Risk-Driven Capital Investment Strategies In The Coal Mining Sector: A Fuzzy Ahp Perspective

Abstract

Purpose: Coal mining industry plays a pivotal role in structuring the country’s economy and are associated with inherent risk and volatility that impact the operational and financial efficiency of this industry. So, considering these associated risk factor. the primary objective of this study to identify the nature of these risk and to evaluate their proportional effect on the capital decision making process using the Fuzzy Analytic Hierarchy Process (Fuzzy AHP). Given the capital-intensive and high-risk nature of coal mining, a systematic approach to risk evaluation is essential for sustainable operations and informed decision-making.

Methodology: In order to study the risk factor in mining operations a case study of Mahanadi Coalfield Ltd, a coal producing subsidiary of CIL has been taken into consideration. Moreover, to address the uncertainty and subjectivity in the prospectives of experts, a structured framework of Fuzzy AHP has been implemented to the capital investment process. Key risk factors are identified and categorized into Preliminary Survey, Exploration, and Feasibility Study risks, mine Development & Operation-Production risk, product Marketing & Sales and Financial Management risk, Post-Mine Closures risks. Data is collected through expert surveys, and fuzzy logic is applied to derive the relative importance of each risk factor.

Findings: The study reveals that environmental and regulatory risks are the most significant, followed by operational hazards, emphasizing the need for proactive mitigation measures. The fuzzy approach provides nuanced insights into risk prioritization, offering a clearer understanding of the complex interdependencies between risk factors.

Research Limitations: The findings are based on expert opinions fand may be context-specific to the coal mining industry and generalized based on the prospective of a single company. These methodologies could be applied not only to the mining industry but also to any such resource intensive industry in future researches for broader prospectives.

Practical Implications: This study will facilitate a tool for decision maker with comprehensive consideration and prioritization of risk and uncertainty, with significant alignment with strategic objectives and sustainability goals. The framework provides for better allocation of resources and planning for risk mitigation.

Originality Value: The combine approach of fuzzy logic with AHP provides a novel approach to address the uncertainty in risk analysis, and hereby enhance the reliability and adaptability of the present findings for the coal mining sector. The study contributes to the literature on risk management in capital-intensive industries, bridging the gap between theory and practice.