Modeling reconfigurability in supply chains using total interpretive structural modeling

2017 ◽  
Vol 14 (2) ◽  
pp. 194-221 ◽  
Author(s):  
Pallab Biswas
Keyword(s):  
Supply Chain ◽  
Supply Chains ◽  
New Product Development ◽  
Structural Changes ◽  
Structural Modeling ◽  
Global Market ◽  
Interpretive Structural Modeling ◽  
Content Type ◽  
Micmac Analysis ◽  
Expert Opinions

Purpose The purpose of this paper is to identify, analyze, and categorize the major enablers of reconfigurability that can facilitate structural changes within a supply chain in a global scenario. The paper also addresses five reconfigurability dimensions in the perspective of supply chains and the major enablers to attain them. The paper further aims to understand the mutual interactions among these enablers through the identification of hierarchical relationships among them. Design/methodology/approach A framework that holistically considers all the major enablers of reconfigurability has been developed. The hierarchical interrelationships between major enablers have been presented and interpreted using a novel qualitative modeling technique, i.e., total interpretive structural modeling (TISM), which is an extension of ISM. SPSS 22.0 is employed to carry out a one-tailed one-sample t-test further to test the hypotheses for validating the results of TISM. Impact matrix cross-reference multiplication applied to a classification (MICMAC) analysis has been employed to identify the driving and dependence powers of these reconfigurability enablers. Findings In this paper, 15 enablers for reconfigurability paradigm have been identified through literature review and expert opinions. The authors established interrelationships and interdependencies among these enablers and categorized them as enablers of each dimension. New product development and customer satisfaction come at the highest level of priority. The levels of these enablers were obtained using TISM. The authors compared the results with the clusters derived from MICMAC analysis, and the results are found to be well within the acceptable range. Research limitations/implications The study has implications for both practitioners and academia. The work provides a comprehensive list of enablers that are relevant to reconfigure supply chains in today’s volatile global market. This research will also help decision makers to strategically focus on the top-level enablers and their concerned dimensions. The research is based on an automobile company case study and can be extended to products with volatile and changing demands. Originality/value The proposed model for reconfigurability enablers using TISM is a new effort altogether in the area of supply chain management. The novelty of this research lies in its identification of specific enablers to reconfigure a supply chain through different dimensions.

Readiness assessment of leagility supply chain based on fuzzy cognitive maps and interpretive structural modeling: a case study

2018 ◽  
Vol 33 (4) ◽  
pp. 442-456 ◽  
Author(s):  
Taher Kalantari ◽  
Farid Khoshalhan
Keyword(s):  
Supply Chain ◽  
Supply Chains ◽  
Cognitive Maps ◽  
Structural Modeling ◽  
Study Data ◽  
Fuzzy Cognitive Maps ◽  
Readiness Assessment ◽  
Interpretive Structural Modeling ◽  
Content Type ◽  
Functional Areas

Purpose The evaluation of readiness provides insight into the readiness of its individual components for successful accomplishment of tasks. This study aims to evaluate readiness in leagility of supply chains based on the design and analysis of fuzzy cognitive maps (FCM) and interpretive structural modeling (ISM). Design/methodology/approach On the basis of the purpose of this study, data are gathered via the Delphi method. Moreover, FCM and ISM are also used to evaluate readiness. Findings Findings initially demonstrate a categorization of factors influencing leagility into static and dynamic variables according to the degree of their influence derived from the resultant behavior of FCM and ISM. It is also found that evaluating readiness in leagility of supply chains with ISM and FCM was done with respect to the type and role of the study variables, which were determined within the minimum and maximum ranges of 20 to 100 per cent, respectively. Originality/value The evaluation of the readiness using the FCM and ISM is proved to be more efficient than other classical methods. Experimental results of the study contribute to improve readiness of leagility of supply chain as well as develop functional areas of business.

An integrated interpretive structural modeling and a graph-theoretic approach for measuring the supply chain complexity in the Indian automotive industry

2018 ◽  
Vol 29 (3) ◽  
pp. 478-514 ◽  
Author(s):  
Kavilal E.G. ◽  
Shanmugam Prasanna Venkatesan ◽  
Joshi Sanket
Keyword(s):  
Supply Chain ◽  
Automotive Industry ◽  
Structural Modeling ◽  
Theoretic Approach ◽  
Passenger Vehicle ◽  
Interpretive Structural Modeling ◽  
Content Type ◽  
Graph Theoretic ◽  
Graph Theoretic Approach ◽  
Numerical Index

Purpose Easily employable quantitative supply chain complexity (SCC) measures considering the significant dimensions of complexity as well as the drivers that represent those dimensions are limited in the literature. The purpose of this paper is to propose an integrated interpretive structural modeling (ISM) and a graph-theoretic approach to quantify SCC by a single numerical index considering the interdependence and the inheritance of the SCC drivers. Design/methodology/approach In total, 18 SCC drivers identified from the literature are clustered according to the significant dimensions of complexity. The interdependencies established through ISM and inheritance values of SCC drivers are mapped into a Variable Permanent Matrix (VPM). The permanent function of this VPM is then computed and the resulting single numerical index is the measure of SCC. Findings A scale is proposed by computing the minimum and maximum threshold values of SCC with the help of expert opinions of the Indian automotive industry. The complexity of commercial and passenger vehicle sectors within the automotive industry is measured and compared using the proposed scale. From the results, it is identified that the number of suppliers, increase in spare-parts due to shortened product life-cycle and demand uncertainties increase the SCC of the passenger vehicle sector, while number of parts, products and processes, variety of products and process and unreliability of suppliers increase the complexity of the commercial vehicle sector. The result indicates that various SCC drivers have a different impact on determining the SCC level of these two sectors. Originality/value The authors propose an integrated method that can be readily applied to measure and quantify SCC considering the significant dimensions of complexity as well as the interdependence and the inheritance of the SCC drivers that contribute to those dimensions. This index further helps to compare the complexity of the supply chain which varies between industries.

