I want to perform conjoint analysis, please suggest me some material. I am more interested to look some reports, where interpretation has been given. Having complete guide of interpretation is more beneficial. Thanking you in advance for your cooperation.
According to Wikipedpa, Conjoint analysis, also called multi-attribute compositional models or stated preference analysis, is a statistical technique that originated in mathematical psychology. It is used in surveys developed in applied sciences, often on behalf of marketing, product management, and operations research
Here are a few relevant articles:
Sharma, S., & Malhotra, N. K. (2015). Examining Social Setting and Product Reference via Conjoint Analysis An Empirical Study of Restaurant Patronage. In The 1980’s: A Decade of Marketing Challenges (pp. 59-63). Springer International Publishing.
Ryan, M., & Farrar, S. (2000). Using conjoint analysis to elicit preferences for health care. BMJ: British Medical Journal, 320(7248), 1530.
Green, P. E., Krieger, A. M., & Wind, Y. (2001). Thirty years of conjoint analysis: Reflections and prospects. Interfaces, 31(3_supplement), S56-S73.
Cattin, P., & Wittink, D. R. (1982). Commercial use of conjoint analysis: A survey. The journal of marketing, 44-53.
Green, P. E., & Srinivasan, V. (1990). Conjoint analysis in marketing: new developments with implications for research and practice. The Journal of Marketing, 3-19.
https://en.wikipedia.org/wiki/Conjoint_analysis_(marketing)
According to Wikipedpa, Conjoint analysis, also called multi-attribute compositional models or stated preference analysis, is a statistical technique that originated in mathematical psychology. It is used in surveys developed in applied sciences, often on behalf of marketing, product management, and operations research
Here are a few relevant articles:
Sharma, S., & Malhotra, N. K. (2015). Examining Social Setting and Product Reference via Conjoint Analysis An Empirical Study of Restaurant Patronage. In The 1980’s: A Decade of Marketing Challenges (pp. 59-63). Springer International Publishing.
Ryan, M., & Farrar, S. (2000). Using conjoint analysis to elicit preferences for health care. BMJ: British Medical Journal, 320(7248), 1530.
Green, P. E., Krieger, A. M., & Wind, Y. (2001). Thirty years of conjoint analysis: Reflections and prospects. Interfaces, 31(3_supplement), S56-S73.
Cattin, P., & Wittink, D. R. (1982). Commercial use of conjoint analysis: A survey. The journal of marketing, 44-53.
Green, P. E., & Srinivasan, V. (1990). Conjoint analysis in marketing: new developments with implications for research and practice. The Journal of Marketing, 3-19.
https://en.wikipedia.org/wiki/Conjoint_analysis_(marketing)
Dear Rahul,
Please find attached a paper providing some useful guidelines for "Good Research Practices for Conjoint Analysis".
I hope it helps you!!
Regards,
Ruben.
For Conjoint Analysis, you can consult:
1. Marketing Research: An Applied Orientation - Naresh K. Malhotra,Satyabhushan, Pearson Publication.
2. SPSS package -- Conjoint Analysis -- go to help.
3. Google search --- Use key word as Conjoint Analysis -- you will find details with example and how can you use SPSS package.
4. Many more resources you can find through internet.
Full text of fallowing articles is available in RG.
Kuzmanovic, M., Vujosevic, M., & Martic, M. (2012). Using conjoint analysis to elicit patients’ preferences for public primary care service in Serbia. HealthMED, 6(2), 496-504.
Nikou, S., Bouwman, H., & de Reuver, M. (2014). A Consumer Perspective on Mobile Service Platforms: A Conjoint Analysis Approach. Communications of the Association for Information Systems, 34(1), 82.
Camilleri, L., & Azzopardi, L. M. (2011, October). Market Segmentation through Conjoint Analysis using Latent Class Models. In 25th ESM (European Simulation and Modelling) Conference.
Cadavid, A., & Maya, J. (2013). Inspirational categories for product design: a study within the conjoint trends analysis method. In International Conference on Engineering and Product Design Education.
[minor editorial changes on 2015.09.29]
Please note that CA is a subfield of mutlivariate statistical analysis (MSA), deeply rooted also in the Representational Measurement tradition. It is an analytical tool for researchers, rather than for practitioners. It follows that you can't use / apply it as were it a black box: put in some data blindly, let CA do the work, and enjoy some nice output.
As you may read in Green, P. E., Krieger, A. M., & Wind, Y. (2001) Thirty years of conjoint analysis: Reflections and prospects (cf. recommendation by Behrouz Ahmadi-Nedushan above), the first thing to be aware of is that there isn't just a single CA, there are different variants and flavors of it, more or less complex, more or less applicable in your case.
You should invest a proper amount of preparatory study of various techniques, before delving into your own application of it. Then you will also be able to report and communicate the results of your own CA case in a proper way, even to people who don't have any previous knowledge of it, aren't perhaps so much interested in it and certainly aren't inclined to learn this beautiful technique themselves.
- Badges
- Science topic
- Similar topics
- Physical Sciences
- Materials Science
- Materials