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This paper presents an integrated methodology to support decision making in cooperation through interorganizational information sharing. The methodology employs game-theoretic approach to determine whether it is advantageous to share information between two or three firms, each possessing one piece of information. While a firm in a two-firm situation has to decide either sharing nothing or sharing all, a firm in a three-firm situation has an additional decision to determine with which firm it should form coalition. A scope of this research focuses on two collaborative frameworks: 1) competitioncooperation and 2) co-opetition. Finally, examples are provided to illustrate how the methodology can be used in practice.

There are several techniques of inventory classification and prioritization based on a single criteria, bi-criteria, or multiple criteria; however, managing inventory can fail when trying to fit inventory classes into the operating budget and available warehouse space. This research focuses on optimizing inventory classes and determining an optimal service level of each class while simultaneously satisfying operating budget and space constraints. The idea is to help decision makers to effectively rank and group SKUs and manage them within the constraints while satisfying customers. This proposed methodology is an optimality-based approach that uses mixed integer linear programing to solve the problem. Computational experiments are conducted to illustrate the proposed method. Results are compared with a classical ABC inventory analysis.