Presentation on theme: "Chapter 2 The Role of Computer Science in Electronic Commerce."— Presentation transcript:
Chapter 2 The Role of Computer Science in Electronic Commerce
- 2 - (c) 2000 Dr. Ralph Bergmann and Prof. Dr. Michael M. Richter, Universität Kaiserslautern Recommended References Knowledge Management: –W. Wilke: Knowledge Management for Intelligent Sales Support in Electronic Commerce. DISKI 213, infix Verlag 1999. Computer science issues not discussed in this course: –Th. Härder, E.Rahm: Datenbanksysteme. Springer Verlag 1999. –H. Loeser: Techniken für Web-basierte Datenbankanwendungen. Informatik - Forschung und Entwicklung 13:4, 1998, p. 196-216
- 3 - (c) 2000 Dr. Ralph Bergmann and Prof. Dr. Michael M. Richter, Universität Kaiserslautern The Task In this chapter we will select some basic problems from chapter 1 and interprete them from the view of computer science. For this purpose, the problems have to be investigated in some more detail. To translate them into computer science problems means ultimately to define appropriate data structures, to organize the data flow, to create the necessary algorithms and to embed this into a systematic scenario governed by software engineering techniques. In this chapter we will indicate the main patterns for this.
- 4 - (c) 2000 Dr. Ralph Bergmann and Prof. Dr. Michael M. Richter, Universität Kaiserslautern Wide Variety In electronic commerce computers are ultimately intended to carry out all activities in the sales circle. Several activities are already standard in classical sale, e.g.the use of data bases for products. Others require (sometimes difficult but not knowledge intensive) techniques. Knowledge intensive means: Actually, at problem solving time (run time) there is access to knowledge necessary. In this course we put emphasis on those activities which „require intelligence“ and make actual use of knowledge.
- 5 - (c) 2000 Dr. Ralph Bergmann and Prof. Dr. Michael M. Richter, Universität Kaiserslautern Customer Service and Transactions A basic requirement of customer service is that demands are performed as requested: –If products are ordered –If hotel rooms are booked –if payment is done –... Such activities have to be carried out in a precise and efficient way. Basic techniques of computer science have been adapted and extended for such purposes like data base transactions, network technology etc. This will, however, not be a part of this course.
- 6 - (c) 2000 Dr. Ralph Bergmann and Prof. Dr. Michael M. Richter, Universität Kaiserslautern Classical versus Electronic Commerce (1) There are two major sources for new types of difficulties in electronic commerce: In a single sale the informal discussions have to be formalized, e.g. dialogues have to be organized etc. In the overall scenario the customer can be present in many shops and can correlate his activities in a new way (see chapter 14). This requires new search methods and negotiation strategies which should be supported by the computer. The change of the roles from customer to supplier and vice versa is now much faster and demands again computer support.
- 7 - (c) 2000 Dr. Ralph Bergmann and Prof. Dr. Michael M. Richter, Universität Kaiserslautern Classical versus Electronic Commerce (2) There are several new aspects arising in electronic commerce: –Activities previously done by humans has no to be performed by computers: This is a new demand on computer technology –The access to knowledge is improved: The software agent has a better performance than the human agent –Not existing products can be visualized –The principle “an object is at some time at only an place” is no longer valid: A customer can be in different shops at the same time, a supplier can serve different customers at the same time. –The presentation of a product, a sales person or a sales location can be adapted to the customer. –The customer can have access to software agents at any time from any locations.
