This particular research work provided a better understanding for the practices of existing supply chain paradigms i.e., lean, agile, resilient and green which is commonly known as LARG; and how these LARG practices of Supply Chain (SC) impact the performance of SC. To measure the performance of SC three sub-factors were identified from literature i.e., operational performance, economic performance, and environmental performance. Measuring the performance of LARG practices of SC is entirely under researched area, as it has never been attempted by researcher before. To measure the performance of LARG practices of SC a framework was theorized after through literature review. The performance evaluation of LARG practices of SC provided the supervisors with better understandings about the areas where the performance of SC could be enriched. Moreover, it could also be identified that what are the areas which require special attention so that better performance could be achieved. Measurement of SC performance allowed not only the suppliers but also the retail distributors to evaluate their own performance as well as performance of their sub-contractors. Likewise, it also provided the opportunity to recognize what elements enhance the SC performance and what all factors weaken the SC performance. There should be equilibrium among the sub factors of performance i.e., operational performance, economic performance, and environmental performance. The previously available research studies relating to the topic of LARG practices of SC paradigms have been carried out independently; because there is not even a single research study available in which all four LARG paradigms of SC has been evaluated simultaneously and no effort has been made to empirically validate any of LARG paradigms. It is also worth mentioning that there is no single research study available in which impact of LARG practices of SC have been evaluated on the performance of SC having three sub factors i.e., operational performance, economic performance and environmental performance. So this is the very first study in which key performance indicators are identified and developed to form four constructs of independent variable i.e., lean, agile, resilient and green and three constructs of dependent variables i.e., operational performance, economic performance and environmental performance. Subsequently the indicators for the constructs were selected, basing upon these indicators final items were also adapted with the help of previous literature. Afterwards by using these indicators and constructs few hypotheses were suggested and basing upon these hypotheses a conceptual framework was formulated. For the empirical validation of this framework mixed methodology approach was applied in this thesis, the theorized conceptual framework was tested in two phases. In first phase the causal relationships were evaluated at the indicator to indicator level; indicators were compared for four independent and three dependent level variables with the help of five Pakistani textile industry‘s qualitative case studies. In these qualitative case studies, firstly the perception is recorded for the importance of every indicator and then subsequently actual implementation level of these indicators in the said case study industries was recorded. Consequently, the causal loop diagram technique was used to measure the causal relationship of every indicator of independent variable with every indicator of dependent variable. The results of causal loop diagram provided us the general view of causal relationships amongst indicators of depend and independent variables. The qualitative case study analysis results facilitated us to conclude that the executives involved in the textile industry SC, not only give due importance but also actually implement these LARG practices of SC and likewise to the measures of SC performance; which accordingly better revealed the impacts of these practices on the performance of SC. The results and conclusion of this exploratory type of qualitative analysis helped us to understand that how this framework could be useful for Pakistani textile industry particularly and global textile industry generally. Theorized conceptual framework was empirically validated in second phase with the help large scale quantitative analysis. This is the unique attempt in which the scale was adapted from state of the art literature review, which was not only tested for reliability but also for different kinds of validity which included, face; content; discriminant and convergent validity using SPSS 20 and AMOS 20 soft wares. The large-scale data of survey responses was obtained by using this reliable and validated instrument form Pakistani manufacturing industries and then this data was transferred to SPSS for further analysis. After carrying out initial descriptive statistics analysis, Structure Equation Modeling (SEM) was performed using AMOS-20 software, to test four main and twelve sub hypotheses. These hypotheses testing enabled us to empirically validate the theorized conceptual framework. The SEM, hypotheses testing results and goodness of fit statistics showed that there is no issue in theorizing of the conceptual framework, as well as empirically validation of the theorized conceptual framework. Empirically validated framework in third phase was also case tested where LARG framework was applied on China Pakistan Economic Corridor as a case study; for verification of the results scenario planning technique was applied.