Interpretive Structural Modelling Approach Research Articles

Understanding critical barriers to the adoption of blockchain technology in the logistics context: An interpretive structural modelling approach

Blockchain technology has promising benefits and provides robust solutions for managing business processes. While prior studies have primarily explored its potential in supporting logistics and supply chain management, many practitioners still lack a clear understanding of how to leverage blockchain technology, hindering its adoption within the industry. Bridging this gap and addressing critical barriers requires further empirical research. This study adopts a comprehensive approach, identifying potential barriers through a literature review and validating their significance through the Index of Item-Objective Congruence (IOC). The study then delves into the interrelationships among the significant barriers, utilising Interpretive Structural Modelling (ISM) and MICMAC methods. The results highlight seven significant barriers within the logistics sector, encompassing a lack of government support, operational standards, top management support, limited public awareness, trust issues, technical challenges, and network collaboration difficulties. Notably, the lack of public awareness and inadequate governmental support form fundamental obstacles that drive various challenges. This research offers insights into the barriers that hinder the successful adoption of blockchain technology in logistics, proposing several mitigation strategies that are in line with the principles of open innovation.

An interpretive structural modelling approach to determine the critical causes and effects of design changes in public infrastructure projects

An interpretive structural modelling approach to determine the critical causes and effects of design changes in public infrastructure projects

Deciphering the factors shaping blockchain technology adoption in the BFSI industry: TISM-MICMAC approach

Purpose As the global financial ecosystem grapples with the complexities of modernization, blockchain technology emerges as a pivotal catalyst, offering the banking, financial services, and insurance (BFSI) industry unprecedented opportunities for secured digital transformation and enhanced customer trust. To gain a comprehensive understanding of blockchain technology adoption, this study aims to identify the factors and establish the contextual interrelationships among them. Design/methodology/approach The authors have identified the factors affecting blockchain technology adoption in BFSI industry through extensive literature review and experts’ interviews. After identification of factors, contextual relationship has been established based on experts’ opinion and total interpretive structural modeling (TISM) approach. Furthermore, factors are categorized into autonomous, dependent, linkage and driving variables using cross-impact matrix multiplication applied to classification analysis. Findings The TISM-based structural model is divided into eight different hierarchal levels in which Government support is placed on the lower most layer (level 8) which indicates that this is the most crucial factor in blockchain adoption. Further social influence and security are placed on seventh and sixth level in the hierarchy. Practical implications The results of this study will help the policymakers to direct the resources from the most crucial factor to other factors in the hierarchy as per their relevance. In essence, this study serves as a guiding compass, steering the course of blockchain technology adoption in the BFSI sector toward a more secure and digitally transformed future. Originality/value In the current landscape, blockchain technology remains in its nascent stage, leaving ample room for exploration and innovation. This study stands as the pioneering effort to comprehensively identify and establish the contextual relationships among the adoption factors of blockchain technology within BFSI industry. Through rigorous TISM analysis, this paper enriches the existing body of knowledge on blockchain technology adoption.

The organic waste management supply chain performance evaluation strategy uses an Interpretive Structural Modeling approach

National Waste Management Information System shows that the amount of waste handled in Semarang City over the last three years has decreased with an average decline index of 1.06% per year. This is reinforced by the results of interviews with the Semarang City Environmental Service, that the handling of organic waste is still very limited because so far the handling has been more focused on an-organic waste. Therefore, it is necessary to evaluate supply chain performance to determine the constraints in organic waste management from upstream to downstream. Based on the research results using the Interpretive Structural Modeling (ISM) method through a focus group discussion process involving eight experts in the field of waste management, it is known that the supply chain performance for handling organic waste in Semarang City has 11 elements of constraints, which are divided into seven priority levels. The element with the highest priority is related to the availability of organic waste supplies, while the element with the lowest priority is technological innovation and the application of appropriate technology. Improving the performance of organic waste management supply chains should focus on elements according to priority.

