Simulation of intermediation using rich cognitive agents

Abstract

In trading networks many elements determine the success of the network. They can be economic, social, personal, structural, environmental, etc. In many simulation frameworks only one of these elements is considered. However we argue that it is exactly the interaction between the different types of elements that is interesting when considering the mediation of business processes. Whether a mediator has a right of existence does not just depend on the quality of his service, but also on the social structure between suppliers and users, the communication infrastructure, etc. In this paper we propose an agent-based simulation framework in which this type of situations can be studied and we show an example of its use in a simulation of the house market.

Introduction

Decision-making with regard to business coordination is non-trivial, especially in situations where intermediaries are involved. Much research has been carried out to study intermediation theory and the roles of intermediaries, however, the situations in which intermediaries may play a role, and which functionalities they can then best provide, are not clearly identified. Intermediation can be defined as a business process that lies between and facilitates (adds value to) the points in a value chain. Intermediaries often provide an information-based service rather than a product. Their typical role is to bring multiple buyers and sellers together. Common examples are: stock brokers and travel agents.

The simulation of business processes helps in understanding, analyzing, and designing processes. With the use of simulation the (re)designed processes can be evaluated and compared. Simulation provides estimates of the impact that a business strategy is likely to have on performance, and supports design choices.

Our research is guided by a main assumption: the added-value of an intermediation service is relative and contextual. Relative because the added-value can be different for different business actors as this notion directly depends on their personal concern (e.g. one may value more the quality of a product, the time required to transact, or reduce the risk involved in the transaction). And contextual because it also depends on the environment properties and the social context. To address this issue, we propose a new approach to investigate intermediation using agent-based simulation (ABS). Following the agent-based paradigm, a system is modeled as a collection of autonomous decision-making entities called agents. Each agent individually assesses its situation and makes decisions on the basis of a set of rules. Agents may execute various behaviors appropriate for the system they represent - for example, producing, consuming, or selling. Repetitive competitive interactions between agents are a feature of agent-based modeling, which relies on the power of computers to explore dynamics out of the reach of pure mathematical methods [1] There is a growing interest in the socio-economic science community for the use of ABS to give new insights into several phenomena, which are often difficult to analyze with standard methods [31]. For our current purpose, the motivation to use ABS is twofold.

Firstly, Agent-based modeling provides the means to model the individual properties of business actors, as well as the characteristics of the environment where they act. As such, it is a suitable abstraction that allows us to consider intermediation with a broad range of perspectives embracing a variety of individual, economic, social, and material factors. Secondly, a simulation approach allows us to perform a systematic analysis of the added-value of intermediation by exploring various configurations. This allows us to identify what types of intermediaries are appropriate for what types of situations.

In this paper, we present a multi-agent framework, called Agent-based Business Coordination Lab (ABC Lab), which allows to describe and simulate trading configurations taking into account individual, social, economic and material factors, and making explicit the value in trading. This can help organizations make decisions on whether to choose an intermediary, and on which intermediaries to choose. ABC Lab enables to study the processes involved in mediated business coordination from two different perspectives: that of the stakeholder (whether and which intermediary to choose) and that of the intermediary (which services to provide). ABC Lab is based on the MASQ meta-model [2], [3]. MASQ provides basic constructs to describe a complex social system distinguishing clearly between individuals and the collective structures on the one hand, and between decision-making process and behaviors exhibited on the other hand. The properties of the MASQ meta-model fit well with our major interests, which are on one hand to model explicitly individual, economic, social, and material factors, and on the other hand to design models that are both modular and extensible. In order to demonstrate the capabilities and the usefulness of the ABC Lab, we present an illustrative application which consists of the simulation of a housing rental market.

The paper is organized as follows. Section 2 discusses mediated business coordination, and the role of intermediaries in trading networks. Section 3 introduces the MASQ meta-model. Section 4 presents the architecture and the implementation of the ABC Lab. Section 5 demonstrates the capabilities of ABC Lab in an illustrative scenario of a housing rental market. Finally, Section 6 presents conclusions and future work.