Ranking of choice cues for smartphones using the Best–Worst scaling method

Abstract

Purpose

The number of studies on the use of choice cues in the purchase decision of a smartphone does not appear to be extensive, given the size and rate of growth of the market. Surprisingly, it appears that no study of this type in the Chinese context has been undertaken. Therefore, the purpose of this paper is to fill the existing gap in the marketing literature in this area.

Design/methodology/approach

Best–Worst (BW) scaling method was used in the study. It is suggested that the method overcomes some of the biases commonly found in surveys where Likert-type scales are used, and it has superior discriminating power, because respondents are asked to rank the most and the least important factor from a group, and are thereby forced to make tradeoffs between factors.

Findings

Among the 13 choice cues, connectivity, price and memory capacity are found to be the most important, whereas recommendation from others, ease of handling and availability of apps are found to be the least important. Findings due to gender, income and age difference were also analyzed and discussed for orderly decision-making purposes.

Practical implications

The ranking of factors showing what choice cues consumers consider most or least important in a particular market helps practitioners to develop appropriate adaptation strategies for the market. The comparison of findings for gender, income and age difference can further help practitioners to devise various alternative marketing strategies for different market segments and identify underserved segments, if any.

Originality/value

The BW scaling method, however, appropriate in ranking order of importance, had never been used in ranking choice cues of smartphone purchase. Moreover, there seems to be a dearth of studies about ranking of choice cues on smartphone purchases in the Chinese context.

Citation

Pinto, L., Kaynak, E., Chow, C.S.F. and Zhang, L.L. (2019), "Ranking of choice cues for smartphones using the Best–Worst scaling method", Asia Pacific Journal of Marketing and Logistics, Vol. 31 No. 1, pp. 223-245. https://doi.org/10.1108/APJML-01-2018-0004