Analysis of labour turnover of the bankng industry in Singapore

• Main Authors: Chong, William Kim Khong, Tan Siew Ngi, Tham, David Fook Thai
• Other Authors: Koh Hian Chye
• Format: Final Year Project
• Language: English
• Published: 2015
• Subjects: DRNTU::Business
• Online Access: http://hdl.handle.net/10356/64375
• Institution: Nanyang Technological University

An integrative turnover prediction model for investigating the determinants influencing the turnover intention of clerical bank employees in Singapore is proposed. To facilitate the data collection, a survey was conducted between August and October 1991. A total of 330 questionnaires was administered to the clerical employees of 11 randomly selected commercial banks in Singapore comprising 8 full-licence banks, 2 offshore-licence banks and 1 restricted-licence bank. The range of usable responses received was between 120 and 202 questionnaires, giving a usable response rate of between 36.36% and 61.21% . An array of statistical methods including descriptive statistics, t-:tests of significant differences, simple regression, stepwise regression and multiple regression were employed to analyze the data. 16 independent variables consisting of 6 demographic factors, 8 specific job satisfaction factors and 2 job attitude factors, were measured. The results are supportive of the existence of significant relationships between the set of independent variables presented in the modelling framework and intention to turnover, but the results do not support the hypothesis that all variables influence turnover behaviour. Preliminary uni-variate analyses reveal that 10 of the variables proposed are significantly related to the turnover intention of the subjects 'at a 0.10 level of significance. A multiple· regression on the 16 variables, however, isolated only 3 of these 10 variables as significant at a 0.10 level of significance. The results were confirmed through the use of the stepwise regression process and a final turnover prediction model, with a predictive power of 57.41% (R^2 = 0.5741), was developed from the following variables: (1) kind of work, (2) financial rewards, and (3) career future.