Facilitating e-Negotiation Processes with Semantic Web Technologies

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НазваниеFacilitating e-Negotiation Processes with Semantic Web Technologies
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Facilitating e-Negotiation Processes with Semantic Web Technologies

Dickson K.W. Chiu1, Senior Member, IEEE, S. C. Cheung2 Senior Member, IEEE,

Patrick C. K. Hung3 and Ho-fung Leung4

1Dickson Computer Systems, Hong Kong

2Department of Computer Science, Hong Kong University of Science and Technology

3Faculty of Business and Information Technology, University of Ontario Institute of Technology, Canada

4Department of Computer Science and Engineering, The Chinese University of Hong Kong

email: dicksonchiu@ieee.org, scc@cs.ust.hk, Patrick.Hung@uoit.ca, lhf@cse.cuhk.edu.hk


Semantic Web technologies have recently been maturing to make e-commerce interactions and cross-organizational processes more flexible and automated. Ontology has also been developed in various business domains. However, researches in Semantic Web have largely focused on the facilitation of successful matchmaking but not much on the negotiation upon matchmaking failures and exceptions. In this paper, we propose a novel application of Semantic Web technologies for the facilitation of e-Negotiation processes. We discuss how the elicitation of negotiation issues, alternatives, and tradeoff can be streamlined. We further propose a novel methodology for the elicitation of dependencies among negotiation issues so that negotiators can focus on tradeoff among inter-related issues, instead of arguing about single issues. A negotiation plan can thus be derived to observe negotiation orders across different issues. As a result, negotiators can have a better cognition of their negotiation tasks and the overall e-Negotiation process can be streamlined. We are extending a negotiation support system to demonstrate the feasibility of our approach, which is the most useful to repeatable and semi-structured negotiations in business-to-business (B2B) e-Commerce and e-Marketplace environments.

  1. Introduction

Negotiation is a decision process in which two or more parties make individual decisions and interact with each other for mutual gain (Raiffa 1982). The order of a negotiation process should guide the progress of actual business interactions. Proposals are sent to the other parties, and a new proposal may be generated after receiving a counter proposal. The process continues until an agreement or a deadlock is reached, or even one or more parties quit. Each party needs to determine reactions of the other parties and obtain their responses, and each party also needs to estimate the outcomes that the other parties would like to achieve.

However, negotiators tend to be ignorant of the others’ values and strategies, especially in a non-cooperative environment. As a result, negotiations may involve high transaction costs and do not always reach the best solution. The Internet has recently become a global common platform where organizations and individuals communicate among each other to carry out various commercial activities and to provide value-added services. However, as many business activities become automated as electronic transactions, negotiation between human can be a bottleneck. A major problem of this is its slowness, which is further complicated by issues of culture, ego, and pride (Raiffa 1982). An automated negotiation system should conduct negotiation to create value by interacting with different parties to create mutually acceptable deals. This is particularly applicable to standard business interactions that could be taken place over the Internet, such as real-estate transactions, purchase and sale of goods, etc.

During negotiation processes, understanding the interactions between parties is critical (Griffel 1997). Negotiation often involves the evaluation of several issues and of several alternatives per issue. As a result, a large combination of values has to be evaluated by decision makers, which is time consuming and could be difficult for decision makers from a cognitive perspective. Thus tradeoffs can often be identified when two or more issues are considered simultaneously (Druckman 1977). Most of the related work in negotiations takes the consideration of issues in isolation. Decision makers are assumed to consider the issues one at a time, in a stepwise fashion, instead of integrating multiple issues into a single package so that potential tradeoffs can be recognized (Foroughi and Jelassi 1990).

Recently, Semantic Web technologies (Fensel et al. 2001, Daconta et al. 2003) have been maturing to make e-commerce interactions more flexible and automated. The Semantic Web provides explicit meaning to the information available on the Web for automated processing and information integration based on the underlying ontology. An ontology defines the terms used to present a domain of knowledge that is shared by people, databases, and applications. In particular, ontologies encode knowledge possibly spanning different domains as well as describe the relationships among them. Ontologies have also been developed in various business domains such as HIPAA (2003). One can imagine that ontologies can help negotiators to better understand the negotiation process.

However, researches in Semantic Web have mainly focused on the facilitation of successful matchmaking but not much on the negotiation upon matchmaking failures and exceptions. Yet, ontologies facilitate mutual understanding of negotiators on the negotiation issues and alternatives. Our previous papers (Cheung et al. 2002, 2003) discuss inter-dependencies among issues help formulation of efficient negotiation processes, but do not discuss how to elicit such dependencies systematically. In this paper, we further propose a novel methodology for the elicitation of dependencies among negotiation issues from ontologies so that negotiators can focus on tradeoff among inter-related issues, instead of arguing about single issues. A negotiation plan can thus be derived to observe relationships across issues. As a result, negotiators can have a better cognition of their negotiation tasks and the overall e-Negotiation process can be streamlined. Further, this also offers a basis for checking the completeness of issues and alternatives for the negotiation.

