Emerald InsightTheInternationalJournal ofLogisticsManagementSmartsupplychainmanagement:areviewandimplicationsforfutureresearchLifangWuXiaohangYueAlanJinDavidC.YenArticleinformation:To cite this document:LifangWuXiaohangYueAlanJinDavidC.Yen,(2016),"Smartsupplychainmanagement:areviewandimplicationsforfutureresearch",TheInternationalJournalofLogisticsManagement,Vol.27Iss2d)Pp.395-417inPermanentlinktothisdocument:2http://dx.doi.org/10.1108/lJLM-02-2014-0035ADownloadedon:29November2016,At:22:44(PT)二References:thisdocumentcontainsreferencesto96otherdocuments.Tocopythisdocument:permissions@emeraldinsight.com2Thefulltextofthisdocumenthasbeendownloaded957timessince2016*CUserswho downloaded thisarticle alsodownloaded:1(2016)."Towardscloud-basedsupplychainprocesses:Designingareferencemodelandelementsofaresearchagenda",TheInternationalJournalof LogisticsManagement,Vol.27Iss2pp.438-462http://dx.doi.0rg/10.1108/lJLM-09-2014-0139O(2016),"Assessingthe impactofbusinessuncertaintyonsupplychain integration",The3internationalJournalof LogisticsManagement,Vol.27Iss2pp.463-485http://dx.doi.org/10.1108/8IJLM-11-2014-0175SJOEAccesstothisdocumentwasgrantedthroughanEmerald subscriptionprovidedbyemerald-srm:313548[]uForAuthorsIfyouwouldliketowriteforthis,oranyotherEmeraldpublication,thenpleaseuseourEmeraldforAuthors serviceinformationabouthowtochoosewhichpublicationtowriteforandsubmission1guidelinesareavailableforall.Pleasevisitwww.emeraldinsight.com/authorsformoreinformationAboutEmeraldwww.emeraldinsight.comUMOCEmeraldisaglobalpublisherlinkingresearchandpracticetothebenefitof society.Thecompanymanages aportfolioof more than29o journals andover2,350books andbook series volumes,aswellasprovidinganextensiverangeofonlineproductsandadditionalcustomerresourcesandservices.EmeraldisbothCOUNTER4andTRANSFERcompliant.TheorganizationisapartneroftheCommitteeonPublicationEthics(COPE)andalsoworkswithPorticoandtheLOCKSSinitiativefordigitalarchivepreservation.*Relatedcontentanddownloadinformationcorrectattimeofdownload
The International Journal of Logistics Management Smart supply chain management: a review and implications for future research Lifang Wu Xiaohang Yue Alan Jin David C. Yen Article information: To cite this document: Lifang Wu Xiaohang Yue Alan Jin David C. Yen , (2016),"Smart supply chain management: a review and implications for future research", The International Journal of Logistics Management, Vol. 27 Iss 2 pp. 395 - 417 Permanent link to this document: http://dx.doi.org/10.1108/IJLM-02-2014-0035 Downloaded on: 29 November 2016, At: 22:44 (PT) References: this document contains references to 96 other documents. To copy this document: permissions@emeraldinsight.com The fulltext of this document has been downloaded 957 times since 2016* Users who downloaded this article also downloaded: (2016),"Towards cloud-based supply chain processes: Designing a reference model and elements of a research agenda", The International Journal of Logistics Management, Vol. 27 Iss 2 pp. 438-462 http://dx.doi.org/10.1108/IJLM-09-2014-0139 (2016),"Assessing the impact of business uncertainty on supply chain integration", The International Journal of Logistics Management, Vol. 27 Iss 2 pp. 463-485 http://dx.doi.org/10.1108/ IJLM-11-2014-0175 Access to this document was granted through an Emerald subscription provided by emeraldsrm:313548 [] For Authors If you would like to write for this, or any other Emerald publication, then please use our Emerald for Authors service information about how to choose which publication to write for and submission guidelines are available for all. Please visit www.emeraldinsight.com/authors for more information. About Emerald www.emeraldinsight.com Emerald is a global publisher linking research and practice to the benefit of society. The company manages a portfolio of more than 290 journals and over 2,350 books and book series volumes, as well as providing an extensive range of online products and additional customer resources and services. Emerald is both COUNTER 4 and TRANSFER compliant. The organization is a partner of the Committee on Publication Ethics (COPE) and also works with Portico and the LOCKSS initiative for digital archive preservation. *Related content and download information correct at time of download. Downloaded by Huazhong University of Science and Technology At 22:44 29 November 2016 (PT)
The current issue and full text archive of this journal is available on Emerald Insight atwww.emeraldinsight.com/0957-4093.htmSmartsupplySmart supply chain management:chaina review and implicationsmanagementfor future research395Lifang WuWilliamsCollege ofBusiness,XaierUniversity,Cincinnati, Ohio,USAReceived 9 September 2013Xiaohang Yue1Revised 27 February 20143 March 2015SheldonB.Lubar Schoolof Business,University of Wisconsin-Milwaukee18 May 2015Milwaukee,Wisconsin,UsAAccepted 5 Jume 2015Alan JinDepartment of Management,Wiliams College ofBusiness,Xavier University,Cincinnati,Ohio,USA, andDavid C. YenSUNYCollege atOneonta,Oneonta,NewYork,USAAbstractPurpose -As traditional supply chains are increasingly becoming intelligent with more objectsembedded with sensorsand better communication,intelligent decisionmaking and automationcapabilities,the newsmartsupplychainpresents unprecedented opportunitiesfor achievingcostpuereduction and enhancing efficiency improvement.The purpose of this paper is to studyand explore thecurrents status and remaining issues of smart supply chainmanagement.Design/methodology/approach-A literature review is conducted to synthesize the earlier work in品this area, and to conceptualize and discuss the smart supply chain characteristics.Further, the authorsformulate and investigate five key research topics including information management,ITSinfrastructure,process automation,advancedanalytics,and supplychain integration.Findings - Studies in those aforementioned subject fields are reviewed, categorized, and analyzedbased on the review questions defined in the study.It is notable that while thetopics of converging3atoms withdigits areincreasinglyattractingattentionfrom researchers and practitionersalikethereBuoaremanymoreinterestingresearchquestions needingtobeaddressedzenOriginality/value -The paper provides original and relevant guidance for supply chain二management researchers and practitioners on developing smart supply chains.KqKeywords RFID, Supply chain managementaeooPaper type Literature review1.IntroductionSupplychain management (SCM) speaks of"having theright item in theright quantity attherighttimeat the rightplacefor theright price in theright condition totherightcustomer"(Mallik,2010).However,duetothecomplexity,uncertainty,andotherfactorsinvolved,mostof thereal supplychains areknownforhavingmany supply-demandmismatchproblems suchas overstocking,stockout,anddeliverydelays whichhavelongEmeraldbeenpopularresearchtopicsinthebusinessmanagementliterature(Wongetal,20o12)Asalways,cheaper,faster,and betterhasbeenthemantraforsupplychainmanagersThe Intermational Journal ofMeanwhile,supplychainsarebecomingmorecomplex,costly,uncertain,andvulnerableLogistiVol 27 No. 2, 2016To deal effectively with the increasing challenges, supply chains must become a lotpp. 395-417smarter (Butner,2010).Taking full advantage of improvements in such areas asCEmerald Group Publishing Limited0957-4098semiconductor,computer science,andotherengineeringtechnologies,thenewversion ofDOI 10.1108/JLM-02-2014-0035
