Interpretive Structural Modelling Approach Research Articles

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.

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.

Why small business owners get demotivated? Modeling “unwillingness to grow” using ISM approach

Purpose Even after establishing their business successfully, many business owners get demotivated, and it leads to unwillingness to grow. This study aims to propose a comprehensive model that represents interrelationships among various personal factors affecting “unwillingness to grow.” Design/methodology/approach The personal factors for unwillingness to grow were identified by extant literature, and expert interviews were conducted to establish the contextual relationships among these factors. The interrelationships among the filtered variables have been done using interpretive structural modeling (ISM) and MICMAC analysis was done to determine the importance of each factor in influencing “unwillingness to grow.” Findings In total, 30 personal attributes were identified from previous literature, out of which 15 were selected for the final study. The result identifies 7 variables having a strong impact on “unwillingness to grow.” These attributes are “absence of strong network,” “lack of vision,” “lack of proactiveness,” “reluctance to involve external consultants,” “absence of/small founding team,” “lack of ambition” and “improper attitude.” Originality/value The research attempts to create a bricolage of all the important personal factors affecting “unwillingness to grow.” Previous researches have used few attributes, but with the help of ISM, a graphical modeling technique, it became possible to draw interrelationship between 15 attributes. Further, with the help of MICMAC, the importance of each attribute was determined.

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.

Designing a Constructive Leadership Implementation Model in the Higher Education System Using an Interpretive Structural Modeling (ISM) Approach

The present study designed a model for the implementation of constructive leadership in the higher education system using an interpretive structural modeling approach. This study was applied in terms of aim and qualitative type of descriptive in terms of method of implementation. The statistical population of the study included experts in educational and constructive leadership in higher education at Urmia University. Based on the principle of random sampling, 7 of them were selected as a sample using convenience and snowball sampling methods. A semi-structured interview with experts whose questions were designed based on the theoretical foundations of constructive leadership in higher education with the help of professors was used as the study tool. The validity of the results was examined and confirmed by the triangulation method. Also, its face validity was confirmed by the opinions of experts who were not members of the study, and its reliability was calculated at 0.83 using the inter-coder coefficient of the agreement method. The data obtained from semi-structured interviews were analyzed with open, axial, and selective coding based on grounded theory in MAXQDA software. The results showed that the model of constructive leadership in higher education based on grounded theory included 12 components and 9 dimensions. The category of causal conditions included two dimensions of the necessity of constructive management (with two components of knowledge management and organizational innovation) and organizational culture (with two components of collaborative management and innovative atmosphere). The category of contextual conditions included two dimensions of management maturity (with the component of evaluating and applying policies for constructive management) and the system of fostering change and transformation (with the component of establishing relationships with aligned people and organizations). The category of intervening conditions included the dimension of competition with the surrounding environment and increasing progress (with the component of planning and paying attention to facilities). The category of strategies included two dimensions having facilities and requirements (with the component of financing and equipment) and responsibility and cooperation (with the components of empathy and public desire). Finally, the category of implications included two dimensions of academic development (with 2 components of individual competence development and university development) and social development (with the component of gaining public trust).

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.