Interpretive Structural Modeling Technique Research Articles

An aquaculture risk model to understand the causes and consequences of Atlantic Salmon mass mortality events: A review

AbstractMass mortality events (MMEs) are defined as the death of large numbers of fish over a short period of time. These events can result in catastrophic losses to the Atlantic salmon aquaculture industry and the local economy. However, they are challenging to understand because of their relative infrequency and the high number of potential factors involved. As a result, the causes and consequences of MMEs in Atlantic salmon aquaculture are not well understood. In this study, we developed a structural network of causal risk factors for MMEs for aquaculture and the communities that depend on Atlantic salmon aquaculture. Using the Interpretive Structural Modeling (ISM) technique, we analysed the causes of Atlantic salmon mass mortalities due to environmental (abiotic), biological (biotic) and nutritional risk factors. The consequences of MMEs were also assessed for the occupational health and safety of aquaculture workers and their implications for the livelihoods of local communities. This structural network deepens our understanding of MMEs and points to management actions and interventions that can help mitigate mass mortalities. MMEs are typically not the result of a single risk factor but are caused by the systematic interaction of risk factors related to the environment, fish diseases, feeding/nutrition and cage‐site management. Results also indicate that considerations of health and safety risk, through pre‐ and post‐event risk assessments, may help to minimize workplace injuries and eliminate potential risks of human fatalities. Company and government‐assisted socio‐economic measures could help mitigate post‐mass mortality impacts. Appropriate and timely management actions may help reduce MMEs at Atlantic salmon cage sites and minimize the physical and social vulnerabilities of workers and local communities.

Breaking down barriers and building up facilitators of lecture free curriculum in medical education: An interpretive structural modeling

Introduction The field of medical education has seen a growing interest in lecture free curriculum. However, it comes with its own set of challenges and obstacles. In this article, we aim to identify the prerequisites, facilitators, challenges, and barriers of lecture-free curriculum in medical education and examine their interrelationships using interpretive structural modeling (ISM) technique. Methods In this mixed-method study initially, we performed a scoping review and semi-structured interviews and determined the main prerequisites, facilitators, challenges, and barriers of lecture-free curriculum in medical education using qualitative content analysis approach. The interrelationships among these components were investigated using ISM. Therefore, self-interactive structural matrices were formed, initial and final reachability matrices were achieved, and MICMAC analysis was conducted to classify the factors. Results Finally, two ISM models of prerequisites and facilitators with 27 factors in 10 levels and challenges and obstacles with 25 factors in eight levels were developed. Each of the models was divided into three parts: key, strategic, and dependent factors. ‘Providing relevant evidence regarding lecture free curriculum’ emerged as the most important prerequisite and facilitator, and ‘insufficient support from the university’ was identified as the most critical barrier and challenge. Conclusions The study highlights the significant importance of lecture-free curriculum in medical education and provides insights into its prerequisites, facilitators, challenges, and barriers. The findings can be utilized by educational managers and decision-makers to implement necessary changes in the design and implementation of lecture-free in medical education, leading to more effective improvements in the quality and success of education.

Critical factors for capacity building of NGOs working in the intellectual disability sector in India: a TISM-MICMAC approach

Purpose This study aims to identify the critical factors contributing to India-based non-governmental organizations (NGOs) capacity building and value creation for beneficiaries. Design/methodology/approach A total interpretive structural modeling technique has been used to develop a hierarchical model of critical factors and understand their direct and indirect interrelationships. The driving force and dependence force of these factors were determined by using cross-impact matrix multiplication applied to classification analysis. Findings This study identifies 12 critical factors influencing NGO capacity building in India’s intellectual disability sector across four dimensions. Internal organizational capabilities include infrastructure, staff qualifications, fundraising, vocational activities and technical resources. Second, coordination and stakeholder engagement highlight government and agency collaboration, dedicated board members and stakeholder involvement. Third, adaptability and responsiveness emphasize adjusting to external trends and seizing opportunities. Finally, impact and value creation emphasis on improving value for persons with disabilities (PWDs). Practical implications The findings of this study have practical implications for Indian NGOs working for PWDs. The study provides NGOs with a structural model for improving organizational capacity by identifying and categorizing critical factors into the strategic model. Originality/value There is a scarcity of literature on capacity building for disability-focused NGOs in India. This study seeks to identify critical factors and develop a hierarchical model of those factors to assist policymakers in India in building the capacity of NGOs.

