A Survey-Based Structural Equation Model Analysis on Influencing Factors of Non-Citation

Although bibliometric approach has been frequently utilized to analyse reasons behind non-citation and show relations between uncitedness and impact factors, the survey-based structural equation model approach is not usually used. Therefore, a Likert scale questionnaire was designed to collect data on non-citation and its various types of determinants. The survey-based structural equation model was used to analyse mutual relations and correlation degrees between non-citation rate and its various determinants. As a result, the categories ‘academic status of journal’ and ‘personal features of papers’ were found to be two extremely significant determinants of non-citation rate. Their path coefficients reached 0.83 and 0.43 respectively. Accordingly, the category ‘contents and topics of papers’ was shown to have extremely significant indirect influence on non-citation rate through ‘academic status of journal’. The three observed variables of ‘academic status of journal’ including ‘public praise of journal’, ‘impact factor of journal’, and ‘member of SCI, EI and Scopus Journals’, showed the highest values of indirect effect on the non-citation rate. Furthermore, there were weaker correlations among ‘academic status of journal’, ‘personal features of papers’, ‘contents and topics of papers’ and ‘publicity and recommendation’ except between ‘contents and topics of papers’ and ‘academic status of journal’. Meanwhile, the six observed variables of ‘publicity and recommendation’ and ‘contents and topics of papers’ show the smaller values at ≤0.12 of indirect effect on non-citation rate. Our empirical results suggest some significant determinants of non-citation rate that might enlighten researchers on how to improve the chance of having their works cited, and assist them in expanding their research impact. These findings can also help journal editors to identify contributions with high-citation potential.