Term of Award

Spring 2014

Degree Name

Doctor of Philosophy in Logistics and Supply Chain Management (Ph.D.)

Document Type and Release Option

Dissertation (open access)

Department

Department of Marketing and Logistics

Committee Chair

Gerard J. Burke

Committee Member 1

Ednilson Bernardes

Committee Member 2

Alan Mackelprang

Committee Member 3

Christopher Boone

Abstract

Managers no longer view sustainability of organizations only in terms of profitability and economic growth of shareholders. Various competitive pressures are forcing managers to broaden the scope of sustainability to include explicit environmental and societal objectives too. These pressures are emanating from various sources such as depleting natural resources, regulatory policies from governments, erratic weather cycles, demanding customers and brand damage due to exposure about poor working conditions in supplier factories located in other countries. This dissertation consists of three essays that contribute to the practice and literature of strategic sustainable supply chain management by examining its four aspects: measure, manage, mitigate, and market. The purpose of this dissertation is to utilize a multi-method approach and multiple secondary data sources to examine sustainable supply chain management from a strategy point of view.

Three separate but connected studies form the core of this dissertation. Chapter Two of this dissertation proposes a framework of seven market-oriented sustainability strategies by objectively analyzing sustainability reports of leading organizations of four industry sectors using structured content analysis and linear programming techniques.

Chapter Three utilizes linear aggregation methodology and data envelopment analysis to form a sustainability index comprising of various sustainability indicators in logistics and shipping services industry. This index may be used as a decision making tool by managers to evaluate sustainability efforts of their organizations and also to benchmark their sustainability performance over the competition.

Chapter Four examines the sources of differential environmental performance of manufacturing facilities using risk screening environmental indicators database and Markov chain Monte Carlo estimation procedure. The results provide support that resource-based view explains the maximum differential environmental performance of firms as opposed to industry-based view or institutional theory.