《系统工程》课程教学资源（英文文献）Research on the Key Issue of Logistics System Integration in the Web

Research on the Key Issue of Logistics System Integration in theWebLixin Shen, Zhiguo Wang, Jun Zhai, Kejia WangTransportation Management College, Dalian Maritime Universitydl_wangzg@hotmail.comAbstractIn the network environment, constructing a thirdparty logistics system is the process of composingdifferent logistics Web services, and assessing business partners is the action of selecting andevaluating Web services.Referringto theregulation of partner selection in the logistics, thepaperproposes that KPI (Key Performance Index) is applied to non-functional Web services interfacedefinition, which enables the result of selecting and evaluating web services closer to the object ofconstructing third-party logistics system. This paper also establishes a model to decide which KPI willbe applied to Web services interface definition. Then the model is used to get KPI indicators in thetransport logistics industry.1.IntroductionWith Web service technology widely accepted, Web service has become the standard method ofresources package in the Internet [1]. Logistics enterprises, in order to participate in internationalcompetition and collaboration, have been releasing their core business in the form of Web service.With the type of Web service continuously being rich, the technology of service compositionbecomes the natural demand of the development of the Web service technology. The technology ofservice composition,based onthetechnologyofthe Web service interoperability,ishigh-levelintegration means, and realizes composing some Web services to one more powerful Web service.Widely available and standardized Web services make it possible to realize Business-to-BusinessInteroperability(B2Bi)by interconnecting Web services provided bymultiplebusinesspartnersaccording to some business process: a practice known as Web Services Composition [2]. So theconstruction process of traditional third-party logistics system [3-4] has been transformed into abuildingprocess of Webservicecomposition.The construction of a third party logistics system needs first to assess the enterprises, In thenetwork environment, the process is selecting and evaluating different Web service. This is the keyissue of Web service composition

Research on the Key Issue of Logistics System Integration in the Web Lixin Shen，Zhiguo Wang，Jun Zhai，Kejia Wang Transportation Management College, Dalian Maritime University dl_wangzg@hotmail.com Abstract In the network environment, constructing a thirdparty logistics system is the process of composing different logistics Web services, and assessing business partners is the action of selecting and evaluating Web services. Referring to the regulation of partner selection in the logistics, the paper proposes that KPI (Key Performance Index) is applied to non-functional Web services interface definition, which enables the result of selecting and evaluating web services closer to the object of constructing third-party logistics system. This paper also establishes a model to decide which KPI will be applied to Web services interface definition. Then the model is used to get KPI indicators in the transport logistics industry. 1. Introduction With Web service technology widely accepted, Web service has become the standard method of resources package in the Internet [1]. Logistics enterprises, in order to participate in international competition and collaboration, have been releasing their core business in the form of Web service. With the type of Web service continuously being rich, the technology of service composition becomes the natural demand of the development of the Web service technology. The technology of service composition, based on the technology of the Web service interoperability, is high-level integration means, and realizes composing some Web services to one more powerful Web service. Widely available and standardized Web services make it possible to realize Business-to-Business Interoperability (B2Bi) by interconnecting Web services provided by multiple business partners according to some business process: a practice known as Web Services Composition [2]. So the construction process of traditional third-party logistics system [3-4] has been transformed into a building process of Web service composition. The construction of a third party logistics system needs first to assess the enterprises. In the network environment, the process is selecting and evaluating different Web service. This is the key issue of Web service composition

