Interpretive Structural Modelling Approach Research Articles

An integrative perspective on inter-organisational collaboration in healthcare: a modified total interpretive structural modelling approach

PurposeThis study develops a model for understanding the relationships and interactions between the antecedents influencing inter-organisational collaboration in the healthcare sector.Design/methodology/approachA comprehensive and systematized search was conducted on Scopus to identify all relevant studies investigating the antecedents of inter-organisational collaboration in the healthcare sector. Antecedents were identified based on insights from experts and a systematised search method. A modified total interpretive structural model (m-TISM) was used to determine the hierarchical relationships between the identified antecedents. Finally, the Matrice d’Impacts Croisés Multiplication Appliquée à un Classement (MICMAC) analysis was employed to categorise the identified antecedents into clusters based on their driving or dependence influence.FindingsEight antecedents of inter-organisational collaboration in the healthcare sector were identified. The results revealed that having a shared vision and goals, digital infrastructure and proximity are the most crucial antecedents of inter-organisational collaboration in healthcare, along with leadership, shared resources and communication.Research limitations/implicationsFuture research on inter-organisational collaboration in the healthcare sector can include additional factors that may influence collaboration beyond those currently studied. Structural equation modelling can be employed to validate the proposed model.Originality/valueThe study proposes a hierarchical model for inter-organisational collaboration in the healthcare sector. The framework will help healthcare executives and academicians identify key antecedents that are most critical to enabling effective collaboration.

Analysing post adoption factors for determining MOOC continuance intentions: Interpretive Structural Modelling and fuzzy MICMAC approach

Analysing post adoption factors for determining MOOC continuance intentions: Interpretive Structural Modelling and fuzzy MICMAC approach

Factors affecting sustainable entrepreneurial behaviour among youth community: assessment through interpretive structural modelling and MICMAC approach

Factors affecting sustainable entrepreneurial behaviour among youth community: assessment through interpretive structural modelling and MICMAC approach

Balancing Growth and Preservation: Strategic Pathways for Sustainable Rural Tourism in China’s Environmental Landscape

Sustainable rural tourism development is paramount for the socio-economic advancement of rural regions in China. This study systematically prioritizes the key drivers essential for the successful implementation of sustainable rural tourism development by employing the Interpretive Structural Modeling (ISM) and MICMAC analysis methodologies. Through an extensive literature review and expert consultations, we identify and categorize the critical drivers influencing sustainable rural tourism. Utilizing the ISM approach, we construct a hierarchical structure to elucidate the interrelationships among these drivers. Following this, MICMAC analysis is applied to assess their driving and dependence power. We find that government policy and support is the most powerful driver forming the basis for sustainable rural tourism development. Moreover, our findings uncover a complex network of interdependencies, with several drivers emerging as crucial for effective implementation. This research provides invaluable insights for policymakers, stakeholders, and practitioners, offering a robust framework to inform strategic decision-making in fostering sustainable rural tourism development in China.

Barriers to Implementing Lean Six Sigma in the Chemical Process Industry: The Case of Brazil

Lean Six Sigma (LSS) is recognized as a powerful process improvement methodology for enhancing operational efficiency and long-term sustainability. This study examined the barriers hindering LSS implementation in the chemical process industry within an emerging economy, Brazil. It developed a structured methodology for designing mitigation measures to overcome those barriers. First, 26 barriers from the literature were ranked by LSS experts through a Delphi survey to select the top 15. Then, a combined interpretive structural modeling (ISM) approach and impact matrix cross-reference multiplication applied to a classification (MICMAC) analysis approach was used, supported by a focus group, to determine the hierarchical relationships among the barriers and their driving power and dependence. Finally, a second focus group defined adequate mitigation measures. The top four main barriers are the lack of time, insufficient systemic understanding of lean principles, misalignment between LSS and corporate strategies, and inadequate top management commitment. Additionally, 10 mitigation measures are proposed. This study contributes to LSS implementation in the chemical process industry in Brazil, thus enhancing industry sustainability by improving operational efficiency, curbing waste, reducing transportation-related emissions through a decreasing reliance on imported chemical products, and contributing to economic growth and job creation within the industry.

