Interpretive Structural Modeling Research Articles

Supply chain collaboration, agility and firm performance: a case of manufacturing SMEs in India

PurposeThe dynamic business environment and intense competition have mandated agility in operations for manufacturing firms. Effective inter-organizational collaboration can make operations more agile. This paper develops an interpretive model to explore the effect of supply chain collaboration (SCC) on supply chain agility (SCA) and, subsequently, on business performance.Design/methodology/approachA hierarchical model that illustrates the relationship between SCC, SCA and firm performance components is developed using total interpretative structural modeling (TISM). Also, statistical validation of the model has been performed.FindingsThe results indicate that the vision and alertness of the firm on the strategic front promote collaboration between supply chain partners. This creates operational agility, helping the firm to absorb fluctuations in demand, thereby enhancing business performance.Research limitations/implicationsThe opinion of most respondents was considered to develop the TISM framework over the fuzzy one, which necessitates a significantly more extensive data set. However, multiple discussions with participants can eliminate the prejudice of the majority approach. Also, the paper's development and validation were restricted to Indian manufacturing small and medium-sized enterprises (SMEs). The model can potentially be evaluated in large organizations to provide further insights.Originality/valueThe study blends the factors of SCC and SCA in a novel way to explain their combined impact on business performance. The TISM model addresses the “why” of theory development in addition to the “what” and “how” of it. Using triangulation in combination with the interpretative tool, this study additionally offers methodological value.

The influence of corporate social responsibility on impulse buying

PurposeCorporate social responsibility (CSR) ISO standards have been noted as an essential marketing strategy by which firms can achieve consumer trust while improving environmental, social, and quality factors. This study discloses the contextual relationship between CSR ISO standards and sustainable impulse buying behavior. This study also looks to uncover the CSR ISO driving and linkage factors that motivate consumers to make sustainable impulsive purchases.Design/methodology/approachThree distinct research methods were employed in this research. First, a consumer expert opinion-based Interpretive Structural Modeling (ISM) approach was adopted to reveal the contextual relationship between CSR ISO factors and sustainable impulse buying behavior. Secondly, Matrice Impacts Croises Multiplication Appliques Classement (MICMAC) was used to examine these factors' driving and dependent power. In addition, Minitab package software was also used to check the statistical validation of ISM-MICMAC results.FindingsThe results indicate that although environmentally responsible CSR ISO 14001, socially responsible CSR ISO 26000, and consumer perception of product quality CSR ISO 9001 standards contain strong driving power, their dependent power was weak. All these CSR ISO factors (14,001, 26,000, and 9001) strongly impact each other and sustainable impulse buying. Therefore, these three CSR ISO factors have been placed at the bottom of the ISM model. The CSR ISO 14020 standard (labeling of the product), knowledge of CSR ISO standards, consumer trust, and advertising about CSR ISO standards have been placed in the middle. The mentioned factors have intense driving and dependent power and are classified as linkage factors for sustainable impulse buying. Impulse buying behavior has weak driving and strong dependent power, yet this factor strongly depends on other CSR ISO factors. Hence, this factor is placed at the top of the ISM model. In addition, the Minitab package software results indicate that ISM-MICMAC results are statistically valid.Originality/valueTo the best of our knowledge, this research is unique and examines the influence of CSR ISO factors on sustainable impulse buying in the context of Pakistani consumers. Secondly, our study has thoroughly investigated several CSR ISO factors and allied these factors in the context of consumer buying behavior. Third, several CSR ISO factors and impulse buying behavior were examined using a mix of ISM-MICAC and Minitab methods. Thus, including these steps in our study has led to the development of a novel technique.

An aquaculture risk model to understand the causes and consequences of Atlantic Salmon mass mortality events: A review

