Research synthesis in collaborative planning forecast and replenishment

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  • Research synthesis incollaborative planning forecast

    and replenishmentAntonio Marcio Tavares ThomeIndustrial Engineering Department,

    Pontifcia Universidade Catolica do Rio de Janeiro, Rio de Janeiro,Brazil and BEMFAM, Rio de Janeiro, Brazil, and

    Roberto Luis Hollmann andLuiz Felipe Roris Rodriguez Scavarda do Carmo

    Industrial Engineering Department,Pontifcia Universidade Catolica do Rio de Janeiro, Rio de Janeiro, Brazil

    Abstract

    Purpose The purpose of this research synthesis is to gather and integrate findings on CollaborativePlanning Forecast and Replenishment (CPFR) as a business process and as a management practice;and to assemble quantitative evidence of its impact on supply chain (SC) performance.Design/methodology/approach The researchers independently conducted a systematic reviewof 629 abstracts and 47 full-text papers. Original keywords were applied to four key electronicdatabases for operations management and information systems. Rigorous and verifiable selectioncriteria governed inter-coders reliability, review of steps and exclusion of papers. Resource anddependency-based view of the firm, contingency research and maturity models informed the analysis.Findings There is not a single blueprint for CPFR. Competing models emphasize the needfor trust and confidence and reliable data systems. The type of products, scope, spatialdiversity and number of partners in the network are important contextual variables. Firmresources that are unique and advantages from multiple and reciprocal dependencies are powerfullevers. There is no consensus on maturity model and on required investment in data andcommunication systems.Practical implications Practical implications are implementation related: cost-benefit analysisand simulations should precede full-scale collaboration. There is a consensus on starting CPFR smalland expanding gradually.Originality/value This synthesis applies a rigorous review method and attempts to assemblethe dispersed literature in one study, utilizing explanatory operations management and informationsystems theories.

    Keywords Collaboration, Operations management, Supply chain, Trust,Information communication technology

    Paper type Research paper

    1. IntroductionCollaborative Planning Forecast and Replenishment (CPFR) is a cohesive bundle ofbusiness processes whereby supply chain (SC) trading partners share information,synchronized forecasts, risks, costs and benefits with the intent of improving overallSC performance through joint planning and decision making. Accordingly, CPFRenhances customer demand visibility and matches supply and demand with a

    The current issue and full text archive of this journal is available atwww.emeraldinsight.com/0263-5577.htm

    Received 13 March 2014Revised 21 April 2014

    Accepted 22 April 2014

    Industrial Management & DataSystems

    Vol. 114 No. 6, 2014pp. 949-965

    r Emerald Group Publishing Limited0263-5577

    DOI 10.1108/IMDS-03-2014-0085

    The authors gratefully acknowledge MCT/CNPq (Research Project No. 307996/2011-5), CAPES/DFG (BRAGECRIM Research Project No. 010/09) and CAPES/DAAD (PROBRAL).

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  • synchronized flow of goods from the production and delivery of raw materials to theproduction and delivery of the final product to the end consumer. According toVoluntary Inter-industry Commerce Standard (VICS)s (2004) model, CPFR frameworkencompasses different business processes subdivided into specific steps or tasks(strategy and planning, demand and supply management, execution and analysis).From a contingency view, CPFR takes different forms, according to context (Sousa andVoss, 2008; Danese, 2011).

    The concept emerged as an inter-industry standard designed to move beyond theshortcomings of other Supply Chain Collaboration (SCC) initiatives, such asElectronic Data Interchange (EDI), Efficient Consumer Response Movement (ECR),Vendor Managed Inventories (VMI) and Continuous Replenishment (CR) (Stanket al., 1999; Barratt and Oliveira, 2001; Seifert, 2003). CPFR captures the advantagesof such initiatives while adding the collaborative mechanism to facilitateinformation exchange in a multi-tiered SC (Cassivi, 2006). CPFR takes a morecomprehensive approach with respect to the planning of promotions, sales andorders forecast; synchronization of plans between trading partners; the making ofjoint decisions and the management of exceptions (Danese, 2011). CPFR increasesresponsiveness to changing demand patterns and provides a better coordinationalong the SC (Barratt and Oliveira, 2001). Additionally, CPFR is an exception-drivenprocess while the other SCC initiatives are more data driven and exceptions are notpart of the process (Burnette, 2010). Through exception management, tradingpartners can collaboratively review sales and order forecasts (Du et al., 2009,Burnette, 2010), and they can do so on a large scale (Du et al., 2009). It was an effortof Wal-Mart and Warner-Lambert in the mid 1990s for the Listerine line of products(Sherman, 1998). Since then, a sustained attention has been given to CPFR. In 1998,the Voluntary Inter-industry Commerce Standard (VICS) committee published thefirst guideline for implementation, reviewed in 2004 and 2010 (VICS, 1998, 2004,2010). By 2010, the VICS committee reported that over 300 large companies hadimplemented it (Lapide, 2010; Yao et al., 2013).

