A comparison of the validity of interviewer-based and online- conjoint analyses

Interviewer-based conjoint analyses are usually time consuming and expensive. By changing the data collection process to the Internet, it is easier to contact a larger number of people within a shorter amount of time. In addition, it is a more cost effective method. However, it is questionable if the data is of the same quality, since conjoint analyses regularily need more time to explain the task to the interviewee. This might have a negative impact onto the validity of the gathered data. Therefore, a scientific study was conducted in order to compare the validity of such two data sets. The results show that there are no big differences in the validity between an interviewer-based computer and an online-conjoint analysis. Rather it can be shown that the validity of the data of the online-conjoint analysis is slightly higher.

[1]  Joel Huber,et al.  The Effectiveness of Alternative Preference Elicitation Procedures in Predicting Choice , 1993 .

[2]  Henrik Sattler,et al.  Ein empirischer Vergleich von Instrumenten zur Erhebung von Zahlungsbereitschaften , 2003 .

[3]  Christina Sichtmann,et al.  An empirical comparison of methods to measure willingness to pay by examining the hypothetical bias , 2005 .

[4]  A. Theobald Das World Wide Web als Befragungsinstrument , 2000 .

[5]  R. Brodie,et al.  Building models for marketing decisions , 2000 .

[6]  Waldemar Toporowski,et al.  Zur Validität von Conjoint-Analysen , 1993 .

[7]  Roderick J. Brodie,et al.  Conditions when market share models are useful for forecasting: further empirical results , 1994 .

[8]  M. Couper,et al.  Picture This!Exploring Visual Effects in Web Surveys , 2004 .

[9]  Olivier Toubia,et al.  The Impact of Utility Balance and Endogeneity in Conjoint Analysis , 2005 .

[10]  Rick L. Andrews,et al.  Hierarchical Bayes versus Finite Mixture Conjoint Analysis Models: A Comparison of Fit, Prediction, and Partworth Recovery , 2002 .

[11]  Markus Voeth,et al.  25 Jahre conjointanalytische Forschung in Deutschland , 1999 .

[12]  Chan Su Park,et al.  Surprising Robustness of the Self-Explicated Approach to Customer Preference Structure Measurement , 1997 .

[13]  Henrik Sattler,et al.  Multimediale versus traditionelle Conjoint-Analysen: Ein empirischer Vergleich alternativer Präsentationsformen , 2000 .

[14]  Thomas Bamert,et al.  Designeffekte in Online-Umfragen , 2001 .

[15]  B. Duffy,et al.  Comparing Data from Online and Face-to-face Surveys , 2005 .

[16]  Raj Sethuraman,et al.  A field study comparing online and offline data collection methods for identifying product attribute preferences using conjoint analysis , 2005 .

[17]  Jon Martin Denstadli,et al.  Information Overload in Conjoint Experiments , 2004 .

[18]  Niels Schillewaert,et al.  Comparing response distributions of offline and online data collection methods , 2005 .

[19]  T. Hooley What is online research , 2012 .

[20]  Henrik Sattler,et al.  Wie robust sind Methoden zur Präferenzmessung? , 2004 .

[21]  Sally Dibb,et al.  New survey medium: Collecting marketing data with e-mail and the World Wide Web , 2001 .

[22]  Adriane Hartmann,et al.  Kaufentscheidungsprognose auf Basis von Befragungen , 2004 .

[23]  Dick R. Wittink,et al.  Verbal versus realistic pictorial representations in conjoint analysis with design attributes , 1998 .

[24]  Markus Voeth,et al.  Nutzenmessung in der Kaufverhaltensforschung , 2000 .

[25]  K. Backhaus,et al.  Conjointanalytische Präferenzmessungen zur Prognose von Preisreaktionen , 2004 .

[26]  Paul E. Green,et al.  Individualized hybrid models for conjoint analysis , 1996 .

[27]  Peter J. Danaher,et al.  Comparing naive with econometric market share models when competitors' actions are forecast , 1994 .

[28]  Klaus Backhaus,et al.  Limit-Conjoint-Analyse , 1998 .

[29]  Susanne Hensel-Börner,et al.  Validität computergestützter hybrider Conjoint-Analysen , 2000 .

[30]  Paul E. Green,et al.  Thirty Years of Conjoint Analysis: Reflections and Prospects , 2001, Interfaces.

[31]  Manoj K. Agarwal,et al.  Adaptive conjoint analysis versus selfexplicated models: Some empirical results , 1991 .

[32]  Heribert Gierl,et al.  Der Reihenfolgeeffekt auf Präferenzen , 2002 .

[33]  Christoph Teller,et al.  ‘Hidden’ Opportunities and Benefits in Using Web-based Business-to-business Surveys , 2005 .

[34]  Herbert Woratschek Preisbildung im Dienstleistungsbereich auf der Basis von Marktinformationen , 1998 .

[35]  R. Wilken,et al.  Predicting Purchase Decisions with Different Conjoint Analysis Methods: A Monte Carlo Simulation , 2007 .

[36]  S. Baron,et al.  ONLINE SURVEYS IN MARKETING RESEARCH: PROS AND CONS , 2002 .