AbstractMass mortality events (MMEs) are defined as the death of large numbers of fish over a short period of time. These events can result in catastrophic losses to the Atlantic salmon aquaculture industry and the local economy. However, they are challenging to understand because of their relative infrequency and the high number of potential factors involved. As a result, the causes and consequences of MMEs in Atlantic salmon aquaculture are not well understood. In this study, we developed a structural network of causal risk factors for MMEs for aquaculture and the communities that depend on Atlantic salmon aquaculture. Using the Interpretive Structural Modeling (ISM) technique, we analysed the causes of Atlantic salmon mass mortalities due to environmental (abiotic), biological (biotic) and nutritional risk factors. The consequences of MMEs were also assessed for the occupational health and safety of aquaculture workers and their implications for the livelihoods of local communities. This structural network deepens our understanding of MMEs and points to management actions and interventions that can help mitigate mass mortalities. MMEs are typically not the result of a single risk factor but are caused by the systematic interaction of risk factors related to the environment, fish diseases, feeding/nutrition and cage‐site management. Results also indicate that considerations of health and safety risk, through pre‐ and post‐event risk assessments, may help to minimize workplace injuries and eliminate potential risks of human fatalities. Company and government‐assisted socio‐economic measures could help mitigate post‐mass mortality impacts. Appropriate and timely management actions may help reduce MMEs at Atlantic salmon cage sites and minimize the physical and social vulnerabilities of workers and local communities.

Successful Implementation of Disruptive Innovation by New Entrants: Modeling the Challenges Using Interpretive Structural Modelling

Successful implementation of disruptive innovation involves numerous challenges, especially for new entrants. This study tries to identify and analyze a set of critical challenges that might plague a new entrant to successfully implement disruptive innovation. Multicriteria decision-making (MCDM) technique of Interpretive Structural Modeling (ISM) was used to analyze the identified challenges, as well as to derive their interrelationship. The study was conducted in the context of the Indian manufacturing sector. The findings revealed that the lack of financial resources, lack of non-financial resources, and lack of top management support emerged as the three key challenges impeding disruptive innovation for manufacturing organizations in India. The motivation–opportunity–ability (MOA) model served as the basic theoretical underpinning for the study. The findings of the study are expected to help managers and policymakers to understand possible challenges associated with the implementation of disruptive innovation, and to develop counter strategies accordingly.

Determining geo-disaster chains probabilities and disaster mitigation mode: A meta-analytical perspective

In a harsh geological environment, different geo-disasters might co-occur or be in a chain sequence. Currently, existing research in related fields documents numerous instances of disaster chains and responses, which provided this study with important materials for determining disaster chains probability and summarized the disaster prevention and mitigation (DPM) mode. In this study, through the depth of the geo-disaster chains cases and the DPM cases, enabled a mitigation mode analysis summary. We take the case of geo-disaster chains as an example for this study, and represent 20 typical geo-disaster chains by data fusion and structuring of 139 geo-disaster chains cases.The probability assessment of geo-disaster chains is crucial for risk management and regional resilience. We introduced a Bayesian network (BN) model to describe the process of geo-disaster chains formation to map the structure and assess the joint probability of geo-disaster chains. The BN results showed that the longer the disaster chains length, the smaller the probability of the chains occurring. Among these, the probability of “Collapses-landslides-debris flows–barrier lakes–flash floods” is the lowest (0.069). Through sensitivity analysis, it is found that precipitation is the most sensitive factor in the development of geo-disaster. Interpretive structural modeling (ISM) is employed to examine the DPM index system across three key aspects: disaster emergency preparation, disaster response, and disaster recovery, and the conceptualized interaction among these components. ISM results showed that government policy intervention and scientific DPM measures can effectively reduce the losses caused by the development of geo-disaster chains. This research combined the occurrence process of the disaster chains with the disaster response process, and determined the entire chains of characterization from disaster understanding to disaster response, and helped reduce the vulnerabilities caused by disasters.

What gets measured well is managed well: Determining a hierarchy of interdependencies of environmental elements for effective environmental performance

AbstractClimate effects of greenhouse gas emissions, land use, water use, energy use, and waste are a universal concern. With disparate reporting firms and a lack of universal measures of corporate sustainability, environmental sustainability for businesses is an afterthought, with minimal consequences for inaccurate reporting, or green washing and brown washing. This research explores four widely used reporting measures to first derive 12 universally applicable elements from five sustainability themes of emissions, land, water, energy, and waste. Using expert inputs and existing literature, the identified elements are subjected to interpretive structural modeling (ISM) to develop a framework of interdependencies among the elements and their influence on emissions. The framework identifies crucial elements, beyond carbon emissions, that have greater potential to reduce the climate impact of economic activity. Although aware of energy use implications, businesses have long ignored the indirect but catastrophic effects of non‐hazardous waste, the second level element, on climate change.

