Component-based Specification and Composition of Market Structures
Juho Mäkiö, Ilka Weber
Universität Karlsruhe (TH)
Department of Economics and Business Engineering Information Management and Systems
Englerstr. 14 76131 Karlsruhe, Germany maekioe|weber@iw.uni-karlsruhe.de
Abstract: The design of electronic markets is a time consuming process and often produces unpredictable results. This paper describes a component-based specification of the market microstructure parameters and their composition. In this approach, orthogonal components are defined by rules and algorithms. Composing these components results in a market structure - an element of market space - spanned by the components. The logical connection of the components themselves is based on rules, and has characteristics such as inheritance and overriding. The characteristics of the component-based approach propose a new way of designing electronic markets.
1 Motivation - Market Engineering
A market is a physical or virtual location where price is determined, and buy and sell orders are matched to create trades according to a set of rules that governs the processing of these orders. A central function of a market is the determination of price and conditions of the transaction. Many mechanisms are used to coordinate demand and supply in markets. These mechanisms vary from bilateral to more complex negotiations like multi- attribute negotiations. In [WWW01] the authors argue, that “the task of designing negotiation rules is essentially that of designing auctions”. For example, financial markets employ several types of auctions like continuous double auction for price determination and allocation.
Traditional markets have evolved over centuries. In contrast to traditional markets, electronic marketplaces have been designed and developed in recent years on the back of advances and innovation in information technology. To fulfil the heterogeneous preferences of the market participants, the market structure of any particular electronic marketplace has to be planned and designed properly, indeed, ‘engineered’.
The discipline of Market Engineering [HNW02] aims at systematising theoretical and empirical knowledge in the area of market design. The market structure is a combination of three interdependent perspectives that determine the structure of an electronic market:
market microstructure, market infrastructure and market business structure. The rules, which define an institution, can be subdivided into market microstructure, business
structure, and infrastructure. The market microstructure defines the trading rules, the infrastructure defines rules given by the computerization of markets, and the business structure defines rules for the fee structure of the market. These three perspectives affect the strategic behaviour of the participants and the market outcome. Knowledge about the influence of the structural parameters on the quality of the market helps the market designer construct better markets. Concrete assistance might consist of practical advice, for example, in the form of templates. Such templates include one or more components required by a market. This paper presents an approach for the definition of such components. Section 2 presents related work. Section 3 offers a definition of a market component and the composition of market components to a new market structure. Section 4 presents both the composition of components as a hierarchical structure, and its analogy to inheritance in object-oriented software engineering. The final section concludes with a brief outlook on future work.
2 Related Work
Negotiations are based on explicitly defined rules. These rules are the basis for a well- structured process, defining the interaction of the involved parties and the circumstances under which the interaction takes place. Identification of the basic rules is the key to standardisation and automation of negotiation. First steps towards the identification of the rules and the criteria have been made by Ströbel and Weinhardt [SW03] in the Montreal Taxonomy, which allows a characterisation of various electronic negotiation designs and systems. Wurman, Wellman and Walsh [WWW01] propose a parameterisation of auction designs, suggesting a standardisation of auction rules, or a standard way to describe auction rules. Lomuscio, Wooldridge and Jennings [LWJ03] define negotiation as “…the process by which a group of agents communicate with one and another to try and come to mutually acceptable agreement on some matter.” They identify possible parameters to classify any negotiation mechanism for electronic commerce and identify components of the negotiation space that facilitate automation of negotiation.
Bichler, Kersten and Strecker [BKS03] state that the negotiation process is based on
“explicit rules defining the arena and agenda, and describing permissible decision making and communication activities”. They describe the place where the negotiation takes place (the arena) and how the negotiation is defined (the agenda). The negotiation protocol includes all decision making and communication rules, and specifies the different degree of negotiation structuring. According to Benyoucef and Keller “a formalism is needed which allows for the serialization and visualization of the rules” [BK00]. They argue that the formalis m chosen should be able to describe the negotiation rules and all the details of the negotiation. Furthermore, “it should be possible to automatically convert the description to other existing formalisms” [BK00]. Reeves, Wellman and Grosof [RWG02]
have chosen a declarative specification (Courteous Logic Program) to support the negotiation of business contracts, where the contract process comprises three steps:
discovery of potential contracting partners, negotiation, and execution. The Courteous Logic Program is used to present partial contracts, additional rules about the negotiation
process from buyers and sellers, knowledge about the negotiation process, the negotiation mechanism, and executable contracts [RWG02].
