A Proposed Islamic Microfinance Impact Assessment Methodology

Impact assessment of microfinance programs have been remained the foremost concern of microfinance stakeholders for optimal policy measures. The existing literature regarding the impact assessment varies from parametric to experimental methods to evaluate the performance of microfinance programs across the world however; the literature is lacking a single measure to reveal maximum possible changes in socioeconomic variables resulting from microfinance institutions’ intervention. This study aims to develop a composite index for evaluating the performance of microfinance programs in multi-dimensional contexts. The study exposes a set of eight “diverse indicators” to evaluate the performance of a microfinance program on a wider socioeconomic scale. The dimensions of the index are consist of economic (Income, saving) and socioeconomic (poverty, access to basic facilities, family empowerment) indicators. The changes in deprivations of household, based on the selected indicators, reveal the intensity of success of a microfinance program towards their goals. Finally, we have developed an index by the interaction of incidence and intensity of socioeconomic deprivations. The index is named as “Multidimensional Microfinance Deprivation Index”. This is an index developed in the same line as multidimensional poverty index. The implications of this study are three folds; firstly, it will open up a new dimension of literature in the field of microfinance including Islamic microfinance by instigating an important area. Secondly, it may provide a better alternative to microfinance’s stakeholders to investigate the impact assessment of microfinance programs on a wider socioeconomic scale rather than a few economic. Last but not the least, the study integrates diverse socioeconomic indicators, after assigning weights and adjustment to portray an overall picture of the performance of microfinance in terms of uplifting the socioeconomic conditions of the poor and financially marginalized people.

Failure Creteria for the Design & Stability Anlaysis of Tunnels in the Rock Mass Environment of Kp Using Numerical Modeling

The stability of a tunnel in rocks can be evaluated through different methods. Empirical design methods are commonly used supplemented and validated with numerical design methods to improve the stability. Each and every design method requires certain rock and rock mass parameters as input. Empirical design methods include Rock Mass Classification systems as integral part. Strength and/or stiffness parameters are frequently required for Numerical design analysis. Rock mass properties can either be determined directly or predicted, however, the direct determination is not always viable and these are generally predicted. Rock mass strength and deformability is realistically well predicted through the use of rock mass classification systems in conjunction with appropriate empirical failure criteria such as Hoek-Brown failure criterion and empirical expressions using rock mass classification systems respectively. However, the use of such relations requires right, precise and authentic input data. The thesis focuses on devising better ways and means for approximating the input parameters needed for engineering design of tunnels in rocks. The first part of this research focuses on fitting of failure criterion to laboratory data to get a suitable failure criterion for the local rock mass environment and optimize the strength parameters for numerical design purposes. The second part describes the empirical estimation of rock mass deformation modulus. The Hoek – Brown failure criterion 2002 version and its variants are fitted to full scale laboratory rock data of Kohat Tunnel as well as Diamir Basha Dam Diversion Tunnels using linear and multiple regression methods and Microsoft Excel optimization tool "Solver". Analysis shows that for majority cases/ rock types, the ―Globalized‖ variant of the Hoek – Brown failure criterion is best fit based on error of estimation. For the deformation modulus, previous equations (based on Rock Mass Rating, Q index and Geological Strength Index) are divided into 10 groups on the basis of input parameters and modeled using ―Sigmoidal‖ and ―Gaussian‖ functions in Microsoft Excel solver optimization tool. Eight new generalized equations are presented, among which, the sigmoidal function was the best. iii It is observed that the displacement values from the modeled deformation modulus (sigmoidal function based on GSI using the 2D Finite Element Analysis (FEA) Phase2 tool) was very close to the actual displacement monitored in the field.