Employee perception of managerial leadership power bases in the nationalised commercial banks of Bangladesh : an empirical study
Publisher© 2004 Journal of Business Administration
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CitationJahangir, N., Haq, M., & Ahmed, E. (2004). Employee perception of managerial leadership power bases in the nationalised commercial banks of Bangladesh : an empirical study. Journal of Business Administration, 30(3 & 4), 21–44.
The problems of job performance in the nationalised commercial banks (NCBs) of Bangladesh arise from both physical and managerial sources. While most of the branch offices of the these banks are poorly equipped to handle business activities, absence of efficient leadership qualities are also generally observed among other managerial aspects of effective job performance. Despite the emergence of a significant number of banks and other financial institutions in the private sector, the nationalised commercial banks offer the lion share of banking services of the country because of their large countrywide operational network. The success of the banking industry of Bangladesh therefore depends largely on the success of these NCBs. The success of the NCBs depends on the job performance of their employees at the operational level, which in turn, depends on the managerial ability of their superiors. The leadership quality of the managers at the NCBs of Bangladesh is therefore seen as an essential ingredient for the success of these banks. This research paper attempts to explore the effect of one important aspect leadership---the managers' use of social power---on their ability to manage their subordinates. A sample of randomly selected employees of the three NCBs of the country were asked to give their opinions about their respective superiors on their (superiors') use of the various items of the five bases of social power. Three bases of social power used by the managers of the NCBs of Bangladesh were found to have significant bearings on the employee ., ' perception of the leadership quality of their managers through factor analysis and multiple regression.