Stakeholders’ perspectives on critical success factors for environmental social and governance (ESG) implementation

Environmental Social and Governance (ESG) has emerged as a sensitive issue, attracting the attention of a large audience that could not be ignored. Government bodies continue to pass regulations mandating organizations to comply with ESG principles. However, many organizations have had unsatisfactory results while promoting sustainability ideals due to various challenges. To achieve ESG goals, the present study offers a thorough framework for ESG implementation across organizations based on the critical success factor (CSF) theory and the opinions of diverse stakeholders. Following a literature review and brainstorming with ESG experts and academicians, a survey questionnaire was sent to 400 respondents to evaluate the 20 factors identified as ‘super-set’ CSFs for ESG implementation. This paper represents a novel attempt in ESG research as it conducts a survey supported by exploratory factor analysis (EFA). The interactions between the significant CSFs were studied by employing total interpretative structural modeling (TISM) and fuzzy MICMAC approach. ESG implementation is found to be highly driven by firm characteristics, earnings quality, and environmental performance, which can be argued to be the fundamental determinants of ESG implementation. According to these findings, organizations' leadership should (1) focus on effectively structuring firms' attributes to swiftly operate the ESG implementation framework, (2) ensure consistent business earnings that signal improved future performance, and (3) continuously monitor and assess their environmental performance. These efforts should be supported by engaging with diverse stakeholder groups, each playing its respective role in ESG implementation. Consequently, ESG implementation across organizations is anticipated to accelerate with thoughtful organizational coordination, strategic planning, and compliance with authoritative policies. However, rather than solely focusing on creating ESG disclosure laws, policymakers should also focus on creating better ESG outcomes through effective ESG implementation. Therefore, this research offers valuable insights into improving ESG practices, which facilitates the adoption of mandatory ESG disclosure regulations.

Interpretive Structural Modelling Approach to Evaluate Knowledge Sharing Enablers in Circular Supply Chain: A Study of The Indian Manufacturing Sector

Interpretive Structural Modelling Approach to Evaluate Knowledge Sharing Enablers in Circular Supply Chain: A Study of The Indian Manufacturing Sector

Critical Success Factors for Emerging Technology Adoption, Strategic Flexibility, and Competitiveness: An Evidence-Based Total Interpretive Structural Modeling Approach (TISM-E)

Critical Success Factors for Emerging Technology Adoption, Strategic Flexibility, and Competitiveness: An Evidence-Based Total Interpretive Structural Modeling Approach (TISM-E)

Barriers to the adoption of blockchain technology in the construction industry: a total interpretive structural modeling (T ISM) and DEMAT EL approach

Purpose The purpose of this study is to identify the key barriers to the adoption of blockchain technology (BCT) in the construction industry. This investigation seeks to understand the challenges that hinder the implementation of blockchain in this sector. Design/methodology/approach The study begins with a comprehensive review of relevant literature to identify the main barriers to blockchain adoption in construction. It then uses an integrated approach using total interpretive structural modeling (TISM) and Matrice d'Impacts Croisés Multiplication Appliquée à un Classement to investigate the interrelationships among these barriers. In addition, the decision-making trial and evaluation laboratory (DEMATEL) method is used to establish cause-and-effect relationships between the identified barriers. Findings The study’s integrated TISM and DEMATEL methodology reveals several crucial barriers to blockchain adoption in the construction industry, including regulatory uncertainty, data privacy and security concerns, limited knowledge and expertise and dependence on blockchain operators. It also identifies scalability issues, uncertain benefits and lack of collaboration as dependent barriers, influenced by other identified barriers. Originality/value This study contributes original value by applying an integrated methodological approach to understand the complex interrelationships and dependencies among barriers to blockchain adoption in the construction industry. The findings provide decision-makers with insights to prioritize and effectively manage the key driving barriers, enhancing the understanding and strategic planning for blockchain implementation in this sector.

