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In this study, carbon dioxide emissions resulting from transportation are assessed, carbon emission reduction opportunities in the current service supply chain design of Cisco Systems, Inc. are explored. Among these opportunities, changing transport mode from a high-carbon transport mode to a low-carbon transport mode is found to be the most promising option and is scrutinized. The effect of transportation mode change on carbon emission and expected total cost are scrutinized by developing a mathematical model that minimizes expected total cost subject to aggregate fill rate constraint. Furthermore, a second model that minimizes the expected total cost under aggregate expected fill rate and carbon emission constraints is developed. In this model transportation mode choice decisions are integrated into inventory decisions. Since it is difficult to make transportation mode selection for each individual item, the items are clustered and transportation mode selection is made for each cluster. Therefore we propose two clustering methods that are k-means clustering and an adopted ABC analysis. In addition, a greedy algorithm based on second model is developed. Since currently there are no regulations on carbon emissions, in order to examine possible regulation scenarios computational studies are carried out. In these studies, efficient solutions are generated and the most preferred solutions that have less carbon emission and lower total cost among all efficient solutions are examined.M.S. - Master of Scienc