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The purpose of this paper is to examine the effect of portrayed smoking status of actors on their popularity with both smoking and non‐smoking young people, as well as their perceptions of the prevalence of smoking

Two experimental studies were conducted with Australian undergraduate university students, in which students were exposed to different versions of mock magazines featuring images of actors smoking and not smoking, as well as control actors.

The attitudes of young people towards well‐known actors were little influenced by the presence or absence of cigarettes, but non‐smoking actors were perceived more favourably when depicted in a group with smoking actors. Smoking actors tended to be preferred by young people who smoked. The results of both studies confirm that young people's estimates of smoking prevalence are considerably inflated.

The results of the current study suggest two key implications for health education: the need to address young people's elevated perceptions of smoking prevalence among their peers, parents, and celebrities by communicating the social norm of non‐smoking; and the potential use of celebrities – such as actors – as spokespersons or role models in anti‐smoking campaigns.

This paper aims to respond to John Rossiter's call for a “Marketing measurement revolution” in the current issue of EJM, as well as providing broader comment on Rossiter's C‐OAR‐SE framework, and measurement practice in marketing in general.

The paper is purely theoretical, based on interpretation of measurement theory.

The authors find that much of Rossiter's diagnosis of the problems facing measurement practice in marketing and social science is highly relevant. However, the authors find themselves opposed to the revolution advocated by Rossiter.

The paper presents a comment based on interpretation of measurement theory and observation of practices in marketing and social science. As such, the interpretation is itself open to disagreement.

There are implications for those outside academia who wish to use measures derived from academic work as well as to derive their own measures of key marketing and other social variables.

This paper is one of the few to explicitly respond to the C‐OAR‐SE framework proposed by Rossiter, and presents a number of points critical to good measurement theory and practice, which appear to remain underdeveloped in marketing and social science.

This paper aims to extend Rossiter’s C-OAR-SE method of measure design (IJRM, 2002, p. 19, p. 4, pp. 305-335; EJM, 2011, p. 45, p. 11, p. 12, pp. 1561-1588) by proposing five distinct construct models for designing optimally content-valid multiple-item and single-item measures.

The paper begins by dismissing convergent validation, the core procedure in Nunnally’s (1978) and Churchill’s (1979) psychometric method of measure design which allows alternative measures of the same construct. The method of dismissal is the mathematical demonstration that an alternative measure, no matter how highly its scores converge with those from the original measure, will inevitably produce different findings. The only solution to this knowledge-threatening problem is to agree on an optimal measure of each of our major constructs and to use only that measure in all future research, as is standard practice in the physical sciences. The paper concludes by proposing an extension of Rossiter’s C-OAR-SE method to design optimal standard measures of judgment constructs, the most prevalent type of construct in marketing.

The findings are, first, the mathematical dismissal of the accepted practice of convergent validation of alternative measures of the same construct, which paves the way for, second, the proposal of five new C-OAR-SE-based construct models for designing optimal standard measures of judgment constructs, three of which require a multiple-item measure and two of which a single-item measure.

The common practice of accepting alternative measures of the same construct causes major problems for the social sciences: when different measures are used, it becomes impossible, except by remote chance, to replicate findings; meta-analyses become meaningless because the findings are averaged over different measures; and empirical generalizations cannot be trusted when measures are changed. These problems mean that we cannot continue to accept alternative measures of the constructs and that, for each construct, an optimal standard measure must be found.

The ideas in this paper, which have untold value for the future of marketing as a legitimate science, are unique to Rossiter’s C-OAR-SE method of measure design.

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.

Through the energetic initiative of “The Globe” newspaper a Middle Classes Union has been formed for the purpose of organising that great body of people into an Alliance that shall be capable of making its power felt. A preliminary meeting was held recently under the presidency of Major J. R. Pretyman Newman, M.P., of gentlemen interested in the scheme recently outlined in “The Globe” for combining the Middle Classes in a Union for their own protection. All present were unanimous as to the necessity for the formation of such an organisation, and after discussion it was provisionally agreed that its title should be—

New measures in marketing are invariably created by using a psychometric approach based on Churchill's “scale development” procedure. This paper aims to compare and contrast Churchill's procedure with Rossiter's content‐validity approach to measurement, called C‐OAR‐SE.

The comparison of the two procedures is by rational argument and forms the theoretical first half of the paper. In the applied second half of the paper, three recent articles from the Journal of Marketing (JM) that introduce new constructs and measures are criticized and corrected from the C‐OAR‐SE perspective.

The C‐OAR‐SE method differs from Churchill's method by arguing for: total emphasis on achieving high content validity of the item(s) and answer scale – without which nothing else matters; use of single‐item measures for “basic” constructs and for the first‐order components of “abstract” constructs; abandonment of the “reflective” measurement model, along with its associated statistical techniques of factor analysis and coefficient alpha, arguing that all abstract constructs must be measured as “formative”; and abandonment of external validation methods, notably multitrait‐multimethod analysis (MTMM) and structural equation modeling (SEM), to be replaced by internal content‐validation of the measure itself. The C‐OAR‐SE method can be applied – as demonstrated in the last part of the article – by any verbally intelligent researcher. However, less confident researchers may need to seek the assistance of one or two colleagues who fully understand the new method.

If a measure is not highly content‐valid to begin with – and none of the new measures in the JM articles criticized is highly content‐valid – then no subsequent psychometric properties can save it. Highly content‐valid measures are absolutely necessary for proper tests of theories and hypotheses, and for obtaining trustworthy findings in marketing.

C‐OAR‐SE is completely original and Rossiter's updated version should be followed. C‐OAR‐SE is leading the necessary marketing measurement revolution.