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Relevant bibliographies by topics / Nash-bargaining model

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Academic literature on the topic 'Nash-bargaining model'

Author: Grafiati

Published: 21 December 2024

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Journal articles on the topic "Nash-bargaining model"

1

Maude-Griffin, Roland, Roger Feldman *, and Douglas Wholey *. "Nash bargaining model of HMO premiums." Applied Economics 36, no. 12 (2004): 1329–36. http://dx.doi.org/10.1080/0003684042000238938.

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2

Chan, Kenneth S. "Trade negotiations in a Nash bargaining model." Journal of International Economics 25, no. 3-4 (1988): 353–63. http://dx.doi.org/10.1016/0022-1996(88)90060-8.

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3

Hema, P., N. R. Rejin Paul, Lenka Čepová, Bhola Khan, Kailash Kumar, and Vladimira Schindlerova. "Complexity and Monitoring of Economic Operations Using a Game-Theoretic Model for Cloud Computing." Systems 11, no. 2 (2023): 50. http://dx.doi.org/10.3390/systems11020050.

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In this study, a model is presented for allocating cloud computing resources based on economic considerations using tools from game theory. The model, called the Non-Cooperative Game Resource Allocation Algorithm (NCGRAA), is designed to achieve the optimum stage in cloud computing. In addition, the Bargaining Game Resource Allocation Algorithm (BGRAA) is introduced to the existing system to develop the billing process within the constraints of availability and fairness. This system-based algorithm implements methods for converging on and improving the Nash Equilibrium and Nash Bargaining solutions. While the Nash equilibrium helps to develop decision-making concepts with game theory, one of its main goals is to achieve the desired outcome and avoid deviation from the working stage. Nash Bargaining is a unique solution that occurs between two parties and takes into account the process of bargaining to provide a fair solution that is scale invariant and independent. In recent years, cloud computing has become a popular way to manage computing services and enable producers and consumers to interact. This process allows users to obtain goods at an affordable cost from sellers according to their expectations. This research investigates the economic operation monitoring of cloud computing using the gaming theory model. A Static Negotiation Analysis Method with a Bargaining Process (SNAM-BP) for a dynamic conceptual framework is presented to display the weighted relationship between primary issues and keywords used to evaluate the potential partnership of each country.

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Feng, Zhongwei, Fangning Li, and Chunqiao Tan. "Alternating-Offers Bargaining with Nash Bargaining Fairness Concerns." Behavioral Sciences 13, no. 2 (2023): 124. http://dx.doi.org/10.3390/bs13020124.

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The Rubinstein alternating-offers bargaining game is reconsidered, where players show fairness concerns and their fairness references are characterized by the Nash bargaining solution. The objective of this paper is to explore the impact of fairness concerns in the alternating-offer bargaining game. Alternating-offer bargaining with fairness concerns is developed. We construct a subgame perfect equilibrium and show its uniqueness. Then, it is shown that players’ payoffs in the subgame perfect equilibrium are positively related to their own fairness concern coefficient and bargaining power and negatively to the opponents’ fairness concern coefficient. Moreover, it is shown that the limited equilibrium partition depends on the ratio of discount rates of the two players when the time lapse between two offers goes to zero. Finally, the proposed model is applied to the bilateral monopoly market of professional basketball players, and some properties of equilibrium price are shown. Our result provides the implication that players should carefully weigh their own fairness concerns, bargaining power and fairness concerns of their opponents, and then make proposals, rather than simply follow the suggestion that the proposal at the current stage is higher than that at the past stages.

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Bastianello, Lorenzo, and Marco LiCalzi. "The Probability to Reach an Agreement as a Foundation for Axiomatic Bargaining." Econometrica 87, no. 3 (2019): 837–65. http://dx.doi.org/10.3982/ecta13673.

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We revisit the Nash bargaining model and axiomatize a procedural solution that maximizes the probability of successful bargaining. Our characterization spans several known solution concepts, including the special cases of the Nash, egalitarian, and utilitarian solutions. Using a probability‐based language, we offer a natural interpretation for the product operator underlying the Nash solution: when the bargainers' individual acceptance probabilities are independent, their product recovers the joint acceptance probability.