Most of the aspects mentioned above have the automation of the negotiation process, or the support of market design, in common. Here we have to distinguish between two views: a process view and a rule -based view. The process view describes the interaction or transaction process in negotiations between the participants, whereas the rule-based view describes the rules and algorithms of a negotiation or market mechanism. To bring these views together, it can be stated that the definition of rules and algorithms is necessary to define the interactions or transactions of the market participants. On a more abstract level, we can define components - sometimes called building blocks - by the rules and algorithms, and by composing the components, we can construct negotiation mechanisms, or market mechanisms.
This paper focuses on the Montreal Taxonomy [SW03], which provides a framework for a classification of rules for electronic negotiations. This classification supports a structured and methodological electronic negotiation engineering approach, and, therefore
- provides a common set of terms describing electronic negotiations with a well- defined set of classification criteria,
- helps analysing and understanding dimensions of electronic negotiations and their independencies,
- supports the selection of the right electronic negotiation scenario, or an appropriate electronic negotiation system, and
- assists the conceptual design of specific electronic negotiations and supports the abstraction necessary for the development of generic electronic negotiation engines.
In the next section we present a definition of components, as well as the composition of components, and show how a market structure or mechanism can be defined.
3 Components
Central issues of Market Engineering are the design of market mechanisms, the determination of rules and algorithms needed to design a market, and their linking to a market structure. To address these questions, we define components based on market parameters, show how these components can be linked or composed, and determine requirements and characteristics of a composition-function.
In this paper, components are based on rules and algorithms. We define rule as a principle or condition that customarily governs process in a market. Rules are, for example, rules from agents about their preferences and constraints over the market, rules for offer submission, and constraints of offer allocation. According to [Kn73] we understand an algorithm as a computable set of steps to achieve a desired result. Algorithms are, for example, tie breaking algorithms (first in, first out), matching algorithms, and winner- determination algorithms. These criteria are well-defined and clearly assignable to the
transaction phases of a market structure [SW03]. The Montreal Taxonomy gives a comprehensive overview of the rules and algorithms necessary to define a market structure, in the Montreal Taxonomy called criteria.
The design of an electronic negotiation depends on the criteria, relevant for the determination of the participating roles, the process itself, the information revelation, and strategy definition. The Montreal Taxonomy suggests a classification scheme of n independent criteria forming a n-dimensional1 criteria space – the negotiation space:
• roles = {participation, agents, admission, identity, collusion}
• offer submission or offer allocation = {variation, rounds, stages, concurrency}
• offer specification = {attributes, values, relaxation, structure, relation, object}
• offer submission = {sides, position, activity, direction, process, threshold}
• offer analysis = {value, threshold}
• offer matching = {schedule, sorting, evaluation, resolution}
• offer allocation = {distribution, provision, configuration}
• offer acceptance = {commitment}
• information revelation = {communication, transaction, negotiation, transparency, trace,
content, timing}
• strategy definition = {fees, arbitration, ratings}
Based on the Montreal Taxonomy and its classification scheme of electronic negotiations, we propose a more abstract and comprehensive approach that defines components over rules and algorithms, and thus provides a basis for the negotiation process. These criteria are the basis for the definition of components, building a component-based view of negotiation.
The component-based view is an abstract approach to support the automation of negotiations and to configure complex negotiations in an easy manner. Central questions which arise by designing and configuring markets are: what is to be negotiated, who is involved in the transaction process, and how can the order be negotiated. The components are used to design markets and they contain rules and algorithms of the market microstructure. These rules and algorithms are orthogonal (independent). It thus follows that the components defined are also independent.
Definition 3.1 provides a precise description of components.
