Interpretive Structural Modeling Model Research Articles

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.

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.

Determination of driving power and dependency of wastes in the healthcare sector: a lean and ISM-Based approach

PurposeThe objective of this study is to systematically identify, categorize and assess the driving factors and interdependencies associated with various types of healthcare waste. The study specifically focuses on waste that has been managed or is recommended for treatment through the application of Lean Six Sigma (LSS) methodologies.Design/methodology/approachTo accomplish the study’s objectives, interpretive structural modeling (ISM) was utilized. This analytical tool aided in quantifying the driving power and dependencies of each form of healthcare waste, referred to as “enablers,” as well as their related variables. As a result, these enablers were classified into four distinct categories: autonomous, dependent, linkage and drivers or independents.FindingsIn the healthcare sector, the “high cost” (HC) emerges as an autonomous variable, operating with substantial independence. Conversely, variables such as skill wastage, poor service quality and low patient satisfaction are identified as dependent variables. These are distinguished by their low driving power and high dependency. On the flip side, variables related to transportation, production, processing and defect waste manifest strong driving forces and minimal dependencies, categorizing them as independent factors. Notably, inventory waste (IW) is highlighted as a salient issue within the healthcare domain, given its propensity to engender additional forms of waste.Research limitations/implicationsEmploying the ISM model, along with comprehensive case study analyses, provides a detailed framework for examining the complex hierarchies of waste existing within the healthcare sector. This methodological approach equips healthcare leaders with the tools to accurately pinpoint and eliminate unnecessary expenditures, thereby optimizing operational efficiency and enhancing patient satisfaction. Of particular significance, the study calls attention to the key role of IW, which often acts as a trigger for other forms of waste in the sector, thus identifying a crucial area requiring focused intervention and improvement.Originality/valueThis research reveals new insights into how waste variables are structured in healthcare, offering a useful guide for managers looking to make their waste-reduction strategies more efficient. These insights are highly relevant not just for healthcare providers but also for the administrators and researchers who are helping to shape the industry. Using the classification and ranking model developed in this study, healthcare organizations can more easily spot and address common types of waste. In addition, the model serves as a useful tool for practitioners, helping them gain a deeper, more detailed understanding of how different factors are connected in efforts to reduce waste.

An Analysis of Post COVID-19 Scenario using Data Science in Digital Marketing

The Purpose of the study is to analyze the uses of data science in digital marketing in post COVID-19 scenario. General design of the study includes survey of relevant research literature, primary data collection, structural modeling and critical analysis. The study uses Interpretive Structural Modeling (ISM) for structural modeling and Matriced' Impacts Croise's Multiplication Appliquée a UN Classement (MICMAC) for analysis. Introducing new products, personalizing customers’ online experience and improve user experience occupy top (Level I) and tracking social media commentary/interactions occupies bottom (Level IX) of ISM model. Analyzing user generated content, tracking social media commentary/interactions, analysis of online sales data, analyzing social media trends, analyzing product recommendations and reviews and analyze real-time big data are categorized as independent uses. Optimize customers’ preferences, optimize stock levels in e-commerce businesses, introducing new products, improve user experience and identify fake news & false content are categorized as dependent uses but others are categorized as linkage uses and no one is categorized in autonomous. It is an original study because it uses real time market survey data the findings of which are useful for folks of its stakeholders. It is particularly useful for marketers. It has serious implications for businesses since nowadays there is influx of data generation that has become a type of a noise for businesses. Use of data science not only converts this data noise into useful information but also an opportunity. This study provides lot of information about uses of data science particularly for marketing.

Barriers to TQM implementation in SMEs in Bangladesh: an interpretive structural modeling approach

PurposeThis study aims to recognize the significant barriers of small and medium-sized enterprises (SMEs) in Bangladesh, hindering the adoption of total quality management (TQM). Additionally, this research intends to explore the interrelations among these barriers to develop essential managerial insights for promoting TQM implementation in SMEs.Design/methodology/approachThe interpretive structural modeling (ISM) approach and Matrice d'impacts croisés multiplication appliquée á un classment (MICMAC) a cross-impact matrix multiplication applied to classification show the relationship among the barriers and classification of the barriers to TQM implementation respectively, and partial least squares structural equation modeling (PLS-SEM) is applied for ISM model validation.FindingsThis study examined previous literature and conducted interviews with professionals to identify 17 barriers. The study then develops and investigates a model that outlines the relationships and priorities among these barriers and categorizes them based on their impact and interdependence. This analysis can assist SMEs in implementing TQM during their operations successfully.Practical implicationsThis research emphasizes the crucial obstacles that greatly affect other barriers and require immediate attention. Furthermore, this study provides valuable information for SMEs to effectively prioritize their resources and efforts to overcome these obstacles.Originality/valueThis study delves into the primary obstacles impeding the integration of TQM in SMEs through a novel approach. Additionally, this study constructs a verified contextual framework that depicts the hierarchies and interconnections among these barriers.

