Capturing heterogeneity and PLS-SEM prediction ability: Alliance governance and innovation

Martin Ratzmann, Siegfried P. Gudergan*, Ricarda Bouncken

*Corresponding author for this work

Publication: Scientific journalJournal articleResearchpeer-review

Abstract

Whether the uses of PLS-SEM latent interaction effect (PLS-LIE), PLS prediction-oriented segmentation (PLS-POS), or PLS-PATHMOX approaches improve prediction ability remains unclear. The present study draws on holdout sample estimations to assess prediction ability for the three approaches. The illustrative empirical model focuses on examining the differences in innovation outcomes that coopetive alliances produce, in which three governance factors may affect the structural model parameter estimates reflecting these differences. The findings suggest improvements in prediction ability with the use of PLS-LIE and PLS-POS but not for PLS-PATHMOX.

Original languageEnglish
Pages (from-to)4593-4603
Number of pages11
JournalJournal of Business Research
Volume69
Issue number10
DOIs
Publication statusPublished - 1 Oct 2016
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2016 Elsevier Inc.

Keywords

  • Alliance
  • Coopetition
  • Governance
  • Heterogeneity
  • Innovation
  • PLS-PATHMOX
  • PLS-POS

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