Definition 3.1.: Components
Given a set of rules R = {R1,R2,….,Rk} with Ri ,i∈{1,…,k}, k mutual independent rules, and a set of algorithms A = {A1,A2,….,Al} with Aj, j∈{1,…,l}, l mutual independent algorithms. We define a component C as a set of rules R and a set of algorithms A that is C = {R, A}.
Defining n components C1,C2,….,Cn mutual different and independent, then the n components form a n-dimensional negotiation space. This n-dimensional negotiation space is achieved by linking the n components.
1 n is the number of all criteria mentioned in the Montreal Taxonomy.
The following gives an example of components illustrated by a special type of negotiation: an English auction. The Montreal Taxonomy calls rules and algorithms
“criteria”.
Example 3.1.:
Consider an English auction with one seller, multiple buyers, multiple round bidding, a winner determination - highest bid, and a payment rule - pay as you bid. According to these rules and algorithms we get the following components:
C1 = {Participation(two-sided)}
C2 = {Agents(n bidders:1 auctioneer)}
C3 = {Rounds(multiple)}
C4 = {Evaluation(ranking)}
C5 = {Distribution(discriminatory)}
C6 = {Provision(offer-dependent)}
Matching the components and the rules of an English auction results in: one seller (C1,C2), multiple buyers (C1,C2), multiple round bidding (C3), winner determination - highest bid (C4), payment rule - pay as you bid (C5,C6).
The question of how a market structure can be composed by these components, what the requirements for composition are, and what characteristics this composition has, are addressed in the following. Thus, we can give an abstract definition for a composition and for a component-based market structure.
Definition 3.2.: Composition
A composition is a logic operation of two or more components.
Given two components C1 and C2, each component defined by a rule and an algorithm, a new component is achieved by the logical combination of C1 and C2, that is C = C1 o C2 = C2 o C1. In this case C1 and C2 are subcomponents of C.
As this composition is a logic operation, we can furthermore define a neutral component N such that: C = C o N = N o C. The composition of the neutral component with a component results in the component itself.
Example 3.2.:
Consider once more an English auction scenario (cf. Example 3.1) under the Montreal Taxonomy criteria. Applying Definition 3.1 and 3.2 results in the following:
C1 = {Component Role } = C11 o C12 o C13 o C14 o C15
C11 = {Participation(two-sided)}
C12 = {Agents(n b idders:1 auctioneer)}
C13 = {Admission(open)}
C14 = {Identity(anonymous)}
C15 = {Collusion(prohibited)}
C2 = {Component Process-overall rules} = C21 o C22 o C23 o C24
C21 = {Variation(fixed)}
C22 = {Rounds(multiple)}
C23 = {Stages(single)}
C24 = {Concurrency(prohibit)}
Both C1 and C2 are a composition of rule-based components (subcomponents). The Component Role C1 as well as the Component Process – overall rules C2 are criteria taken from the Montreal Taxonomy and define criteria of the market microstructure.
Having introduced components and the composition as logic operations we will define how a market can be composed by linking components.
Definition 3.3.: Component-based market structure
Given a set of rules R, a set of algorithms A, and n components Ci = {Ri, Ai} for i = 1,…,n with Ri⊆R a subset of R and Ai⊆A a subset of A we define a market structure based on components as a composition of n Components, that is a component-based market structure
M = C1 o C2 o …. o Cn = {R1, A1} o { R2, A2} o …. o {Rn, An}.
By defining the composition of components to a market structure, a recursive definition is implicit: each component can be defined by other components. This can be formulated in the following way:
Given n components C1,C2,….,Cn . The composition of these n components: M = C1 o C2
o …. o Cn results in the market structure M.
Fig. 3.1: Market structure components
Figure 3.1 illustrates a composition for n=3. The market structure M is the result of linking the three components C1,C2 and C3. Each of these n Components is a combination or composition of some subcomponents (r, s, t∈N):
C1 = C11 o C12 o …. o C1r
C2 = C21 o C22 o …. o C2s
…
Cn = Cn1 o Cn2 o …. o Cnt
C1
C2
C3
C4
M C1
C2
C3
C4
M Composition of components M=C1o C2o C3
C1
C2
C3
C4
M C1
C2
C3
C4
M Composition of components M=C1o C2o C3
With each component Cab = {Rab, Aab} for all a,b index of the subset of rules and subset of algorithms chosen.
