《供应链系统设计与管理》课程教学资源（文献资料）The Impact of Big Data Applications on Supply Chain Management

The Impact of Big Data Applicationson Supply Chain ManagementDong-xiang Zhang and Bin ChengAbstract Through analysis of supply chain management and big data applicationin enterprise survival. This paper researches on the impact of big data under quickreaction, high speed transfer of information and feedback of itself functions onsupply chain performance under supply chain information coordination manage-ment foundation. To figure out the indirect effects of big data applications on supplychain management by slowly seeping into the information coordinationmanagement, an assumption model isestablished and examined by basicquestionnaires.Keywords Big data·Information coordination·Supply chain management1IntroductionSince21century,theeconomyofour countryhasbeingreformed and innovatedrapidly, more and more enterprises have entered a stage of rapid development. Inthe era of economic globalization, economy has being developed towards a ten-dency of integration and an organic whole, which as well provides enterprise withunprecedented opportunities for developing well in fierce competition. The Germanreference of"Industrial 4.0"and the transformation of manufacturing service are thehot topics on how manufacturing industries can get more developments. More andmore enterprises go after the satisfaction from customer and want to provide cus-tomers with high quality products quicker as well as more services. What is more,thethird profit in manufacturing industry,sourcedevelopment and excavation,become focused issue that more managers discuss. Supply chain management,looked as a means of improving the core competitiveness of enterprises is also amajor concern.But there are existing some difficultiesin information coordinationD. Zhang - B. Cheng ()Department of Industrial Engineering, University of Shihezi, Shihezi, Chinae-mail: 972603504@qq.com127Atlantis Press and the author(s) 2016E.Qi (ed.), Proceedings of the 6th International Asia Conferenceon Industrial Engineering and Management Innovation,DOI10.2991/978-94-6239-148-2_13

The Impact of Big Data Applications on Supply Chain Management Dong-xiang Zhang and Bin Cheng Abstract Through analysis of supply chain management and big data application in enterprise survival. This paper researches on the impact of big data under quick reaction, high speed transfer of information and feedback of itself functions on supply chain performance under supply chain information coordination manage￾ment foundation. To figure out the indirect effects of big data applications on supply chain management by slowly seeping into the information coordination management, an assumption model is established and examined by basic questionnaires. Keywords Big data
Information coordination
Supply chain management 1 Introduction Since 21 century, the economy of our country has being reformed and innovated rapidly, more and more enterprises have entered a stage of rapid development. In the era of economic globalization, economy has being developed towards a ten￾dency of integration and an organic whole, which as well provides enterprise with unprecedented opportunities for developing well in fierce competition. The German reference of “Industrial 4.0” and the transformation of manufacturing service are the hot topics on how manufacturing industries can get more developments. More and more enterprises go after the satisfaction from customer and want to provide cus￾tomers with high quality products quicker as well as more services. What is more, the third profit in manufacturing industry, source development and excavation, become focused issue that more managers discuss. Supply chain management, looked as a means of improving the core competitiveness of enterprises is also a major concern. But there are existing some difficulties in information coordination D. Zhang
B. Cheng (&) Department of Industrial Engineering, University of Shihezi, Shihezi, China e-mail: 972603504@qq.com © Atlantis Press and the author(s) 2016 E. Qi (ed.), Proceedings of the 6th International Asia Conference on Industrial Engineering and Management Innovation, DOI 10.2991/978-94-6239-148-2_13 127

