Interpretive Structural Modeling Method Research Articles

An Expanded Interpretive Structural Modeling Analysis of the Barriers to Integrated Flood Risk Management Adaptation in Metro Manila

The implementation of integrated flood risk management (IFRM) is still in its infancy in both developed and developing countries, yet some countries have already encountered barriers to IFRM adaptation. The interrelationships between these barriers need to be determined and analyzed systematically, as such an analysis is the groundwork for decision-making when devising solutions to overcome the barriers. Interpretive Structural Modeling (ISM) is a popular and systematic method for analyzing the interrelationship between variables in broad study areas. This study applies the proposed expanded ISM (Ex-ISM) approach to comprehensively analyze the interrelationships between the barriers to IFRM in Metro Manila. Ex-ISM enhances conventional ISM in that the symbolism is modified to explicitly show the contextual interrelationships, the step for hierarchy assignment is simplified, and the diagram shows all of the interrelationships that allow a comprehensive analysis. The results obtained using the Ex-ISM method do not deviate from those yielded by the conventional ISM method, but the Ex-ISM method allows an easy assignment of hierarchy, and it shows not only the direct but also the indirect interrelationships to provide a comprehensive analysis of the relationships between the barriers.

Analyzing the enablers of circular supply chain using Neutrosophic-ISM method: lessons from the Indian apparel industry

PurposeThis research identifies the enablers for implementing circular supply chains (CSCEs) and analyzes interrelationships between them to quantify their driving and dependence power to understand the critical CSCEs.Design/methodology/approachInitially, 10 CSCEs are identified for the Indian apparel industries through an extant literature review and validated using the Delphi method by seeking experts' opinions. The identified CSCEs are subjected to a novel neutrosophic interpretive structural modeling (N-ISM) method to capture the interrelationships between CSCEs and compute the driving and dependence power of CSCEs.FindingsThe findings of the present research work revealed that “supportive legislative framework, awareness of circular economy's potential for revenue gain and availability of trained research and development (R&D) team” are the critical CSCEs that need to be considered while implementing a circular supply chain in apparel industries.Research limitations/implicationsThis study offers insightful implications to guide practitioners in implementing the circular economy in apparel supply chains.Originality/valueThis research work is one of the earlier studies to analyze the enablers for implementing circular supply chains. This study has explored CSCEs in the context of apparel industries. From a methodological perspective, the novel N-ISM method is worth highlighting as the originality of the work.

Structural analysis of factors for revitalizing lena river logistics using ISM method

Currently, inland water transport is the main mode of transport in the Republic of Sakha (Yakutia). The Lena remains the main river connecting Yakutia with the federal transport infrastructure. However, the state of the Republic’s transport infrastructure does not meet the needs of its economy The infrastructure limits the effective realization of the industrial and resource potential and use of the geographical position of the Republic of Sakha. Therefore, to provide an insightful analysis of the factors affecting the logistics of the Lena River, we conducted a detailed analysis of the current problems of the inland waters of the Republic. This article analyzes the logistics of the Lena River and presents an assessment of the problems hindering the process of modernizing the inland water transport of the Republic of Sakha. Analyzing the factors for revitalizing the Lena River logistics through the Interpretative Structural Modeling method revealed the region’s main water transport logistics problems. Through the literature review, 12 key factors affecting the logistics of the Lena River were identified, and interrelationships among them were represented. The results illustrate that inland water transport of the Republic requires the development of transport infrastructure and financial support from the state to implement republican targeted programs. Therefore, this study is important in both academic and practical aspects.

A mixed method for determination of cut-off dates in liner shipping

ABSTRACT Operating with fixed schedules requires coordinating and cooperating with many actors in liner shipping. Therefore, liner operators announce predetermined cut-off dates for each voyage for Sippers to perform cargo-related transactions and send their documents. The shippers complain that the cut-off times are primarily for the operator’s benefit and create a very tight time. However, the operators have trouble that the shippers cannot fulfill the necessary instructions and documents on time. From this point of view, this study aims to offer optimized cut-off determination for liner services and employs a mixed-method approach to evaluate the cut-off process of liner operators. Firstly, a qualitative study was conducted to obtain factors affecting cut-off date determination. Second, the factors affecting cut-off dates were analyzed with the fuzzy Total Interpretive Structural Modelling (TISM) method. Third, a step-by-step shipping process from booking to the vessel’s departure was developed. Moreover, the simulation method was applied with actual data to offer alternative schedules for a liner operator for its two liner services. The results show that even using only the two strongest driving factors determined in the TISM process (TEU capacity of the vessel and number of port calls) improves the cut-off determination simulation performance results by 20%.

