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Response to “Note on supply chain integration in vendor managed inventory”
Decision Support Systems 44 (2007) 366 – 367 www.elsevier.com/locate/dss
Response to “Note on supply chain integration in vendor managed inventory” Yuliang Yao a,⁎, Philip T. Evers b , Martin E. Dresner b b
a College of Business & Economics, Lehigh University, United States Robert H. Smith School of Business, University of Maryland, United States
Received 3 January 2007; received in revised form 24 January 2007; accepted 12 March 2007 Available online 20 March 2007
van der Vlist et al. [1] extend the Yao et al. [2] model in two fruitful ways: They explicitly consider transportation costs, first as an additional per unit order cost and then as an additional per shipment cost, whereas Yao et al. implicitly include transportation as a component of order cost. Second, while Yao et al. assume that the supplier places an order (or schedules production) when an order from the buyer decreases the supplier's inventory to zero, van der Vlist et al. allow the supplier to wait before it places its order. In addition to these two constructive extensions, however, van der Vlist et al. make two tenuous assumptions (i.e., van der Vlist et al. Eqs. (6), (7)) that are not in Yao et al. If the two assumptions are relaxed, van der Vlist et al.'s conclusions cannot be drawn, suggesting that the validity of their conclusions is based not only on their extensions but also on these two assumptions. In van der Vlist et al. Eq. (6), the authors assume that the sum of the buyer's order and transportation costs do not significantly change with the implementation of VMI, whereas Yao et al. assume that the buyer's order cost (including a transportation component) are higher without VMI than with VMI. Yao et al. justify their assumption by noting that the supplier assumes the
⁎ Corresponding author. Tel.: +1 610 758 6726. E-mail address: [email protected] (Y. Yao). 0167-9236/$ - see front matter © 2007 Elsevier B.V. All rights reserved. doi:10.1016/j.dss.2007.03.004
ordering function, so that the buyer's order cost should decrease. In order for the sum to be approximately equal as per van der Vlist et al., transportation cost has to be higher (i.e., more frequent deliveries) with VMI since the authors assume lower order cost (i.e., van der Vlist et al. Eq. (5)). However, delivery frequency under VMI is an outcome of their model, dependent on order size. By assuming more frequent deliveries ex ante, the logic of the model is circular. Ironically, the authors find larger shipment size as an outcome of their model; that is, less frequent deliveries. If order cost is reduced and transportation cost (delivery frequency) is also reduced, the sum of these two costs cannot possibly be equal under the VMI and non-VMI cases. The assumption in van der Vlist et al. Eq. (7), that the holding cost rate for the buyer is lower under VMI than without VMI, is also problematic. If the inventory holding cost rate is assumed to be lower after the implementation of VMI, the outcome of the model is perfectly predictable; i.e., suppliers will move inventory to the buyer's location if VMI is implemented to take advantage of the lower holding cost rate. Not surprisingly, this is exactly what Vlist et al. find; their outcome is a direct result of this assumption. Moreover, the authors state that a lower inventory holding cost rate may be due to a lower transaction price or consignment arrangement under VMI. If the buyer receives price discounts from the supplier, the buyer can lower its selling price to its own customers while maintaining the same profit margin.
Y. Yao et al. / Decision Support Systems 44 (2007) 366–367
This price reduction could very well have the effect of increasing overall demand and, thus, completely altering the analysis well beyond the scope of the model. Similarly, the buyer's and supplier's cost functions would be affected under a consignment assumption. In conclusion, it is acknowledged that the extensions put forward by van der Vlist et al. [1] are reasonable additions to the Yao et al. [2] model. However, the conclusions drawn by van der Vlist et al. depend not only on the extensions, but also on two questionable assumptions. A more suitable incorporation of these extensions into the Yao et al. model could form a basis for future work. References [1] P. van der Vlist, R. Kuik, B. Verheijen, Note on supply chain integration in vendor-managed inventory, Decis. Support Syst. (in press). [2] Y. Yao, P.T. Evers, M.E. Dresner, Supply chain integration in vendor-managed inventory, Decis. Support Syst. 43 (2) (2007) 663–674. Yuliang “Oliver" Yao is an assistant professor of Information Systems and Supply Chain Management at the College of Business & Economics at Lehigh University in Bethlehem, Pennsylvania. He holds a B.S. in mechanical engineering from Shanghai Jiaotong University in China, an M.B.A. from Rensselaer Polytechnic Institute, and a Ph.D. from the University of Maryland.
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Philip T. Evers is an associate professor of Logistics and Transportation in the Robert H. Smith School of Business at the University of Maryland. He has a B.S. in business administration from Tri-State University, an M.B.A. from the University of Notre Dame, and a Ph. D. in logistics management from the University of Minnesota.
Martin Dresner is a professor of Logistics and Transportation at the University of Maryland's Robert H. Smith School of Business. He received his B. Com. from the University of Toronto, his M.B.A. from York University, and his Ph.D. in Policy Analysis from the University of British Columbia.
