Interpretive Structural Modelling Approach Research Articles

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.

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.

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.

Exploring Factors Affecting the Sustainability of Islamic Affairs in Malaysia: An Interpretive Structural Modeling (ISM) Approach

Exploring Factors Affecting the Sustainability of Islamic Affairs in Malaysia: An Interpretive Structural Modeling (ISM) Approach

Constructing an Interpretive Structural Model to Unravel the Interconnected Drivers of Teaching Quality in Higher Education

Identifying the primary factors of teaching quality remains a pivotal agenda for informed decision making, strategic planning, and resource allocation. This study builds upon ten key factors derived from previous research and recognizes the inherent complexity within their relationships. Emphasizing the necessity for a structured model, this work employs an interpretive structural modelling (ISM) approach and Matrice d'impacts croisés multiplication appliquée á un classment (MICMAC) analysis for constructing a hierarchical model that delineates the interrelationships among the factors influencing teaching quality. The findings indicate the substantial impact of intrinsic factors, particularly teachers' individual and psychological characteristics, on other factors. Additionally, our analysis highlights the critical role of student composition in enhancing overall teaching quality. These insights significantly contribute to the literature by offering valuable guidance to decision makers for maintaining teaching quality within higher education institutions.

Are we really addressing the roadblocks to adoption of renewable and sustainable energy technologies? Total interpretive structural modeling approach.

Urban areas serve as a vital contribution to the global structural change towards renewable and sustainable energy technologies which also influence climate change. The aim of this paper is to identify the adoption roadblocks to renewable and sustainable urban energy technologies. This research has three parts: a mini-systematic literature study was conducted to identify the most prevalent roadblocks. Using total interpretive structural modeling (ISM), the relationships between the roadblocks and the source of causation were then examined. The roadblocks are classified based on their dependence and driving powers using MICMAC analysis in the third part of this research. The principal results and major conclusions demonstrate that all roadblocks are necessary for renewable and sustainable urban energy technologies. The roadblocks at level I are insufficient infrastructure, lack of coordination among authorities, lack of quality and reliable data and information, and competition with non-renewable technologies; roadblocks in level II are lack of skilled and trained personnel, limited public participation, awareness, and consumer interest, and lack of standardized technology; roadblock in level III is high initial investment cost; and lastly, roadblocks in level IV are lack of subsidies and financial support programs and absence of coherent related policies. Furthermore, as a result of theMICMAC analysis, none of the aforementioned roadblocks are classified as autonomous variables, implying that they are all required. The dependent roadblocks to renewable and sustainable energy technologies are defined as lack of coordination among authorities, lack of information, and competition with non-renewable technologies. Moreover, linkage roadblocks have high dependence and driving powers which are insufficient infrastructure, limited awareness and consumer interest, and lack of standardized technology. Lastly, high initial investment costs, lack of subsidies and financial support programs, absence of coherent related policies, and lack of skilled and trained personnel are the driving roadblocks with high driving power however not dependent.

An analysis of the inhibitors of resilience in the global value chains of multinational enterprises

PurposeThe COVID-19 pandemic has showcased the lack of resilience found in the global value chains (GVCs) of multinational enterprises (MNEs). Existing evidence shows that MNEs have only recently and slowly started recovering and attempting to rebuild the resilience of their GVCs. This paper analyzes the challenges/inhibitors faced by MNEs in building their resilience through their GVCs.Design/methodology/approachA four-stage hybrid model was used to identify the interrelationship among the identified inhibitors and to distinguish the most critical ones by ranking them. In the first stage, we employed a modified total interpretive structural modeling (m-TISM) approach to determine the inter-relationship among the inhibitors. Additionally, we identified the inhibitors' driving power and dependency by performing a matrix multiplication applied to classification (MICMAC) analysis. In the second stage, we employed the Pythagorean fuzzy analytic hierarchy process (PF-AHP) method to determine the weight of the criteria. The next stage followed, in which we used the Pythagorean fuzzy combined compromise solution (PF-CoCoSo) method to rank the inhibitors. Finally, we performed a sensitivity analysis to determine the robustness of the framework we had built based on the criteria and inhibitors.FindingsWe find business sustainability to have the highest importance and managerial governance as the most critical inhibitor hindering the path to resilience. Based on these insights, we derive four research propositions aimed at strengthening the resilience of such GVCs, followed by their implications for theory and practice.Originality/valueOur findings contribute to the extant literature by uncovering key inhibitors that act as barriers to MNEs. We link out our findings with a number of propositions that we derive, which may be considered for implementation by MNEs and could help them endow their GVCs with resilience.