128D. Zhang and B. Chengin the process of supply chain management among enterprises, and bring about"Bullwhip"effect,which could bring on immeasurable losses.The informationcoordination of Supply chain has a great significant effect on the whole supplychain development, considered as thekey issues in supply chain management [1].With the development of the internet and the advent of Internet of Things,tremendous information is entering into people's lives. Correspondingly, feedbackof information from eachnode intercommunicates with every singer subsystem ofthe supply chain. However, due to the communication media existed mutuallyamong the non-adjacent nodes of supply chain systems, there are some distortionand delayinthe course ofcommunicatingtheinformation, and haveagreatimpacton the overall efficiency of the supply chain. In addition, the users'recognition anddegree of satisfaction with products and services also be more affected.Ultimately,the aim of customer-centered in the whole supply chain get influenced. In supplychain managementprocess,deviation resulted from information acquisition andanalysis directly affect decision maker for making a decision. Achieving informa-tion fast, timely, efficiently and accurately and further sharing within the supplychain can improve the competitiveness of the whole supply chain [2].2ConceptIntroduction and ModelAssumptions2.1 Supply Chain PerformanceSupply chain, a simple supply business services chain, including production, dis-tribution, usage, recycling and other activities is a customer-facing requirementssystem, which has integrity, stability,nature of dynamic, continuity and so on thatalso owned by general system [3]. It mainly refers that the performance of thesupply chain respond to the market and customer needs as quickly as possible tomaximize customers'satisfaction.Since thetraditional supply chain contacting lesswith each other among nodes,taking more attention on node-oriented internalrelations, flexibility of entire supply chain being not enough yet, it affects thevalue-added activities of business on the whole supply chain and ignore theoperation efficiency of the whole supply chain.2.2 InformationCoordinationWhen facing with increasingly complex supply chain systems, collaborative man-agement of information is especially important.Dueto the asymmetric informationin the supply chain,the serious distortion during theprocess of informationtransfer,interest conflict among supply-chain nodes, and a poor contract relationship,managers are affected on making right decisions and their ability for handlingmarkets once transmitting feedback information is seriously incorrect

in the process of supply chain management among enterprises, and bring about “Bullwhip” effect, which could bring on immeasurable losses. The information coordination of Supply chain has a great significant effect on the whole supply chain development, considered as the key issues in supply chain management [1]. With the development of the internet and the advent of Internet of Things, tremendous information is entering into people’s lives. Correspondingly, feedback of information from each node intercommunicates with every singer subsystem of the supply chain. However, due to the communication media existed mutually among the non-adjacent nodes of supply chain systems, there are some distortion and delay in the course of communicating the information, and have a great impact on the overall efficiency of the supply chain. In addition, the users’ recognition and degree of satisfaction with products and services also be more affected. Ultimately, the aim of customer-centered in the whole supply chain get influenced. In supply chain management process, deviation resulted from information acquisition and analysis directly affect decision maker for making a decision. Achieving informa￾tion fast, timely, efficiently and accurately and further sharing within the supply chain can improve the competitiveness of the whole supply chain [2]. 2 Concept Introduction and Model Assumptions 2.1 Supply Chain Performance Supply chain, a simple supply business services chain, including production, dis￾tribution, usage, recycling and other activities is a customer-facing requirements system, which has integrity, stability, nature of dynamic, continuity and so on that also owned by general system [3]. It mainly refers that the performance of the supply chain respond to the market and customer needs as quickly as possible to maximize customers’ satisfaction. Since the traditional supply chain contacting less with each other among nodes, taking more attention on node-oriented internal relations, flexibility of entire supply chain being not enough yet, it affects the value-added activities of business on the whole supply chain and ignore the operation efficiency of the whole supply chain. 2.2 Information Coordination When facing with increasingly complex supply chain systems, collaborative man￾agement of information is especially important. Due to the asymmetric information in the supply chain, the serious distortion during the process of information transfer, interest conflict among supply-chain nodes, and a poor contract relationship, managers are affected on making right decisions and their ability for handling markets once transmitting feedback information is seriously incorrect. 128 D. Zhang and B. Cheng

129The Impact of Big Data Applications on Supply Chain ManagementUnder the information coordination supply chain management, supply chainrequires upstream and downstream companies to share information with each other.Suppliers need to know what raw materials manufacturers demand, and when theyneed. Manufacturers require retailers to give feedback about how their goods incirculation throughout the market, the entire supply chain is more in need to knowthe degree of customers'satisfaction with the quality of supplychain services.Lifinds that the close cooperation with the main supplier and close contact withcustomers and receiving feedback from our customers can contribute significantlyto improving competitive advantage and performance of the whole supply chain, soastohavean immediate significant impacton enterprises [4].High degree of integration and information sharing of supply chain systems canimprove the ability to respond quickly to the market in supply chain and improvecustomers'degree of satisfaction.Especially on customer demand and sharingsupply information of upstream and downstream can still further help reduce thecosts on inventory, shorten the order cycle to quicken the speed of fund recyclingand enhance the ability of whole supply chain to cope with market environment [5].It shares the information among supply chain partners,leads to them cooperatecloser and even makes the contractual relations among supply chain more closely.2.3ApplicationofBigDataWith the popularization of information technology and the internet, data emphasizehis role increasingly in people's lives, the age of big data being coming [6]. In theMarch of 2012, Obama government of American issued"Big Data Research andDevelopment Initiative",and invested 2 billion dollars to officially start thebig datadevelopmentplans.Theplan aimed to get breakthroughs in the area of scientificresearch and environment biomedicine with big data technology and enhancedmining from the complex flow of useful information to help solve more nationallevel scientific difficulties [7]. Big data, because of its large volume with therenewed and constant velocity,as well as a verity of date structures, known as 3Vfeatures, which bring along unprecedented value for the enterprise [8].In the data context, between the upstream and downstream of supply chain,enterprises share their information with each other.Information from the marketcustomers,or supply chain within the system is all processed and analyzed by theunified information platform and then track, clean, analyze and calculate them.Finally,by the adoption of information technologies,all management softwaremembers of the supply chain management connect seamless and then quicklycommunicate the decision to the whole supply chain node, then in charge ofsupervising and managing them