Factors Impacting Women Gaining Leadership Roles in the Jordanian Construction Sector: Architects and Civil Engineers

The persistent underrepresentation of women in leadership positions within the construction industry remains a global concern. In Jordan, despite comprising 60.45% and 22.4% of the total workforce of architects and civil engineers, respectively, women’s contribution to management roles is significantly low. Therefore, there is an urgent necessity to examine the factors hindering women’s advancement in the construction sector and their ability to attain leadership positions. This research aims to provide an overview of the current situation in Jordan, focusing specifically on the architectural and civil engineering professions. It presents findings from a desktop study, a survey questionnaire, and focus groups. The Severity Index (SI) formula is utilised to identify critical barriers in the Jordanian context, derived from both the literature review and questionnaire responses. Additionally, the Interpretive Structural Modelling (ISM) technique is employed to establish a hierarchy of critical barriers and analyse their interrelationships. The study reveals that the obstacles impeding women from assuming leadership roles in the Jordanian construction sector primarily stem from 20 critical barriers categorised across 11 levels in ISM. Notably, the lack of childcare programmes is identified as a fundamental barrier at the lower level, while informal networks formed by men emerge as the highest-rated barrier at level 11. Addressing and mitigating these challenges is crucial to facilitating women’s progression into leadership positions within the sector and is anticipated to contribute significantly to addressing the growing complexity of modern construction projects.

Establishing the relationship between the strategic factors influencing blockchain technology deployment for achieving SDG and ESG objectives during infrastructure development: an ISM-MICMAC approach

PurposeImplementing blockchain in sustainable development goals (SDGs) and environmental, social and governance (ESG)-aligned infrastructure development involves intricate strategic factors. Despite technological advancements, a significant research gap persists, particularly in emerging economies. This study aims to address the challenges related to SDGs and ESG objectives during infrastructure delivery remain problematic, identifying and evaluating critical strategic factors for successful blockchain implementation.Design/methodology/approachThis study employs a three-stage methodology. Initially, 13 strategic factors are identified through a literature review and validated by conducting semi-structured interviews with six experts. In the second stage, the data were collected from nine additional experts. In the final stage, the collected data undergoes analysis using interpretive structural modeling (ISM)–cross-impact matrix multiplication applied to classification (MICMAC), aiming to identify and evaluate the independent and dependent powers of strategic factors driving blockchain implementation in infrastructure development for SDGs and ESG objectives.FindingsThe study’s findings highlight three significant independent factors crucial for successfully integrating blockchain technology (BT) into infrastructure development for SDGs and ESG goals: data security (F4), identity management (F8) and supply chain management (F7). The study unravels these factors, hierarchical relationships and dependencies by applying the MICMAC and ISM techniques, emphasizing their interconnectedness.Originality/valueThis study highlights critical strategic factors for successful blockchain integration in SDG and ESG-aligned infrastructure development, offering insights for policymakers and practitioners while emphasizing the importance of training and infrastructure support in advancing sustainable practices.

Factors influencing competitive advantage in start-ups operations 4.0

Purpose The ability of a business to outperform its rivals is known as its competitive edge, and it presents special difficulties in the context of the “digital revolution,” or the fourth industrial revolution. To obtain a competitive edge in the startup operations 4.0 era, this study aims to examine the organizational, technological and competence-related challenges presented by Industry 4.0. It does this by concentrating on the tools, competencies, methods, approaches, tools and strategies that are crucial. Using the Total Interpretive Structural Modeling (TISM) technique, the goal is to find, analyze and classify enablers for startup operations 4.0. Design/methodology/approach A closed-ended questionnaire and planned interviews were used in the data collection process. In startup operations 4.0, the cross-impact matrix multiplication applied to classification method is used to rank and categorize competitive advantage factors, whereas the TISM technique is used to analyze how components interact. Findings The study highlights the critical significance of the “Internet of Things (IoT),” “information technologies,” “technological platforms,” “employee empowerment,” “augmented reality (AR)” and “operational technologies” in its identification of 12 enablers for startup operations 4.0. Research limitations/implications The main focus of the study is on the variables that affect startup operations 4.0’s competitive advantage. Practical implications Academics and important stakeholders can better understand the factors influencing competitive advantage in startup operations 4.0 with the help of this research. Originality/value Large businesses have been profoundly impacted by Industry 4.0 principles; however, startup operations 4.0’s competitive advantage has not received as much attention. This paper offers a fresh take on the concept of competitive advantage in startup operations 4.0 research.

