Thermal Power Sector Sustainability

2018 ◽  
pp. 381-401
Author(s):  
Suchismita Satapathy ◽  
Jitendra Narayan Biswal
Keyword(s):  
Supply Chain ◽  
Supply Chain Management ◽  
Power Plants ◽  
Thermal Power ◽  
Thermal Power Plants ◽  
Sustainable Supply Chain ◽  
Power Sector ◽  
Chain Management ◽  
Sustainable Supply Chain Management ◽  
Artificial Neural Network Ann

Sustainable supply chain management (SSCM) practices in thermal power plants is dependent on mostly three pillars: social factor, economic factor, and environmental factor. So, in this chapter, sustainable supply chain management of Indian thermal power sector is evaluated. Artificial neural network (ANN) method is implemented to measure whether the benefits of sustainable supply chain management are achieved after practices of sustainable supply chain management in Indian thermal power sector. This chapter also designs a framework by QFD (quality function deployment) method to find solution for some unsatisfactory measures (inputs in sustainable factors) that are not achieved against outputs. As sustainable supply chain management practices in thermal power plants are influenced by a significant number of interrelated enablers and barriers, the drivers or enablers of SSCM are taken as the design requirement to improve SSCM in thermal power industries, and the most important driver is prioritized against the unsatisfied measurands in thermal power sector.

An Analysis on Sustainable Supply Chain Management in Thermal Power Plants

2019 ◽  
pp. 258-285
Author(s):  
Suchismita Satapathy
Keyword(s):  
Supply Chain ◽  
Supply Chain Management ◽  
Power Plants ◽  
Thermal Power ◽  
Thermal Power Plants ◽  
Sustainable Supply Chain ◽  
Chain Management ◽  
Sustainable Supply Chain Management ◽  
Artificial Neural Network Ann ◽  
Flow Of Information

Research on sustainable supply chain management (SSCM) has been garnering interest because of its multi-approach in nature. SSCM has emerged as an essential method for organizations to develop and to enhance their competitive strategy through innovative ways in order to satisfy customer basic needs. It facilitates competitive advantage, faster flow of information, material, less response time, speeding up delivery action, better relation and coordination among partners, easy way of information sharing, and increasing order fulfilment rate. Implementing SSCM in organizations like thermal power plants has other benefits such as increasing attention about environmental performance intending the integration of social as well as economic performance. In this chapter, the artificial neural network (ANN) method is used to measure the customer satisfaction after implementing SSCM by thermal power industries.

Waste Management in Thermal Power Plants

2019 ◽  
pp. 170-182
Author(s):  
Suchismita Satapathy
Keyword(s):  
Supply Chain ◽  
Supply Chain Management ◽  
Environmental Pollution ◽  
Power Plants ◽  
Thermal Power ◽  
Thermal Power Plants ◽  
Sustainable Supply Chain ◽  
Chain Management ◽  
Sustainable Supply Chain Management ◽  
Social Environmental

Environmental pollution and clean energy is the main challenge faced by all over world. The thermal power sector is famous as the highest creator of energy, but still it is blamed for creating Environmental pollution. So, they are trying their best to help themselves on sustainability issues. Basically, Indian powerplants are not only focusing on Sustainable Issues but also trying to develop a sustainable supply chain strategy to carry out their operations while respecting social as well as environmental issues. Sustainable supply chain management(SSCM) practices of thermal power plants mostly dependent on the practice of utilizing waste, water, energy, ash, and taking care of environment in such a manner that social, environmental, and economic factors should not be affected. So, in this chapter sustainable supply chain management practices of Indian thermal power sectors are focused, analyzed, and ranked by Maut method. Simultaneously, their interrelation and correlation are found.

Interpretive Structural Modeling-based Framework for Analysis of Sustainable Supply Chain Management Enablers: Indian Thermal Power Plant Perspective

2018 ◽  
Vol 1 (1) ◽  
pp. 34-56
Author(s):  
Jitendra Narayan Biswal ◽  
Kamalakanta Muduli ◽  
Suchismita Satapathy ◽  
Devendra K. Yadav ◽  
John Pumwa
Keyword(s):  
Supply Chain ◽  
Supply Chain Management ◽  
Thermal Power ◽  
Structural Modeling ◽  
Sustainable Supply Chain ◽  
Interpretive Structural Modeling ◽  
Chain Management ◽  
Sustainable Supply Chain Management ◽  
The Impact ◽  
Interpretive Structural Model

Indian thermal power industries, being perceived as the most polluting, are experiencing tremendous pressure to implement sustainable supply chain practices. In this light, the purpose of this article is to explore the factors that initiate sustainable supply chain management (SSCM) adoption in Indian thermal power industries and understand the interrelationship existing among them. Interpretive structural modeling (ISM) technique is employed to extract the structural relationship existing among the SSCM enablers and portray the same through a hierarchical model. Further, MICMAC (Matrice d’Impacts Croisés Multiplication Appliquée á un Classement) analysis has been employed to classify the enablers by taking their driving and dependence power as a measure. Eleven SSCM enablers have been explored through an extensive review of the literature. The interpretive structural model of selected enablers indicates that SSCM adoption in thermal power plants is mainly due to “pressure from environmental advocacy groups” and “government policies and employee pressure”. Prior knowledge of these influential factors and their interdependence will help the decision makers to develop suitable strategies that would enable the organizations to reduce the impact of barriers while optimizing the benefits derived from the enablers.

Sustainable supply chain management: continuing evolution and future directions

2019 ◽  
Vol 50 (1) ◽  
pp. 122-146 ◽  
Author(s):  
Craig R. Carter ◽  
Marc R. Hatton ◽  
Chao Wu ◽  
Xiangjing Chen
Keyword(s):  
Supply Chain ◽  
Supply Chain Management ◽  
Theory Development ◽  
Future Research ◽  
Sustainable Supply Chain ◽  
Unit Of Analysis ◽  
Chain Management ◽  
Content Type ◽  
Empirical Validity ◽  
Sustainable Supply Chain Management

Purpose The purpose of this paper is to update the work of Carter and Easton (2011), by conducting a systematic review of the sustainable supply chain management (SSCM) literature in the primary logistics and supply chain management journals, during the 2010–2018 timeframe. Design/methodology/approach The authors use a systematic literature review (SLR) methodology which follows the methodology employed by Carter and Easton (2011). An evaluation of this methodology, using the Modified AMSTAR criteria, demonstrates a high level of empirical validity. Findings The field of SSCM continues to evolve with changes in substantive focus, theoretical lenses, unit of analysis, methodology and type of analysis. However, there are still abundant future research opportunities, including investigating under-researched topics such as diversity and human rights/working conditions, employing the group as the unit of analysis and better addressing empirical validity and social desirability bias. Research limitations/implications The findings result in prescriptions and a broad agenda to guide future research in the SSCM arena. The final section of the paper provides additional avenues for future research surrounding theory development and decision making. Originality/value This SLR provides a rigorous, methodologically valid review of the continuing evolution of empirical SSCM research over a 28-year time period.

Sign in / Sign up

Export Citation Format

Share Document