Geographical Information System (GIS)
2.3.2 Geographical Information System (GIS)
Geographical information means the relevant information to geographical distribution of the research subject, including quantity, quality, distribution characteristics, correlation of the subject and its environment. Geographical information is a kind of spatial information, and since the identification of locations is closely related to data, it is regional. Geographical information is also characterized by multi-dimensions, that is, the same location may possess an information structure covering several subjects and properties. For instance, at a certain point, there is information concerning altitude, earth bearing strength, noise, pollution and transportation. Moreover, geographical information is evident characteristic of time sequence, namely, dynamic feature. This feature requires timely data collection and updating so that prediction of the future can be made on the basis of its temporal laws that are worked out according multi-phase data and information.
GIS is a spatial information system mainly concentrating on collecting, storing, managing, analyzing and describing information of part of or the whole surface (including the atmosphere) of the earth that is relevant with the spatial and geographical data.
GIS is an interdisciplinary subject that combines computer science and spatial data analysis. The areas it relates to include geodesy, photography, cartography, geology, remote sensing, and image analysis and so on. GIS is closely related with but differentiated from these disciplines. The following are several differences that are easily misunderstood.
Introduction to E-commerce
1. GIS vs. general database
The primary difference between GIS and general database is that GIS deals with space data, that is, besides a text database, there is also a graph database. Thus GIS has more complex hardware and software than general databases, and is more powerful. For instance, if the telephone directory is considered as a general database, it can only answer the requested telephone number. However, the communication information system can also provide the information about geographical distribution and spatial density of the telephone users, and the location of nearby post offices and telephone booths. Of course, the general database can also be a part of the GIS.
2. GIS vs. digital map
Digital map is a simulated map in computer, which primarily considers the landform and the presentation of various elements on the map. It is digitally stored, managed and outputed. On the other hand, GIS enables the graph data and non-graph data to be separately stored but interoperated. The emphasis of digital map is on the map, while GIS emphasizes information and the operation.
Digital map, if managed by the map database, can provide spatial query, analysis and indexing functions. However, it is unlike GIS, which can integrate graph data and attribute data to make more profound analysis, and provide useful information for planning, management and decision-making. Of course digital map is the data source of GIS, and plays an important role in GIS.
The development of GIS in China started a little late, which has experienced four phases, namely, initiation (1970 ü 1980), preparation (1980 ü 1985), development (1985ü 1995), industrialization (after 1996). GIS has been widely used in many areas and therefore it has gained much attention from the government. Many software products (such as GeoSTAR, CityStar, MapGIS) have been successful developed and GIS-related subjects or disciplines and hi-tech enterprises are founded. In addition, China GIS Association and China GIS Application Association have been set up.
With the development in a decade, China GIS has achieved great progress. And the research and application of GIS is gradually developing into an industry.
2.3.3 Decision Supporting System (DSS)
Decision Supporting System (DSS), is an intelligent man-machine system that is based on management science, operational research, control system and behavioral science. It uses computer technology, simulation technology and information technology to solve semi-structured decision problems. This system provides data, information and background for the decision maker to help them identify the problems and establish decision models. It evaluates and selects various cases
2 E-commerce Supporting Technologies
through analysis, comparison and judgment, providing necessary support for the best decision.
The concept of DSS was proposed in the 1970’s, and developed in the 1980’s. It originated from the following backgrounds: traditional MIS did not bring tremendous benefit to the enterprises while people require more advanced systems to support decision; therefore the computer application satisfied the need and provides the foundation for the DSS.
The concept structure of DSS is composed of session system, control system, operating system, database system, model base system, and rule base system and the users. The simplest and most practical DSS logical structure (database, model base, rule base) is illustrated in Fig. 2.11.
Figure 2.11 Structures of DSS three bases The process of DSS can be simply described as: the user inputs the decision
problem through the session system, which then passes the input problem to problem processing system; then the problem processing system begins to collect data and identify the problem according to the knowledge stored. If a problem occurs, the system will interact with the user via the session system until the problem is identified; then the system begins to search for the appropriate model to solve the problem, induces the feasibility of the solution, and finally renders the decision information to the user.
DSS technology includes: (1) Interface part. It is the interface of input and output and also acts as the
platform of interaction.
