Surveys based on Likert scales and similar ratings-based scales continue to domite market research practice despite their many and well-documented limitations. Key issues of concern for Likert scales include over- or under-reporting depending on the context, and variation in responses based on cultural background. Altertives exist to overcome the inherent weaknesses of these scales. This paper reflects on the Best Worst (BW) Scaling method that we have recently used in eight online studies. In these studies, we employed a novel pictorial approach to capture product preferences for over 3,600 respondents. One case 3 BW experiment investigating consumer preferences for organic apples is featured and evaluated using two approaches. The first alysis treats the data as a case 1 BW experiment to outline the simplicity of case 1 alysis. Case 3 BW alysis involving multinomial logit and latent class modelling is then illustrated to highlight the rich preference insights that can be obtained from case 3 BW studies. We look at some of the drawbacks of the BW case 3 approach, including design and data processing issues, weighted against the overall positive feedback received from respondents. Overall, we do believe the BWS method has a significant potential to improve predictability in market research - the response rate and positive participant feedback speaks for itself.
|Number of pages||19|
|Journal||Market & Social Research|
|Publication status||Published - Jun 2013|