Evaluation of Land Use Efficiency in Tehran’s Expansion between 1986 and 2021: Developing an Assessment Framework Using DEMATEL and Interpretive Structural Modeling Methods

This paper aims to reveal the shortcomings of the land use efficiency assessment formula presented in SDG 11.3.1 Indicator and develop a framework that can provide urban planners with a more accurate understanding of the variables influencing and/or influenced by urban expansion. Based on the mentioned formula, Tehran never experienced urban shrinkage between 1986 and 2021, as shown by the relationship between land consumption and population growth. However, the research findings indicate that land allocation patterns have not only decreased most urban services per capita, but have also undermined ecosystem services during this period. In this paper, we propose a new assessment framework by which a dual aspect of urban planning is addressed, namely providing sustainable urban services while protecting natural resources, and using ecosystem services sustainably to support cost–beneficial urbanization. For this purpose, a total of ten mainly repeated contributing variables were collected in the categories of environmental, physical-spatial, and economic–social effects of urban expansion. A questionnaire based on these variables was prepared, and 14 urban planning experts collaborated to classify the variables and identify causal relationships between them. In the following, data obtained from the questionnaires were analyzed using DEMATEL and Interpretive Structural Modeling (ISM) methods to determine which variables influence and/or are influenced by urban expansion (and to what extent). Third-level variables that directly influence urban expansion include transportation (A6), infill development (A7), and entrepreneurship (A10). Spatial justice (A8) and housing and population attraction (A9) were identified as middle-level variables that both affect and are affected by urban expansion. Finally, land surface temperature (A1), air pollution (A2), sewage and waste (A3), water resources (A4), and vegetation (A5) were identified as first-level variables that are mainly affected by urban expansion.

The role of Society 5.0 in achieving sustainable development: a spherical fuzzy set approach.

Society 5.0 promotes the use of artificial intelligence in human life and the return of humanity to the center of the world. Society 5.0 seeks to achieve economic growth while overcoming social and environmental challenges, contributing to the welfare of the global community. The purpose of this study is to explore how digital transformations introduced by Society 5.0 can contribute to the realization of sustainable development? To answer this question, the study primarily used the systematic literature review method to identify the dimensions and indicators that would quantify the role of Society 5.0 in achieving sustainable development. Then, the study utilized the total interpretive structural modeling (TISM) method to construct the conceptual model. Through spherical fuzzy analytical hierarchy process (SF-AHP) and spherical fuzzy decision-making trial and evaluation laboratory (SF-DEMATEL), the importance and influence of the indicators were determined. The results revealed that the most important indicators were "super-smart society" and "implementing circular economy to decrease environmental waste." The novelty of this research can be found in its application of the spherical fuzzy approach to examine the impacts of Society 5.0 smart technologies on achieving sustainable development, by addressing five major dimensions (governmental, economic, social, environmental, and technological). The findings could help managers to more effectively respond to the challenges of sustainable development by relying on Society 5.0.

Interpretive structural modelling of critical success factor for lean product lifecycle management in industry 4.0

The industrial revolution has gone through four revolutions, this fourth one is Industry 4.0 or I4.0, which aims to improve the performance of companies by moving towards digitalization and relying on the internet of things technology IOT and the cyber physical system CPS. Lean-PLM is a system that has become a pillar of Industry 4.0 because of the benefits it brings: productivity improvement, performance, waste reduction. The objective of our study is to examine the correlation between Lean/Industry 4.0 and PLM/I4.0 and to present an implementation model using the ISM (Interpretive Structural Modelling of Critical Success Factor) method of Lean-PLM in Industry 4.0. The results obtained from this research show that Lean can be associated with Industry 4. 0, which gives us Lean 4.0, PLM is a pillar of Industry 4.0 and finally the success of the Lean-PLM model in Industry 4.0 is based on the support and commitment of top management”, “Big Data (BD)”, “Change Management” and “Professional Training and Development (PTD)”.

