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

Title data

Ratzmann, Martin ; Gudergan, Siegfried P. ; Bouncken, Ricarda B.:
Capturing heterogeneity and PLS-SEM prediction ability : Alliance governance and innovation.
In: Journal of Business Research. Vol. 69 (2016) Issue 10 . - pp. 4593-4603.
ISSN 0148-2963
DOI: https://doi.org/10.1016/j.jbusres.2016.03.051

Abstract in another language

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.

Further data

Item Type: Article in a journal
Refereed: Yes
Additional notes: Journal of Business Research, Special Section on "Prediction-oriented Modeling in Business Research by Means of PLS Path-Modeling"
Keywords: PLS-POS; PLS-PATHMOX; Alliance; Innovation; Governance; Coopetition; Heterogeneity
Institutions of the University: Faculties
Faculties > Faculty of Law, Business and Economics
Faculties > Faculty of Law, Business and Economics > Department of Business Administration
Faculties > Faculty of Law, Business and Economics > Department of Business Administration > Chair Business Administration VI - Strategic Management and Organization
Faculties > Faculty of Law, Business and Economics > Department of Business Administration > Chair Business Administration VI - Strategic Management and Organization > Chair Business Administration VI - Strategic Management and Organization - Univ.-Prof. Dr. Ricarda Bouncken
Result of work at the UBT: Yes
DDC Subjects: 300 Social sciences
300 Social sciences > 330 Economics
Date Deposited: 24 Nov 2016 08:14
Last Modified: 29 Jun 2022 14:01
URI: https://eref.uni-bayreuth.de/id/eprint/35205