A Modeling-Based Examination of Determinants Influencing Work Satisfaction Among High Court Lawyers
DOI:
https://doi.org/10.63056/Keywords:
High Court Lawyers, work Satisfaction, work Performance, Workplace Harassment, Senior Attitude, Gender Differences, Statistical Analysis, SPSS, AMOSAbstract
The objective of this study is to examine the direct and indirect relationships between work satisfaction and work performance among lawyers. Specifically, the study investigates the association between work satisfaction and work performance of lawyers working in both private practice and government legal institutions serving in High Courts. Primary data were collected from High Court lawyers across selected jurisdictions. As the determinants of work satisfaction vary across institutional and professional contexts, it is essential to employ measurement approaches that are contextually appropriate for the High Court legal environment. The statistical data analysis techniques employed in this study include descriptive statistics—such as measures of central tendency (mean, median, and mode)—to summarize the distribution of the data. Bivariate statistical methods, including the correlation coefficient, as well as multivariate analysis techniques, were also applied. Graphical representation and advanced modeling were conducted using SPSS and AMOS. The findings reveal that factors such as the attitude of seniors, work satisfaction, workplace harassment, and age group are significantly and positively associated with job performance among lawyers serving in High Courts. work performance was also found to be strongly related to the type of chamber, though the relationship was negative. Furthermore, female High Court lawyers were more likely to report work dissatisfaction compared to their male counterparts. The results also indicate that women lawyers tended to exhibit lower job performance, which in turn negatively influenced their overallwork satisfaction.
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Copyright (c) 2025 Hamza Hundal, Aurangzaib, Hafiz Shabir Ahmad (Author)

This work is licensed under a Creative Commons Attribution 4.0 International License.