Analysis of accident risk factors in chemical industry based on ISM-BN

The chemical industry involves the production, storage, and use of many flammable, explosive, toxic, and other hazardous chemicals. Once an accident occurs, it will cause serious harm to human and economic activities. In order to prevent chemical accidents, this paper combines Interpretive Structural Modeling (ISM) and Bayesian network (BN) to quantitatively study the relationship and interaction strength among accident risk factors in chemical industry. Through the analysis of accident cases and questionnaire survey, 21 accident risk factors in chemical industry are selected. According to the decision of experts, the influence relationship between risk factors is determined, and a multi-level directed graph of ISM is obtained. And the ISM model is transformed into a quantitative BN model. The BN model is applied to forward reasoning, sensitivity analysis, and reverse reasoning. The results indicate that there is a positive correlation between various risk factors and chemical accidents, and the supervision mechanism has the highest probability of occurrence in production activities. Illegal operation has the highest sensitivity and the greatest impact on chemical accidents. Inherent hazards of materials and products is the most likely cause of accidents. Based on the research results, feasible measures have been proposed to improve safety management in the chemical industry.

Fostering supply chain agility by prominent enablers’ identification and developing conceptual modeling based on the ISM-MICMAC approach

PurposeToday’s marketplace has witnessed intense competitive pressures and high levels of uncertainty and disruption. Therefore, supply chains require agility to obtain a sustainable competitive advantage and cope with uncertainties as well as disruptions. Although a wide range of studies exists on supply chain agility (SCA) from the perspective of antecedents or consequences, there is little research on the investigation of enablers of SCA and their relations among them. Furthermore, the literature has investigated proactive and reactive enablers for enhancing SCA, but most studies have not sufficiently framed their analysis of both aspects synchronically. This paper aims to find out the interrelationships among the proactive and reactive enablers for enhancing SCA.Design/methodology/approachAn extensive literature review has been conducted to identify SCA enablers and a Delphi study has been performed to elucidate SCA enablers in the manufacturing industry in Turkey. Interpretive structural modeling (ISM) has been used to identify the contextual relationship among the SCA enablers, and the model has been validated based on Matriced Impact Croises Multiplication Appliquee a un Classement (MICMAC) analysis.FindingsOn theoretical and practical levels, the proposed ISM model in this study can help organizations analyze and interpret interrelationships among enablers of SCA. For managers, it can provide better insights and understanding of the facilitators of SCA to enhance the effectiveness of the supply chain and cope with uncertainties and turbulence. According to results, enhancing “supply and demand side competency”, “delivery speed” and “strategic sourcing” are the most significant enablers of SCA.Originality/valueThe study extends the existing literature related to the enablers of SCA by modeling the proactive and reactive enablers of SCA based on the Al Humdan et al. (2020) classification. Arranging the enablers of SCA in a hierarchy and classifying the enablers into different levels with the help of the ISM-MICMAC approach is an exclusive effort to achieve successful management of the supply chain.

Establishing interrelationships and dependencies of critical success factors for implementing offsite construction in the UK

PurposeThe United Kingdom (UK) construction sector is transforming with increasing confidence in offsite construction (OSC) solutions following its accrued benefits. To sustain this momentum, exploring viable strategies to promote successful OSC implementation is a top priority. This paper aims to identify and establish interrelationships and logical dependencies of critical success factors (CSFs) for implementing OSC on building projects in the UK.Design/methodology/approachThis study utilised a qualitative research approach. Following a critical review of extant literature, brainstorming and focus group sessions were carried out with OSC experts in the UK construction industry to identify and contextualise CSFs for OSC implementation. Interpretive structural modelling (ISM) and matrix impact cross-reference multiplication applied to a classification (MICMAC) were used to analyse and model the interrelationships between the contextualised CSFs.FindingsThe study identified eighteen CSFs for implementing OSC on projects in the UK positioned on seven hierarchical levels and clustered into dependent, linkage and independent factors. The top five CSFs established were client commitment, top management support, adequate OSC knowledge and experience, flexible leadership and flexible business models. These were located at the base of the ISM model, possessing the highest driving powers in facilitating the successful implementation of OSC on projects.Originality/valueThis study established a hierarchical interrelationship and the importance of the CSFs influencing the successful implementation of OSC. This would assist OSC clients and project teams in identifying and prioritising particular areas for strategic actions, which offer advantages in pursuing successful OSC project outcomes in the UK. Previous research on OSC implementation in the UK had not examined CSFs' interrelationships.

