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Gain more insight from your PLS-SEM results the importance-performance map analysis

Publikationstyp
Journal Article
Date Issued
2016-10-17
Sprache
English
Author(s)
Ringle, Christian M.  orcid-logo
Sarstedt, Marko  
Institut
Personalwirtschaft und Arbeitsorganisation W-9  
TORE-URI
http://hdl.handle.net/11420/4021
Journal
Industrial management & data systems  
Volume
116
Issue
9
Start Page
1865
End Page
1886
Citation
Industrial Management and Data Systems 116 (9): 1865-1886 (2016)
Publisher DOI
10.1108/IMDS-10-2015-0449
Scopus ID
2-s2.0-84992418316
Purpose - The purpose of this paper is to introduce the importance-performance map analysis (IPMA) and explain how to use it in the context of partial least squares structural equation modeling (PLSSEM). A case study, drawing on the IPMA module implemented in the SmartPLS 3 software, illustrates the results generation and interpretation. Design/methodology/approach - The explications first address the principles of the IPMA and introduce a systematic procedure for its use, followed by a detailed discussion of each step. Finally, a case study on the use of technology shows how to apply the IPMA in empirical PLS-SEM studies. Findings - The IPMA gives researchers the opportunity to enrich their PLS-SEM analysis and, thereby, gain additional results and findings. More specifically, instead of only analyzing the path coefficients (i.e. the importance dimension), the IPMA also considers the average value of the latent variables and their indicators (i.e. performance dimension). Research limitations/implications - An IPMA is tied to certain requirements, which relate to the measurement scales, variable coding, and indicator weights estimates. Moreover, the IPMA presumes linear relationships. This research does not address the computation and interpretation of non-linear dependencies. Practical implications - The IPMA is particularly useful for generating additional findings and conclusions by combining the analysis of the importance and performance dimensions in practical PLS-SEM applications. Thereby, the IPMA allows for prioritizing constructs to improve a certain target construct. Expanding the analysis to the indicator level facilitates identifying the most important areas of specific actions. These results are, for example, particularly important in practical studies identifying the differing impacts that certain construct dimensions have on phenomena such as technology acceptance, corporate reputation, or customer satisfaction. Originality/value - This paper is the first to offer researchers a tutorial and annotated example of an IPMA. Based on a state-of-the-art review of the technique and a detailed explanation of the method, this paper introduces a systematic procedure for running an IPMA. A case study illustrates the analysis, using the SmartPLS 3 software.
Subjects
Importance-performance map analysis (IPMA)
Partial least squares (PLS)
SmartPLS
Structural equation modeling (SEM)
Unified theory of acceptance and use of technology (UTAUT)
DDC Class
330: Wirtschaft
380: Handel, Kommunikation, Verkehr
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