Designing a framework for integrating environment management with drivers of economic performance

2015 ◽  
Vol 9 (3) ◽  
pp. 376-392 ◽  
Author(s):  
Rashmi Ranjan ◽  
Niladri Das

Purpose The purpose of this paper is to integrate drivers of economic performance with environmental management aspects and core managerial functions of the Indian coal mining industry. Design/methodology/approach For this research paper, primary and secondary data have been used. The primary data were collected through a questionnaire survey which was distributed in the four subsidiaries of Coal India Limited. The validity and reliability of the questionnaire were tested by appropriate statistical techniques. Further, one-sample t-test and multiple linear regression analysis have been used for data analysis. Findings Testing of hypotheses reveals that there is a high level of integration of environmental management aspects with the seven core managerial functions, namely, production process, distribution process, beneficiation process, quality issues, stakeholders’ interest, health and safety and corporate strategy. Further, the paper identified that there is a positive association between integration of environmental aspects with core functions and the four drivers of economic performance and it is strongly associated with societal-related and risk-related drivers of economic performance. But it is less strongly associated with image-related and efficiency-related drivers of economic performance. Research limitations/implications This paper focuses on integrating the environmental management and core functions with key drivers of economic performance in coal mining industry which is one of the most polluting industries of the world. The limitation of the paper is that it is very specific and limited to the coal mining industry. Originality/value The paper contributes to the existing work by designing a framework which identifies the key drivers of economic performance and integrating it with the environmental management system of the organisation.

2020 ◽  
Vol 20 (Special1) ◽  
pp. 38-44
Author(s):  
Trisna Mulyati ◽  
Prima Denny Sentia ◽  
Anis Maulana ◽  
Friesca Erwan

A coal mining industry typically applies a 24-hours working time, which enforces some workers to stay conscious during night shift, opposing human body's biological clock. This study aims to analyse the level of fatigue experienced by high dump truck operators (HD operators) in a coal mining site in East Kalimantan, Indonesia. This study utilizes primary data which obtained from distributing Industrial Fatigue Research Committee (IFRC) survey to all HD operators and secondary data (for Fatigue Likelihood Scoring - FLS) which consists of HD operators’ working schedule that currently applied in the company. Results obtained is analyzed using Fatigue Risk Management System (FRMS) framework which combines FLS classification and Dawson-McCulloch’s model of fatigue risk trajectory. This study reveals that based on IFRC survey, HD operators experienced low/mild fatigue due to insignificant influence of fatigue-related factors contained in the survey. However, consideration for improvement is in need since the result of fatigue for night shift operators is close to moderate level. In addition, based on FLS, the level of fatigue indicates that HD operators experienced excessive working hours, in which in FRMS graph classified as fatigue-related errors. Thus, this study proposes several strategies as the hazard control mechanism: (1) providing optimum resting time, (2) equipping operators with audio music that lead to positive energy and increasing work focus, and (3) adding afternoon shift to balance the working hours.


2017 ◽  
Vol 24 (4) ◽  
pp. 882-902 ◽  
Author(s):  
Sorokhaibam Khaba ◽  
Chandan Bhar

Purpose The purpose of this paper is to quantify the strengths, weaknesses, opportunities and threats (SWOT) analysis for the Indian coal mining industry using Fuzzy Decision-Making Trial and Evaluation Laboratory. Design/methodology/approach After obtaining 17 factors from literature and expert opinion, an interview questionnaire was designed and tested to assure the content validity of questionnaire. A group of 15 qualified experts consisting of 4 professors from academic institutions and 11 management professionals from mining sector with substantial experience were consulted. Findings The result from causal relationship implied that the decision makers should focus on improving the ability of exploitation and production using quality improvement initiative such as lean production, developing research and development units for clean coal technology and working with strong exporters. This study also finds that foreign investment in mining sector is also a main factor that highly influences other factors. Research limitations/implications The study is based on personal judgments and the shortage of respondents limits the study to ensure the validity. Practical implications The stated strategies both for the government and industry through SWOT analysis could facilitate improved productivity of the Indian coal industry if adopted. Originality/value This paper demonstrates a process for quantitative SWOT analysis for the Indian coal mining industry that can be performed even when there is dependence among factors.


