Abstract
Value chain reconstruction, designed according to green and growth coordination requirements, is a critical path for an enterprise to implement the green growth model and realize green transformation. During value chain reconstruction, the enterprise systematically evaluates each activity’s agent and element in the value network and establishes the value chain based on the mission or problem orientation. The reconstruction implementation involves the reselection and matching of cooperation agents, such as the choice of suppliers, and the devotion and adjustment of activity elements, such as the adoption of environmental management technology, is often carried out in the form of a project. Due to the influence of uncertain factors on the value chain reconstruction, the enterprise faces the disturbance of complex and dynamic environments. Hence, it should effectively manage the activities before and during the reconstruction. For the aforementioned facts, the proactive and reactive project scheduling theories can provide important support for the enterprise to reconstruct its value chain. Additionally, because value chain reconstruction involves the coordination of green and growth, its implementation must simultaneously consider time, cost, and schedule robustness. As a result, multi-objective project scheduling theory can also be employed to help the organization of value chain reconstruction. Based on the above discussion, this chapter presents the relationship between value chain reconstruction and project management first. Then, we introduce the model and algorithm for proactive and reactive project scheduling to maximize the net present value (NPV). Finally, we describe the time-cost-robustness trade-off project-scheduling method in an uncertain environment.
| Original language | English |
|---|---|
| Title of host publication | Enterprises’ Green Growth Model and Value Chain Reconstruction |
| Subtitle of host publication | Theory and Method |
| Publisher | Springer Nature |
| Pages | 347-372 |
| Number of pages | 26 |
| ISBN (Electronic) | 9789811939914 |
| ISBN (Print) | 9789811939907 |
| DOIs | |
| State | Published - 1 Jan 2022 |