Abstract
In this study, we have examined the performance of an online seller under two distinct fulfillment modes (fulfillment by seller and fulfillment by E-marketplace) under two shipping fee policies (free shipping and flat rate shipping). We have derived closed form analytical expressions for the decision variables of the seller such as sale price, sales volume and profit under the fulfillment modes for the shipping policies under consideration. We have checked the validity of the model by considering a leading Indian E-marketplace. From the case example, we obtained the following results (1) The seller is better off when engaged in a contract with the E-marketplace for inventory storage and order fulfillment (2) The seller is gainful by adopting a free shipping policy than a flat rate shipping policy (3) The impact of referral fee variation by the E-marketplace can significantly affect the profit of the seller whereas the impact of lead time variation has minimal impact on the profit of the seller.
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References
Lewis, M., Singh, V., & Fay, S. (2006). An empirical study of the impact of nonlinear shipping and handling fees on purchase incidence and expenditure decisions. Marketing Science, 25(1), 51–64.
Amazon India says number of sellers crosses 1 lakh | IndianOnlineSeller.com. (2016). Indian Online Seller.
Xia, L., & Monroe, K. B. (2004). Price partitioning on the internet. Journal of Interactive Marketing, 18(4), 63–72.
Hua, G., Wang, S., & Cheng, T. C. E. (2012). Optimal order lot sizing and pricing with free shipping. European Journal of Operational Research, 218(2), 435–441.
Boone, T., & Ganeshan, R. (2013). Exploratory analysis of free shipping policies of online retailers. International Journal of Production Economics, 143(2), 627–632.
Khouja, M. (2001). The evaluation of drop shipping option for e-commerce retailers. Computers & Industrial Engineering, 41(2), 109–126.
Netessine, S., & Rudi, N. (2006). Supply chain choice on the internet. Management Science, 52(6), 844–864.
Randall, T., Netessine, S., & Rudi, N. (2006). An empirical examination of the decision to invest in fulfillment capabilities: A study of internet retailers. Management Science, 52(4), 567–580.
Yao, D. Q., Kurata, H., & Mukhopadhyay, S. K. (2008). Incentives to reliable order fulfillment for an internet drop-shipping supply chain. International Journal of Production Economics, 113(1), 324–334.
Hovelaque, V., Soler, L. G., & Hafsa, S. (2007). Supply chain organization and e-commerce: A model to analyze store-picking, warehouse-picking and drop-shipping. 4OR, 5(2), 143–155.
Chen, F. Y., Hum, S. H., & Sim, C. H. (2005). On inventory strategies of online retailers. Journal of Systems Science and Systems Engineering, 14(1), 52–72.
Chiang, W. K., & Feng, Y. (2009). Retailer or e-tailer? Strategic pricing and economic-lot-size decisions in a competitive supply chain with drop-shipping. Journal of the Operational Research Society, 61(11), 1645–1653.
Gan, X., Sethi, S. P., & Zhou, J. (2010). Commitment-penalty contracts in drop-shipping supply chains with asymmetric demand information. European Journal of Operational Research, 204(3), 449–462.
Chen, J., Chen (Frank), Y., Parlar, M., & Xiao, Y. (2011). Optimal inventory and admission policies for drop-shipping retailers serving in-store and online customers. IIE Transactions, 43(5), 332–347.
Ayanso, A., Diaby, M., & Nair, S. K. (2006). Inventory rationing via drop-shipping in internet retailing: A sensitivity analysis. European Journal of Operational Research, 171(1), 135–152.
Serel, D. A. (2015). Production and pricing policies in dual sourcing supply chains. Transportation Research Part E: Logistics and Transportation Review, 76, 1–12.
Becerril-Arreola, R., Leng, M., & Parlar, M. (2013). Online retailers’ promotional pricing, free-shipping threshold, and inventory decisions: A simulation-based analysis. European Journal of Operational Research, 230(2), 272–283.
Koukova, N. T., Srivastava, J., & Steul-Fischer, M. (2012). The effect of shipping fee structure on consumers’ online evaluations and choice. Journal of the Academy of Marketing Science, 40(6), 759–770.
Zhou, B., Katehakis, M. N., & Zhao, Y. (2009). Managing stochastic inventory systems with free shipping option. European Journal of Operational Research, 196(1), 186–197.
Song, J., Yin, Y., & Huang, Y. (2017). A coordination mechanism for optimizing the contingent-free shipping threshold in online retailing. Electronic Commerce Research and Applications, 26, 73–80.
Leng, M., & Becerril-Arreola, R. (2010). Joint pricing and contingent free-shipping decisions in B2C transactions. Production and Operations Management, 19(4), 390–405.
