1,570 research outputs found
Online Learning of Aggregate Knowledge about Non-linear Preferences Applied to Negotiating Prices and Bundles
In this paper, we consider a form of multi-issue negotiation where a shop
negotiates both the contents and the price of bundles of goods with his
customers. We present some key insights about, as well as a procedure for,
locating mutually beneficial alternatives to the bundle currently under
negotiation. The essence of our approach lies in combining aggregate
(anonymous) knowledge of customer preferences with current data about the
ongoing negotiation process. The developed procedure either works with already
obtained aggregate knowledge or, in the absence of such knowledge, learns the
relevant information online. We conduct computer experiments with simulated
customers that have_nonlinear_ preferences. We show how, for various types of
customers, with distinct negotiation heuristics, our procedure (with and
without the necessary aggregate knowledge) increases the speed with which deals
are reached, as well as the number and the Pareto efficiency of the deals
reached compared to a benchmark.Comment: 10 pages, 5 eps figures, ACM Proceedings documentclass, Published in
"Proc. 6th Int'l Conf. on Electronic Commerce ICEC04, Delft, The
Netherlands," M. Janssen, H. Sol, R. Wagenaar (eds.). ACM Pres
Online learning of aggregate knowledge about non-linear preferences applied to negotiating prices and bundles
In this paper, we consider a form of multi-issue negotiation where a shop negotiates both the contents and the price of bundles of goods with his customers. We present some key insights about, as well as a procedure for, locating mutually beneficial alternatives to the bundle currently under negotiation. The essence of our approach lies in combining aggregate (anonymous) knowledge of customer preferences with current data about the ongoing negotiation process. The developed procedure either works with already obtained aggregate knowledge or, in the absence of such knowledge, learns the relevant information online. We conduct computer experiments with simulated customers that have emph{nonlinear} preferences. We show how, for various types of customers, with distinct negotiation heuristics, our procedure (with and without the necessary aggregate knowledge) increases the speed with which deals are reached, as well as the number and the Pareto efficiency of the deals reached compared to a benchmar
Negotiating over Bundles and Prices Using Aggregate Knowledge
Combining two or more items and selling them as one good, a practice called
bundling, can be a very effective strategy for reducing the costs of producing,
marketing, and selling goods. In this paper, we consider a form of multi-issue
negotiation where a shop negotiates both the contents and the price of bundles
of goods with his customers. We present some key insights about, as well as a
technique for, locating mutually beneficial alternatives to the bundle
currently under negotiation. The essence of our approach lies in combining
historical sales data, condensed into aggregate knowledge, with current data
about the ongoing negotiation process, to exploit these insights. In
particular, when negotiating a given bundle of goods with a customer, the shop
analyzes the sequence of the customer's offers to determine the progress in the
negotiation process. In addition, it uses aggregate knowledge concerning
customers' valuations of goods in general. We show how the shop can use these
two sources of data to locate promising alternatives to the current bundle.
When the current negotiation's progress slows down, the shop may suggest the
most promising of those alternatives and, depending on the customer's response,
continue negotiating about the alternative bundle, or propose another
alternative. Extensive computer simulation experiments show that our approach
increases the speed with which deals are reached, as well as the number and
quality of the deals reached, as compared to a benchmark. In addition, we show
that the performance of our system is robust to a variety of changes in the
negotiation strategies employed by the customers.Comment: 15 pages, 7 eps figures, Springer llncs documentclass. Extended
version of the paper published in "E-Commerce and Web Technologies," Kurt
Bauknecht, Martin Bichler and Birgit Pr\"{o}ll (eds.). Springer Lecture Notes
in Computer Science, Volume 3182, Berlin: Springer, p. 218--22
05011 Abstracts Collection -- Computing and Markets
From 03.01.05 to 07.01.05, the
Dagstuhl Seminar 05011``Computing and Markets\u27\u27 was held
in the International Conference and Research Center (IBFI),
Schloss Dagstuhl.
During the seminar, several participants presented their current
research, and ongoing work and open problems were discussed. Abstracts of
the presentations given during the seminar as well as abstracts of
seminar results and ideas are put together in this paper. The first section
describes the seminar topics and goals in general.
Links to extended abstracts or full papers are provided, if available
Individual Tariffs for Mobile Communication Services
This paper introduces a conceptual framework and a computational model for individual tariffs for mobile communication services. The purpose is to provide guidance for implementation by communication service suppliers or user groups alike. The paper first examines the sociological and economic incentives for personalized services and individual tariffs. Then it introduces a framework for individual tariffs which is centered on user and supplier behaviours. The user, instead of being fully rational, has "bounded rationality" and his behaviours are subject to economic constraints and influenced by social needs. The supplier can belong to different types of entities such as firms and communities; each has his own goals which lead to different behaviors. Individual tariffs are decided through interactions between the user and the supplier and can be analyzed in a structured way using game theory. A numerical case in mobile music training is developed to illustrate the concepts.risks;mobile communication services;Individual tariffs;computational games
Many-objective design of reservoir systems - Applications to the Blue Nile
This work proposes a multi-criteria optimization-based approach for supporting the negotiated design of multireservoir systems. The research addresses the multi-reservoir system design problem (selecting among alternative options, reservoir sizing), the capacity expansion problem (timing the activation of new assets and the filling of new large reservoirs) and management of multi-reservoir systems at various expansion stages. The aim is to balance multiple long and short-term performance objectives of relevance to stakeholders with differing interests. The work also investigates how problem re-formulations can be used to improve computational efficiency at the design and assessment stage and proposes a framework for post-processing of many objective optimization results to facilitate negotiation among multiple stakeholders. The proposed methods are demonstrated using the Blue Nile in a suite of proof-of-concept studies. Results take the form of Pareto-optimal trade-offs where each point on the curve or surface represents the design of water resource systems (i.e., asset choice, size, implementation dates of reservoirs, and operating policy) and coordination strategies (e.g., cost sharing and power trade) where further benefits in one measure necessarily come at the expense of another. Technical chapters aim to offer practical Nile management and/or investment recommendations deriving from the analysis which could be refined in future more detailed studies
Individual Tariffs for Mobile Communication Services
This paper introduces a conceptual framework and a computational model for individual tariffs for mobile communication services. The purpose is to provide guidance for implementation by communication service suppliers or user groups alike. The paper first examines the sociological and economic incentives for personalized services and individual tariffs. Then it introduces a framework for individual tariffs which is centered on user and supplier behaviours. The user, instead of being fully rational, has "bounded rationality" and his behaviours are subject to economic constraints and influenced by social needs. The supplier can belong to different types of entities such as firms and communities; each has his own goals which lead to different behaviors. Individual tariffs are decided through interactions between the user and the supplier and can be analyzed in a structured way using game theory. A numerical case in mobile music training is developed to illustrate the concepts
Recommended from our members
PRO-SOCIAL CONSUMER AND FIRM BEHAVIOR IN IMPERFECTLY COMPETITIVE REGIONAL AGRICULTURAL MARKETS
In this dissertation, I combine field research, econometric methods, and economic theory to analyze a market in which both firms’ and consumers’ choices are motivated by social preferences. This work contributes to the fields of behavioral economics, industrial organization, and local food systems economics. The dissertation expands the growing literature on social preferences to incorporate firms’ choices that are motivated by utility maximizing objectives in an environment that allows endogenous equilibrium prices and quantities. Firms with social preferences operate in a competitive environment in which they may face downstream market power. In particular, the research focuses on intermediated Farm to School markets for local food in which producers’ marketing decisions may be influenced by both market structure and the pro-social motivations embedded in local food markets
- …