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This article analyses the effects of a regulatory cap on executive pay when the agent is loss averse. I use a principal–agent model with moral hazard in which a principal and an agent bargain over an incentive contract. I show that even a non-binding cap on the agent’s payments can have consequences for the bargained outcome and consequently for the effort the agent exerts. [ABSTRACT FROM AUTHOR]

The rapid growth of cloud computing and data centers with skyrocketing energy consumption, together with the accelerating penetration of renewable energy sources, is creating both severe challenges and tremendous opportunities. Data centers offering large flexible loads in the grid, opens up a unique opportunity to smooth out the significant fluctuation and uncertainty of renewable generation and hence enable seamless integration. To take the market power of data centers into consideration, this paper proposes a bargaining solution to the market program for data center demand response when the load serving entity (LSE) has power supply deficiency. Specifically, due to the uncertainty of load flexibility of data centers incurred by the intermittent on-site renewable generation and dynamic service requests, there exists information asymmetry between the LSE and the data center, which complicates the design of the bargaining solution. Making use of the log-concavity of the (expected) utility functions, a computationally efficient method to implement the best response updates in the bargaining procedure is presented. Furthermore, it is shown analytically that the bid sequences of the LSE and the data center are guaranteed to converge and the final price clinched by the bargaining algorithm is indeed the Nash bargaining solution, which is proportionally fair. In addition, the proposed bargaining solution is compared with two other schemes, namely the Stackelberg game and the social welfare maximization schemes. Finally, extensive numerical experiments are conducted to validate the theoretical guarantees of the bargaining and to examine the impact of various model parameters. Empirical comparison indicates the fairness advantage of the bargaining approach over the other two schemes, especially when the load of the data center is not very flexible, highlighting the importance of information feedback embodied by the bargaining procedure. [ABSTRACT FROM AUTHOR]

We analyze the problem of dividing a fixed amount of a single commodity between two players on the basis of the Nash bargaining solution (NBS). For one-shot negotiations, a cornerstone result of Roth (Axiomatic models of bargaining. Springer, Berlin, 1979) establishes that the more risk averse player will obtain less than half the total amount. In the present paper, we assume that the bargaining procedure occurs over several rounds. In each round, an increasing share of the total amount is negotiated over in accordance with the NBS, the disagreement point being determined by the outcome of the previous round. In line with Roth's result, the final amount received by the more risk averse player is still bounded by half the total amount. As a new feature, however, this player does not lose from bargaining for more rounds if his opponent exhibits non-increasing absolute risk aversion. What is more, both players' risk profiles become essentially irrelevant if successive bargaining takes place over sufficiently small commodity increments. Each player then gets approximately half of the commodity. [ABSTRACT FROM AUTHOR]

We provide two alternative characterizations of the Nash bargaining solution. We introduce new simple axioms, strong undominatedness by the disagreement point, and egalitarian Pareto optimality. First, we prove that the Nash solution is characterized by symmetry, scale invariance, independence of irrelevant alternatives, and strong undominatedness by the disagreement point. Second, we replace the independence of irrelevant alternatives axiom with the sandwich axiom (Rachmilevitch in Theory Decis 80:427-442, 2016) and egalitarian Pareto optimality. We then demonstrate that the Nash solution is characterized by symmetry, scale invariance, strong undominatedness by the disagreement point, the sandwich axiom, and egalitarian Pareto optimality. [ABSTRACT FROM AUTHOR]

This paper contributes to the analysis of centralised versus decentralised labour market negotiations. Applying the familiar Nash bargaining solution, we show that centralised negotiations lead to a lower employment level but to a higher wage rate than decentralised labour market bargaining. While this is an important theoretical result on its own, it has important effects for both empirical labour market research and labour market policies. Also, this result counters the critique that efficient negotiations result in employment levels exceeding the competitive level. [ABSTRACT FROM AUTHOR]

In this article a three-stage framework is proposed for allocating water and welfare in transboundary river basins under water scarcity. The proposed allocation framework combines the bargaining theory with resource allocation and bankruptcy games. The water bankrupt Euphrates River was taken as a case study to demonstrate the applicability of the allocation framework. The results showed that the total monetary welfare that can be generated by reallocating the water in order of decreasing water productivity value of each riparian country is greater by 43.43% of total monetary warfare that can be made if each country were to utilize the water allocated to it independently. The proposed allocation framework rewarded Turkey, Syria and Iraq with welfare assignments which are 41.5%, 42.1% and 57.45% greater than what they could have achieved by unilaterally utilizing the water allocated to them. Generally, the proposed water allocation, water reallocation and welfare assignment framework provide some insights for allocating transboundary water in a way which is efficient, fair and sustainable. [ABSTRACT FROM AUTHOR]

