Abstract
What is best way to conduct conjoint analysis when there is a large number of attributes such as mobile phone? Although there is little empirical evidence that directly bears on this question, it is widely believed that the predictive accuracy of full-profile methods degrades as the number of attributes increases beyond ten. In order to minimize the complication of multi-attributes and reduce the consumers’ choice task burden, the author proposes an integrated hierarchical survey design (IHSD) with the Kano model. The author compared the utility of mobile phone’s attributes for each market and for customer segment by analyzing empirical data which wear obtained from 6 Middle East & Africa countries, 5 Asia Pacific countries and 3 European countries. Based on an IHSD of 10,200 respondents, overall, Brand, Camera, Memory and Mobile-tv play a vital role in all countries. In contrast, WiFi, File-editor, MMS, LCD size, and Phone-type are displayed as the least important attribute. The results of this study were successfully implemented for product planning, product development, and marketing strategy in terms of price setting, features prioritizing, and optimal designing for new products in the mobile phone company.
Highlights
The functions and designs of mobile phones have rapidly evolved since they were first introduced into the markets of emerging and mature countries
What is best way to conduct conjoint analysis when there is a large number of attributes such as mobile phone? there is little empirical evidence that directly bears on this question, it is widely believed that the predictive accuracy of full-profile methods degrades as the number of attributes increases beyond ten
In order to minimize the complication of multi-attributes and reduce the consumers’ choice task burden, the author proposes an integrated hierarchical survey design (IHSD) with the Kano model
Summary
The functions and designs of mobile phones have rapidly evolved since they were first introduced into the markets of emerging and mature countries. Mobile phone users want to have many and advanced features such as internet and radio on their phone. As mobile phones become more commoditized and as consumers become more informed about various product features and contents, marketers wish to measure consumers’ multi-attribute preferences and the willingness to pay (Lancaster, 1971) for mobile phones may vary among different customer segments within a country. Conjoint analysis has been successfully applied to several marketing decisions to optimally design new mobile phones, price new products (Gustafsson et al, 2000) and prioritize features across segments in studies by Carroll and Green (1995), Green and Srinivasan (1978, 1990), Gustafsson et al (2000), Louviere (1994) and Rao and Hauser (2004). A number of problems arose when conventional conjoint analysis was used to handle a large number (ten or more) of product attributes (Netzer & Srinivasan, 2011). Toubia, Simester, Hauser, and Dahan (2003) have developed an adaptive conjoint analysis method for dealing with a large number of attributes that reduces respondent burden while simultaneously improving accuracy
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