Application of interpretive structural modelling for analysis of lean adoption barriers in heavy industry

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Aadithya B.G. ◽  
Asokan P. ◽  
S. Vinodh
Keyword(s):  
Structural Model ◽  
Matrix Multiplication ◽  
Interaction Matrix ◽  
Management Support ◽  
Structural Modelling ◽  
Content Type ◽  
Interpretive Structural Modelling ◽  
Top Management Support ◽  
Micmac Analysis ◽  
Practical Implications

Purpose The purpose of the paper is to depict a study on analysis of barriers to lean adoption in fabrication industry using interpretive structural modelling (ISM). Design/methodology/approach From the literature review, 22 barriers to lean adoption in fabrication industry have been recognized . Self-structure interaction matrix has been developed based on expert opinion. Computational steps of ISM are being done to develop the structural model. cross-impact matrix multiplication applied to classification (MICMAC) analysis is being done to group the barriers into four types. Findings Based on the study, it has been found that “lack of knowledge about lean (philosophy, principles, tools)”, “lack of top management support and commitment” and “poor leadership” are found to be the principal barriers. MICMAC analysis indicated that number of driving, dependent, linkage and autonomous barriers are 9, 8, 4 and 1, respectively. Practical implications The study has been executed based on the inputs from industrial practitioners and hence the inferences are found to have practical relevance. Originality/value The study is an attempt to analyze the barriers for lean concepts adoption in fabrication kind of industry.

Application of total interpretive structural modelling (TISM) for analysis of factors influencing sustainable additive manufacturing: a case study

2019 ◽  
Vol 25 (7) ◽  
pp. 1198-1223 ◽  
Author(s):  
Rohit Agrawal ◽  
Vinodh S.
Keyword(s):  
Additive Manufacturing ◽  
Structural Model ◽  
Matrix Multiplication ◽  
Structural Modelling ◽  
Content Type ◽  
Interpretive Structural Modelling ◽  
Micmac Analysis ◽  
Factors Influencing ◽  
Total Interpretive Structural Modelling

Purpose The purpose of this study is to develop a structural model based on total interpretive structural modelling (TISM) approach for analysis of factors influencing sustainable additive manufacturing (AM). Design/methodology/approach A total of 20 factors influencing sustainable AM are identified on the basis of literature review. Appropriate inputs from experts are obtained and TISM model is developed. Also, cross-impact Matrix multiplication applied to classification (MICMAC) analysis is carried out to categorize the factors. Findings Based on TISM model, “Flexibility in manufacturing”, “Time to develop new product” and “Local availability of technology” are found to be the dominant factors. MICMAC analysis indicates that 10 factors belong to driving and 10 factors belong to dependent category. Research limitations/implications In the present study, 20 factors have been considered. In future, additional factors can be considered to deal with technological advancements. Practical implications The conduct of the study will enable AM experts to systematically analyze the factors influencing sustainable AM. Originality/value The development of structural model for analysis of factors influencing sustainable AM manufacturing is the original contribution of authors.

Using positive deviance to enhance employee engagement: an interpretive structural modelling approach

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Naman Sharma
Keyword(s):  
Employee Engagement ◽  
Human Resource ◽  
Positive Deviance ◽  
Workplace Deviance ◽  
Superior Performance ◽  
Structural Modelling ◽  
Content Type ◽  
Interpretive Structural Modelling ◽  
Micmac Analysis ◽  
Practical Implications

Purpose Organisations today seek high engagement levels from their employees for their superior performance amid the highly competitive environment. The purpose of this paper is to examine the role of positive deviance facilitators (PDFs) in enhancing employee engagement at work. Design/methodology/approach The study adopts the interpretive structural modelling (ISM) and Matrice d’Impacts Croisés-Multiplication Appliquée á un Classement (MICMAC) analysis to understand the process of how positive deviance may fuel employee engagement in an organisation. Because of the lack of empirical evidence on the relationship between employee engagement and positive deviance, ISM approach was adopted as it helps in understanding the subjective experience and learnings of experts involved in the field. The MICMAC analysis classifies the relevant factors into four clusters and helps in understanding the dynamics involved. Findings Based on the opinions shared by industry and academia experts, a structural model was developed to understand the hierarchy and interactions among the eight PDFs leading towards employee engagement. Research limitations/implications The study offers both theoretical and practical implications. The model developed in the current study could be used as a base model for future studies concerning employee engagement and deviance. The importance of human resource management practices in fuelling positive deviance and employee engagement is also highlighted. The study discusses various practical implications for human resource managers and top management. Originality/value The literature on positive deviance at work is still at a nascent stage. Empirical studies on deviance largely focus on the destructive/negative side of workplace deviance, and studies on positive outcomes from workplace deviance are rare. This present study provides a unique opportunity to understand how positive deviance can be used to enhance the engagement levels of employees.

