Universität zu Köln

Becker, Jan-Michael ORCID: 0000-0003-3013-3739, Rai, Arun, Ringle, Christian M. and Voelckner, Franziska (2013). DISCOVERING UNOBSERVED HETEROGENEITY IN STRUCTURAL EQUATION MODELS TO AVERT VALIDITY THREATS. MIS Q., 37 (3). S. 665 - 716. MINNEAPOLIS: SOC INFORM MANAGE-MIS RES CENT. ISSN 0276-7783

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Abstract

A large proportion of information systems research is concerned with developing and testing models pertaining to complex cognition, behaviors, and outcomes of individuals, teams, organizations, and other social systems that are involved in the development, implementation, and utilization of information technology. Given the complexity of these social and behavioral phenomena, heterogeneity is likely to exist in the samples used in IS studies. While researchers now routinely address observed heterogeneity by introducing moderators, a priori groupings, and contextual factors in their research models, they have not examined how unobserved heterogeneity may affect their findings. We describe why unobserved heterogeneity threatens different types of validity and use simulations to demonstrate that unobserved heterogeneity biases parameter estimates, thereby leading to Type I and Type II errors. We also review different methods that can be used to uncover unobserved heterogeneity in structural equation models. While methods to uncover unobserved heterogeneity in covariance-based structural equation models (CB-SEM) are relatively advanced, the methods for partial least squares (PLS) path models are limited and have relied on an extension of mixture regression-finite mixture partial least squares (FIMIX-PLS) and distance measure-based methods-that have mismatches with some characteristics of PLS path modeling. We propose a new method-prediction-oriented segmentation (PLS-POS)-to overcome the limitations of FIMIX-PLS and other distance measure-based methods and conduct extensive simulations to evaluate the ability of PLS-POS and FIMIX-PLS to discover unobserved heterogeneity in both structural and measurement models. Our results show that both PLS-POS and FIMIX-PLS perform

Item Type:	Journal Article
Creators:	Creators Email ORCID ORCID Put Code Becker, Jan-Michael UNSPECIFIED orcid.org/0000-0003-3013-3739 UNSPECIFIED Rai, Arun UNSPECIFIED UNSPECIFIED UNSPECIFIED Ringle, Christian M. UNSPECIFIED UNSPECIFIED UNSPECIFIED Voelckner, Franziska UNSPECIFIED UNSPECIFIED UNSPECIFIED
URN:	urn:nbn:de:hbz:38-476262
DOI:	10.25300/MISQ/2013/37.3.01
Journal or Publication Title:	MIS Q.
Volume:	37
Number:	3
Page Range:	S. 665 - 716
Date:	2013
Publisher:	SOC INFORM MANAGE-MIS RES CENT
Place of Publication:	MINNEAPOLIS
ISSN:	0276-7783
Language:	English
Faculty:	Unspecified
Divisions:	Unspecified
Subjects:	no entry
Uncontrolled Keywords:	Keywords Language TECHNOLOGY ACCEPTANCE MODEL; RESPONSE-BASED SEGMENTATION; INFORMATION-SYSTEMS; FINITE-MIXTURE; MEASUREMENT INVARIANCE; FORMATIVE MEASUREMENT; TASK INTERDEPENDENCE; MULTIPLE-REGRESSION; BAYESIAN-ANALYSIS; MEASUREMENT ERROR Multiple languages Computer Science, Information Systems; Information Science & Library Science; Management Multiple languages
URI:	http://kups.ub.uni-koeln.de/id/eprint/47626