Modeling the relationships among the driving factors of food waste in Indonesian city

Purpose: Food waste in cities has become a pressing issue not only in developed countries but also in developing countries like Indonesia. The main objectives of this study are to (1) identify the relationships among the driving factors of food waste in Indonesian cities by considering the perspective of food industry practitioners and academics and (2) model the relationships among the driving factors of food waste to reduce food waste in Indonesian cities.Design/methodology/approach: The driving factors of food waste were selected from literature reviews and corroborated using in-depth interviews with practitioners and academics. A combination of three methods comprising (1) Decision-Making Trial and Evaluation Laboratory (DEMATEL), (2) Interpretive Structural Modelling (ISM), and Matrice d'Impacts Croisés Multiplication Appliqué un Classement (MICMAC) were used to construct the hierarchical model the relationship among the driving factors of food waste based on their driving power and dependence power.Findings: There are three key players in the food waste chain in urban areas in Indonesia: households, restaurants, supermarkets/markets. Fifteen driver factors on food waste based on the supplier-input-process-output-customer (SIPOC) framework were identified. The relationship among the driving factors of food waste was constructed in a hierarchical structure of food waste in Indonesian cities. With this, strategic action is formulated to reduce food waste.Practical implications: The proposed model of the driving factors of food waste can inform the city government on how to manage food waste. Likewise, the findings can assist Indonesian households, restaurants, and markets/supermarkets in minimizing their food waste. The ISM approach's hierarchical structure allows practitioners to better identify the objectives for reducing food waste in Indonesian cities.Originality/value: Previous studies have not examined and specifically modeled the relationships among the driving factors of food waste in Indonesian cities with three main players, i.e., households, restaurants, and supermarkets or traditional markets.

An improved WINGS-ISM approach with consensus model in group decision-making for addressing critical success factors of collaborative emergency management

Since the variety and destructiveness of unexpected natural disasters and health emergencies, and the weakness of emergency systems around the world, studies on collaborative emergency management (CEM) are receiving increasingly attention recently. The existing literature has proved that with respect to the constraint of limited resources, it’s usually unrealistic for CEM practitioners to push forward all influential factors that affect the comprehensive performance of CEM simultaneously. Thus, identifying the most critical success factors (CSFs) is of great significance to promote the effectiveness of CEM practices. To achieve this intention, we proposed a novel multi-granularity extended probabilistic linguistic weighted influence nonlinear gauge system and interpretative structural modeling (WINGS-ISM) approach with a consensus model optimized by the convolutional neural network algorithm. The new technique specializes in addressing the CSFs of episodes involving CEM characterized by the combination of uncertainty and complexity in group decision-making process. To validate its feasibility and robustness, we mainly investigate 10 CSFs to conduct an illustrative CEM case, the result shows that ‘Applicable emergency response plan and regulations’, ‘Government unity of leadership and coordination’ and ‘Reasonable organizational structure and clear functions’ are identified out of 10 influential factors. Besides, the cause-effect and hierarchal relationship digraphs indicate that the CSFs of CEM are interconnected, and this finding can support CEM practitioners to devote more attention to the most important factors, which may yield more improvements in CEM practices. Finally, some research implications are provided for better improving the effectiveness of CEM practices based on the findings of this study.

