Article Comments: “In Researching Emerging Markets, Anthropology Often Trumps Statistics”

Nailer, C., B. Stening, M. Zhang. 2015. “In Researching Emerging Markets, Anthropology Often Trumps Statistics”. International Journal of Market Research, vol. 57, issue 6. Pp. 855-876.

Nailer et al. argue that with the exception of large firms, qualitative market research is very much in its infancy – especially so in emerging markets. Despite the problems associated with quantitative research in international markets (reliability of data, timeliness of procurement, and short-comings in handling sensitive issues), it remains the more popular approach. In general, they argue, the trend towards “big data” comes with a price: rigour is often at the expense of communicability and simplicity; construct-to-construct links are addressed rather than their place within systems of behaviour; the valuable amalgamations of what people are doing, but a failure to provide an answer as to why they do it (856). Yet, qualitative data alone is no panacea to these ails.

What makes an emerging international market different? According to the authors, there are a few distinct features which define emerging markets: “First, the mainstream segment in emerging markets often comprises customers with different socio-economic backgrounds compared to the mainstream segment of a large middle class in mature markets. Second, fringe segments in emerging markets are often too big to be ignored by international firms. Third, industries in emerging markets evolve faster in this catch-up mode of development than is the case in mature market” (857).

The quantitative method aims to test causal relationships between input factors (independent variables) and variations in outcomes (dependent variables). The qualitative method, rather, is a context-sensitive observation of things which tries to provide explanations for why things happen as they do, often looking for motives and values within a shared structure of cultural meanings. As addressed above, the authors point to three serious limitations with quantitative data in emerging markets: reliability of data; timeliness and relevance; and in relation to dealing with highly contextual (sensitive) issues (859).

For these reasons, the authors present what they call a “meso-level” approach which integrates quantitative and qualitative research methods that is especially relevant for emerging markets. I’ve decided to reproduce the entire graphic here because of its value not just for marketing research, but for the integration of quantitative and qualitative methods more generally throughout social sciences, not excluding potentially design research (865):

july 18 a graphic

In the author’s diagram, research begins with a series of research questions (upper left) based on gaps in literature and the observable empirical context. Following the arrow (red) emerging from the right of that box, we move directly towards a qualitative approach. This is not inconsistent with what I have written about in the past regarding the value of qualitative data as a primary, “exploratory” method. In this qualitative approach (green), interviews, ethnographic work, and focus-groups, expose qualitative raw data. As a researcher, we can then contextualize this data, tie it to narratives, interpret it, and evaluate it to produce a picture of the larger symbolic system in which actions take place. This is essentially a process of determining how to best approach creating the most appropriate input factors for our quantitative analysis. By appropriately contextualizing variables we can have a much firmer grasp of the causal connection explored through more quantitative methods (blue). We now have context-sensitive input values arising from the empirical context, and can develop the most appropriate hypotheses to test the causal relationships of these variables.

That is not to say that all modes of market research, or even social science research must follow these steps exactly, but the framework elaborated here presents a way to contextualize and maximize the findings of quantitative data, and to conversely address (in part) the frequency and appropriateness of any qualitative interpretations.

The authors also present, what they believe is a model for qualitative marketing research in emerging international markets. It too, however, presents a way to conceive of the ethnographic process as a series of methodological steps to gathering, organizing and interpreting qualitative data generated by ethnography in general. It doesn’t necessarily present any new or ground-breaking way of conceptualizing ethnography: ethnography is essentially a system of framing an issue, developing a context-sensitive and contingent view of the issue, and subsequently questions regarding the assumptions of this view through both reflection and the incorporation of new empirical data, and then reframing that issue. It can be found on page 867 of their article.

Conclusion:

Quantitative data while presenting valuable statistical accuracy, lacks the richness of qualitative data and the ability to contextualize causal relationships within a larger system of values. This is true for marketing research, as well as any other instance of research. In emerging international markets particularly, quantitative methods have been favoured, despite a number of weaknesses. Nailer et al. present a valuable schema for combining the value of ‘big data’ with the richness of a qualitative approach, which is not only applicable to marketing research, but to social science research more generally. All of this does not necessitate that all research combine both qualitative and quantitative approaches in this manner (or at all, as that would potentially incur too much cost for any one marketing assessment). However, the knowledge of limitations of both qualitative and quantitative methods is an invaluable consideration for any research strategy at the outset, and should contribute at the very least to determining next steps in social science research.

 


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