Blockchain Technology and Industry 5.0 synergy for sustainable development in RMG industries: an ISM and fuzzy DEMATEL approach

This research explores the contribution of Blockchain Technology and Industry 5.0 in driving sustainability within Bangladeshi Ready-Made Garments (RMG) industry, with a focus on alignment with key Sustainable Development Goals (SDGs). The study employs Interpretive Structural Modeling (ISM) and fuzzy Decision-Making Trial and Evaluation Laboratory (DEMATEL) methods to identify and analyze 14 critical synergies that can drive sustainability. The ISM analysis categorizes the synergies into independent, dependent, and linkage variables, providing insights into their roles and significance within the system. Fuzzy DEMATEL further refines this understanding by evaluating the direct and indirect relationships among the linkage synergies. Key findings reveal the importance of synergies such as reverse logistics and recycling, supply chain collaboration & visibility and ethical practices in driving sustainability. This research contributes by offering a detailed analysis of how the synergy between Blockchain technology and Industry 5.0 can enhance sustainability practices in the RMG industry, providing actionable insights into the technological transformation of supply chain dynamics in support of global sustainability targets.

Improving halalness and food safety management systems in the Indonesian broiler supply chain: an interpretive structural modeling and Bayesian network approach

Purpose By exploring the halalness and food safety risks from the perspective of technology and the relationship among them, this study aims to make quantitative predictions of such risks in the broiler supply chain to determine the critical control points (CCPs) in Hazard Analysis Critical Control Point (HACCP). Design/methodology/approach This study integrates Interpretive Structural Modeling (ISM) and Bayesian Network (BN) to achieve the objectives. Data were collected from focus group discussions (FGDs) with experts and direct observations at the broiler supply chain. Findings This paper identified 19 risks in the Indonesian broiler supply chain. The risk for halalness and food safety reached 30.92%, indicating that assuring halalness and food safety remains improbable or unlikely. The two CCPs of halalness and food safety are the knife’s sharpness and the vehicle’s storage temperature. Research limitations/implications This study quantifies the halalness and food safety risks in the Indonesian broiler supply chain, but it only involves one step forward and one step backward in the slaughterhouse’s chain. Practical implications The findings can provide insights for stakeholders, such as business owners, employees, management system auditors and consumers, regarding the critical control points of halalness and food safety in the broiler supply chain to improve the halalness and food safety management systems. Originality/value This study’s novelty lies in the examination of halalness and food safety risks using a risk prediction model to determine CCPs for the HACCP plan in the broiler supply chain in Indonesia.

Capabilities toward adoption of outcome-based contracts

PurposeManufacturing enterprises have started to offer the “outcome” derived from machines with the help of outcome-based contracts (OBCs). Offering OBCs leads to benefits such as increased revenues, stronger customer relationships and sustainability. However, implementing OBCs requires critical capabilities. Existing literature has focused on identifying these necessary capabilities, but the prioritization and interrelationships among them remain unexplored. This study aims to address this gap.Design/methodology/approachOur study employs a hybrid analytical hierarchy process and interpretative structural modeling approach to prioritize and map interrelationships among OBC-related capabilities within small and medium-sized enterprises (SMEs).FindingsThe findings highlight the importance of digitalization capabilities such as data privacy and security, remote monitoring, and data analytics; and organizational and governance capabilities, including quantifying, controlling, and monitoring risks, teamwork, and leadership, are highlighted.Research limitations/implicationsWe quantitatively prioritize OBC capabilities and establish their level-wise structural interrelationships, which will facilitate a more effective and efficient implementation of OBCs. Due to the emergent nature of OBCs, our study could identify just one SME case company meeting our selection criteria.Originality/valueExisting OBC literature focusses on the design of OBCs in large companies. Similarly, earlier capability-related OBC literature is oriented toward identifying the OBC capabilities to perform specific functions. However, in the current study, we propose a systematic decision-making approach that comprehensively prioritizes and identifies the interrelationships among the capabilities necessary to provide OBCs, thus complementing the existing scientific literature on OBCs. In addition, we focus on SMEs, that have specific limitations and characteristics.

Examining the challenges impeding the utilization of construction materials with lower embodied carbon in the construction sector

ABSTRACT This paper aimed at determining the barriers preventing the extensive utilization of innovative materials in the construction sector. As a way of providing clear understanding of the complex interrelationship between the barriers, the literature review was supplemented by an expert-based survey to determine the barriers, whereas the hierarchical structure between the barriers was analyzed using the interpretive structural modelling (ISM) approach. Based on the outcome of the level partitioning of the ISM approach, it was found out that “reluctance to take responsibility for embodied carbon reduction (B14) was partitioned at the 8th level indicating that it is the most highly prioritized barrier considered to be the most crucial in preventing the use of low-carbon building materials in the construction industry. The paper produces vital knowledge and evidence that could be applied to encourage more sustainable construction practices by the wide adoption of alternative construction materials with lower embodied carbon in the construction sector. The implications inferred based on the findings of this paper seek to suggest remedies, strategies, and actions that could help to overcome the undesirable impact of the barriers that affect the utilization of low-carbon building materials, particularly amongst prominent stakeholders of construction projects.

