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Contribution: The main contribution is to provide practitioners and researchers with an insight in efficiently and effectively employing multi-attribute decision making (MADM) methods in e-learning website selection problems. Background: Advances in information systems and the Internet have resulted in e-learning websites becoming an important interface for learners. The selection of a particular website directly affects the end users' performance, with the objectives and expected outcomes of e-learning being largely dependent on the quality of the teaching processes and the effectiveness of online access. Evaluation and selection of these websites has thus become a decisive issue for learners and developers. Intended Outcomes: This paper is expected to provide decision support to leaders in education and educational organizations in effectively analyzing and managing their e-learning system. A knowledge-based system may be developed to develop and assess e-learning websites in a meaningful way. Application Design: A hybrid MADM method, fuzzy complex proportional assessment (COPRAS) is used to evaluate, rank, and select e-learning websites of "C" programming language. The fuzzy COPRAS method is validated by comparison with the technique for order preference by similarity to ideal solution, on an existing selection problem of 12 websites available in the open literature. Findings: Fuzzy COPRAS provides a comprehensive ranking of e-learning websites based on fitness degree values. The case study results rated tutorialspoint.com as the best of the e-learning websites considered, and howstuffworks.com was rated lowest. This paper shows that fuzzy COPRAS could be useful for e-learning practitioners, developers, and the researchers.

Purpose: Financial access is key to achieving several economic goals in developing countries. This paper aims to construct a longitudinal village-level measure of financial access in India and understand the role of RBI's policies and village characteristics in influencing the access. Design/methodology/approach: The authors adopt a spatial approach in developing a metric of financial access. In particular, they measure the distance of each unbanked village in India to the nearest banked-centre from 1951 to 2019. The authors use this measure to conduct two exercises. First, a descriptive study is undertaken to assess how RBI's policies on bank branch expansion from 1951 to 2019 influenced the proximity to bank branches. Second, the authors conduct regression analyses to investigate how socio-economic and demographic characteristics of villages influence their proximity to bank branches. Findings: The average distance of an unbanked village to the nearest banked-centre has declined from 43.5 km in 1951 to 4.2 km in 2019. The gain in bank access has varied geographically and over time. In 2001, bank branches were relatively distant from villages with under-privileged caste groups and proximate to areas with better infrastructure. This relationship worsened after 2005 when RBI introduced liberalized branch expansion policies. By 2019, proximity responds much more adversely to the presence of underprivileged groups. At the same time, banks have moved closer to economically better-off villages and villages with workforce in non-farm enterprises rather than agriculture. Originality/value: First, studies in the Indian context focus on state-level determinants of bank branching, this is the first study to develop a longitudinal measure of financial access at the village level. This helps to understand spatial heterogeneity in bank branch access within states, which other studies are unable to do. Second, the paper analyses the role of village-level socio-economic and demographic characteristics in proximity to bank branches. This analysis helps in discovering micro-foundations of growth of bank branch network. The granularity of the approach adopted here overcomes the confoundedness problems that the studies at a more aggregate level face. [ABSTRACT FROM AUTHOR]

This article attempts to measure tax capacity and tax effort of fourteen major Indian states from 1991–1992 to 2010–2011 using stochastic frontier analysis. It shows that the variation across states in tax effort is wide and increasing over time. While per capita gross state domestic product, literacy rate, and labor force participation have positive association with tax capacity, a greater share of agriculture has negative association. Furthermore, intergovernmental transfers, given tax capacity, have negative association with tax effort of states. Expenditure on debt repayment is also adversely associated with tax effort but to a lower extent than outstanding liabilities. Enactment of Fiscal Responsibility and Budget Management Act is associated with improvement in states’ tax effort. Both within-state political competition and governance indicators have positive association on tax effort. [ABSTRACT FROM AUTHOR]