The remainder of this paper is organized as follows. Section 2 discusses background and related work. Section 3 presents an e-Negotiation concept model based on which we formulate an methodology of the overall e-Negotiation process. Section 4 describes a motivating example ontology. Section 5 discusses how ontologies are useful in negotiation. Section 6 describes our system architecture and some implementation details. This is followed by discussions and summary in Sections 7.

  1. Background and Related Work

Computer applications were first employed for negotiation support in the 1960s. In the 1980s, computer-based Negotiation Support Systems (NSS) emerged, and they were typically used for training and research in a laboratory environment but rarely used in practice (Delaney et al. 1997). In general, NSS have the following basic features (InterNeg 2000): (1) a formalism to describe the negotiation activity in terms of choices and outcomes, (2) a way to generally characterize the associated outcome probabilities, and (3) a methodology for processing the model to evaluate the expected value of choice alternatives. NSS normally assist negotiators to assess situations, generate and evaluate alternatives, and implement decisions.

NEGOTIATOR (Bui and Shakun 1996) is a classical NSS that seeks to guide negotiators to move their individual goals and judgments to enhance the chance of achieving a common solution. It supports problem adaptation through information sharing, concession making, and problem restructuring or re-framing. However, NEGOTIATOR only helps the negotiators make decisions without explicit support to other entities involved in negotiation. INSPIRE (InterNeg Support Program for Intercultural Research) (Kersten and Noronha 1999) is a web-based prototype for supporting inter-cultural as well as intra-cultural negotiations. It can conduct negotiation anonymously, evaluate the goodness of an offer, and review the history of a negotiation. INSPIRE supports the communication among negotiators by exchanging messages, but it does not directly deal with the interactions among different entities.

Analysis by Forrester (2000) research reveal that 18% of global exports will flow online by 2004 and that cross-border electronic marketplaces (e-Marketplace) trade will surpass $400 billion. Despite technical challenges, e-Marketplaces have emerged to be important trading platforms in recent years. The popularity of e-Marketplaces is largely attributed to their improvement in economic efficiency, reduction in margins between price and costs, and speeding up complicated business deals (Feldman 2000). Although most e-Marketplaces provide adequate support for product and price discovery, their support for negotiation is far from satisfactory (Cho 2001). Negotiation support is mostly limited to simple bidding functions. There is a lack of general support for bargaining like the proposed mechanism in this paper. Despite rapid automation of the other phases of e-commerce transactions, negotiations are often done by using emails or traditional manual communication technologies such as phones or face-to-face meeting, causing serious overhead costs (Cho 2001).

As for negotiation support in e-Marketplaces, Yen et al. (2000) propose an intelligent clearing-house approach that supports both data and textual information about dynamic markets during negotiation, and develops an agent-based prototype Virtual Property Agency. Cho (2001) studies various requirements of negotiation support in e-Marketplace and evaluates a number of popular e-Marketplaces. The work further provides a framework for designing and evaluating a multi-dimensional auction model. However, these studies do not cover different modes of negotiation comprehensively in one complete framework nor negotiation based on e-contracts. Schoop and Quix (2001) present the negotiation process as the exchange of contracts between the parties in an e-Marketplace. The contract contents are presented as extensible semi-structured documents. During the negotiation process, the contract evolves over time until a final agreement has been reached or the negotiation is terminated. All these works do not consider relations among issues of negotiation or other fundamental mechanisms relating to the effectiveness of contract negotiation.

On the other hand, although Semantic Web technologies are maturing, ontology standards are still forming (Fensel et al. 2001). Challenges remain for reusing available ontological information and researchers focus on information integration. In the past years, there are different standardized languages proposed. For example, DARPA Agent Markup Language (DAML, 2004) is a language created by DARPA as an ontology language based upon the Resources Description Framework (RDF, 2004). DAML-S was designed to serve as the basis for representing descriptions of inverses, unambiguous properties, unique properties, lists, restrictions, cardinalities, pairwise disjoint lists, and data types. The Web Ontology Language (OWL, 2004) is an eXtended Markup Language (XML) proposed by the World Wide Web Consortium (W3C) for defining Web ontologies. OWL ontology includes descriptions of classes, properties, and their instances, as well as formal semantics for deriving logical consequences in entailments.

