Moving up the energy ladder: does socio-religious status matter?

This paper investigates the role played by socio-religious categories in determining primary cooking fuel choices among Indian households. We study this role in the broader context of climbing up the energy ladder. Our estimates based on a sample of 601,509 households and using multinomial probit regression suggest that socio-religious status along with economic status is critical in the choice of modern eco-friendly fuels. We find that belonging to a marginalized community in Hindu religion significantly dampens a households’ likelihood to move up the ladder when compared with upper caste households. While intra-religion differences among Hindu castes in terms of their probability of using modern fuels are wider, differences among Muslims appear smaller. Also, though Muslims perform worse than Hindu upper castes in terms of probability of using modern fuels they are much better off in comparison with other Hindu castes. Our results remain robust to alternative specifications and several robustness checks.

     

The Design of a Knowledge-Based Decision Support System to Support the Information Analyst in Determining Requirements

Decision support system (DSS) researchers and designers continue to look for unstructured organizational tasks where there is a critical need for intelligent computer-based support. One such decision task is information requirements determination. Requirements determination is recognized as the most crucial phase of the systems development life cycle. Unfortunately, most methodologies and CASE tools focus only on how to specify the requirements once they are determined. There is very little computer support for the process of determining requirements. This paper discusses the conceptual design and development of a knowledge-based DSS to support information analysts in the critical decision task of determining requirements for the design of effective information systems. The expert modeling support system has the expertise to assist the analyst in studying the organization as a whole and in modeling the system under study in the context of the overall organization's goals and needs. The focus of the paper is on the problems associated with building the knowledge base component of the intelligent decision support system. A prototype implementation of the system is described.     

Application of hybrid framework to facilitate lean six sigma implementation: a manufacturing company case experience

This study aims to propose a hybrid framework for lean six sigma (LSS) based on the prioritisation of barriers and solution approaches, to facilitate hassles free applications for handling the challenges of wastes reduction and quality improvement. The study identifies 27 LSS barriers and 22 solution approaches through literature review and utilises feedback from industry experts. For framework, study uses fuzzy AHP-PROMETHEE to prioritise LSS barriers and solution approaches. Incorporating fuzzy sets in analytical hierarchy process (AHP) ensures the optimality of barrier weights. Whereas, preference ranking organisation method for enrichment of evaluations (PROMETHEE) helps in pairwise comparisons of solution approaches with respect to each LSS barrier, facilitating fair judgements. This research guides regarding the development of framework and checks its suitability and robustness through case application of an Indian manufacturing organisation. Authors expect that researchers and practitioners will find study useful for LSS and multi criteria decision making(MCDM) domains.     

A Class of Estimators of Population Variance Using Auxiliary Information in Sample Surveys

This article advocates the problem of estimating the population variance of the study variable using information on certain known parameters of an auxiliary variable. A class of estimators for population variance using information on an auxiliary variable has been defined. In addition to many estimators, usual unbiased estimator, Isaki's (1983), Upadhyaya and Singh's (1999), and Kadilar and Cingi's (2006) estimators are shown as members of the proposed class of estimators. Asymptotic expressions for bias and mean square error of the proposed class of estimators have been obtained. An empirical study has been carried out to judge the performance of the various estimators of population variance generated from the proposed class of estimators over usual unbiased estimator, Isaki's (1983), Upadhyaya and Singh's (1999) and Kadilar and Cingi's (2006) estimators.     

Relative performance of academic departments using DEA with sensitivity analysis

The process of liberalization and globalization of Indian economy has brought new opportunities and challenges in all areas of human endeavor including education. Educational institutions have to adopt new strategies to make best use of the opportunities and counter the challenges. One of these challenges is how to assess the performance of academic programs based on multiple criteria. Keeping this in view, this paper attempts to evaluate the performance efficiencies of 19 academic departments of IIT Roorkee (India) through data envelopment analysis (DEA) technique. The technique has been used to assess the performance of academic institutions in a number of countries like USA, UK, Australia, etc. But we are using it first time in Indian context to the best of our knowledge. Applying DEA models, we calculate technical, pure technical and scale efficiencies and identify the reference sets for inefficient departments. Input and output projections are also suggested for inefficient departments to reach the frontier. Overall performance, research performance and teaching performance are assessed separately using sensitivity analysis.     

Interventions for an Artemisinin‐based Malaria Medicine Supply Chain

Artemisinin combination therapy, the most effective malaria treatment today, is manufactured from an agriculturally derived starting material Artemisia annua. Artemisinin, the main ingredient in malaria medicines, is extracted from Artemisia leaves and used in the production of medicine for treating malaria. The artemisinin market has witnessed high volatility in the supply and price of artemisinin extract. A large fraction of malaria medicines for endemic countries in sub‐Saharan Africa is financed by the Global Fund to Fight AIDS, TB, and Malaria and the US President's Malaria Initiative. These agencies together with the World Health Organization, UNITAID, the United Kingdom Department for International Development and the Bill and Melinda Gates Foundation are exploring ways to increase the level of artemisinin production, reduce volatility of artemisinin prices, and improve overall access to malaria medicines for the population. We develop a model of the supply chain, calibrate the model using field data, and investigate the impact of various interventions. Our model shows that initiatives aimed at improving average yield, creating a support‐price for agricultural artemisinin, and a larger and carefully managed supply of semi‐synthetic artemisinin have the greatest potential for improving supply and reducing price volatility of artemisinin‐based malaria medicine.     

Supply Chains and Global Health: An Imperative for Bringing Operations Management Scholarship into Action

Many people in developing countries do not have access to effective vaccines, medicines, and other life‐saving health technologies. Shortage of health care workers, severe financial constraints, and lack of awareness are some of the major obstacles that prevent higher access. However, ineffective and poorly designed supply chains for purchasing and distributing the medicines, vaccines, and health technologies are one of the most important barriers to increasing access. We argue that the ineffectiveness of the global health supply chain can be attributed largely to: coordination problems across multiple stakeholders with widely divergent objectives, lack of careful supply chain design, and use of myopic operational objectives and metrics. The operations management research community can contribute to improving this by applying existing knowledge to the field of global health delivery and by researching new frameworks of analysis which would then become the cornerstones for policy advice to those who design, operate, or finance these supply chains.