Previously published as: Work Study
Online from: 2004
Subject Area: Performance Management and Measurement
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|Title:||Prioritization of key performance indicators: An integration of analytical hierarchy process and goal setting|
|Author(s):||Arash Shahin, (Department of Management, University of Isfahan, Isfahan, Iran), M. Ali Mahbod, (Department of Industrial Management, Faculty of Postgraduate Studies, Islamic Azad University, Isfahan, Iran)|
|Citation:||Arash Shahin, M. Ali Mahbod, (2007) "Prioritization of key performance indicators: An integration of analytical hierarchy process and goal setting", International Journal of Productivity and Performance Management, Vol. 56 Iss: 3, pp.226 - 240|
|Keywords:||Analytical hierarchy process, Integration, Performance measures|
|Article type:||Research paper|
|DOI:||10.1108/17410400710731437 (Permanent URL)|
|Publisher:||Emerald Group Publishing Limited|
Purpose – The purpose of this paper is to provide an integrated approach that prioritizes organizational key performance indicators (KPIs) in terms of the criteria of SMART (Specific, Measurable, Attainable, Realistic, Time-sensitive) goal setting.
Design/methodology/approach – The research was carried out using the analytical hierarchy process (AHP) technique as the basis for pairwise comparisons of SMART criteria, considering each KPI.
Findings – A new approach is outlined, encompassing step-by-step guidelines for decision makers to conduct the prioritization process of SMART KPIs. The results of the case study highlight the applicability of the proposed approach and the calculation process for prioritizing KPIs.
Research limitations/implications – The rating scales used in the AHP analysis are conceptual; although it identifies which dimensions require improvement, the proposed approach does not provide guidance on an appropriate action plan to address deficiencies; another limitation is that the framework adopted only the SERVQUAL service dimensions.
Originality/value – This paper gives a novel approach for prioritization of KPIs. The proposed approach has a holistic mechanism; it could empower decision-making teams; it is capable of enhancing advanced quality engineering approaches; and provides great opportunities for future research.
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