2.Researchstatus andproblemsAlthoughtherearevariouskindsofapproachesdealingwithWebservicediscoveryissue,threeofcommonly used methods are identified in the paper: keywords-based and Ontology-based reasoningandQoS-based(Quality of Service)approaches.One,keywords-basedmechanism isoneof thedominating techniques for web services discovery and matching.However, this approach based on the syntax keyword (string) is lowly accurate. And, this approachbased on term frequency analysis is insufficient in the majority of the cases because it fails tocontemplate the semantic concepts hidden behind the service descriptions.An alternative to thekeywords-based approach is to find common semantic concepts between the terms in the query andthe services advertisements. More recently, ontology-based reasoning approach has been seeking touse ontology to annotate elements in web services, which aims to not only capture the information onthe structure and semantics of a domain, but facilitate software agents to make inference at the level ofconcept.As selecting Web services, by defining semantic information of Web services can find theappropriated Web services, and compose the Web services to meet the functional requirements [5-7].Third, there is also a research of the choice of Web service, which based on the quality of service(QoS). Such researches mainly focus on: when system is running, dynamically discover then selectthen bind Web service [8-10]. That can select the appropriate Web service from the candidate servicesset with functional equivalent to meet the management objectives of QoS. General speaking, QoS ofWeb service is a group of non-functional attribute collections of Web service.[8] Such as service timeservice prices, the success rate, reliability, security, and so on.But, according to Steven E. Leahy [11] and others' research [12, 13], the assessment of logisticsenterprises should take customer service, cost savings and cooperative relations as the basic criteriaU.S. supply chain relations expert Rosabeth M.Kanter[14], after visiting 500 multiple to 37manufacturer managers from 11 different parts of the world, summed up the 8I standard of theeffective cooperation between the companies: Individual excellence, Importance, InterdependenceInvestment, Information, Integration, Institutionalization and Integrity.However, theresearch aboutWeb service selection has not find the research based on logistics enterprises' selection criteria.Therefore this paper puts forward that KPI index will be added to the Web service interface definition,so that each of the Web service (or service composition) has KPI information, then in the field oflogistics the choice of Web services will be closer to reality, better reflect the actual logistics.3.WebservicebasedonKPI

2. Research status and problems Although there are various kinds of approaches dealing with Web service discovery issue, three of commonly used methods are identified in the paper: keywords-based and Ontology-based reasoning and QoS-based (Quality of Service) approaches. One, keywords-based mechanism is one of the dominating techniques for web services discovery and matching. However, this approach based on the syntax keyword (string) is lowly accurate. And, this approach based on term frequency analysis is insufficient in the majority of the cases because it fails to contemplate the semantic concepts hidden behind the service descriptions. An alternative to the keywords-based approach is to find common semantic concepts between the terms in the query and the services advertisements. More recently, ontology-based reasoning approach has been seeking to use ontology to annotate elements in web services, which aims to not only capture the information on the structure and semantics of a domain, but facilitate software agents to make inference at the level of concept. As selecting Web services, by defining semantic information of Web services can find the appropriated Web services, and compose the Web services to meet the functional requirements [5-7]. Third, there is also a research of the choice of Web service, which based on the quality of service (QoS). Such researches mainly focus on: when system is running, dynamically discover then select then bind Web service [8-10]. That can select the appropriate Web service from the candidate services set with functional equivalent to meet the management objectives of QoS. General speaking, QoS of Web service is a group of non-functional attribute collections of Web service.[8] Such as service time, service prices, the success rate, reliability, security, and so on. But, according to Steven E. Leahy [11] and others’ research [12, 13], the assessment of logistics enterprises should take customer service, cost savings and cooperative relations as the basic criteria. U.S. supply chain relations expert Rosabeth M. Kanter[14], after visiting 500 multiple to 37 manufacturer managers from 11 different parts of the world, summed up the 8I standard of the effective cooperation between the companies: Individual excellence, Importance, Interdependence, Investment, Information, Integration, Institutionalization and Integrity. However, the research about Web service selection has not find the research based on logistics enterprises’ selection criteria. Therefore this paper puts forward that KPI index will be added to the Web service interface definition, so that each of the Web service (or service composition) has KPI information, then in the field of logistics the choice of Web services will be closer to reality, better reflect the actual logistics. 3. Web service based on KPI