(2) Model management part. The system will retrieve the existing basic models according to the problems raised by users. Therefore the model management part has to possess storage and dynamic modeling functions. Currently the implementation of model management is accomplished by model base system.
(3) Knowledge management part. It concentrates on managing the knowledge (rule and facts) of decision problem, including the retrieval, expression and management of knowledge.
(4) Database part. It manages and stores decision-related data.
Introduction to E-commerce
(5) Induction part. It identifies and answers the questions raised by users, divided into determinant induction and non-determinant induction. (6) Analysis and comparison part. It makes comprehensive analysis and comparison among solutions, models and results, in order to obtain the most satisfactory solution.
(7) Problem dealing part. According to the question raised by users, it constructs the model and solution of the problems, and matches algorithm, variable and data to obtain solutions.
(8) Controlling part. It connects and coordinates all parts of the system, prescribes and controls running applications for different parts of the system to maintain and protect the system. In addition, it includes consultation part, simulation part, and optimization part.
The primary features of DSS have been outlined as follows: (1) The system is decision-maker-oriented. The participant in the whole
process is the decision maker.
(2) The problems that can be solved by the system belong to semi-structured decision problems and the use of the model and methods is determinant; but the decision makers differ in their understanding, and the condition of the problem is uncertain. Therefore the result of the decision is made un-determinant.
(3) The system emphasizes the support concept and helps the decision-maker to make scientific decision.
(4) The driving force of the system stems from the models and users. And man is the initiator of the system while model is the core of the link between different parts.
(5) The system emphasizes interactive transactions. A decision needs repetitive and frequent interactions; the human factors such as personal preference, subjective judgment, ability and experience have profound influence on the decision result.
DSS is generally developed with the combination of objective-oriented method and prototype method, described as follows: first use prototype method to develop individual parts of the DSS, then assembles them to form development toolset and environment of DSS according to the general method of system generation.
Analyzed from the perspective of system development, DSS can be divided into three different technical layers: DSS tools, namely, DSS fundamental parts; DSS generators, i.e. the general framework that organizes DSS; specialized DSS,
i.e. the practical application system generated by the DSS generator. The relation between three layers is illustrated in Fig. 2.12.
Figure 2.12 Hierarchical relations The design of the foundational layer is done by software developers, and the
user belongs to the highest layer. The construction process from the foundational
2 E-commerce Supporting Technologies
layer to the intermediate layer is the task of system engineers; the intermediate layer is DSS constructor-oriented. The design between the intermediate layer and the highest layer is the task of system analysts and designers. The development of DSS usually aims at a specific problem, which can be divided into five phases: problem analysis, feasibility research, selection of development method, system development and decision supporting. The decision maker should be involved in the process for he is the director user and his need is the aim of the system.
The work of each phase is outlined as follows: (1) Problem analysis phase. This phase includes field investigation and analysis
to identify the problem. (2) Feasibility research. Based on the analysis of the previous phase, the feasibility of the system development is studied in terms of technology, feasibility, effectiveness of solution, and economic and social benefits.
(3) Determination of the development methods and strategies. This phase involves the determination of how the system development is organized and what tools, methods and approaches are employed.
(4) System development phase. It involves the development of a DSS specific to the problem, including the establishment of the DSS structure, data model and evaluation standard.
(5) Decision supporting phase. It means the actual operation phase after the system development is completed. It includes the result analysis, decision support and the data collection that reflects the validity of the system operation.
2.3.4 Group Decision Supporting System (GDSS)
Group Decision Supporting System (GDSS) means that multiple decision makers communicate with each other to find a satisfying and feasible solution, but the final decision is made by a certain one, who also takes responsibility for the result. GDSS is developed out of the DSS by increasing the number of participants and making the information source more extensive. It effectively avoids one-sidedness of decision and dogmatized behaviors.
The function of GDSS includes the following points: (1) The difference is eliminated by enforcing communication and the relation
between participants is controlled and coordinated by restricting the unnecessary emotional interaction.
(2) The status of participants and the justness of the conclusion are enhanced. (3) The implementation of the system is permanent or temporary. The technical functions of GDSS include the following points: (1) Control over data exchange in the decision process. (2) Automatic selection of appropriate GDSS technology. (3) Computation and explanation of the feasible solutions.