Huang, W. H., & Cheng, Y. C. (2015). Threshold free shipping policies for internet shoppers. Transportation Research Part A: Policy and Practice, 82, 193–203.
Shao, X. F. (2017). Free or calculated shipping: Impact of delivery cost on supply chains moving to online retailing. International Journal of Production Economics, 191(June), 267–277.
Schindler, R. M., Morrin, M., & Bechwati, N. N. (2005). Shipping charges and shipping-charge skepticism: Implications for direct marketers’ pricing formats. Journal of Interactive Marketing, 19(1), 41–53.
Dinlersoz, E. M., & Li, H. (2006). The shipping strategies of internet retailers: Evidence from internet book retailing. Quantitative Marketing and Economics, 4(4), 407–438.
Yao, Y., & Zhang, J. (2012). Pricing for shipping services of online retailers: Analytical and empirical approaches. Decision Support Systems, 53(2), 368–380.
Gümüş, M., Li, S., Oh, W., & Ray, S. (2013). Shipping fees or shipping free? A tale of two price partitioning strategies in online retailing. Production and Operations Management, 22(4), 758–776.
Leng, M., & Parlar, M. (2005). Free shipping and purchasing decisions in B2B transactions: A game-theoretic analysis. IIE Transactions (Institute of Industrial Engineers), 37(12), 1119–1128.
Brynjolfsson, E., & Smith, M. D. (2000). Frictionless commerce? A comparison of internet and conventional retailers. Management Science, 46(4), 563–585.
Lewis, M. (2006). The effect of shipping fees on customer acquisition, customer retention, and purchase quantities. Journal of Retailing, 82(1), 13–23.
Menezes, R. (2017). Amazon sellers forced to hike prices by 3rd May once commissions are revised. Indian online seller.
Acknowledgements
The authors gratefully acknowledge University Grants Commission-India for supporting the study under UGC JRF scheme under the grant number 1528 (NET-DEC 2012).
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Appendix
Appendix
1.1 Equilibrium analysis of fulfillment by seller model
In this section, we carry out the equilibrium analysis of FBS model. First, we translate the cost elements to their corresponding symbolic expressions for deriving closed form analytic solutions.
1.1.1 Cost elements of the seller
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(1)
$${\rm Inventory} \, {\rm holding} \, {\rm cost} \, + \, {\rm Shipping} \, {\rm cost} \, + \, {\rm Packaging} \, {\rm cost} \, = h^{s} \frac{{D_{j}^{s} }}{2} + D_{j}^{s} (x_{1}^{s} f_{1}^{s} + x_{2}^{s} f_{2}^{s} + x_{3}^{s} f_{3}^{s} ) + D_{j}^{s} g^{s}$$(15)
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(2)
$${\rm e-marketplace} \, {\rm fee} \, = \, \text{Referral} \, \text{fee} \, + \, \text{Closing} \, \text{fee} \, = D_{j}^{s} (p_{FS}^{s} \delta + k)$$(16)
1.1.2 Profit of the seller under free shipping policy
Profit of the seller = Demand * Margin per product sold − Cost incurred by the seller
The objective of the retailer is to maximize his profit, i.e. \({\text{Max }}\pi_{FS}^{s}\).The F.O.C \(\frac{{\partial \pi_{FS}^{s} }}{{\partial p_{FS}^{s} }} = 0\) yields the optimal price as follows
Using the expression of the optimal price, we can derive the expression for optimal sales volume from Eq. (1) as shown below
Now by substituting \(p_{FS}^{s*}\) and \(Q_{FS}^{s*}\), we can obtain the expression for the optimal profit of the seller from Eq. (3) as follows
1.1.3 Profit of the seller under flat rate shipping fee policy
The margin per product sold under flat rate shipping is as follows
Margin per product sold = sale price − procurement cost + shipping fee
Hence, the profit of the seller is as follows
The optimal price of the seller under flat rate shipping fee policy
The optimal sales volume of the seller can be derived by substituting \(p_{CS}^{s*}\) into Eq. (2) as given below
Further, substituting the \(p_{CS}^{s*}\) and \(Q_{CS}^{s*}\) into Eq. (21) will yield the optimal profit of the seller as follows
1.2 Equilibrium analysis of fulfillment by E-marketplace model
In this section, we carry out the equilibrium analysis of FBE model. Under FBE model the seller uses E-marketplace partnered logistic services (lower shipping cost) for shipping products to the fulfillment centers. The shipping cost of E-marketplace partnered logistics service is lower than that of a 3PL service provider. We have assumed that the seller replenishes the inventory on a monthly basis, i.e. at the start of a month (selling season), the seller ships the products to the fulfillment centers of the E-marketplace through the E-marketplace partnered logistics service provider.