- 8 - (c) 2000 Dr. Ralph Bergmann and Prof. Dr. Michael M. Richter, Universität Kaiserslautern The Vision “On the Internet companies only have computers representing them. They should better be intelligent computers!” Chuck Williams, San Francisco Examiner ”The next wave of economic growth is going to come from the knowledge-based business.” Davis & Botkin, Harvard Business Review
- 9 - (c) 2000 Dr. Ralph Bergmann and Prof. Dr. Michael M. Richter, Universität Kaiserslautern Overall Support Computers techniques are used whenever information flows in the company key words: –Customer Service –Accounting –Logistics –Workflow management systems –Public relations and advertising –... –Information is stored in and moved between data bases
- 10 - (c) 2000 Dr. Ralph Bergmann and Prof. Dr. Michael M. Richter, Universität Kaiserslautern –Modeling of products (see chapter 9) –Modeling of customers (see chapter 10) –Modeling of general relations between them (see chapter 10) –Providing the possibility of a dialogue with the customer (see chapter 11) –Providing after sales support (see chapter 12) Customer Relationship Management Knowledge intensive tasks:
- 11 - (c) 2000 Dr. Ralph Bergmann and Prof. Dr. Michael M. Richter, Universität Kaiserslautern Knowledge is about something Knowledge is not only a about a certain area Knowledge is also about a certain task This means: –Knowledge about what ? –Knowledge about how ? The latter is far more difficult to answer and therefore an important task for knowledge management
- 12 - (c) 2000 Dr. Ralph Bergmann and Prof. Dr. Michael M. Richter, Universität Kaiserslautern Knowledge as a Valuable Good A company owns many values: Material Contracts, rights Real estate Experts etc. and Knowledge It is important to define concepts which make it possible to quantify the value of knowledge. This is a precondition for the trade of knowledge (see chapter 15).
- 13 - (c) 2000 Dr. Ralph Bergmann and Prof. Dr. Michael M. Richter, Universität Kaiserslautern Language Product Expertise Client Type Wishes Requirements Preferences Structure Properties Applicaion Classification Availability Faults Competive Products Pricing Knowledge about... Clients Selling Negotiation Recommendation Information mediation Strategies Products
- 14 - (c) 2000 Dr. Ralph Bergmann and Prof. Dr. Michael M. Richter, Universität Kaiserslautern Tasks for Knowledge Representation There are many ways to formally represent knowledge (see chapters 4 and 5). This includes exact as well as approximately exact knowledge. Knowledge has to be represented in such a way that it can be retrieved whenever necessary (see chapters 7 and 15). It is of particular interest when data base techniques do not suffice. In changing environments knowledge has to be updated and maintained (see chapter 15). Knowledge has to be acquired (see chapter 13)
- 15 - (c) 2000 Dr. Ralph Bergmann and Prof. Dr. Michael M. Richter, Universität Kaiserslautern Representation of Real World Things (1) When we deal with things of the real world (like products to sell) we have to represent them. This can be done in two ways: I) Things represent themselves (or an identical copy is used); this is the case in most traditional shops. II) Representation and original thing differ. This is in particular in e-Commerce the case. The difference can be more or less large (e.g. a picture, a verbal description or simply a code). Any representation needs a certain language for which syntax and semantics have to be defined.
- 16 - (c) 2000 Dr. Ralph Bergmann and Prof. Dr. Michael M. Richter, Universität Kaiserslautern Representation of Real World Things (2) An item of the real world is usually of an infinite complexity. Any representation can only partially grasp this The specific aspects represented depend on the problems to be solved, e.g. in a catalogue. The representation mapping has itself an informal character because it relates an infomal item to a formal one. Sometimes, however, the represented thing does not have a formal semantics because it is interpreted by humans.
- 17 - (c) 2000 Dr. Ralph Bergmann and Prof. Dr. Michael M. Richter, Universität Kaiserslautern Representation of Real World Things (3) Pictures or videos are the most important examples which are directly interpreted by humans. In classical sale only these representation originate from really existing objects. Visualization makes it possible to generate images from from descriptions: Potentially existing objects can be shown: –Houses, rooms with different furniture, dresses and suits etc. It is important to integrate visualization into into the sales process, in particular into the sales dialogue (see chapter 11).
- 18 - (c) 2000 Dr. Ralph Bergmann and Prof. Dr. Michael M. Richter, Universität Kaiserslautern Representation of Real World Things (4) Customer and supplier usually prefer different types of representations (see chapter 9): –Customer prefer often intuitive understandable presentations –Supplier prefer formal representations suitable for data processing purposes. For this reason often two representations exist. The problem is to translate between them. If the customer representation is very informal then this translation is often not unique. One purpose of translating a user description of a product is to generate an SQL-query in order to retrieve the product (see chapter 7).
- 19 - (c) 2000 Dr. Ralph Bergmann and Prof. Dr. Michael M. Richter, Universität Kaiserslautern Representation of Real World Things (5) The difficulties involved in the transformation of some self represented item is due to the fact that it refers to the use of the item in the external world. Examples: –Images: Require an understanding of the scenario represented in the image. –Texts: Require an understanding of the terms occurring in the text and the needed background knowledge. –Etc.