Interpretive structural modelling for attributes of software quality

2017 ◽  
Vol 14 (3) ◽  
pp. 256-269 ◽  
Author(s):  
Adarsh Anand ◽  
Gunjan Bansal
Keyword(s):  
Software Quality ◽  
Matrix Multiplication ◽  
Quality Attributes ◽  
Sample Population ◽  
Structural Modelling ◽  
R Software ◽  
Content Type ◽  
Interpretive Structural Modelling ◽  
Micmac Analysis

Purpose The “quality” of any product or service defines the agility of the product and its life cycle in dynamic environment. The demand of high “quality” becomes an imperative concern, when “software” is acting as a product or a service. Since the nature of the software is intangible and more complex, therefore the assurance of providing accurate results is anxiety for companies. The overall quality of the software is based upon many individual factors (or attributes) that makes software reliable, inclined and a long-lasting product in the marketplace. But how these factors can influence each other is significant to identify. Therefore, the purpose of this paper is to study the quality aspect of the software and analyse the interrelationship of impactful attributes. Design/methodology/approach The analysis has been done through responses sought from software development teams/clients in India. The questionnaire related to the software quality was administered to the sample population. Interconnection among impactful characteristics has been analysed by using a qualitative technique called interpretive structural modelling (ISM). The driving and dependency of the attributes under consideration has been classified using cross-impact matrix multiplication applied to classification (MICMAC) analysis. The procedure of applying ISM method has been automated and provided it as package “ISM” using R software. Findings In general, it is very complex job to determine the most impactful attribute of software quality. By applying ISM and MICMAC analysis on the set of attributes under consideration, it has been found that “reliability” along with “usability” and “performance” is the most influential attribute of software quality and preferred most. Research limitations/implications Though ISM provides an organized modelling framework yet its results are considered less statistically significant. Therefore, it would be interesting to concatenate the present findings with the findings of any analytical methodology; which gives statistically significant results. Practical implications The present proposal deals with the interpretation of the software quality attributes and their contextual relationship but with more effective and efficient manner. It can help management to understand the complexity of relationship amongst attributes (which are quality attributes here) more accurately and precisely. Since today is an era of automation, the manual part is being substituted so as to reduce the labour cost, improve safety, security and product quality to increase production. This study is, therefore, an effort and a helping hand in making the hassle free calculations for obtaining intermediate matrices and doing eventual calculations. Social implications n numbers of parameters can be selected to analyse the interrelationship of any project/study. Eradication human errors in applying transitivity law or applying any other operation in solving problem. The package created here can save precious time of users. Provides well-formatted and readable excel output files that make interpretation easier. Originality/value Software is one such product/service which plays a significant role in this high-technological world, where each and every firm try their best to be on the top of the list of consumers’ preference. For this purpose, companies reduce manual efforts by converting it into qualitative software that provides deliverables in a systematic manner. Therefore, it becomes imperative to study various interrelated quality attributes of the software. On the similar platform, ISM is a widely used technique and just to provide a helping hand in quantification of the qualitative attributes this paper facilitates the readers with algorithm developed using R software.

Sustainable industry 4.0 – an exploratory study for uncovering the drivers for integration

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
N. Harikannan ◽  
S. Vinodh ◽  
Anand Gurumurthy
Keyword(s):  
Industry 4.0 ◽  
Structural Model ◽  
Public Awareness ◽  
Sustainable Manufacturing ◽  
Matrix Multiplication ◽  
Interpretive Structural Modeling ◽  
Content Type ◽  
Micmac Analysis ◽  
Societal Pressure ◽  
Practical Implications