Challenges of Applying Circular Economy in Agricultural Sustainable Development: A Case Study of Kurdistan Province, Iran

Current production and distribution models in agriculture primarily operate based on the 'linear economy' approach. This means that after the exploitation of natural resources and the production of the final product, a significant portion of these resources and products, now contaminated or turned into waste, exit the economic cycle. The circular economy approach in agriculture seeks to reuse waste products and depleted inputs, thereby reducing the intensity of resource exploitation and taking a step towards sustainable agriculture. However, applying circular economy concepts in agriculture across different regions, especially in developing countries like Iran, can encounter various obstacles and challenges. The present study aims to identify and analyze these obstacles and challenges in the agriculture sector of Kurdistan Province, one of Iran’s key agricultural regions. For this purpose, after reviewing the literature and gathering expert opinions from the province's agrarian elites, 16 challenging factors were identified as potential barriers to expanding the circular economy in Kurdistan Province. These were examined and analyzed using the Interpretive Structural Modeling (ISM) approach. The required data were collected via a questionnaire in the spring of 2024. The research findings indicate that among the 16 factors analyzed, the key variables are the second, first, and third factors—namely, the illiteracy and low literacy rates among farmers, traditional and subsistence farming, and the small size and fragmentation of agricultural lands in Kurdistan Province. According to the experts and specialists interviewed, addressing these variables can significantly influence others, reducing the barriers and challenges facing the circular agricultural economy and the sustainable development of agriculture in Kurdistan Province.

Mapping the critical factors of emerging technologies adoption intention in foodservice industry: a modified total interpretive structural modeling approach

ABSTRACT The advancement in technology is transforming the competitive ecosystem of the foodservice industry, thus enabling firms to enhance their intention to adopt emerging technologies. This transformation enables foodservice industry-based firms to focus on innovation and emerging technologies adoption within a rapidly changing business landscape. This study explores the critical factors of emerging technologies adoption intention in the foodservice industry and employs “modified total interpretive structural modeling” and “matrices impacts cruises multiplication applique classement” analysis to create a hierarchical model that establishes the relationship among identified factors impacting emerging technologies adoption intention. A five-level hierarchical model is developed. Findings of this study indicate that organizational characteristics and competitive pressure experienced by the foodservice industry are the driving factors that impact emerging technologies adoption intention. This paper helps to understand the dynamics between identified factors of technology adoption in the context of the foodservice industry using frameworks (“unified theory of acceptance and use of technology” and “technology acceptance model”). The proposed hierarchical model provides a structural framework that helps practitioners and researchers to understand the interrelation among critical factors of emerging technologies adoption intention in the rapidly evolving dynamic ecosystem of the foodservice industry.

Enabling sustainable circular economy in Indian municipal solid waste management system: an ISM and fuzzy MICMAC approach

PurposeMismanagement of municipal solid waste (MSW) has led to resource depletion, ecosystem degradation and socio-economic risks, emphasizing the necessity to promote sustainable circular economy (SuCE) practices. This article identifies relevant enablers and unveils their interconnected roles in facilitating a municipal solid waste management (MSWM) system aligned with the principles of SuCE.Design/methodology/approachTo identify pertinent enablers for MSWM systems based on SuCE principles, the study conducted a literature review and engaged experts from waste management sectors and academia to consolidate the final list of enablers. Following this, the study investigated the inter-relationships among these enablers using both Interpretive Structural Modeling (ISM) integrated and fuzzy Matrix Impact Cross-Reference Multiplication Applied to a Classification (fuzzy MICMAC) with MATLAB.FindingsThe study identified a comprehensive set of 23 enablers and categorized them into four control measures instrumental for the effective integration of SuCE principles in the context of the Indian MSWM system. Notably, the analysis highlighted that “authoritative pressure” and “policy transformation” are the highly influential enablers.Practical implicationsThe study emphasizes actionable implications for stakeholders in the Indian MSWM sector. Policymakers and governmental bodies can enforce “authoritative pressure,” “policy transformation” and “budget allocation”. Meanwhile, managers can focus on “promotion of SuCE awareness”, “formalizing the informal workforce”, “infrastructure modernization”, “stakeholder engagement and alignment”, “segregation strategy”, “disruption preparedness”, and “local-based strategy”.Originality/valueThis study proposed a unique ISM diagraph and cluster of enablers to enhance the novelty of the study.

