Campus Units

Supply Chain and Information Systems

Document Type

Article

Publication Version

Accepted Manuscript

Publication Date

5-5-2019

Journal or Book Title

Journal of Business Analytics

DOI

10.1080/2573234X.2019.1609341

Abstract

It is said that knowledge is power, yet often, decision makers ignore information that ought to be considered. The phenomenon known as Semmelweis reflex occurs when new knowledge is rejected because it contradicts established norms. The goal of evidence-based management (EBMgt) is to help overcome Semmelweis reflex by integrating evaluated external evidence with stakeholder preference, practitioner experiences, and context. This evaluated external evidence is the product of scientific research. In this paper, we demonstrate an EBMgt business analytics model that uses computer simulation to provide scientific evidence to help decision makers evaluate equipment replacement problems, specifically the parallel machine replacement problem. The business analytics application is demonstrated in the form of a fleet management problem for a state transportation agency. The resulting analysis uses real-world data allowing decision makers to unfreeze their current system, move to a new state, and re-freeze a new system.

Comments

This is an Accepted Manuscript of Kevin P. Scheibe, Sree Nilakanta, Cliff T. Ragsdale & Bob Younie (2019) An evidence-based management framework for business analytics, published by Taylor & Francis Group in Journal of Business Analytics on 5/05/2019, available online: https://doi.org/10.1080/2573234X.2019.1609341. Posted with permission.

Copyright Owner

Operational Research Society

Language

en

File Format

application/pdf

Published Version

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