Knowledge Sharing and Investment Decisions in Information Security
University of Alberta School of Business Research Paper No. 2013-652
Decision Support Systems Volume 52, Issue 1, December 2011, Pages 95–107
Posted: 2 Jul 2013
Date Written: December 1, 2010
Abstract
We study the relationship between decisions made by two similar firms pertaining to knowledge sharing and investment in information security. The analysis shows that the nature of information assets possessed by the two firms, either complementary or substitutable, plays a crucial role in influencing these decisions. In the complementary case, we show that the firms have a natural incentive to share security knowledge and no external influence to induce sharing is needed. However, the investment levels chosen in equilibrium are lower than optimal, an aberration that can be corrected using coordination mechanisms that reward the firms for increasing their investment levels. In the substitutable case, the firms fall into a Prisoners' Dilemma trap where they do not share security knowledge in equilibrium, despite the fact that it is beneficial for both of them to do so. Here, the beneficial role of a social planner to encourage the firms to share is indicated. However, even when the firms share in accordance to the recommendations of a social planner, the level of investment chosen by the firms is sub-optimal. The firms either enter into an “arms race” where they over-invest or reenact the under-investment behavior found in the complementary case. Once again, this sub-optimal behavior can be corrected using incentive mechanisms that penalize for over-investment and reward for increasing the investment level in regions of under-investment. The proposed coordination schemes, with some modifications, achieve the socially optimal outcome even when the firms are risk-averse. Implications for information security vendors, firms, and social planner are discussed.
Keywords: Security investment, Knowledge sharing, Coordination scheme, Nash equilibrium, Taylor series approximation
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