International Journal of Market Research

Public service accountability is a large and complex topic. One important aspect of the accountability of a public service provider is that they should be aware of what matters to the recipients of their service. This paper uses the Metropolitan Police as a case study to explore some of the implications of this aspect of accountability. It concludes that sometimes having fewer data points leads to more comprehensive insight than having more.

We took a promising new method of political polling – snap judgements of political candidates' facial appearance – from the lab to the real world with internet-enabled mobile phones. Using iPhones and online multimedia-rich surveys, we collected over 6000 snap judgements of political candidates' faces, providing proof of concept for a new method of candidate pre-testing and political polling. Consistent with prior research, we find that snap judgements by small samples (178) of politically naive respondents can accurately predict election outcomes. Further, we advance this method of research by testing design elements and providing practical details about the use of mobile technology to aid data collection.

This paper reports the feasibility and methodological considerations of using the Short Message System Experience Sampling (SMS-ES) method, which is an experience sampling research method developed to assist researchers to collect repeat measures of consumers' affective experiences. The method combines SMS with web-based technology in a simple yet effective way. It is described using a practical implementation study that collected consumers' emotions in response to using mobile phones in everyday situations. The method is further evaluated in terms of the quality of data collected in the study, as well as against the methodological considerations for experience sampling studies. These two evaluations suggest that the SMS-ES method is both a valid and reliable approach for collecting consumers' affective experiences. Moreover, the method can be applied across a range of for-profit and not-for-profit contexts where researchers want to capture repeated measures of consumers' affective experiences occurring over a period of time. The benefits of the method are discussed, to assist researchers who wish to apply the SMS-ES method in their own research designs.

This paper shows that respondents are better at predicting when they won't give a recommendation than when they will. The main reason for inaccuracy was an over-reliance on past circumstances (past receiving or giving of recommendations) in making future predictions of their own behaviour. Therefore, self-report probabilities are best used as measures of the potential or desire to give a recommendation, rather than predictions of future behaviour. The translation of this potential to behaviour will depend largely on the external environment, which is outside the respondent's control. To improve the accuracy of aggregatelevel predictions of how many people will give recommendations, we suggest reducing the number of those with a high self-reported probability to around 30% of survey estimates.

In the last decade, there has been an explosion in the use of online survey tools. Online data collection tools have lowered the cost of data collection and removed barriers to entry for carrying out research. While a number of questions have been raised about the general reliability of internet survey research, one specific use of the web for survey work has been in reaching niche populations that are difficult to access using traditional survey tools – so-called ‘rare samples’. In this paper, we present an approach to accessing such hard-to-reach populations using search engine pay-per-click (PPC) advertising. We carried out a study that makes uses of PPC advertising on search engines as an alternative means of developing a sample for a hard-to-reach group of health consumers. Based on a sample of 466 consumer responses, we discuss the effectiveness of this technique for reaching such rare populations.

Although the concept of affect transfer has been addressed by many in the literature, the process underlying the transfer of brand associations from parent brands to their extensions is still unclear despite important theoretical and managerial implications. This paper proposes to conceptualise and model the empirical process underlying such transfer. The findings reveal that the capability of a parent brand to transfer specific brand associations to a line extension depends on an optimisation process where strong transfer occurs only when repeated measures of the same associations are not statistically distinct. Conversely, the transfer is limited when the statistical difference is either positive or negative in repeated measures. When the difference is positive, the extension appears to already ‘own’ the association in comparison to the parent brand and when negative the association is not compatible with the extension. The methodological and managerial implications of brand association transfer are discussed.

These are two summaries based on presentations from the above conference, both concerned with improving engagement in the research process. The first, from Jon Puleston, discusses ways to engage more effectively with respondents in online research. The agenda proposed by Puleston includes the application of methods used in qualitative research, and computer games – usually termed ‘gamification’. The second, by Niels Schillewaert, discusses ways to engage more effectively with all the key stakeholders in market research, around an ENgagement and ACTivation (ENACT) framework. They provide further perspectives on this key theme of ‘engagement’ following on from the Conference Notes published in IJMR Vol. 53 Issue 1, based on presentations from the ASC conference held last September.