There has been a rapid growth in industrialization over the last few decades. This has in-turn lead to an increase in production and consumption of various goods.  Industrialization at such a rapid pace has done a considerable amount of damage to the society and environment including depletion of natural resources, wastes generation during  production, rising transport emissions and congestion,  non-disposability of goods at the end of their product life-cycle, and stressful work environment for employees. These emerging issues have put forth the need for greater emphasis on sustainability issues and consequently development of sustainable supply chains to sustain this rapid economic growth while respecting environmental and social issues.
In this thesis, we present a modeling framework to study the different enablers for sustainable supply chains, analyze their inter-relationships and propose alternatives for sustainable supply chain development. In the first step, a comprehensive literature review is performed to identify the enablers and provide insights on the triple bottom line concept (environment, social, economic) of sustainability. In the second step, Interpretative Structural Modelling is used to develop the relationship among various enablers for each dimension of sustainability.   In the third and the last step, results of ISM are used as an input to Analytic Network Process along with potential list of alternatives to determine the best alternative(s) for developing sustainable supply chains. 
The proposed approach is novel and deals with an important problem of modeling enablers and alternatives for sustainable supply chain management. The results have strong practical applicability and can be adapted by organizations with least changes in their existing work structure.