Smart supply chain management: a review and implications for future research Lifang Wu Williams College of Business, Xavier University, Cincinnati, Ohio, USA Xiaohang Yue Sheldon B. Lubar School of Business, University of Wisconsin-Milwaukee, Milwaukee, Wisconsin, USA Alan Jin Department of Management, Williams College of Business, Xavier University, Cincinnati, Ohio, USA, and David C. Yen SUNY College at Oneonta, Oneonta, New York, USA Abstract Purpose – As traditional supply chains are increasingly becoming intelligent with more objects embedded with sensors and better communication, intelligent decision making and automation capabilities, the new smart supply chain presents unprecedented opportunities for achieving cost reduction and enhancing efficiency improvement. The purpose of this paper is to study and explore the currents status and remaining issues of smart supply chain management. Design/methodology/approach – A literature review is conducted to synthesize the earlier work in this area, and to conceptualize and discuss the smart supply chain characteristics. Further, the authors formulate and investigate five key research topics including information management, IT infrastructure, process automation, advanced analytics, and supply chain integration. Findings – Studies in those aforementioned subject fields are reviewed, categorized, and analyzed based on the review questions defined in the study. It is notable that while the topics of converging atoms with digits are increasingly attracting attention from researchers and practitioners alike, there are many more interesting research questions needing to be addressed. Originality/value – The paper provides original and relevant guidance for supply chain management researchers and practitioners on developing smart supply chains. Keywords RFID, Supply chain management Paper type Literature review 1. Introduction Supply chain management (SCM) speaks of“having the right item in the right quantity at the right time at the right place for the right price in the right condition to the right customer” (Mallik, 2010). However, due to the complexity, uncertainty, and other factors involved, most of the real supply chains are known for having many supply-demand mismatch problems such as overstocking, stockout, and delivery delays which have long been popular research topics in the business management literature (Wong et al., 2012). As always, cheaper, faster, and better has been the mantra for supply chain managers. Meanwhile, supply chains are becoming more complex, costly, uncertain, and vulnerable. To deal effectively with the increasing challenges, supply chains must become a lot smarter (Butner, 2010). Taking full advantage of improvements in such areas as semiconductor, computer science, and other engineering technologies, the new version of The International Journal of Logistics Management Vol. 27 No. 2, 2016 pp. 395-417 © Emerald Group Publishing Limited 0957-4093 DOI 10.1108/IJLM-02-2014-0035 Received 9 September 2013 Revised 27 February 2014 3 March 2015 18 May 2015 Accepted 5 June 2015 The current issue and full text archive of this journal is available on Emerald Insight at: www.emeraldinsight.com/0957-4093.htm 395 Smart supply chain management Downloaded by Huazhong University of Science and Technology At 22:44 29 November 2016 (PT)
JLMsupply chain seeks to establish a large-scale intelligent infrastructure for merging datainformation,physical objects,products,and business processes together (Schuster et al.27,22007).Forexamplethefactoriesequippedwithsmartequipmentandinstrumentscanfulfill orders withglobal teams, intelligent analytics,and dynamic systems allacross thefarthest stages of the valuechain(Hessman,2013).For sure,companiesthat takeadvantageoftheseaforementionedcapabilitiesstandtogainagainstcompetitorsthatdo396not.Nowonder thereareabundant examples of smart supplychainapplications inexistence,forexample,smarttransportationmanagementsystem,and smartfactory.In the literature,a number of distinctive termswere used to describethenewaeacommunicatedglobal business systemstofulfillcustomerorders,suchas e-supply chain(AkyuzandRehan,2009),ambientintelligence(Klochetal.,2010),InternetofThings(loT)(Ma, 2011), industrial intermet (Evans and Annunziata, 2012),physical internet(Montreuil,2011),smartfactory (Hessman,2013),smartenvironment(Weiseretal,1999)and smarter supply chain (Butner,2010).While e-commercepromotes transactionsperformed on thetraditional internet,theconcept of“e-supply chain"makes one furtherstepto integrateprocessesacrosssupplychainstages(AkyuzandRehan,2009).Further,IoT referstothe nextgeneration internet whereconnectingphysical thingsthroughanetworkhasthecapabilityofexchanginginformationaboutthemselvesandtheirsurroundings(Gubbietal,2013).Thesethingsmay includeartifacts,machines,productsand gizmos (unstable, modifiable things) (Sundmaeker et al, 2010). It is evident in theliteraturethatthecurrentloTresearchfocussesontechnologies (suchassignal,networkcommunication,security)and applications (Sundmaekeretal,2010).GE's industrialinternet convergesglobal industrial systems with thepowerof advanced computinganalytics,low-cost sensing,and newlevels of connectivity permitted by theinternet(Evans and Annunziata,2012).Inaddition,a smartenvironment is definedas“thephysical world that is richly and invisibly interwoven with sensors, actuators, displaysandcomputationalelements,embeddedseamlesslyintheevervdayobjectsofourlivesand connected through a continuous network"(Weiser et al,1999).IBM particularlyproposes three characteristics (e.g. instrumented, interconnected, and intelligent) for thenextgenerationsmartersupplychains(Butner,2010)It is evident that these aforementioned concepts such as e-supply chain, IoT, smartfactory,and industrial internet, havebeenused to represent larger and morecomplicatedbusinesssystems:from isolated RFIDapplicationto local IoTimplementation,to smartfactory,and then topart oftheglobal supply chainnetworkwithinthesamecompany.Followingthistrend,weintendtodefinea"smartsupplychain"as the new interconnectedbusiness systemwhichextendsfrom isolatedlocal,and single-companyapplications to supply chain wide systematic smartimplementations.Thesmart supply chain would possessmostof thefeatureswediscussedabove,includingtechnologies suchasloT,smartmachines,andintelligentinfrastructure,and capabilities such as interconnectivity,fullyenablingdata collectionand real-time communication across all supply chain stages, intelligent decisionmaking,and efficient and responsiveprocesses to better serve customers.Asthephysicalworlditselfisbecomingatypeofinformationsystemwheresensorsandtinydevicesarelinkedthroughwiredand/orwirelessnetworks,businessmodelsbased on today's largely static-information architectures face many challenges as newwaysofcreatingcustomervaluearise(Bughinetal,20i0).Thedeepintegrationofthedigital world with the physical world holds the potential to bring a profoundtransformation toglobal supply chains.However,despitetheconsensus on thegreatpotentialofthesmartconceptandthesignificantprogressinanumberofenabling
