research-article

Agent based mobile negotiation for personalized pricing of last minute theatre tickets

Authors:

Namho LeeAuthors Info & Claims

Expert Systems with Applications: An International Journal, Volume 39, Issue 10

Pages 9255 - 9263

https://doi.org/10.1016/j.eswa.2012.02.079

Published: 01 August 2012 Publication History

Abstract

Highlights We propose a negotiation mechanism which uses the current location of customers. Case based reasoning is employed to narrow the initial price offer zone. Fuzzy cognitive map is applied to evaluate counter offers with multiple factors. A simulation results proves the efficiency of the proposed market system. This paper proposes an agent based mobile negotiation framework for personalized pricing of last minutes theatre tickets whose values are dependent on the time remaining to the performance and the locations of potential customers. In particular, case based reasoning and fuzzy cognitive map techniques are adopted in the negotiation framework to identify the best initial offer zone and adopt multi criteria decision in the scoring function to evaluate offers. The proposed framework is tested via a computer simulation in which personalized pricing policy shows higher market performance than other policies therefore the validity of the proposed negotiation framework.

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Cited By

Mukherjee ASundarraj RDutta K(2021)Time-preference-based on-spot bundled cloud-service provisioningDecision Support Systems10.1016/j.dss.2021.113607151:COnline publication date: 1-Dec-2021
https://dl.acm.org/doi/10.1016/j.dss.2021.113607
Tsadiras APempetzoglou MViktoratos I(2021)Making Predictions of Global Warming Impacts Using a Semantic Web Tool that Simulates Fuzzy Cognitive MapsComputational Economics10.1007/s10614-020-10025-158:3(715-745)Online publication date: 1-Oct-2021
https://dl.acm.org/doi/10.1007/s10614-020-10025-1
Davis CGiabbanelli PJetter ASon YHaas P(2019)The intersection of agent based models and fuzzy cognitive mapsProceedings of the Winter Simulation Conference10.5555/3400397.3400501(1292-1303)Online publication date: 8-Dec-2019
https://dl.acm.org/doi/10.5555/3400397.3400501
Show More Cited By

Agent based mobile negotiation for personalized pricing of last minute theatre tickets
1. Computing methodologies
  1. Artificial intelligence
    1. Distributed artificial intelligence

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cover image Expert Systems with Applications: An International Journal

Expert Systems with Applications: An International Journal Volume 39, Issue 10

August, 2012

1434 pages

ISSN:0957-4174

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Copyright © Elsevier Ltd.

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Pergamon Press, Inc.

United States

Publication History

Published: 01 August 2012

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Cited By

Mukherjee ASundarraj RDutta K(2021)Time-preference-based on-spot bundled cloud-service provisioningDecision Support Systems10.1016/j.dss.2021.113607151:COnline publication date: 1-Dec-2021
https://dl.acm.org/doi/10.1016/j.dss.2021.113607
Tsadiras APempetzoglou MViktoratos I(2021)Making Predictions of Global Warming Impacts Using a Semantic Web Tool that Simulates Fuzzy Cognitive MapsComputational Economics10.1007/s10614-020-10025-158:3(715-745)Online publication date: 1-Oct-2021
https://dl.acm.org/doi/10.1007/s10614-020-10025-1
Davis CGiabbanelli PJetter ASon YHaas P(2019)The intersection of agent based models and fuzzy cognitive mapsProceedings of the Winter Simulation Conference10.5555/3400397.3400501(1292-1303)Online publication date: 8-Dec-2019
https://dl.acm.org/doi/10.5555/3400397.3400501
Maroofi F(2019)Investigating Q-learning approach by using reinforcement learning to decide dynamic pricing for multiple productsInternational Journal of Business Information Systems10.1504/ijbis.2019.09952831:1(86-105)Online publication date: 1-Jan-2019
https://dl.acm.org/doi/10.1504/ijbis.2019.099528
Giabbanelli PFattoruso MNorman MJin DLiu JKale L(2019)CoFluencesProceedings of the 2019 ACM SIGSIM Conference on Principles of Advanced Discrete Simulation10.1145/3316480.3322887(71-82)Online publication date: 29-May-2019
https://dl.acm.org/doi/10.1145/3316480.3322887
Fu XZeng XLuo XWang DXu DFan Q(2017)Designing an intelligent decision support system for effective negotiation pricingDecision Support Systems10.1016/j.dss.2017.02.00396:C(49-66)Online publication date: 1-Apr-2017
https://dl.acm.org/doi/10.1016/j.dss.2017.02.003
Rana ROliveira F(2015)Dynamic pricing policies for interdependent perishable products or services using reinforcement learningExpert Systems with Applications: An International Journal10.1016/j.eswa.2014.07.00742:1(426-436)Online publication date: 1-Jan-2015
https://dl.acm.org/doi/10.1016/j.eswa.2014.07.007
Tsadiras ABassiliades N(2013)RuleML representation and simulation of Fuzzy Cognitive MapsExpert Systems with Applications: An International Journal10.1016/j.eswa.2012.08.03540:5(1413-1426)Online publication date: 1-Apr-2013
https://dl.acm.org/doi/10.1016/j.eswa.2012.08.035

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