Structural Equation Modeling with the SmartPLS

458 indexed citations
published 2015

Impact in

Classified as

Authors
Christian M. RingleDirceu da SilvaDiógenes de Souza Bido
Journal
SSRN Electronic Journal

In The Last Decade

doi.org/w10050726 →

Countries where authors are citing Structural Equation Modeling with the SmartPLS

Specialization
Citations

This map shows the geographic impact of Structural Equation Modeling with the SmartPLS. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Structural Equation Modeling with the SmartPLS with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Structural Equation Modeling with the SmartPLS more than expected).

Fields of papers citing Structural Equation Modeling with the SmartPLS

Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of Structural Equation Modeling with the SmartPLS. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the Structural Equation Modeling with the SmartPLS.

About Structural Equation Modeling with the SmartPLS

This paper, published in 2015, received 458 indexed citations . Written by Christian M. Ringle, Dirceu da Silva and Diógenes de Souza Bido covering the research area of Organizational Behavior and Human Resource Management. It is primarily cited by scholars working on Marketing (122 citations), Strategy and Management (112 citations), Sociology and Political Science (104 citations), Organizational Behavior and Human Resource Management (93 citations) and Information Systems and Management (86 citations). Published in SSRN Electronic Journal.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

This paper is also available at doi.org/w10050726.

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