supply chain seeks to establish a large-scale intelligent infrastructure for merging data, information, physical objects, products, and business processes together (Schuster et al., 2007). For example, the factories equipped with smart equipment and instruments can fulfill orders with global teams, intelligent analytics, and dynamic systems all across the farthest stages of the value chain (Hessman, 2013). For sure, companies that take advantage of these aforementioned capabilities stand to gain against competitors that do not. No wonder there are abundant examples of smart supply chain applications in existence, for example, smart transportation management system, and smart factory. In the literature, a number of distinctive terms were used to describe the new communicated global business systems to fulfill customer orders, such as e-supply chain (Akyuz and Rehan, 2009), ambient intelligence (Kloch et al., 2010), Internet of Things (IoT) (Ma, 2011), industrial internet (Evans and Annunziata, 2012), physical internet (Montreuil, 2011), smart factory (Hessman, 2013), smart environment (Weiser et al., 1999), and smarter supply chain (Butner, 2010). While e-commerce promotes transactions performed on the traditional internet, the concept of “e-supply chain” makes one further step to integrate processes across supply chain stages (Akyuz and Rehan, 2009). Further, IoT refers to the next generation internet where connecting physical things through a network has the capability of exchanging information about themselves and their surroundings (Gubbiet al., 2013). These things may include artifacts, machines, products, and gizmos (unstable, modifiable things) (Sundmaeker et al., 2010). It is evident in the literature that the current IoT research focusses on technologies (such as signal, network, communication, security) and applications (Sundmaeker et al., 2010). GE’s industrial internet converges global industrial systems with the power of advanced computing, analytics, low-cost sensing, and new levels of connectivity permitted by the internet (Evans and Annunziata, 2012). In addition, a smart environment is defined as “the physical world that is richly and invisibly interwoven with sensors, actuators, displays, and computational elements, embedded seamlessly in the everyday objects of our lives, and connected through a continuous network” (Weiser et al., 1999). IBM particularly proposes three characteristics (e.g. instrumented, interconnected, and intelligent) for the next generation smarter supply chains (Butner, 2010). It is evident that these aforementioned concepts such as e-supply chain, IoT, smart factory, and industrial internet, have been used to represent larger and more complicated business systems: from isolated RFID application to local IoT implementation, to smart factory, and then to part of the global supply chain network within the same company. Following this trend, we intend to define a “smart supply chain” as the new interconnected business system which extends from isolated, local, and single-company applications to supply chain wide systematic smart implementations. The smart supply chain would possess most of the features we discussed above, including technologies such as IoT, smart machines, and intelligent infrastructure, and capabilities such as interconnectivity, fully enabling data collection and real-time communication across all supply chain stages, intelligent decision making, and efficient and responsive processes to better serve customers. As the physical world itself is becoming a type of information system where sensors and tiny devices are linked through wired and/or wireless networks, business models based on today’s largely static-information architectures face many challenges as new ways of creating customer value arise (Bughin et al., 2010). The deep integration of the digital world with the physical world holds the potential to bring a profound transformation to global supply chains. However, despite the consensus on the great potential of the smart concept and the significant progress in a number of enabling 396 IJLM 27,2 Downloaded by Huazhong University of Science and Technology At 22:44 29 November 2016 (PT)
technologies,there isageneral lackofan integrated vision onhowtorealize thesystemSmart supplyand theassociated value (Lopezet al, 2012).chainWe intend to conduct a systematic review in this paperto examine the relevantmanagementliteratureonsmartsupplychainmanagement(SSCM):businessmanagementtopicsrelatedto thedesign, management,and improvement of smart supplychainsSpecifically,thepaperaims at summarizing thekey SSCMresearch findings in existenceand discussing397the remaining research issues. In particular, this paper has the following objectives:(l)to complete a surveyof the literatureassociated with SSCM;)9100(2)to conceptualize thekey issues and develop a framework pertinent to SSCM;(3)to identify several key emerging phenomenon in the smart supply chainapplications and toassociatethe prior academic research with thesedevelopments; and(4)to highlight the remaining research issues in this field.The reminder of the paper is structured as follows. The next further introduces themethodologicalaspectsoftheliteraturereview.Thisisfollowedbythecontentanalysisoftheliteratureineachofthefivekeyresearchareasincludinginformation,IT,processautomation,advancedanalytics,and supplychainintegration.Then,adiscussionofcurrent statusandremaining research issues of SSCM is presented Thepaperconcludes by summarizing the key findings of the review and identifying theimplicationsforpractitionersandresearchers.Lpue2.ReviewmethodologyA literature review is a systematic, transparent, and reproducible design foridentifying,evaluating,and interpreting theexisting literature(Fink,2005).Thecriticalanalysis ofthe research papers identifies systematic patterns, synthesizes knowledge,reveals unnoticed trends, and gaps in the literature, all contributing to theorydevelopment (Meredith,1993).We recognize that SSCMisa quickly evolving conceptthat is researched and discussed in many relevant disciplines, e.g, isolated smartoaeohardwareapplicationsareoftenstudiedinengineeringfield,andadvancedanalyticsisrepeatedly investigated in data analysis and information system research.The researchfield has been quite fragmented and divergent. In order to guide our literature review,we begin with defining the following review questions:RQ1.What is the current status of smart supply chain research and applications?RQ2.What arethemajorissues and debates about thetopics?Theanswers to theabove questionscan providebuilding blocks for a conceptualframeworkalongwithabasisoftheorydevelopment.Whiletryingtoplacethestudyinabroadercontext,weadmitSSCMhasdeeprootsinmanytraditionalfieldssuchoptimizationand supplychainnetwork.Whenconductingliteraturesearch,wefindusing generic search words such as inventory,network, logistics, and e-businessresultedinanoverwhelmingnumberofarticleswhicharelessrelevanttoSSCMandrelatively outdated.Instead, weuse a retrospective approach to find the most recentarticlesonsmartsupplychainandworkbackwardstorefineoursearchkeywords.which include supply chain,smart,information system,loT,advanced analytics,bigdata,automation,and supplychain integration.Thesekeywordsarefrequentlyused intherecentsmartsupplychainliterature
