Utility Improvements Using Smart Contracts

16 Pages Posted: 9 Aug 2022

See all articles by Elmira Mohammadhosseini Fadafan

Elmira Mohammadhosseini Fadafan

University of Vienna- Department of Business Decisions and Analytics

Date Written: December 15, 2021


In this paper we propose a smart contract as an innovation model that modifies the contract outcomes in a way that some of the inaccuracies caused by unforeseen external factors modeled as noise may improve the results. If we have overall beneficial changes, we allocate them so that all contracting parties accept the change. Initially, we choose a contract on the efficient frontier, and this contract, that we call traditional fixed contract, will be agreed by the two parties. In this work we study the change in the utility values caused by some random unforeseen events. Because of this change one of the parties will experience lower utility value and will be less satisfied and the other one will be better off. Our proposed smart contract will compensate this change in an automatic way by adjusting the contract according to the external noise. The smart contract calculates the price range obtained by the price boundaries according to the utility value of the consumer and the supplier. This may define the negotiation interval for the contracting parties. Here we consider cases in which the random external factor, modeled as noise worsens the consumer utility outcome. Therefore, for any agreed price in the above range the utility values of the consumer and the supplier will not be worse than the utility values in the conventional fixed contract case. Hence, it means that random external noise factor can be even beneficial and it could be caused by innovation.

Keywords: Smart Contract, Innovation, Efficiency, Flexibility, Bargaining Range, Satisfaction.

Suggested Citation

Mohammadhosseini Fadafan, Elmira, Utility Improvements Using Smart Contracts (December 15, 2021). Available at SSRN: https://ssrn.com/abstract=4181621 or http://dx.doi.org/10.2139/ssrn.4181621

Elmira Mohammadhosseini Fadafan (Contact Author)

University of Vienna- Department of Business Decisions and Analytics ( email )


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