Past research has recognised the influence of religion on marketing, particularly the role of religious cues in marketing communications. Drawing on symbolic interactionism theory, this empirical study identifies symbols that possess symbolic value with Muslims, and how these symbols on product packaging may influence the response of Muslim consumers. Furthermore, we examine how this influence may vary between products of low versus high symbolic values, and across consumers of varying level of religiosity. An elicitation survey identified five symbols, five high symbolic-value products, and five low-symbolic value products. Afterwards, a quasi-type experiment examined the influence of a symbol on product purchase intentions. The presence of the symbol significantly increased purchase intentions, but only for low symbolic-value products. Also, the presence of symbol affected those with high religiosity more than those with low religiosity. This study is the first to investigate the role of religious symbols on product packaging. An implication is for marketers to recognise the importance of such symbols for Muslim consumers.

2009),"Region of origin and its importance among choice factors in the wine-buying decision makingIf you would like to write for this, or any other Emerald publication, then please use our Emerald for Authors service information about how to choose which publication to write for and submission guidelines are available for all. Please visit www.emeraldinsight.com/authors for more information. About Emerald www.emeraldinsight.comEmerald is a global publisher linking research and practice to the benefit of society. The company manages a portfolio of more than 290 journals and over 2,350 books and book series volumes, as well as providing an extensive range of online products and additional customer resources and services.Emerald is both COUNTER 4 and TRANSFER compliant. The organization is a partner of the Committee on Publication Ethics (COPE) and also works with Portico and the LOCKSS initiative for digital archive preservation. AbstractPurpose -The usual method of analysis of product attributes in marketing is to fit a multinomial logit model within a stated choice experiment, to determine the impact of attributes on the choice probability, which is equivalent to market share. The market share is intuitive and is based on each single choice in the study. However, revealed preference allows for a study into repeat purchase and loyalty, which can also be rich constructs for determining consumer preference. Design/methodology/approach -The authors introduce a loyalty measure, polarisation, and show results based on a wine data set of revealed preference. Polarisation is a function of the beta binomial distribution (BBD) and can also be a function of the Dirichlet multinomial distribution (DMD). The DMD provides a standardised or average loyalty effect for each attribute (such as wine variety), and the BBD an individual effect for each attribute level (such as cabernet) within the attribute. While the DMD results provide a rich ''first-pass'' of the data, it is the individual results which can classify levels as reinforcing, niche, or change-of-pace in nature, with subsequent different marketing implications. These implications are drawn out in this study. Findings -Specifically, the DMD results show higher loyalty towards price and variety rather than to region and brand. The BBD results show that segmented preferences in the wine market are influenced more by the price attribute levels and that the two key single varietals in the red wine category tend to behave as reinforcing attribute levels with important marketing implications for small and large wine brands. Originality/value -The authors extend the work of stated choice experiments into the realm of actual consumer purchase behaviour for wine. They also find that consumers' repeat purchasing is based on attributes other than brand. This provides a useful platform for both researchers to further investigate loyalty/repurchasing using attributes as well as for marketing practitioners to better position their products to consumers.

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The Dirichlet model is an empirical generalization describing and predicting repeated choice amongst a set of competitive alternatives. With the advent of big data, there are many new potential applications for this model. Its developers emphasized one goodness-of-fit statistic, and subsequent researchers have used this along with others. There is, however, no consensus in the literature regarding which measures to use or, more importantly, benchmarks. This paper proposes a suite of six goodness-of-fit statistics developed from the literature to assess the fit of the model and develops two new measures that account for category specific factors enabling the development of benchmarks. It also provides appropriate benchmarks for all statistics derived from 54 FMCG categories in the UK.