Web Survey Bibliography
Title How much individualisation does a conjoint survey need? - Experiences from an online experiment
Access date 24.09.2006
Abstract Conjoint (trade-off) analysis has become one of the most widely-used quantitative methods in Marketing Research. It is used to measure the perceived values of specific product features, to learn how demand for a particular product or service is related to price, and to forecast what the likely acceptance of a product would be if brought to market. Rather than directly ask survey respondents what they prefer in a product, or what attributes they find most important, conjoint analysis employs the more realistic context of respondents evaluating potential product profiles. Each profile includes multiple conjoined product features (hence, conjoint analysis). There are different ways to show product profiles. Currently the most frequently used state-of-the-art technique in marketing research is Choice Based Conjoint (CBC). CBC interviews closely mimic the purchase process for products in competitive contexts: respondents are shown a set of products on the screen (in full-profiles) and asked to indicate which one they would purchase. As in the real world, respondents can decline to purchase in a CBC interview by choosing “None”. CBC can be administered via Paper-and-Pencil, CAPI (Computer assisted personal interviewing) or Internet surveys. With the growing popularity of online research (cost efficiency, speed, etc.), more and more surveys are conducted via the Web. Even though CBC offers a lot of complexity regarding modelling and designing of surveys, CBC lacks of individualisation, which an other conjoint technique (ACA, Adaptive Conjoint Analysis), also applicable in online surveys, offers. A nowadays frequently discussed methodological question for market researcher is, whether CBC surveys would need some of these individualisation aspects as well in order to improve the measurement of purchase behaviour. Means that, based on the answers in a previous conventional part of the survey, respondents are only shown choice tasks which fit to their interests and requirements. The talk will first outline techniques for individualizing an online full profile conjoint exercise. Then, based on an online experiment carried out with such traditional and individualized conjoint surveys having the same attributes and levels, the measured performance of the techniques used will be discussed and the results in terms of respondent\'s preference scores and choice behaviour of the tested approaches will be compared.
Access/Direct link Conference homepage (abstract)
Bibliographic typeConferences, workshops, tutorials, presentations
Year of publication2006
Full text availabilityNon-existant
Web Survey Bibliography - General Online Research Conference (GOR) 2006 (29)
- Cash Lotteries as Incentives in Online Panels; 2006; Goeritz, A.
- ‘Low social presence’ in web surveys: advantage or disadvantage or both? An experiment; 2006; Taddicken, M.
- How much individualisation does a conjoint survey need? - Experiences from an online experiment; 2006; Tuschl, S., Morasch, N.
- The effect of different kinds of progress bars on online survey compliance and data quality; 2006; van der Horst, W., Snijders, C., Matzat, U.
- The impact of persuasion strategies on the response rate in online surveys: Incentives, foot-in-the-...; 2006; Verheyen, C.; Schuebel, C., Moser, K.
- Online visual landscape assessment using Internet survey techniques in landscape planning and environmental...; 2006; Roth, M.
- Image Impact Evaluation - A new methodological approach with virtual test environments; 2006; Selke, S., Fetzner, D.
- Air refresheners online? Validity check of an Internet online sample using external reference data; 2006; Starsetzki, T., Lehmann, G.
- Online Evaluation Survey; 2006; Strzoda, C.
- Online Survey Response Patterns; 2006; Sutton A., Hopkins Burke, K.
- Does the Collection of Ego-Centered Network Data on the Web reduce the Data Quality? An Experimental...; 2006; Matzat, U., Snijders, C.
- Optimizing open-ended questions in online questionnaires for measuring price perception and willingness...; 2006; Melles, T., Ellers, G.
- Ranking vs. Rating in an online Environment; 2006; Neubarth, W.
- Online Recruiting on Internet pages New Solution for On Exit Recruitment on WebSites; 2006; Otto, P.
- Online Conjoint Analysis: The faster, the worse?; 2006; Puetzfeld, S., Melles, T.
- Web survey on transition from university to work: measuring the marginal effect mode; 2006; D'Agostino, A., Quintano, C., Castellano, R.
- Qualitative research online: Self-reported pros and cons of being chat-interviewed online with web cameras...; 2006; Davidovich, U., Uhr, H.
- Visual Analogue Scales: Non-linear Data Categorization by Transformation with Reduced Extremes; 2006; Funke, F., Reips, U. -D.
- Response Biases in Online Surveys; 2006; Galesic, M., Bosnjak, M.
- Using Instant Messaging for Internet-based interviews; 2006; Goeritz, A., Stieger, S.
- A online-offline method comparison based on quasi-experimental data from two surveys to family stress...; 2006; Haenggi, Y., Heldner, C.
- Hybrid Methods in Market Research - Learnings and Limits; 2006; Helmold, D., Kohlmann, U.
- The impact of visualization of question types and screen pages on the answering behaviour in online...; 2006; Hemsing, W., Hellwig, O.
- Specific Demands of Longitudinal Online-Surveys; 2006; Kahnwald, N., Koehler, T.
- A Comparison of the validity of a paper based and an online Conjoint Analysis; 2006; Klein, A., Scheffold, K.
- Determinants of Response Rates of Online Surveys - The Anita Effect - Results of a Joint Project; 2006; Althoff, S., Greif, V., Griel, B., Batinic, B.
- Technical opportunities for automation and integration of online surveys in business processes; 2006; Batinic, B.
- Personality traits and participation in an online access panel; 2006; Galesic, M., Bosnjak, M.