technologies, there is a general lack of an integrated vision on how to realize the system and the associated value (Lopez et al., 2012). We intend to conduct a systematic review in this paper to examine the relevant literature on smart supply chain management (SSCM): business management topics related to the design, management, and improvement of smart supply chains. Specifically, the paper aims at summarizing the key SSCM research findings in existence and discussing the remaining research issues. In particular, this paper has the following objectives: (1) to complete a survey of the literature associated with SSCM; (2) to conceptualize the key issues and develop a framework pertinent to SSCM; (3) to identify several key emerging phenomenon in the smart supply chain applications and to associate the prior academic research with these developments; and (4) to highlight the remaining research issues in this field. The reminder of the paper is structured as follows. The next further introduces the methodological aspects of the literature review. This is followed by the content analysis of the literature in each of the five key research areas including information, IT, process automation, advanced analytics, and supply chain integration. Then, a discussion of current status and remaining research issues of SSCM is presented. The paper concludes by summarizing the key findings of the review and identifying the implications for practitioners and researchers. 2. Review methodology A literature review is a systematic, transparent, and reproducible design for identifying, evaluating, and interpreting the existing literature (Fink, 2005). The critical analysis of the research papers identifies systematic patterns, synthesizes knowledge, reveals unnoticed trends, and gaps in the literature, all contributing to theory development (Meredith, 1993). We recognize that SSCM is a quickly evolving concept that is researched and discussed in many relevant disciplines, e.g., isolated smart hardware applications are often studied in engineering field, and advanced analytics is repeatedly investigated in data analysis and information system research. The research field has been quite fragmented and divergent. In order to guide our literature review, we begin with defining the following review questions: RQ1. What is the current status of smart supply chain research and applications? RQ2. What are the major issues and debates about the topics? The answers to the above questions can provide building blocks for a conceptual framework along with a basis of theory development. While trying to place the study in a broader context, we admit SSCM has deep roots in many traditional fields such optimization and supply chain network. When conducting literature search, we find using generic search words such as inventory, network, logistics, and e-business resulted in an overwhelming number of articles which are less relevant to SSCM and relatively outdated. Instead, we use a retrospective approach to find the most recent articles on smart supply chain and work backwards to refine our search keywords, which include supply chain, smart, information system, IoT, advanced analytics, big data, automation, and supply chain integration. These keywords are frequently used in the recent smart supply chain literature. 397 Smart supply chain management Downloaded by Huazhong University of Science and Technology At 22:44 29 November 2016 (PT)
JLMSubsequently,thesekeywordsare searched in majordatabases includingABI/lnformResearch and Business SourceComplete (EBSCOpublishing).The focus is on searching27,2title, keywords, or abstract in relevant refereed journals with regard to smart supplychains.Thepapers were either selected or rejected after performing a content check basedon these delimiting conditions: papers published in peer-reviewed journals in Englishpapers addressing SSCMand relevantoperational issues.Considering the relative infancy398of the topic, it is not deemed appropriate to exclude unpublished studies, newspaperreports,among others.As such, weusethe samekeywords to search non-academic sourcesincludingthepractitioner journalstocollectthemostrecent smartapplications inpracticeWetake inputs from the literatureto formulate the structural attributes and thencategorize papers into relevant SSCMresearch topics.Thefollowing four-step processisfollowed to perform the content analysis where the first level analyzes the manifestcontentofdocumentsbystatisticalmethodsandthesecondlevelexcavatesthelatentcontent(SeuringandGold,2012):(l)Material collection:the papers were collected and later subjected todelimitingcriteriadefinedearlier(2)Descriptive analysis: formal aspects of the collected material are analyzed toprovidethe base for theoretical analysis.Selected papers are sorted accordingtotheyearof publication,publication outlet, etc.(3)Category selection: structural attributes and corresponding analytic categoriesare selected to categorizethe collectedmaterialStructuralattributes constitutethe analytical categories to form themajor topics of analysis.(4)Material evaluation:the collected papers are analyzed to find relevant issuesandtrendsintheliterature.The above clear and purposeful structure is followed iteratively to complete the reviewprocess.Our overall researchprocess flow is illustrated in Figure1.The 189 research papers that qualified the delimitation criteria were selected asthemost relevant and significant research relating to SSCM, then analyzed for thedescriptive attributes. It is revealed from the review that most of the literature isfragmented and is in silos thatmakes synthesis a difficultprocess.Among them,most(168) werepublished in the recentten years, with an increasing slope oftwo articles peryearbetween 2003 and 2012.Figure 2 shows thenumberof refereed articles publishedover theyears (until April 2013).TableI presents thelist of thepopular journals thatpublished most of the refereed papers selected in our survey.As a full review of all papers is neither feasible nor does it offer any furtherinsights(SeuringandGold,2012),wefocusontheselected189refereedarticlesforcontent analysis.3. SSCM researchWhy are the smart supply chain applications being quickly developed and used today?Despitethedifficulties andcomplexities,smart supplychainapplications surelyprovidemanybenefitsotherwisenotavailable.For example,unprecedented amountofinformation can be collected and used to make better business decisions.Betterbusinessprocessesaredevelopedtosupporthigherefficiencyandquickerresponse.Inaddition,thedynamiccomplexityhasoutstrippedthepossibilityofhumaninterventiontoidentifyand solvemanysystem issues,smart supplychainscanpossiblytakeoutmuchof thepersistent inefficiencies.As such,it is harderto achieveperformance
