Interdependency analysis of lean manufacturing practices in case of Bulgarian SMEs: interpretive structural modelling and interpretive ranking modelling approach

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Sarita Prasad ◽  
Milen Baltov ◽  
Neelakanteswara Rao A. ◽  
Krishnanand Lanka
Keyword(s):  
Lean Manufacturing ◽  
Real Life ◽  
Successful Implementation ◽  
Structural Modelling ◽  
Content Type ◽  
Interpretive Structural Modelling ◽  
Performance Variables ◽  
Micmac Analysis ◽  
The Relationship ◽  
Modelling Approach

Purpose The paper aims to analyse the contextual relationship and dependency amongst enablers for lean manufacturing implementation in Bulgarian small and medium-sized enterprises (SMEs). Design/methodology/approach In this study, the interpretive structural modelling (ISM) technique was used to develop a hierarchical structural model for enablers. Also, the interpretive ranking process (IRP) was used to analyse and rank enablers with reference to performance variables. For the ISM approach, a structural self- integration matrix was developed with the help of experts’ suggestions and opinions. Cross-impact matrix multiplication applied to classification (MICMAC) analysis was used to analyse the relationship amongst enablers. A total of nine experts were chosen for collecting the primary data in which seven experts belong to the industry and two experts were academicians. The dominant relationship amongst the enablers was analysed through IRP modelling. Findings A total of 11 enablers were identified for the purpose of this study. The model shows that “leadership and commitment by management”, “human resource management”, “customer relation management”, “supplier relation management” and “information technology system” are the most significant enablers for lean implementation in Bulgarian SMEs as these are positioned at the bottom levels in ISM model. MICMAC analysis shows that five enablers fall in the independent factor, two enablers in linkage factor and four enablers in the dependant factor while there is no enabler in the autonomous factor. ISM and IRP models show that “continuous improvement” is an essential enabler for the successful implementation of lean in Bulgarian SMEs. This study also helps to explain the comparative analysis of ISM and IRP, which indicates that IRP is a more robust modelling approach than ISM, as it incorporates the relationship of enablers with performance variables. Research limitations/implications ISM and IRP modelling approaches are based solely on expert opinions and responses. This limitation can be overcome with the help of empirical study. Practical implications This study supports the professionals/experts to prioritise and manage enablers at strategic and tactical levels while implementing lean manufacturing practices in Bulgarian SMEs. The models developed in the study will be helpful for practitioners to understand and analyse the interdependence of enablers for lean manufacturing implementation. Originality/value This study helps to identify and prioritise enablers that affect lean manufacturing adoption using ISM and IRP approaches. Literature shows that numerous authors have used the ISM approach but the use of IRP approach is limited. The models were developed in the study, totally dependent on data collected from the experts to ensure their real-life validity.

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.

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.

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.

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.

Modeling and analysis of FMS performance variables by fuzzy TISM

2019 ◽  
Vol 14 (1) ◽  
pp. 2-30 ◽  
Author(s):  
Vineet Jain ◽  
Vimlesh Kumar Soni
Keyword(s):  
Fuzzy Sets ◽  
Flexible Manufacturing ◽  
Material Handling ◽  
Extensive Literature ◽  
Interpretive Structural Modeling ◽  
Content Type ◽  
Performance Variables ◽  
Micmac Analysis ◽  
Fuzzy Micmac ◽  
The Relationship

PurposeThe purpose of this paper is to identify the flexible manufacturing system performance variables and analyze the interactions among these variables. Interpretive structural modeling (ISM) has been reported for this but no study has been done regarding the interaction of its variables. Therefore, fuzzy TISM (total ISM) has been applied to deduce the relationship and interactions between the variables and driving and dependence power of these variables are examined by fuzzy MICMAC.Design/methodology/approachFuzzy TISM and fuzzy MICMAC analysis have been applied to deduce the relationship and interactions among the variables and driving and dependence power of these variables are examined by fuzzy MICMAC.FindingsIn total, 15 variables have been identified from the extensive literature review. The result showed that automation, use of automated material handling, an effect of tool life and rework percentage have high driving power and weak dependence power in the fuzzy TISM model and fuzzy MICMAC analysis. These are also at the lowest level in the hierarchy in the fuzzy TISM model.Originality/valueFuzzy TISM model has been suggested for manufacturing industries with fuzzy MICMAC analysis. This proposed approach is a novel attempt to integrate TISM approach with the fuzzy sets. The integration of TISM with fuzzy sets provides flexibility to decision-makers to further understand the level of influences of one criterion over another, which was earlier present only in the form of binary (0, 1) numbers; 0 represents no influence and 1 represents influence.

