層級分析法(analytic hierarchy process, AHP)於1971年由Thomas Saaty所提出，經過三十多年之發展，已成為現今決策領域中常見之決策工具。然而層級分析法於發展過程中，其群體決策偏好整合之問題一直備受質疑。就目前而言，文獻中常見之群體決策偏好整合模式的方法乃是採用幾何平均數及算術平均數法，但由於幾何平均數及算術平均數皆屬於平均數之範疇，故易受到極端值之影響，且僅利用簡單之數學平均式來整合決策者之意見，未免顯得過於單純化，無法將群體決策者對方案間之偏好順序及偏好程度充分表現於整合結果上。因此，本研究將就層級分析法於群體決策偏好整合之問題上，提出以考量「決策者偏好」為基礎的整合模式。以「方案間之權重偏差值」作為群體決策偏好程度整合階段之係數，可充分表現出符合現實世界各決策者於不同方案間之偏好程度;以「方案偏好順序之係數」為基礎之偏好順序整合模式，乃由於決策者通常在意的是最偏好之方案，他們通常會在乎自己所最偏好之方案是否被採用，接下來依序為第2方案、第3方案…等方案是否被採用，因此為了符合現實生活中決策者之決策心理，我們有必要將決策者對方案之偏好順序予以納入考量。接下來，再將偏好程度整合階段的「方案間之權重偏差值」與偏好順序整合階段的「方案偏好順序之係數」結合，以求出最終方案之權重。最後，將本研究之模型與原始模型進行比較，並利用「客觀衡量-滿意指標」及「主觀衡量-專家回饋性訪談」予以衡量，據以了解本研究考量「決策者偏好」之專家整合模型與傳統利用幾何平均數法整合模型兩者之間的差異。

Analytic hierarchy process (AHP), proposed by Thomas Saaty in 1971, have already become a common decision technique in the field of decision science. In the development of AHP, the question about group decision aggregation has been discussed. A vast amount of literature has adopted the geometric mean method or the arithmetic mean method in dealing with the group decision aggregation. However, geometric mean methods and arithmetic mean methods are usually subject to the influence of extreme value, and only make use of simple average type of mathematics to combine the decision makers’ suggestions. In this paper, “weight differences”, which denotes the preference degrees among different alternatives for each decision maker, and “preference priorities”, which denotes the rank lists for the alternatives for each decision maker, are both considered to construct the final weights of group members for group decision model. Finally, a comparative analysis is perform to compare the proposed model and the traditional model, and a “satisfaction index” is proposed to indicate the satisfactory level of such a final group decision. An “Expert feedback interviews” investigates the differences between the proposed approach and traditional model which aggregate the decision by the geometric mean method.

中文部分【依筆劃順序】

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