History and Use of Relative Importance Indices in Organizational Research

By Jeff W. Johnson, James M. LeBreton. 2004

982 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/10ccdf05b6fed66a74a065d2e4341f2340f81206

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Citations in the corpus

Axiomatic arguments for decomposing goodness of fit according to Shapley and Owen values (2012, background): “Very rarely, however, the GOF is allocated to individual regressor variables, even though—or because—the literature provides numerous different approaches to do so [3, 9].”
Unpacking Rumination and Executive Control: A Network Perspective (2017, methodology): “This model considers the contribution each predictor makes to R2 after controlling for multicollinearity, thereby assigning a relative importance metric (lmg) between 0 and 1 to each edge (Grömping, 2006; Johnson & LeBreton, 2004).”
Beyond Global Measures of Relative Importance: Some Insights from Dominance Analysis (2004, background): “…addition to the literature on relative importance: It provides a good, and almost exhaustive, review of the literature on relative importance (J. W. Johnson & LeBreton, 2004 [this issue]); it illustrates the relevance and benefits of proper analysis; and it provides clear guidelines for…”
The Relative Importance of Correlates of Organizational Citizenship Behavior and Counterproductive Work Behavior Using Multiple Sources of Data (2007, background): “This emphasizes predictive power, but in the presence of multicollinearity, it does not specify which variables are the most important (eg, Azen & Budescu, 2003 ; Johnson & LeBreton, 2004 ).”
Engaging and retaining customers with AI and employee service (2020, positive): “Diagnosis of multicollinearity using the variance inflation factor (VIF) was well below the threshold of 3.0, indicating no violation of multicollinearity (Johnson and LeBreton, 2004).”
Leadership, creativity and innovation: a meta-analytic review (2020, background): “…approach that takes into account a variable’s contribution to an outcome by itself and in combination with other predictor variables (see Johnson, 2000; Johnson & LeBreton, 2004; LeBreton & Tonidandel, 2008; Tonidandel & LeBreton, 2011, for a detailed discussion of relative weight analysis).”
Salesperson's listening ability as an antecedent to relationship selling (2013, background): “Dominance analysis is commonly used when examining the relative importance of correlated predictors in a multiple regression and in the case of examining two listening measure this type of test was appropriate (Johnson and LeBreton, 2004).”
Are Bad Experiences Stronger than Good Ones in Mentoring Relationships? Evidence from the Protege and Mentor Perspective. (2010, methodology): “This statistical technique overcomes the inherent limitations of typical approaches used to examine relative importance such as hierarchical regression (see Johnson & LeBreton, 2004).”
Competence- and Integrity-Based Trust in Interorganizational Relationships: Which Matters More? (2018, background): “Such analyses allow researchers to compare the relative importance of predictors, which is the contribution that each individual variable makes to the explained variance of the dependent variable (Johnson & LeBreton, 2004).”