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1. Introduction
In today's knowledge economy, there are much concern associated in finding the best way to measure and report many types of activities that could improve the performance of an organization. Thus, all ambitious and high-performance organizations, whether public or private, are, and must be, interested in developing and deploying effective performance measurement systems (PMS) since it is only through such systems that they can remain high-performance organizations ([77] US Department of Energy, 2000). For over twenty years, researchers have been looking at PMS, often prescribing their usefulness but few venture into the discussion of the specific aspects of the PMS under study such as data (variables), measures, indicators and metrics, and the methods (techniques) used to implement them (see [51], [53] Neely, 1999, 2005; [54], [57] Neely et al. , 1995, 2000; [72] Toni and Tonchia, 2001; [19], [18] Franco-Santos et al. , 2007, 2012; [70] Taticchi et al. , 2010; [11] Choong, 2013). In this paper, a measure, metric and an indicator are collectively, termed as measuring attributes as they possess specific attributes of measurement, and each plays different measuring roles.
[19] Franco-Santos et al. (2007) posited that data (variables), measuring attributes, and a supporting infrastructure (e.g. a simple method of data collection and analysis using Excel or a sophisticated information system facilitated by an enterprise resource planning system) are the features of a PMS. To make things simple, this paper uses the term method(s) for measurement instead of supporting infrastructure. The features are the properties or elements which make up the PMS. The features can be described as the key characteristics that are necessary for the existence of a measuring system. Without these features, a PMS is unable to stand as a measuring system ([19] Franco-Santos et al. , 2007; [11] Choong, 2013). Therefore, it is imperative for us to understand this very important element of PMS.
While data (variables) was discussed by PMS authors but the discussions were confined to the use of financial (accounting) and nonfinancial form, and there is little articulation of data (variables) in terms of the scales of measurement (see [11] Choong, 2013). There is also a dearth of articulation of data (variables) in relation to the measuring attributes; and how the measurement process is implemented...