隨著資訊量的爆炸，面對問題時的決策變得困難。加上問題涵蓋範圍變得廣泛，專家的專業程度只能評估問題範圍中的一部分，給予的資訊也就無法處理整個問題，因此產生了不完整資訊下的決策問題。為了能夠解決問題的各個面向，所以採用群體決策方法找出與問題相關的各類專家處理問題。專家們來自不同領域，各專家在決策過程中選擇可以評估的屬性給予相關資訊以增加結果的正確性，並同時排除掉自身不熟悉的屬性，以確保結果不會造成嚴重偏差的情況。因此，本研究的目的在於能夠更合理地處理不完整問題，透過推論的方式萃取專家心中的隱藏資訊，提供問題更多的資訊，使得問題能較以往有效的被解決。
決策過程主要將不完整的資訊透過推論的方式補足，找出最有可能的遺漏資訊。決策流程共分為三大階段，第一階段為初始階段，確定所要面對的問題並進行探討；第二階段則是針對問題中的不完整的屬性權重評估值及方案評估值進行推論並補足，使得問題能消除不確定性；最後一階段為整合以及選擇階段，將各專家經過補足後的結果整合為群體結果，並從中找出最佳方案。
最後將本研究所構想出的決策模式透過現有例子進行驗證，結果與以往所得到的方案排序雖然不同，但方案間的優劣程度與過往學者得到的結果類似，因此能夠說明此研究模式具備一定的合理性，但使用本研究決策模式較能夠反映出各專家的想法。本研究的優點在於找出每個未提供完整資訊的專家，並找出這些專家的參考專家，將參考專家所提供的資訊作為未提供完整資訊的專家的依據，提供問題更多可能的資訊輔助決策，讓決策結果能夠更說服於人。決策過程中的整合方式也比之前文獻合理，能夠充分地考量各專家所提供的結果，而且不易受極端值影響。

Group decision making (GDM) is a typical way to make decision in many enterprises. Due to the complicated business environment, experts might not possess sufficient knowledge concerning the decision-making problem, so that they may not provide complete evaluation information for it. To overcome this problem, this study presents novel decision models to make up the missing information which expects couldn’t handle.
Decision models include three phases. Firstly, Experts evaluate the decision-making problem based on their knowledge. This study allows experts to only provide some assessments for those attributes they can evaluate. Therefore, there could be some missing information in the evaluation process. Then, the missing information is filled up by the proposed approached. Finally, the filled-up assessments from each expert are aggregated as the group assessments. Based on the group assessments, the best alternative can be selected.
An example is used to demonstrate the feasibility of decision models. Through the comparison, the results from this study are more reasonable than the existing approaches. Finally, the conclusion is drawn and some ideas are proposed for further exploration.

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