KPI accords with an important management principle Paredo" [15]. It was raised by Pareto, anItaly's economist, and it is an abbreviation ofimportant minority"and " trivial majority".Paretobelieved that: in any given group, the important factors account for the minority; however, theunimportant factors account for the majority.We can control the global as long as we controlled theimportant minority.Which reflected in the quantity proportion is roughly 2:8. The"20/80" rule alsoexists in the value creation in enterprises, that is, 20 percent of the backbone employees create 80percent of the valuefor the enterprise.For each employee, 80%of the tasks are completed by the20per cent of the key actors. Therefore, we should seize 20 percent of the key actors to grip the crux oftheperformanceappraisal throughanalysisandmeasurement.KPI is an important performance appraisal tool. With the combination of the management byobjectives thought and the quantitative examination thought, it makes the objectives of all levels(including team and individual objectives) can not deviate from the organization's strategic target bybreaking down the objectives steadily,have a very good measure of team performance as well asindividual contributions to the team, and play an important role in value assessment and behaviororiented.3.1.KPIAdvantagesKPI is key performance index, rather than a general index, of achievement that is portion of indexproducing a key influence on performance, compared to other indexes, their advantages:There is less evaluation index in the KPI.2) The target values of then evaluation indexes in the KPI are progressive.3) The evaluation indexes in the KPI are dynamic.4) The evaluation indexes in the KPI are critical5)TheevaluationindexesintheKPIarecontrollableandadministrableIn addition, KPI has many advantages, such as: it has a clear objective and is favorable to achievethe strategic goal of the company; it puts forward the customer value concept, and it is helpful toconformity of the organizational interest to the personal interest.3.2.KPIDisadvantagesThere are a few researches of KPI Shortcomings. There are two main aspects concerned in thereference: First, the KPI did not provide a complete, concrete and meaningful index frameworksystem which has big significance in operation guiding, second, the determination of KPI is of up-bottomand layered composition,and it easilyleadstotheunscientific creation ofKPI.Itispointed

KPI accords with an important management principle “Paredo” [15]. It was raised by Pareto, an Italy's economist, and it is an abbreviation of “important minority" and " trivial majority ". Pareto believed that: in any given group, the important factors account for the minority; however, the unimportant factors account for the majority. We can control the global as long as we controlled the important minority. Which reflected in the quantity proportion is roughly 2:8. The "20/80" rule also exists in the value creation in enterprises, that is, 20 percent of the backbone employees create 80 percent of the value for the enterprise. For each employee, 80% of the tasks are completed by the 20 per cent of the key actors. Therefore, we should seize 20 percent of the key actors to grip the crux of the performance appraisal through analysis and measurement. KPI is an important performance appraisal tool. With the combination of the management by objectives thought and the quantitative examination thought, it makes the objectives of all levels (including team and individual objectives) can not deviate from the organization’s strategic target by breaking down the objectives steadily, have a very good measure of team performance as well as individual contributions to the team, and play an important role in value assessment and behavior oriented. 3.1. KPI Advantages KPI is key performance index, rather than a general index ， of achievement that is portion of index producing a key influence on performance, compared to other indexes, their advantages: There is less evaluation index in the KPI. 2) The target values of then evaluation indexes in the KPI are progressive. 3) The evaluation indexes in the KPI are dynamic. 4) The evaluation indexes in the KPI are critical. 5) The evaluation indexes in the KPI are controllable and administrable. In addition, KPI has many advantages, such as: it has a clear objective and is favorable to achieve the strategic goal of the company; it puts forward the customer value concept, and it is helpful to conformity of the organizational interest to the personal interest. 3.2. KPI Disadvantages There are a few researches of KPI Shortcomings. There are two main aspects concerned in the reference: First, the KPI did not provide a complete, concrete and meaningful index framework system which has big significance in operation guiding; second, the determination of KPI is of up￾bottom and layered composition, and it easily leads to the unscientific creation of KPI. It is pointed

