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Przeglądaj wybrane metody obok siebie; wiersze, które się różnią, są wyróżnione.

Analiza conjoint×Mikrosymulacja×Symulacja Monte Carlo×
DziedzinaPlanowanie eksperymentówSymulacjaPodejmowanie decyzji
RodzinaHypothesis testProcess / pipelineMCDM
Rok powstania197819571949
TwórcaPaul E. Green & V. SrinivasanGuy Orcutt (concept, 1957); modern tax-transfer frameworks developed through EUROMOD and related projectsMetropolis, N., Ulam, S.
TypDecomposition-based utility estimationPolicy simulation / computational social scienceRobustness wrapper — Monte Carlo uncertainty propagation
Źródło pierwotneGreen, P.E. & Srinivasan, V. (1978). Conjoint analysis in consumer research: Issues and outlook. Journal of Consumer Research, 5(2), 103–123. DOI ↗O'Donoghue, C. (Ed.) (2014). Handbook of Microsimulation Modelling. Emerald. DOI ↗Metropolis, N., Ulam, S. (1949). The Monte Carlo method. Journal of the American Statistical Association DOI ↗
Inne nazwyCBC conjoint, choice-based conjoint, adaptive conjoint analysis, full-profile conjointMikrosimülasyon, micro-simulation, policy microsimulation
Pokrewne650
PodsumowanieConjoint 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.
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ScholarGatePorównaj metody: Conjoint Analysis · Microsimulation · MONTE-CARLO-SIMULATION. Pobrano 2026-06-18 z https://scholargate.app/pl/compare