An Evaluation of Factors Influencing the Resilience of Flood-Affected Communities in China

In recent years, the acceleration of urbanization processes coupled with more frequent extreme weather including more severe flood events, have led to an increase in the complexity of managing community flood resilience. This research presents an empirical study to explore the factors influencing community flood resilience in six communities located in the Hubei Province of China. The study presents the development of a flood resilience evaluation index system, comprising the use of the decision-making trial and evaluation laboratory (DEMATEL) and interpretative structural modeling method (ISM) methods. The results show that the three most important factors affecting the flood resilience capacity of the community are (i) the investment in disaster prevention, (ii) disaster relief capacity and (iii) flood control and drainage capacity. The differences between the six communities were analyzed across four dimensions to reveal the strengths and weaknesses of the communities across these dimensions and in terms of their overall resilience. By analyzing the causal hierarchical relationship that affects community flood resilience, this study helps to enhance community resilience to flood disasters and reduce disaster risk. These findings are conducive to enhancing the sustainable development of urban communities and are expected to provide scientific guidance for community risk management and strategic decision-making.

The ISM Method to Analyze the Relationship between Blockchain Adoption Criteria in University: An Indonesian Case

Referring to the widespread problem of diploma forgery in Indonesian educational institutions as the impetus for UNTIRTA’s latest vision as an “Integrated, Smart, and Green University,” UNTIRTA intends to use blockchain technology to prevent diploma forgery and overcome issues related to existing platforms at UNTIRTA, such as frequent connection interruptions when accessed by a large number of users simultaneously. Before using blockchain technology, UNTIRTA must evaluate several readiness issues. This study presented the interpretative structural modeling (ISM) method to assess the primary preparedness elements for adopting blockchain technology in universities and sought to provide pertinent strategy ideas for UNTIRTA’s blockchain technology application. The results reveal sixteen major parameters that influence the adoption readiness of blockchain technology at UNTIRTA. The primary variables impacting the adoption and deployment of blockchain technology at UNTIRTA are management and employee support and a grasp of the technology. To realize UNTIRTA’s mission as an “Integrated, Smart, and Green University”, the proposed method entails determining an initial agreement in which all stakeholders have a shared understanding and commitment to Blockchain technology implementation at UNTIRTA. The objective of the tactical proposal is to establish each unit’s mission in the blockchain implementation program. The objective of the technical proposal is to construct a planning document that will serve as a coordination tool between the chairman and members, as well as all parties interested in the adoption of Blockchain technology at UNTIRTA.

Presenting a Model for Virtual Education Using Interpretive Structural Modeling Method at Farhangian University of Khorasan Razavi

Objective: The primary goal of this research was to present a model for virtual education using the interpretive structural modeling method at Farhangian University in Khorasan Razavi. Method: The current research methodology was qualitative and applied in nature. Participants included faculty members from Farhangian University in Khorasan Razavi, selected purposively with a sample size of 13 individuals. The research tool was semi-structured interviews, the validity of which was established through face validity, and reliability was determined by an agreement coefficient between coders, resulting in a 0.85 upon re-coding between the researcher and an external coder. Additionally, a researcher-developed questionnaire was designed based on qualitative findings and distributed among the sample members. Data analysis employed coding analysis, and for the initial stage of identifying factors, the interpretive structural modeling (SIM) method was used. Findings: The findings indicated that the virtual education model consists of five levels and priorities, including: Level One: Futuristic Vision; Level Two: Targeted Educational Quality, Measurability, Support Services, Information and Content; Level Three: Accessibility, Knowledge Management, and Flexibility in Education; Level Four: Pedagogical, Technological Factors, and Organizational Factors; and Level Five: Integrated Management. Conclusion: Based on this research, the board of trustees, policymakers, senior managers, and the central university planning organization can work towards improving virtual education at Farhangian University, specifically as a pilot in Farhangian University of Khorasan Razavi. The managers of this academic unit can create conditions to implement the findings of this research to enhance education, particularly virtual education at this university.

