includes bibliographical references
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Graduate School - Newark Electronic Theses and Dissertations
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rucore10002600001
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NjNbRU
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doi:10.7282/t3-wxwf-xj62
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(authority = ExL-Esploro)
ETD doctoral
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Rights
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The author owns the copyright to this work.
RightsHolder
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Name
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Chang
GivenName
Ai-Chih
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Copyright Holder
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Permission or license
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2019-09-13 23:50:15
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Name
Aichih Chang
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Affiliation
Rutgers University. Graduate School - Newark
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Author Agreement License
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I hereby grant to the Rutgers University Libraries and to my school the non-exclusive right to archive, reproduce and distribute my thesis or dissertation, in whole or in part, and/or my abstract, in whole or in part, in and from an electronic format, subject to the release date subsequently stipulated in this submittal form and approved by my school. I represent and stipulate that the thesis or dissertation and its abstract are my original work, that they do not infringe or violate any rights of others, and that I make these grants as the sole owner of the rights to my thesis or dissertation and its abstract. I represent that I have obtained written permissions, when necessary, from the owner(s) of each third party copyrighted matter to be included in my thesis or dissertation and will supply copies of such upon request by my school. I acknowledge that RU ETD and my school will not distribute my thesis or dissertation or its abstract if, in their reasonable judgment, they believe all such rights have not been secured. I acknowledge that I retain ownership rights to the copyright of my work. I also retain the right to use all or part of this thesis or dissertation in future works, such as articles or books.
Copyright
Status
Copyright protected
Availability
Status
Open
Reason
Permission or license
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2019-10-09T17:09:01
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