A Bayesian network estimation of the service-profit chain for transport service satisfaction

被引:41
作者
Anderson, RD [1 ]
Mackoy, RD
Thompson, VB
Harrell, G
机构
[1] Butler Univ, Coll Business Adm, Indianapolis, IN 46208 USA
[2] Indiana Univ, Kelly Sch Business, Indianapolis, IN 46202 USA
[3] Indiana Univ, Indiana Business Res Ctr, Bloomington, IN 47405 USA
[4] Michigan State Univ, Eli Broad Grad Sch Management, E Lansing, MI 48824 USA
关键词
D O I
10.1111/j.1540-5915.2004.02575.x
中图分类号
C93 [管理学];
学科分类号
12 ; 1201 ; 1202 ; 120202 ;
摘要
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.
引用
收藏
页码:665 / 689
页数:25
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