Using a comprehensive DEMATEL-ISM-MICMAC and importance–performance analysis to study sustainable service quality features

PurposeTo gain and differentiate competitive advantage, the sustainable service quality is a determining factor that railway companies can use. The purpose of this study is to identify both the importance and performance of rail transportation service quality factors in a case study as well as determine the most influential quality features.Design/methodology/approachA comprehensive approach namely importance–performance analysis (IPA) technique and decision-making trail and evaluation laboratory (DEMATEL), and interpretive structural modeling (ISM) and Matriced’ Impacts Croisés Multiplication Appliquée á un Classement (MICMAC) techniques was utilized.FindingsThe relative position of each attribute is specified on the IPA matrix proposing four strategies of concentrate here, keep up the good work, low priority and possible overkill. This study reveals that attributes of “the company cares about having a good society” are the most influential factor, and “having good business relations with shareholders” is the most permeable factor. Actually, consumers pay attention to how companies act toward society and maintain communication with shareholders. Through ISM technique and by summing the row and column of the consistency matrix, the attributes were partitioned into four levels. Also, MICMAC analysis identified the four clusters of linkage, independent, autonomous and dependent status of the attributes in terms of the driving power and dependence power.Research limitations/implicationsDue to the nature of single case study methodology, caution should be taken into consideration regarding the generazability of the obtained results.Originality/valueThe hybrid DEMATEL-ISM technique is used to analyze service quality factors in Iran’s transportation industry, which can be utilized in other industries as well as other countries.

Identification and assessment of risk factors in offshore wind-integrated hydrogen production system

Green hydrogen (H2) has received increasing attention as a potential fuel to decarbonize hard-to-electrify industries and support renewables’ growth. Compared to steam methane reforming (SMR), water electrolysis can produce green hydrogen with substantially less emissions. Efforts are ongoing worldwide to develop offshore wind-integrated green hydrogen production plants, particularly in regions with abundant water resources and favorable wind conditions to offset the external energy requirement during H2 production through water electrolysis. However, in the current literature, limited focus has been given to identifying the associated risk factors to establish such plants. To address this issue, the current work conducts a comprehensive examination of technology, economics, safety, and security-related risk factors. A thorough investigation has been performed to trace the risk factors, unraveling their contextual interrelationships, and where possible, quantitatively analyze their impact. A total of 40 risk factors were identified and modelled using the interpretive structural modelling (ISM) technique to visualize their interrelations. Control-related risk factors are found to be the most pivotal in the context of overall project failure. This research serves as a key reference for decision-makers to establish offshore wind-integrated water electrolysis-based hydrogen production facilities, ensuring due consideration for the interdependent risk factors involved in the process.

Comprehensive factor analysis and risk quantification study of fall from height accidents

Working at heights poses frequent and significant risks, demanding scientific approaches for investigating fall-from-height (FFH) incidents and proposing preventive measures to enhance building safety. Nevertheless, ongoing research on analyzing the causal factors behind fall-from-height accidents lacks a comprehensive qualitative and quantitative assessment of the interplay between these factors. To bridge this gap, this study introduces an integrated risk analysis model. Utilizing incident reports and leveraging the multi-case rootedness theory, the model initially identifies influential elements. Subsequently, employing the Grey Decision Making Laboratory (Grey-DEMATEL) and Interpretive Structural Modeling (ISM) techniques, a hierarchical network is constructed, followed by the transformation of this hierarchical network model into a Bayesian Network (BN) model using GeNie2.0 software. Ultimately, the study was based on data from 420 accident cases and analyzed the causes and diagnosis of the accidents. The findings indicate that A5 (Low-security awareness) is the most significant factor contributing to falls from great heights and that the connection between the components is dynamic and non-linear rather than simply independent and linear. Furthermore, the study established a likelihood of occurrence of such incidents of up to 57 % and ranked the probability of occurrence of each contributing component in the case of a fall from height. This study presents a scientifically valid method for analyzing fall-from-height accidents. Experimental results confirm the model's applicability, empowering contractors to improve safety management by accessing precise risk information and prioritizing preventive measures against interrelated accidents. The model facilitates informed decision-making for contractors to effectively mitigate fall-from-height risks and establish a safer working environment.

