A Beginner's Guide to Partial Least Squares Analysis

By Michael Haenlein, Andreas M. Kaplan. 2004

1,715 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Information Systems and Management, Management Science and Operations Research

View Paper: https://www.semanticscholar.org/paper/90821f2a4531bbc1f7df53ee8372e3bd205d23f9

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Citations in the corpus

Lateral Collinearity and Misleading Results in Variance-Based SEM: An Illustration and Recommendations (2012, methodology): “The work of various researchers, especially Karl Gustav Jöreskog, established covariance-based SEM as the most widely used method for SEM (Haenlein & Kaplan, 2004; Hair et al., 2009; Schumacker & Lomax, 2004).”
Antecedents and effects of engaged frontline employees (2011, background): “Further, PLS is known to be robust to multicollinearity (Haenlein and Kaplan, 2004), which may occur between the different constructs in the data.”
Geographical and cognitive proximity effects on innovation performance in SMEs: a way through knowledge acquisition (2011, result): “This specific structural equation analysis is preferred in comparison with other traditional multivariate techniques (Haenlein and Kaplan 2004).”
Mirror, mirror on the wall: a comparative evaluation of composite-based structural equation modeling methods (2017, result): “Our results also cast doubt on the widely held belief that PLS is universally applicable for small sample size situations (e.g., Chin and Newsted 1999; Haenlein and Kaplan 2004; Hair et al. 2011).”
An Empirical Comparison of the Efficacy of Covariance-Based and Variance-Based SEM (2009, methodology): “Article Estimation technique CBSEM PLS Sample size Design factor Number of Indicator indicators distribution Indicator loadings Parameter bias Analysis focus Proper solutions Statistical Power Areskoug (1982) Yes Yes Yes Yes No No Yes No No Hui and Wold (1982) No Yes Yes Yes No No Yes NA No Gerbing ”
Entrepreneurial Orientation and Growth of SMEs: A Causal Model (2008, positive): “The EO dimensions of innovativeness, risk taking and proactiveness were measured using a scale developed by Lumpkin (1998) based on the scales developed and tested for reliability by Khandwalla (1977), Miller and Friesen (1983), Covin and Slevin (1989), and Covin and Covin (1990).”
From social capital to entrepreneurial orientation: The mediating role of dynamic capabilities (2017, methodology): “To develop our empirical analysis, we used structural equation analysis because it has some advantages over traditional multivariate analysis (Haenlein & Kaplan, 2004).”
A new criterion for assessing discriminant validity in variance-based structural equation modeling (2015, background): “Figure 7 shows the reduced ACSI model and the PLS results.”
User Acceptance of Virtual Reality: An Extended Technology Acceptance Model (2020, methodology): “…a flexible method of structural equation modeling that can be applied in a wide range of situations (Hair, Hult, Ringle, & Sarstedt, 2014) and whose requirements in relation to sample size (Haenlein & Kaplan, 2004) and distribution (Chin, 1998) are less restrictive than other modeling approaches.”
Fault detection in multi-sensor networks based on multivariate time-series models and orthogonal transformations (2014, methodology): “Principal Component Analysis (PCA) [22] and Partial Least Squares (PLS) [23], together with statistical pattern classifiers form a major component of statistical feature extraction methods [24].”
Factors Affecting Bloggers' Knowledge Sharing: An Investigation Across Gender (2011, methodology): “…a structural equation modeling technique such as amos or lISREl, PlS is free of strict assumptions regarding the population or scale of measurement [46]. a bootstrap resampling procedure was performed to examine the stability of estimates [27] and to develop robust confidence intervals. all factor…”