A modified PLS path modeling algorithm handling reflective categorical variables and a new model building strategy. (English) Zbl 1161.62460
Summary: Partial least squares (PLS) path modeling has found increased applications in customer satisfaction analysis thanks to its ability to handle complex models. A modified PLS path modeling algorithm together with a model building strategy are introduced and applied to customer satisfaction analysis at the French energy supplier Electricité de France. The modified PLS algorithm handles all kinds of scales (categorical or nominal variables) and is well suited when nominal or binary variables are involved. PLS path modeling and structural equation modeling are confirmatory approaches and thus need an initial conceptual model. A two-step model building strategy is presented; the first step is based on Bayesian networks structure learning to build the measurement model and the second step is based on partial correlation and hypothesis tests to build the structural model. Applications to customer satisfaction data are presented.
MSC:
| 62P99 | Applications of statistics |
| 90B60 | Marketing, advertising |
| 91B42 | Consumer behavior, demand theory |
Keywords:
PLS path modeling; partial least squares; structural equation models; model building strategy; marketing applicationReferences:
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