《中國電子商務(wù)》期刊說明

1、中國電子商務(wù)期刊簡介一、期刊名稱中國電子商務(wù)二、刊號國內(nèi)標(biāo)準刊號：CN11-4440/F國際標(biāo)準連續(xù)出版物號：ISSN1009-4067三、主管單位國家工業(yè)與信息化部四、主辦單位中國電子企業(yè)協(xié)會五、辦刊宗旨中國電子商務(wù)以傳播信息化理念、報道經(jīng)濟前沿、倡導(dǎo)信息創(chuàng)新、促進經(jīng)濟進展為辦刊宗旨，大力普及電子商務(wù)知識，弘揚科學(xué)精神，傳播科學(xué)思想，倡導(dǎo)科學(xué)方法。六、刊登內(nèi)容中國電子商務(wù)是寬敞經(jīng)濟和信息化領(lǐng)域的治理人員、科教工作者、高校師生、信息化技術(shù)人員公布學(xué)術(shù)文章的重要理論陣地，是獵取精神陶冶、知識滋養(yǎng)和科技經(jīng)濟信息的重要渠道。本刊要緊刊登我國當(dāng)前信息化有關(guān)的科技、經(jīng)濟、教育、治理等方面具有一定學(xué)術(shù)和應(yīng)

2、用價值的學(xué)術(shù)文獻和反映各學(xué)科、各領(lǐng)域的新成果、新技術(shù)、新工藝、新產(chǎn)品等方面的論述文章。七、要緊欄目1. 經(jīng)濟治理研究：國際經(jīng)貿(mào)、物流論壇、商業(yè)研究、物流平臺、供應(yīng)鏈治理、資本運營、區(qū)域經(jīng)濟、投資分析、產(chǎn)業(yè)經(jīng)濟、網(wǎng)絡(luò)營銷、企業(yè)治理、經(jīng)營治理、營銷策略、品牌戰(zhàn)略、市場調(diào)研、人力資源、企業(yè)文化、財務(wù)審計、財經(jīng)論壇、學(xué)術(shù)研究、治理科學(xué)。2. 信息化研究：信息技術(shù)與安全、通訊技術(shù)、網(wǎng)絡(luò)技術(shù)、自動識不技術(shù)與應(yīng)用、電子商務(wù)、支付與結(jié)算、供應(yīng)鏈治理、數(shù)據(jù)庫與數(shù)據(jù)庫治理、案例分析。3. 科技研究：科技項目、科技政策 、科技成果、科學(xué)普及、技術(shù)市場、科技新品、有用科技、科學(xué)實踐等、機電一體化、電氣自動化。4. 教

3、育教學(xué)研究：教學(xué)研究、教育生活、課程與教學(xué)、教育信息化、職教時空、教學(xué)園地、信息化教學(xué)等。5. 工程技術(shù)研究：建筑工程、生物工程、醫(yī)學(xué)工程、環(huán)境科學(xué)、礦業(yè)工程、市政建設(shè)、水利工程、交通工程等。八、讀者對象經(jīng)濟領(lǐng)域和信息化領(lǐng)域的治理人員、科技企業(yè)科研開發(fā)人員、高等院校師生、信息化技術(shù)科研人員，社會各界關(guān)注經(jīng)濟進展和信息化進展的各界人士。聯(lián)系方式 TELEmail: HYPERLINK mailto: Some of the material presented in this article was excerpted with permission from The

4、 Data Model Resource Book: A Library of Logical Data Models and Data Warehouse Designs published by John Wiley and Sons and authored by Len Silverston, W. H. Inmon and Kent Graziano. The Concept The age of the data modeler as artisan is passing. Organizations can no longer afford the labor or time r

5、equired for handcrafting data models from scratch. In response to these constraints, the age of the data modeler as engineer is dawning. Engineers build new products using proven components and materials. In data modeling, the analogue to a component is a universal data model. A universal data model

6、 is a generic or template data model that can be used as a building block to jump-start development of the corporate data model, logical data model or data warehouse data model. Resistance to the use of universal data models is usually based on the belief that a particular organization has unique ne

7、eds or the dreaded not invented here syndrome. This article describes the application of universal data models to several disparate organizations. It demonstrates that the same basic models, with minor customization, can be successfully applied in each example. One Size Fits All? The belief that a p

