The Challenge of Prediction in Information Systems Research

58 Pages Posted: 27 Mar 2008 Last revised: 2 Sep 2014

See all articles by Galit Shmueli

Galit Shmueli

Institute of Service Science, National Tsing Hua University, Taiwan

O. Koppius

Rotterdam School of Management, Erasmus University; Erasmus Research Institute of Management (ERIM)

Date Written: April 10, 2009

Abstract

Empirical research in Information Systems (IS) is dominated by the use of explanatory statistical models for testing causal hypotheses, and by a focus on explanatory power. Predictive statistical models, which are aimed at predicting out-of-sample observations with high accuracy, are rare, and so is attention to predictive power. The distinction between explanatory and predictive statistical models is key, as both types of models play a different, yet essential, role in advancing scientific research. Similarly, explanatory power and predictive accuracy are two distinct qualities of a statistical model, and are measured in different ways. A literature review of MISQ and ISR shows that predictive goals, predictive claims, and predictive statistical models are scarce in mainstream empirical IS research. In addition, we find three questionable common practices: First, even when the stated goal of modeling is predictive, explanatory statistical modeling is often employed. Second, the predictive power of a model is often inferred from its explanatory power. And third, the vast majority of explanatory statistical models lack proper predictive assessment, which is a key scientific requirement. In light of the distinction between explanatory and predictive statistical modeling and power, and current practice in IS, we highlight the main differences between them, focusing on practical issues that confront an empirical researcher in the data analysis process.

Keywords: predictive models, inference, information systems, statistical methods

Suggested Citation

Shmueli, Galit and Koppius, Otto, The Challenge of Prediction in Information Systems Research (April 10, 2009). Robert H. Smith School Research Paper No. RHS 06-152. Available at SSRN: https://ssrn.com/abstract=1112893 or http://dx.doi.org/10.2139/ssrn.1112893

Galit Shmueli (Contact Author)

Institute of Service Science, National Tsing Hua University, Taiwan ( email )

Hsinchu, 30013
Taiwan

HOME PAGE: http://www.iss.nthu.edu.tw

Otto Koppius

Rotterdam School of Management, Erasmus University ( email )

RSM Erasmus University
PO Box 1738
3000 DR Rotterdam
Netherlands
+31 10 408 2032 (Phone)
+31 10 408 9010 (Fax)

Erasmus Research Institute of Management (ERIM)

P.O. Box 1738
3000 DR Rotterdam
Netherlands

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