방법 비교

	컨조인트 분석	미시모의	몬테카를로 시뮬레이션
분야	실험설계	시뮬레이션	의사결정
계열	Hypothesis test	Process / pipeline	MCDM
기원 연도	1978	1957	1949
창시자	Paul E. Green & V. Srinivasan	Guy Orcutt (concept, 1957); modern tax-transfer frameworks developed through EUROMOD and related projects	Metropolis, N., Ulam, S.
유형	Decomposition-based utility estimation	Policy simulation / computational social science	Robustness wrapper — Monte Carlo uncertainty propagation
원전	Green, P.E. & Srinivasan, V. (1978). Conjoint analysis in consumer research: Issues and outlook. Journal of Consumer Research, 5(2), 103–123.	O'Donoghue, C. (Ed.) (2014). Handbook of Microsimulation Modelling. Emerald.	Metropolis, N., Ulam, S. (1949). The Monte Carlo method. Journal of the American Statistical Association
별칭	CBC conjoint, choice-based conjoint, adaptive conjoint analysis, full-profile conjoint	Mikrosimülasyon, micro-simulation, policy microsimulation	—
관련	6	5	0
요약	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.	Microsimulation is a computational method that simulates policy effects by operating directly on a population of individual micro-units — households, firms, patients — and applying rules to each unit according to its own demographic, economic, and behavioural characteristics. Developed conceptually by Guy Orcutt in 1957, it has become the standard tool for evaluating tax reform, pension systems, and health policy before implementation.	MONTE-CARLO-SIMULATION (Monte Carlo Simulation — Stochastic uncertainty propagation through MCDM model) is a ranking multi-criteria decision-making (MCDM) method introduced by Metropolis, N., Ulam, S. in 1949. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.