Purpose The purpose of this paper is to create a hierarchy of critical success factors affecting the higher technical education institutions, taking a case study of India. Using total interpretive structural modeling (TISM), the paper attempts to establish the inter-linkages among ten critical success factors for enhancing the performance of these institutions. Design/methodology/approach The paper employs Total Interpretive Structural Modeling (TISM) to understand the hierarchy of the factors and their interplay using response from 18 experts in the domain. Findings The findings reveal that autonomy and accountability coupled with availability of sustainable funds are the driving factors for the success of the institutions. Infrastructural facilities and establishment of centers of excellence act as amplification factors. Introduction of new programs and their accreditation, improvement in faculty quality, research output and improvement in performance of academically weak students emerge as process factors that drive the output factors, namely, academic performance and student placement. Research limitations/implications The major limitation of this study is the scope that was limited to 191 institutions, as mandated in the project. Practical implications This study has important implications for the institutions as well as the policy makers to channelize their focus and efforts on driving and amplification factors that would ultimately lead to enhanced performance of the next generation higher technical education institutions. Originality/value This paper is a part of pan India project carried out to assess the performance of higher technical education institutions in India.
The sustainable development goals (SDGs) were result of extensive stakeholder participation and global consensus. Despite large promises, there is an increasing concern among the member states whether SDGs address real problems of nations, particularly the developing world. This study discusses key issues raised by developing countries with respect to the SDGs. Using opinion of experts on SDGs regarding its implications and future, a case study for India is presented. The study with its findings and policy recommendations intend to benefit SDG implementation efforts and planning at the national and sub-national level in India and other developing countries, helping them redesign and investigate their national SDG implementation strategies on similar lines as India to improve its reach and effectiveness.
The global agenda of sustainable development (SD) will get a major boost from the successful implementation of the Sustainable Development Goals (SDGs) in developing countries. This requires effective planning and understanding of the SDGs at the national level and developing sound SDG indicators that account for country priorities. Currently, there is no formal SDG indicator set in India, but the process for it is underway. This paper has attempted to propose a unique technique for identifying the most representative indicator set for SD measurement in India based on the SDGs. Considering the needs and preferences of the country, a three‐stage process is proposed to develop the priority indicator set. The application of the approach has been presented for SDG 7, which relates to energy. This is supported with a background on India's SD progress. The proposed technique is simple yet effective, and can be easily replicated by other developing countries.
Purpose This paper aims to focus on the contribution of segregated renewable energy (RE) sources such as solar, wind, bagasse, biomass, small hydropower (SHP) and waste to heat in driving sustainable industrial production in India. Design/methodology/approach This study uses non-linear modelling techniques such as quantile regression and the non-linear Granger causality test to explore the interplay between segregated RE generation and industrial production in India. Findings The study findings support the role of segregated RE sources generation, especially SHP and bagasse, on industrial production in India. This paper finds unidirectional non-linear Granger causality running from segregated RE sources to industrial production. Bidirectional non-linear Granger causality has been established from biomass, waste-heat to index of industrial production and vice versa, supporting an asymmetric feedback hypothesis. Research limitations/implications The study findings will aid the energy policymaker in framing policies for RE sources, especially bagasse-based and SHP generation for the sustainable industrial growth of India. Originality/value To the best of the authors’ knowledge, this is one of the first studies to explore the role of segregated RE sources generation to drive sustainable industrial growth in India using non-linear techniques.
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