Introduction to E-commerce
(4) If GDSS cannot reach agreement, the difference is discussed or the problem is redefined.
A typical GDSS structure is illustrated in Fig. 2.13.
Figure 2.13 General structures of GDSS GDSS is a new branch of the decision supporting area, an extension of DSS,
which includes:
(1) A Communication Base is added to facilitate the communications between the decision makers.
(2) Model base is enhanced, providing voting, sorting, classified evaluation to fulfill the agreed decision. (3) The system can be self-prepared and coordinated before used, such as scheduling a meeting. (4) Necessary physical devices are extended. The type of GDSS depends on the problem which will be decided and its
environment to a certain degree, thus GDSS is generally classified into four types:
(1) Decision room: it seems like a traditional meeting room, where the decision makers gather and take part in the decision making process through terminals. This process is restricted by time.
(2) Local decision network: the participants of GDSS are not restricted by space. Once the LAN is equipped with public GDSS software and database is stored in the central processor, the participants can make communication between the central processor and the members or each other via the LAN.
(3) Fax conference: it is intended for the group that is separated geographically but can be assembled when necessary.
2 E-commerce Supporting Technologies
(4) Remote decision-making: it is intended primarily for those members who have to meet regularly but cannot meet each other physically. These dispersed decision makers keep constant communication with each other via remote decision stations.
2.3.5 Intelligent Decision Supporting System (IDSS)
Intelligent Decision Supporting System (IDSS) is a supporting system that combines Artificial Intelligence and DSS, and uses the technology of Expert System to enable DSS to sufficiently apply human knowledge so as to solve complex decision problems. With Expert System, the DSS can apply human knowledge more sufficiently to solve problems through logic reasoning.
The concept of IDSS was originally proposed by Bonczek in the 1980’s, the function of which was to deal with quantitative problems as well as qualitative problems. The core idea of IDSS was to combine AI and other relevant disciplines to make DSS more intelligent. In order to introduce AI to DSS, the expert system is combined with DSS, what’s more, inference machine and rule base are also introduced to DSS. In the decision process, some knowledge cannot be represented by data or model. The rule base introduced in IDSS can store the knowledge and provide important reference to the decision process.
IDSS has multiple kinds of information bases (as illustrated in Fig. 2.14): text base (TB), database (DB), approach base (AB), model base (MB) and rule base (RB).
Figure 2.14 The framework of IDSS The text base stores numerous texts written in natural language; the database
stores records of key fields; the model base stores various models that illustrate the relations of information; the rule base stores the rules. The process of information extraction from raw data to processed information is called “evolving link”.
Introduction to E-commerce
The IDSS can be technically divided into three layers: (1) Application layer. It is directly oriented to the user of IDSS. In this layer,
the decision maker can determine the state and impose restrictions on IDSS according to his need. And through the user interface he may input some information, which will be understood by DSS via information transformation. Through inference and calculation, the system will return the user the result through interface. The whole process is transparent to the user.
(2) Control and coordination layer. It is oriented to the designer of IDSS, the fundamental element of which is the control and coordination modules of the databases. The system engineer establishes the connections between such modules via the standard interfaces.
(3) Basic structure layer. It is oriented to programmers. The programmer realizes all bases through this layer, including the structure and communication mode of them, so as to accomplish internal management and external communication of bases.
IDSS has the following features: (1) It is based on mature technology. So it is easy to construct applicable system. (2) It sufficiently uses the information resources of all the layers. (3) It is based on rules, which enables users to use it easily. (4) It is characterized with strong modulization, which enables reuse and low cost. (5) It is flexible to combine system parts, which enables easy maintenance and
powerful functions.
(6) It is easily upgraded by adopting advanced supporting technology, such as AI. The modules have to call the upper layer repetitively, which has lower efficiency
than calling lower layer while IDSS is running. However, since IDSS is just used in important decisions, it is worthwhile to sacrifice the running efficiency for the efficiency of system maintenance.
2.4 Summary
E-commerce is a kind of dynamic business that emerges when the Internet and traditional information technologies combine. The application and development of e-commerce system cannot be divorced from the support of the fundamental technologies. E-commerce is a comprehensive support and service to the new business operations.