Analyzing the function of metaverse technology in the retention and absorption of knowledge using the integrated approach of interpretive structural modeling and structural equations

Analyzing the function of metaverse technology in the retention and absorption of knowledge using the integrated approach of interpretive structural modeling and structural equations

Analyzing factors influencing competitiveness of Indian tech start-ups: modified total interpretive structural model (m-TISM) approach

Analyzing factors influencing competitiveness of Indian tech start-ups: modified total interpretive structural model (m-TISM) approach

Evaluating the impact of digital and financial literacy on MSME performance

ABSTRACT The objective of this study was to determine the critical success factors that contribute to the performance of micro-, small, and medium-sized enterprises (MSMEs) in the context of digital and financial literacy. This study employed the total interpretive structural modeling approach to construct a hierarchical model of important success elements and analyze their direct and indirect interconnections. This article specifies six success factors that impact the performance of MSMEs, with the consideration of their effects and value generation leading to enhanced performance. The results indicate that entrepreneurial orientation and digital literacy are the primary components of the developed model, with all factors collectively contributing to overall performance. By identifying and categorizing key components within the strategic model, the study provides MSME founders with a systematic way to enhance business competency, which has significant consequences for business growth and success. The hierarchical model developed in this research assists policy makers and practitioners in improving the performance of MSMEs.

Industry 4.0 implementation barriers in automotive manufacturing industry: Interpretive structural modelling approach

Industry 4.0 manufacturing practices are the trends of automation and data exchange, which involve heavy investment to adopt the latest modern technologies for improving the manufacturing process in terms of productivity, efficiency, flexibility, and profitability. In this context, the current study focuses on the key implementation barriers of Industry 4.0 in the automotive industry. An interpretive structural model of the barriers to implement Industry 4.0 in the automotive industry has been proposed to create a hierarchical order of key barriers, find the relationships among them, and create a graphical model of the system. Based on the review of available literature and discussion with experts in the automotive field, thirteen barriers have been identified to frame the model. Further, out of these thirteen, two barriers have been found to be dependent, another two as driving barriers, the remaining nine as linkage barriers, and none as autonomous barriers. Based on the developed model, ‘Great Risk of Obsolescence’ has been found to be the top-level dependent barrier and geographical risk to be the lowest-level independent barrier. A clear comprehension of the interactions between the key barriers can help in deciding priorities and managing the same to have higher efficacy and efficiency in implementing Industry 4.0. Overall, we aim to identify Industry 4.0 barriers in the automotive industry and prioritize them during the implementation of Industry 4.0. The structured model, so designed and developed, is expected to facilitate the understanding of the interdependence of the barriers of the Industry 4.0 manufacturing system amid its implementation.

The Analysis of Trigger Factors of the Environmental Entrepreneurship Process in Saudi Arabia: An Innovative Approach

Environmental entrepreneurship is considered a critical avenue for sustainable development. Despite increasing studies on its benefits and impacts, we lack insights about its corresponding process. There is an increasing need for policymakers to know how to develop this process and what is required for its definition. This research aims to build an innovative theoretical model to explore the trigger factors for the environmental entrepreneurship process in Saudi Arabia, which is the ultimate focus point of this research. To achieve this objective, a deep literature review and a survey of expert entrepreneurs’ opinions were performed. Experts and professionals in entrepreneurship validated the opportunity of readiness factors identified. Data were gathered using a combined approach based on closed-ended questionnaires and arranged interviews according to a schedule. Employing the mixed influence matrix of cross-impact multiplications applied to classification (MICMAC) and the Interpretive Structural Modeling (ISM) approach, the research identifies a hierarchical model of these factors, addressing why and how they interact according to a specific order and priorities. The investigation reveals 15 factors that are structured into three main levels of influence: (1) factors driving the adoption of environmental entrepreneurship orientation, (2) factors related to environmental entrepreneurship intention, and (3) factors for materializing environmental entrepreneurship behavior. The findings emphasize the complementarity between environmental entrepreneurship intention and orientation as a key factor in generating entrepreneurial behavior. This research pioneers the empirical exploration of environmental entrepreneurship as a process. It contributes significantly to theoretical and practical domains by offering a pragmatic framework and better understanding for policymakers and stakeholders to focus on key factors that facilitate this process. This paper is innovative because it uses the integrative ISM–MICMAC approach, supported by a primary and brief bibliometric analysis of entrepreneurship.