- 20 - (c) 2000 Dr. Ralph Bergmann and Prof. Dr. Michael M. Richter, Universität Kaiserslautern Representation of Real World Things (6 ) Visualization is a means to communicate between human and software agents. This is a complex problem. The purpose of visualization is to communicate information between software agents and human agents. A human may have more direct contact to an image than a text with respect to the information of interest. In a sales context there is the requirement not only to represent objects which are given but to represent images from the view of possible customer demands, i.e., to represents a picture from a textual description in a specific way: –how can I see this building at night ? –what is a good place for this furniture ?
- 21 - (c) 2000 Dr. Ralph Bergmann and Prof. Dr. Michael M. Richter, Universität Kaiserslautern Databases and Knowledge Bases (1) Databases have been with us for decades and proved to store data successfully. The knowledge connected with the data was only in the heads of people. Knowledge bases have proved to be useful for storing logic-oriented knowledge. The knowledge had to be understood by the user because part of the knowledge was implicitly encoded.
- 22 - (c) 2000 Dr. Ralph Bergmann and Prof. Dr. Michael M. Richter, Universität Kaiserslautern Databases and Knowledge Bases (2) Some knowledge of interest is a logical consequence of the knowledge and data stored in the base For this purpose deductive databases and knowledge based systems have been developed To such a system one can give a query and the system gives an answer using its inference engine All these engines are based on fragments of classical predicate logic (e.g. PROLOG)
- 23 - (c) 2000 Dr. Ralph Bergmann and Prof. Dr. Michael M. Richter, Universität Kaiserslautern Databases and Knowledge Bases (3) The main problem is not only to store knowledge but to retrieve it. To retrieve data or knowledge one has to have knowledge in order to know exactly which queries to rise. In particular, classical systems were not able to give a good answer if the precise answer to the question was not available. Data and knowledge bases were usually stand alone systems and not incorporated in the rest of the company
- 24 - (c) 2000 Dr. Ralph Bergmann and Prof. Dr. Michael M. Richter, Universität Kaiserslautern Search and Retrieval With search we associate that there are no direct retrieval functions available and we may have an open world. A typical example is internet search. In a search process retrieval functions can be called. Retrieval has always implemented retrieval operators. The retrieval can split into two parts: –A first method which generates an exact query (e.g. an SQL- query). This is applied when the object of interest is not exactly described. –The exact call to the data base. The search steps and the query generation require knowledge in each actual situation.
- 25 - (c) 2000 Dr. Ralph Bergmann and Prof. Dr. Michael M. Richter, Universität Kaiserslautern Knowledge Gaps Knowledge is usually incomplete in complex situations. A knowledge gap can mean: Some knowledge entry is simply missing or (worse) incorrectly stated. Knowledge gaps occur dynamically due to a changing context. To deal with knowledge gaps is a major task for knowledge acquisition and knowledge management (see chapters 13 and 15)
- 26 - (c) 2000 Dr. Ralph Bergmann and Prof. Dr. Michael M. Richter, Universität Kaiserslautern Knowledge Gap: Example Client Strategies Supplier/ Product Gap
- 27 - (c) 2000 Dr. Ralph Bergmann and Prof. Dr. Michael M. Richter, Universität Kaiserslautern Knowledge Gaps and Maintenance How to characterize knowledge gaps ? They can occur when knowledge is –simply missing –in principle present but not (sufficiently easy) accessible –not or not sufficiently well understood –not adequately presented –out of date –Incorrectly stated
- 28 - (c) 2000 Dr. Ralph Bergmann and Prof. Dr. Michael M. Richter, Universität Kaiserslautern Indicators for Knowledge Gaps (1) Knowledge gaps usually do not say on their own initiative: Look at me, I am a gap! Whether a gap can be realized by the agent who carries out a certain activity depends on – the situation – the experience of the agent If e.g. some action requires the value of some parameter and the agent knows this fact then it is easy to realize that this value is missing and the agent can send a corresponding query. In such situations we have direct indicators for gaps. In many situations, however, there are only indirect indicators for the gaps.