Barriers to Building Information Modeling (BIM) Implementation in Pakistan during The Post-Flood Era: An Interpretive Structural Modelling (ISM) Approach

Pakistan experienced one of the most severe floods recently in 2022. The post-flood eras have faced huge destruction in economic loss and infrastructure disaster. Effective infrastructure is essential in the development of a region. Pakistan is a developing country having less availability of resources and a lack of proper planning to cater to natural hazards and faces huge destruction in flood-hit areas. The reasons behind these destructions are unending, some of which have been identified through past literature. Building information modelling is thus a foundation of digital transformation in the infrastructure or architecture, engineering, and the Architecture, engineering, and construction industry. Incorporating BIM in the renovation and rebuilding of infrastructure is a prominent solution to prevent the post-flood era from devastation. This study aims to determine the barriers to the implementation of BIM. After reviewing the literature, several barriers have been identified, and 13 of them have been used in this study as strong hurdles in the implementation of BIM in the post-flood areas of Pakistan. The ISM technique (interpretive structure modelling) has been used to draw results regarding the identified barriers. The results indicated these barriers of different levels corresponding to their importance. This study is a great addition to the growing body of literature regarding flood adverse effects and a practical guideline to the AEC industry where architecture, constructors, and other experts in this field can take great assistance towards lessening and overcoming the barriers identified to implementing BIM.

Economic Benefits and Governance of Guiding Barrier Fishing Gear in White-Spotted Spinefoot Fish Fishing Activities (Siganus canaliculatus, Park 1797) In Bontang City Waters

Guiding barrier fishing gear has been used in recent years in the mangrove, seagrass, and coral ecosystem areas of Bontang City. In previous studies, the main target, white-spotted spinefoot fish, has depreciated and degraded as a result of overfishing. This study calculates the economic benefits and attempts to analyze the management policy of guiding barrier fishing gear to overcome the depreciation and degradation problems. To calculate the economic benefits, the fisheries production approach was used, while the policy analysis used the interpretive structural model technique. During the peak season of white-spotted spinefoot fish, the average fisherman earns up to IDR400,750 per day, with a minimum of IDR103,000 and a maximum of IDR1,904,000. The optimal fishing period is nine months, after which fishermen will stop fishing in Ramadan, August, and September. There are six guiding barrier fishing gear management policies, namely: 1) open and close systems at the installation site; 2) increase the mesh size used; 3) reduce the number; 4) moratorium on new installations; 5) limit the number of owners for each fisherman; and 6) regulate the distance between guiding barrier fishing gear. Of the six policy alternatives, the top priority is to increase the mesh size used.

Examining the facilitators of I4.0 practices to attain stakeholders’ collaboration: a circular perspective

ABSTRACT The fourth industrial revolution (I4.0) has changed the traditional business model, bringing various benefits, including increased efficiency and productivity in organizations. However, to attain success in I4.0 practices requires collaboration from various stakeholders. This study objectives to identify the facilitators of I4.0 practices that can lead to successful collaboration among stakeholders from a circular perspective. An extensive literature review is performed to identify 14 potential facilitators. Further, the study adopts a mixed methodology of Best-Worst Method (BWM) and Interpretive Structural Modeling (ISM) to analyze the interconnectedness among the identified facilitators. BWM method was used to determine the relative importance of the identified facilitators, while ISM technique was used to determine the relationships between the facilitators of I4.0 practices. The findings from the study reveal that to strengthen stakeholder collaboration, organizations need to focus more on training and capacity-building programs and create more opportunities for technology exchange.

Critical success factors of heritage building maintenance management: An ISM-MICMAC analysis

To improve the functionality of heritage buildings, modern facility management (FM) practices have been increasingly adopted in heritage building maintenance management (HBMM). To achieve effective FM operations in HBMM, it is essential to identify the critical success factors (CSFs) and understand their relationships. Since this is an underexplored area, a study was initiated to establish a hierarchical structure of the CSFs and ascertain their influence on each other. Under the study, HBMM experts were invited to assess the interrelationships of the CSFs through an online survey. Then, an interpretative structural modeling (ISM) technique was used to establish the envisaged hierarchical structure. Finally, Matrice d'Impacts Croisés Multiplication Appliqués à un Classement (MICMAC) analysis was used to classify the CSFs into four clusters based on their dependence and driving powers. From the ISM analysis, a hierarchical structure composed of seven levels was resulted, with the CSFs at the bottom of the hierarchy belonging to the independent categories with strong driving power but weak dependence power. Achieving these CSFs, which will drive the realization of other CSFs, warrant particular attention from HBMM practitioners. With an integrated ISM – MICMAC model developed, this study contributes to knowledge by establishing the hierarchy and interactions among the CSFs. The CSFs classification also serves as a guide for HBMM practitioners in understanding the operational dynamics of the CSFs and prioritizing their importance. The approach of this study, which is novel in the HBMM research domain, also forms a fertile foundation for future studies in this field.