Risk Assessment of Highway Infrastructure REITs Projects Based on the DEMATEL—ISM Approach

Highway infrastructure projects financed by real estate investment trusts (REITs) have garnered significant attention due to their potential for generating stable returns. However, assessing the risks associated with such projects remains a critical challenge. This study addresses this gap by proposing a novel approach to risk assessments utilizing the Decision-Making Trial and Evaluation Laboratory (DEMATEL) integrated with Interpretive Structural Modeling (ISM). Unlike traditional risk assessment methods, which often treat risk factors as isolated entities, the DEMATEL—ISM approach provides a comprehensive framework that reveals the direct and indirect relationships between risk factors, thus offering a systemic understanding of the interactions. The results found that falling market prices, insufficient operating revenues, and operational inefficiencies were direct influences, and high financing costs and force majeure were the fundamental influences, while other factors acted as intermediate influences. In addition, the study identifies direct and indirect relationships between different risk factors, providing a hierarchical topology of risk factors to reflect the relationships between the risk factors. The findings not only contribute to enhancing the understanding of risk dynamics in highway infrastructure REITs projects, but also offer a structured framework for risk assessment and mitigation. This research represents a significant innovation in the field of infrastructure investment risk management, offering practical implications for project planning, decision-making, and risk management strategies.

A multilevel model for organizational productivity management: an interpretive structural modeling approach

PurposeThis research highlights the ongoing concern about organizational productivity and the lack of focus on designing an optimal model. The authors aim to create a comprehensive model for managing organizational productivity, considering its impact on profitability, customer satisfaction, and employee morale. They use qualitative research methods, including Systematic Literature Review and Interpretive Structural Modeling (ISM).Design/methodology/approachIn this research using the qualitative research method of Systematic Literature Review, 57 variables affecting productivity were identified. These variables were placed in 16 layers by using the ISM method, which were classified analytically in four sections: INPUTS, OUTPUTS, OUTCOMES and IMPACTS. By determining the relationship between the sections, the research model was designed.FindingsThe potential model for organizational productivity management provides a comprehensive framework addressing critical factors like technology adoption, employee empowerment, organizational culture, and more. It identifies Linkage, Dependent, and independent variables. The lower layers consist of INPUTS such as Technological Tools, Organizational Values, and more. In the highest layer, impactful variables like Enhanced competitiveness, Improved decision-making, and Improved organizational culture are labeled as IMPACTS. Middle layer variables are categorized as OUTPUTS and OUTCOMES.Originality/valueIn this study, the concept of productivity management was redefined for the first time, and a multi-layered model for productivity management was creatively explicated using the structural equation modeling method.

Enablers for Usage of the Mobile Wallet by Msmes in Rural India: Using the Interpretive Structural Modelling Approach

Abstract In today`s digital era, it is all the more desirable that all businesses, whether gigantic or minor in operation, should adopt financial technology and grow their businesses within their region and outside of the region. The Micro, Small & Medium Enterprises (MSME) segment is the mainstay of the Indian economic environment thus it is crucial that MSME players adopt financial technology in their routine commercial transactions. The present research study was conducted to investigate the enablers of usage of a Mobile Wallet by MSMEs in rural areas of India using interpretive structural modeling. It aims to categorize the foremost enablers and assess the relative relations between the recognized ten key enablers and proposes a hierarchical outline of vital enablers on MSME entrepreneurs from several hill states of India. The most prominent enabler that promoted the use of mobile wallets among MSME entrepreneurs included risk factors and perceived cost. The study suggested that multi-dimensional determinations are required to make certain of the use of mobile wallets by MSME entrepreneurs so that they can assess maximum economic opportunities and support the fiscal expansion of the state and the country.

Leadership and Infrastructure in Implementing Professional Learning Communities in Lahore HEIs: An Interpretive Structural Modeling Approach

Professional learning communities (PLCs) are considered vital for teachers’ professional development and filling the achievement gaps among students. Implementing PLCs in higher educational institutions (HEIs) may be affected by various factors such as leadership support, infrastructure, environment, and knowledge about its usefulness. Identifying all these key factors is necessary for the HEIs growth and students’ outcomes. This study aims to identify such important factors that help implement PLCs in Pakistani universities by utilizing Interpretive Structural Modeling (ISM). The data were collected from fourteen university faculty members. This qualitative study first identified the important factors for the implementation of PLCs from the prior studies then established relationships among these factors and proposed a final model through the ISM approach. The results suggest that leadership support and infrastructure are important factors for the implementation of PLCs in Pakistani HEIs while time constraints, equal participation, workload, working environment trust among stakeholders and vague understanding of PLCs act as mediators. The suggested final model can be used for further empirical investigation and future planning and implementation of the PLCs.