Purpose The concept of sustainable manufacturing has been adopted by manufacturing organizations to develop eco-friendlier products and processes. In recent times, industries are progressing toward Industry 4.0 (I4.0). Guided with smart intelligent devices, I4.0 can possibly decrease excess production, material movement and consumption of energy. If so, it is hypothesized that there is a good synergy between I4.0 and sustainability, which warrants an integrated approach for implementation. This amalgamation is termed as “Sustainable industry 4.0.” Hence, this paper aims to systematically identify and analyze the drivers for this integration. Design/methodology/approach This paper presents the analysis of 20 drivers identified from literature review for simultaneous deployment of I4.0 and sustainable manufacturing. Interpretive structural modeling (ISM) is used to derive the structural model for analyzing the causal association between drivers. Cross-Impact Matrix Multiplication Applied to Classification (MICMAC) analysis is being performed to group the drivers. Findings The results showed that the dominant drivers derived are societal pressure and public awareness (D18), government policies on support I4.0 (D12), top management involvement and support (D15) and government promotions and regulations (D16). Also, the MICMAC analysis revealed many driving, dependent, linkage and autonomous drivers. Research limitations/implications The opinion from experts with combined expertise on I4.0 and sustainability was obtained. The respondent size could be increased in future studies. Practical implications The study has been done based on inputs from industry practitioners. Managerial and practical implications are presented. ISM shows that the drivers for deploying sustainable I4.0 are highly inter-related. It also reveals the pre-requisites for each level of the drivers. Originality/value The idea of analyzing the drivers for sustainable I4.0 is the original contribution of the authors.

Understanding complex relationship among JIT, lean behaviour, TQM and their antecedents using interpretive structural modelling and fuzzy MICMAC analysis

2015 ◽  
Vol 27 (1) ◽  
pp. 42-62 ◽  
Author(s):  
Rameshwar Dubey ◽  
Tripti Singh
Keyword(s):  
Lean Manufacturing ◽  
Business Performance ◽  
Complex Relationship ◽  
Management Support ◽  
Structural Modelling ◽  
Content Type ◽  
Top Management Support ◽  
Extant Literature ◽  
Micmac Analysis ◽  
Fuzzy Micmac

Purpose – The purpose of this paper is to understand possible linkage between variables that constitute a lean manufacturing enterprise. In the study the authors have tried to decode the complex relationship among variables which is missing in extant literature. Design/methodology/approach – In the study the authors have used systematic literature review (SLR) approach to identify the variables from extant literature and used interpretive structural modelling (ISM) and Fuzzy MICMAC analysis to understand complex equation among variables from Indian manufacturing firm perspective. Findings – The findings using ISM modeling indicate top management support is the bottom level and business performance is the top level. In order to further resolve conflicts the authors have further analyzed variables using Fuzzy MICMAC analysis which has further divided variables into four clusters. The Fuzzy MICMAC output suggests that top management support, real time production information, training and team work are the driving variables and business performance, total quality management and lean behavior are the dependence variables. Research limitations/implications – Like any study, the study have its own limitations. In the study the authors have developed the model based on expert opinion. The number may be not enough to validate this model statistically. However, it can be regarded as a platform for further investigation using structural equation modeling. Originality/value – The present study using ISM model has proposed a model based upon experts, identified from Indian major manufacturing firms. This model can further provide empirical platform for further investigation which can resolve lean manufacturing issues.

Analysis of barriers in implementation of digital transformation of supply chain using interpretive structural modelling approach

2019 ◽  
Vol 15 (1) ◽  
pp. 297-317 ◽  
Author(s):  
Prakash Agrawal ◽  
Rakesh Narain ◽  
Inayat Ullah
Keyword(s):  
Supply Chain ◽  
Structural Model ◽  
Matrix Multiplication ◽  
Digital Transformation ◽  
Successful Implementation ◽  
Structural Modelling ◽  
Content Type ◽  
Interpretive Structural Modelling ◽  
Managerial Implications ◽  
Power And Dependence

