### Abstract

Original language | English |
---|---|

Title of host publication | Partial Least Squares Path Modeling |

Subtitle of host publication | Basic Concepts, Methodological Issues and Applications |

Editors | Hengky Latan, Richard Noonan |

Place of Publication | Cham |

Publisher | Springer |

Pages | 19-39 |

Number of pages | 21 |

ISBN (Electronic) | 978-3-319-64069-3 |

ISBN (Print) | 978-3-319-64068-6 |

DOIs | |

Publication status | Published - 2017 |

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### Cite this

*Partial Least Squares Path Modeling: Basic Concepts, Methodological Issues and Applications*(pp. 19-39). Cham: Springer. https://doi.org/10.1007/978-3-319-64069-3_2

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*Partial Least Squares Path Modeling: Basic Concepts, Methodological Issues and Applications.*Springer, Cham, pp. 19-39. https://doi.org/10.1007/978-3-319-64069-3_2

**Partial least squares path modeling : Updated guidelines.** / Henseler, Jörg ; Hubona, Geoffrey; Ray, Pauline Ash.

Research output: Chapter in Book/Report/Conference proceeding › Chapter › Academic › peer-review

TY - CHAP

T1 - Partial least squares path modeling

T2 - Updated guidelines

AU - Henseler, Jörg

AU - Hubona, Geoffrey

AU - Ray, Pauline Ash

PY - 2017

Y1 - 2017

N2 - Partial least squares (PLS) path modeling is a variance-based structural equation modeling technique that is widely applied in business and social sciences. It is the method of choice if a structural equation model contains both factors and composites. This chapter aggregates new insights and offers a fresh look at PLS path modeling. It presents the newest developments, such as consistent PLS, confirmatory composite analysis, and the heterotrait-monotrait ratio of correlations (HTMT). PLS path modeling can be regarded as an instantiation of generalized canonical correlation analysis. It aims at modeling relationships between composites, i.e., linear combinations of observed variables. A recent extension, consistent PLS, makes it possible to also include factors in a PLS path model. The chapter illustrates how to specify a PLS path model consisting of construct measurement and structural relationships. It also shows how to integrate categorical variables. A particularly important consideration is model identification: Every construct measured by multiple indicators must be embedded into a nomological net, which means that there must be at least one other construct with which it is related. PLS path modeling results are useful for exploratory and confirmatory research. The chapter provides guidelines for assessing the fit of the overall model, the reliability and validity of the measurement model, and the relationships between constructs.

AB - Partial least squares (PLS) path modeling is a variance-based structural equation modeling technique that is widely applied in business and social sciences. It is the method of choice if a structural equation model contains both factors and composites. This chapter aggregates new insights and offers a fresh look at PLS path modeling. It presents the newest developments, such as consistent PLS, confirmatory composite analysis, and the heterotrait-monotrait ratio of correlations (HTMT). PLS path modeling can be regarded as an instantiation of generalized canonical correlation analysis. It aims at modeling relationships between composites, i.e., linear combinations of observed variables. A recent extension, consistent PLS, makes it possible to also include factors in a PLS path model. The chapter illustrates how to specify a PLS path model consisting of construct measurement and structural relationships. It also shows how to integrate categorical variables. A particularly important consideration is model identification: Every construct measured by multiple indicators must be embedded into a nomological net, which means that there must be at least one other construct with which it is related. PLS path modeling results are useful for exploratory and confirmatory research. The chapter provides guidelines for assessing the fit of the overall model, the reliability and validity of the measurement model, and the relationships between constructs.

U2 - 10.1007/978-3-319-64069-3_2

DO - 10.1007/978-3-319-64069-3_2

M3 - Chapter

SN - 978-3-319-64068-6

SP - 19

EP - 39

BT - Partial Least Squares Path Modeling

A2 - Latan, Hengky

A2 - Noonan, Richard

PB - Springer

CY - Cham

ER -