Under the information coordination supply chain management, supply chain requires upstream and downstream companies to share information with each other. Suppliers need to know what raw materials manufacturers demand, and when they need. Manufacturers require retailers to give feedback about how their goods in circulation throughout the market, the entire supply chain is more in need to know the degree of customers’ satisfaction with the quality of supply chain services. Li finds that the close cooperation with the main supplier and close contact with customers and receiving feedback from our customers can contribute significantly to improving competitive advantage and performance of the whole supply chain, so as to have an immediate significant impact on enterprises [4]. High degree of integration and information sharing of supply chain systems can improve the ability to respond quickly to the market in supply chain and improve customers’ degree of satisfaction. Especially on customer demand and sharing supply information of upstream and downstream can still further help reduce the costs on inventory, shorten the order cycle to quicken the speed of fund recycling and enhance the ability of whole supply chain to cope with market environment [5]. It shares the information among supply chain partners, leads to them cooperate closer and even makes the contractual relations among supply chain more closely. 2.3 Application of Big Data With the popularization of information technology and the internet, data emphasize his role increasingly in people’s lives, the age of big data being coming [6]. In the March of 2012, Obama government of American issued “Big Data Research and Development Initiative”, and invested 2 billion dollars to officially start the big data development plans. The plan aimed to get breakthroughs in the area of scientific research and environment biomedicine with big data technology and enhanced mining from the complex flow of useful information to help solve more national level scientific difficulties [7]. Big data, because of its large volume with the renewed and constant velocity, as well as a verity of date structures, known as 3 V features, which bring along unprecedented value for the enterprise [8]. In the data context, between the upstream and downstream of supply chain, enterprises share their information with each other. Information from the market, customers, or supply chain within the system is all processed and analyzed by the unified information platform and then track, clean, analyze and calculate them. Finally, by the adoption of information technologies, all management software members of the supply chain management connect seamless and then quickly communicate the decision to the whole supply chain node, then in charge of supervising and managing them. The Impact of Big Data Applications on Supply Chain Management 129

130D.Zhang and B. Cheng2.4 ResearchHypothesesAsforthesystems assessmentto the optimizationof supplychain managementunder big data is passed by application of large data, supply chain informationcoordination and supplychainoptimizationstudyonthecausalrelationship combined with structural equation model and then test the impact on enterprises by theusageof big data.Through studying the foreign relevant literature reference, by asking for big dataapplications:"We integratedata and information by the way of thebig data platform(DB1)",Wehavea very strong sense of strategyof information (DB2)";by askingabout supply chain management information coordination “All product-relatedinformation is shared among supply chain (CX1)",and“Wehave a skilled capacityto associate with the production and running information processing platform(CX2)";by asking question on supply chain performance"Supply chain canultimately achieve customer satisfaction (SP1)"and“"All members of the supplychain could act up to market changes with rapid response (SP2)"[9, 12, 13].2.4.1TheRelationship BetweenApplications of Big Dataand InformationCoordinationIn the current age of big data,each cutting-edged Internet company tries to collect,filter, and sort the data, by the means of establishing big data platform, which makeit possible for supply chain information to share information each other amongnodes.By establishing a new data management platform made up of new dateprocessing and analysis arithmetic to clean and sort the various types of structureddata transfer[10].The application of big data will help supply chain informationmanagement get substantive changes.Thus, here is hypotheses 1: supply chain dataapplications have a significant positive impact on information coordination (H1).2.4.2The Relationship Between Applications of Big Data and SupplyChainPerformanceIn the booming era of big data, businesses exploit and analyze massive data toincrease the capacity of market responsiveness and core competitiveness so as tobring with the enterprise more benefits [1l]. To analyze the big data provided bybig data platform,and to give models analysis and predictions on effectivedata, canmake the supply chain more “intelligent", and easier management of supply chaindecisions. Thus here is hypothesis 2: Supply chain data applications have a sig-nificant positive impact on optimizing results from supply chain (H2)