Designing a Customer Interaction Model with an Emphasis on Electronic Customer Relationship Management in Digital Banking

Objective: The aim of this research is to design a customer interaction model with an emphasis on electronic customer relationship management in digital banking. Method: This research, in terms of methodology, is qualitative based on grounded theory and in terms of objective, is applied. The participants in the study included experts familiar with the research topic (university professors, bank managers, and marketing managers in public and private banks in Tehran), 12 of whom were selected using purposive sampling. The research tool included semi-structured interviews, the validity of which was confirmed by face validity, and reliability was also calculated with a coefficient of agreement between coders, resulting in a value of 0.83. For data analysis, a three-stage coding method and the level of categorization of factors and components using the Interpretive Structural Modeling (ISM) method were employed. Findings: The results showed that the causal conditions in designing the customer interaction model with an emphasis on electronic customer relationship management in digital banking include infrastructure, brand-related factors, digital banking and information systems, contextual factors including training, customer-related issues and socio-cultural factors, the central phenomenon including brand, digital banking and information systems, intervening factors including motivation and access and application, strategies encompassing management and planning, support and protection, substitution, development of return on investment, and outcomes including relationship management, marketing, performance, and interactions. Conclusion: Financial system and banking planners can use the results of this research to formulate digital banking and improve the quality of banking services.

Designing a self-management model of the career of higher education graduates with a focus on new perspectives career

The present study was conducted with the aim of designing a self-management model of the career path of higher education graduates, focusing on new perspectives on the career path and based on mixed research, which was applied in terms of purpose and descriptive survey in terms of nature and method. The statistical population of the qualitative and quantitative part of the research included all entrepreneurial graduates and professors who are members of the faculty of entrepreneurship faculties of universities of a country, and in the qualitative phase, 35 of them were selected based on the principle of theoretical adequacy and using the Purposive sampling method. The data collection tool in the qualitative part was a semi-structured interview, and in the quantitative part, a researcher-made questionnaire based on the results of the qualitative phase of the research, whose validity was confirmed by using the CVR coefficient and its reliability was confirmed by calculating the inconsistency rate. Qualitative data analysis was done using thematic analysis method and Atlas.ti software, as a result of which 10 main effective factors in career self-management were identified. In the quantitative part, the model was designed in six levels using Matlab software and fuzzy interpretive structural modeling method, in which self-awareness and entrepreneurial self-confidence with the greatest power of guidance was placed as the main effective factor in self-management of the career path in the sixth level of the model. Clarity of goals and expectations was another effective factor that was in the fifth level of the model, and physical dynamics and personal marketing were the variables that were in the fourth level of the model. In the continuation of leveling, the three variables of psychological skills, human skills and adaptation and environmental awareness were placed in the third level, academic knowledge in the second level, and cognitive and information skills in the first level of the model.

Cash Waqf through Islamic Banks

This research aims to identify the priority factors that are barriers to developing the practice of cash waqf through Islamic financial institutions in Indonesia using the Interpretive Structural Modeling (ISM) method. The development of cash waqf through Islamic banks in Indonesia with ISM framework is divided into three criteria: (1) Challenges (aspects) faced in developing cash waqf, (2) Strategy or foundation required within the framework of developing cash waqf, and (3) Stakeholders or actors involved in the development of cash waqf in Indonesia. The result show that the core problems and challenges faced in the development of cash waqf institutions are: System aspect, product, regulation, and information technology. The core strategies or foundations that are needed in the framework of cash waqf development are transparency and accountability of waqf institutions, Quality development of nadzir, and Innovative marketing strategy from waqf institutions. Government and Badan Wakaf Indonesia are stakeholders or actors involved and related to the development of cash waqf in Indonesia.

Flood risk assessment by using an interpretative structural modeling based Bayesian network approach (ISM-BN): An urban-level analysis of Shenzhen, China

With increasingly uncertain environmental conditions under global change, it is rather important for water security management to evaluate the flood risk, which is influenced by the compound effect of severe weather events and strong anthropogenic activities. In this paper, a risk assessment model in the framework of Bayesian network (BN) was proposed through incorporating with the Interpretative Structural Modeling method (ISM), which would produce an integrated ISM-BN model for reliable flood assessments. The ISM is employed to identify the relations among multiple risk factors, and then helps to configure the BN structure to conduct a risk inference. The established model was further demonstrated in Shenzhen city of China to perform an urban-level risk analysis of the flood disaster, and the Enhanced Water Index (EWI) was introduced to derive model parameters for training and verification. The obtained results of risk assessment lead to an accuracy of 76% with the Area Under ROC Curve (AUC) of 0.82, and spatial distribution of risk levels also showed a satisfactory performance. In addition, it was found that the maximum daily rainfall among ten risk factors play a key part in flood occurrence, while the elevation and storm frequency are also sensitive indicators for the study area. Besides, the spatial flood risk map generated under various design rainfall scenarios would contribute to identifying potential areas that are worth paying particular attention. Thus, the developed assessment model would be a useful tool for supporting flood risk governance to achieve reliable urban water security.

