পদ্ধতির তুলনা করুন
নির্বাচিত পদ্ধতিগুলো পাশাপাশি পর্যালোচনা করুন; যে সারিগুলোয় পার্থক্য আছে সেগুলো চিহ্নিত করা হয়।
| Bayesian Conjoint Analysis× | কনজয়েন্ট অ্যানালাইসিস× | |
|---|---|---|
| ক্ষেত্র≠ | পরিসংখ্যান | পরীক্ষামূলক নকশা |
| পরিবার≠ | Latent structure | Hypothesis test |
| উদ্ভবের বছর≠ | 1995 | 1978 |
| প্রবর্তক≠ | Allenby & Ginter (hierarchical Bayes formulation); conjoint roots in Luce & Tukey (1964) | Paul E. Green & V. Srinivasan |
| ধরন≠ | Preference measurement / Bayesian hierarchical model | Decomposition-based utility estimation |
| মৌলিক উৎস≠ | Allenby, G. M. & Ginter, J. L. (1995). Using extremes to design products and segment markets. Journal of Marketing Research, 32(4), 392–403. DOI ↗ | Green, P.E. & Srinivasan, V. (1978). Conjoint analysis in consumer research: Issues and outlook. Journal of Consumer Research, 5(2), 103–123. DOI ↗ |
| অপর নাম≠ | Bayesian CA, hierarchical Bayes conjoint, HB conjoint, Bayesian preference modeling | CBC conjoint, choice-based conjoint, adaptive conjoint analysis, full-profile conjoint |
| সম্পর্কিত | 6 | 6 |
| সারসংক্ষেপ≠ | Bayesian conjoint analysis estimates individual-level consumer preference weights for product attributes by combining conjoint choice tasks with a hierarchical Bayesian model. It yields part-worth utilities for each respondent rather than only group averages, enabling precise market simulation and segment discovery even from small per-person choice sets. | Conjoint analysis is a preference-measurement technique that decomposes overall product evaluations into the separate utility values — called part-worths — that respondents assign to each attribute level. Formalised by Green and Srinivasan in their seminal 1978 Journal of Consumer Research paper, the method has become the dominant tool in marketing research and product design for quantifying what buyers truly trade off when they choose between options. |
| ScholarGateডেটাসেট ↗ |
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