8、articular organization is unique because of its missions, goals, policies, values, functions, processes and rules can be very strong. After all, some businesses sell to people and others sell to other organizations. Some deal with products and others deal with services. Each industry has its own set

9、 of business issues, and each organization within an industry varies as much as the differences between the personalities of various individuals. People and Organizations A subject data area that is common to most enterprises involves the people and organizations that are part of conducting business

10、. There is an important need to track the names, addresses, contact numbers and various relationships and interactions between the parties conducting business. Enterprises need to track information about customers, distributors, agents and suppliers as well as the internal organizations and people w

11、ithin the enterprise. This type of information is critical throughout all aspects of business including sales, marketing, customer service, purchasing, shipping, invoicing, budgeting, accounting and human resources. Enterprises spend significant effort and time defining the most effective ways to mo

12、del this type of information. The data model may lead to sub-optimal solutions if careful analysis is not conducted. For example, many data models depict separate entities for each type of party that exists in an enterprise. There may be entities for CUSTOMER, SUPPLIER, INTERNAL ORGANIZATION, BROKER

13、, EMPLOYEE, INVESTOR and any other role that a person or organization may play in the enterprise. There are problems with modeling the information this way. What if a person or organization plays more than one role in the organization? For instance, what if an organization supplies products and/or s

14、ervices to our organization and also buys products from us? Does this mean that we maintain their name, addresses, contact numbers and other organizational information in both the CUSTOMER and SUPPLIER entities? Under this scenario, if a name or address changes, the information needs to be changed i

15、n two places. Furthermore, does the organization play other roles such as an agent of the company or a distributor of products? Each time an organizations role is modeled as a separate entity, there is a potential for redundant and inconsistent information. The same argument applies to people. Shoul

16、d we have a separate EMPLOYEE entity as well as a CONTRACTOR entity? What if a contractor becomes an employee of the enterprise or vice versa? The persons name, demographics and contact information may still be the same. The only thing that has changed is the nature of the relationship between the p

17、arties. It only makes sense to refer to pre-defined templates or universal data models when modeling common data structures. Universal data models can point out the most effective means to maintain this information and assure that subtle, yet important, data integrity issues are not overlooked. Peop

18、le and Organization Information Figures 1, 2, 3 and 4 depict universal data models for the people and organizations involved in conducting business. These data models include information concerning the relationships between each person and organization as well as their associated contact information

19、. Before beginning our discussion of these models, lets clarify some data modeling conventions. Entities are represented using rounded-edge rectangular boxes. Sub-types are represented by showing boxes within the larger box. For example, in Figure 1, ORGANIZATION and PERSON are both represented as s

20、ub-types of PARTY. The lines between entities define relationships. The dashed section of each line represents that a relationship is optional. For example, in Figure 1, a PARTY does not necessarily have an associated PARTY DEFINITION. The part of the line closest to PARTY DEFINITION is solid, and t

21、his represents a mandatory relationship. Therefore, each PARTY DEFINITION must be associated with a related PARTY. The small crossed line across the PARTY DEFINITION to PARTY relationship specifies that the key to PARTY (party_id) is included as part of the key to PARTY DEFINITION. The crows feet (t

22、hree small lines at the end of each relationship line) denote a one-to-many (1:M) relationship. For example, Each PARTY may be defined by one or more PARTY DEFINITIONs. Vice versa, each PARTY DEFINITION must be used to define one and only one PARTY since the line from PARTY DEFINITION to PARTY does

23、not end with a crows foot. Now lets discuss the data models. Figure 1 identifies a super-type named PARTY, with two sub-types, PERSON and ORGANIZATION. Information about a person or organization is maintained independent of their roles or relationships. This leads to a much more stable and normalize

24、d data structure since information about various people and organizations is only stored once. The same information can then be associated with each of the partys roles. The reason that PERSON and ORGANIZATION are both sub-typed into a PARTY entity is that there is common information related to both

25、 people and organizations such as their credit rating, credit limit, address, phone number, fax number or e-mail address. Additionally, organizations and people can serve in similar roles. Both people and organizations may be buyers, sellers, members or parties to a contract. Parties may be classifi

