Modeling and analysis of lateral collaboration decision protocols in supply networks

Hyesung Seok, Purdue University

Abstract

Collaboration has been discussed for a long time as the key for sustainable and competitive supply networks. As the complexity of supply networks has been increasing and market competition has become keener, professional and appropriate use of collaboration becomes an indispensable strategy of companies. A lot of research has been studied in this area; however, most of them have mainly focused on vertical collaboration rather than lateral collaboration in supply networks. Therefore, in this thesis, we emphasize the importance of lateral collaboration, and find out what is needed for its effective uses. Especially, intelligent lateral collaboration by information sharing can increase companies' profit by achieving more effective planning; lateral collaboration by selective and adaptive demand and capacity sharing can reduce lost sales and idle capacity, and increase profit. Furthermore, distributed decision making among independent companies can achieve well-balanced lateral collaboration. We propose a general framework supported by several Collaboration Control Theory (CCT) principles for addressing intelligent decision making in lateral collaboration problems. This is applied to three specific cases--intelligent information sharing, collaborative demand and capacity sharing (CDCS), and adaptive reformation of CDCS among manufacturing companies. Different parts of a general framework are activated, depending on the characteristics of each case. Also, in each case, an appropriate decision protocol is developed: Intelligent Supplier Information Sharing (ISIS) protocol for the first case, Collaborative Demand and Capacity Sharing (CDCS) protocol for the second case, and Adaptive CDCS protocol for the third case. Compared to the alternative strategies, no collaboration and complete collaboration, the results from the three case studies indicate that the proposed general framework and decision protocols achieve significant improvements in several performance indicators, e.g., ISIS protocol increases on average 15.5% profit; CDCS-(2) protocol reduces on average 51.9% lost sales and 32.8% idle capacity, and increases on average 3.9% profit. Also, the level of well-balanced profits is increased by between 13.8% and 27.5%, and on average, by 20.1%; Adaptive CDCS protocol increases profit from 4.4% to 8.1%, on average, 6.5%.

Degree

Ph.D.

Advisors

Nof, Purdue University.

Subject Area

Industrial engineering

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