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With the rapid development of global industry and economy, excessive carbon dioxide emission has emerged as a critical issue in both developed and developing countries. Using an evolutionary game framework in which game players can adjust their strategies constantly, this paper investigates how to optimize the strategy of low carbon investment for suppliers and manufacturers in supply chains, and discuss the impacts of various factors on evolutionarily stable strategies. Additionally, we examine an incentive mechanism based on governmental subsidies to eliminate free riding and motivate co-investment. Furthermore, a case study and numerical examples are provided for illustration and simulation purposes, leading to several countermeasures and suggestions. Our analytical results show that the strategic choice of low carbon investment is correlated with profit growth coefficients, investment costs and profits from free riding. Investment costs have more significant impacts than other factors on evolutionarily stable strategies, while profit growth coefficients are more important at initial stages in the evolutionary process. The incentive mechanism based on governmental subsidies is an effective solution to motivate co-investment, and governments should take some measures to improve the assess accuracy and supervisory efficiency of investment strategy.

With the rapid deployment of mobile technologies and their applications in the healthcare domain, privacy concerns have emerged as one of the most critical issues. Traditional technical and organizational approaches used to address privacy issues ignore economic factors, which are increasingly important in the investment strategy of those responsible for ensuring privacy protection. Taking the mHealth system as the context, this article builds an evolutionary game to model three types of entities (including system providers, hospitals and governments) under the conditions of incomplete information and bounded rationality. Given that the various participating entities are often unable to accurately estimate their own profits or costs, we propose a quantified approach to analyzing the optimal strategy of privacy investment and regulation. Numerical examples are provided for illustration and simulation purpose. Based upon these examples, several countermeasures and suggestions for privacy protection are proposed. Our analytical results show that governmental regulation and auditing has a significant impact on the strategic choice of the other two entities involved. In addition, the strategic choices of system providers and hospitals are not only correlated with profits and investment costs, but they are also significantly affected by free riding. If the profit growth coefficients increase to a critical level, mHealth system providers and hospitals will invest in privacy protection even without the imposition of regulations. However, the critical level is dependent on the values of the parameters (variables) in each case of investment and profits.

With the rapid development of information technologies, security violations in online social networks (OSN) have emerged as a critical issue. Traditional technical and organizational approaches do not consider economic factors, which are increasingly important to sustain information security investment. In this paper, we develop an evolutionary game model to study the sustainability of information security investment in OSN, and propose a quantitative approach to analyze and optimize security investment. Additionally, we examine a contract with an incentive mechanism to eliminate free riding, which helps sustain the security investment. Numerical examples are provided for illustration and simulation purposes, leading to several countermeasures and suggestions. Our analytical results show that the optimal strategy of information security investment not only is correlated with profit growth coefficients and investment costs, but is also influenced significantly by the profits from free riding. If the profit growth coefficients are prohibitively small, both OSN service providers and online platforms will not choose to sustain investment based on small profits. As profit growth coefficients increase, there is a higher probability that game players will invest. Another major finding is that the (Invest, Invest) profile is much less sensitive to the change of profit growth coefficients and the convergent speed of this scenario is faster than the other profiles. The government agency can use the proposed model to determine a proper incentive or penalty to help both parties reach the optimal strategies and thus improve OSN security.