A Game-theoretic Approach to Formation and Establishment of Partnership among Developers and Public Sector in Urban Development Project

1995 ◽  
Vol 30 (0) ◽  
pp. 427-432
Author(s):  
Eizo Hideshima ◽  
Norio Okada
2018 ◽  
Vol 7 (2) ◽  
pp. 171-199
Author(s):  
Wiston Risso

This paper analyzes the renegotiation problem in the context of public-private partnership projects. Utilizing a game-theoretic approach, an equilibrium is found in which the government finds that accepting renegotiation can be efficient. A first indicator is proposed based the public sector comparator (PSC) that can be estimated by policymakers as an additional tool when deciding about renegotiation. A second more theoretical indicator is derived to analyze the economic and financial variables affecting renegotiation. This indicator is applied to four case studies in different countries (England, Taiwan, Portugal and China) and the results suggest that the model performs well.


1982 ◽  
Vol 55 (3) ◽  
pp. 367 ◽  
Author(s):  
Carl Alan Batlin ◽  
Susan Hinko

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Maya Diamant ◽  
Shoham Baruch ◽  
Eias Kassem ◽  
Khitam Muhsen ◽  
Dov Samet ◽  
...  

AbstractThe overuse of antibiotics is exacerbating the antibiotic resistance crisis. Since this problem is a classic common-goods dilemma, it naturally lends itself to a game-theoretic analysis. Hence, we designed a model wherein physicians weigh whether antibiotics should be prescribed, given that antibiotic usage depletes its future effectiveness. The physicians’ decisions rely on the probability of a bacterial infection before definitive laboratory results are available. We show that the physicians’ equilibrium decision rule of antibiotic prescription is not socially optimal. However, we prove that discretizing the information provided to physicians can mitigate the gap between their equilibrium decisions and the social optimum of antibiotic prescription. Despite this problem’s complexity, the effectiveness of the discretization solely depends on the type of information available to the physician to determine the nature of infection. This is demonstrated on theoretic distributions and a clinical dataset. Our results provide a game-theory based guide for optimal output of current and future decision support systems of antibiotic prescription.


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