This chapter describes the supporting technologies of e-commerce system in terms of fundamental information technology, advanced communication technology and applied information processing technology. Fundamental information technology primarily includes Web, HTML and Java. Advanced communication technology primarily includes network technologies, such as TCP/IP, EDI, WLAN and Bluetooth protocols. Applied information processing technology means special information systems involved in e-commerce, including GPS, GIS and DSS.
2 E-commerce Supporting Technologies
References
[1] Qin Z., Li S D., Zhang L., Xie G T. & Yan L X. An Introduction to E-Commerce. Beijing: People’s Post and Telecommunication Press, 2000. [2] Qin Z., Xie G T., Li S D., & Jia X L. E-Commerce System Structure and System Design. Xi’an: Xi’an Jiaotong University Press, 2001. [3] Qin Z., Han Y. & Yan L X. Computer System Intergration and E-commerce. Xi’an: Xi’an Jiaotong University Press, 2001. [4] Qin Z., Liu X Y. & Wang LR. Case Study on E-commerce. Xi’an: Xi’an Jiaotong University Press, 2001. [5] Gong B. EDI and E-commerce. Beijing: Tsinghua University Press, 1999. [6] Xue R J. International Trade. Chengdu: Sichuan People’s Press, 1998. [7] Meyer, A.; Taylor, P. E-commerce: An Introduction. Computing & Control Engineering
Journal, Volume: 11 Issue: 3, June 2000, 107 108. [8] Schneier B. Applied Cryptography. Beijing: Machinery Industry Press, 2000. [9] Shim, S.S.Y.; Pendyala, V.S.; sundaram, M.; Gao, J.Z. Business-to-Business E-commerce
Frameworks. Computer, Volume: 33 Issue: 10, Oct. 2000, 40 47. [10] Yuan C Y. A Principle of Petri Net (the first edition) Beijing: Electronics Industry Press, 1998. [11] William G.Page.Jr. A Handbook of Oracle 8/8i Development and Application (the first edition) Beijing: Machinery Industry Press, 2000. [12] Bradley D.Brown. A Handbook of Oricle8i Web Development (the first edition) Beijing: Machinery Industry Press, 2001. [13] Fu LL., Chen G C. & Shen W Z. The Achievement of Safe Electronic Transaction Procedures. Electronic Techniques, Issue 2, 1999. [14] Qi M. A Practical Course of E-commerce. Beijing: Higher Education Press, 2000. [15] Michael Abbey. A Handbook of Oracle 8i for Beginners. (the first edition) Beijing: Machinery
Industry Press, 2000. [16] P. Pu, L. Chen, P. Kumar. Evaluating product search and recommender systems for E-commerce environments. Electronic Commerce Research, Vol. 8(1 2): 1
17, 2008. [17] Yu Z T., Song L Z. Che W G. & Guo J Y. The Strategies of Database Techniques in
Shopping Vehicles on Internet. Computer Application, No.8, Vol(20), 2000, 66 68. [18] Zhao J Z., Zhu C M. & Zhang S. The Techniques of Information Integration in Virtual Business. Small and Micro Computer System. Volume 21, Issue 9, 2000. [19] Yang S F. Practical Techniques and Cases of Java Program. (the first edition) Beijing: Tsinghua University Press, 2000. [20] Yen-Liang Chang, Chen, S. Chyun-Chyi Chen Chen, I. Workflow process Definition and Their Applications in E-commerce. Multimedia Software Engineering, 2000. Proceedings. International Symposium on, 2000, 193 200.
[21] Bhaskaran, K. Jen-Yao Chung Das, R. Heath, T. Kumaran, S. Nandi, P. An E-business Integration & Collaboration Platform for b2b E-commerce. Advanced Issues of E-Commerce and Web-Based Information Systems, WECWIS 2001, Third International Workshop on, 2001, 120 122.
Introduction to E-commerce
[22] DeFazio, S. Krishnan, R. Srinivasan, J. Zeldin, S. The Importance of Extensible Database Systems for E-commerce. Data Engineering, 2001. Proceedings. 17th International Conference on, 2001, 63 70.