Application of ISM to Identify the Contextual Relationships between the Sustainable Solutions Based on the Principles and Pillars of Industry 4.0: A Sustainability 4.0 Model for Law Offices

This paper addresses the concept of Sustainability 4.0 in services, which can be defined as an integrated approach that seeks to balance the dimensions of the triple bottom line (economic, social, and environmental factors) using Industry 4.0, enabling technologies to improve organizational processes. This paper aims to identify the contextual relationships between the sustainable solutions of I4.0 based on the principles and pillars of Industry 4.0 in services while using Interpretive Structural Modeling (ISM). The ISM model, composed of 16 sustainable solutions, was developed based on the vision of a law firm manager and validated by 19 experts. As a result, the model presented a six-level hierarchy for sustainable solutions and classified sustainable solutions for law firms as Dependent Sustainable Solutions, Liaison Sustainable Solutions, and Independent Sustainable Solutions. Moreover, this study highlights the importance of sustainable solutions in Industry 4.0 in services, raising awareness of the need for sustainable practices in organizations. Therefore, this research contributes to the advancement of scientific knowledge, offers practical guidance for law firm managers, and promotes sustainability in Industry 4.0 in services, benefiting both academia and society.

Research On Bidding for The Olympic Games Based on Meta-Network and ISM Model

In view of the dwindling interest of countries to bid for hosting the Olympic Games, this paper proposes two models to assess the impact and feasibility of hosting the Olympic Games. The first model is an Olympic Impact D&A System Meta-Network model based on 20 indicators in four categories including economy, society, politics and environment, and the correlations between the indicators are classified and determined by Principal Component Analysis (PCA). The second model is based on Interpretive Structural Modeling (ISM), which proposes four new hosting methods and analyzes their centrality, causality and hierarchy in the new network. The results show that fixed location in developed countries and annual smaller game in developing countries are the two most advantageous methods.

Modelling enablers of the post-disaster recovery of road infrastructure using ISM and fuzzy MICMAC analysis

The road infrastructure is damaged after a disaster, resulting in the area being disconnected from other locations. Thus, road clearing, and recovery operations are on priority during the emergency recovery operations to restore access to the disaster-affected area. Therefore, an investigation was conducted on the disaster in Uttarakhand (a Northern state in India) that occurred during February 2021, to advance our understanding of the enablers of the emergency recovery operations for road infrastructure. For this purpose, the study undertakes a comprehensive review of contemporary literature and discussion with the practitioners and academicians involved in this field of study. The study uses interpretive structural modeling (ISM) and Fuzzy MICMAC analysis to identify and develop a hierarchical model of enablers to improve the post-disaster recovery of road infrastructure. The study identifies eleven enablers to the post-disaster recovery of road infrastructure, and interrelationships among these enablers are derived using the ISM model. The enablers include a focus on preparedness, prevention and mitigation phase, engagement of local communities, engagement of local contractors, support from local government, developing policies with more focus on disaster preparedness, allocation of funds, investment in technology, more utilization of technology, developing trust among stakeholders, promoting information sharing among stakeholders and foster coordination and collaboration among stakeholders. Further, the result indicates that driver variables, including the focus on preparedness, prevention and mitigation phase, engagement of local communities, engagement of local contractors, support from local government, and developing policies with more focus on disaster preparedness, are critical to improving the post-disaster recovery of road infrastructure.

IMO 선박 온실가스 감축 규제에 대한 국내 해운업계 대응의 해석적 구조 분석

Purpose : The purpose of this research is to analyze responses of the Korean shipping industry to IMO’s regulations to reduce greenhouse gas from ships. This includes identifying responses and analyzing their interactions, thus providing with reasonable grounds for the industry’s responses as well as policy suggestions. Research design, data and methodology : This paper collected data from the industry by using the Delphi method, and then adopted ISM(Interpretive Structural Modelling) to structure responses to regulations in a graphical manner. Results : According to the ISM model, it was found that the causal interactions starts from compliance with national action plans thorough alternative vessel fuel and operational efficiency to market-based initiatives. Conclusions : This paper provides policy suggestions, such as establishment of national action plans, concentration of national competencies on the decision and development of alternative fuels, and an impact analysis for supporting the most preferred market-based initiatives for Korean shipping industry.