out in the literature[16] that KPI also has thefollowing shortcomings.First, KPI only makes clear"what will be tested", that is, using what index to assess, but it does not pay much attention to "How totest," and "Who do the test". It must be used with other assessment methods to obtain good effect.Second, the KPI is an objective method of assessment, but in the actual performance appraisal work,some indexes are not quantitative. Therefore it must be used with some qualitative assessmentmethods to develop merits, avoid weakness and make up for the shortfall, thereby enhancing theeffectivenessofperformanceappraisal.3.3. Non-functional description of Web serviceDefinition 1: WS = (Fun, KPIpub, KPIpri). WS is the abbreviation of Web service. Fun represents thefunctional attribute of the service. KPI is the non-functional attributes. Considered the generalcharacter of the industry and the particular character of the company, the non-functional description ofWeb service is composed of KPIpub and KPIpri. KPIpub is a common KPI index in the industry, whileKPIpri is the KPI index which is particular in every single organization of this area.Definition 2: Set S the set of Web services, then divide these services into a number of non-emptysubsets of service class, which makes every element belongs to a collection at least, and thedifferences among the services in the same set consists in the attribute of KPI.Definition 3: KPI is a set. Every comprehended element comes from the selecting KPI modelwhich will be introduced in the followingKPIpri and KPIpub can be empty set. When KPIpub is empty while KPIpri is non-empty, such a WS isaffected heavily by the user and their empiric value. Conversely,when KPIpub is non-empty whileKPpr is empty, such a WS can not reflect the user's aspirations. So the paper conducts the serviceswhich are based on two nonempty index circumstances, as well as the example applications.HowtoselecttheKPI indexservingfortheWebservices?Whatkind ofKPI ispublic,and what isprivate? In order to choose the KPI index effectively and scientifically, the paper designs a selectingKPI model, which selected a group of relatively stable KPI values as the definition parameters of Webservices.4.The selectingKPI model4.1.Introductionof themodelFor selecting KPI, the paper designs a selecting KPI model. As figure 1 show, the model iscomposed of four components: data layer, rules definition layer, data analysis layer and resultmanifestation layer. Data layer searches ontology data and stores the historic KPI data in the logistics

out in the literature [16] that KPI also has the following shortcomings. First, KPI only makes clear "what will be tested", that is, using what index to assess, but it does not pay much attention to "How to test," and "Who do the test”. It must be used with other assessment methods to obtain good effect. Second, the KPI is an objective method of assessment, but in the actual performance appraisal work, some indexes are not quantitative. Therefore it must be used with some qualitative assessment methods to develop merits, avoid weakness and make up for the shortfall, thereby enhancing the effectiveness of performance appraisal. 3.3. Non-functional description of Web service Definition 1: WS = (Fun, KPIpub, KPIpri). WS is the abbreviation of Web service. Fun represents the functional attribute of the service. KPI is the non-functional attributes. Considered the general character of the industry and the particular character of the company, the non-functional description of Web service is composed of KPIpub and KPIpri. KPIpub is a common KPI index in the industry, while KPIpri is the KPI index which is particular in every single organization of this area. Definition 2: Set S the set of Web services, then divide these services into a number of non-empty subsets of service class, which makes every element belongs to a collection at least, and the differences among the services in the same set consists in the attribute of KPI. Definition 3: KPI is a set. Every comprehended element comes from the selecting KPI model which will be introduced in the following. KPIpri and KPIpub can be empty set. When KPIpub is empty while KPIpri is non-empty, such a WS is affected heavily by the user and their empiric value. Conversely, when KPIpub is non-empty while KPIpri is empty, such a WS can not reflect the user’s aspirations. So the paper conducts the services which are based on two nonempty index circumstances, as well as the example applications. How to select the KPI index serving for the Web services? What kind of KPI is public, and what is private? In order to choose the KPI index effectively and scientifically, the paper designs a selecting KPI model, which selected a group of relatively stable KPI values as the definition parameters of Web services. 4. The selecting KPI model 4.1. Introduction of the model For selecting KPI, the paper designs a selecting KPI model. As figure 1 show, the model is composed of four components: data layer, rules definition layer, data analysis layer and result manifestation layer. Data layer searches ontology data and stores the historic KPI data in the logistics