2.4 Research Hypotheses As for the systems assessment to the optimization of supply chain management under big data is passed by application of large data, supply chain information coordination and supply chain optimization study on the causal relationship com￾bined with structural equation model and then test the impact on enterprises by the usage of big data. Through studying the foreign relevant literature reference, by asking for big data applications: “We integrate data and information by the way of the big data platform (DB1)”, “We have a very strong sense of strategy of information (DB2)”; by asking about supply chain management information coordination “All product-related information is shared among supply chain (CX1)”, and “We have a skilled capacity to associate with the production and running information processing platform (CX2)”; by asking question on supply chain performance “Supply chain can ultimately achieve customer satisfaction (SP1)” and “All members of the supply chain could act up to market changes with rapid response (SP2)” [9, 12, 13]. 2.4.1 The Relationship Between Applications of Big Data and Information Coordination In the current age of big data, each cutting-edged Internet company tries to collect, filter, and sort the data, by the means of establishing big data platform, which make it possible for supply chain information to share information each other among nodes. By establishing a new data management platform made up of new date processing and analysis arithmetic to clean and sort the various types of structured data transfer [10]. The application of big data will help supply chain information management get substantive changes. Thus, here is hypotheses 1: supply chain data applications have a significant positive impact on information coordination (H1). 2.4.2 The Relationship Between Applications of Big Data and Supply Chain Performance In the booming era of big data, businesses exploit and analyze massive data to increase the capacity of market responsiveness and core competitiveness so as to bring with the enterprise more benefits [11]. To analyze the big data provided by big data platform, and to give models analysis and predictions on effective data, can make the supply chain more “intelligent”, and easier management of supply chain decisions. Thus here is hypothesis 2: Supply chain data applications have a sig￾nificant positive impact on optimizing results from supply chain (H2). 130 D. Zhang and B. Cheng

131The Impact of Big Data Applications on Supply Chain ManagementFig. 1 Theoretical modelInformationCoordinatH3 (+)SupplyChainsH1/+PerformanceH2(+)Applicatioof Big Data2.4.3TheRelationshipBetween InformationCoordinationandSupplyChainPerformanceAssured authenticity and high level to share information, attach great importance tosharinginformation,avoidingthedistortionof informationanditsinformationrisk.willhave apositiveimpactonthesupplychain[12].Supplychaininformationsharing among dramatically eliminates the“bullwhip",so that closer contractualrelations between upstream and downstream supply chain can help improvingsupply chain efficiency, increasing supply chain market responsiveness, improvingcompetitiveness.Hypothesis 3: supply chain information coordination has a sig-nificantpositiveimpacton supplychainperformance(H3)Based on aforementioned comprehensive analysis, a theoretical model is pre-sented and as shown in Fig. 1.3Data MeasurementandModelAnalysis3.1SourceofSampleDomestic and foreign research on similar topics and theories of knowledge con-structionismoremature,sofor selection ofvariableandmeasurementof indicatorswe design questionnaires principally refer the references and on the basis of ourcountry's situation. The completed questionnaires distribute through variouschannels to different levels of managers who is from various types of enterprisesand different industries, and questionnaires were eventually recovered 132, the datahas a certain degree of representativeness.3.2Reliability and Validity of the SampleReliability and validity of sample data, ensure the good fit of the assumed model.By SPSS19.0 statistical reliability analysis software can be effective usingCronbach's Alpha coefficients, generally considered Cronbach's a coefficient is