Dynamic requests of viewers from sparse and dispersed locations for crowdsourced-live-streaming (CSLS) service make current cloud service providers (CSPs) inadequate to provide sufficient quality of experience (QoE). To solve this issue, we propose a multi-CDN-assisted-CSLS (MCACLS) architecture, a novel cloud architecture complemented by multiple content delivery networks (Multi-CDNs). MCACLS architecture can enhance a CSP’s capacity of video distribution service and improve the quality of CSLS service for end-users while reducing the overall operational cost. MCACLS adaptively adjusts resources between a CSP and its leased CDN service in a fine granularity to deal with the volatility of user requests. However, scheduling resources cost-effectively in response to user requests from different regions is a critical issue that must be addressed. We formulate the above problem into a constrained stochastic optimization problem and propose an algorithm based on the Nash bargaining solution. Our proposed algorithm makes tradeoff between QoE of users and the overall operational cost for CSPs. Illustrative studies validate the advantages of MCACLS and show that it is more cost-effective, reducing the overall operational cost by up to 15% compared with other alternatives while achieving sufficient QoE for viewers. [ABSTRACT FROM AUTHOR]

In this work, a multi-person mean-field-type game is formulated and solved that is described by a linear jump-diffusion system of mean-field type and a quadratic cost functional involving the second moments, the square of the expected value of the state, and the control actions of all decision-makers. We propose a direct method to solve the game, team, and bargaining problems. This solution approach does not require solving the Bellman-Kolmogorov equations or backward-forward stochastic differential equations of Pontryagin's type. The proposed method can be easily implemented by beginners and engineers who are new to the emerging field of mean-field-type game theory. The optimal strategies for decision-makers are shown to be in a state-and-mean-field feedback form. The optimal strategies are given explicitly as a sum of the well-known linear state-feedback strategy for the associated deterministic linear-quadratic game problem and a mean-field feedback term. The equilibrium cost of the decision-makers are explicitly derived using a simple direct method. Moreover, the equilibrium cost is a weighted sum of the initial variance and an integral of a weighted variance of the diffusion and the jump process. Finally, the method is used to compute global optimum strategies as well as saddle point strategies and Nash bargaining solution in state-and-mean-field feedback form. [ABSTRACT FROM AUTHOR]

As a problem in supply chain management, the decision problem of terms and conditions of a contract between a supplier and a retailer is recognized commonly. The concept of cooperative bargaining between a supplier and a retailer is the key concepts to resolve this problem in the supply chain. Then, the bargaining evaluation function by Nash in the game theory exists as a tool to obtain the solution by cooperation bargaining. The Nash bargaining solution is derived under the premise that a power balance between a supplier and a retailer is equal. However, the situation where the power balance between a supplier and a retailer in actual bargaining is not equal is supposed frequently. For the purpose of reflecting the power balance in obtaining the bargaining solution, the concept of a general bargaining solution was proposed and then the general bargaining evaluation function for obtaining the general bargaining solution was devised. However, in the case of adopting the general bargaining evaluation function as a bargaining tool, some problems are included. In this article, we address the problems in the general bargaining solution. Then, we propose a new concept of bargaining process to obtain a solution under considering the existence of power balance between a supplier and a retailer. [ABSTRACT FROM AUTHOR]

This study was carried out with the aim of feasibility evaluation of the application of multi-objective game theory and fuzzy programing approaches for settling balance between economic development and environmental impact as well as to facilitate the respective decision-makings in Zemkan basin, west of Iran. The bi-objectives of multi-objective game theory and fuzzy programing approaches are minimizing the destructive effects on the environment (less erosion and sediments) and maximizing the economical incomes resulted from different land uses (more net present value). Satellite images were used for recognition of different land uses and the areas of these land use. In this study, the environmentalists and Zemkan basin users were selected as environmental and economical players, respectively. The results reveal that Nash bargaining solution, which is the result of the multi-objective game theory model, differs from Pareto optimalities, obtained through the classical multi-objective model. Nash bargaining solution offered more satisfactory solutions based on decision-makers’ priorities. In addition, the overall results showed that the results of fuzzy programming approach were very close to the results of the multi-objective game theory model. Therefore, in both methods, the decision variables of semi-closed forest, open forest, non-irrigated agricultural lands and barren rocky lands were eliminated and the ones of rural areas, urban areas, and water body remained unchanged. The innovation of multi-objective game theory and fuzzy programing approaches, which can be understood and interpreted well by decision makers, is setting a kind of balance between economic and environmental concerns in watershed management. The results also show that multi-objective game theory and fuzzy programing approaches can be applied to many other issues concerning the environmental management. The upcoming researches can concentrate on developing a third objective like social concerns and accordingly tri-objective games would be applied instead of bi-objective ones. [ABSTRACT FROM AUTHOR]