Publications Database

Welcome to the new Schulich Peer-Reviewed Publication Database!

The database is currently in beta-testing and will be updated with more features as time goes on. In the meantime, stakeholders are free to explore our faculty’s numerous works. The left-hand panel affords the ability to search by the following:

  • Faculty Member’s Name;
  • Area of Expertise;
  • Whether the Publication is Open-Access (free for public download);
  • Journal Name; and
  • Date Range.

At present, the database covers publications from 2012 to 2020, but will extend further back in the future. In addition to listing publications, the database includes two types of impact metrics: Altmetrics and Plum. The database will be updated annually with most recent publications from our faculty.

If you have any questions or input, please don’t hesitate to get in touch.

 

Search Results

Pandey, R., D. Chatterjee, and M. Rungtusanatham (Forthcoming). "The Effects of Tie Strength and Data Integration with Supply Base on Supply Disruption Ambiguity and Its Impact on Inventory Turnover", International Journal of Operations and Production Management.

View Paper

Abstract

Purpose

In this paper, the authors introduce supply disruption ambiguity as the inability of a sourcing firm to attach probability point estimates to the occurrence of and to the magnitude of loss from supply disruptions. The authors drew on the “ambiguity in decision-making” literature to define this concept formally, connected it to relevant supply disruption information deficit, positioned it relative to supply chain risk assessment and hypothesized and tested its negative associations with both supply base ties and inventory turnover.

Design/methodology/approach

The authors analysed survey data from 171 North American manufacturers and archival data for a subset (88 publicly listed) of these manufacturers via Ordinary Least Squares (OLS) estimation after ensuring that methodological concerns with survey research have been addressed. They used appropriate controls and employed the heteroskedasticity-based instrumental variable (HBIV) approach to ensure that inferences from our results are not unduly influenced by endogeneity.

Findings

Strong supply base ties decrease supply disruption ambiguity, which, in turn, increases inventory turnover. Moreover, strong supply base ties and data integration with the supply base have indirect and positive effects on inventory turnover. As sourcing firms strengthen ties and integrate data exchange with their supply base, their inventory turnover improves from access to information relevant to detect and diagnose supply disruptions effectively.

Originality/value

Research on supply disruption management has paid more attention to the “disruption recovery” stage than to the “disruption discovery” stage. In this paper, the authors add novel insights regarding the recognition and diagnosis aspects of the “disruption discovery” stage. These novel insights reveal how and why sourcing firms reduce their overall ambiguity associated with detecting and assessing losses from supply disruptions through establishing strong ties with their supply base and how and why reducing such ambiguity improves inventory turnover performance.