Purpose Digital supply chain (DSC) is an agile, customer-driven and productive way to develop different forms of returns for companies and to leverage efficient approaches with emerging techniques and data analytics. Though the advantages of digital supply chain management (DSCM) are many, its implementation is quite slow for several reasons. The purpose of this paper is to identify the major barriers which hinder the adoption of DSC and to analyse the interrelationship among them. The barriers of DSC are explored on the basis of existing literature and experts’ opinion. Design/methodology/approach This paper uses the interpretive structural modelling (ISM) approach to develop a hierarchical structural model which shows the mutual dependence among the barriers of DSC. Cross-impact matrix multiplication applied to classification analysis was performed to represent these barriers graphically on the basis of their driving power and dependence. Findings The research demonstrates that the barriers “no sense of urgency”, “lack of industry specific guidelines”, “lack of digital skills and talent” and “high implementation and running cost” are the most significant barriers to digital transformation of supply chain. This paper also suggests some managerial implications to overcome the barriers which hinder the implementation of digital transformation of supply chain. Practical implications This paper assists managers and policymakers to understand the order in which these barriers must be tackled and adopts a roadmap for successful implementation of DSCM and reap its benefits. Originality/value This is one of the initial research studies which has analysed the barriers of DSC using ISM approach.

E-procurement in small and medium sized enterprises; facilitators, obstacles and effect on performance

2019 ◽  
Vol 27 (2) ◽  
pp. 839-866
Author(s):  
Cristóbal Sánchez-Rodríguez ◽  
Angel Rafael Martínez-Lorente ◽  
David Hemsworth
Keyword(s):  
Business Performance ◽  
Design Methodology ◽  
Top Management ◽  
Process Performance ◽  
Management Support ◽  
Content Type ◽  
Procurement Process ◽  
Top Management Support ◽  
Strategic Purchasing ◽  
Practical Implications

Purpose The purpose of this paper is to analyze e-procurement in small and medium-sized enterprises (SMEs) and its relationship with top management support, IT obstacles and strategic purchasing and the effect of e-procurement on performance (procurement performance and business performance). Design/methodology/approach The hypotheses were tested using a sample of 199 managers from SMEs in manufacturing. Findings The results indicated a significant relationship between e-procurement in SMEs and top management support, IT obstacles and strategic purchasing. Similarly, the authors found a positive relationship between e-procurement and procurement process performance and business performance. Practical implications The findings stress to SME managers, the need to pay attention to top management support, IT obstacles and strategic purchasing when implementing e-procurement. Similarly, it provides evidence of the benefits of e-procurement on procurement process performance and business performance. Originality/value This study fills a gap in the literature regarding e-procurement in SMEs and its impact on performance. SMEs constitute a significant part of today’s economies and e-procurement can significantly impact the performance of these organizations.

Application of total interpretive structural modeling for analyzing factors of additive manufacturing and industry 4.0 integration

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Vishal Ashok Wankhede ◽  
Vinodh S.
Keyword(s):  
Additive Manufacturing ◽  
Industry 4.0 ◽  
Structural Model ◽  
Matrix Multiplication ◽  
Structural Modeling ◽  
Influential Factors ◽  
Time Data ◽  
Interpretive Structural Modeling ◽  
Content Type ◽  
Micmac Analysis

Purpose The purpose of this paper is to develop a model based on the total interpretive structural modeling (TISM) approach for analysis of factors of additive manufacturing (AM) and industry 4.0 (I4.0) integration. Design/methodology/approach AM integration with I4.0 is attributed due to various reasons such as developing complex shapes with good quality, real-time data analysis, augmented reality and decentralized production. To enable the integration of AM and I4.0, a structural model is to be developed. TISM technique is used as a solution methodology. TISM approach supports establishing a contextual relationship-based structural model to recognize the influential factors. Cross-impact matrix multiplication applied to classification (MICMAC) analysis has been used to validate the TISM model and to explore the driving and dependence power of each factor. Findings The derived structural model indicated the dominant factors to be focused on. Dominant factors include sensor integration (F9), resolution (F12), small build volumes (F19), internet of things and lead time (F14). MICMAC analysis showed the number of driving, dependent, linkage and autonomous factors as 3, 2, 12 and 3, respectively. Research limitations/implications In the present study, 20 factors are considered. In the future, additional factors could be considered based on advancements in I4.0 technologies. Practical implications The study has practical relevance as it had been conducted based on inputs from industry practitioners. The industry decision-makers and practitioners may use the developed TISM model to understand the inter-relationship among the factors to take appropriate measures before adoption. Originality/value The study on developing a structural model for analysis of factors influencing AM and I4.0 is the original contribution of the authors.