Fig. 1. Conceptual Model of e-Negotiation in UML Class Diagram

Yu and Mylopoulus (1996) consider dependencies of business goals but not down to the practical details of issue dependencies for negotiation. Phelps et al. (2004) suggest the use of ontology for agent-based negotiation with a focus on the heuristics of bidding strategies of auctions instead of negotiation plan for bargaining support. Lee (2000) points out the use of semantic value and ontology servers with the help of context agents to avoid inconsistency in the exchange of offers during e-negotiation, but not further to the formulation of negotiation plans. Ontology negotiation enables users to cooperate in performing an activity based on different ontologies (Bailin and Truszkowski 2001). Modeled on the patterns of successful human communication, ontology negotiation consists of a series of interpretations and clarifications intended to locate common vocabulary and assumptions (Bailin and Lehmann 2003). However, these studies concerned with how consensus of ontologies can be arrived at. They do not consider further how agreed ontologies can help the formulation of negotiation processes in general, as our novel attempt in this paper.

  1. Fig. 1. Conceptual Model of e-Negotiation in UML Class Diagram

    Fig. 2. Ontology Based e-Negotiation Process Model in UML Activity Diagram

    e-Negotiation Process Conceptual Model and our Methodology

Whereas much research has focused on supporting negotiation activities with various information technologies, the proposed approach in this paper concentrates on the e-Negotiation based on ontologies. In this section, we introduce an e-Negotiation concept model and a methodology to support it.

1.1.e-Negotiation Conceptual Model

Fig. 1 presents an e-Negotiation conceptual model in the Unified Modeling Language (UML)(OMG 2001) class diagram based on ontologies. An e-Negotiation is made of up tasks, each of which aims at resolving an issue or a collection of co-related issues. Each of these issues maps to a set of concepts and their relationships based on an agreed ontology. If an issue is mapped into exactly one concept in an ontology, we call this concept a base concept for the negotiation. However, if an issue can break down into several concepts according to an ontology, we call these concepts auxiliary concepts. The agreed ontologies help identify the inter-relationships among the issues and concepts, as well as possible alternatives for issues (as explained in Section 5). An e-Negotiation plan can thus be formulated based on the relationships across these concepts. The plan presents a strategy to drive and organize various tasks in an e-Negotiation. Multiple offers and counter offers are made in a task until a consensus has been reached. A task in an e-Negotiation represents some work that needs to be executed by a set of parties that can be a negotiator, or even a program such as Negotiation Support Systems (NSS) to resolve a specific issue.


Fig. 3. An Ontology for Sale Negotiation of Rubber Gloves in UML Class Diagram

Fig. 2. Ontology Based e-Negotiation Process Model in UML Activity Diagram
Methodology for Ontology based e-Negotiation Process Formulation

Fig. 2 summarizes our proposed methodology for formulation of e-Negotiation processes based on ontologies in the notation of UML activity diagram. This negotiation process is driven by our conceptual for e-negotiation as described in previous sections. Both parties have to participate in each constituting activity of the process, which consists of two major phases: pre-negotiation and negotiation. Although the pre-negotiation phase looks complicated, it is based on the most common and logical way of analyzing the issues with ontologies (as detailed in Section 5). We do not preclude other possible sequences for negotiation plan formulation. In particular, negotiation plans once elicited can be stored in a repository for reuse and adaptation. That means, if negotiators agree, they may just pick a negotiation plan from the repository and starts right away. Therefore, our approach is the most suitable for negotiations in e-marketplaces or B2B e-commerce, where semi-structured negotiations are often repeated and negotiation efficiency is important.

The e-Negotiation process leads either to a successful creation of an agreement or to nothing. Note that only through mutual concessions can the negotiation process reach an agreement. The following steps further elaborate on our methodology.

  1. First of all, the negotiators have to determine the issues to be negotiated.

  2. At the same time, commonly agreed ontologies are selected to help the elicitation of issues.

  3. Issues are related to the concepts in the selected ontologies.

  4. Check all the dependencies of concepts that constitute the issues from the (refined) ontology map. Mutually dependent clusters of concepts determine the indivisible group of negotiation issues that have to be negotiated together so that effective tradeoff can be evaluated.

  5. Check the consistency of all the concepts, issues, and their dependencies (Cheung et al. 2002).

  6. For a consistent plan, we can proceed to elicit the possible alternatives for negotiation; otherwise we have to re-iterate from step 3.

  7. According to the dependencies, we can formulate a precedence graph of the issues and issue groups. Based on the precedence graph, efficient negotiation plan can be determined to exploit the maximum possible concurrency. The progress of a negotiation can be thus visualized.

  8. Negotiators are then ready to make or evaluate offers and counter-offers based on the plan. An agreement is successfully created when all issues have been resolved.

  9. Should new issues arise during the negotiation phase (say, due to incomplete specification), repeat from step 3 to analyze the new issue and its relationships to existing ones. In real-life, the formulation of a negotiation plan may involve several iterations before attaining the consensus of all negotiators. This reflects the inter-relationships among the parameters may not often be captured precisely in one-shot.

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