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.

Interpretive structural modelling: Hierarchical relationship model of appreciating diversity competency for educational leaders

<span lang="EN-US">The dynamics of diversity and cultural competency are elements that run parallel with globalization. Appreciating diversity is part of global leadership competency. However, this assumption may not hold in a context in which multiculturalism diversity and competency are not an integral element for leadership competency for public sector educational leaders. Public organization should assimilate and practice appreciating diversity in the organizational leadership competency. Thus, the central aim of this study is to investigate and examine the appreciating diversity competency for educational leaders. The paper analyzed the appreciating competencies by using interpretive structural modelling (ISM) based on experts’ consensus. The cross-impact matrix multiplication applied to classification (MICMAC) analysis ascertained and classified each competency based on their driving and dependent power. The hierarchical model developed through ISM yielded seven appreciating competencies divided into two dimensions for educational leaders. The model proposed could be adopted by stakeholders to upgrade the competency of educational leaders to practice and apply appreciating diversity. The ISM model could be adopted for the training and development of future educational leaders in preparation to administer and lead multicultural and multigenerational organizational communities.</span>

Interpretive structural modelling of organizational innovation factors: An emerging market perspective

This research aims to identify key factors in organizational innovation and their interrelationships using Interpretive Structural Modelling (ISM). An interpretive review of related literature was utilized to develop a multi-level structured model ISM with the help of MICMAC analysis to determine the driving and dependence power of each identified factor. 11 factors were identified and the extent to which they influence organizational innovation was explored. Diversity, empowerment, and Training & Development are the strongest driving forces (independent factors), whereas innovation and organizational culture had the lowest driving power and highest dependence (dependent factors). This study provides a foundation for further research development and managerial practice to emphasize major factors driving organizational innovation. However, the application of ISM model incorporates subjective judgments that may affect the results. This research extends beyond existing literature in integrating a plethora of factors influencing and inhibiting innovation in organizations, and in providing an explicit and comprehensive view of these factors’ interrelationships and mutual primary effects, with implications for promoting employee creativity and thus organizational innovation.

Interrelationship Performance Indicators Model of Agile Supply Chain Management in Palm Oil Industry

This paper tries to model agile supply chain management performance indicators in the palm oil industry. The interpretative Structural Modeling (ISM) method is used to find the relationship between these indicators. The ISM stages begin with identifying indicators, compiling contextual relationships, compiling reachability matrices, compiling level partitions, compiling digraphs, and compiling ISM models. Then MICMAC analysis is used to group each of these indicators into four categories based on their driving power and dependence power. In this study, 16 hands of agile supply chain management in the palm oil industry were obtained, of which the four-level ISM model could be constructed. Two indicators are at level 4, six hands are at level 3, three indicators are at level 2, and five indicators are at level 1. Meanwhile, through MICMAC analysis, five indicators are found in the independent indicators category, six hands are in the linkage indicator category, four indicators are included in the dependent indicator category, and one indicator is in the autonomous indicator category. This research can be used by managers in the palm oil industry who want to increase agility in their supply chain. In general, indicators at level 4 can affect indicators at level 3, and so on. So that management can start fixing the indicators at level 4 first. In addition, indicators that have a driving power value in MICMAC analysis can be prioritized to improve their performance.

Indonesian agroindustry business agility: Enablers and challenges in the poultry industry based on ISM model

The Indonesian agroindustry is a crucial sector for food security, comprising several platforms such as the poultry industry that play a role in providing animal protein. Despite the advantages portrayed by the poultry sector in the country, stiff competition is still encountered with business transformation situation. The rigid and static structures of the Indonesian poultry industry are also reflected in bureaucracy, fear-based cultures, the inefficiency of functional silos, and aversion to change, leading to the need for appropriate agility incorporation. Therefore, this study aims to identify and analyze the key challenges and enablers influencing the achievement of business agility, as well as construct a structural interpretation model for the process through ISM (Interpretative Structural Modeling). The results showed that the hierarchical structure establishment of the influential factors emphasized a logical linkage through ISM implementation. This structural level also identified the major challenges to attaining business agility, indicating the difficulties encountered in work culture transformation and mindset adjustment toward an agile orientation. Meanwhile, management response and knowledge deftness are key enablers in achieving business agility. These results are expected to help business professionals in implementing sustainable organizational model, due to the existence of business agility.