Fostering environmentally sustainable business: Analysis of factors from entrepreneurial ecosystem perspective

Sustainable business practices are paramount for long-term environmental preservation and fostering economic growth. Despite the extensive body of literature on various aspects of business sustainability, there remains a noticeable gap in understanding the fundamental factors influencing its adoption. Drawing on the entrepreneurial ecosystem perspective, this study endeavors to examine the hierarchical importance of various factors affecting the environmental sustainability of the business. Employing a comprehensive literature review, we meticulously identified a list of factors and performed analysis using data gathered from experts. In particular, we used Total Interpretive Structural Modelling and MICMAC approach to analyze the identified factors, with an aim to uncover their interlinkage and association. Our findings underscore the critical role played by the government in shaping business sustainability. Additionally, factors such as consumer, technological innovation, and market competition also hold substantial importance. In contrast, factors such as financial considerations, stakeholders, leadership dynamics, human resources, infrastructure, and internal organizational factors appear to have comparatively less influence. Our study not only reveals the significance of these factors but also unveils the intricate web of interrelationships among them. The resulting strategic theoretical framework offers valuable insights for managers and policymakers, highlighting the practical relevance and contextualized interactions among various factors.

Investigating the Key Drivers in the Transition to Sustainable Hydrogen Transportation Fuel

Introduction. Hydrogen is a promising energy carrier that can achieve net-zero carbon emissions and decrease fossil fuel dependency. However, the importance of the driving forces in hydrogen adaptation and acceptance during the transition to this technology should be emphasised. When assessing hydrogen as a sustainable transportation fuel, defining the success criteria is vital to comprehend the benefits of hydrogen in the transition process. The transport sector is a priority area for the transition to zero emissions, which requires an understanding of the links between the key drivers of hydrogen adoption in transportation. Aim and tasks. This study aims to identify the key drivers of the hydrogen transition and explore the relationship between the transition drivers to hydrogen as a sustainable transport fuel based on a comprehensive literature review and an interpretative structural modelling approach to determine the relationship between the above-mentioned key drivers. Results. This study identified key drivers for the transition to hydrogen as a sustainable transport fuel using the Interpretive Structural Modelling (ISM) approach. This study examines the potential of hydrogen transition, analyses the driving forces, and examines their interrelationships in terms of driving force and dependent force. The role of technological development and transition awareness in achieving the SDGs is revealed. Robust regulatory agendas and supportive strategies, Workforce development and training based on hydrogen deployment, and Industry partnerships and collaboration are the most fundamental drivers for achieving the transition to hydrogen as a sustainable transport fuel. In addition, the advancement of hydrogen technologies in production, storage, and transportation, as well as hydrogen production and use, aligns with environmental aims, which are key factors that depend mainly on the actions of other driving forces. However, the limitations of this study include subjectivity and potential differences in the driving forces across countries and sectors. Conclusions. The deployment of green hydrogen transition for a clean energy source is critical in carbon-intensive sectors of the economy, which are characterised by key drivers and their interlinkages, such as regulatory strategies, workforce development, and industry partnerships. This has increased the flexibility of energy systems with the collaboration of the stakeholders for developing hydrogen technologies and infrastructure, considering the environmental safety, economic efficiency, and social acceptability of hydrogen.

Interpretive Structural Modelling and MICMAC Analysis for Rethinking Special Mathematics Education

Quality and inclusive education, especially for people with disabilities, finds priority in academic and policy initiatives for special education (SPED) programs. Several scholars have highlighted the significance of SPED in the domain literature; however, a comprehensive analysis of critical factors contributing to successful teaching, especially mathematics, is currently missing. Hence, the structural relationship among the critical success factors is established in this study through an interpretive structural modeling approach and Matrice d'impacts croisés multiplication appliquée á un classment (MICMAC) analysis. Results from the adopted methodology show that a teacher's mathematical knowledge is the most significant factor contributing to the success of teaching mathematics with SPED students. Allocating resources to improve and address this particular driving factor will influence the remaining factors. The study findings offer valuable insights for decision-makers and relevant stakeholders in academic institutions.