2018 ◽  
Vol 25 (7) ◽  
pp. 2145-2168 ◽  
Author(s):  
Sorokhaibam Khaba ◽  
Chandan Bhar

Purpose The purpose of this paper is to develop and validate a model for key barriers to lean implementation in the Indian coal mining industry. Design/methodology/approach Interpretive structural modeling (ISM) has been used to develop a proper hierarchy and contextual relationship of key barriers to lean implementation in the Indian coal mining industry through literature review and expert opinion which is followed by the classification of barriers using Matrice d’ Impacts Croisés-Multiplication Appliquée á un Classement (MICMAC) and questionnaire-based survey to validate the ISM model using structural equation modeling (SEM). Findings In this study, 14 key barriers to lean implementation in the Indian coal mining industry have been identified, modeled and analyzed. The lack of top management commitment, financial constraints and lack of inter-departments co-ordination are found to be the most important barriers to lean implementation in the mining industry. The ISM-based model is validated using the SEM. Research limitations/implications The analysis of data represents that relatively more participants were from the mines located in eastern India and the maximum participants were managers and executives holding different levels (lower, middle or upper), although key participants in different mines were encouraged to distribute the survey to other employees also. Practical implications This model on lean barriers would help the decision makers, researchers and practitioners to anticipate potential barriers to lean implementation and support the existing academic research on lean. Accordingly, the focus on the lean barriers can be prioritized for the better utilization of the available resources for eliminating or minimizing the barriers. Originality/value This paper is an original contribution of analysis of the lean barriers in Indian mining industry using the integrated ISM–MICMAC and SEM approach.


2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Sorokhaibam Khaba ◽  
Chandan Bhar ◽  
Ankita Ray

PurposeThe purpose of this research is to identify and study the contextual relationships of the significant lean enablers in the Indian coal mining industry using the application of interpretive structural modeling (ISM), matrice d' impacts croisés-multiplication appliquée á un classement (MICMAC) and structural equation modeling (SEM).Design/methodology/approachIn this study, a conceptual model based on ISM was developed forming a hierarchy and contextual relationships of significant enablers for lean implementation in the Indian coal mining industry using a literature review and eliciting expert opinion, which is followed by MICMAC for grouping of enablers and questionnaire survey to validate the ISM based conceptual model using SEM.FindingsThe study modeled and analyzed ten significant enablers of lean implementation in the Indian coal mining industry. The findings suggest that the most important lean enablers in the Indian coal mining industry are employee empowerment, employee motivation and commitment, consistent financial performance measurement and management support.Research limitations/implicationsJudgmental sampling was used for selecting the respondents for conducting the questionnaire survey in this research work as there are a few numbers of coal mines implementing lean principles in India. Although the study was not restricted to a particular part of India with the sample representing the heterogeneous population, the study represents more data from the coal mines in eastern India.Practical implicationsThe model on lean enablers would help the researchers, decision-makers and practitioners to anticipate potential lean enablers in the Indian coal mines and rank the enablers for improved and efficient usage of the available resources creating value to customers with lean and to sustenance academic research on lean.Originality/valueStudies on lean enablers in the mining sector are scarce in the literature, and this study is a novel contribution of exploring lean enablers in the Indian coal mining industry using an integrated approach of ISM–MICMAC and SEM.


2013 ◽  
Vol 6 (1) ◽  
pp. 711-718 ◽  
Author(s):  
Rashmi Ranjan ◽  
Niladri Das

This paper provides an insight of the relationship between economic performance and environmental management which is necessary for sustainable development and economic prosperity. The present paper uses factor analysis methodology for identifying the major factors relating to economic performance which also enhances environmental management in mining industry.The survey has been conducted in four subsidiaries of Coal India Limited (CIL) which are Bharat Coking Coal Limited (BCCL), Dhanbad, Central Coalfield Limited (CCL), Ranchi, Coal Mines Planning and Design Institute India Limited (CMPDIL), Dhanbad and Eastern Coalfield Limited (ECL), Asansol. This study identifies four factors, namely risk related driver, image related driver, societal related driver and efficiency related driver of economic performance which should be integrated with corporate strategy of the company for sustainable growth and development.


2018 ◽  
Vol 35 (6) ◽  
pp. 1215-1231 ◽  
Author(s):  
Sorokhaibam Khaba ◽  
Chandan Bhar

Purpose The purpose of this paper is to determine the degree of lean awareness and implementation and to identify the perception on tools, enablers, barriers and potential benefits of lean in the Indian coal mining industry. Design/methodology/approach A systematic review of lean literature and expert opinion was used to design the survey instrument. Data were collected through electronic survey and traditional pencil and paper approach. In order to test the research hypotheses, independent sample t-tests were done. Findings The study reveals that there is a certain degree of lean awareness although the level of lean implementation is still at a nascent stage in the Indian coal mining sector. The main applicable tools, barriers, enablers and benefits have also been identified based on 54 respondents out of 109 suitable respondents. Research limitations /implications In this study, relatively the maximum participants were from the mines located in Eastern India. Thus, a certain level of bias can be anticipated. The findings would help the decision makers, researchers and practitioners to better utilize the available resources for lean implementation and support the existing academic research on lean. Originality/Value The concept of lean in mining industry is relatively a new paradigm and there is a lack of empirical study that explores applicable tools, barriers, enablers and benefits of lean in Indian mining industry. The study addresses this gap in the lean literature.


2017 ◽  
Author(s):  
Margaret Armstrong ◽  
Alain G. Galli ◽  
Carlos Petter ◽  
Renato Aurelio Petter ◽  
Anna da Silva ◽  
...  

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