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A statement from Michell (Michell, J., “Normal science, pathological science, and psychometrics”, Theory and Psychology, Vol. 10 No. 5, 2000, pp. 639‐67), “psychometrics is a pathology of science”, is contrasted with conventional definitions provided by leading texts. The key to understanding why Michell has made such a statement is bound up in the definition of measurement that characterises quantification of variables within the natural sciences. By describing the key features of quantitative measurement, and contrasting these with current psychometric practice, it is argued that Michell is correct in his assertion. Three avenues of investigation would seem to follow from this position, each of which, it is suggested, will gradually replace current psychometric test theory, principles, and properties. The first attempts to construct variables that can be demonstrated empirically to possess a quantitative structure. The second proceeds on the basis of using qualitative (non‐quantitatively structured) variable structures and procedures. The third, applied numerics, is an applied methodology whose sole aim is pragmatic utility; it is similar in some respects to current psychometric procedures except that “test theory” can be discarded in favour of simpler tests of observational reliability and validity. Examples are presented of what future practice may look like in each of these areas. It is to be hoped that psychometrics begins to concern itself more with the logic of its measurement, rather than the ever‐increasing complexity of its numerical and statistical operations.

Amid increased size and complexity of the banking industry, operational risk has a greater potential to occur in more harmful ways than many other sources of risk. This paper seeks to provide a succinct overview of the current regulatory framework of operational risk under the New Basel Accord with a view to inform a critical debate about the influence of data collection, loss reporting, and model specification on the consistency of risk‐sensitive capital rules.

The paper's approach is to investigate the regulatory implications of varying characteristics of operational risk and different methods to identify operational risk exposure.

The findings reveal that effective operational risk measurement hinges on how the reporting of operational risk losses and the model sensitivity of quantitative methods affect the generation of consistent risk estimates.

The presented findings offer tractable recommendations for a more coherent and consistent regulation of operational risk.

The subject of the quantitative measurement of solderability of electronic components is introduced. The wetting balance in various configurations and modes of operation is being used as the focal point to establish a quantitative measurement capability for solderability of conventional leaded components, surface mounting components and printed circuit interconnections. The principles of operation of the wetting balance and the factors that influence the measurement are discussed. This paper is the first of a series that will cover the development of traceable reference standards for wetting balance calibration, the influence of instrumental design on the measurement, the standardisation of the measurement procedures, the choice and evaluation of a solderability index for the dynamic measurement, and the traceability of the measurement to international standards.

This article introduces the best-worst scaling object case, a quantitative method of producing individual level models of heterogeneous perceptions, for use in behavioural decision making research in projects. Heterogeneous individual perceptions refer to observed or unobserved differences between individual perceptions that impact the outcome being studied. Individual level models of perceptions are important to account for the impact of heterogeneous perceptions on measurement tasks, so they do not become an unobserved source of variance that potentially biases research inferences.

An overview of individual heterogeneity is provided highlighting the requirement for individual level models in quantitative perception measurements. A literature review is then conducted of the quantitative methods and tasks used to measure perceptions in behavioural decision making research in projects and their potential to produce individual level models.

The existing quantitative methods cannot produce the necessary individual level models primarily due to the inability to address individual level scale effects, responses styles and biases. Therefore, individual heterogeneity in perceptions can become an unobserved source of variance that potentially biases research inferences.

A method new to project management research, the best-worst scaling object case, is proposed to produce individual level models of heterogeneous perceptions. Guidance on how to implement this method at the individual level is provided along with a discussion of possible future behavioural decision making research in projects.

This article identifies a largely unacknowledged measurement limitation of quantitative behavioural decision making research in projects and provides a practical solution: implementing the best-worst scaling object case at the individual level.

The purpose of this paper is to highlight the fact that a common universal qualitative model of measurement is lacking in global productivity analysis. International quantitative comparisons of country macro-level measurements of productivity have been available in the world for decades. However, there has been no consensus on what exactly constitute the indicators and measures of productivity with a focus on quality.

Through literature review and analysis, a new conceptual qualitative productivity measurement model is being suggested. This model could become the basis for future research undertakings in productivity studies.

This paper finds that there are differences in the definitions of what constitute productivity at the global level and what measurements could be considered to make productivity studies more quantitative as well as qualitative at the same time.

This paper aims to bring about further discussions for a general agreement on what factors constitute a more well-balanced qualitative as well as quantitative productivity measurement model.

The purpose of this paper is to provide an assessment framework for evaluating the success of knowledge management (KM) initiatives in a government setting.

The approach used was to first conduct a brief review of the leading thinking on KM and intellectual capital (IC) measurement approaches. The selection process used to recommend the results‐based management assessment framework (RMAF) as the most appropriate measurement framework is then discussed together with the development of logic models for all KM objectives. Finally, the validation methodology used, a survey design and data collection methodology, is described.

The study finds that the RMAF framework proved to be a good fit for KM assessment in a government setting.

The evaluation of KM and IC are necessarily organization‐specific. Further research is needed to report on the generalizability of this evaluation approach.

The KM evaluation approach proposed here helped the government organization translate its KM strategy into action and enhanced management of the KM program. The proposed evaluation approach will help ensure that each type of stakeholder receives assessment results in a form that is of greatest use to them.

While there are many KM and IC metrics described in the literature, there have been limited attempts to address the evaluation question from a more holistic perspective. This paper shows how quantitative and qualitative measures can be combined to better assess the success of KM initiatives in a systematic and concrete manner.