Modeling the Strategic Enablers of Financial Sustainability in Saudi Higher Education Institutions Using an Integrated Decision-Making Trial and Evaluation Laboratory–Interpretive Structural Modeling Approach

Ensuring financial sustainability is paramount for higher education institutions (HEIs) to maintain financial viability and accomplish their strategic objectives by efficiently managing and utilizing resources. Studying strategic enablers’ interconnections and influences on each other is essential to forming a profound understanding and guiding the execution of initiatives linked to achieving financial sustainability plans. The main objective of this research study is to construct a model and analyze the strategic enablers of financial sustainability in HEIs and their associated dimensions. An integrated modeling approach was followed based on the Decision-Making Trial and Evaluation Laboratory (DEMATEL) and Interpretive Structural Modeling (ISM) methods. Input data collected from experts with specialist experience in financial sustainability in HEIs were used in the modeling. The overarching finding is that starting with the development of regulations and legislation-related systems leads to good governance practices, enabling the achievement of financial sustainability in HEIs. The developed model unpacks the complex relationships among the enablers and their dimensions. It reveals their cause-and-effect relationship classifications, ranks based on relative importance weights, dependence and driving powers classifications, relationship directions, and interpretive structure. It provides an overarching view of the interconnected network that acts as a roadmap to achieving financial sustainability in HEIs.

Examining interdependencies among solution dimensions for sustainable development in SMEs based on Industry 4.0 concept

PurposeIn the context of promoting sustainable development in SMEs, the present study aims to investigate the relationship among solution dimensions based on the Industry 4.0 (I4.0) concept.Design/methodology/approachThe study employs a comprehensive methodology that includes a systematic literature review, workshop, grounded theory and interpretive structural modeling. Various dimensions concerning I4.0 sustainability are tested and evaluated using a questionnaire design followed by hypothesis formulation. Further, grounded theory is used to extract the key solution dimensions that capture the essence of I4.0 implementation in SMEs. Finally, the solution dimensions for I4.0 sustainability are modeled using the ISM approach to understand the structural interdependencies among them, and Matrice d'Impacts Croisés Multiplication Applied to a Classification (MICMAC) analysis is done to understand the driving and dependence power among these dimensions.FindingsThe study identified 14 solution dimensions for the implementation of I4.0 in SMEs for sustainable development. Out of the 14 solution dimensions, human resource training programs (D4) appear at level 11, followed by top management commitment (D1), strategic collaborations (D3) and coordination among key stakeholders (D5) at level 2 in the hierarchical interpretive structural modeling (ISM) model. Also, these dimensions have an effect size of more than 0.50 which indicates a substantial correlation between the sustainability dimensions and Industry 4.0 implementation in SMEs.Originality/valueThe study contributes to the overall goal of fostering sustainability within the SME sector, which can pave the way for various stakeholders for the successful implementation of I4.0 sustainable solution dimensions.

Barriers to green procurement of the Iranian construction industry: an interpretive structural modeling approach

Barriers to green procurement of the Iranian construction industry: an interpretive structural modeling approach

Designing a Human Resource Productivity Model for the Deaf Sports Federation: A Combined Delphi-Fuzzy and Interpretive Structural Modeling Approach

Objective: The objective of this study was to design a human resource productivity model for the Deaf Sports Federation using a combined Delphi-Fuzzy and Interpretive Structural Modeling approach. Methods and Materials: The methodology of this research was mixed (qualitative and quantitative). Participants included managers and officials of committees within the Deaf Sports Federation of the Islamic Republic of Iran and elites in deaf sports, including coaches, referees, and athletes. The selection of these individuals was purposeful, based on criteria of expertise and experience, representation, diversity, and cooperation potential, with 18 individuals chosen. Data collection tools were a 41-question questionnaire and a 17x17 dimensional matrix, both validated for reliability and validity. Data analysis was conducted using Delphi-Fuzzy and subsequently Interpretive Structural Modeling. It is noteworthy that for these analyses, Excel macros and the SmartISM web program were utilized respectively. Results: Findings identified 17 determinant factors related to human resource productivity in the Deaf Sports Federation, which were categorized into five levels based on interpretive structural analysis, forming a hierarchical relationship model that indicates the fundamental factors in optimizing human resources in the Deaf Sports Federation are the alignment of authority-responsibility and organizational culture, which ultimately lead to an individual’s perception of their role. Conclusions: Accordingly, in planning to enhance human resource productivity in the Deaf Sports Federation, the initial step should involve establishing a balance of authority-responsibility and promoting values that assist employees in understanding their roles.