Socio‐economic strategy for settlement of refugees amidst crisis: The case of Pak‐Afghan

AbstractToday, global concerns are at their peak due to the fast‐growing number of refugees. The world faces the dilemma of the refugee crisis, which needs to be addressed by the United Nations (U.N.) sustainable development goals (SDGs). Pakistan hosts about 1.4 million registered refugees in camps and urban areas. The majority consist of Afghans who departed due to severe poverty, conflict, and security concerns. These refugees bring socio‐economic distress to the host country. In order to comprehend the whole crisis, this study primarily focuses on three areas: the unstable political and security situation in the country of origin, the refugee concerns and their implications. This research is unique throughout the literature as it applies the interpretive structural modelling (ISM) tool to view the refugee crisis holistically. Results from ISM show that the ‘Political situation of Afghanistan’ is the most influential factor with very high driving power. Afterward, 10 resulting factors were opted from the ISM model, which demonstrate the implications on the host country. The relative importance index (RII) approach was used to rank the resultant factors. Ranking from RII depicts a significantly different impact of refugees while residing in urban areas. Using the Prisoner's dilemma of cooperative game theory (GT), this study concludes by recommending refugees to get registered and the host country to settle them in the local population. The use of cooperative GT with the nexus of ISM and RII is also exceptional and will be helpful for researchers and policymakers to resolve any conflict.

Enhancing resilience in transnational E-commerce supply chains: Critical factors, perspectives and strategic action plan

This study develops a hybrid model to investigate the factors affecting transnational e-commerce supply chain resilience (TNSCRE) by integrating the Entropy Weight Method (EWM), Simple Additive Weighting (SAW), and Interpretive Structural Modeling (ISM). The study identifies 36 critical factors categorized under supply chain adaptability, supply chain efficiency, and supply chain evolution, and five criteria are used to rank these factors. The EWM is used to calculate the relative weights of the criteria, and the SAW method is used to rank the factors based on their weighted scores. The ISM is then used to evaluate the interrelationships among the key factors. The research highlights the significance of several factors, such as the speed of supply chain disruption recovery, interactive collaboration, and response time to supply chain disruption. Sensitivity analysis was performed to assess the robustness of the findings. Finally, a SWOT analysis is conducted to develop a strategic action plan for addressing these significant factors. The study provides a comprehensive understanding of the factors that impact TNSCRE from the perspective of multiple stakeholders. The findings can help e-commerce business owners improve their existing supply chain resilience and achieve sustainable growth in the context of globalization.

Strategy to Decrease Counterproductive Work Behavior: Implementation of Interpretive Structural Modeling

This study aims to analyze the determinant factors of Counterproductive Work Behavior (CWB) to make plan strategies for overcoming Counterproductive Work Behavior. This research used the Interpretative Structural Modeling (ISM) method. The ISM method is able to show the interrelationships between existing elements. This method can be developed to plan strategic human resource management policies related to CWB. The strategy for managing human resources related to CWB in automotive companies in Bekasi is carried out according to the level of importance based on a problem. The results showed that it is necessary to overcome Counterproductive Work Behavior by handling job stress (Task demands, Role demands, Family problems, and Economic problems) and role ambiguity (Clarity of Responsibilities, Clarity of goals, and Clarity of roles and scope of work).

Exploring the Enablers of Organisational Inclusion: An Interpretive Structural Modelling Approach

This research paper aims to identify and structure the enablers that promote organisational inclusivity, fostering a workplace that values diversity and inclusion. Using Interpretive Structural Modelling (ISM), the study identifies the following four clusters of enablers: autonomous, linkage, dependent and driving. Furthermore, the research findings suggest that inclusive leadership acts as a key driving factor for promoting inclusivity in the organisation. The study offers practical implications for human resource managers to develop targeted strategies to create an inclusive culture and enhance overall organisational performance by recognising and prioritising the identified enablers.

Analysis of interplay between food safety systems and halal standards in Indonesia

The present work aimed to develop a comprehensive certification process for halal food products within the Indonesian agribusiness, which integrates food safety and halal standards. The objective was to reduce financial barriers, certification burden, and workforce shortages currently impeding the establishment of quality halal food supply chains. To achieve this aim, Interpretive Structural Modelling (ISM) was used to elucidate the complex relationships between decision variables in the halal certification process. Data collection included interviews with sectoral experts overseeing food safety and halal compliance. The present work identified 17 strategic variables crucial to integrating the Halal Assurance System (HAS) with food safety using ISM analysis. The findings of the ISM model showed 11 hierarchical levels of integration between the HAS and food safety, identifying key factors influencing produce security mechanisms. Additionally, the present work emphasised the significance of transparency, proper handling of produce, and efficient certification processes for businesses operating in the global food sector. This proposed framework not only offers practical guidance for enhancing food security, but also correlated certification processes with supply chain objectives, thereby bridging the gap between theory and practice.

