Measurement of Multiple Cognitive Judgments Model - Fuzzification of Social Judgment Theory Case Study
作者
中文摘要
本研究之目的在於結合社會判斷理論與模糊集理論，嘗試針對多元認知模式判斷效果重新建立量測方式。經由實證結果發現，模糊集理論（fuzzy set theory, FST）的模糊質化方式，確實能夠改善收斂社會判斷理論（social judgment theory, SJT）的權重數值。此外，針對傳統的社會判斷理論方法提出三點結論：（1）以質化方式提供決策者針對決策參考變數進行判斷值的評估，亦即採取語意變數區隔的方式，由決策者進行判斷選擇，如此或能更加具體掌握決策者之方案偏好水準；（2）在與模糊集理論的結合方面，需建立適當的決策者語意變數判斷值範圍，包括適合的語意變數區間與模糊歸屬函數型態；以及（3）宜運用其他適當分析方法，先行完成語意變數區間之確認，與模糊歸屬函數型態和範圍的界定後，再投入社會判斷理論模式提供決策者進行判斷，如此將能獲得更佳成果。綜合上列三點結論顯示，以模糊集理論結合擴展社會判斷理論，應可得到良好之實質成效。
中文關鍵字
社會判斷理論、模糊集理論、決策判斷、權重
英文摘要
This study aims to propose a measurement improvement method for multiple cognitive judgments with a case study using fuzzification of social judgment theory. The empirical results show fuzzy set theory (FST) can efficiently improve the weights of social judgment theory (SJT). The main conclusions find (1) Qualitative method can provide decision makers with judgment value evaluation for cues, that linguistic variables can reflect the decision preference of programs. (2) Applying fuzzy set it is required to offer an appropriate judgment value range of linguistic variable for decision makers. That includes interval of linguistic variable and the type of fuzzy membership function. (3) Better results comes from appropriate methods for confirming the interval of linguistic variable, type of fuzzy membership function and range in advance, therefore decision makers can make judgments better in SJT model. Finally integrating fuzzy set theory with SJT can contribute to better results.
英文關鍵字
Social Judgment Theory, Fuzzy Set Theory, Decision Making, Weights