26、ed into various categories (i.e., industry codes, minority classifications) using the PARTY DEFINITION which stores each category into which parties may belong. Figure 2 depicts that each PARTY may be involved in one or more PARTY RELATIONSHIPs. PARTY RELATIONSHIP is used to define the relationship

27、between two parties. An occurrence of a PARTY RELATIONSHIP may be between two organizations, such as a customer relationship to an internal company. The relationship may be between a person and an organization-for example, an employee of an internal company. Finally, the relationship may be between

28、two people. An example of this is the relationship between a purchasing agent and their preferred supplier representative. The PARTY RELATIONSHIP TYPE defines the possible types of relationships. Possible instances of PARTY RELATIONSHIP TYPE are employer/employee, parent/subsidiary, and customer/cus

29、tomer representative. The PARTY TYPE ROLE defines the two parts of the relationship. For example, one role of the relationship may be employer and the other role for that same relationship may be employee. Finally, the PARTY PRIORITY and PARTY RELATIONSHIP STATUS TYPE entities allow each PARTY RELAT

30、IONSHIP to be prioritized (high, medium, low) and defined via a status (active, inactive). By distinguishing whether information should be associated with the PARTY or the PARTY RELATIONSHIP, we can avoid data anomalies. For example, many data models associate a status with a PARTY. This does not ac

31、count for the fact that three sales representatives may have three distinct relationships with the same party. Each sales representative may want to record a different status for their relationship with the party. If the status were stored with the PARTY, then the sales representatives would have to

32、 override each others information. In actuality, there are really three separate relationships, and the status should be associated with the PARTY RELATIONSHIP. Figures 3 represents address or location information about parties. It shows that ADDRESS is its own entity and can be applied to many part

33、ies. The PARTY ADDRESS is a cross-reference or associative entity that allows each party to have many addresses (home address, work address) and each address to have many parties (an office location of many employees). Each PARTY ADDRESS may have many PARTY ADDRESS ROLES and vice versa. These relati

34、onships determine the purpose of the address. Examples of PARTY ADDRESS ROLE include corporate headquarters, sales office and warehouse. Figure 4 is a model to maintain phone numbers, fax numbers, cell numbers, e-mail addresses and all other CONTACT MECHANISMs. Instead of defining these contact mech

35、anisms as attributes, this model provides flexibility in allowing as many contact mechanisms to be stored for a PARTY or PARTY LOCATION as needed. The CONTACT MECHANISM TYPE entity identifies the type of mechanism such as phone, fax, cellular or pager. The PARTY CONTACT MECHANISM is an associative e

36、ntity that allows each CONTACT MECHANISM to be related to many PARTY ADDRESSes or PARTYs (a shared telephone number for several consultants). Conversely, each PARTY or PARTY ADDRESS may be contacted via many PARTY CONTACT MECHANISMs (a person or location with numerous contact mechanisms of different

37、 types). The line connecting the two relationships under PARTY CONTACT MECHANISM represents an exclusive arc and states that either one of these relationships exists, but not both. A PARTY CONTACT MECHANISM may be either the mechanism to contact a PARTY or a PARTY ADDRESS. Similar to addresses, cont

38、act mechanisms may have roles. Examples of PARTY CONTACT MECHANISM ROLE TYPEs include general information number, sales information and customer service number. After extensive analysis and consideration of many alternate data models, I believe that these four universal data models represent a very

39、effective way to model people and organizations for most enterprises. Now lets take a look at how these universal data models can be applied to specific enterprises. A Manufacturing Enterprise Lets consider the needs of a particular type of enterprise, specifically a manufacturing firm. Suppose this

40、 firm manufactures personal computers. They sell their products to retail chains, distributors and directly to individuals and organizations. It is important to record contact information on each distributor and the people within those organizations. They need to track supplier information to indica

41、te who provides PC components for their machines. Information on their end-user customers who have bought their equipment is critical. They also maintain employee information as well as information about the many subsidiaries, divisions and departments and their associated locations. The first comme

42、nts an enterprise may make about using the previously presented universal data models are Where is the customer entity? Our most important information needs are about our customers. We need to record their credit limit, billing options and their customer status. Similarly, where are the entities for

