Dual-channel sourcing and selling strategies in operations management
Abstract/Contents
- Abstract
- The ability of manufacturers and suppliers to adapt to changing market conditions is crucial in today's uncertain business environment. Having more than one sourcing or selling channel with complementary services can be an effective strategy for firms to enhance their operational flexibility. This dissertation thus investigates how firms can utilize multiple channels to efficiently procure their production and service capacity or distribute sales volumes to meet the needs of a dynamic market. It contains two major parts: First, in Chapters 2 and 3, we focus on the sourcing side and study how firms in capital-intensive industries can reduce their idle capacity while maintaining a high service level by purchasing production capacity from two supply sources. We construct a dual-mode equipment procurement model (DMEP), in which an equipment supplier provides two delivery modes to a firm: a base mode that is less expensive but slower and a flexible mode that is faster but more expensive. The combination of these two modes provides the firm the flexibility to mitigate demand risk at a potentially lower cost. Chapter 2 presents our theoretical approach and investigates a dynamic dual-source capacity expansion problem with consecutive leadtimes and demand backlogging. We demonstrate that the flexible orders follow a state-dependent base-stock policy; the base orders, however, follow only a partial-base-stock policy, which lacks structure and is difficult to track. Chapter 3 then tackles this problem from a practical perspective. Compromising optimality for applicability and efficiency, we construct a general DMEP heuristic that consists of three layers: a contract negotiation layer, in which the firm chooses the best combination of leadtime and price for each supply mode from the supply contract menu; a reservation layer, in which the firm reserves total equipment procurement quantities through the two supply modes by paying the supplier a reservation fee up front before the planning horizon starts; and an execution layer, in which the firm acquires the latest demand information in each period and orders equipment through both supply modes. We numerically quantify the value of the added flexibility for the firm and explore how the optimal reservation and execution decisions would change with respect to the key model parameters. Second, in Chapter 4, we instead study the selling side and discuss how a large commodity supplier should strategically allocate his limited production capacity between a fixed-price contract channel and a spot market to maximize his total sales income. We discuss two settings: one in which the equilibrium spot price follows an exogenous random distribution and one in which the equilibrium spot price is endogenously determined by the spot demand curve and the spot supply curve, both of which can be affected by the supplier's capacity allocation decision. In the former case, we find that the demand-price correlation and a risk-averse attitude are two reasons for the supplier to adopt a dual-channel strategy. The supplier should allocate more quantity to the spot channel if the contract channel demand and the spot price are more positively correlated, and he should allocate more to the contract channel if he is more risk-averse. In the latter setting, which further contains a contract trading stage and a spot trading stage, we show that a dual-channel policy is optimal in the first stage if the shifting effect of the supplier's spot allocation quantity on the default supply curve is stronger than the shifting effect of the unfulfilled contract channel demand on the default demand curve. Further, we demonstrate that it is not necessarily optimal to sell all leftover quantities in the spot market during the second stage. Using benchmark industry data, we quantify the average improvement in profit of adopting a dual-channel strategy versus using a single contract channel or a single spot channel through numerical analysis.
Description
| Type of resource | text |
|---|---|
| Form | electronic; electronic resource; remote |
| Extent | 1 online resource. |
| Publication date | 2011 |
| Issuance | monographic |
| Language | English |
Creators/Contributors
| Associated with | Peng, Chen |
|---|---|
| Associated with | Stanford University, Department of Management Science and Engineering |
| Primary advisor | Erhun, Feryal |
| Primary advisor | Lee, Hau Leung |
| Thesis advisor | Erhun, Feryal |
| Thesis advisor | Lee, Hau Leung |
| Thesis advisor | Hausman, Warren H |
| Advisor | Hausman, Warren H |
Subjects
| Genre | Theses |
|---|
Bibliographic information
| Statement of responsibility | Chen Peng. |
|---|---|
| Note | Submitted to the Department of Management Science and Engineering. |
| Thesis | Thesis (Ph.D.)--Stanford University, 2011. |
| Location | electronic resource |
Access conditions
- Copyright
- © 2011 by Chen Peng
- License
- This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).
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