Title: 從資訊處理觀點探討領域知識對管理者應用財務資訊行為之影響
The Effects of Domain Knowledge on Managers’ Financial Information Application Behavior: An Information Processing Perspective
Authors: 黃俊源
Dr. Po-Young Chu
Keywords: 原案分析法;人類問題解決;財務資訊;領域知識;心智模式;protocol analysis method;human problem solving;financial information;domain knowledge;mental model
Issue Date: 2002
Abstract: 本研究利用心理學家研究人類行為時經常採取之原案分析(protocol analysis)方法,嘗試探管理者在使用財務資訊時的心理歷程,及管理者的專業背景與財務經驗是否影響其財務資訊使用之個別差異因素。冀望能以此實證結果為指引,推論出運用財務資訊改善決策品質的各種可能途徑,以縮短財務資訊與管理者認知之間的差距,提升決策績效。實驗結果顯示,領域知識與財會背景之決策者使用財務資訊模式,與不具領域知識與財會背景之決策者行為顯著不同,領域知識與財會背景確具過濾不相關資訊之功能。
“Knowledge” has been a popular issue for the management academic recently, and a great deal of literatures about “knowledge management” has been published. As the firms’ competitive advantages mainly come from variety of knowledge accumulation, the way how to utilize the existing knowledge to enhance competence has turn into a myth that every manager wants to know. Financial information has important position already became an important knowledge power that cannot be neglected through this trend. Financial statements were originally developed to provide information for general-purpose. Therefore, managers usually have to spend a lot of time in restructuring these enormous data to meet their needs for effective decision making. For the reason, several financial scholars have been motivated to study “behavioral finance” or “behavioral accounting” lately, so more efficient ways to organize and present information to facilitate managers’ decision making. In this study, the protocol analysis method generally used to study human behavior by psychologists is adopted to identify manager’s financial information application behavior. Two factors: domain knowledge and professional financial working experience which might influence the human financial information processing behavior, are structuralized in the research design. The empirical results suggest that domain knowledge and professional working experience function as a filter to screen out unrelated data to facilitate decision makers’ efficient information process.
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