Faculty Advisor or Committee Member

Joseph Sarkis, Advisor

Faculty Advisor or Committee Member

Dileep G. Dhavale, Committee Member

Faculty Advisor or Committee Member

Sharon Johnson , Committee Member

Faculty Advisor or Committee Member

Purvi Shah, Committee Member

Identifier

etd-042519-115754

Abstract

One of the most significant changes in the evolution of modern business management is that organizations no longer compete as individual entities in the market, but as interlocking supply chains. Markets are no longer simply trading desks but dynamic ecosystems where people, organizations and the environment interact. Products and associated materials and resources are links that bridge supply chains from upstream (sourcing and manufacturing) to downstream (delivering and consuming). The lifecycle of a product plays a critical role in supply chains. Supply chains may be composed by, designed around, and modified for products. Product-related issues greatly impact supply chains. Existing studies have advanced product management and product lifecycle management literature through dimensions of product innovation, product growth, product line extensions, product efficiencies, and product acquisition. Product deletion, rationalization, or reduction research is limited but is a critical issue for many reasons. Sustainability is an important reason for this managerial decision. This study, grounded from multiple literature streams in both marketing and supply chain fields, identified relations and propositions to form a firm-level analysis on the role of supply chains in organizational product deletion decisions. Interviews, observational and archival data from international companies (i.e.: Australia, China, India, and Iran) contributed to the empirical support as case studies through a grounded theory approach. Bayesian analysis, an underused empirical analysis tool, was utilized to provide insights into this underdeveloped research stream; and its relationship to qualitative research enhances broader methodological understanding. Gibbs sampler and reversible jump Markov chain Monte Carlo (MCMC) simulation were used for Bayesian analysis based on collected data. The integrative findings are exploratory but provide insights for a number of research propositions.

Publisher

Worcester Polytechnic Institute

Degree Name

PhD

Department

Management

Project Type

Dissertation

Date Accepted

2019-04-19

Accessibility

Restricted-WPI community only

Subjects

Bayesian analysis, Gibbs sampler, Markov chain Monte Carlo simulation, Product deletion, Product lifecycle, Supply chain management

Available for download on Monday, April 25, 2022

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