Consider the example of the English auction (cf. Example 3.1 and 3.2). Firstly, we have depicted rule based components of the English auction, and secondly, the linkage of components. Linking all relevant components supplies a complete market structure, in this case an English auction.
4 Composition of Components
The previous section defines components and the composition of components. This section describes implications of the composition of components, for example, inheritance and overriding. In addition, a linking automata, that joins components to new components or market models, is described.
4.1 Components as a Tree
A graph consists of nodes and arcs whose elements are (un-)ordered pairs of distinct nodes. A tree is a graph without any cycles. The root node of the tree is an ancestor of all the other nodes, and each node has at least one adjacent node. Components linked to a market structure build a hierarchical organisation, in which one component is considered to be an ancestor of other components. This hierarchical organisation can be visualised as a tree, where each node represents a component and each arc defines a link between two nodes. The path from the root node to an other node defines a composition of components in a hierarchical order. The hierarchy reflects the characteristics of inheritance describ ed in the following section.
4.2 Inheritance of the Components, Overriding of Rules
From the composition of components arises questions such as:
1. What is the benefit of composition?,
2. What happens, when composing two components with common subcomponents?, and
3. Can one component be composed from multiple components?
The first question leads to inheritance of components and to the question about the handling of inheritance. In computer science's object-oriented programming theory, inheritance is a programming language feature which allows one class or object to incorporate data or behavioural facets of another. In other words, inheritance is the mechanism which allows propagation of property values from parent elements to their children, which means that the parent's element will automatically be used unless otherwise specified.
Fig. 4.1: Inheritance and overriding of components
Common reasons for using inheritance are to
a) create specialisations of existing classes or objects, b) provide additional data or behavioural features, or c) allow a new class to reuse an existing code.
The second question is a consequence of the first question and of the inheritance, leading to overriding of the components. The third question leads to multiple inherit ance and its manageability. Multiple inheritance means that an object inherits behaviours and features from more than one super class (this can cause confusing situations, hence debate about whether or not its benefits outweigh its risks) and it means that one subclass can have more than one super class. This enables the subclass to inherit properties of more than one super class and to “merge” their properties. Problematic with the multiple inheritance is to decide from which parent the subclass inherits, when both of the parents have properties of similar types.
Figure 4.1 shows the inheritance and the overriding of components. Starting point is Component C1, which functions as a root in the component tree. Component C1 contains two subcomponents C11 and C12. The insertion of the component C2 to C1 generates a new component C1 o C2 with subcomponents C11, C12 and C2. Components C1 o C2 o C4 and C1
o C2o C3 are created analogously. Components C1 o C2o C4 and C1 o C2o C3 differ from each other in respect of components C4 and C3. Component C5 overrides component C12 in the component C1. All new components having C1 o C2 o C3o C5 as a parent, all become properties from it. In contrast, components under C1 o C2 o C3 still have the subcomponent C12 from component C1.
An example clarifies the situation described above (cf. Figure 4.1). Given component C1 with subcomponents C11 = offer matching will be executed continuously and C12 = the
Component C1 ¡C2¡C3¡C5
Component C1 ¡C2¡C4
C11
C2
C3 C4
C12 C1
C5= C‘12
C’12 overrides the subcomponent C12
Component C1 ¡C2¡C3¡C5
Component C1 ¡C2¡C4
C11
C2
C3 C4
C12 C1
C5= C‘12
C’12 overrides the subcomponent C12
offer has to provide a higher value than 5 monetary units (threshold). The components C2 and C3 are defined as follows:
C2 := only the agents involved in the actual process can access the status information and
C3 := only sellers are allowed to submit offers within the process.
Component C5 overrides C12 and defines that the offers have to provide a higher value than 10 monetary units.