[23] Yuan R. How to Choose Web Servers. Computer World, 2000. [24] Wang F Y. & Wu C H. ASOS: The Development Tendency of Inlaying Type Operation
System. Computer World, Sum No. 818. [25] P. Li, M. H Tu, I. L. Yen et al. Preference update for e-commerce applications: Model, language, and processing. Electronic Commerce Research, Vol.7 (1): 17
44, 2007. [26] R. Kohavi, Mining e-commerce data: the good, the bad, and the ugly. In: Proceedings of the seventh ACM SIGKDD international conference on Knowledge discovery and data mining, pp. 8
13, ACM Press, NY, USA, 2001. [27] Ma M H. Principles and Techniques of Computer Information System Safety Law. Xi’an: Shanxi People’s Press, 2000. [28] C. W. Holsapple, S. Sasidharan. The dynamics of trust in B2C e-commerce: a research
model and agenda. Information Systems and E-Business Management, Vol.3 (4): 377 403, 2005.
[29] Van Dyke Parunak, H. A Practitioners&apos. Review of Industrial Agent Applications.
Autonomous Agents and Multi-Agent Systems; 1387 2532; No.4, Vol (3), 2000. [30] Erosion of the Concept of Permanent Establishment: Electronic Commerce Skaar, Arvid Aage; Intertax; 0165 2826; No.5 (28), 2005. [31] Michael J. Electronic Commerce: Integration of Web Technologies with Business Models Shaw. Information Systems Frontiers; 1387 3326; Volume 1, Issue 4, 2004. [32] O’Leary,Daniel E. Reengineering Assembly, Warehouse and Billing Processes, for
Electronic Commerce Using “Merge-in-Transit”. Information Systems Frontiers; 1387 3326; No.4 (1), 2000.
[33] Porra, Jaana.Electronic Commerce Internet Strategies and Business Models-A Survey. Information Systems Frontiers; 1387 3326; No.4 (1), 2000. [34] Sandholm, Tuomas. Agents in Electronic Commerce: Component Technologies for Automated Negotiation and Coalition Formation. Autonomous Agents and Multi-Agent Systems; 1387 2532; No.1 (3), 2000.
[35] Shaw, Michael J. Building an E-Business from Enterprise Systems. Information Systems Frontiers; 1387 3326; No.1 (2), 2000. [36] Arora, Ashish, Cooper, Gregory, Krishnan, Ramayya, Padman, Rema. IBIZA: E-market Infrastructure for Custom-built Information Products. Information Systems Frontiers; 1387 3326; No.1 (2), 2000.
[37] P. Desharnais, J. Lu, T. Radhakrishnan. Exploring agent support at the user interface in e-commerce applications. International Journal on Digital Libraries, Vol. 3(4): 284 290, 2002.
3 Payment Technologies for E-commerce
Zheng Qin Ĺ Han Yi Li Shundong Dong Jinchun
Yan Lixiang ĺ Qin Jun
School of Software, Tsinghua University, Beijing 100084, China
School of Computer Science, Shaanxi Normal University, Xi’an 710062, China
Panda Electronics Group Co., Ltd. Nanjing 210002, China
School of Information Management and Engineering, Shanghai University of
Finance and Economics, Shanghai 200433, China
Abstract All business activities need the support of payment system, so does the e-commerce. As e-commerce process transactions through the Internet, it requires a more secure, stable and efficient payment system for supporting commerce done electronically. By the success of online banking and online payment in recent years, the market seems to have a solution for e-commerce. Online payment can be conducted in different means, such as intelligent card (IC), e-check, e-Wallet, e-Cash etc. This chapter briefly introduces the online banks and the online payment tools that are common used in e-commerce.
Key Words e-commerce, payment, online bank, intelligent card, e-check, e-wallet, e-cash.
Payment technology is an important part of the capital flow in the development of e-commerce. Its development determines the fate of e-commerce directly. In the context of international e-commerce operation, how to utilize relevant electronic payment technologies is the key of realizing online purchase and real-time payment. The keys in this chapter include the functions and features of online banks, e-payment system, e-cash, e-check and e-wallet.
In the new century, e-payment technology will change the way we live and trade. E-payment system is being applied all over the world and has achieved tremendous success. With the wide spread of e-money, e-payment has become a new development area. In the information era, e-payment will definitely enter every common family.
Introduction to E-commerce