    There are several CPFR models in the literature, with varying configurations andno systematic review available to date. Despite the growing number of publicationsin CPFR, efforts to synthesize the state of the art are still limited. As an attempt to fillthis gap, this paper provides a research synthesis aiming at assembling the dispersedliterature on the subject. The purpose of this review is twofold: to gather and integratefindings on CPFR as a business process and as a management practice; andto assemble quantitative evidences of its impact on SC performance. First, themethodology used in the research synthesis is described. Next, main findings andresults are analysed and discussed. Finally, the main conclusions and suggestions forfuture research are presented.

    2. MethodologyA six-step process was used to select and retrieve papers: computerized databaseselection, identification of key words for search, criteria for exclusion of studies,manual review of selected abstracts, full-text review and review of selected referencesfrom full-text articles (Thome et al., 2012).

    The databases selected were EMERALD, EBSCO, SCIENCEDIRECT and WILEY. Inaccordance with recommendations for initial research synthesis (Cooper, 2010),keywords selected were sufficiently broad to avoid artificially limiting results and stillprovided limitations to avoid undesirable results. The search keywords were

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    IMDS114,6

  • Collaborative Planning Forecasting and Replenishment and CPFR, with no limitationsregarding publication dates.

    Papers were excluded due to threats to validity for systematic reviews (Cooper,2010). Criteria for the exclusion of papers were related to the relevance for the subjectof the literature search, such as poorly defined constructs of CPFR, CPFR being usedjust as an example and not as a research topic and papers treating CPFR elements inisolation of each other (e.g. inventory management, demand forecast). An additionalcriterion for exclusion was related to the quality of original research, as papers basedon authors opinion and anecdotic evidences of results only, papers from trade andindustry magazines not consubstantiate with empirical evidences, and paperspresenting causal relationship not based on clearly defined empirical evidences fromexplicit mathematical modelling, survey research or case studies.

    The search based on the keywords returned 629 papers. The full bibliography listis available upon request. Duplicate papers and those not corresponding to the abovecriteria were excluded, resulting in 53 papers selected for full-text review. Afterfull-text reading, six papers were excluded. Thus, 47 papers were reviewed andcross-examined by three researchers. The review process was interactive and resultedin high level of agreement, with a Cohens k in the range of 0.87-0.99 (95 per cent CI)(Cohen, 1960).

    3. Results and discussionsThe results are presented in three broad categories: study identification, literaturesearch synthesis framework and study descriptors.

    3.1 Study identificationThe 47 articles included in the analysis are listed in Table I together with the number ofcitations, source and methodology.

    As depicted in Table I, just one author published more than two studies on thesubject. Publications on CPFR are also recent, with the first ones appearing in the late1990s. The second column presents the number of citations of each article from GoogleScholar, after the required cleaning to avoid duplicate entries (Thome et al, 2012).In all, 52 per cent of citations concentrate on seven papers published in four leadingJournals: IJPDLM, SCMIJ, IJLM and IMDS. The third column depicts the sourceof the publications, mostly concentrated in Business Forecasting and OperationsManagement (OM) journals. The last column shows the methodology used in thestudies. Single and multiple case studies and simulations prevail, followed byconceptual models of SC collaboration. Five industry reports, five survey research andone literature review are also related in Table I.

