Negotiation transaction costs estimation of an industrial enterprise

The article describes the negotiation process between a supplier and an industrial enterprise. The mathematical model of this process is developed. We consider a bargaining game between two players with conflicting interests. Two phases of negotiations are identified. In the first phase, the players make significant changes in their offers. This happens before the zone of agreement is reached. After that, the second phase begins. In the second phase, the players change their offers much more cautiously. The number of rounds that the negotiations may take before they are completed is determined on the basis of the tit-for-tat strategy. In this strategy, one party adjusts its its behavior to the behavior of the other party. In accordance with the expected number of rounds of negotiations, the player’s offers are formed in the model. To get realistic results, each player is assigned a coefficient of force that determines the effectiveness of the negotiation process. We present a technique for calculating the coefficients for the buyer’s and the seller’s force. An industrial enterprise’s bargaining and negotiation transaction costs classification is introduced as well as formulas for their calculation. We develop software that allows you to carry out simulation of the bargaining process and determine the expected number of rounds of negotiations, the final price of the contract, the size of transaction costs of an industrial enterprise in each round, and allows you to find the optimal total contract price with respect to transaction costs. We use the model experiment to show the work of the software. Transaction costs estimation and optimization of the total contract price is done. The results of this research can be used by industrial enterprises for assessing the total value of contracts with respect to transaction costs. The most effective use of this software is possible as part of a dynamic model of relations between an industrial enterprise and a group of suppliers. This model takes into account the time spent on negotiations, reputation and quality of fulfilling the contractual obligations.В статье рассмотрен процесс проведения переговоров промышленного предприятия с поставщиком. Построена математическая модель, в которой процесс переговоров представлен как игра двух игроков, имеющих конфликтные интересы. Выделены две фазы переговоров. В первой фазе, до достижения зоны согласия, на каждом шаге происходят значительные изменения в предложениях игроков. Во второй фазе, когда зона согласия определена, новые предложения выдвигаются игроками значительно осторожнее. Ожидаемое число раундов, необходимых для завершения переговоров, находится по стратегии tit-for-tat, согласно которой поведение игрока основывается на поведении противоположной стороны переговоров. В соответствии с ожидаемым числом раундов переговоров, в модели формируются предложения игроков. Для получения реалистичных результатов каждому игроку присваивается сила, определяющая эффективность переговорного процесса. Представлена методика расчета коэффициентов силы покупателя и продавца. Проведена классификация трансакционных издержек ведения переговоров и заключения контракта на промышленном предприятии. Приведены формулы для расчета трансакционных издержек. Разработано программное средство, позволяющее проводить моделирование процесса переговоров, определять ожидаемое число раундов переговоров, итоговую сумму контракта, сумму трансакционных затрат промышленного предприятия в каждом раунде, а также находить оптимальную полную стоимость контракта с учетом трансакционных затрат. Работа программного средства показана на модельном эксперименте: проведен расчет трансакционных издержек и оптимизация полной стоимости контракта. Результаты исследования могут быть использованы промышленными предприятиями для расчета полной стоимости контракта с учетом трансакционных издержек. Наиболее эффективное использование данного программного средства возможно в качестве составляющей динамической модели отношений «промышленное предприятие - поставщики», в которой учитывается время, затрачиваемое на переговоры, репутация и качество выполнения контрактных обязательств

CloudNeg: An autonomous multi issue negotiation system, with preference elicitation component, for trading cloud services

Cloud services provide its users with flexible resource provisioning. But in the current market, a user has to choose from a limited set of configurations at a fixed price. This paper presents an autonomous negotiation system termed CloudNeg for negotiating cloud services. CloudNeg provides buyers and sellers of cloud services with autonomous agents to negotiate on the specifications of a cloud instance, including price, on their behalf. These agents elicit their buyers’ time preferences and use them in negotiations. Further, this paper presents two artifacts: a negotiation algorithm and a prototype which together form CloudNeg

