Decision Support Systems, Forthcoming
13 Pages Posted: 30 Sep 2013
Date Written: September 30, 2013
Researchers have used the stock price reaction to firms' disclosures of investment in information technology to investigate the value of those investments. This paper extends that research to include knowledge management (KM). In particular, we test whether and how KM is valued by market participants by examining the stock market reaction and future performance of companies receiving the “Most Admired Knowledge Enterprise” (MAKE) award, which recognizes companies that excel at KM. MAKE awards are generated based on opinions gathered from experts using the Delphi method, a well-known group decision support tool. We find that MAKE winners: (1) experience positive abnormal returns around the award announcement, (2) report superior operating performance relative to their peers subsequent to the receipt of the award, (3) receive upward analyst forecast revisions following the award, (4) experience a positive upward stock price drift following the award, and (5) that the market has taken time to learn how to process and interpret information useful in valuing KM. Thus, our findings contribute to the literature by finding that market participants value KM and KM apparently positively influences accounting performance indicators. In addition, a unique feature of our study is that we investigate the market's response to information gathered using the Delphi method, an information source not previously investigated in stock price reaction literature.
Keywords: Capital markets, Knowledge management, Stock valuation, Asset pricing, MAKE award winners, Market study, Delphi method
JEL Classification: D83, E37, G12, G14, G17, M41
Suggested Citation: Suggested Citation
DeFond, Mark L. and Konchitchki, Yaniv and McMullin, Jeff L. and O'Leary, Daniel E., Capital Markets Valuation and Accounting Performance of Most Admired Knowledge Enterprise (MAKE) Award Winners (September 30, 2013). Decision Support Systems, Forthcoming. Available at SSRN: https://ssrn.com/abstract=2333156