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English social housing providers are increasingly turning to social impact measurement to assess their social value. This paper aims to understand the contextual factors causing this rise in the practice, specifically within this sector; the mechanisms that enable it to be effectively implemented within an individual organisation and the outcomes of successful implementation for individual organisations and more widely across the sector and beyond.

A realist theory-based approach is applied to the study of a small number of social housing organisations and leaders within the sector to explore the use of social impact measurement. The paper addresses three questions: Why is social impact measurement being adopted in this sector? How is it successfully implemented? And what happens (outcomes) when it is successfully implemented? Addressing these questions necessitates deeper insight into the contextual pressures that have brought to the fore social impact measurement within the sector and the beneficial outcomes the practice provides (or is anticipated to provide) to social housing providers. The methodological approach of Realist Evaluation (Pawson and Tilley, 1997, 2004) is used to structure and analyse the empirical data and findings into a programme theory for social impact measurement. Realist Evaluation provides a programme theory perspective, seeking to answer the question “what works, for whom and in what circumstances?”. In this research, the “whom” refers to English social housing providers and the circumstances are the contextual conditions experienced by the sector over the past decade. The programme theory aims to set out the links between the contextual drivers for social impact measurement, the mechanisms that bring about its implementation and the outcomes that occur as a result. Within this, greater detail on the implementation perspective is provided by developing an implementation theory using a Theory of Change approach (Connell et al., 1995; Fulbright-Anderson et al., 1998). The implementation theory is then embedded within the wider programme theory so as to bring the two elements together, thereby creating a refinement of the overall theory for social impact measurement. In turn, this paper demonstrates its importance (the outcomes that it can achieve for organisations and the sector) and how it can effectively be implemented to bring about those outcomes.

Social housing providers use social impact measurement both internally, to determine their organisational priorities and externally, to demonstrate their value to local and national governments and cross-sector partners then to shape and influence resource allocation. The practice itself is shown to be an open and active programme, rather than a fixed calculative practice.

The intensive nature of the research means that only a limited number of cases were explored. Further research could test theories developed here against evidence collected from a wider range of cases, e.g. other types of providers or non-adopters.

The research makes a strong contribution to practice in the form of a re-conceptualisation of how social impact measurement can be shown to be effective, based on a deeper understanding of causal mechanisms, how they interact and the outcomes that result. This is of value to the sector as such information could help other organisations both to understand the value of social impact measurement and to provide practical guidance on how to implement it effectively.

As the practice of impact measurement continues to develop, practitioners will need to be aware of any changes to these contextual factors and consider questions such as: is the context still supportive of impact measurement? Does the practice need to be adjusted to meet the needs of the current context? For instance, the recent tragedy at Grenfell Tower has led to a reconsideration of the role of social housing; a new Green Paper is currently being drafted (Ministry for Housing, Communities and Local Government, 2018). This may have a number of implications for social impact measurement, such as a rebalancing of emphasis on outcomes relating to environmental improvements, towards outcomes relating to the well-being of tenants.

Existing literature is largely limited to technical guides. This paper links theory-based evaluation to practice contributing to social housing practice.

Indicators of economic and social phenomena can be useful descriptive and analytical inputs for public policy. The “social indicators movement” has emerged in the last decade and is devoted to the measurement of widely‐ranging dimensions of human welfare. For the most part, questions of systematic measurement for public policy are explored here. Drawing initially on some traditions of measurement in economics, the principal aim is to provide a broad theoretical frame of reference for policy indicator design. Questions of indicator development necessarily involve ideas of suitability or validity of indicators designed for a purpose. Approaches to indicator design for the purpose of enhancing collective decision‐making—including formal model building approaches—are subsumed as special cases once a more general theory is espoused in sections II and III.

This paper provides a balanced commentary on Rossiter’s paper “How to use C-OAR-SE to design optimal standard measures” in this issue of the “European Journal of Marketing”. It also relates the comments in general to Rossiter’s other C-OAR-SE work and throws light on a number of key measurement issues that seem under-appreciated at present in marketing and business research.

The authors use conceptual argument based on measurement theory and philosophy of science.

The authors find that Rossiter’s work makes a number of important points that are necessary in the current stage of development of marketing and social science. However, the authors also find that many of these points are also well made by fundamental measurement theories. When measurement theory is correctly interpreted, the idea of multiple measures of the same thing is not problematic. However, they show that existing social science measurement practice rarely takes account of the important issues at play here.

The authors show that marketing, management and social science researchers need to get better in terms of their appreciation of measurement theory and in their practices of measurement.

The authors identify a number of areas where marketing and social science measurement can be improved, taking account of the important aspects of C-OAR-SE and incorporating them in good practice, without needlessly avoiding existing good practices.

