作者: Roland W. Goetgeluk
DOI: 10.1007/978-90-481-8894-9_3
关键词: Freedom of choice 、 Machine learning 、 Respondent 、 Artificial intelligence 、 Acceptance rate 、 Consumer research 、 Decision model 、 Valuation (finance) 、 Decision tree 、 Decision support system 、 Computer science
摘要: The decision plan net (DPN) or tree (DT) is a graphic representation of preferences and the way they are traded off when supply low. method allows one to determine compensatory non-compensatory choice rules that people use. Compensatory decision-making implies low value on attribute can be compensated for by high more other attributes. In contrast, highly valued cannot make up weakly one. valuation an above below certain preferred threshold must therefore lead rejection alternative. Unlike most methods, DPN offers respondent complete freedom in determining which attributes (dwelling characteristics) important, levels satisfactory combinations provide attractive dwellings. It often used explorative stage consumer research. shows individual support systems (DSS) based knowledge-based-rules. DSS evaluates any offer (vacancy) results set rejections accepts. This output researchers evaluate systematically how change level changes both sets. best cost-benefit ratio new construction projects experimental design unravel underlying structure detail.