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Knowledge Management Using Information Technology: Determinants of Short‐Term Impact on Firm Value *
Author(s) -
Sabherwal Rajiv,
Sabherwal Sanjiv
Publication year - 2005
Publication title -
decision sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.238
H-Index - 108
eISSN - 1540-5915
pISSN - 0011-7315
DOI - 10.1111/j.1540-5414.2005.00102.x
Subject(s) - contingency theory , diversification (marketing strategy) , contingency , organizational learning , value (mathematics) , process (computing) , term (time) , empirical research , business , marketing , knowledge management , industrial organization , economics , microeconomics , computer science , physics , linguistics , philosophy , epistemology , quantum mechanics , machine learning , operating system
The importance of knowledge management (KM) processes for organizational performance is now well recognized. Seeking to better understand the short‐term impact of KM on firm value, this article focuses on public announcements of information technology (IT)‐based KM efforts, and uses cumulative abnormal return (CAR) associated with an announcement as the dependent variable. This article employs a contingency approach, arguing that the KM announcement would have a positive short‐term impact on firm value in some conditions but not in others. Thus, it pursues the following research question: What are the effects of contextual factors on the CAR associated with the announcement of an IT‐based KM effort? Specific hypotheses are proposed based on information‐processing theory, organizational learning theory, the knowledge‐based theory of the firm, and the theory of knowledge creation. These hypotheses link CARs to alignment between industry innovativeness and the KM process, alignment between firm efficiency and the KM process, firm‐specific instability, and firm diversification. The empirical study utilizes secondary data on 89 KM announcements from 1995 to 2002. The results largely support the hypotheses. Overall, this article provides empirical support for the theory‐based arguments, and helps develop a contingency framework of the effectiveness of KM efforts.