The purpose of this paper is to investigate why small- and medium-sized enterprises (SMEs) are using social media and how they should measure its return on investment (ROI). The measurement of economic value associated with the use of social media by business is discussed in order to construct a model designed for analysing the ROI of social media for SMEs. The importance of a planned entry into the social media arena, formulation of measurable goals and objectives and understanding the business process are presented as vital pre-cursors to measuring, and indeed attaining, ROI.

A literature review was compiled to explore the current thinking that exists on business use and measurement of social media in mainstream academic literature and other business-oriented publications. Primary research in the form of a survey was conducted with SMEs to determine the usefulness of social media and how SMEs measure its ROI.

SMEs find some social media applications more valuable than others but 65 per cent of the companies surveyed did not measure the ROI. An overarching framework, aimed at SMEs, is presented which advocates that SMEs should take a strategic focus and plan their use of social media, and draw insight from both quantitative and qualitative data when measuring ROI.

Most existing research on social media is related to large organisations and tends to focus on technical and commercial use rather than examining the value and ROI gained from social media from an SME perspective. This paper offers a simple framework to help SMEs plan their use of social media as well as measure its true value.

Hot and humid climates (HHCs) are potential environmental hazards that directly affect construction workers' health and safety (HS) and negatively impact workers' productivity. Extensive research efforts have addressed the effects of HHCs. However, these efforts have been inconsistent in their approach for selecting factors influencing workers in such conditions. There are also increasing concerns about the drop-off in research interest to follow through intrusive and non-real-time measurements. This review aims to identify the major research gaps in measurements applied in previous research with careful attention paid to the factors that influence the intrusiveness and selection of the applied data collection methods.

This research integrates a manual subjective discussion with a thematic analysis of Leximancer software and an elaborating chronological, geographical and methodological review that yielded 701 articles and 76 peer-reviewed most related articles.

The literature included the physiological parameters as influencing factors and useful indicators for HHC effects and identified site activity intensity as the most influencing work-related factor. In total, three main gaps were identified: (1) the role of substantial individual and work-related factors; (2) managerial interventions and the application of the right time against the right symptoms, sample size and measurement intervals and (3) applied methods of data collection; particularly, the intrusiveness of the utilised sensors.

The focus of researchers and practitioners should be in applying nonintrusive, innovative and real-time methods that can provide crew-level measurements. In particular, methods that can represent the actual effects of allocated tasks are aligned with real-time weather measurements, so proactive HHC-related preventions can be enforced on time.

This review contributes to the field of construction workers' safety in HHCs and enables researchers and practitioners to identify the most influential individual and work-related factors in HHCs. This review also proposes a framework for future research with suggestions to cover the highlighted research gaps and contributes to a critical research area in the construction industry.

Acknowledgement of the social impact created by organisations has become an increasingly frequent discussion among practitioners. The importance of such value creation cannot be understated, yet in an increasingly competitive funding environment, the need to articulate “true” value is paramount. The purpose of this paper is to examine how Australian and US managers of non-profit organisations (NPOs) and foundations view the measurement of the social impact of NPOs.

The paper includes 19 in-depth interviews of non-profit professionals in the USA and Australia. Respondents included non-profit managers, foundation managers and consultants in both countries.

The in-depth interviews found that in both countries respondents generally agreed that objective measures of impact are desirable, but recognised the difficulties in developing objective assessment frameworks enabling comparisons across the non-profit sector. These difficulties, as well as the implications for developing assessments of social value for NPOs, are discussed. This paper demonstrates that there is an opportunity to reposition reporting expectations. The NPO sector can pool together and build on each other’s strengths and market their outcomes as a collective entity. A sector-wide approach provides potential for much needed within-sector mentoring and will showcase the rich and varied outcomes generated by NPOs.

This research compares viewpoints in two Western countries, thus offering at least an exploratory examination of social impact assessment from an international perspective. Additionally, this research shows commonalities in terms of what is valued and what is most difficult for non-profits when determining social impact.

Effective use of post-occupancy evaluation (POE) data – quantitative physical measurements and qualitative occupants’ perceptions are limited due to practical challenges and research gaps. Although building information modelling (BIM) has enabled a paradigm shift in the architecture, engineering and construction (AEC) industries, its use in facility management (FM) is still infancy. Limited research has used building performance data to enable changes to BIM models for the benefit of FM. This paper aims to propose the innovative process to collect and contextualize two fragmented types of POE data sets by filling methodological gap in POE research. Moreover, it presents innovative modelling techniques to facilitate BIM as a more effective platform to visualize such currently fragmented data sets in real-time while enabling a decision-making model to benefit facility managers.

The paper presents a process of capturing cloud-based POE data, both wireless sensor network-based physical measurement data and mobile app-based occupant perception data. Real-time capture and visualization of such building performance data was demonstrated through a pilot data collection. Subsequently, the innovative visualization of the cloud connected data is supported by a prototype game engine-based BIM model.

Cloud-based POE data, both quantitative physical measurements and qualitative occupants’ reported perceptions, can be effectively used in FM practice with the use of innovative data capture and visualization techniques in a beneficial manner for facility operation and management decisions. This paper also demonstrates the ability of BIM to serve as a “single source of truth” to support post-construction building performance data.

While addressing a number of research gaps, the paper provides a holistic approach to BIM-based performance monitoring for smart FM to achieve the ultimate vision of BIM enabled FM. The innovative system is expected to provide a powerful and practical tool for data collection, analysis and visualization for intelligent facility management decision making. This paper contributes to fill an important research and practice gap in the area of next generation smart building management practices.