43、 supplier, employee, distributor or internal organization? Each of these business entities is characterized by very common information. They all have names, addresses, phone numbers, statuses and other contact information. This leads us to the conclusion that they could be sub-typed together. Should

44、 we then modify the model to add the sub-types CUSTOMER, SUPPLIER, DISTRIBUTOR, INTERNAL ORGANIZATION and EMPLOYEE all within the PARTY entity? An issue is that a single person or organization may be involved in more than one of these relationships. For example, a distributor of the manufacturer may

45、 also be a supplier of some of their PC components. Again, we do not want to maintain more than one occurrence of the same person or organization as this can lead to data inconsistencies. Figure 5 illustrates how the previously described universal data models can be modified to meet the information

46、needs of our manufacturing example. For simplicity reasons, only a few important entities are shown in Figure 5, but all previously described entities also apply to our manufacturing firm. The PARTY RELATIONSHIP is sub-typed into the applicable business relationships, CUSTOMER, SUPPLIER, DISTRIBUTOR

47、, EMPLOYEE and INTERNAL ORGANIZATION. This allows each person or organization to be involved in one or more of those relationships. If there are other types of relationships such as sales agents, government agencies who regulate manufacturing or stockholders, they can also be defined as additional P

48、ARTY RELATIONSHIP sub-types. The basic information about each person or organization such as their names, credit rating, addresses, phone numbers and other contact information is associated with the PARTY. The information about each relationship is stored in the PARTY RELATIONSHIP entity. All sub-ty

49、pes of PARTY RELATIONSHIP have a from_date, through_date and comments. Each PARTY RELATIONSHIP sub-type may have different attributes to define that specific relationship type. For example, the CUSTOMER sub-type has a credit limit, statement_day (defined as the closing day for statements), and state

50、ment_frq (defining the frequency of statements such as weekly, bi-monthly or monthly). This model provides an extensive, flexible and stable means of maintaining person and organization information for the manufacturing organization. The only customization required was to add the PARTY RELATIONSHIP

51、sub-types applicable to the manufacturer. A Financial Securities Company Is this model applicable to other enterprises such as a financial securities company? Lets assume that this enterprise sells investment vehicles such as mutual funds, stocks, bonds and other investments to the general public, m

52、ostly through brokers. The same type of base information is needed for people and organizations in this type of company: their names, addresses, phone numbers and information about different types of parties and relationships. The difference is in the types of business relationships involved in a fi

53、nancial securities firm. A financial securities company needs to track information about their brokers, investors, wholesalers (the party selling to the broker), employees and internal organizations. Figure 6 shows that this same universal data model can be effectively used for a financial securitie

54、s company by adding the applicable PARTY RELATIONSHIP sub-types and associating appropriate attributes to each type of relationship. Investment goal is an attribute of INVESTOR, annual quota is an attribute of the WHOLESALER that sells to the broker and the exclusive indicator and broker license num

55、ber are stored for the BROKER sub-type. Other Enterprises By now, it is hopefully evident that most enterprises can use this same model and customize it by adding sub-types to represent their own party relationships. Health care enterprises may have DOCTOR, PATIENT, INSURANCE COMPANY, HMO and PPO as

56、 PARTY RELATIONSHIP sub-types. Universities may have STUDENT, FACULTY, ADMINISTRATOR, GOVERNMENT AGENCY (for grants) and DONATOR as possible sub-types. In a consulting services enterprise the party relationships may be CONSULTANT, CLIENT, INTERNAL STAFF and DEPARTMENT. Every enterprise has the same

57、type of data structures related to people and organizations, but they are applied toward different types of relationships. Other Models We have only examined data models for one common aspect of business; namely, managing party and relationship information. There are many other universal data models

58、 for maintaining information on product/services, orders/agreements, shipments, time entry, invoices, accounting, budgeting and human resources. There are also universal data models for standard data warehouse design applications such as sales analysis, financial analysis and human resource analysis

59、. I have successfully assisted enterprises in applying these template models against many industries and have found that quite often 60 percent of the universal data model constructs are applicable. This translates into data models of much better quality and substantial savings of time and cost. Con

60、clusion Universal data models can substantially reduce the time to complete a corporate data model, logical data model or data warehouse design. They can lead to higher quality designs by identifying subtleties that may be overlooked by inexperienced modelers or harried modelers who may have tight p