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Author

N. Nagesha

Other affiliations: Indian Institute of Science
Bio: N. Nagesha is an academic researcher from University B.D.T College of Engineering. The author has contributed to research in topics: Energy consumption & Environmental impact assessment. The author has an hindex of 6, co-authored 15 publications receiving 256 citations. Previous affiliations of N. Nagesha include Indian Institute of Science.

Papers
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Journal ArticleDOI
01 Sep 2006-Energy
TL;DR: This paper identifies relevant barriers to energy efficiency and their dimensions in SSI clusters using the analytic hierarchy process (AHP) and reveals that the prioritization remained the same despite differences in the relative weights of barrier groups.

184 citations

Journal ArticleDOI
TL;DR: In this article, the authors analyzed energy consumption and associated issues in the textile dyeing cluster of Tirupur in the Indian state of Tamil Nadu and found that the importance of energy among the inputs was established by estimating the Cobb-Douglas production function.

36 citations

Journal ArticleDOI
01 Oct 2006
TL;DR: In this paper, the importance of energy input is established using a Cobb-Douglas production function, and the energy consumption pattern and associated environmental pollution are also studied using regression analysis.
Abstract: Small Scale Industries (SSIs) are a crucial component of the Indian economy and the majority of them exist in clusters. Survival and growth of such clusters in the current globalized era hinges on three vital dimensions of sustainability viz. Economic, Environmental, and Social. In energy intensive SSIs, the first two dimensions depend on effective utilization of energy, a key input in their operations. The improved Energy-Efficiency (EE) helps not only in enhancing competitiveness through cost reduction, but also in minimizing environmental degradation. But, a good understanding of factors influencing EE is essential for its improvement. This paper attempts to probe these factors in an energy intensive Brick and Tile cluster in India. Based on the primary data from 44 SSIs, the importance of energy input is established using a Cobb-Douglas production function. The energy consumption pattern and associated environmental pollution are also studied. The variables influencing EE are classified a priori under four categories viz. Technical Factor (TF), Economic Factor (EF), Human Resource Factor (HRF) and Organizational and Behaviour Factor (OBF). While the TF comprises variables like age of plant and machinery, quality of energy used, and process specific variables, the EF includes plant capacity utilization, resource use efficiency, and production volume. Similarly, the HRF involves labour skill level, owner/supervisor education, and business experience of the owner, with OBF encompassing variables such as work-practices, layout and housekeeping, importance attached to energy, and the external interaction level. Regression analysis is adopted while assessing the significance of these factors in explaining the variation in EE. The production function revealed energy as the most important contributor to the value of output amongst all inputs. Though all the hypothesized factors are found significant, EF and OBF obtained the top two ranks. These results have useful policy implications for ensuring Sustainable growth of the SSI sector.

21 citations

Journal ArticleDOI
TL;DR: Cleaner production (CP) method has fetched improvements to large energy intensive industries, which have the principal, technical knowledge and the organisational capacity for applying new and innovative techniques as mentioned in this paper.

20 citations

Journal ArticleDOI
TL;DR: In this paper, the authors present a model developed to assess the Cleaner Production status and implementation of this model on 22 cashew processing units, in the assessment of CP level, contributing parameters viz., process efficiency, environmental degradation, and sustainability aspects are considered.

19 citations


Cited by
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Journal ArticleDOI
TL;DR: A comprehensive listing of AHP applications in operations management is presented and a framework for identifying the decision areas that have better research gaps to be studied by future researchers is developed.

516 citations

Journal ArticleDOI
TL;DR: A detailed literature review of the recent applications of the analytic hierarchy process (AHP) and analytic network process (ANP) group decision‐making methodologies shows that during the years 2005‐2009, use of the AHP technique has continued to increase exponentially.
Abstract: Purpose – The purpose of this paper is to present a detailed literature review of the recent applications of the analytic hierarchy process (AHP) and analytic network process (ANP) group decision‐making methodologies.Design/methodology/approach – Among more than 600 related papers published in the period 2005‐2009, a total of 232 application articles published in highly reputed international academic journals were selected and referenced in this paper. Papers were categorized according to application areas, subject titles, publication date, country of origin, academic journals, and integrated methodologies, and are summarized herein by various tables and charts.Findings – The findings show that during the years 2005‐2009, use of the AHP technique has continued to increase exponentially. Moreover, it is expected that ANP will gain more popularity in the future, as the benefits of ANP become better understood. Applications of AHP have been dominant in manufacturing, followed by the environmental management ...

463 citations

Journal ArticleDOI
01 Oct 2009-Energy
TL;DR: In this paper, fuzzy multicriteria decision-making methodologies are suggested for the selection among renewable energy alternatives, which are based on axiomatic design (AD) and analytic hierarchy process (AHP).

404 citations

Journal ArticleDOI
TL;DR: In this paper, a taxonomy of barriers to the adoption of industrial energy-efficient technologies is proposed, which is based on an extensive literature review of the literature and is able to evaluate the differences between perceived and real barriers, the effect of barriers on decision-making processes, and the interactions among barriers.
Abstract: A critical review of the literature highlighted the need for a new taxonomy encompassing the most relevant barriers stemmed from previous studies, and accounting for interactions and independences of the barriers to avoid overlaps and implicit interactions. Based on an extensive literature review the paper provides a novel approach for barriers to the adoption of industrial energy-efficient technologies, coping with the issues risen by the review of the literature. We developed a taxonomy adaptable to empirical research, and able to evaluate the differences between perceived and real barriers, the effect of the barriers on decision-making processes, and the interactions among barriers. We modeled three types of interactions, i.e., causal relationship, composite effect and hidden effect, in order to start analyzing the dynamics among barriers, and tested the taxonomy in a preliminary investigation. The study proposes a useful instrument both to enterprises and policy-makers to identify critical factors to improve industrial energy efficiency and to open the research to further investigation in this topic.

295 citations

Journal ArticleDOI
01 Mar 2014-Energy
TL;DR: In this paper, the AHP and ANP are applied to help the managing board of an important Spanish solar power investment company to decide whether to invest in a particular solar-thermal power plant project and, if so, to determine the order of priority of the projects in the company's portfolio.

286 citations