2.4.3 The Relationship Between Information Coordination and Supply Chain Performance Assured authenticity and high level to share information, attach great importance to sharing information, avoiding the distortion of information and its information risk, will have a positive impact on the supply chain [12]. Supply chain information sharing among dramatically eliminates the “bullwhip”, so that closer contractual relations between upstream and downstream supply chain can help improving supply chain efficiency, increasing supply chain market responsiveness, improving competitiveness. Hypothesis 3: supply chain information coordination has a sig￾nificant positive impact on supply chain performance (H3). Based on aforementioned comprehensive analysis, a theoretical model is pre￾sented and as shown in Fig. 1. 3 Data Measurement and Model Analysis 3.1 Source of Sample Domestic and foreign research on similar topics and theories of knowledge con￾struction is more mature, so for selection of variable and measurement of indicators we design questionnaires principally refer the references and on the basis of our country’s situation. The completed questionnaires distribute through various channels to different levels of managers who is from various types of enterprises and different industries, and questionnaires were eventually recovered 132, the data has a certain degree of representativeness. 3.2 Reliability and Validity of the Sample Reliability and validity of sample data, ensure the good fit of the assumed model. By SPSS19.0 statistical reliability analysis software can be effective using Cronbach’s Alpha coefficients, generally considered Cronbach’s α coefficient is Information Coordination Applications of Big Data H3 (+) H1 (+) H2 (+) Supply Chains Performance Fig. 1 Theoretical model The Impact of Big Data Applications on Supply Chain Management 131

132D. Zhang and B. ChengTable1 Reliability analysis and factor analysisVariableQuestionFactor of load-carrying capacityCronbach's aCXI0.7990.821Information coordinationCX20.826DB10.8010.794Application of big dataDB20.674SPI0.8440.811Supply chain performanceSP20.747greater than 0.7, samples with high reliability [13]. Table 1 shows each variable hasa good reliability. Validity analysis for structures, response variables correspondingto each factor and its load-carrying capacity study of factors, generally the nor-malization factorload of absolutevaluesgreaterthan 0.6 thinks is appropriate[14].3.3Model FitnessThefitnessofdatamodel isusedtodetectwitchdegreetheselected sampleofdataand the degree of adaptation of thewholemodel is fit ornot.ByAMOS17.0forstructural equation modeling analysis outputs the following data, the results asshown in Table 2.3.4ResultsAccording to the conceptual model in the AMOS17.0 in the structural equationmodel,it successful outputsthe structural equationmodel after inputthedateresult.Table 2 Part adaptation of the model statistics and statisticsModelAdapterAdapterAdapter indexadaptationstandardAbsolute fit22.127Chi-square values ()The smaller thebettermeasurement0.0190.90Fit wellGoodness-of-fitindex (GFI)0.931>0.90Fit wellIncremental fitNormed fit index (NFI)measurement0.949>0.90Fit wellIncremental fit index (IFI)Comparative fit index0.947>0.90Fit well(CFI)

greater than 0.7, samples with high reliability [13]. Table 1 shows each variable has a good reliability. Validity analysis for structures, response variables corresponding to each factor and its load-carrying capacity study of factors, generally the nor￾malization factor load of absolute values greater than 0.6 thinks is appropriate [14]. 3.3 Model Fitness The fitness of data model is used to detect witch degree the selected sample of data and the degree of adaptation of the whole model is fit or not. By AMOS17.0 for structural equation modeling analysis outputs the following data, the results as shown in Table 2. 3.4 Results According to the conceptual model in the AMOS17.0 in the structural equation model, it successful outputs the structural equation model after input the date result. Table 1 Reliability analysis and factor analysis Variable Question Factor of load-carrying capacity Cronbach’s α Information coordination CX1 0.799 0.821 CX2 0.826 Application of big data DB1 0.801 0.794 DB2 0.674 Supply chain performance SP1 0.844 0.811 SP2 0.747 Table 2 Part adaptation of the model statistics and statistics Adapter index Model adaptation Adapter standard Adapter Absolute fit measurement Chi-square values (χ 2 ) 22.127 The smaller the better Root mean square residual (RMR) 0.019 0.90 Fit well Incremental fit measurement Normed fit index (NFI) 0.931 >0.90 Fit well Incremental fit index (IFI) 0.949 >0.90 Fit well Comparative fit index (CFI) 0.947 >0.90 Fit well 132 D. Zhang and B. Cheng