Multi-agent systems and birtual producers in electronic marketplaces

This paper presents an agent-based simulator designed for analyzing agent market strategies based on a complete understanding of buyer and seller behaviours, preference models and pricing algorithms, considering user risk preferences. The system includes agents that are capable of improving their performance with their own experience, by adapting to the market conditions. In the simulated market agents interact in several different ways and may joint together to form coalitions. In this paper we address multi-agent coalitions to analyse Distributed Generation in Electricity Market

Human-Agent Negotiations: The Impact Agents’ Concession Schedule and Task Complexity on Agreements

Employment of software agents for conducting negotiations with online customers promises to increase the flexibility and reach of the exchange mechanism and reduce transaction costs. Past research had suggested different negotiation tactics for the agents, and had used them in experimental settings against human negotiators. This work explores the interaction between negotiation strategies and the complexity of the negotiation task as represented by the number of negotiation issues. Including more issues in a negotiation potentially allows the parties more space to maneuver and, thus, promises higher likelihood of agreement. In practice, the consideration of more issues requires higher cognitive effort, which could have a negative effect on reaching an agreement. The results of human–agent negotiation experiments conducted at a major Canadian university revealed that there is an interaction between chosen strategy and task complexity. Also, when competitive strategy was employed, the agents\u27 utility was the highest. Because competitive strategy resulted in fewer agreements the average utility per agent was the highest in the compromising–competitive strategy

Effects of Factors Influencing Residential Property Negotiation Process on Market Outcome in Akure, Nigeria

This study determined the effect of factors influencing residential property negotiation process on the final market outcome in Akure, Nigeria. The research design was field survey in which the target population were the property buyers within the three selected residential densities of the city.  Data was elicited from the self administered structured questionnaire to the 400 property buyers sampled. Data analysis was performed using logistic regression model where the dependent variable was market outcome and the independent variables were eleven dichotomous variables. The findings revealed that some variables showed significant values at p-value ≥ 0.05 influences on market outcome. These variables were agents’ commission, owners’ reservation prices, communication channel, property titled, duration of transaction, owners’ negotiators behaviours and neighbourhood characteristics. The variables that showed insignificant values of influence on market outcome were number of negotiators in each transaction, buyers’ reservation price, strategy employed, buyers’ negotiation behaviour; and cultural differences. There was information asymmetry between the owners’ negotiators and buyers as most of the buyers did not have an independent negotiators to strike a fair outcome (final price) The study therefore recommended two independent and  skilled negotiators who had the detailed knowledge of  information on the previous market condition and range  upon which to strike a fair deal. Equally there should be parallel market price regulatory agencies that must keep and regularly display past records of transactions. Such must be used to negotiate present transactions. No doubt this will break the information advantage that often make owners to have an edge over the buyers. Keywords: Akure, Market Outcome, Negotiation Process, Property, Residential DOI: 10.7176/JESD/12-8-08 Publication date: April 30th 202

A bargaining-specific architecture for supporting automated service agreement negotiation systems

The provision of services is often regulated by means of agreements that must be negotiated beforehand. Automating such negotiations is appealing insofar as it overcomes one of the most often cited shortcomings of human negotiation: slowness. Our analysis of the requirements of automated negotiation systems in open environments suggests that some of them cannot be tackled in a protocol-independent manner, which motivates the need for a protocol-specific architecture. However, current state-of-the-art bargaining architectures fail to address all of these requirements together. Our key contribution is a bargaining architecture that addresses all of the requirements we have identified. The definition of the architecture includes a logical view that identifies the key architectural elements and their interactions, a process view that identifies how the architectural elements can be grouped together into processes, a development view that includes a software framework that provides a reference implementation developers can use to build their own negotiation systems, and a scenarios view by means of which the architecture is illustrated and validatedComisión Interministerial de Ciencia y Tecnología (CICYT) SETI (TIN2009-07366)Junta de Andalucía P07-TIC-2533 (Isabel)Ministerio de Ciencia y Tecnología TIN2010-21744-C02-1Ministerio de Ciencia y Tecnología TIN2007-64119Junta de Andalucía P07-TIC-02602Junta de Andalucía P08-TIC-4100Ministerio de Ciencia e Innovación TIN2008-04718-