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POSTING TYPE: Revisits

Posted by: Kyung Hoon Kim

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2025 GAMMA WORKSHOP

Combined Usage of the Necessary Condition Analysis (NCA) and Partial Least Squares Structural Equation Modeling (PLS-SEM)

July 24, 2025

The Hong Kong Polytechnic University, Hong Kong

Instructor and a short bio:

Prof. Dr. Christian M. Ringle

Institute of Management and Decision Sciences (MDS)

Hamburg University of Technology, Germany

Email: c.ringle@tuhh.de | Internet: 

Dr. Christian M. Ringle is a Chaired Professor of Management and Decision Sciences at the Hamburg University of Technology, Germany, and an Adjunct Professor at the James Cook University, Australia. His research, which has been cited more than 250,000 time (Google Scholar), focuses on management and marketing topics, method development, business analytics, machine learning, and the application of business research methods to decision making. His contributions have been published in journals such as Industrial Marketing Management, International Journal of Research in Marketing, Information Systems Research, Journal of Business Research, Journal of the Academy of Marketing Science, Long Range Planning, MIS Quarterly, and Organizational Research Methods. Since 2018, Christian has been included in the Clarivate Analytics’ Highly Researchers list. He is a cofounded and codeveloper SmartPLS (), a software tool with a graphical user interface for applying the partial least squares structural equation modeling (PLS-SEM) method.

More information about Professor Ringle can be found at

2. Background on the combined use of PLS-SEM and the NCA:

In their Journal of Management editorial, Bergh et al. (2022) highlight the relevance and increasing use of the necessary condition analysis (NCA; Dul, 2016, 2024) in management research. They also note the unique potential researchers can leverage by combining NCA with the partial least squares structural equation modeling (PLS-SEM) method in their studies. These findings also apply to marketing research. Our special session introduces and encourages the combined use of PLS-SEM and the NCA, enabling researchers to explore and validate hypotheses following a sufficiency logic while also considering a necessity logic.

PLS-SEM belongs to a family of regression-based methods for estimating models with latent variables developed by the Swedish econometrician Herman Wold (1985). Since the 2000s, PLS-SEM has gained widespread popularity in a variety of disciplines, among them (international) marketing and management research (e.g., Guenther, 2023; Hair et al., 2012; Richter et al., 2016; Sarstedt et al., 2022; Sarstedt et al., 2023). The method estimates theoretically established causal-predictive relationships (Wold, 1982) between latent variables while accounting for measurement error inherent in the indicators. The results can empirically substantiate the determinants (X) that lead to an outcome (Y) (Sarstedt et al., 2021). Authors interpreting their PLS-SEM findings often use expressions such as “X increases Y” or “a higher X leads to a higher Y.” The interpretation follows a sufficiency logic (Richter et al., 2020), which is highly relevant for deriving managerial recommendations from the results. For example, researchers aim to understand the factors that lead to a stronger intention to use certain technology by applying different theories of technology acceptance (e.g., Lin & Lin, 2019); or they aim to understand the factors that contribute to a higher loyalty of their customers (e.g., Ahrholdt et al., 2019; Hegner-Kakar et al., 2018).

In contrast to this sufficiency logic of standard PLS-SEM analyses (Becker et al., 2023; Hair et al., 2019; Sarstedt et al., 2021), the NCA follows a necessity logic (“X is necessary for Y”) in that it seeks to identify necessary conditions in variable relationships. A necessary condition is a critical factor for an outcome: if the necessary cause is not in place, the outcome will not materialize. Hence, the necessary condition can be a bottleneck, critical factor, constraint, disqualifier, etc. The right level of a necessary condition must be put and kept in place to avoid guaranteed failure. By adding a different logic and data analysis approach, an NCA adds both rigor and relevance to theory, data analysis, and publications (Dul, 2020). Because of the high practical relevance of NCA results, this relatively new method has recently attracted much attention in the academic community (e.g., Bokrantz & Dul, 2023; Hauff et al., 2021; Richter & Hauff, 2022).

Using PLS-SEM and NCA in combination (Richter et al., 2020; Richter et al., 2023; Shukov et al., 2022; Tiwari et al., 2024) allows researchers to determine the factors that produce the best possible outcome (i.e., the should-have factors; sufficiency logic) and those that are critical for an outcome (i.e., the must-have factors; necessity logic). Importantly, the should-have factors can only increase an outcome after the must-have factors have been taken care of (see also Hauff et al. 2024; Riggs et al, 2024; Sarstedt et al., 2024).

3. Course objectives and learning outcomes:

This workshop will contrast the sufficiency and necessity logic and the foundations of a combined PLS-SEM and NCA use. Participants will comprehend the foundations of PLS-SEM, the NCA, and the combined use of both methods. For a case study illustration, we will use the SmartPLS 4 software (Ringle et al., 2022). We provide insights into the logic, assessment, challenges, and benefits of a combined use of PLS-SEM and NCA. More specifically, participants will comprehend the following topics:

• When and how to use the NCA,
• Fundamentals of PLS-SEM,
• The combined use of PLS-SEM and the NCA,
• Reporting and interpreting results, and
• Combined PLS-SEM and NCA applications using the statistical software SmartPLS.

This course has been designed for researchers interested in state-of-the-art methods for their studies and publication projects. A basic knowledge of multivariate statistics and SEM techniques is helpful but not required.

4. Teaching and learning methods:

• The course is based on these textbooks:
• Dul, J. (2020). Conducting Necessary Condition Analysis. Thousand Oaks, CA: Sage.
• Dul, J. (2021). Advances in Necessary Condition Analysis, Version 0.1. Online book retrieved from: .
• Hair, J. F., Hult, G. T. M., Ringle, C. M., and Sarstedt, M. (2022). A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM). 3rd edition. Thousand Oaks, CA: Sage.
• Hair, J. F., Sarstedt, M., Ringle, C. M., and Gudergan, S. P. (2024). Advanced Issues in Partial Least Squares Structural Equation Modeling (PLS-SEM). 2nd edition. Thousand Oaks, CA: Sage.
• Presentations: The session will cover theory and its application.
• Computer exercises using the latest SmartPLS 4 version: Specifically, theoretical explanations underlying the software procedures and practical exercises where participants will apply their learning to real-world examples provided by the instructors.

5. Registration and teaching resources:

• Conference participants can register for the workshop as part of the conference registration process. Please visit: 
• Tuition: GAMMA Prestige Club Member: USD 100; KSMS Member: USD 150; Non-KSMS Member (Student): USD 200; Non-KSMS Member (Faculty): USD 300
• Comprehensive lecture slides will be provided to all participants
• Bring your laptop computer and a 2 or 3-way power extension lead.
• Download and install the SmartPLS 4 software from  before attending the workshop. Participants will receive detailed instructions – including a two-month SmartPLS 4 license key – shortly before the course starts.

6. Schedule:

Location: The Hong Kong Polytechnic University, Hong Kong

Time	Topic
09:00 – 10:30	Introduction to the necessary condition analysis (NCA) with a practical application example
10:30 – 11:00	Break
11:00 – 12:30	Foundations of partial least squares structural equation modeling (PLS-SEM) with practical application example
12:30 – 13:30	Lunch
13:30 – 15:00	The combined use of PLS-SEM and NCA with practical application example