Subsequently, these keywords are searched in major databases including ABI/Inform Research and Business Source Complete (EBSCO publishing). The focus is on searching title, keywords, or abstract in relevant refereed journals with regard to smart supply chains. The papers were either selected or rejected after performing a content check based on these delimiting conditions: papers published in peer-reviewed journals in English; papers addressing SSCM and relevant operational issues. Considering the relative infancy of the topic, it is not deemed appropriate to exclude unpublished studies, newspaper reports, among others. As such, we use the same keywords to search non-academic sources including the practitioner journals to collect the most recent smart applications in practice. We take inputs from the literature to formulate the structural attributes and then categorize papers into relevant SSCM research topics. The following four-step process is followed to perform the content analysis where the first level analyzes the manifest content of documents by statistical methods and the second level excavates the latent content (Seuring and Gold, 2012): (1) Material collection: the papers were collected and later subjected to delimiting criteria defined earlier. (2) Descriptive analysis: formal aspects of the collected material are analyzed to provide the base for theoretical analysis. Selected papers are sorted according to the year of publication, publication outlet, etc. (3) Category selection: structural attributes and corresponding analytic categories are selected to categorize the collected material. Structural attributes constitute the analytical categories to form the major topics of analysis. (4) Material evaluation: the collected papers are analyzed to find relevant issues and trends in the literature. The above clear and purposeful structure is followed iteratively to complete the review process. Our overall research process flow is illustrated in Figure 1. The 189 research papers that qualified the delimitation criteria were selected as the most relevant and significant research relating to SSCM, then analyzed for the descriptive attributes. It is revealed from the review that most of the literature is fragmented and is in silos that makes synthesis a difficult process. Among them, most (168) were published in the recent ten years, with an increasing slope of two articles per year between 2003 and 2012. Figure 2 shows the number of refereed articles published over the years (until April 2013). Table I presents the list of the popular journals that published most of the refereed papers selected in our survey. As a full review of all papers is neither feasible nor does it offer any further insights (Seuring and Gold, 2012), we focus on the selected 189 refereed articles for content analysis. 3. SSCM research Why are the smart supply chain applications being quickly developed and used today? Despite the difficulties and complexities, smart supply chain applications surely provide many benefits otherwise not available. For example, unprecedented amount of information can be collected and used to make better business decisions. Better business processes are developed to support higher efficiency and quicker response. In addition, the dynamic complexity has outstripped the possibility of human intervention to identify and solve many system issues, smart supply chains can possibly take out much of the persistent inefficiencies. As such, it is harder to achieve performance 398 IJLM 27,2 Downloaded by Huazhong University of Science and Technology At 22:44 29 November 2016 (PT)
Smart supplyResearchQuestionFormulationCurrent status of SSCM? Issues and debates?chainmanagement业Selection of Relevant Studies189 papers qualfied the delimitation criteria399￥Descriptive AnalysisPapers are sorted according to the publicationeoaetime, and outlets业Content AnalysisSix key characteristics and five researchcategories are defined; papers are reviewed￥Evaluation and SynthesisResearch questions are answered within each research category, reviewresults are aggregated, integrated, and explainedFigure 1.￥Research processflowdiagramConclusion and Recommendations4540353025 20151050Figure 2.0a000S1S20%09O26-166Number of selected22222Sreferred journalNotes:The literature search was completed in April 2013articles publishedThenumberfor2013wasprojectedbasedon14articlesfoundover the yearsfor the first quarter of 2013improvements through the traditional means and companies clearly see the criticalneed to develop newer solutions arising from technology and business model-basedinnovations.Further,the costs of instrumentation have declined dramatically in recentyears and smart devices arebeing deployed everywhere (Zhuetal,2012).Computingand informationtechnologies(lT)cannowsupportwidespreadinstrumentation,monitoring,andperformanalytics
improvements through the traditional means and companies clearly see the critical need to develop newer solutions arising from technology and business model-based innovations. Further, the costs of instrumentation have declined dramatically in recent years and smart devices are being deployed everywhere (Zhu et al., 2012). Computing and information technologies (IT) can now support widespread instrumentation, monitoring, and perform analytics. Research Question Formulation Current status of SSCM? Issues and debates? Selection of Relevant Studies 189 papers qualified the delimitation criteria Descriptive Analysis Papers are sorted according to the publication time, and outlets Content Analysis Six key characteristics and five research categories are defined; papers are reviewed Evaluation and Synthesis Research questions are answered within each research category; review results are aggregated, integrated, and explained Conclusion and Recommendations Figure 1. Research process flow diagram 45 40 35 30 25 20 15 10 5 0 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 Notes: The literature search was completed in April 2013. The number for 2013 was projected based on 14 articles found for the first quarter of 2013 Figure 2. Number of selected referred journal articles published over the years 399 Smart supply chain management Downloaded by Huazhong University of Science and Technology At 22:44 29 November 2016 (PT)
JLMNumber of publicationsJournal name27,210Management Science9999886555443333322European Journal of Operational ResearchInternational Journalof ProductionEconomicsProductionandOperationsManagementSupplyChainManagement:AnInternationalJournal400HarvardBusiness ReviewJournal of Operations ManagementInternational JournalofInformationManagementInternational Journal of Plysical Distribution&Logistics ManagementInternational Journalof ProductionResearchOmegaInternational Journalof Operations &ProductionManagementMITSoanManagement ReviewBusiness Process Management JournalMISQuarterlyTable I.McKinsey QuarterlyRefereed journalsManufacturing and Service Operations Management主with the mostOperationsResearcharticles selected inJournal ofBusinessLogisticsInternational Journal of Logistics Managementthe literaturereviewoaeaasoaeeaeooBased on our definition of smart supply chain and earlier discussions on relevantapplications,wesummarizethat smart supply chains collectively possessthefollowingsix distinctive characteristics:instrumented: information in the next generation supply chainis(1) overwhelmingly being machine-generated, for example, by sensors, RFIDtags,meters, and many others;(2)interconnected: the entire supply chain, including business entities,and assets,IT systems,products, and other smart objects are all connected in a smartsupply chain;intelligent:smart supply chains make large-scaleoptimal decisions to optimize(3)performance;automated: smart supply chains must automate much of its process flows by(4)usingmachinestoreplaceotherlow-efficiencyresourcesincludinglabor,(5)integrated:supply chain process integration involves collaboration across supplychainstages,jointdecisionmaking,commonsystems,andinformationsharing,and(6)innovative: innovation is the development of new values through solutions thatmeet new requirements, inarticulate needs, or even existing needs in better ways.Among all critical resources,information systems continue to play a criticalrole in SCMas supply chain performance is often characterized and facilitated by the real-timecollaboration and sophisticated integration.SCM would not even bepossiblewithoutthe advances in information systems and technology.In fact, smart supply chains willcreatenewvaluebydeveloping newbusiness models, improvingbusiness processes,and reducing theassociated costs and risks (Chuietal.,2010).Moreinformation, betterdecision, better process,even better product would be what smart supply chain can and
