{"title":"Typology and Literature Review on Multiple Supplier Inventory Control Models","authors":"J. Svoboda, S. Minner, Man Yao","doi":"10.2139/ssrn.2995134","DOIUrl":null,"url":null,"abstract":"This paper presents a typology and classifies the literature on inventory models with multiple sourcing options. The categories for classification include the number of considered echelons, the source of uncertainty, the model structure, as well as the general research approach. By means of the classification, the existing research is reviewed and insights and gaps are identified. The literature shows that stochasticity, constraints, cost structures and lead times have a significant impact on the sourcing decision. High demand volatility as well as high uncertainty in the lead time, yield or disruption of a primary source indicates a significant value of a second, reliable, fast but more expensive source. The same is true if a buyer has limited storage space or if the primary supplier is constrained in capacity or order size. If the emergency supplier has a minimum order requirement or the buyer is limited financially, the opposite is true and single sourcing is viable. Furthermore, besides a small emergency cost premium, large lead time differences between suppliers and short emergency lead times favor multiple sourcing. The review identifies several research gaps. Firstly, one important gap is on multi-echelon supply chain structures. Secondly, simple policy structures for more realistic and complex problem settings with multiple suppliers, multiple decision criteria and multiple, possibly correlated, sources of uncertainty should be investigated. Lastly, data driven approaches in industry applications could be a focal point of future research efforts.","PeriodicalId":237187,"journal":{"name":"ERN: Production; Cost; Capital & Total Factor Productivity; Value Theory (Topic)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"64","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ERN: Production; Cost; Capital & Total Factor Productivity; Value Theory (Topic)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2139/ssrn.2995134","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 64
Abstract
This paper presents a typology and classifies the literature on inventory models with multiple sourcing options. The categories for classification include the number of considered echelons, the source of uncertainty, the model structure, as well as the general research approach. By means of the classification, the existing research is reviewed and insights and gaps are identified. The literature shows that stochasticity, constraints, cost structures and lead times have a significant impact on the sourcing decision. High demand volatility as well as high uncertainty in the lead time, yield or disruption of a primary source indicates a significant value of a second, reliable, fast but more expensive source. The same is true if a buyer has limited storage space or if the primary supplier is constrained in capacity or order size. If the emergency supplier has a minimum order requirement or the buyer is limited financially, the opposite is true and single sourcing is viable. Furthermore, besides a small emergency cost premium, large lead time differences between suppliers and short emergency lead times favor multiple sourcing. The review identifies several research gaps. Firstly, one important gap is on multi-echelon supply chain structures. Secondly, simple policy structures for more realistic and complex problem settings with multiple suppliers, multiple decision criteria and multiple, possibly correlated, sources of uncertainty should be investigated. Lastly, data driven approaches in industry applications could be a focal point of future research efforts.