SEM/SEO環境中探討歸因理論之個體異質性問題

Abstract

隨著數據量的增加，當研究人員在分析來自網路世界或企業內部這些難以數計的資料，企圖歸因從中尋找因果關係以進行研究或決策時，在此種不停變動的網路世代傳統的實驗方式勢必要進行修正，DID估計法提供了一個解決途徑。 當研究人員在進行研究時，除了對於自變數與應變數的選取應有理論基礎避免陷入套套邏輯之外，研究人員也需要重視個體異質性對於研究結果的影響。研究過程中受試者個人根深蒂固的思維很有可能影響該名受試者的態度，進而影響受試者在實驗中表現出來的行為模式。因而研究人員所得到的研究結果其真相很有可能就被隱藏在這些個人特質或思維底下，而無法達到正確的歸因。

It becomes more difficult for researcher to analyze data from internet or company due to data increases dramatically. Therefore, when researcher intends to find the causal relationship from the database to study or decide, the traditional experiment needs to be modified. Fortunately, DID approximation provides a way to solve this problem. When the analysis is made, we should choose independent variable and dependent variable based on theory to avoid tautology mistake. In addition, the individual heterogeneity is also a very important parameter for research results. However, the individual experience of subject may influence his/her attitude in the studying process, and further affect the behavior he/she presents in the study. Once it happens, the truth may be hidden beyond the individual characteristics or thinking and the correct attribution cannot be obtained.