The evaluation of drop shipping option for e-commerce retailers |
| |
| Affiliation: | 1. School of Economics and Management, Tongji University, Shanghai 200092, China;2. School of Management and Economics, Beijing Institute of Technology, Beijing 100081, China;3. Center for Energy and Environmental Policy Research, Beijing Institute of Technology, Beijing 100081, China;4. Sustainable Development Research Institute for Economy and Society of Beijing, Beijing 100081, China;5. Naveen Jindal School of Management, University of Texas at Dallas, Dallas, TX 75080, USA;1. School of Business, Nantong University, 9 Seyuan Road, Nantong 226019, PR China;2. School of Management, University of Science and Technology of China, 96 Jinzhai Road, Hefei 230026, PR China;3. Department of E-Business & Technology Management, College of Business and Economics, Towson University, MD 21252, USA;4. Institute of Systems Engineering, School of Economics and Management, Southeast University, Sipailou 2, Nanjing 210096, PR China |
| |
| Abstract: | Many e-commerce retailers use drop shipping to satisfy demand. A retailer simply forwards customers' orders to the manufacturer who fills the orders directly to the customers and is paid a predetermined price by the retailer. Advantages of drop shipping include lower costs of holding inventory, materials handling, and obsolescence. Disadvantages of drop shipping include fragmented order delivery when a single customer order involves products from different manufacturers and longer delivery times. A mix of holding inventory and drop shipping is frequently optimal for e-retailers. In this paper, we design an optimal mix strategy which captures the advantages of drop shipping and avoids many of its shortcomings. We use two different optimization criterion, maximizing the expected profit and maximizing the probability of achieving a target profit. We provide results for uniform, exponential, and normal demand distributions. We illustrate the results with numerical examples. |
| |
| Keywords: | |
| 本文献已被 ScienceDirect 等数据库收录！ |
|