133The Impact of Big Data Applications on Supply Chain Managementeps2epe3eps1eps4.64.68.71.56CX1CX2SP2SP1AR.80.84.83.75.57InformationSupply Chainesp8CoordinationPerformance67.63.33Applicationof Big Data.80.67Chi-square = 22.13DB1DB2df=6p=.00.64-45sp5esp6Standardized EstimatesFig.2 Results of structural equation modelsTable 3 Test resultsPAssumingPath directionStandard pathVerificationcoefficientHI***0.697Application of bigSupportdata → information**H2Application of big data0.350Support→ supplychainperformanceH3***0.558Information coordination→supplySupportchain performanceShown in Fig. 2 and in Table 3. Including data through the application of infor-mation coordination on supply chain performance, belongs to the indirect positiveeffects.4Summary and AnalysisThrough conducting a questionnaire survey on several enterprises, and examiningthe model assumptions analysis of structure model, a result comes out, whichproves hypothesis H1, H2, and H3

Shown in Fig. 2 and in Table 3. Including data through the application of infor￾mation coordination on supply chain performance, belongs to the indirect positive effects. 4 Summary and Analysis Through conducting a questionnaire survey on several enterprises, and examining the model assumptions analysis of structure model, a result comes out, which proves hypothesis H1, H2, and H3. .64 CX1 .68 CX2 .71 SP2 .56 SP1 .64 DB1 .45 DB2 .40 Information Coordination .67 Supply Chain Performance eps1 eps2 eps3 eps4 Application of Big Data esp5 esp6 .80 .83 .84 .75 .80 .67 .57 .33 .63 eps7 esp8 Chi-square = 22.13 df = 6 p = .00 Standardized Estimates Fig. 2 Results of structural equation models Table 3 Test results Assuming Path direction Standard path coefficient P Verification H1 Application of big data → information 0.697 *** Support H2 Application of big data → supply chain performance 0.350 ** Support H3 Information coordination → supply chain performance 0.558 *** Support The Impact of Big Data Applications on Supply Chain Management 133

134D. Zhang and B. ChengSupply chain collaborative information'seffects on supply chain optimizationare significant.Through information collaborative,supply chain managementbecomes more convenient, thetransfer of all parts of supply chain becomes moreaccurate and quicker. It pushed the efficiency of production become higher and,thus supply chain reacts faster on market; requirements and needs of customers canalso be responded to all circles timely.Supply chain can satisfy on customerprovides quality of service, thus, service of high quality can be achieved to meet theexpectations of customers.Compared with collaborative information,the positive effect of big data onsupply chain is not that evident.Big data applications works through collaborativeinformation management methods have a positive impact on supply chain opti-mization, so assumption Hl is the model of most obvious positive effects amongthree, which is expectedtoprovethe influenceof big data.Few existing literature focus on application of bigdata, not mentioned thoserefer to supply chain management.The survey hopes to bring some inspirations onthe application of big data to supply chain management.In the manufacturingindustry-to-manufacturing service industry transition period after Industrial 4.0, bigdata applicationhasbecomeapowerful weaponof modern enterprisemanagement.Through collecting huge amount of information,enterprise can grasp the orientationof the market and elevate the service quality to satisfy customers; what's more,logistics transportation cost is decreased,partial complex logistics transportationcostconvertsto simple treatment costof information stream.On theplatform of bigdata application, application software is well-connected, which enables the inte-gration of supply chain. Future researches can pay more attention to the big dataapplicationtosupplychainmanagement.References1.Chopra S, Meindl P (2008) Supply chain management: strategy, planning, and operation.Tsinghua University Press, Beijing 5(1):25-812. Sezen B (2008) Relative effects of design, integration and information sharing on supply chainperformance.SupplyChainManageIntJ13(3):233-2403. Anbang D, Liao Z (2002) Supply chain management research. Indus Eng 05: 16-20(Chinese)4.Li S,Ragu-Nathan B, Ragu Nathan TS(2006)The impact of supply chain managementpractices on competitiveadvantage and organizational performance.Omega 34(2):107-1245. Lee HL (2000) Creating value through supply chain integration. Supply Chain Manage Rev 4(4):6306.Li G, Cheng X (2012)Big data: future technology and other strategic areas of economic andsocial development-big data: current status and scientific thinking. Chin Acad Sci J06:647-657(Chinese)7. Meng XF, Ci X (2013) Big data management: concepts, techniques and challenges. Res DevComput 01:146-169 (Chinese)8. Liang H (2014) Cloud logistics and large data changes to the logistics model. China Circ Econ05:41-45 (Chinese)