EXPLORING FACTORS INFLUENCING THE DIGITAL ECONOMY: UNCOVERING THE RELATIONSHIP STRUCTURE TO IMPROVE SUSTAINABILITY IN CHINA

Digital economy is a great route to promote the efficient utilization of natural resources and promote sustainability due to its high-tech, rapid growth, extensive penetration, deep integration and other characteristics. Existing study on the influencing factors of the digital economy is not deep enough and lacks the analysis on the relationship structure of factors influencing the digital economy, which is not conducive for an overall grasp of the digital economy. To correctly understand how to better develop the digital economy, this paper studies its influencing factors and the relationships between them. Based on the time-series data of China from 2002 to 2018, grey correlation analysis was applied to calculate the correlation between these influencing factors and the digital economy, and determine the major influencing factors of digital economy development in China. The Granger causality test and a review of existing research were used to judge the interrelationship of various factors. The interpretative structure model was utilized to determine the relationship structure of the main factors affecting the development of China’s digital economy. The results show that the number of digital talents, state of the technology market, and degree of digitalization are direct influencing factors of the digital economy. The results help to better understand the development of the digital economy and will enable the implementation of policies to improve towards more sustainable cities.

Breaking down barriers and building up facilitators of lecture free curriculum in medical education: An interpretive structural modeling

Introduction The field of medical education has seen a growing interest in lecture free curriculum. However, it comes with its own set of challenges and obstacles. In this article, we aim to identify the prerequisites, facilitators, challenges, and barriers of lecture-free curriculum in medical education and examine their interrelationships using interpretive structural modeling (ISM) technique. Methods In this mixed-method study initially, we performed a scoping review and semi-structured interviews and determined the main prerequisites, facilitators, challenges, and barriers of lecture-free curriculum in medical education using qualitative content analysis approach. The interrelationships among these components were investigated using ISM. Therefore, self-interactive structural matrices were formed, initial and final reachability matrices were achieved, and MICMAC analysis was conducted to classify the factors. Results Finally, two ISM models of prerequisites and facilitators with 27 factors in 10 levels and challenges and obstacles with 25 factors in eight levels were developed. Each of the models was divided into three parts: key, strategic, and dependent factors. ‘Providing relevant evidence regarding lecture free curriculum’ emerged as the most important prerequisite and facilitator, and ‘insufficient support from the university’ was identified as the most critical barrier and challenge. Conclusions The study highlights the significant importance of lecture-free curriculum in medical education and provides insights into its prerequisites, facilitators, challenges, and barriers. The findings can be utilized by educational managers and decision-makers to implement necessary changes in the design and implementation of lecture-free in medical education, leading to more effective improvements in the quality and success of education.

Enhancing academic support for students in higher education

PurposeThe need to enhance student support is evident in higher education (HE) curricula. In addition to the complications created by the COVID-19 pandemic, the current strategies used in academia are criticised for their lack of appropriate student support in HE. The study focused on the themes under Section 4 of the National Student Survey (NSS): availability to contact tutors, receiving good advice and guidance and availability of good advice. The study aimed to provide recommendations for enhancing academic support by developing drivers that need implementation during course delivery.Design/methodology/approachA documental analysis and a qualitative survey were adopted for this study. A documental analysis of 334 mid-module reviews (MMRs) from levels three to six students in the built environment (BE) discipline. Critical themes identified from the MMRs were fed forward in developing a questionnaire for academics. A sample of 23 academics, including a Head of school, a Principal lecturer, Subject leads and Lecturers, participated in the questionnaire survey. Content analysis is adopted through questionnaire data to develop drivers to enhance academic support in BE. These drivers are then modelled by interpretive structural modelling (ISM) to identify their correlation to NSS Section 4 themes. A level partition analysis establishes how influential they are in enhancing academic support.FindingsThe study identified nine drivers, where two drivers were categorised as fundamental, two as significant, four as important, and one insignificant in enhancing academic support in HE. Module leaders’/tutors’ improving awareness and detailing how academic support is provided were identified as fundamental. Differentiating roles in giving advice and the importance of one-to-one meetings were identified as significant. A level partitioning diagram was developed from the nine drivers to illustrate how these drivers need to be implemented to promote the best practices in academic support in HE.Practical implicationsThe identified drivers and their categories can be used to set prioritised guidelines for academics and other educational institutions to improve students’ overall satisfaction.Originality/valueNovelty from the study will be the developed drivers and the level partitioning diagram to assist academics and academic institutions in successfully integrating academic support into HE curricula.

