Green supplier development focuses on helping organizations integrate activities to improve the natural environmental performance of their supply chains. These green-supplier-development programs require substantial resources and investments by a buyer company. Investigation into investment management in this context has only begun. This paper introduces a methodology to help manage investment in green-supplier-development and business-supplier-development practices. Managing these practices and their outcomes requires managing of a large sets of data. We propose a combination of rough set theoretic and fuzzy clustering means (FCM) approaches; first to simplify, and then sharpen the focus on the complex environment of evaluation of the investment decisions. The combined methodology, based on performance measures of supplier practices and agreed-upon investment objectives, identifies a set of guidelines that can help make decisions about sound investments in the supplier practices more effectively and judiciously. Various steps involved in the methodology are illustrated through using an example developed to highlight the salient steps and issues of the methodology. We show how the results may be interpreted to obtain many insights useful from both practical and research perspectives. Although the impetus to developing this methodology came from sustainability considerations, the methodology is general enough to be applicable in other areas where management and evaluation of investments is based on large data sets. 
Complex investment decisions using rough set and fuzzy c-means: An example of investment in green supply chains