activities. The part includes Ontology query engine/ontology storage engine and relational databaseRules definition layer preselects and takes layer of the projects and rules of KPI and KPI definitionwhich is designatedbythe experts.Thepart includes weight algorithm engine,evaluation factorconstructor and theweight for constructing and computing the evaluation factors.Data processinglayertransforms and processes the sample data and theoriginal data which are obtained respectivelyfrom experts and customers. The part is composed of data collection module and data processormodule.Resultmanifestationlayerannouncestheresults.ThepartiscomposedofClientsReceivePlatform, Results Distribution Module and evaluation engine.The model uses Ontology language todescribetheconceptofKPI selectionandrelationship,and customizesevaluationfactorinthedifferent application fields through domain experts. It also automatically learns weight distribution ofevaluationfactorfromhistorydatabyusingmachinelearningmethod,combinedwithpriorknowledge that given by domain experts, and put forward interactive weight optimization algorithm.The model ensures that the KPI index which is added into the Web services definition is scientific,standardizedand withless effect ofuser's fondness.RulesDefinition LayerEvaluationNewStructuingEvaluationFactorEvaluaEvaluationFactorIntormationaFactorsConstuctorEvaluationSettingModelWeightDistibutioDomainWeightpreprocessingManagementResultsExpertAlgorithmrulesViewEngineSampleDataOntologyProvide SampleQueryPreprocessing RulesDataEnginesOntologyRelationaStorageDataDatabaseSampleDataDataDataStandardiztEnginesCollectionolaatDataOriginal DatadataprocesserSystemModuleData Analysis LayerOniginalDataEvaluationOutputResults/ClientsEvaluationEvaluationFactorEvaluationReceiveDistributionEngineResultResultsFinalPlatformModuleCustomersData LayerDataResult ManifestationLayerFigure 1. The selecting KPI model4.2. Inspect and verify the modelIn order to verify the accuracy, the model is applied to the field of logistics. According to sourcedata provided bythelogisticsLeaderenterprises,get somepublicKPI indexes ofthefield of logisticsSuch as Table 1. We can see that all indexes are directed at the common indicator project to the entirelogistics. But the logistics node enterprises have their own unique indicator project. The model is usedin the transport.Through analyzing the transport historic data and requesting help to transport experts

activities. The part includes Ontology query engine/ontology storage engine and relational database. Rules definition layer preselects and takes layer of the projects and rules of KPI and KPI definition which is designated by the experts. The part includes weight algorithm engine, evaluation factor constructor and the weight for constructing and computing the evaluation factors. Data processing layer transforms and processes the sample data and the original data which are obtained respectively from experts and customers. The part is composed of data collection module and data processor module. Result manifestation layer announces the results. The part is composed of Clients Receive Platform, Results Distribution Module and evaluation engine. The model uses Ontology language to describe the concept of KPI selection and relationship, and customizes evaluation factor in the different application fields through domain experts. It also automatically learns weight distribution of evaluation factor from history data by using machine learning method, combined with prior knowledge that given by domain experts, and put forward interactive weight optimization algorithm. The model ensures that the KPI index which is added into the Web services definition is scientific, standardized and with less effect of user’s fondness. Figure 1．The selecting KPI model 4.2. Inspect and verify the model In order to verify the accuracy, the model is applied to the field of logistics. According to source data provided by the logistics Leader enterprises, get some public KPI indexes of the field of logistics. Such as Table 1. We can see that all indexes are directed at the common indicator project to the entire logistics. But the logistics node enterprises have their own unique indicator project. The model is used in the transport. Through analyzing the transport historic data and requesting help to transport experts

