Date of Award

2016

Degree Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

Department

Mechanical, Industrial and Systems Engineering

First Advisor

Valerie Maier-Speredelozzi

Abstract

This thesis provides practical approaches to supply chain (SC) relationship assessment and monitoring for the fields of collaborative supply chain management (CSCM), supplier relationship management (SRM), customer relationship management (CRM), and partner relationship management (PRM). This work presents relationship analysis results concerning sourcing, demand planning, and logistics processes and relationships based upon a case study conducted at a multinational corporation. These results identified key relationship strengths and weaknesses across three value chains. These results, combined with results from the academic literature, are used to develop an organized list of relationship factors useful for relationship assessment and modeling purposes. The relationship factors are used to create a new Supply Chain Relationship Assessment Model (SCRAM) that incorporates the use of Plan-Do-Check-Act (PDCA) cycles and the use of statistical process control (SPC) to assess, monitor, and manage individual relationship performance. These methods can be incorporated into existing customer, supplier, or SCM software systems. This thesis extends and builds upon the existing academic literature in the fields of marketing, purchasing, and supply chain management, most importantly in developing an approach to quantify the impact of supply chain relationship factors and strategic changes upon overall supply chain performance. More accurate and precise quantification of relationship factors and relationship performance could lead to better selection of SC partners, improve SC relationships, lower SC costs, and increase value for customers.

Available for download on Saturday, July 28, 2018

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