Based on our definition of smart supply chain and earlier discussions on relevant applications, we summarize that smart supply chains collectively possess the following six distinctive characteristics: (1) instrumented: information in the next generation supply chain is overwhelmingly being machine-generated, for example, by sensors, RFID tags, meters, and many others; (2) interconnected: the entire supply chain, including business entities, and assets, IT systems, products, and other smart objects are all connected in a smart supply chain; (3) intelligent: smart supply chains make large-scale optimal decisions to optimize performance; (4) automated: smart supply chains must automate much of its process flows by using machines to replace other low-efficiency resources including labor; (5) integrated: supply chain process integration involves collaboration across supply chain stages, joint decision making, common systems, and information sharing; and (6) innovative: innovation is the development of new values through solutions that meet new requirements, inarticulate needs, or even existing needs in better ways. Among all critical resources, information systems continue to play a critical role in SCM as supply chain performance is often characterized and facilitated by the real-time collaboration and sophisticated integration. SCM would not even be possible without the advances in information systems and technology. In fact, smart supply chains will create new value by developing new business models, improving business processes, and reducing the associated costs and risks (Chui et al., 2010). More information, better decision, better process, even better product would be what smart supply chain can and Journal name Number of publications Management Science 10 European Journal of Operational Research 9 International Journal of Production Economics 9 Production and Operations Management 9 Supply Chain Management: An International Journal 9 Harvard Business Review 8 Journal of Operations Management 8 International Journal of Information Management 6 International Journal of Physical Distribution & Logistics Management 5 International Journal of Production Research 5 Omega 5 International Journal of Operations & Production Management 4 MIT Sloan Management Review 4 Business Process Management Journal 3 MIS Quarterly 3 McKinsey Quarterly 3 Manufacturing and Service Operations Management 3 Operations Research 3 Journal of Business Logistics 2 International Journal of Logistics Management 2 Table I. Refereed journals with the most articles selected in the literature review 400 IJLM 27,2 Downloaded by Huazhong University of Science and Technology At 22:44 29 November 2016 (PT)
should produce.SsCM research should certainlyfocuson thebusinessmanagement ofSmart supplysmart supply chains. Using the six characteristics as structural attributes together withchaintheabovediscussionsoninformation,wetakethelibertytoclassifythemainresearchmanagementtopicsof SSCMintothefollowingfivecategories:(1)information in supplychains;(2)IT;401(3)processautomation;)1(4)advanced analytics; and(5)process integration and innovation.It is evident that categories (2-4) fully capture the six distinctive characteristicsdiscussed early,e.g,IT includes hardwarewe(instrumented)andnetwork(interconnected), and the intelligent feature is facilitated by advanced analytics.Information in supply chains really refers to what“smart"is all about. Furthermore,2these five categories are all well-established research themes extensively studied in theooesosneeaoliterature.As such, they areusedas a convenient waytorepresent SSCM research andgroup relevant papers reviewed in the study. Under this structure, we find the mostpopular research methodologies are conceptual/framework for addressingITinfrastructure topics (39 papers), and analytical modeling method for addressingadvancedanalyticstopics (22papers).Sometopics suchasITobviouslyattractedmoreresearchers'attention than others in recent years (TableIl).We will attempt to addresstheRQ1 and RQ2 in the context of each of the abovefive topics (Tables II and II).CaseConceptual/AnalyticalOthersClassification criteriaEmpiricalframeworkmodelingstudy211011521111General SSCM strategy13144InformationTable II.6398Information technologyNumber of papers24a20Automationusing different37132200Advanced analyticsresearch0118SC integrationmethodologies in theNote:"Including one paper using simulation approachliterature reviewITInformationAutomationAdvanced analyticsIntegration and innovation22230311221312.322200320040172005120066233125302007133;321642008Table III.020094Number of papers33.1120103published in61505382011various fields in112012ten recent years
should produce. SSCM research should certainly focus on the business management of smart supply chains. Using the six characteristics as structural attributes together with the above discussions on information, we take the liberty to classify the main research topics of SSCM into the following five categories: (1) information in supply chains; (2) IT; (3) process automation; (4) advanced analytics; and (5) process integration and innovation. It is evident that categories (2-4) fully capture the six distinctive characteristics we discussed early, e.g., IT includes hardware (instrumented) and network (interconnected), and the intelligent feature is facilitated by advanced analytics. Information in supply chains really refers to what “smart” is all about. Furthermore, these five categories are all well-established research themes extensively studied in the literature. As such, they are used as a convenient way to represent SSCM research and group relevant papers reviewed in the study. Under this structure, we find the most popular research methodologies are conceptual/framework for addressing IT infrastructure topics (39 papers), and analytical modeling method for addressing advanced analytics topics (22 papers). Some topics such as IT obviously attracted more researchers’ attention than others in recent years (Table III). We will attempt to address the RQ1 and RQ2 in the context of each of the above five topics (Tables II and III). Classification criteria Conceptual/ framework Analytical modeling Empirical Case study Others General SSCM strategy 21 1 0 1 1 Information 13 14 4 1 1 Information technology 39 8 6 5 1 Automation 2 4a 2 20 Advanced analytics 13 22 3 1 0 SC integration 11 8 7 0 0 Note: a Including one paper using simulation approach Table II. Number of papers using different research methodologies in the literature review Information IT Automation Advanced analytics Integration and innovation 2003 2 0 1 3 2 2004 2 3 1 1 3 2005 2 1 2 0 2 2006 3 7 2 1 2 2007 3 6 1 0 2 2008 1 3 2 3 3 2009 4 3 5 2 0 2010 3 11 3 1 3 2011 6 5 0 6 3 2012 1 11 5 4 8 Table III. Number of papers published in various fields in ten recent years 401 Smart supply chain management Downloaded by Huazhong University of Science and Technology At 22:44 29 November 2016 (PT)