Entrepreneurial orientation (EO) has emerged as a core concept in the field of entrepreneurship. Yet, there continue to be questions about the nature of EO and how best to conceptualize and measure it. This chapter makes the case that EO has grown beyond its roots as a firm-level unidimensional strategy construct and that a new multidimensional version of EO is needed to capture the diverse manifestations and venues for entrepreneurial activity that are now evident around the world – global entrepreneurial orientation (GEO). Building on the five-dimension multidimensional view of EO set forth when Lumpkin and Dess (1996) extended the work of Miller (1983) and Covin and Slevin (1989, 1991), the chapter offers an updated definition of EO and a fresh interpretation of why EO matters theoretically. Despite earnest efforts to reconcile the different approaches to EO, in order to move the study of EO and the theoretical conversation about it forward, we maintain that as a group of scholars and a field, we need to acknowledge that two different versions of EO have emerged. Given that, we consider original approaches to measuring EO, evaluate formative measurement models, consider multiple levels of analysis, call for renewed attention to EO configurations, and discuss whether there is a theory of EO.

Promoters of performance measurement are convinced that performance measurement can greatly contribute to an efficiency boost in the field of public services. The purpose of this article is to treat this as a hypothesis and examine this hypothesis from various theoretical perspectives.

After some introductory remarks dealing with terminology, the article examines the potential offered by performance measurement and performance‐based contracting for increasing the efficiency of public service delivery. As a framework for this investigation, several theories are used in order to obtain a theory‐driven answer.

The majority of the theories applied are sceptical about the assumption that performance measurement will act as an efficiency driver. All in all an ambivalent picture prevails.

Further research is required into the factors which ensure that performance measurement will function as an efficiency driver for public services. Also, the empirical basis which investigates the relationship between performance measurement and efficiency is, up to now, very slim.

This paper looks into the chances of performance measurement – a central plank of new public management – as an efficiency driver. That performance measurement contributes significantly to an increase in efficiency is often articulated in official documents. This belief is treated throughout the paper as a hypothesis. The chances performance measurement may offer are examined from various theoretical angles. On a theoretical level, the paper contributes to obtaining a clearer picture of the potential performance measurement may offer.

This paper aims to critically comment Rossiter’s “How to use C-OAR-SE to design optimal standard measures” in the current issue of EJM and provides a broader perspective on Rossiter’s C-OAR-SE framework and measurement practice in marketing in general.

The paper is conceptual, based on interpretation of measurement theory.

The paper shows that, at best, Rossiter’s mathematical dismissal of convergent validity applies to the completely hypothetical (and highly unlikely) situation where a perfect measure without any error would be available. Further considerations cast serious doubt on the appropriateness of Rossiter’s concrete object, dual subattribute-based single item measures. Being immunized against any piece of empirical evidence, C-OAR-SE cannot be considered a scientific theory and is bound to perpetuate, if not aggravate, the fundamental flaws in current measurement practice. While C-OAR-SE indeed helps generate more content valid instruments, the procedure offers no insights as to whether these instruments work properly to be used in research and practice.

This paper concludes that great caution needs to be exercised before adapting measurement instruments based on the C-OAR-SE procedure, and statistical evidence remains essential for validity assessment.

This paper identifies several serious conceptual and operational problems in Rossiter’s C-OAR-SE procedure and discusses how to align measurement in the social sciences to be compatible with the definition of measurement in the physical sciences.

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.

The application of performance measurement procedures can provide major benefits to organisations. The broad performance measurement need for management applies in a facilities management (FM) context when FM is considered as a subset of general management. To this can be added need which is applicable more narrowly to FM. This paper presents a case for the need for and benefits of performance measurement systems in FM environments. It is discussed together with relevant trends in the performance measurement literature which identify key opportunities in this area. It further discusses the increasing trend towards performance measurement in FM organisations and illustrates the different ways in which authors perceive the relationship between FM and performance measurement. Both motivational and organisational variables are considered and an attempt is made to identify relationships between these issues and performance measurement in FM.

The research practice in management research is dominantly based on structural equation modeling (SEM), but almost exclusively, and often misguidedly, on covariance-based SEM. The purpose of this paper is to question the current research myopia in management research, because the paper adumbrates theoretical foundations and guidance for the two SEM streams: covariance-based and variance-based SEM; and improves the conceptual knowledge by comparing the most important procedures and elements in the SEM study, using different theoretical criteria.

The study thoroughly analyzes, reviews and presents two streams using common methodological background. The conceptual framework discusses the two streams by analysis of theory, measurement model specification, sample and goodness-of-fit.

The paper identifies and discusses the use and misuse of covariance-based and variance-based SEM utilizing common topics such as: first, theory (theory background, relation to theory and research orientation); second, measurement model specification (type of latent construct, type of study, reliability measures, etc.); third, sample (sample size and data distribution assumption); and fourth, goodness-of-fit (measurement of the model fit and residual co/variance).

The paper questions the usefulness of Cronbach's α research paradigm and discusses alternatives that are well established in social science, but not well known in the management research community. The author presents short research illustration in which analyzes the four recently published papers using common methodological background. The paper concludes with discussion of some open questions in management research practice that remain under-investigated and unutilized.