Developing a model of technological innovation for export development in developing countries

It is crucial for companies to develop a competitive advantage in today's competitive business environment. Technological innovation is one of the most effective ways for companies to achieve this advantage and enhance their competitiveness. Therefore, identifying the most important dimensions of technological innovation is key for managers and decision-makers in order to achieve organizational goals, which in fact, reveals its high importance. In this paper, we develop a model of how technological innovation impacts export development in developing countries. At present, the process of globalization, especially the development of exports, has a special place. In this paper, based on the rigorous literature review, eleven main dimensions of technological innovation were obtained. The relationships between system elements were determined using the Interpretive Structural Model (ISM) technique, and the final model with four levels was extracted. The factors in the last level are the most effective, and the factors in the first level are the most influential. These factors are considered the basis of the model. According to research findings, knowledge management has the most impact, and manufacturing capability, service Innovation, marketing, and learning process are the most impressionable. Finally, based on the Mick Mac technique, the factors are classified based on the degree of dependence and influence. Since this method is under the opinions of experts, the opinions of 28 industry experts and university professors have been used. We have contributed to the understanding of the complex relationships among different factors and variables through our research by providing a structured and systematic approach. Policymakers and other stakeholders can use our model to propose ways to promote economic growth and development through technological innovation and exports. We believe that our findings have important implications for the field of innovation and international business research.

Implementing Area Business Continuity Management for Large-Scale Disaster: A Total Interpretive Structural Modeling Approach

A large-scale disaster striking a fundamental infrastructure can disrupt the entire business area. Hence, Area Business Continuity Management (Area-BCM) is proposed to bring together stakeholders in the same area who aim to minimize economic losses and impacts due to a disaster. Its distinctive features consider public–private partnerships, critical external resources, and scalability of risk management. However, Area-BCM is still a long way from being successful as many challenges are found. This study aimed to build a model of success factors and analyze relationships among factors for Area-BCM implementation. The total interpretive structural modeling technique was utilized to construct a hierarchical model. Interviews and questionnaire surveys were performed for data collection. A process-automated tool was used to ensure accuracy and eliminate complicated calculations. The results indicate the foundation factors and critical suggestions to be grounded for success. The outstanding findings are the interpreted interrelationships in the final model. Moreover, cross-impact matrix multiplication applied to classification approach categorizes factors into four groups based on driving and dependence powers. The outcomes provide strong implications for Area-BCM practitioners or executors, helping them prioritize attention and prepare suitable strategies for successful implementation.

Unravelling the enablers of Industry 4.0 in Indian automobile industry amid COVID-19: an integrated TISM and fuzzy MICMAC approach

PurposeThis study aims to identify the key enablers for the adoption of Industry 4.0 (I4.0) in the automobile industry of India, which has been severely impacted by COVID-19. Adopting I4.0 will provide organizations greater flexibility and resilience during the COVID-19 pandemic.Design/methodology/approachBased on the literature review and experts’ opinions, 21 enablers were identified. Further, contextual relationships among the identified factors and a hierarchical digraph was developed by using the total interpretive structural modelling (TISM) technique. Finally, fuzzy cross-impact matrix multiplication applied to classification (MICMAC) analysis was conducted to classify the enablers into different categories based on their dependence and driving power.FindingsThe results indicate that top management support, clarity on government policy, strategic vision on I4.0 and development of new industrial policy are the most influential factors, with the highest driving power placed at the bottom of the TISM hierarchical model. Furthermore, agile workforce, smart HR practices and IT standardization and security are identified as linkage enablers with the most driving and dependency power.Practical implicationsThe hierarchical TISM model and fuzzy MICMAC approach provide a comprehensive understanding of the I4.0 implementation process through a visual, logical structure to the managers. It will help the researchers and practitioners understand the contextual relationship among various enablers in fostering the I4.0 adoption process and digital reorganization in the automobile industry during the COVID-19 pandemic.Originality/valueThis study provides a holistic TISM hierarchical framework on I4.0 adoption that will elevate the next maturity level of innovation adoption and may act as a blueprint for automobile industries during the COVID-19 pandemic.

Investigation of barriers and mitigation strategies to blockchain technology implementation in construction industry: an interpretive structural modeling approach.