- 29 - (c) 2000 Dr. Ralph Bergmann and Prof. Dr. Michael M. Richter, Universität Kaiserslautern Indicators for Knowledge Gaps (2) Indirect indicators for knowledge gaps are: Actions which insufficiently well performed: – Missing expertise if needed – Expensive errors, missed opportunities Changes in the context and in the environment: – New products, aging products – New technologies, aging technologies – New customers and business partners with new interests – Changes in organization and management – Changes in the general opinion and tast Some of such changes occur at once, others continuously.
- 30 - (c) 2000 Dr. Ralph Bergmann and Prof. Dr. Michael M. Richter, Universität Kaiserslautern Dynamic and Maintenance Knowledge gaps have a dynamic character –They can occur continuously –They are not anounced and often not recognized –They will slowly lead to low quality in every respect Requirements for knowledge maintenance : –Has to be a coninuous process –Has to include a control function –Has to be correlated with all parts of the management
- 31 - (c) 2000 Dr. Ralph Bergmann and Prof. Dr. Michael M. Richter, Universität Kaiserslautern Knowledge has for each task to be accessible: for the right persons at the right time at the right place in the needed format Missing Knowledge creates errors Too much knowledge confuses Organizing the Use of Knowledge The access to the knowledge is a search process which again requires knowledge and which has to be organized
- 32 - (c) 2000 Dr. Ralph Bergmann and Prof. Dr. Michael M. Richter, Universität Kaiserslautern Knowledge Management (KM) Intelligent activities require knowledge The knowledge has to be managed: –acquired –stored –structured –maintained –made available These activities have to be interleaved with all other activities in the company
- 33 - (c) 2000 Dr. Ralph Bergmann and Prof. Dr. Michael M. Richter, Universität Kaiserslautern Quality Management Quality conditions are defined as constraints (see chapter 4) Hard constraints: Have to be satisfied in any case Weak constraints: should be satisfied but not under all circumstances. Weak constraints have degrees: –in hierarchical orderings –by point valuations –in fuzzy degrees This leads to an optimization task: Weak constraints should be satisfied in an optimal way Quality management is a part KM (see chapter 15)
- 34 - (c) 2000 Dr. Ralph Bergmann and Prof. Dr. Michael M. Richter, Universität Kaiserslautern Customer Service in E-Commerce The advantages of e-commerce are obvious: –world-wide and 24-hours availability etc These advantages have been achieved using machines Customer service, however, was always a domain of humans The problem is now to program machines in such a way that they can perform such a service too
- 35 - (c) 2000 Dr. Ralph Bergmann and Prof. Dr. Michael M. Richter, Universität Kaiserslautern The Initial Situation A customer has some demand. For the realization he needs support, resources, personell etc. For this purpose certain decisions have to be made What have I to do know ??
- 36 - (c) 2000 Dr. Ralph Bergmann and Prof. Dr. Michael M. Richter, Universität Kaiserslautern No unique answers Customer demands usually do not have unique answers –financial advises cover a wide range –there is now unique home or best hotel –several PC‘s may be suitable Even if there is a unique product description this product may not be available (St. Moritz is sold out). In this case one needs an offer which satisfies customer wishes in an optimal way although it is not exactly what the customer asked for.
- 37 - (c) 2000 Dr. Ralph Bergmann and Prof. Dr. Michael M. Richter, Universität Kaiserslautern CRM and Knowledge Customer service includes as a central element helping the customer to make good decisions Therefore customer service has to employ the right information and adequate knowledge The knowledge has to connect general properties of the decision with personal aspects of the customer Knowledge acquisition is a difficult task Knowledge management requires constant updating
- 38 - (c) 2000 Dr. Ralph Bergmann and Prof. Dr. Michael M. Richter, Universität Kaiserslautern A Fundamental Problem We demand that machines behave exactly as they are told If humans behave exactly as told by certain rules this will sooner or later be a way into a chaos Is it possible that both aspects can be combined?
- 39 - (c) 2000 Dr. Ralph Bergmann and Prof. Dr. Michael M. Richter, Universität Kaiserslautern The First Idea: Introduction of Inexactness If exactness cannot be achieved anyway one should not try to obtain it: We do not offer exactly the product for which the customer asked (the PC, the home, the journey...) but rather one which is useful for him with a high degree of certainty. The difficulty: Strictly speaking, we commit a mistake. But do mistakes not directly lead into a chaos?
