Prediction: coveted, yet forsaken? Introducing a cross-validated predictive ability test in partial least squares path modeling

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Title

Prediction: coveted, yet forsaken? Introducing a cross-validated predictive ability test in partial least squares path modeling

Content partner

University of Waikato

Collection

ResearchCommons@Waikato

Description

Management researchers often develop theories and policies that are forward‐looking. The prospective outlook of predictive modeling, where a model predicts unseen or new data, can complement the retrospective nature of causal‐explanatory modeling that dominates the field. Partial least squares (PLS) path modeling is an excellent tool for building theories that offer both explanation and prediction. A limitation of PLS, however, is the lack of a statistical test to assess whether a proposed or...

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Format

Research Paper

Research format

Journal article

Date created

2020

Creator

Liengaard, Benjamin Dybro / Sharma, Pratyush Nidhi / Hult, G. Tomas M. / Jensen, Morten Berg / Sarstedt, Marko / Hair, Joseph F. / Ringle, Christian M.

URL

https://hdl.handle.net/10289/13641

Related subjects

Social Sciences / Management / Business & Economics / Cross-Validation / Explanation / Partial Least Squares / Prediction / Structural Equation Modeling / CUSTOMER SATISFACTION / CONFIDENCE-INTERVALS / STATISTICAL TESTS / P-VALUES / PLS-SEM / FUTURE / RETHINKING / TECHNOLOGY / ACCEPTANCE / EVOLUTION

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