Supply chain collaborative information’s effects on supply chain optimization are significant. Through information collaborative, supply chain management becomes more convenient, the transfer of all parts of supply chain becomes more accurate and quicker. It pushed the efficiency of production become higher and, thus supply chain reacts faster on market; requirements and needs of customers can also be responded to all circles timely. Supply chain can satisfy on customer provides quality of service, thus, service of high quality can be achieved to meet the expectations of customers. Compared with collaborative information, the positive effect of big data on supply chain is not that evident. Big data applications works through collaborative information management methods have a positive impact on supply chain opti￾mization, so assumption H1 is the model of most obvious positive effects among three, which is expected to prove the influence of big data. Few existing literature focus on application of big data, not mentioned those refer to supply chain management. The survey hopes to bring some inspirations on the application of big data to supply chain management. In the manufacturing industry-to-manufacturing service industry transition period after Industrial 4.0, big data application has become a powerful weapon of modern enterprise management. Through collecting huge amount of information, enterprise can grasp the orientation of the market and elevate the service quality to satisfy customers; what’s more, logistics transportation cost is decreased, partial complex logistics transportation cost converts to simple treatment cost of information stream. On the platform of big data application, application software is well-connected, which enables the inte￾gration of supply chain. Future researches can pay more attention to the big data application to supply chain management. References 1. Chopra S, Meindl P (2008) Supply chain management: strategy, planning, and operation. Tsinghua University Press, Beijing 5(1):25–81 2. Sezen B (2008) Relative effects of design, integration and information sharing on supply chain performance. Supply Chain Manage Int J 13(3):233–240 3. Anbang D, Liao Z (2002) Supply chain management research. Indus Eng 05: 16–20(Chinese) 4. Li S, Ragu-Nathan B, Ragu Nathan TS (2006) The impact of supply chain management practices on competitive advantage and organizational performance. Omega 34(2):107–124 5. Lee HL (2000) Creating value through supply chain integration. Supply Chain Manage Rev 4 (4):6–30 6. Li G, Cheng X (2012) Big data: future technology and other strategic areas of economic and social development—big data: current status and scientific thinking. Chin Acad Sci J 06:647–657 (Chinese) 7. Meng XF, Ci X (2013) Big data management: concepts, techniques and challenges. Res Dev Comput 01:146–169 (Chinese) 8. Liang H (2014) Cloud logistics and large data changes to the logistics model. China Circ Econ 05:41–45 (Chinese) 134 D. Zhang and B. Cheng

135The Impact of Big Data Applications on Supply Chain Management9. Ye F, Xue Y. Information sharing among supply chain partners on operational performance ofthe indirect mechanismrelational capital as an intermediate variable. Chin J Manage Sci06:112-125 (Chinese)10. Li J (2014) New thinking on big data and statistics. Stat Stud 01:10-17 (Chinese)11. Sultan N (2013) Knowledge management in the age of cloud computing and web 2.0:experiencing the power of disruptive innovations. Int J Inf Manage 33(1):160-16512. Zeng M, Wu Q (2012) Supply chain integration supply chain design, research, informationsharing and supply chain performance. Indus Eng Manage 04:814 (Chinese)13. Wang L, Dai Y (2013) Empirical research on the influencing factors of incentive mechanismin supply chain. Indus Eng Manage 01:13-19 + 24 (Chinese)14. Fornell C, Larcher FE (1981) Valuating structural equation models with unobservablevariables and measurement error. J Mark Res 18(1):29-50

9. Ye F, Xue Y. Information sharing among supply chain partners on operational performance of the indirect mechanism—relational capital as an intermediate variable. Chin J Manage Sci 06:112–125 (Chinese) 10. Li J (2014) New thinking on big data and statistics. Stat Stud 01:10–17 (Chinese) 11. Sultan N (2013) Knowledge management in the age of cloud computing and web 2.0: experiencing the power of disruptive innovations. Int J Inf Manage 33(1):160–165 12. Zeng M, Wu Q (2012) Supply chain integration supply chain design, research, information sharing and supply chain performance. Indus Eng Manage 04:8–14 (Chinese) 13. Wang L, Dai Y (2013) Empirical research on the influencing factors of incentive mechanism in supply chain. Indus Eng Manage 01:13–19 + 24 (Chinese) 14. Fornell C, Larcher FE (1981) Valuating structural equation models with unobservable variables and measurement error. J Mark Res 18(1):29–50 The Impact of Big Data Applications on Supply Chain Management 135