IJLM3.1Information in supply chainsWhile data can be considered as“rawfacts"that reflect the characteristics of27,2an event or entity,information can be viewed as“meaningful data" to supportdecision making (Detlor,2010).Thegoal of information management is always tohelp organizations create,access, process, and use information so that they cancompletetheirbusiness tasksmore efficiently and effectively.Meanwhile,delayed402scarce,or distorted information can create serious problems in supply chains(Chowetal,2008).There is a rich collection of literature on supply chain information managementaea(see, e.g.Pereira 2009; for a review).Researchers have long advocated the notion thatinformationiscriticaltothesuccessofSCM(ChopraandMeindl,2013).Mostoftheexisting literature available in this area focusses on demand (or order) informationmanagement along the supply chains (Kumar and Pugazhendhi,2012).Information iseven more important in a dynamic environment that involves uncertainties anddisruptions (Mithas etal,2011).Specifically,demand information visibility can cutleadtimes,reduceassociated costs,improveresponsiveness,and enhancedecisionmaking(HandfieldandNichols,2002)Information in business world can be classified in a number of ways, forinstance, proprietary or public information, tactical (e.g.purchasing orders,production schedule, logistics data), or strategic (e.g.facility capacity,supplynetworks).A great deal of attention in the current SCM literature is devoted to theinvestigation of material and demand information flows and their respectivecoordination (Pedroso and Nakano, 2009).As all supply chains are essentiallydemand-driven, final customer demand information is widely considered as themost important information in supply chain systems.Othertypical informationgenerated may also include inventory, cost, pricing, shipping, location, capacity,quality,and technical information (Pedroso and Nakano, 2009).In a broad context,everyfirm serves as a producer as well as a user of information.In addition to theinformationtheyreceivefromtheirpartners,firmsalsoneedtogenerateandanalyzemuch of the information they use internally and share externally with respectivepartners.While some of the information items like lot size and lead time have beenextensively studied individually, it is evident that the current literature lackscomprehensive research at broader scales,e.g.,how to collectively manage all thefull-scale information itemsthe manufacturer needs.The economic value andaccessibility of different information items need to be systematically assessedfrom different angles to provide insights for full-scale information management insmartsupplychains.In order to develop the information system for a smart supply chain, one shouldprobably startwithaskingquestionsabout what information thefirmand other supplychain partners need, and answering questions about what information they canprovidetobenefitthemselvesandotherpartners.Withoutdefiningwhatinformationtoproduce, it would be very difficult to share data across supply chain stages as thepartners might nothavethe righttype of information,Consequentlytherewouldbenocommunicationatall,evenwhencompanieswant tocommunicate.As theinterconnected supply chain networks link data from customers,products, companyassets, and the operating environment, they can generate more high-qualityinformation much quickly.The trend is that machine-generated sensor data willbecomeafarlargerportionofthebigdataworld(to42percentofalldataby2020,upfrom 11 percent in 2005)(Loher, 2012).Smart supply chains are geared toward
3.1 Information in supply chains While data can be considered as “raw facts” that reflect the characteristics of an event or entity, information can be viewed as “meaningful data” to support decision making (Detlor, 2010). The goal of information management is always to help organizations create, access, process, and use information so that they can complete their business tasks more efficiently and effectively. Meanwhile, delayed, scarce, or distorted information can create serious problems in supply chains (Chow et al., 2008). There is a rich collection of literature on supply chain information management (see, e.g. Pereira 2009; for a review). Researchers have long advocated the notion that information is critical to the success of SCM (Chopra and Meindl, 2013). Most of the existing literature available in this area focusses on demand (or order) information management along the supply chains (Kumar and Pugazhendhi, 2012). Information is even more important in a dynamic environment that involves uncertainties and disruptions (Mithas et al., 2011). Specifically, demand information visibility can cut lead times, reduce associated costs, improve responsiveness, and enhance decision making (Handfield and Nichols, 2002). Information in business world can be classified in a number of ways, for instance, proprietary or public information, tactical (e.g. purchasing orders, production schedule, logistics data), or strategic (e.g. facility capacity, supply networks). A great deal of attention in the current SCM literature is devoted to the investigation of material and demand information flows and their respective coordination (Pedroso and Nakano, 2009). As all supply chains are essentially demand-driven, final customer demand information is widely considered as the most important information in supply chain systems. Other typical information generated may also include inventory, cost, pricing, shipping, location, capacity, quality, and technical information (Pedroso and Nakano, 2009). In a broad context, every firm serves as a producer as well as a user of information. In addition to the information they receive from their partners, firms also need to generate and analyze much of the information they use internally and share externally with respective partners. While some of the information items like lot size and lead time have been extensively studied individually, it is evident that the current literature lacks comprehensive research at broader scales, e.g., how to collectively manage all the full-scale information items the manufacturer needs. The economic value and accessibility of different information items need to be systematically assessed from different angles to provide insights for full-scale information management in smart supply chains. In order to develop the information system for a smart supply chain, one should probably start with asking questions about what information the firm and other supply chain partners need, and answering questions about what information they can provide to benefit themselves and other partners. Without defining what information to produce, it would be very difficult to share data across supply chain stages as the partners might not have the right type of information. Consequently there would be no communication at all, even when companies want to communicate. As the interconnected supply chain networks link data from customers, products, company assets, and the operating environment, they can generate more high-quality information much quickly. The trend is that machine-generated sensor data will become a far larger portion of the big data world (to 42 percent of all data by 2020, up from 11 percent in 2005) (Loher, 2012). Smart supply chains are geared toward 402 IJLM 27,2 Downloaded by Huazhong University of Science and Technology At 22:44 29 November 2016 (PT)
