Information distortion in a supply chain: the bullwhip effect
Management Science - Special issue on frontier research in manufacturing and logistics
Value of Information in Capacitated Supply Chains
Management Science
Developing a Theory of Reverse Logistics
Interfaces
Manufacturing & Service Operations Management
The Effect of Collaborative Forecasting on Supply Chain Performance
Management Science
The Value of Information Sharing in a Two-Level Supply Chain
Management Science
Supply Chain Inventory Management and the Value of Shared Information
Management Science
A model and a performance measurement system for collaborative supply chains
Decision Support Systems
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
A Knowledge-based Customization System for Supply Chain Integration
Expert Systems with Applications: An International Journal
Multi-enterprise collaborative decision support system
Expert Systems with Applications: An International Journal
Hi-index | 12.05 |
In the past few decades several supply chain management initiatives such as Vendor Managed Inventory, Continuous Replenishment and Collaborative Planning Forecasting and Replenishment (CPFR) have been proposed in literature to improve the performance of supply chains. But, identifying the benefits of collaboration is still a big challenge for many supply chains. Confusion around the optimum number of partners, investment in collaboration and duration of partnership are some of the barriers of healthy collaborative arrangements. To evolve competitive supply chain collaboration (SCC), all SC processes need to be assessed from time to time for evaluating the performance. In a growing field, performance measurement is highly indispensable in order to make continuous improvement; in a new field, it is equally important to check the performance to test conduciveness of SCC. In this research, collaborative performance measurement will act as a testing tool to identify conducive environment to collaborate, by the way of pinpointing areas requiring improvements before initializing collaboration. We use actual industrial data and simulation to help managerial decision-making on the number of collaborating partners, the level of investments and the involvement in supply chain processes. This approach will help the supply chains to obtain maximum benefit of collaborative relationships. The use of simulation for understanding the performance of SCC is relatively a new approach and this can be used by companies that are interested in collaboration without having to invest a huge sum of money in establishing the actual collaboration.