get the KPI indexes which transport industry is different from other sectors.These should be anintegral partofKPIprieither.SuchasTable2Table 1. Logistics industry KPIpubNoNoKPIaNameKPI.aNameReaction ratetocustomerTotal costunits (yuan)6requirement(%)ReactiontimetocustomerMarket scale (%)7requirement(day)CompetitiveExpected value of0Environment (1-5)delivery amount (each)Market structure(GjniStrategic alignment (1-5)coefficient)Evaluation resultQualitysystem (1-5)10Table 2. Transport industry KPIpriNoKPI..NameNoKPI.Nametransportation time (day)abilityofkeyprocess(C,)mean square deviation ofassurance of transportationtransportation time(day)quality(1-5)minimum of deliveryamoumt(each)5.SummaryThis paper introduces that KPI is usually used as the standard of judging and choosing partnerbusiness inthefield ofbusiness management.In the Web environment,each logistics companypackages its business into Web service and release it. For alliance enterprises who organize a logisticsactivity,the choice of partnership has changed into the choice ofmassiveWeb services on theinternet.Therefore introducingKPI index intothe definition of Web services will makethe choiceofWeb servicemore accurate and be in line with thetargets oflogistics activities.The paper proposes anew technology management method for the common development of logistics enterprises.And thetechnology has been successfully embedded in the manage system of transport logistics firms. Thefollowing work will be focus on increasing its reliability and flexibility and further promote to otherareas of logisticsReferences[1jFabio Casati, and Ming-Chien Shan, “Models and Languages for Describing and Discovering E-Services (Tutorial)", the International ACM SIGMOD Conference on Management of Data SantaBarbara, California, USA, 2001[2]LiangzhaoZeng,BoualemKalagnanam,andHenryBenatallah,QoS-AwareMiddlewareforWeb Jayant ServicesComposition",IEEETRANSACTIONSONSOFTWAREENGINEERING2004, 30(5), pp. 311-327

get the KPI indexes which transport industry is different from other sectors. These should be an integral part of KPIpri either. Such as Table 2. Table 1. Logistics industry KPIpub Table 2. Transport industry KPIpri 5. Summary This paper introduces that KPI is usually used as the standard of judging and choosing partner business in the field of business management. In the Web environment, each logistics company packages its business into Web service and release it. For alliance enterprises who organize a logistics activity, the choice of partnership has changed into the choice of massive Web services on the internet. Therefore introducing KPI index into the definition of Web services will make the choice of Web service more accurate and be in line with the targets of logistics activities. The paper proposes a new technology management method for the common development of logistics enterprises. And the technology has been successfully embedded in the manage system of transport logistics firms. The following work will be focus on increasing its reliability and flexibility and further promote to other areas of logistics. References [1]Fabio Casati, and Ming-Chien Shan, “Models and Languages for Describing and Discovering E￾Services (Tutorial)”, the International ACM SIGMOD Conference on Management of Data Santa Barbara, California, USA, 2001 [2] Liangzhao Zeng, Boualem Kalagnanam, and Henry Benatallah, “QoS-Aware Middleware for Web Jayant Services Composition”, IEEE TRANSACTIONS ON SOFTWARE ENGINEERING, 2004, 30(5), pp. 311-327

