Latent Variable Path Modeling with Partial Least Squares

Technometrics ◽  
1992 ◽  
Vol 34 (1) ◽  
pp. 110 ◽  
Author(s):  
Charles K. Bayne ◽  
Jan-Bernd Lohmöller ◽  
Jan-Bernd Lohmoller
Keyword(s):  
Least Squares ◽  
Partial Least Squares ◽  
Latent Variable ◽  
Path Modeling ◽  
Latent Variable Path

EVALUASI PENERAPAN E-FAKTUR DENGAN MODEL KESUKSESAN SISTEM INFORMASI DELONE DAN MCLEAN (STUDI KASUS DI KPP PRATAMA METRO)

2019 ◽  
Vol 3 (2) ◽  
pp. 129
Author(s):  
Tosan Yanuar Rachmadi ◽  
Riya Dwi Handaka
Keyword(s):  
Least Squares ◽  
Partial Least Squares ◽  
Path Modeling

Penerapan e-Faktur di Indonesia dilaksanakan untuk memudahkan Pengusaha Kena Pajak dalam menerbitkan faktur pajak dengan memanfaatkan teknologi informasi. Namun dalam penerapan e-Faktur yang telah diwajibkan penggunaanya sejak pertengahan 2016 masih ditemukan berbagai kendala. Penelitian ini bertujuan untuk mengevaluasi penerapan e-Faktur dengan menggunakan model kesuksesan sistem informasi DeLone dan McLean dalam mengukur kualitas sistem, kualitas informasi, dan kualitas layanan terhadap kepuasan pengguna serta manfaat bersih. Penelitian ini merupakan penelitian kuntitatif dengan metode studi kasus dan menggunakan data primer yang diperoleh melalui kuesioner yang disebarkan kepada  Pengusaha Kena Pajak (PKP) terdaftar di Kantor Pelayanan Pajak Pratama Metro.Dari hasil penelitian dengan menggunakan partial least squares path modeling, didapatkan bahwa kualitas informasi dan kualitas layanan berpengaruh positif dan signifikan terhadap kepuasan pengguna. Sementara itu, kualitas sistem berpengaruh positif namun tidak signifikan terhadap kepuasan pengguna. Kemudian, kepuasan pengguna juga berpengaruh positif dan signifikan terhadap manfaat bersih yang diterima Pengusaha Kena Pajak. Hasil penelitian ini juga menunjukan bahwa kepuasan pengguna merupakan variabel intervening dalam hubungan antara kualitas informasi dan kualitas layanan terhadap manfaat bersih. Sementara itu kepuasan pengguna tidak dapat menjadi variabel intervening dalam hubungan antara kualitas sistem terhadap manfaat bersih.

scholarly journals A bibliometric study of global research activity in relation to the use of partial least squares for policy evaluation

2021 ◽  
pp. 49-54
Author(s):  
Rosanna Cataldo ◽  
Laura Antonucci ◽  
Corrado Crocetta ◽  
Maria Gabriella Grassia ◽  
Marina Marino
Keyword(s):  
Least Squares ◽  
Partial Least Squares ◽  
Policy Evaluation ◽  
Structural Equation ◽  
Bibliometric Study ◽  
Equation Modeling ◽  
Path Modeling ◽  
Research Activity ◽  
Knowledge Database ◽  
Scopus Database

Structural equation modeling (SEM), especially partial least squares path modeling (PLS-PM) has become a mainstream method in many fields of research. In the last years it has been increasingly disseminated in a variety of disciplines. The researchers have been promoting this new statistical methods for the evaluation of policies. Generally, policy evaluation applies evaluation principles and methods to examine the content, implementation or impact of a policy. To better understand and characterize this trend, a bibliometric study of international papers on this subject has been developed in order to describe the use of SEM and PLS-PM approaches in the policy evaluation in the almost last 20 years. A total of 450 articles from 2000 to 2020 have been selected and analyzed in order to discover the research trends in this field and the main dimensions and words related to the terms “decision making” and “SEM-PLS” approach, that are most commonly employed in the scientific literature. The research has been conducted in theWeb of Science from ISI Web of Knowledge database and Scopus database, with the aim of identifying the major themes, authors, areas, types of the sources, titles, years of publication and countries of these publications, as well as the main themes related to the two topic analyzed

scholarly journals Mensuração da satisfação dos usuários do sistema municipal de estacionamento rotativo pago

2016 ◽  
Vol 9 (1) ◽  
pp. 19-34
Author(s):  
Franciane Cougo da Cruz ◽  
Anderson Cougo da Cruz ◽  
Paulo Sergio Ceretta
Keyword(s):  
Customer Satisfaction ◽  
Least Squares ◽  
Partial Least Squares ◽  
Rio Grande ◽  
Rio Grande Do Sul ◽  
Path Modeling ◽  
Satisfaction Index ◽  
Customer Satisfaction Index