Strategy Analysis for Implementing Rice Transplanter Planting Machine Technology in Rice Farming Using the Interpretive Structural Modeling (ISM) Method in South Sulawesi

Indonesia has several rice producing centers, one of which is Sidrap Regency which is located in South Sulawesi with the support of a rice transplanter technology system. This research aims to analyze the factors inhibiting the implementation of rice transplanter rice planting machine innovation and strategies for implementing the use of this planting machine. This research uses descriptive analysis by creating frequency tables and percentages from primary data results obtained through interviews with respondents. Likert scale to measure farmers' responses to the dissemination of the Rice Transplanter rice planting machine innovation in Sidrap Regency and the ISM method was used to develop a strategy for implementing the dissemination of agricultural innovation to support agricultural development in Sidrap Regency. The research results show that the factors inhibiting the implementation of Rice Transplanter machine innovation are farmers' lack of skills in using rice transplanter, limited rice transplanter, facilities in farmer groups, lack of rice transplanter service providers and lack of farmer staff, motivation to use rice planting tools. The strategy for implementing rice transplanter innovation is through training in implementing rice transplanter innovation, increasing farmers' interest in using rice transplanters, providing rice transplanter facilities and strengthening institutions.

BARRIERS IN ADOPTION OF FINTECH BY STREET VENDORS AND HAWKERS IN INDIA USING INTERPRETIVE STRUCTURAL MODELING

The adoption of financial technology (fintech) has the potential to make banking and financial services more accessible and convenient for all, but there are significant barriers preventing the adoption of fintech by street vendors and hawkers in India. This study aims to identify and analyse the barriers to fintech adoption using interpretive structural modelling (ISM). The research identified nine key barriers to fintech adoption, including perceived risk, lack of trust, lack of perceived benefit, social influence, lack of awareness, cash culture, lack of literacy, perceived ease of use, and lack of financial literacy. The study utilizes ISM to develop a hierarchy of these barriers and their interrelationships. The findings suggest that to promote the adoption of fintech, it is essential to build trust and awareness of fintech services through education and out-reach programs. This research provides a comprehensive understanding of the barriers to fintech adoption among street vendors and hawkers in India and offers insights into how these barriers can be overcomed. The study contributes to the development of strategies that can help promote the adoption of fintech among marginalized populations and advance financial inclusion in India.

Modelling the enablers of productivity of enterprise-level Agile software development process using modified TISM approach

Purpose This study aims to examine the enablers of productivity of enterprise-level Agile development process using modified total interpretative structural modeling (TISM). The two main objectives of the current study are to determine the variables influencing enterprise-level agile development productivity and to develop modified TISM for the corresponding components. Design/methodology/approach To identify enablers of the productivity of enterprise-level agile software development process a literature review and opinions of domain experts were collected. A hierarchical relationship among variables that show direct and indirect influence is created using the modified TISM (M-TISM) technique with Cross Impact Matrix-Multiplication Applied to Classification analysis. This study examined and analyzed the relationships between the determinants within the enterprise using a M-TISM technique. Findings With the literature review, the study could identify ten enabling factors of the productivity of Agile development process at the enterprise level. Results depict that program increment (PI) planning and scalable backlog management, continuous integration and continuous delivery (CI/CD), agile release trains (ART), agile work culture, delivery excellence, lean and DevOps practices, value stream mapping (VMS), team skills and expertise, collaborative culture, agile coaching, customer engagement have an impact on the productivity of enterprise-level Agile development process. The results show that team collaboration, agile ways of working and customer engagement have a greater impact on productivity improvement for enterprise-level Agile development process. Research limitations/implications The developed model is useful for organizations employing scaled Agile development processes in software development. This study provides a recommended listing of key enablers, that may enable productivity improvements in the Agile development process at the enterprise level. Strategists should focus on team collaboration and Agile project management. This study offers a modified TISM model to academicians to help them understand the effects of numerous variables on maintaining the productivity of an enterprise-level Agile. The identified characteristics and their hierarchical structure can help project managers during the execution of Agile projects at the enterprise level, more effectively, increasing their success and productivity. Originality/value The study addresses the gap in the literature by interpretative relationships between the identified enabling factors. The model validation is carried out by a panel of nine experts from several information technology organizations deploying Agile software development at the enterprise level. This unique method broadens the knowledge base in Agile software development at scale and provides project managers and practitioners with a practical foundation.