[3] Talluri S, and Baker RC, "A quantitative frame work for designing efficient business processalliances", International Conference on Engineering Management and Control (IEMC), 1996, pp.656-661.[4] NIIIP, "NIIP Reference Architecture Book: Introduction to NIIIP Concepts", NIIIP INC, http ://www.nilip.org, 1999.[5] Ai Weihua, Song Zilin, Wei Lei, and Wu Liang, "Web Service Discovery Based on DomainOntology",Journal of University of Electronic Science and Technology of China,China,2007,36(3)pp.506-509.[6] Yuan Qin, and YangXiaohu,“Research and Application of Web Service Composition Basedon Ontology", Computer Engineering, China, 2007,33(2) pp.79-81.[7] WANG Zhenyou, XIANG Honggui, and ZHAO Juan, “Research on the Intelligent WebService based on the Ontology", Modern Computer, China, 2006, 12, pp.19-21.[8] Daniel, "A Menace QoS Issues in Web Services", IEEE INTERNET COMPUTING, 2002, 6(6)pp.72-75.[9] V Cardellini, E. Casalicchio, M. Colajanni and M. Mambelli, Enhancing a Web-server clusterwithQualityof Servicemechanisms",Proc.of21stIEEE Int'1Performance,Computing,andCommunications Conf: (IPCCC 2002), Phoenix, Arizona, April 2002.[10] Chen, Present Mohapatra Session-Based Overload Control in QoS-Aware Web Servers",IEEEINFOCOM,2002[11] Steven E Leahy, Paul R Murphy, and Richard E Poist,Determinants of Successful LogisticalRelationships: A Third-Party Provider Perspective", Transportation Journal, 1995, pp. 5-13.[12] Karen Tate, “The Elements of A successful logistics partnership", International Journal ofPhysical Distribution & Logistics Management,1996, pp.7-13.[13] Roodhooft F, and Konings J, "Vendor selection and evaluation: An Activity-based CostingApproach, European Journal of Operation Research, 1996 (96),pp.97-102.[14] Kanter, R. M, "Collaborative Advantage: The Art of Alliances." Harvard Business Review 72,1994,pp.96-108[15]Zhihua Qin,“Human Resource Management",People's University ofChina Press,Beijing.2000.[16] Yinhua Gu, Huiqi Wang, and Yaqian Zhang,“Reference Review and the Study of KPI"Neijiang Technology,China, 2008, pp.26-27

[3] Talluri S, and Baker RC, “A quantitative frame work for designing efficient business process alliances”, International Conference on Engineering Management and Control (IEMC), 1996, pp.656- 661. [4] NIIIP, “NIIIP Reference Architecture Book: Introduction to NIIIP Concepts”, NIIIP INC, http ： //www.niiip.org, 1999. [5] Ai Weihua, Song Zilin, Wei Lei, and Wu Liang, “Web Service Discovery Based on Domain Ontology”, Journal of University of Electronic Science and Technology of China, China, 2007, 36(3) pp.506-509. [6] Yuan Qin, and Yang Xiaohu, “Research and Application of Web Service Composition Based on Ontology”, Computer Engineering, China, 2007, 33(2) pp.79-81. [7] WANG Zhenyou, XIANG Honggui, and ZHAO Juan, “Research on the Intelligent Web Service based on the Ontology”, Modern Computer, China, 2006, 12, pp.19-21. [8] Daniel, “A Menace QoS Issues in Web Services”, IEEE INTERNET COMPUTING, 2002, 6(6) pp.72-75. [9] V Cardellini, E. Casalicchio, M. Colajanni and M. Mambelli, “Enhancing a Web-server cluster with Quality of Service mechanisms”, Proc. of 21st IEEE Int'1 Performance, Computing, and Communications Conf: (IPCCC 2002), Phoenix, Arizona, April 2002. [10] Chen, “Present Mohapatra Session-Based Overload Control in QoS-Aware Web Servers”, IEEE INFOCOM, 2002. [11] Steven E Leahy, Paul R Murphy, and Richard E Poist, “Determinants of Successful Logistical Relationships: A Third-Party Provider Perspective”, Transportation Journal, 1995, pp. 5-13. [12] Karen Tate, “The Elements of A successful logistics partnership”, International Journal of Physical Distribution & Logistics Management,1996, pp. 7-13. [13] Roodhooft F, and Konings J, “Vendor selection and evaluation: An Activity-based Costing Approach”, European Journal of Operation Research, 1996 (96), pp. 97-102. [14] Kanter, R. M, "Collaborative Advantage: The Art of Alliances." Harvard Business Review 72, 1994, pp.96-108. [15] Zhihua Qin, “Human Resource Management”, People's University of China Press, Beijing, 2000. [16] Yinhua Gu, Huiqi Wang, and Yaqian Zhang, “Reference Review and the Study of KPI”, Neijiang Technology, China, 2008, pp.26-27