When Predictors of Outcomes Are Necessary: Guidelines for the Combined Use of PLS-SEM and NCA

Industrial Management & Data Systems, 120(12), 2243-2267

Posted: 18 Sep 2020 Last revised: 2 Dec 2020

See all articles by Nicole Richter

Nicole Richter

Technical University Hamburg-Harburg (TUHH)

Sandra Schubring

Technical University Hamburg-Harburg (TUHH)

Sven Hauff

University of Hamburg - Faculty of Economics and Business Administration

Christian M. Ringle

Hamburg University of Technology (TUHH)

Marko Sarstedt

Otto-von-Guericke-Universität Magdeburg; University of Newcastle (Australia)

Date Written: August 5, 2020

Abstract

Purpose: This research introduces the combined use of partial least squares–structural equation modeling (PLS-SEM) and necessary condition analysis (NCA) that enables researchers to explore and validate hypotheses following a sufficiency logic, as well as hypotheses drawing on a necessity logic. The authors’ objective is to encourage the practice of combining PLS-SEM and NCA as complementary views of causality and data analysis.

Design/methodology/approach: The authors present guidelines describing how to combine PLS-SEM and NCA. These relate to the specification of the research objective and the theoretical background, the preparation and evaluation of the data set, running the analyses, the evaluation of measurements, the evaluation of the (structural) model and relationships and the interpretation of findings. In addition, the authors present an empirical illustration in the field of technology acceptance.

Findings: The use of PLS-SEM and NCA enables researchers to identify the must-have factors required for an outcome in accordance with the necessity logic. At the same time, this approach shows the should-have factors following the additive sufficiency logic. The combination of both logics enables researchers to support their theoretical considerations and offers new avenues to test theoretical alternatives for established models.

Originality/value: The authors provide insights into the logic, assessment, challenges and benefits of NCA for researchers familiar with PLS-SEM. This novel approach enables researchers to substantiate and improve their theories and helps practitioners disclose the must-have and should-have factors relevant to their decision-making.

Keywords: Necessary condition analysis, NCA, Partial least squares, PLS, PLS-SEM, Structural equation modeling, SEM, Technology acceptance model, TAM

Suggested Citation

Richter, Nicole and Schubring, Sandra and Hauff, Sven and Ringle, Christian M. and Sarstedt, Marko, When Predictors of Outcomes Are Necessary: Guidelines for the Combined Use of PLS-SEM and NCA (August 5, 2020). Industrial Management & Data Systems, 120(12), 2243-2267, Available at SSRN: https://ssrn.com/abstract=3667726

Nicole Richter (Contact Author)

Technical University Hamburg-Harburg (TUHH) ( email )

Schwarzenbergstrasse 95
Hamburg, DE Hamburg 21073
Germany

Sandra Schubring

Technical University Hamburg-Harburg (TUHH) ( email )

Schwarzenbergstrasse 95
Hamburg, DE Hamburg 21073
Germany

Sven Hauff

University of Hamburg - Faculty of Economics and Business Administration ( email )

Von-Melle-Park 5
Hamburg, 20146
Germany

Christian M. Ringle

Hamburg University of Technology (TUHH) ( email )

Am Schwarzenberg-Campus 4
Hamburg, 21073
Germany

HOME PAGE: http://www.tuhh.de/hrmo

Marko Sarstedt

Otto-von-Guericke-Universität Magdeburg ( email )

Universitätspl. 2
PSF 4120
Magdeburg, D-39106
Germany

University of Newcastle (Australia) ( email )

University Drive
Callaghan, NSW 2308
Australia

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