Comparing a survey and a conjoint study: the future vision of water intermediaries
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 a...
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Veröffentlicht in: | Journal of applied statistics 2008-01, Vol.35 (1), p.19-30 |
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description | 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'. |
doi_str_mv | 10.1080/02664760701683379 |
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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. 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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'.</description><subject>Cluster analysis</subject><subject>Comparative analysis</subject><subject>Conjoint analysis</subject><subject>Correspondence</subject><subject>Discriminant analysis</subject><subject>questionnaire</subject><subject>survey methods</subject><subject>Urban areas</subject><subject>Waste disposal</subject><subject>Water supply</subject><issn>0266-4763</issn><issn>1360-0532</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2008</creationdate><recordtype>article</recordtype><sourceid>X2L</sourceid><recordid>eNqFUMFq3DAUFKGFbtN-QG-idzeS31qSQy9laZtCIFByF7L91GhZW64kb-q_71s29BJKDqNBaGb03jD2QYpPUhhxJWqltloJLaQyALq9YBsJSlSigfoV25zeKxLAG_Y2570QwsgGNuznLo6zS2H6xR3PSzriyt000KWP0z6GqfBclmG95uUBuV_KkpAfQw5x4tHzR1cwcVJhGnEIFIT5HXvt3SHj-ye-ZPffvt7vbqrbu-8_dl9uq34LplSgUaF3XQdNM7jW1dC2tAN2euiNVFtpgGbvWlJjg8r7RoD3WyVR16oDuGQfz7Fzir8XzMXu45Im-tHWErQxUhsSybOoTzHnhN7OKYwurVYKeyrOPiuOPDdnT8IZ-3-G4vzezbk4e7TgoKFjJdTUJFEgSMJ84taCsA9lpCh9jgqTj2l0jzEdBkpaDzH55KY-5OcD2PKnkPPzi074_w5_AY_7nnM</recordid><startdate>20080101</startdate><enddate>20080101</enddate><creator>Mønness, Erik</creator><creator>Pearce, Kim</creator><creator>Coleman, Shirley</creator><general>Routledge</general><general>Taylor and Francis Journals</general><general>Taylor & Francis Ltd</general><scope>DKI</scope><scope>X2L</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>8FD</scope><scope>H8D</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope></search><sort><creationdate>20080101</creationdate><title>Comparing a survey and a conjoint study: the future vision of water intermediaries</title><author>Mønness, Erik ; Pearce, Kim ; Coleman, Shirley</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c438t-37e6efabb355da9a2399664eb7dc8164183053b9c43e5e6ff503ff461e726b33</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2008</creationdate><topic>Cluster analysis</topic><topic>Comparative analysis</topic><topic>Conjoint analysis</topic><topic>Correspondence</topic><topic>Discriminant analysis</topic><topic>questionnaire</topic><topic>survey methods</topic><topic>Urban areas</topic><topic>Waste disposal</topic><topic>Water supply</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Mønness, Erik</creatorcontrib><creatorcontrib>Pearce, Kim</creatorcontrib><creatorcontrib>Coleman, Shirley</creatorcontrib><collection>RePEc IDEAS</collection><collection>RePEc</collection><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Technology Research Database</collection><collection>Aerospace Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><jtitle>Journal of applied statistics</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Mønness, Erik</au><au>Pearce, Kim</au><au>Coleman, Shirley</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Comparing a survey and a conjoint study: the future vision of water intermediaries</atitle><jtitle>Journal of applied statistics</jtitle><date>2008-01-01</date><risdate>2008</risdate><volume>35</volume><issue>1</issue><spage>19</spage><epage>30</epage><pages>19-30</pages><issn>0266-4763</issn><eissn>1360-0532</eissn><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'.</abstract><cop>Abingdon</cop><pub>Routledge</pub><doi>10.1080/02664760701683379</doi><tpages>12</tpages></addata></record> |
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subjects | Cluster analysis Comparative analysis Conjoint analysis Correspondence Discriminant analysis questionnaire survey methods Urban areas Waste disposal Water supply |
title | Comparing a survey and a conjoint study: the future vision of water intermediaries |
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