Example 4.1.:
Consider three auction designs: an English auction, the eBay auction and the Amazon auction (cf. [RWG02]). The English auction represents the general type of the eBay and Amazon style auctions. This leads to a hierarchical order: the English auction is an ancestor of the eBay and the Amazon auction. Changing the closing rule in the eBay auction provides the Amazon auction. Both auction designs are identical – only differing in the closing rule. In other words, the composition components build a hierarchical structure where the English auction is an ancestor of the eBay auction and the eBay auction an ancestor of the Amazon auction: all characteristics of the eBay auctions are inherent to the Amazon auction except the closing rule.
Fig. 4.2: Inheritance based on components
Figure 4.2 depicts the inheritance hierarchy and the tree structure of the three auction designs. The standard English auction M1 as a composition of the components C1, C2, C3 is a general type of both auction designs – the eBay auction and the Amazon auction.
Linking M1 with component C5 we get the eBay auction. The Amazon auction M3 is a composition of the eBay auction M2 and component C6 – the new closing rule of the Amazon auction, which overrides the closing rule of the eBay auction. Due to this, the eBay auction inherits all characteristics of the English auction and the Amazon auction inherits all characteristics of the English auction and the eBay auction.
M1 = English Auction
M2 = eBay
M3 = Amazon M1
M2
M3
C1
C2
C3 C4
C5
C6
C7
M2
M3 M1 M1 = English Auction
M2 = eBay
M3 = Amazon M1
M2
M3
C1
C2
C3 C4
C5
C6
C7
M2
M3 M1
5 Summary and Outlook
Our future work towards component orientred building of market structures will concentrate on both the technical and economical conception and the realisation. Our starting point in future research has the following background: a given platform including several synchronously operating markets and orders that can be placed into more than one of these markets synchronously. This scenario raises issues such as how markets can be concatenated?, which rules are relevant for the market concatenation?, does any classification to dictate exist?, which components cannot be composed into one market model? and what do the components look like?.
This paper presents the configuration and creation of electronic markets through composition of orthogonal components. It defines components as a set of rules and algorithms that can be composed by a logic operation. The composition of orthogonal components can be used for market composition. In such instances, the composition operation must be extended to contain rules to define the correct order of markets valid at any one time.
Market composition is relevant to market design, where complex market structures are created. We believe that our component oriented approach provides an effective manner to construct market structures with predictable results and provides practical solutions to the mentioned issues.
References
[BK00] Benyoucef, M. and R.K. Keller, “An Evaluation of Formalisms for Negotiations in E- Commerce”, in: Proceedings of the Workshop on Distributed Communities on the Web, Quebec City, QC, Canada, Springer, LNCS 1830, pp. 45-54, (2000).
[BKS03] Bichler, M., Kersten, G., and S. Strecker, “Towards a Structured Design of Electronic Negotiations”, Group Decision and Negotiation 12(4), pp. 311-335, (2003)
[HNW02] Holtmann, C., Neumann, D., and Ch. Weinhardt, “Market Engineering – An interdisciplinary Approach”, working paper, University of Karlsruhe, Karlsruhe, (2002).
[Kn73] Knuth D. E., The Art of Computer Programming I: Fundamental Algorithms. Addison- Wesley, Reading, MA, 2. (1973).
[LWJ03] Lomuscio, A.R., Wooldridge, M., and N.R. Jennings, “A Classification Scheme for Negotiation in Electronic Commerce”, International Journal of Group Decision and Negotiation, vol. 12, no. 1, pp. 31-56, (2003).
[RWG02] Reeves, D. M., Wellman, M. P., and B. N. Grosof, “Automated negotiation from Declarative Contract Descriptions”, Computational Intelligence, vol. 18, pp. 482-500, (2002).
[SW03] Ströbel, M. and Ch. Weinhardt, “The Montreal Taxonomy for Electronic Negotiations”, Journal of Group Decision and Negotiation, 12(2), pp. 143-164, (2003).
[WWW01] Wurman, P.R., Wellman, M.P., and W.E. Walsh, “A Parametrization of the Auction Design Space”, Games and Economic Behavior, vol. 35, no. 1-2, pp. 304-338, (2001).
