Necessary Condition Analysis (NCA) for the Extended TAM
The project
This sample project contains an example of the necessary condition analysis (NCA) (Dul, 2016; Dul 2020) for the the extended technology acceptance model (TAM), presented by Richter et al. (2020). The dataset includes 174 observations (for further details, see Richter et al., 2020). As explained explained by Hair et al. (2024), Richter et al. (2020), and Richter et al. (2022), the construct scores generated by PLS-SEM (Hair et al. 2022) are used to build regression models for the relationships between the constructs in the structural model. Based on these regression models, SmartPLS supports the NCA.
Download and import
Simply download the project and import it in SmartPLS 4.
References
Dul, J. (2016). Necessary Condition Analysis (NCA): Logic and Methodology of "Necessary but not Sufficient" Causality. Organizational Research Methods, 19(1): 10-52.
Dul, J. (2020). Conducting Necessary Condition Analysis. Sage: London.
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 Ed., Sage: Thousand Oaks.
Hair, J.F., Sarstedt, M., Ringle, C.M., & Gudergan, S.P. (2024). Advanced Issues in Partial Least Squares Structural Equation Modeling (PLS-SEM), 2nd Ed., Thousand Oaks, CA: Sage.
Richter, N. F., Hauff, S., Kolev, A. E., & Schubring, S. (2023). Dataset On An Extended Technology Acceptance Model: A Combined Application of PLS-SEM and NCA. Data in Brief, 109190.
Richter, N. F., Hauff, S., Ringle, C. M., Sarstedt, M., Kolev, A., and Schubring, S. (2023). How to Apply Necessary Condition Analysis in PLS-SEM. In J. F. Hair, R. Noonan & H. Latan (Eds.), Partial Least Squares Structural Equation Modeling: Basic Concepts, Methodological Issues and Applications (forthcoming). Springer: Cham.
Richter, N. F., Schubring, S., Hauff, S., Ringle, C. M., and Sarstedt, M. (2020). When Predictors of Outcomes are Necessary: Guidelines for the Combined use of PLS-SEM and NCA. Industrial Management & Data Systems, 120(12): 2243-2267.