Investigating cause-and-effect relationships between supply chain 4.0 technologies

Abstract The developments of the fourth industrial revolution have caused changes in all areas of society, including production. The changes in production caused by the fourth industrial revolution have also resulted in fundamental changes in the supply chain and have converted it to supply chain 4.0. Organisations must be receptive to supply chain 4.0 to maintain their competitive advantage. Therefore, this study aimed to investigate the relationships among supply chain 4.0 technologies so that, by learning and understanding these connections, industries can pave the way for the implementation of these technologies in their supply chains and use them in problem-solving. The literature review was used to identify the supply chain 4.0 technologies, and the Delphi technique was applied to extract them, including the Internet of Things (IoT), cyber-physical systems, cloud computing, big data, blockchain, artificial intelligence, Radio-frequency Identification (RFID), augmented reality, virtual reality, and simulation. The relationships of supply chain 4.0 technologies were examined using the DEMATEL technique and based on interpretive structural modelling (ISM), their deployment map was drawn. The type of technologies was determined using the MICMAC method. The MICMAC analysis found that the artificial intelligence technology is independent and, based on the findings through the DEMATEL technique, this technology is related to simulation, which belongs to the first level of the interpretive structural modelling technique, and IoT, cloud computing, big data, and blockchain technologies, which are at the second level. Based on the ISM method, RFID, virtual reality, augmented reality and simulation technologies are located at the first level; IoT, cyber-physical systems, cloud computing, big data and blockchain technologies are situated in the second level; and artificial intelligence technology belongs to the third level. According to the related literature, few studies have been conducted on the issues of supply chain 4.0 and the technologies that affect it.

CEO Transformational Leadership, Supply Chain Agility and Firm Performance: A TISM Modeling among SMEs

This article aims to present an approach to enhance the firm performance of SMEs by understanding the dynamics between the elements of the transformational leadership style of the CEO and the agility of the supply network. The business environment among SMEs is marked by fierce rivalry, quick change, and tremendous instability. While an agile supply chain is seen as a winning option for manufacturing SMEs, a transformational leadership style of the CEO can be a source of competitive advantage to improve their performance. Thus, an attempt has been made to integrate transformational leadership and supply chain agility elements and delineate their structural relationship using the total interpretive structural modeling method. Results indicate that transformational leaders drive agile initiatives in the supply chain by setting and communicating a vision, encouraging supply chain members to think of innovative solutions for problems, and mentoring them individually to achieve high-performance standards. These practices will make the team members put in extra effort to accomplish the task, thereby establishing a committed and flexible workforce. Conclusions are drawn, and implications are discussed for enhancing firm performance.

Evaluating Enterprise Resource Planning (ERP) Implementation for Sustainable Supply Chain Management

Enterprise Resource Planning (ERP) plays a vital role in an organization’s growth and sustainability in the supply chain. ERP implementations have a mix of critical success factors (CSFs) that are very important. Hence, it is essential to study the CSFs, their mutual influence and their severity in terms of prioritization for the I4.0. The goal of the current study is to identify CSFs for ERP implementations, as well as their interdependence and ranking. The CSFs of ERP deployment were discovered by a thorough analysis of the literature and subsequent input from a group of subject matter experts. Using the interpretive structural modeling (ISM) method, the shortlisted CSFs were modeled, and after that, the matrice d’ impacts croises multiplication appliqué an classement (MICMAC) analysis was used to classify them. The interpretative ranking technique was used to carry out the subsequent prioritization and ranking (IRP). In the present research, the modeling of CSFs for successful ERP implementations was carried out to accomplish much-needed sustainability in the supply chain. The result revealed the three top-ranked CSFs for successful ERP implementations: “Top management support”, “Change management” and “Business process reengineering.” This research can help practicing managers prepare an ERP implementation plan to accomplish sustainability in SCM. Each CSF’s role can be studied in terms of the mutual relationships for its control. This research can also help in prioritizing strategies for optimizing the resources required for ERP implementations.

