Comparing a survey and a conjoint study: the future vision of water intermediaries

Erik Mønness, Kim Pearce and Shirley Coleman

Journal of Applied Statistics, 2008, vol. 35, issue 1, pages 19-30

Abstract: This paper compares and contrasts two methods of obtaining opinions using questionnaires. As the name suggests, a conjoint study makes it possible to consider several attributes jointly. Conjoint analysis is a statistical method to analyse preferences. However, conjoint analysis requires a certain amount of effort by the respondent. The alternative is ordinary survey questions, answered one at a time. Survey questions are easier to grasp mentally, but they do not challenge the respondent to prioritize. This investigation has utilized both methods, survey and conjoint, making it possible to compare them on real data. Attribute importance, attribute correlations, case clustering and attribute grouping are evaluated by both methods. Correspondence between how the two methods measure the attribute in question is also given. Overall, both methods yield the same picture concerning the relative importance of the attributes. Taken one attribute at a time, the correspondence between the methods varies from good to no correspondence. Considering all attributes together by cluster analysis of the cases, the conjoint and survey data yield different cluster structures. The attributes are grouped by factor analysis, and there is reasonable correspondence. The data originate from the EU project 'New Intermediary services and the transformation of urban water supply and wastewater disposal systems in Europe'.

Keywords: questionnaire; conjoint analysis; survey methods (search for similar items in EconPapers)

Downloads: (external link)
http://www.informawo ... 40C6AD35DC6213A474B5 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Ordering information: This journal article can be ordered from
http://www.tandf.co.uk/journals/subscription.html

Access Statistics for this article

Journal of Applied Statistics is edited by Professor Gopal K. Kanji

More articles in Journal of Applied Statistics from Taylor and Francis Journals
Series data maintained by Christopher F. Baum ().