    3.2 A synthesis frameworkThe framework depicted in Figure 1 is an aide to assemble and organize the review.It is based on an original framework proposed by Thome et al. (2012), expanded withinformation from explanatory theories of resource-based view (RBV) and resourcedependent theory (RDT) (Ramanathan and Gunasekaran, 2014), maturity models(Larsen et al., 2003) and contingency research (Danese, 2011) applied to CPFR.The structure of the framework embraces all the constitutive elements required todescribe individual CPFR elements, their relationships and impact upon performance.The adapted framework adds the dimension of SCC to the original Thome et al. (2012)sfirm-centred framework. It also adds the vertical functional role of CPFR in bridging

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  • Reference No. of citations Source Methodology

    Sherman (1998) 55 JMTP Conceptual modelStank et al. (1999) 145 SCMIJ SurveyBarratt and Oliveira (2001) 327 IJPDLM SurveyHolmstrom et al. (2002) 124 SCMIJ Conceptual modelMcCarthy and Golicic (2002) 155 IJPDLM Case study, multipleEsper and Williams (2003) 116 TJ Conceptual modelFliedner (2003) 167 IMDS Conceptual modelLarsen et al. (2003) 218 IJPDLM SurveyAttaran (2004) 20 IM Industry reportDanese et al. (2004) 64 JPSM Case study, multipleCaridi et al. (2005) 54 IJPR SimulationIreland (2005) 7 JBF Industry reportSimatupang and Sridharan (2005) 137 IJLM Conceptual modelCaridi et al. (2006) 20 JEIM SimulationCassivi (2006) 89 SCMIJ SurveyDanese (2006a) 3 SCFIJ Conceptual modelDanese (2006b) 46 IJPR Case study, multipleThron et al. (2006) 18 IJPDLM SimulationAttaran and Attaran (2007) 78 BPMJ Conceptual modelChang et al. (2007) 24 SCMIJ SimulationChen et al. (2007) 32 I&M SimulationDanese (2007) 70 IJOPM Case study, multipleSmaros (2007) 56 JOM Case study, singleThron et al. (2007) 17 IJLM SimulationChang and Wang (2008) 14 IJAMT Case study, singleDAubeterre et al. (2008) 19 JAIS Case study, singleDerrouiche et al. (2008) 30 IJCIM Conceptual modelGhosh and Fedorowicz (2008) 46 BPMJ Case study, singlePoler et al. (2008) 33 JMTM SimulationSari (2008a) 21 IMDS SimulationSari (2008b) 65 IJPE SimulationBuyukozkan et al. (2009) 5 WASET SimulationDu et al. (2009) 19 SCMIJ Case study, multipleBaumann (2010) 3 JBF Conceptual modelBurnette (2010) 1 JBF Industry reportChoi and Sethi (2010) 45 IJPE Literature reviewHvolby and Trienekens (2010) 23 CI Conceptual modelLapide (2010) 1 JBF Industry reportShu et al. (2010) 0 IJITDM Conceptual modelSmith et al. (2010) 6 JBF Industry reportYuan et al. (2010) 7 RCIM Case study, singleDanese (2011) 15 IJPR Case study, multipleBuyukozkan and Vardaloglu (2012) 9 ESA SimulationAudy et al. (2012) 19 ITOR Case study, multipleYao et al. (2013) 0 JOM Case study, singleRamanathan (2014) 1 ESA SimulationRamanathan and Gunasekaran (2014) 9 IJPE Survey

    Notes: BPMJ, Business Process Management Journal; CI, Computers in Industry; ESA, Expert Systems withApplications; I&M, Information & Management; IJAMT, International Journal of Advanced Manufacturing Technology;IJCIM, International Journal of Computer Integrated Manufacturing; IJITDM, International Journal of InformationTechnology & Decision Making; IJLM, International Journal of Logistics Management; IJOPM, International Journal ofOperations & Production Management; IJPDLM, International Journal of Physical Distribution & LogisticsManagement; IJPE, International Journal of Production Economics; IJPR, International Journal of Production Research;IM, Industrial Management; IMDS, Industrial Management & Data Systems; JAIS, Journal of the Association forInformation Systems; JBF, Journal of Business Forecasting; JEIM, Journal of Enterprise Information Management;JMTM, Journal of Manufacturing Technology Management; JMTP, Journal of Marketing Theory & Practice; JOM,Journal of Operations Management; JPSM, Journal of Purchasing and Supply Management; RCIM, Robotics andComputer-Integrated Manufacturing; SCFIJ, Supply Chain Forum: an International Journal; SCMIJ, Supply ChainManagement: An International Journal; TJ, Transportation Journal; WASET, World Academy of Science, Engineering& Technology. No. of citations obtained in 11 January 2014

    Table I.Publications, numberof citations, sourceand methodology

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    Figure 1.Literature search

    synthesis framework

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  • business and corporate strategic plans of individual firms with joint SC operations.CPFR results feedback to inputs. Important contextual variables emanated from thecontingency theory were added, such as number of SC partners, product-characteris...

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