The Significance of Machine Learning in the Manufacturing Sector: An ISM Approach

Background: Our day-to-day commodities truly depend on the industrial sector, which is expanding at a rapid rate along with the growing population. The production of goods needs to be accurate and rapid. Thus, for the present research, we have incorporated machine-learning (ML) technology in the manufacturing sector (MS). Methods: Through an inclusive study, we identify 11 factors within the research background that could be seen as holding significance for machine learning in the manufacturing sector. An interpretive structural modeling (ISM) method is used, and inputs from experts are applied to establish the relationships. Results: The findings from the ISM model show the ‘order fulfillment factor as the long-term focus and the ‘market demand’ factor as the short-term focus. The results indicate the critical factors that impact the development of machine learning in the manufacturing sector. Conclusions: Our research contributes to the manufacturing sector which aims to incorporate machine learning. Using the ISM model, industries can directly point out their oddities and improve on them for better performance.

The contribution of organizational learning and green human resource management practices to the circular economy: a relational analysis – evidence from manufacturing SMEs (part II)

PurposeCircular economy has emerged as one of the most important approaches to addressing environmental challenges. Organizations have begun to act on their abilities to enhance their sustainability management to enable a circular economy. The role of organizational learning and green human resource management in the transition to a more circular economy remains unknown. The purpose of this study is to identify and analyze the inter-relationship between the factors of organizational learning and green human resource management, and it aims to rank the identified factors of manufacturing small and medium businesses (SMEs) based on their driving and dependency power and to detect the most substantial factors.Design/methodology/approachThis study identified 11 organizational learning and green human resource management (GHRM) factors after conducting a thorough literature analysis and consulting with experts. To investigate the interaction of the indicated factors and to build their structural hierarchy, this study used the total interpretive structural modeling method. Further, Matriced Impact Croises Multiplication Applique (MICMAC) analysis was used to establish each factor’s driving and dependent power.FindingsThis study discovered that factors “Green separation” and “Organizational learning culture” were found to be significant; “Green performance management” and “Green health and safety management” were observed to be extremely reliant on the remaining GHRM factors.Research limitations/implicationsThe recommended framework has been established in the Indian background and is restricted to manufacturing SMEs. Still, the same framework can be applied to other sectors by slightly modifying it. Also, the analysis is based on the experts’ view and this may be biased. The findings of this study will help human resources managers and SME owner-managers clarify the most and least significant factors of organizational learning and GHRM and their relationships, leading to increased awareness of organizational learning and GHRM practices for enlightened environmental performance.Practical implicationsThe proposed framework might facilitate decision-makers and practitioners to comprehend the relations between organizational learning and GHRM factors. This will support SME owner-managers in understanding the influence of one factor on another factor in manufacturing SMEs.Originality/valueUntil now, the protruding interest of researchers has been focused mostly on large manufacturing enterprises. However, manufacturing SMEs, which are much smaller when compared to large manufacturing companies, significantly contribute to the economy as well as environmental pollution. Thus, this study provides a vital contribution to the current literature by determining the suitable relationship between the organizational learning and GHRM components, as no previous studies focused on exploring the same using the total interpretive structural modeling approach in the Indian manufacturing SMEs environment.

Attributes of the Water Supply Program in Soppeng regency, South Sulawesi

Decreasing water availability and increasing water demand have occurred in Soppeng regency, this is due to the potential of surface water as raw water for clean water is increasingly limited. In ensuring the sustainability of the clean water supply program in Soppeng regency, it is necessary to study the water supply using a system approach, so that the water supply in Soppeng regency can be sustainable. This research was conducted with the aim of analyzing the constraints faced, program needs, and institutions that play a role in the supply of clean water in Soppeng regency with the Interpretative Structural Modeling (ISM) method. The results show that for the implementation of the clean water supply program, there are four key elements that need attention: the lack of institutional capacity, weak institutional governance, availability of raw water, and the role of Central Government (relevant ministries).