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Benchmarking and Performance Measurement: A Statistical Analysis

Moffett, Sandra, Anderson-Gillespie, Karen and McAdam, Rodney (2008) Benchmarking and Performance Measurement: A Statistical Analysis. Benchmarking: An International Journal, 15 (4). pp. 368-381. [Journal article]

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URL: http://www.emeraldinsight.com/10.1108/14635770810887203

DOI: 10.1108/14635770810887203


Purpose – The purpose of this paper is to explore the theoretical understanding and practical application of lead benchmarking and performance measurement as a way to achieve organisational change. Design/methodology/approach – The paper combines a theory building/theory testing approach. Based on literary findings a conceptual model has been postulated to identify constructs associated with upstream performance measurement and lead benchmarking. A selection of research questions are posed and tested via empirical study. The survey instrument was distributed to 800 UK organisations which resulted in 157 responses. Findings – Results from the empirical research indicate that new lead, forward looking, predictive benchmarks need to be developed to support lead benchmarking and performance measurement activities. Furthermore, it was found that currently larger organisations are more likely to adopt these practices, with considerable variation across organisational sectors. Research limitations/implications – The empirical research achieved a 19.6 per cent response rate. While this is adequate to report statistical representation, further data collection would be beneficial for industry generalisations. Practical implications – Many organisations struggle to grasp metric measurement for lead benchmarking. This paper may provide insight into key factors to be considered for lead benchmarking uptake. Originality/value – This paper builds on current literature and develops a conceptual model which is then tested via empirical research. This is a novel approach in the area of lead benchmarking.

Item Type:Journal article
Keywords:Benchmarking, Performance measures, Statistical Analysis
Faculties and Schools:Faculty of Computing & Engineering
Ulster Business School > Department of Management and Leadership
Faculty of Computing & Engineering > School of Computing and Intelligent Systems
Ulster Business School
Research Institutes and Groups:Business and Management Research Institute
ID Code:9606
Deposited By: Dr Sandra Moffett
Deposited On:27 Jan 2010 10:08
Last Modified:08 Oct 2012 11:18

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