Term of Award

Spring 2015

Degree Name

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

Document Type and Release Option

Dissertation (open access)

Copyright Statement / License for Reuse

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.


Department of Marketing and Logistics

Committee Chair

Gerard J. Burke

Committee Member 1

Alan W. Mackelprang

Committee Member 2

Cheryl L. Aasheim


Supply Chain Information Technology (SCIT) is a key enabler of effective supply chain management (SCM) activities. In 2013, $300 billion was spent on SCIT by firms globally, an increase by 1.8% and 3.8% compared to 2012 and 2011, respectively. With such significant investments, firms face risks of eroded financial performance if SCIT does not perform as expected. In fact, there is a mix of evidence with some firms benefiting from SCIT while others failing to benefit from investing in SCIT. Despite substantial research relating to utilizing information technology in a SCM context, the impact of SCIT on firm performance remains unclear. In particular, the extant literature has reported contradictive results regarding relationships between SCIT and firm performance. Therefore, the purpose of this dissertation is to conduct a systematic investigation of roles of information technology in SCM and shed light on this extremely important research area.

In chapter 2, we investigate the direct impact of SCIT on firm performance by conducting a meta-analysis study. Specifically, we look at four types of SCIT characteristics (e.g. application integration, data compatibility, analytic ability, and evaluation and alertness ability) within three loci of utilization: upstream, downstream, and both upstream-downstream. We find that SCIT is not universally associated with improved firm performance. In particular, SCIT has multiple characteristics, and each characteristic is linked to different performance indicators.

In chapter 3, we investigate how SCIT can conditionally change the relationship between supply base complexity (SBC) or customer base complexity (CBC) and performance. Extant literature suggests that a complex supply or customer base can lead to suboptimal organizational performance. Using secondary data from the Bureau of Economic Analysis and the Annual Survey of Manufacturers, we are able to examine the impact of SBC and CBC on performance at the industry level of analysis. Further, we find that SCIT helps eliminate the negative impact of SBC and CBC on performance. By systematically investigating the direct and indirect impacts of SCIT on performance, this dissertation contributes to the understanding of the roles of information technology in supply chain management.