Universal Journal of Management Vol. 4(5), pp. 223 - 227
DOI: 10.13189/ujm.2016.040501
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Applying Back Propagation Neural Networks in the Prediction of Management Associate Work Retention for Small and Medium Enterprises

Kuo-Yan Wang ^1,*, Hsien-Yu Shun ^2
1 CHINA-ASEAN International College, Dhurakij Pundit University, Thailand
² Shanghai Wei Ming Management Consulting Co., Ltd., China

ABSTRACT

Since investment in employee education and development represents a significant capital expenditure, the recruitment of employees whose personal characteristics, professional skills and abilities meet the required standards are the important aspect of business management. In small and medium enterprises selecting appropriate individuals to fill management positions represents a significant challenge. This paper focused on an empirical case study utilizing the data of 100 management trainees using back propagation neural networks to determine the probability of retaining management associates. Several surprising results were obtained. Implications for win-win employee-employer relations and practice are discussed.

KEYWORDS
Employee Education and Development, Employee Retention, Back Propagation Neural Networks, Management Associate

Cite This Paper in IEEE or APA Citation Styles
(a). IEEE Format:
[1] Kuo-Yan Wang , Hsien-Yu Shun , "Applying Back Propagation Neural Networks in the Prediction of Management Associate Work Retention for Small and Medium Enterprises," Universal Journal of Management, Vol. 4, No. 5, pp. 223 - 227, 2016. DOI: 10.13189/ujm.2016.040501.

(b). APA Format:
Kuo-Yan Wang , Hsien-Yu Shun (2016). Applying Back Propagation Neural Networks in the Prediction of Management Associate Work Retention for Small and Medium Enterprises. Universal Journal of Management, 4(5), 223 - 227. DOI: 10.13189/ujm.2016.040501.