Bayesian network methodology is used to model key linkages of the service-profit chain within the context of transportation service satisfaction. Bayesian networks offer some advantages for implementing managerially focused models over other statistical techniques designed primarily for evaluating theoretical models. These advantages are (1) providing a causal explanation using observable variables within a single multivariate model, (2) analysis of nonlinear relationships contained in ordinal measurements, (3) accommodation of branching patterns that occur in data collection, and (4) the ability to conduct probabilistic inference for prediction and diagnostics with an output metric that can be understood by managers and academics. Sample data from 1,101 recent transport service customers are utilized to select and validate a Bayesian network and conduct probabilistic inference.
‘This is a peer reviewed version of the following article:
Anderson, R. D., Mackoy, R. D., Thompson, V. B., & Harrell, G. (September 01, 2004). A Bayesian Network Estimation of the Service-Profit Chain for Transport Service Satisfaction. Decision Sciences, 35, 4, 665-689.,
which has been published in final form at: DOI: 10.1111/j.1540-5915.2004.02575.x. This article may be used for non-commercial purposes in accordance With Wiley Terms and Conditions for self-archiving'.
Anderson, Ronald D. and Mackoy, Robert D., "A Bayesian Network Estimation of the Service-Profit Chain for Transport Service Satisfaction" (2004). Scholarship and Professional Work - Business. 179.