PLS-SEM for Software Engineering Research

Author:

Russo Daniel1ORCID,Stol Klaas-Jan2ORCID

Affiliation:

1. Department of Computer Science, Aalborg University, Denmark

2. Lero—The Irish Software Research Centre and University College Cork, Ireland

Abstract

Software Engineering (SE) researchers are increasingly paying attention to organizational and human factors. Rather than focusing only on variables that can be directly measured, such as lines of code, SE research studies now also consider unobservable variables, such as organizational culture and trust. To measure such latent variables, SE scholars have adopted Partial Least Squares Structural Equation Modeling (PLS-SEM), which is one member of the larger SEM family of statistical analysis techniques. As the SE field is facing the introduction of new methods such as PLS-SEM, a key issue is that not much is known about how to evaluate such studies. To help SE researchers learn about PLS-SEM, we draw on the latest methodological literature on PLS-SEM to synthesize an introduction. Further, we conducted a survey of PLS-SEM studies in the SE literature and evaluated those based on recommended guidelines.

Funder

Science Foundation Ireland

Publisher

Association for Computing Machinery (ACM)

Subject

General Computer Science,Theoretical Computer Science

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