producingbetter information which possesses thefollowing properties(PedrosoandSmart supplyNakano,2009):chaintherighttypeof information (e.g.creatingmorevalue);managementimproved information quality(e.g.accuracyaboutactual demand quantity,precisionaboutorderarrivaltime);403:better timing (e.g.much earlier than previous);:speed (e.g.real-time transmission over network))910.ease of accessing the needed information; andcontrollabilityforinformation sharingand privacyprotection.We justdiscussed what better information togenerate.In practice,however,goodinformationisoftennotavailableorpassedthroughtoothersupplychainpartnersforpractical, political, and/or competitive reasons. As a result, this may undermine aparticularenterprise in terms of functional decisionmaking as well as risk mitigation2To enabletransformative opportunities,firms will increasingly need tointegrateinformationfromdifferentsources.Sincethevalueofinformationisanimportantsubject matter when facing demand uncertainty,there has been abundant researchsupportingthat informationsharing isakeysupplychainperformancedriver(CachonandFisher,2000).Bytakingadvantageoftheinformationavailableandsharingthemwith other parties in the supply chain,afirm can improve coordinationto enableefficient material and informationflows (Damianiet al.,2011).pueWhile information sharing is important, the significance of its impact on theperformance ofa supply chain dependson what information isshared,when andhowit is shared, and with whom (Holmberg,2000).It is found that both informationSsharing and informationquality are influenced positivelybythe trust built in supplyL-chain partners, but negativelyby supplier's uncertainty (Wang et al,2013).Whilefavorablecostsstructurelikelow-operatingcostsmayfacilitatemoreinformationsharing (Chu and Lee,2006), there are many risks associated with sharing item-leveldata and lacking of trust is still one of the major obstacles for information sharingoenin general, and for sensitive informationin particular (Eurich et al,2010).Itisworthwhile noting that in some cases sharinga lot of information mayguarantee thatnobody has the right information when it is needed (Liker and Choi,2004).As such, iteaeoois very importantto identify what information should be shared when creatingsupply chain visibility (Handfield and Nichols,2002).Modern IT has madeinformation sharingpossible in aconvenientmanner.Duetothecomplexityand costsassociatedwiththeincreasinglycomplicated informationflows,itisonlypossibletomake full-scaleapplicationsforinformation sharing and collaboration in smartsupplychains where informationisproduced and managedbymachines and devices(EvansandAnnunziata,2012)Overall, the majority of the prior studies on supply chain informationmanagement focus on theupstream flow of demand information and its effects onmaterialflows.Lackingofvisibilityandcollaborationintraditionalsupplychainsisclearly one of the fundamental issues smart supply chains need to address.To help mitigate the issue, full-scale high-quality information needs to be collectedanalyzed,shared,andusedintherightmannertocreatemorevalue(e.g.systemcostreduction),such that win-win situations can be possibly established to promotesupplychainpartnerships
producing better information which possesses the following properties (Pedroso and Nakano, 2009): • the right type of information (e.g. creating more value); • improved information quality (e.g. accuracy about actual demand quantity, precision about order arrival time); • better timing (e.g. much earlier than previous); • speed (e.g. real-time transmission over network); • ease of accessing the needed information; and • controllability for information sharing and privacy protection. We just discussed what better information to generate. In practice, however, good information is often not available or passed through to other supply chain partners for practical, political, and/or competitive reasons. As a result, this may undermine a particular enterprise in terms of functional decision making as well as risk mitigation. To enable transformative opportunities, firms will increasingly need to integrate information from different sources. Since the value of information is an important subject matter when facing demand uncertainty, there has been abundant research supporting that information sharing is a key supply chain performance driver (Cachon and Fisher, 2000). By taking advantage of the information available and sharing them with other parties in the supply chain, a firm can improve coordination to enable efficient material and information flows (Damiani et al., 2011). While information sharing is important, the significance of its impact on the performance of a supply chain depends on what information is shared, when and how it is shared, and with whom (Holmberg, 2000). It is found that both information sharing and information quality are influenced positively by the trust built in supply chain partners, but negatively by supplier’s uncertainty (Wang et al., 2013). While favorable costs structure like low-operating costs may facilitate more information sharing (Chu and Lee, 2006), there are many risks associated with sharing item-level data and lacking of trust is still one of the major obstacles for information sharing in general, and for sensitive information in particular (Eurich et al., 2010). It is worthwhile noting that in some cases sharing a lot of information may guarantee that nobody has the right information when it is needed (Liker and Choi, 2004). As such, it is very important to identify what information should be shared when creating supply chain visibility (Handfield and Nichols, 2002). Modern IT has made information sharing possible in a convenient manner. Due to the complexity and costs associated with the increasingly complicated information flows, it is only possible to make full-scale applications for information sharing and collaboration in smart supply chains where information is produced and managed by machines and devices (Evans and Annunziata, 2012). Overall, the majority of the prior studies on supply chain information management focus on the upstream flow of demand information and its effects on material flows. Lacking of visibility and collaboration in traditional supply chains is clearly one of the fundamental issues smart supply chains need to address. To help mitigate the issue, full-scale high-quality information needs to be collected, analyzed, shared, and used in the right manner to create more value (e.g. system cost reduction), such that win-win situations can be possibly established to promote supply chain partnerships. 403 Smart supply chain management Downloaded by Huazhong University of Science and Technology At 22:44 29 November 2016 (PT)