Analysis of Barriers to the Successful Implementation of Digitalization in South Africa Using the Interpretive Structural Modelling Approach

Many digitalization programmes fail in the implementation phase due to unforeseen obstacles. This study examines the barriers that affect the successful implementation of digitalization using the interpretive structural model and also evaluates the interrelationships among the barriers in the implementation of digitalization. Previous articles in the discipline of digitalization were used in the literature to mainly draw barriers found during the implementation phase of digitalization. Interpretive Structural Modelling results helped to find different levels of barriers and their influence on the system. The high cost of digital technologies and political instability were identified as the leading barriers affecting the successful implementation of digital systems in South Africa. The findings will aid in decision-making for problem-solving to eliminate the most critical barriers to improve the implementation process.

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.

Factors affecting team performance of external auditors in Iran: A Delphi–interpretive structural modelling approach

Factors affecting team performance of external auditors in Iran: A Delphi–interpretive structural modelling approach

Analyzing shopping cart abandonment enablers: an ISM and MICMAC approach

PurposeThe primary purpose of this study is to examine the factors leading to shopping cart abandonment and construct a model depicting interrelationship among them using interpretive structural modeling (ISM) and Matriced Impact Croises Multiplication Appliquee an un Classement (MICMAC).Design/methodology/approachInitially, 20 factors leading to shopping cart abandonment were extracted through a systematic literature review and expert opinions. Fifteen factors were finalized using the importance index and CIMTC method, for which consistency has been checked in SPSS software through a statistical reliability test. Finally, ISM and MICMAC approach is used to develop a model depicting the contextual relationship among finalized factors of shopping cart abandonment.FindingsThe ISM model depicts a technical glitch (SC8), cash on delivery not available (SC4), bad checkout interface (SC9), just browsing (SC11), and lack of physical examination (SC12) are drivers or independent factors. Additionally, four quadrants have been formulated in MICMAC analysis based on their dependency and driving power. This facilitates technical managers of e-commerce companies to focus more on factors leading to shopping cart abandonment according to their dependency and driving power.Research limitations/implicationsTaking an expert’s opinion as a base may affect the results of the study due to biases based on subjectivity.Practical implicationsThis study’s outcomes would accommodate practitioners, researchers, and multinational or national companies to indulge in e-commerce to anticipate factors restricting the general public from online shopping.Originality/valueFor the successful running of an e-commerce business and to retain the confidence of e-shoppers, every e-commerce company must make a strategy for controlling factors leading to shopping cart abandonment at the initial stage. So, this paper attempts to highlight the main factors leading to shopping cart abandonment and interrelate them using ISM and MICMAC approaches. It provides a clear path to technical heads, researchers, and consultants for handling these shopping cart abandonment factors.

Harvest to basket: understanding drivers of organic food purchase behaviour through interpretive structural modelling and MICMAC approach

Purpose The purpose of this study is to examine the determinants impacting consumer behaviour in organic food consumption in Bangladesh. This study aims to identify the key factors facilitating organic food consumption and establish a framework by analysing their contextual relationships. Design/methodology/approach The study used interpretive structural modelling (ISM), relying on expert perspectives from experienced academicians and marketing professionals. A Matrice d'Impacts Croisés Multiplication Appliqués à un Classement (MICMAC) analysis was performed to assess the driving forces and interdependencies among these determinants. Findings The MICMAC analysis grouped determinants influencing organic food purchases into four categories. The dependent factors, like attitude and food safety, showed moderate driving forces and high dependence. Linkage determinants, such as environmental concern and price, exerted considerable influence with moderate dependence. Independent variables, especially knowledge about organic food, had a strong impact with relatively low dependence. Practical implications This study’s insights offer valuable guidance for managers in the organic food industry, providing strategies to address consumer behaviour. Prioritising education on environmental benefits, transparent pricing, collaborating on policies, ensuring food safety and understanding determinants impacting purchase intent can aid in designing effective marketing strategies and product offerings aligned with consumer needs, ultimately promoting sustainability. Originality/value To the best of the authors’ knowledge, this study is the first to investigate the interconnections and relative significance of determinants influencing organic food purchases, using the ISM approach and MICMAC analysis. It delves into the previously unexplored territory of understanding the relationships and hierarchical significance of these determinants in shaping consumer behaviour towards organic food purchases.