Analysis of supply chain resilience barriers in Indian automotive company using total interpretive structural modelling

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Nishtha Agarwal ◽  
Nitin Seth
Keyword(s):  
Supply Chain ◽  
Second Phase ◽  
Structural Modelling ◽  
Content Type ◽  
Supply Chain Resilience ◽  
Interpretive Structural Modelling ◽  
Micmac Analysis ◽  
Root Barrier ◽  
Definition Of ◽  
Total Interpretive Structural Modelling

PurposeThe study tries to identify the barriers influencing supply chain resilience and examine the inter-relationships between them. These relationships are built on the basis of how one barrier drives or is driven by the changes in another barriers.Design/methodology/approachIn the first phase, literature review and with due discussion with experts, the barriers have been identified and shortlisted for an Indian automotive case company. In the second phase, total interpretive structural modelling (TISM) has been applied to examine inter-relationships between the barriers for an Indian automobile case company. Matrice d'impacts croisés multiplication appliquée á un classment (MICMAC) analysis has also been performed to analyse the driving and dependence power of the barriers.FindingsIn total, 11 barriers are identified from the first phase of the study. In the second phase, the TISM digraph is created which qualitatively explains the reason behind how one barrier leads to another. MICMAC analysis classifies these variables in four clusters namely autonomous, linkage, dependent and independent. These clusters characterise the barriers based on their driving and dependent power which helps managers in strategically tackling them while taking understanding from the TISM digraph.Research limitations/implicationsThree research implications can be made from the study. First, a comprehensive definition of supply chain which helps in understanding of resilience based on disruption phases and recovery. Second, 11 barriers are identified which hinder resilience in automotive sector. Their relationships are modelled using TISM which also gives why a particular relationship exists. Last, MICMAC analysis classifies barriers based on how high or low the driving and dependence power exists.Practical implicationsThe study offers significant implications for supply chain managers helping them in building resilience by identifying barriers and reducing their effect. Barriers are identified for case company which might help managers to tackle them during disruptions. The final TISM digraph depicts the “why” between the inter-relationships between the barriers to resilient supply chains. TISM shows that non-commitment of top management is the major root barrier which has been causing the other problems. MICMAC analysis is also performed along with discussion as to how autonomous, linkage, dependent and independent barriers can be tackled to build resilience.Originality/valueTISM is considered as an effective methodology for conceptual framework development as it also explains “why” between the relationships besides explaining the “what” as against ISM. Identification and understanding of barriers and their interrelationship will help supply chain managers to analyse the influence and inter-dependence of barriers on the resilience of the supply chain. Such understanding will help in mitigating/averting these barriers hence improving the resilience capability. It also adds to the knowledge base in the area of supply chain resilience where several authors have pointed the lack of research.

A framework to enhance agile manufacturing system

2017 ◽  
Vol 24 (2) ◽  
pp. 467-487 ◽  
Author(s):  
Rahul Sindhwani ◽  
Vasdev Malhotra
Keyword(s):  
Manufacturing System ◽  
Structural Model ◽  
Agile Manufacturing ◽  
Top Management ◽  
Management Support ◽  
Interpretive Structural Modeling ◽  
Content Type ◽  
Micmac Analysis ◽  
Model Hierarchy ◽  
Or Organization

Purpose The purpose of this paper is to identify and analyze the interactions among different enablers of agile manufacturing system (AMS). The existing enablers available in the past literature are scattered and not able to meet specific requirements of the customers. So, it becomes a necessity to encapsulate these enablers in appropriate proportions to enable traditional organizations to AMS. To fill this gap total interpretive structural modeling (TISM) and MICMAC analysis-based framework model have been developed to understand the mutual interactions between among the enablers. Design/methodology/approach Identification of enablers followed by application of TISM, which is an innovative version of ISM and MICMAC analysis, is used to study and analyze the mutual interactions between identified enablers. Findings The result reveals that top management support, organizational structure and information technology integration have strong driving power and weak dependence power and are at the lowest level in the TISM model hierarchy, while the outcome enablers of AMS have low-driving power but have high-dependence power. Research limitations/implications This model is developed on the basis of inputs from few experts and may not reflect the opinion of whole industry community. Practical implications Top management must stress on enablers having strong driving power for efficient implementation of AMS. Managers in the area of manufacturing may drive useful insights from the empirical study presented in this paper. Managers should plan an effective strategy for proper implementation of AMS which makes organization more agile, productive, competitive and profitable. Originality/value TISM-based framework structural model has been proposed for industry or organization which is a new effort for implementation of AMS.

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