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6

Demougin, Dominique, and Carsten Helm. "Moral Hazard and Bargaining Power." German Economic Review 7, no. 4 (2006): 463–70. http://dx.doi.org/10.1111/j.1468-0475.2006.00130.x.

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Abstract We introduce bargaining power in a moral hazard framework where parties are risk-neutral and the agent is financially constrained. We show that the same contract emerges if the concept of bargaining power is analyzed in either of the following three frameworks: in a standard principal-agent (P-A) framework by varying the agent’s outside opportunity, in an alternating offer game, and in a generalized Nash-bargaining game. However, for sufficiently low levels of the agent’s bargaining power, increasing it marginally does affect the equilibrium in the Nash-bargaining game, but not in the P-A model and in the alternating offer game.

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7

L.A, Papakonstantinidis. "The “Win-Win-Win Papakonstantinidis Model”: from Social Welfare’s Philosophy towards a Rural Development Concept by Rural Tourism Approach: The WERT Case Study." INTERNATIONAL JOURNAL OF INNOVATION AND ECONOMIC DEVELOPMENT 3, no. 1 (2017): 7–25. http://dx.doi.org/10.18775/ijied.1849-7551-7020.2015.35.2001.

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The article is dealing with two interconnected problems based on the conjectures: a) social welfare is a condition for rural development and not the prerequisite for it; b) shape a new landscape (the “win-win-win”) based on critique of the “Impossibility Theorem (Kenneth Arrow 1951) through the Nash Bargaining Solution (Nash, John 1950). Specifically, this article discusses and analyses social welfare and rural development objectives integrating elements from the impossibility theorem, the bargaining theory, and the theory of agency by (a) reviewing the literature on coordination “social welfare” and “rural development” (b) reversing the focus from “voting” to “bargaining” and (c) underlining that Social choice is the perquisite of social welfare, using the “win-win-win Papakonstantinidis model’s solution as the bridge between “voting”(Arrow) and “bargaining”(proposal). This solution highlights the Role of Rural Community as an “Aggregation” corresponding to its “sensitization process”.

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8

Wang, Meiqiang, and Yongjun Li. "Supplier evaluation based on Nash bargaining game model." Expert Systems with Applications 41, no. 9 (2014): 4181–85. http://dx.doi.org/10.1016/j.eswa.2013.12.044.

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9

Braun, Norman, and Thomas Gautschi. "A Nash bargaining model for simple exchange networks." Social Networks 28, no. 1 (2006): 1–23. http://dx.doi.org/10.1016/j.socnet.2004.11.011.

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10

Fallahnejad, Reza, Mohammad Reza Mozaffari, Peter Fernandes Wanke, and Yong Tan. "Nash Bargaining Game Enhanced Global Malmquist Productivity Index for Cross-Productivity Index." Games 15, no. 1 (2024): 3. http://dx.doi.org/10.3390/g15010003.

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The Global Malmquist Productivity Index (GMPI) stands as an evolution of the Malmquist Productivity Index (MPI), emphasizing global technology to incorporate all-time versions of Decision-Making Units (DMUs). This paper introduces a novel approach, integrating the Nash Bargaining Game model with GMPI to establish a Cross-Productivity Index. Our primary objective is to develop a comprehensive framework utilizing the Nash Bargaining Game model to derive equitable common weights for different time versions of DMUs. These weights serve as a fundamental component for cross-evaluation based on GMPI, facilitating a holistic assessment of DMU performance over varying time periods. The proposed index is designed with essential properties: feasibility, non-arbitrariness concerning the base time period, technological consistency across periods, and weight uniformity for GMPI calculations between two-time versions of a unit. This research amalgamates cross-evaluation and global technology while employing geometric averages to derive a conclusive cross-productivity index. The core motivation behind this methodology is to establish a reliable and fair means of evaluating DMU performance, integrating insights from Nash Bargaining Game principles and GMPI. This paper elucidates the rationale behind merging the Nash Bargaining Game model with GMPI and outlines the objectives to provide a comprehensive Cross-Productivity Index, aiming to enhance the robustness and reliability of productivity assessments across varied time frames.

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