Knowledge Management in an E-commerce System

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Knowledge Management in an E-commerce System 4e-commerce system this is more feasible, but in order to do it the knowledge management processes must be madeas transparent as possible, so that we may offer the improved service that accompanies increased knowledge of thetarget market without scaring the customer by acting like a “big brother” (also see discussion of personalization in[10]).6. In customer-oriented business we are interested not only in what the customer has purchased, but also why shepurchased it, as this knowledge is incredibly useful in “personalizing” the user’s online shopping experience andsuggesting related products. This situation is usually only possible in very small regional stores, in which the ownerknows most of the customers and can readily learn or deduce the reasons for a particular purchase (if a couple isbuying a new washer because they are expecting a baby, the store owner can suggest a number of additionalproducts that should be purchased as well). This capability is not apparent in large chain stores. While it is possiblethat a skilled salesperson can learn something in conversations with the customer, these contacts are usually notenough. On the large scale it is only through extensive knowledge that we may attempt to make educated guesses asto why a purchase decision has been made. Also, because the user is identified to the system (e.g. by a login name)all of his actions may be related, versus the disconnected and mostly anonymous nature of real-life transactions.While this is a very positive development, it poses an important challenge to knowledge management, as the correctknowledge about each customer has to be acquired to provide her with the small store feeling (see [21]).2.3 Differences for the systemFinally, we have to address the differences between commerce and e-commerce that occur inside of the system (here thesystem is understood very broadly and means any regular commercial entity or any e-commerce system).1. There exist a number of techniques and tools that were developed to help manage knowledge in traditionalenterprises, in which knowledge embodied in workers is the primary focus [32]. In the human enterprise we areparticularly interested in extracting this knowledge, and the process of exchange of information between knowledgebearers. In e-commerce we have a much different situation, because most knowledge management occurs “inside”the IT infrastructure and therefore the human factor is minimal. This makes knowledge management difficult, as allof it has to happen in an almost-automatic fashion. At the same time, due to the lack of human involvement, one ofthe more important problems of knowledge management systems (human- and paper-based as well as electronic),the problem of knowledge sharing, does not exist (computers do not mind sharing knowledge with other computers).2. Automatic recording of data related to the functioning of the e-commerce system is easily available; no traditionalsystem has such stores of data readily available. It should be obvious that this collected data will become the crucialinput to the knowledge management process, once it is transformed into information and then into knowledge.3. The need for inventory management is different. While new approaches are starting to take effect among large chainretailers, typically what is “visible” to the customer is what available and it is “impossible” to oversell. In electroniccommerce, if a large number of transactions occur simultaneously, special care must be taken to only sell goods thatare available. On the other hand, since information about the inventory levels is constantly available sales strategiesmay be dynamically adjusted. This leads us back to knowledge management. Knowledge employed in inventorymanagement is directly related to knowledge-driven sale strategies, knowledge used in commodity searches,negotiations with suppliers of a given commodity etc.4. Finally, e-commerce systems are characterized by an almost unlimited and immediately accessible data aboutproducts and services. Therefore an important task of knowledge management is the ability to cope with large andcontinuous flow of information.3. KNOWLEDGE CREATION: INFORMATION INTO KNOWLEDGEKnowledge management experts describe knowledge creation as the continuous process of transforming tacit knowledgeinto explicit knowledge, that which can be expressed with a formal representation [5, 31]. This definition usually refers toknowledge acquisition from human experts. On a large scale, the difficulty of gathering knowledge from experts (oftenreferred to as the bottleneck of the knowledge system) has necessitated the use of alternative, less troublesome sources ofInternational Conference on Electronic Commerce Research (ICECR-5)
Knowledge Management in an E-commerce System 5knowledge. As the amount of data stored in local databases and other electronic repositories continues to increase,techniques for transforming this data into information and then knowledge become more important. The use of thesetechniques requires much less human input than traditional expert knowledge extraction. In the ideal situation, the expertsare given only the task of verifying the generated knowledge and controlling the acquisition process. In our approach wewill follow the general structure of knowledge management function, which consists of knowledge creation, transfer andstorage, and application. We will therefore start from discussing the sources of data that is transformed into informationand then into knowledge (while this is a mental shortcut, we will name these data sources: sources of knowledge).Overall, in the context of an e-commerce system we consider three primary sources of knowledge: users of the system,environment, and experts. We will now address each of these sources in some detail and follow with a brief overview ofknowledge acquisition techniques and mechanisms.3.1 Users of the systemBecause the process of gathering data from sources within the e-commerce system can be automated and operatecontinuously, various types of electronic data are the most relied-upon original sources of knowledge for the system.These include the more transparent data sources related to customers such originating IP logs, cookies stored acrosssessions and verbose information logs generated by the system during interaction with users (which incorporateinformation about actions, as well as non-actions of the client; the fact that the user did not select a given pop-up-banneradmay be as important as the fact that she has selected a given photo camera). In addition, there are several directmethods of extracting information from the user, such as questionnaires [9, 21]. From this information about the customerknowledge can also be extracted about individual and group behavior, about customs, inclination, etc. We also need totake into account that the system is an intermediary between suppliers and customers. In this way one can argue thatwhile to relationship is not completely symmetric, suppliers constitute an additional group of users of the system. Makingthis, slightly controversial assumption, we can conceptualize data collected about suppliers in a similar way to that of thedata collected from the customers. Here the data concerns the negotiation processes (auctions), commodity characteristics(prices, amounts, time), data about the quality of delivered commodities (obtained from customers and matched withsuppliers), number of product returns, reaction time to our requests etc. From this data we gather the knowledge how toconduct the negotiation, with whom, on what conditions, which products to eliminate or incorporate.3.2 The environmentWhile the customers and the suppliers are definitively part of the environment that the system operates in (see [9] formore details), we have separated them due to the fact that they provide a very specific and immediately applicable type ofknowledge about the suppliers to the system and the customers (including potential customers) of the system itself. Theenvironment is the world in which the customers and the suppliers and the system operate and that influences theiractions. This influence goes directly to the suppliers and customers and is mediated through them as it influences thesystem. In the ideal situation the system should be able to consider all factors that influence the customers and theirinteractions with the system. The typical examples of such factors are: economic policy, new technology, fashion trends,cultural events, weather, etc. While easy to see that these factors can have an important influence on the e-commercesystem, due to their generality they are the most difficult to pinpoint and to build knowledge about them throughautomatic knowledge acquisition processes.3.3 ExpertsThough knowledge acquisition from human experts may be a very difficult task, some knowledge may be gained in noother fashion. Expert knowledge is first extracted (using standard techniques) as the basis for the system’s knowledge – afoundation of human experience-derived assumptions, which the system’s knowledge can grow and evolve upon. As thesystem uses this knowledge to learn and expand, the experts are still needed to deal with atypical situations, statisticaloutliers, which the automated knowledge techniques have difficulty integrating into the system. The task of the system inthese situations is to provide the human expert with enough information to help reaching a correct decision in as easy aspossible way. In the next stage this, more intuitive, knowledge is incorporated into the system.International Conference on Electronic Commerce Research (ICECR-5)
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