Resumo A pesquisa identifica a percepção dos usuários do serviço público de estacionamento rotativo pela aplicação do modelo European Customer Satisfaction Index (ECSI). O estudo mensurou as relações que envolvem usuários do sistema, uma vez que é necessário conquistar a lealdade deles por intermédio da maximização da sua satisfação e, ainda, identificar aspectos considerados como valores importantes para o cliente. Para a quantificação dessa satisfação, utilizou-se o ECSI, modelo estimado pelo método Partial Least Squares-Path Modeling (PLS-PM), que se caracteriza por sua robustez diante de modelos estruturais compostos por dados com falta de normalidade. Foram coletados dados por meio de questionários aplicados, de forma não aleatória, a 401 usuários do sistema na cidade de Bagé, no Estado do Rio Grande do Sul. Os resultados concluem que o usuário considera o serviço satisfatório, e que esse constructo foi mais afetado pela expectativa e imagem do serviço. Os constructos diferem de forma sistemática para renda e idade. À medida que aumentam esses fatores, a tendência é de que exista uma melhor avaliação do sistema de estacionamento rotativo.

The Use of Partial Least Squares Path Modeling in Causal Inference for Archival Financial Accounting Research

2014 ◽  
Vol 68 (3) ◽  
Author(s):  
Chin Fei Goh ◽  
Mohamad Bilal Ali ◽  
Amran Rasli
Keyword(s):  
Causal Inference ◽  
Least Squares ◽  
Statistical Method ◽  
Partial Least Squares ◽  
Multivariate Regression ◽  
Structural Equation ◽  
Financial Accounting ◽  
Equation Modeling ◽  
Path Modeling ◽  
Accounting Research

In financial accounting research, multivariate regression is almost exclusively the dominant statistical method. By contrast, Partial Least Squares path modeling is a under-utilized statistical method. The aim of this study is to examine how Partial Least Squares path modeling can be applied to the archival financial accounting research. This article first presents an overview on multivariate regression and structural equation modeling. The authors then highlight that advantages of using Partial Least Squares path modeling to address the research constraints in causal inference for archival financial accounting research. 

scholarly journals A test for multigroup comparison using partial least squares path modeling

2019 ◽  
Vol 29 (3) ◽  
pp. 464-477 ◽  
Author(s):  
Michael Klesel ◽  
Florian Schuberth ◽  
Jörg Henseler ◽  
Bjoern Niehaves
Keyword(s):  
Least Squares ◽  
Partial Least Squares ◽  
Statistical Power ◽  
Euclidean Distance ◽  
Geodesic Distance ◽  
Group Differences ◽  
Path Modeling ◽  
Content Type ◽  
Significance Level ◽  
Squared Euclidean Distance

Purpose People seem to function according to different models, which implies that in business and social sciences, heterogeneity is a rule rather than an exception. Researchers can investigate such heterogeneity through multigroup analysis (MGA). In the context of partial least squares path modeling (PLS-PM), MGA is currently applied to perform multiple comparisons of parameters across groups. However, this approach has significant drawbacks: first, the whole model is not considered when comparing groups, and second, the family-wise error rate is higher than the predefined significance level when the groups are indeed homogenous, leading to incorrect conclusions. Against this background, the purpose of this paper is to present and validate new MGA tests, which are applicable in the context of PLS-PM, and to compare their efficacy to existing approaches. Design/methodology/approach The authors propose two tests that adopt the squared Euclidean distance and the geodesic distance to compare the model-implied indicator correlation matrix across groups. The authors employ permutation to obtain the corresponding reference distribution to draw statistical inference about group differences. A Monte Carlo simulation provides insights into the sensitivity and specificity of both permutation tests and their performance, in comparison to existing approaches. Findings Both proposed tests provide a considerable degree of statistical power. However, the test based on the geodesic distance outperforms the test based on the squared Euclidean distance in this regard. Moreover, both proposed tests lead to rejection rates close to the predefined significance level in the case of no group differences. Hence, our proposed tests are more reliable than an uncontrolled repeated comparison approach. Research limitations/implications Current guidelines on MGA in the context of PLS-PM should be extended by applying the proposed tests in an early phase of the analysis. Beyond our initial insights, more research is required to assess the performance of the proposed tests in different situations. Originality/value This paper contributes to the existing PLS-PM literature by proposing two new tests to assess multigroup differences. For the first time, this allows researchers to statistically compare a whole model across groups by applying a single statistical test.

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