Two hundred thirty-nine participants indicated that at least one RIMS they used allowed them to endorse other researchers for their expertise. One hundred fifteen of them revealed that they endorsed other RIMS users for their expertise. To identify the underlying structure of researchers’ motivations to endorse other researchers, we used a factor analysis in which each item in the survey question was treated as a variable. The initial model included 10 variables. Principal components analysis was used to extract factors. The component factor matrix was rotated using the Varimax rotation algorithm with Kaiser normalization. A scree plot suggested selecting the first three eigenvalues. Factor loadings of 0.55 and greater were identified as significant based on the total number of cases. Variables with an MSA below 0.5 or that loaded significantly on more than one factor were removed one by one, and factor loadings were recalculated. The resultant version of the model consisted of 8 variables and 3 factors. The MSA of each of the variables was higher than 0.5, with the overall MSA equal to 0.72 and the Bartlett test of sphericity significant at the 0.0001 level. The model captured 82% of the total variance of the data.