- 40 - (c) 2000 Dr. Ralph Bergmann and Prof. Dr. Michael M. Richter, Universität Kaiserslautern The Second Idea: Controlled Inexactness First control principle: Estimate the degree of inexactness and make a decision whether it can be tolerated (i.e., find a measure of inexactness) Second control principle: Offer methods for improving solutions (adaptation methods) Example 1: As a replacement for vacations in St. Moritz we offer Davos or Calgary. Example 2: We add more rooms to your house by building a second floor etc. This is done because these are believed to best available approximations to the ideal answer.
- 41 - (c) 2000 Dr. Ralph Bergmann and Prof. Dr. Michael M. Richter, Universität Kaiserslautern From Truth to Approximation The basic idea to enable computers in order to perform inexact but useful reasoning is to give up the simple true-false principle and to replace it by the more complex scenario of approximation. Traditionally, approximation techniques have been developed mainly for numerical problems. In this course we will introduce approximation methods also in symbolic domain and demonstrate how they can be applied for the problems arising in e-commerce. An example is the search for the product which satisfies best customers demands: This search is an approximation process.
- 42 - (c) 2000 Dr. Ralph Bergmann and Prof. Dr. Michael M. Richter, Universität Kaiserslautern Case-Based Reasoning Several techniques have been developed for dealing with inexact knowledge like probability theory, evidence calculus, fuzzy sets and others. In this course we will apply techniques arising from Case-Based Reasoning (CBR) as an appropriate approach (see chapters 3 and 5). This realizes in particular the idea of approximate truth. The central notion in CBR is similarity (see chapter 6) and a central technique is similarity-based retrieval which uses inexact instead of exact reasoning (see chapter 7).
- 43 - (c) 2000 Dr. Ralph Bergmann and Prof. Dr. Michael M. Richter, Universität Kaiserslautern KM, E - Commerce and CRM Knowledge Management is concerned with the whole company. E-Commerce requires that parts of KM are formalized and automated. The weak point of E-Commerce is Customer Relationship Management because this requires: –Making informal aspects accessible to the computer –Formalizing the knowledge used to satisfy customer demands in an optimal way, i.e. increasing the tasks of KM.
- 44 - (c) 2000 Dr. Ralph Bergmann and Prof. Dr. Michael M. Richter, Universität Kaiserslautern Again: Processes (1) The sales cycle presents (iterative) processes (customers and suppliers ones) with several subprocesses This process has to be planned and executed Planning and execution are interleaved. The planning has to be flexible in order to react on changing demands. The sales process has to compatible with other processes of the company. Planning and execution have to be supported by knowledge in an optimal way. The success of processes has to be measured, evaluated and improved if necessary.
- 45 - (c) 2000 Dr. Ralph Bergmann and Prof. Dr. Michael M. Richter, Universität Kaiserslautern Again: Processes (2) Therefore the management and knowledge management of e-commerce processes is embedded into general engineering and business processes (see chapter 15). A characteristics is that we deal with socio-technical processes where machines as well as humans participate. The supporting software has to be generated and updated according to established software engineering techniques and principles. See chapter 15.
- 46 - (c) 2000 Dr. Ralph Bergmann and Prof. Dr. Michael M. Richter, Universität Kaiserslautern Processes, Knowledge and Search Because the knowledge is supposed to improve the quality of actions the knowledge has to be attached to the actions described in the process model. The choice of the next proper action and the determination of the specific values of the parameters of the action is a search process. This search is often knowledge intensive and the available knowledge should support the search. See chapters 14 and 15.
- 47 - (c) 2000 Dr. Ralph Bergmann and Prof. Dr. Michael M. Richter, Universität Kaiserslautern Summary In traditional sales several activities have already been performed by computers. In e-c new activities have been arosen, partially due to the fact that humans are replaced by computers and partially due to new possibilities in the internet. The two main challenges are: –The acquisition, management and explicit use of knowledge; –The proper application and use of inexact reasoning. In addition, the representation of all objects of interest and the access to them has to be realized. The methods of computer science in general and knowledge management in particular are guided by the steps in the economic models of chapter 1.