Framework for the implementation of lean construction strategies using the interpretive structural modelling (ISM) technique

2019 ◽  
Vol 27 (1) ◽  
pp. 1-23 ◽  
Author(s):  
Jamil Ghazi Sarhan ◽  
Bo Xia ◽  
Sabrina Fawzia ◽  
Azharul Karim ◽  
Ayokunle Olubunmi Olanipekun ◽  
...  
Keyword(s):  
Saudi Arabia ◽  
Construction Industry ◽  
Success Factors ◽  
Pairwise Comparison ◽  
Lean Construction ◽  
Successful Implementation ◽  
Structural Modelling ◽  
Content Type ◽  
Interpretive Structural Modelling ◽  
New Framework

Purpose The purpose of this paper is to develop a framework for implementing lean construction and consequently to improve performance levels in the construction industry in the context of Saudi Arabia. There is currently no framework for implementing lean construction specifically tailored to the Kingdom of Saudi Arabia (KSA) construction industry. Existing lean construction frameworks are focussed on other countries and are less applicable in the KSA due to differences in socio-cultural and operational contexts. Design/methodology/approach This study employs the interpretive structural modelling (ISM) technique for data collection and analysis. First, following a survey of 282 construction professionals, 12 critical success factors (CSFs) for implementing lean construction in the KSA construction industry were identified by Sarhan et al. (2016). Second, 16 of these professionals who have 15 years or more experience were exclusively selected to examine the contextual relationship among the 12 CSFs. A row and column questionnaire was used for a pairwise comparison of the CSFs. A matrix of cross-impact multiplications (MICMAC) was applied to analyse the questionnaire data to develop an ISM model that can serve as a framework for implementing lean construction. Third, the framework was subjected to further validation by interviewing five experts to check for conceptual inconsistencies and to confirm the applicability of the framework in the context of the KSA construction industry. Findings The findings reveal that the CSFs are divided into four clusters: autonomous, linkage, dependent and driving clusters. Additionally, the findings reveal seven hierarchies of inter-relationships among the CSFs. The order of practical application of the CSFs descends from the seventh hierarchy to the first hierarchy. Originality/value The new framework is a significant advancement over existing lean construction frameworks as it employs an ISM technique to specify the hierarchical relationships among the different factors that contribute to the successful implementation of lean construction. The primary value of this study is the development of a new framework that reflects the socio-cultural and operational contexts in the KSA construction industry and can guide the successful implementation of lean construction. Therefore, construction industry operators such as contractors, consultants, government departments and professionals can rely on the framework to implement lean construction more effectively and successfully.

Modified total interpretive structural modelling of innovation implementation antecedents

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Shiwangi Singh ◽  
Sanjay Dhir
Keyword(s):  
Hierarchical Model ◽  
Structural Equation ◽  
Successful Implementation ◽  
Structural Modelling ◽  
Innovation Implementation ◽  
Content Type ◽  
Interpretive Structural Modelling ◽  
Extant Literature ◽  
Hierarchical Relationship ◽  
Total Interpretive Structural Modelling

PurposeThe paper aims to identify, analyse and develop a model for measuring the inter-relationship and interaction among the antecedents influencing innovation implementation. The extant literature has not widely studied the interactions and inter-relationships among the antecedents of innovation implementation. To fill this gap, the paper develops a hierarchical relationship framework between the identified antecedents of innovation implementation.Design/methodology/approachThe study follows mixed method-based approach using two methodologies: modified total interpretive structural modelling (m-TISM) and MICMAC (Matriced’ Impacts Croisés Multiplication Appliquée á un Classement) analysis. m-TISM is used for the purpose of establishing the hierarchical relationship among the antecedents. MICMAC analysis is used to study the driver-dependent relationship. To identify the antecedents of innovation implementation, the paper follows a systematic search method found in the review articles. The article search was performed across different databases including Google Scholar, Web of Science, EBSCO and Scopus.FindingsIn this study, eight innovation implementation antecedents are identified. The analysis indicates that competency antecedents such as leader competency and employee competency, having high driving and weak dependence power, are at the lowest level in the hierarchical model, whereas, innovation implementation, having high dependence and low driving power, is at the highest level in the hierarchical model. Strategic resources act as a linkage variable.Research limitations/implicationsAlthough this study summarizes the extant literature to generalize the findings, the future studies can focus upon statistical validation of model by employing structural equation modelling to generalize the results.Practical implicationsThe practitioners must emphasize on antecedents having strong driving power for successful implementation of innovation. The hierarchical model is proposed for implementing innovation successfully that will help organizations to be more competitive, productive and profitable.Originality/valueIn this study, m-TISM and MICMAC-based hierarchical models are proposed for implementing innovation successfully in organizations. It also provides the variables insights such as driver-dependent interrelationship between the identified antecedents.

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