First, we translate the cost elements of the seller into corresponding mathematical expressions for carrying out the equilibrium analysis. Under FBE, the seller incurs two major types of costs viz. (1) Cost of packing the product at an aggregate level and sending it to multiple fulfillment centers of the E-marketplace, i.e. bulk packing cost (2) The fee to be paid to the E-marketplace for carrying out the fulfillment procedure on behalf of the seller. The cost elements of the seller are shown as follows
1.2.1 Profit of the seller under free shipping policy
The profit of the seller = Demand * Margin per product sold − Cost incurred by the seller
The objective of the seller is to maximize his profit, i.e. \({\text{Max }}\pi_{FS}^{e}\). The F.O.C \(\frac{{\partial \pi_{FS}^{e} }}{{\partial p_{FS}^{e} }} = 0\) yields the optimal price as follows
Substitution of \(p_{FS}^{e*}\) into Eq. (3) yields the optimal sales volume of the seller as follows
Further, by substituting \(p_{FS}^{e*}\) and \(Q_{FS}^{e*}\) into Eq. (26), we can obtain the optimal profit of the seller.
1.2.2 Profit of the seller under flat rate shipping fee
The margin per product sold under flat rate shipping policy is as follows
Margin per product sold = sale price − procurement cost + shipping fee
In this case, the profit of the seller is given as follows.
The objective of the seller is to maximize his profit, i.e. \({\text{Max }}\pi_{CS}^{e}\).The F.O.C \(\frac{{\partial \pi_{CS}^{e} }}{{\partial p_{CS}^{e} }} = 0\) yields the optimal price as follows.
We can obtain the optimal sales volume by substituting of \(p_{CS}^{e*}\) in Eq. (3) as given below
Now, we substitute \(p_{CS}^{e*}\) and \(Q_{CS}^{e*}\) into Eq. (30) for obtaining the optimal profit of the seller.
Proof of Proposition 1
Sale price under free shipping (FBS) − Sale price under flat rate shipping fee (FBS)
Sale price under free shipping policy (FBE) − Sale price under flat rate shipping fee policy (FBE)
Proof of Proposition 2
Sales volume under flat rate shipping fee policy (FBS) − Sales volume under free shipping policy (FBS)
Proof of Proposition 3
Profit of the seller under flat rate shipping fee policy (FBS) − Profit of the seller under free shipping policy (FBS)
Proof of Proposition 4
Sales volume under flat rate shipping fee policy (FBE) − Sales volume under free shipping policy (FBE)
Proof of Proposition 5
Profit of the seller under flat rate shipping fee policy (FBE)  −  Profit of the seller under free shipping policy (FBE)
After simplification of the expression.
Inorder to have \(\pi_{FS}^{e*} > \pi_{CS}^{e*}\)(proposition 5), we can derive the following expression.
Proof of Proposition 6
Impact of referral fee variation on the sale price under FBS and free shipping policy
Impact of referral fee variation on the sales volume under FBS and free shipping policy
Impact of referral fee variation on the sale price under FBS and flat rate shipping policy
Impact of referral fee variation on the sales volume under FBS and flat rate shipping policy
Impact of referral fee variation on the sale price under FBE and free shipping policy
Impact of referral fee variation on the sales volume under FBE and free shipping policy
Impact of referral fee variation on the sale price under FBE and flat rate shipping policy
Impact of referral fee variation on the sales volume under FBE and flat rate shipping policy
Proof of Proposition 7
Impact of referral fee variation on the profit of the seller under FBS and free shipping policy
Impact of referral fee variation on the profit of the seller under FBS and flat rate shipping policy
Impact of referral fee variation on the profit of the seller under FBE and free shipping policy
Impact of referral fee variation on the profit of the seller under FBE and flat rate shipping policy
The rationale underlying the deductions corresponding to proposition 7 is high magnitude of base demand compared to the other parameters of the model.
Proof of Proposition 8
Impact of shipping fee variation on the profit of the seller under FBS
Impact of shipping fee variation on the profit of the seller under FBE
Proof of Proposition 9
Impact of lead time variation on the profit of the seller under free shipping policy
Impact of lead time variation on the profit of the seller under flat rate shipping policy
Proof of Proposition 10
Impact of lead time variation on the profit of the seller under free shipping policy
Impact of lead time variation on the profit of the seller under flat rate shipping policy
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Rofin, T.M., Mahanty, B. Fulfillment mode selection for Indian online sellers under free and flat rate shipping policies. Electron Commer Res 21, 263–296 (2021). https://doi.org/10.1007/s10660-019-09348-5
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DOI: https://doi.org/10.1007/s10660-019-09348-5