Blockchain technology has emerged as a promising solution for enhancing transparency, efficiency, and security in various industries, including construction. However, implementing blockchain in the construction industry faces several barriers that hinder its widespread adoption. To fill this gap, this study is aimed at identifying and discussing the key barriers to implementing blockchain in the construction industry. The study employs a four-phase methodology. In the first phase, barriers are identified through a comprehensive literature review and supplemented with semi-structured interviews with different stakeholders, identifying critical barriers. The second phase involves data collection from ten construction experts, while the third phase utilizes the interpretive structural modeling (ISM) technique for data analysis. In the fourth phase, ten effective strategies are formulated to tackle the identified barriers and their interdependencies. The results reveal the overall structure of barriers and classify them into four groups based on driving and dependence power using the cross-impact matrix multiplication applied to the classification (MICMAC) technique. The identified barriers include a lack of collaboration in consortium formation, insufficient capacity and performance, and regulatory uncertainty, which hinders blockchain implementation in the construction industry. The research findings provide valuable information for policymakers on the overall structure with barriers and implementation in India and other countries with similar situations. Additionally, the management implications of the results were analyzed to facilitate the effective implementation of measures to overcome the obstacles and increase the level of blockchain adoption in the construction industry.

Using DEMATEL and ISM for Designing Green Public Policies Based on the System of Systems Approach

In this paper, we propose a novel approach to the development of green public policies. We emphasize the significance of the system of systems (SoSs) methodology, which concentrates on understanding and managing complex systems by contemplating their interdependencies and interactions as a single integrated system. Based on this perspective, we consider green public policy as a system interacting with the energy, health, pollutants, and economic systems of the SoSs. As a method of systematic structural analysis, we use both decision-making trial and evaluation laboratory (DEMATEL) and interpretive structural modeling (ISM) techniques to understand the relationships between the systems listed above. We provide a literature review on the application of these soft operation research (SOR) techniques. We note that SOR methods are suitable for the formulation of effective public policies. Using an example, we demonstrate the primary advantage of DEMATEL and ISM, which is the establishment of easily comprehendible causal relationships between the systems in the SoSs.

Modeling challenges affecting the performance of major ports of India

PurposeDespite several initiatives taken by government of India since 2013 to improve the performance of major ports, growth was not as anticipated. Hence, there is a need to understand the performance of these major ports during 2013–2020 and to identify the critical challenges that affect their performance. Design/methodology/approachPerformance analysis was conducted using Malmquist productivity index (MPI) and critical challenges were identified using interpretive structural modelling (ISM) technique as well as the cross-impact matrix multiplication (MICMAC). FindingsTen major ports in terms of operational, 12 ports in terms of service quality, and six ports in terms of financial performance have been categorised as high performers, based on the MPI values. 19 challenges affecting the performance were identified in an eight layered ISM model. Research limitationsThis research is limited to major ports of India and does not cover the non-major ports of India due to unavailability of data Practical implicationsThis study will enable the port decision-makers to identify the ports which are high performers in terms of operational, service quality, and financial performance, and thereby the best practices followed across can be replicated. Originality/valueThis study explored the multi dimensions of performance of Major ports of India and there was no such study in the past. Despite the existence of performance studies in the literature, none of them explored the challenges faced by the major ports.

Modeling the Growth of Technology Units for Health Technology Incubators Suitable for Low-Income Areas

Background. This research aimed to optimize the technology policy and reduce the costs of technology growth centers at medical sciences universities. Identifying the effective factors in the expansion of technology units facilitates the development and advancement of innovative entrepreneurs through incubators. Methods. The current qualitative research analyzes data collected through structured interviews with 31 individuals from growth centers, administrators of units located in growth centers, and health entrepreneurship experts. In three stages of categorization, the main and sub-categories have been identified. The relationships between the research components were determined using the interpretive structural modeling (ISM) technique. Results. Based on the results of the ISM, "modeling of technology units for health technology incubators in poor areas" we identified 213 codes of verbal propositions, 25 components and 8 categories which was classified into three levels. The first level is the growth of technological units; the second level includes the infrastructure and planned growth; and the third level includes the indicators of external infrastructure, internal infrastructure, acceptance plan, growth plan, and exit plan. Conclusion. This study determined the framework and relationships between variables that influence the growth of technology units in health technology development centers at universities in disadvantaged areas. This is the first study to incorporate the internal infrastructure as an independent variable, indicating the effect of compensating for regional infrastructure weaknesses.