Barrier Factors Model of Innovation Process in the Furniture Industry Supply Chain (Case Study at PT. Duwa Atmimuda)

PT. Duwa Atmimuda is a company engaged in manufacturing in producing stainless metal products and furniture frames. PT. Duwa Atmimuda is experiencing problems with the lack of application of technology in terms of marketing, seen from the absence of social media utilization, causing the company to find it difficult to expand market share. This study aims to identify the factors that hinder the company's innovation process using the Interpretive Structural Modeling (ISM) method and classify the model using MICMAC Analysis. The results showed that the ISM model of the barrier factor for the innovation process in the furniture industry supply chain has 6 levels. After the ISM model is obtained, the next process is to classify each variable indicator on the barrier factors of the innovation process with the help of MICMAC analysis. There are 4 classification clusters, the first cluster (autonomous indicators) has one indicator. While in the second cluster (dependent indicators) there is one indicator. In the third cluster (linkage indicators) there are 9 indicators. In the fourth cluster (independent indicators) there is one indicator. The third cluster (linkage indicators) is the highest cluster of indicator spreads where this indicator has high control and dependence. The conclusion of this study is that there are 12 inhibiting factors in the innovation process which are arranged into six levels of the ISM model and in the MICMAC analysis the third cluster is the highest distribution cluster.

Hierarchical relationships of building partnership competency: the use of nominal group technique and interpretive structural modelling

PurposeThis paper aims to determine the hierarchical relationship between building partnership competencies for public sector educational leaders (ELs) administering and running the education system.Design/methodology/approachAn interpretive structural modelling (ISM) technique was used to develop a hierarchical structural model for building partnership competencies. Nominal group technique (NGT) was used with the help of experts’ suggestions and opinions at the beginning of ISM to identify building partnership competencies. Also, the NGT was used to rank the competencies. A structural self-integration matrix was developed based on experts’ voting and agreement. Cross-impact matrix multiplication applied to classification (MICMAC) analysis was used to analyse the relationship among the building partnership competencies. A total of 11 experts were chosen for NGT and ISM sessions.FindingsA total of 16 building partnership competencies were identified for this study. The competencies were compartmentalised into four domains: creative collaboration, create network, develop collective culture and encouraging constructive dialogue. MICMAC analysis shows each domain of the model of its key competencies ranked at the highest level in the ISM model and dependent competencies.Research limitations/implicationsISM is a modelling approach that is based solely on expert opinions and responses. Its limitation can be overcome with the help of empirical analysis.Practical implicationsThis study supports the public sector ELs’ professional development and upskilling. In addition, the model developed in the study will be helpful for stakeholders, human resources division and policymakers to incorporate building partnership competencies in the training and development of ELs.Originality/valueThis study helps to identify and prioritise building partnership competencies using NGT and ISM. Literature shows that numerous authors have used the ISM approach. Still, the combination of NGT approach is limited. Therefore, the model developed in the study was based solely on experts’ opinions and suggestion based on their experiences and knowledge.

Evaluating and Ranking SCPMS Enablers Using ISM and SWARA

The supply chain performance measurement system (SCPMS) is considered an integral and important part of supply chain management (SCM) for an effective and efficient supply chain (SC). The healthier and more flexible SCPMS is based on the enablers from which the SC metrics are taken. The identification of such enablers must be aligned with the strategic objectives of the organization and mapped to the SC measurement objectives. Hence, this study identifies a set of enablers and ranks them. Interpretive structural modeling (ISM)-based methodology is used in the current study to model the SCPMS implementation enablers. MICMAC analysis is further employed to categorize and comprehend the importance of each SCPMS enabler. ISM offers relationship modeling of SCPMS enablers, whereas MICMAC helps with classifying them into four categories. The Delphi method is then used to validate the ISM model. The SCPMS variable is also used in prioritization using stepwise weight assessment ratio analysis (SWARA). Practicing managers may benefit when developing and installing the SCPMS to satisfy the requirements of supply chain 4.0 for Industry 4.0 (I4.0). They will also be able to recognize and allocate resources while implementing SCPMS. The prioritization using SWARA provides an important ranking according to its importance. The SCPMS enablers of ‘top management support’, ‘SC 4.0 performance measurement awareness’, and ‘managerial readiness’ are found to be significant.