利用系統多因子技術探討團體決策優勢

Using Systems Factorial Technology to Investigate Collective Benefit in Group Decision-Making

過去研究發現綜合多數人的意見可以讓團體決策表現更正確且更有效率；但同時也有其他研究發現團體決策不一定更有優勢。基於此不一致結果，本研究透過操弄作業困難度，探討可能造成團體優劣勢的因素。本研究使用T/L 結合搜尋作業，藉由干擾物L 的數量來操弄作業困難度，並要求參與者在個別搜尋（指由一名參與者單獨完成搜尋作業）與團體搜尋（指由兩名參與者共同完成搜尋作業）情境下搜尋目標物。我們使用系統多因子技術（systems factorial technology, SFT; Townsend & Nozawa, 1995），藉由比較團體搜尋表現與參與者個別搜尋表現所預期的團體表現，計算出容量係數（CAND(t) 與AAND(t)），推論團體決策效率。實驗結果發現，在簡單情境與困難情境下都展現出團體決策優勢（CAND(t) > 1 與AAND(t) > 1），且在困難情境下展現出相對更大的團體決策優勢。此較大優勢結果意味著在困難作業情境下，參與者更依賴合作而做出決策；在適當的作業困難度範圍內，增加作業困難度展現出更大的團體決策優勢。

While most previous studies indicate that aggregating group-level decisions tends to show a decision advantage in their response speed and/or the accuracy, other studies argue that collaboration does not always result in better performance. In the current study, we investigate whether the discrepancy in group-level performance resulted from the designed task difficulty. Participants were instructed to perform a conjunction search task as a group (participants in a dyad search for targets together) or by an individual (participants search for targets independently) in which participants were asked to search for target Ts among distractor Ls and the task difficulty was manipulated through the number of distractors. We applied Systems Factorial Technology (SFT; Townsend & Nozawa, 1995) to infer the group-decision efficiency via the workload capacity, CAND(t), and AAND(t), which compared the actual group performance with the predicted baseline from individual search performance. The results revealed a collective benefit in both easy and difficult conditions (i.e., CAND(t)>1 and AAND(t)>1), with a larger benefit in the difficult task condition. Therefore, our results indicate that participants rely more on collaboration when the task is demanding. To conclude, our results suggest that with appropriate task difficulty, group decision-making would be more efficient than individual decisions as the task difficulty increases.