Title: Human resource performance evaluation from CRM perspective: a two-step association rule analysis

Authors: Elham Akhondzadeh-Noughabi; Mohammad Reza Amin-Naseri; Amir Albadvi; Mohammad Saeedi

Addresses: Department of Industrial Engineering, Tarbiat Modares University, P.O. Box 14115-111, Jalal Ale Ahmad Highway, Tehran, Iran ' Department of Industrial Engineering, Tarbiat Modares University, P.O. Box 14115-111, Jalal Ale Ahmad Highway, Tehran, Iran ' Department of Industrial Engineering, Tarbiat Modares University, P.O. Box 14115-111, Jalal Ale Ahmad Highway, Tehran, Iran ' Department of Industrial Engineering, Tarbiat Modares University, P.O. Box 14115-111, Jalal Ale Ahmad Highway, Tehran, Iran

Abstract: Human resource performance evaluation is one of the main activities in human resource management that is critical for organisational development. In this paper, a new approach of using data mining techniques is proposed for HR evaluation from CRM perspective. In fact, a two-step association rule analysis is presented and implemented on the data of a public transportation organisation in Iran. The data relates to a call centre of this organisation, which is established to hear the citizens' voice about the performance of the human resource. At the first step of the proposed technique, the results indicate the sectors with a dominant pattern of negative human resource performance and the ones with a positive performance. At the second step, the factors that cause the negative human resource performance are investigated. The results show that the CRM approach and the proposed technique are capable in the domain of human resource performance evaluation. The obtained knowledge can be very helpful to improve the performance of the human resource in this organisation.

Keywords: human resource management; HRM; performance evaluation; customer relationship management; CRM; data mining; association rule mining; public transport; Iran; call centres.

DOI: 10.1504/IJBPM.2016.073340

International Journal of Business Performance Management, 2016 Vol.17 No.1, pp.89 - 102

Received: 04 Nov 2014
Accepted: 16 Jan 2015
Published online: 30 Nov 2015 *

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