Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
Structural Equation Modeling: Concepts, Issues, and Applications
19973.5k citationsEdward E. Rigdon, Rick H. HoyleJournal of Marketing Researchprofile →
Experiential value: conceptualization, measurement and application in the catalog and Internet shopping environment☆11☆This article is based upon the first author’s doctoral dissertation completed while at Georgia Institute of Technology.
20011.6k citationsEdward E. Rigdon et al.profile →
Advanced Structural Equation Modeling: Issues and Techniques
Countries citing papers authored by Edward E. Rigdon
Since
Specialization
Citations
This map shows the geographic impact of Edward E. Rigdon's research. 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 Edward E. Rigdon with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Edward E. Rigdon more than expected).
Fields of papers citing papers by Edward E. Rigdon
This network shows the impact of papers produced by Edward E. Rigdon. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Edward E. Rigdon. The network helps show where Edward E. Rigdon may publish in the future.
Co-authorship network of co-authors of Edward E. Rigdon
This figure shows the co-authorship network connecting the top 25 collaborators of Edward E. Rigdon.
A scholar is included among the top collaborators of Edward E. Rigdon based on the total number of
citations received by their joint publications. Widths of edges
represent the number of papers authors have co-authored together.
Node borders
signify the number of papers an author published with Edward E. Rigdon. Edward E. Rigdon is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Ringle, Christian M., Edward E. Rigdon, & Marko Sarstedt. (2018). On Comparing Results from CB-SEM and PLS-SEM: Five Perspectives and Five Recommendations. SSRN Electronic Journal.3 indexed citations
3.
Becker, Jan-Michael, Arun Rai, & Edward E. Rigdon. (2013). PREDICTIVE VALIDITY AND FORMATIVE MEASUREMENT IN STRUCTURAL EQUATION MODELING : EMBRACING PRACTICAL RELEVANCE. ScholarWorks - Georgia State University (Georgia State University).133 indexed citations
4.
Baker, Andrew, George P. Moschis, Edward E. Rigdon, & Anil Mathur. (2011). Effects of Family Structure on Compulsive Buying: A Life Course Perspective. ScholarWorks - Georgia State University (Georgia State University).2 indexed citations
Rigdon, Edward E. & Rick H. Hoyle. (1997). Structural Equation Modeling: Concepts, Issues, and Applications. Journal of Marketing Research. 34(3). 412–412.3545 indexed citations breakdown →
13.
Rigdon, Edward E., Leslie A. Hayduk, James Jaccard, & Choi K. Wan. (1997). LISREL: Issues, Debates and Strategies. Journal of Marketing Research. 34(4). 537–537.25 indexed citations
Schumacker, Randall E. & Edward E. Rigdon. (1995). Testing Interaction Effects in Structural Equation Models.. American Educational Research Association Annual Meeting. 1995(1).2 indexed citations
Rigdon, Edward E.. (1990). The performance of the polychoric correlation coefficient in confirmatory factor analysis with ordinal data. Medical Entomology and Zoology.1 indexed citations
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.