Response to “Note on supply chain integration in vendor managed inventory” Yuliang Yao a,⁎, Philip T. Evers b , Martin E. Dresner b b
a College of Business & Economics, Lehigh University, United States Robert H. Smith School of Business, University of Maryland, United States
Received 3 January 2007; received in revised form 24 January 2007; accepted 12 March 2007 Available online 20 March 2007
van der Vlist et al. [1] extend the Yao et al. [2] model in two fruitful ways: They explicitly consider transportation costs, first as an additional per unit order cost and then as an additional per shipment cost, whereas Yao et al. implicitly include transportation as a component of order cost. Second, while Yao et al. assume that the supplier places an order (or schedules production) when an order from the buyer decreases the supplier's inventory to zero, van der Vlist et al. allow the supplier to wait before it places its order. In addition to these two constructive extensions, however, van der Vlist et al. make two tenuous assumptions (i.e., van der Vlist et al. Eqs. (6), (7)) that are not in Yao et al. If the two assumptions are relaxed, van der Vlist et al.'s conclusions cannot be drawn, suggesting that the validity of their conclusions is based not only on their extensions but also on these two assumptions. In van der Vlist et al. Eq. (6), the authors assume that the sum of the buyer's order and transportation costs do not significantly change with the implementation of VMI, whereas Yao et al. assume that the buyer's order cost (including a transportation component) are higher without VMI than with VMI. Yao et al. justify their assumption by noting that the supplier assumes the
⁎ Corresponding author. Tel.: +1 610 758 6726. E-mail address: [email protected] (Y. Yao). 0167-9236/$ - see front matter © 2007 Elsevier B.V. All rights reserved. doi:10.1016/j.dss.2007.03.004
ordering function, so that the buyer's order cost should decrease. In order for the sum to be approximately equal as per van der Vlist et al., transportation cost has to be higher (i.e., more frequent deliveries) with VMI since the authors assume lower order cost (i.e., van der Vlist et al. Eq. (5)). However, delivery frequency under VMI is an outcome of their model, dependent on order size. By assuming more frequent deliveries ex ante, the logic of the model is circular. Ironically, the authors find larger shipment size as an outcome of their model; that is, less frequent deliveries. If order cost is reduced and transportation cost (delivery frequency) is also reduced, the sum of these two costs cannot possibly be equal under the VMI and non-VMI cases. The assumption in van der Vlist et al. Eq. (7), that the holding cost rate for the buyer is lower under VMI than without VMI, is also problematic. If the inventory holding cost rate is assumed to be lower after the implementation of VMI, the outcome of the model is perfectly predictable; i.e., suppliers will move inventory to the buyer's location if VMI is implemented to take advantage of the lower holding cost rate. Not surprisingly, this is exactly what Vlist et al. find; their outcome is a direct result of this assumption. Moreover, the authors state that a lower inventory holding cost rate may be due to a lower transaction price or consignment arrangement under VMI. If the buyer receives price discounts from the supplier, the buyer can lower its selling price to its own customers while maintaining the same profit margin.
Y. Yao et al. / Decision Support Systems 44 (2007) 366–367
This price reduction could very well have the effect of increasing overall demand and, thus, completely altering the analysis well beyond the scope of the model. Similarly, the buyer's and supplier's cost functions would be affected under a consignment assumption. In conclusion, it is acknowledged that the extensions put forward by van der Vlist et al. [1] are reasonable additions to the Yao et al. [2] model. However, the conclusions drawn by van der Vlist et al. depend not only on the extensions, but also on two questionable assumptions. A more suitable incorporation of these extensions into the Yao et al. model could form a basis for future work. References [1] P. van der Vlist, R. Kuik, B. Verheijen, Note on supply chain integration in vendor-managed inventory, Decis. Support Syst. (in press). [2] Y. Yao, P.T. Evers, M.E. Dresner, Supply chain integration in vendor-managed inventory, Decis. Support Syst. 43 (2) (2007) 663–674. Yuliang “Oliver" Yao is an assistant professor of Information Systems and Supply Chain Management at the College of Business & Economics at Lehigh University in Bethlehem, Pennsylvania. He holds a B.S. in mechanical engineering from Shanghai Jiaotong University in China, an M.B.A. from Rensselaer Polytechnic Institute, and a Ph.D. from the University of Maryland.
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Philip T. Evers is an associate professor of Logistics and Transportation in the Robert H. Smith School of Business at the University of Maryland. He has a B.S. in business administration from Tri-State University, an M.B.A. from the University of Notre Dame, and a Ph. D. in logistics management from the University of Minnesota.
Martin Dresner is a professor of Logistics and Transportation at the University of Maryland's Robert H. Smith School of Business. He received his B. Com. from the University of Toronto, his M.B.A. from York University, and his Ph.D. in Policy Analysis from the University of British Columbia.