Digital Transformation of Incumbent Pipeline Firms through Platformization

ABSTRACT Advancements in digital technology necessitate a shift from traditional linear buyer-supplier value chains to a network-centric approach facilitated by digital platforms. Despite digital platforms being a dominant model for transformation, limited research has explored the enablers for incumbent pipeline firms to embrace platformization. To address this gap, this study reviews existing literature on digital transformation, identifying nine enablers for digital platformization: changing client behavior, information technology (IT) capabilities development, structural efficiencies, disruptive competitive forces, scope advantages, economic triggers, disruptive third-party technology, creation of autonomous corporate structures, and regulatory compliance. Case studies of platformization in diverse industries are analyzed using the modified total interpretive structural modeling (m-TISM) approach, resulting in a hierarchical model with five levels. This model delineates interrelationships among trigger events, external enablers, internal organizational enablers, process enablers, and outcome drivers. Furthermore, the study highlights that the creation and extraction of value from digital platforms are operationalized through e-business strategies, contributing insights to e-business literature by discussing the implications of these enablers on dimensions such as commerce, collaboration, communication, connection, and computing.

Promoting green growth through identification of sustainable strategies: a hybrid approach

PurposeThe aim of the paper is to rank and analyze the key strategies to sustainable finance adoption in the manufacturing sector using Fuzzy Delphi method (FDM), Interpretive Structural Modeling (ISM) and MICMAC (impact matrix cross-reference multiplication applied to a classification) analysis.Design/methodology/approachThe study develops a novel framework to identify and analyze the mutual relationships among set of sustainable policies using extensive literature survey and experts opinion. Initially, the study found 14 strategies to implement sustainable finance with the help of vast literature. Then, the list of identified factors were screened through Fuzzy Delphi Method (FDM). Based on driving and dependence power, the final list of factors are divided into three categories.FindingsThe study findings reveal that “environmental rules and practices”, “financial incentives, tax reduction and subsidy”, have strongest driving power for promoting sustainable financial system in Pakistani manufacturing sector. Furthermore, “environmental awareness” and “long term vision” are found to be highly influenced by other corresponding elements in a system.Practical implicationsThe ISM approach assists professionals, academics, and managers in identifying and ranking policies in implementing green business techniques. The hierarchical representation of ISM results provides a roadmap for decision-makers to navigate and prioritize factors effectively, facilitating the implementation of strategies that contribute to sustainable growth within organizations.Social implicationsThe study results provide interesting clues regarding green finance policies that provide the foundations, incentives, protections or other provisions that support the ecological conservancy’s mission. Specifically, the findings guide that government must offer research grants to private enterprises, research and development institutions, and universities to promote environmental protection and develop transformative technologies such as waste recycling, renewable energy, carbon capture, and power consumption.Originality/valueThe exploration of strategies for sustainable finance adoption with the help of mixed methodological approach and classification of these strategies on the basis of importance level is a new attempt in the field of manufacturing sector.

Flood Hazard Mitigation at Tarusan Watershed, South Pesisir District, West Sumatera Province

Floods are the most common natural disasters in Indonesia and have enormous potential. This study aims to determine the flood hazard zone and regional arrangement in the Tarusan Watershed, South Pesisir Regency. To determine the flood hazard zone using the GIS approach. The indicators used to determine flood hazard are slope, rainfall, soil type, landform, geology, and land use. Determine the direction of regional arrangement with an Interpretative Structural Modeling (ISM) approach. The results showed that the high flood hazard zone in the Tarusan watershed is about 22% of the total area, the medium index is around 58%, and the low flood hazard index is 20%. The high - hazard zone of flood disasters in the study area is caused by high rainfall and topographic conditions of the Tarusan Watershed. The main priority in the management of flood - hazard areas in the Tarusan Watershed is to find economic alternatives to reduce forest destruction. Increasing the economic value of the community can lead to reduced community activities in carrying out land conversion, especially in forest areas.