Leagile supply chains and sustainable business performance: application of total interpretive structural modelling

This study aims to develop an integrated model for the leagile (lean + agile) supply chain strategy to achieve sustainable business performance across the triple bottom line, including economic, environmental, and social performance. We draw upon a literature review and experts’ opinion, using total interpretive structural modelling (TISM), to determine interrelationships among leagile supply chain practices and sustainable business performance measures. To this end, first, unique and common practices of lean and agile supply chain strategies, i.e. leagile building blocks, are identified through a synthesis of the literature. Second, semi-structured interviews with four experts are conducted to gain an understanding of the mutual relationships among the leagile building blocks and to meticulously adjudicate their interactions with sustainable business performance measures. Validated by two independent researchers and literature enfolding, the final TISM model provides a 10-level hierarchical representation of the leagile supply chain strategy for sustainable business performance.

Cost, Usability, Credibility, Fairness, Accountability, Transparency, and Explainability Framework for Safe and Effective Large Language Models in Medical Education: Narrative Review and Qualitative Study.

The world has witnessed increased adoption of large language models (LLMs) in the last year. Although the products developed using LLMs have the potential to solve accessibility and efficiency problems in health care, there is a lack of available guidelines for developing LLMs for health care, especially for medical education. The aim of this study was to identify and prioritize the enablers for developing successful LLMs for medical education. We further evaluated the relationships among these identified enablers. A narrative review of the extant literature was first performed to identify the key enablers for LLM development. We additionally gathered the opinions of LLM users to determine the relative importance of these enablers using an analytical hierarchy process (AHP), which is a multicriteria decision-making method. Further, total interpretive structural modeling (TISM) was used to analyze the perspectives of product developers and ascertain the relationships and hierarchy among these enablers. Finally, the cross-impact matrix-based multiplication applied to a classification (MICMAC) approach was used to determine the relative driving and dependence powers of these enablers. A nonprobabilistic purposive sampling approach was used for recruitment of focus groups. The AHP demonstrated that the most important enabler for LLMs was credibility, with a priority weight of 0.37, followed by accountability (0.27642) and fairness (0.10572). In contrast, usability, with a priority weight of 0.04, showed negligible importance. The results of TISM concurred with the findings of the AHP. The only striking difference between expert perspectives and user preference evaluation was that the product developers indicated that cost has the least importance as a potential enabler. The MICMAC analysis suggested that cost has a strong influence on other enablers. The inputs of the focus group were found to be reliable, with a consistency ratio less than 0.1 (0.084). This study is the first to identify, prioritize, and analyze the relationships of enablers of effective LLMs for medical education. Based on the results of this study, we developed a comprehendible prescriptive framework, named CUC-FATE (Cost, Usability, Credibility, Fairness, Accountability, Transparency, and Explainability), for evaluating the enablers of LLMs in medical education. The study findings are useful for health care professionals, health technology experts, medical technology regulators, and policy makers.

Exploring barriers towards effective coal supply-A non-core perspective using ISM-DEMATEL

While other energy sources are becoming more popular, India is expected to continue to depend on coal in the coming years. This study aims to identify and assess barriers to the efficient supply of coal to non-core industries reliant on this energy source. Employing a hybrid approach combining Interpretive Structural Modeling (ISM) and Decision-Making Trial and Evaluation Laboratory (DEMATEL), we analyse the hierarchical structure and causal relationships among barriers affecting the coal sourcing process. The hybrid model emphasizes that the 'biased government approach' and 'lack of mining technology and infrastructure' are crucial barriers. These key barriers exert a substantial influence on other factors within the scope of our study. Unlike earlier studies, this research enhances theoretical understanding by thoroughly exploring barriers to effective coal sourcing strategies. Policymakers engaged in decision-making for the non-core coal-dependent sector in India can benefit from this research. Attention should be directed towards addressing key barriers influencing effective coal sourcing, specifically focusing on ‘biased approach by the government’, ‘lack of mining technology and infrastructure’, ‘social and political constraints’, ‘low research and development’, and ‘lack of skilled personnel’.