PLS-SEM for Software Engineering Research: An Introduction and Survey

被引:63
|
作者
Russo, Daniel [1 ]
Stol, Klaas-Jan [2 ,3 ]
机构
[1] Aalborg Univ, Dept Comp Sci, Selma Lagerlofs Vej 300, DK-9220 Aalborg, Denmark
[2] Lero Irish Software Res Ctr, Cork, Ireland
[3] Univ Coll Cork, Sch Comp Sci & Informat Technol, Cork, Ireland
基金
爱尔兰科学基金会;
关键词
Partial least squares; structural equation modeling; research methodology; critical review; PARTIAL LEAST-SQUARES; STRUCTURAL EQUATION MODELS; MANAGEMENT RESEARCH; PRODUCT LINE; FIT INDEXES; SAMPLE-SIZE; UNOBSERVED HETEROGENEITY; DISCRIMINANT VALIDITY; BEHAVIORAL-RESEARCH; STATISTICAL POWER;
D O I
10.1145/3447580
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
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.
引用
收藏
页数:38
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