Interpretive structural modeling for integrating quality management in manufacturing and service counterparts

2017 ◽  
Vol 34 (9) ◽  
pp. 1568-1591 ◽  
Author(s):  
Gaurav Goyal ◽  
Harsh Vardhan Samalia ◽  
Piyush Verma
Keyword(s):  
Quality Management ◽  
Citation Analysis ◽  
Process Management ◽  
Structural Modeling ◽  
Interpretive Structural Modeling ◽  
Research Attention ◽  
Chain Flexibility ◽  
Content Type ◽  
Expert Opinions ◽  
Related Service

Purpose The purpose of this paper is to identify and rank the contextual relationship among the quality management (QM) constructs for manufacturing and its related service organizations providing integrated value bundles, which has got limited research attention. Design/methodology/approach The QM constructs of manufacturing and services are selected by performing the citation analysis. Studies related to manufacturing and service are selected by reviewing their citations index in the three major research databases namely ProQuest, Scopus and Google Scholar. The subjective responses from both industry and academia are taken in order to gain better understanding of the contextual relationship among the QM constructs. Finally, an integrated model is proposed using Micmac analysis and Interpretive Structural Modeling (ISM). Findings The citation analysis lead to identification of 12 QM constructs: top management commitment, supplier relationship management, human resource management, strategic focus, customer focus, quality of information sharing, process management, servicescape, employee involvement, service quality, supply chain flexibility and customer satisfaction. The expert opinions of executives in the automotive industry and academia resulted in the development of contextual relationships among the identified QM constructs for the development of an ISM model, which is a major contribution of this study. Originality/value The unique focus of this study is on analyzing the contextual relationship among QM aspects in manufacturing and services as clubbed offering. The researchers in the existing literature have so far differentiated between manufacturing and services but this study integrates the QM constructs for manufacturing and its associated services through expert feedback and proposes an ISM model.

scholarly journals Modelling the inhibitors of cold supply chain using fuzzy interpretive structural modeling and fuzzy MICMAC analysis

PLoS ONE ◽  
2021 ◽  
Vol 16 (4) ◽  
pp. e0249046
Author(s):  
Anshuman Sharma ◽  
Haidar Abbas ◽  
Muhammad Qutubuddin Siddiqui
Keyword(s):  
Supply Chain ◽  
Supply Chains ◽  
United Arab Emirates ◽  
Hierarchical Model ◽  
Structural Modeling ◽  
Structured Interviews ◽  
Interpretive Structural Modeling ◽  
Inadequate Information ◽  
Fuzzy Micmac ◽  
Lack Of Commitment

The Cold Supply Chain (CSC) is an integral part of the supply chain of perishable products. The aim of this research is to examine the inhibitors that have a major impact on the performance of CSC operations in the United Arab Emirates (UAE). This study provides a synthesis and suggests a hierarchical model among CSC inhibitors and their respective relevance. The hierarchical synthesis of twelve (12) primary CSC inhibitors is achieved through a comprehensive literature review and consultation with academics and CSC professionals. This study used semi-structured interviews, a fuzzy interpretive structural modeling (FISM) and a Fuzzy-MICMAC (FMICMAC) analysis to explore and establish the relationship between and among identified inhibitors. FISM is used to examine the interaction between inhibitors, while FMICMAC analysis is used to examine the nature of inhibitors on the basis of their dependence and driving power. The results of the FISM and FMICMAC analysis show the inter-relationships and relative dominance of identified inhibitors. The results show that some inhibitors are of high strategic importance due to their high driving power and low dependence. These inhibitors seek more management attention in order to improve their effectiveness. The result of a hierarchical model helps to understand the influence of a particular inhibitor on others. ‘Higher capital and operating costs’ occupy the highest level in the FISM model. The ‘fragmented cold supply chains’, ‘lack of skilled labor’, ‘inadequate information system infrastructure’ and ‘lack of commitment by top level management’ had strong driving power but weak dependence, which characterizes them as independent inhibitors. Management should be extra careful when dealing with these inhibitors as they influence the effects of other variables at the top of the FISM hierarchy in the overall management of the cold supply chain. The study also suggests a number of recommendations for addressing these inhibitors in cold supply chains operating in the UAE. With due attention and care for these inhibitors, the operation of the cold supply chains is likely to be even more successful.

Modeling Deming’s quality principles to improve performance using interpretive structural modeling and MICMAC analysis

2019 ◽  
Vol 36 (7) ◽  
pp. 1159-1180 ◽  
Author(s):  
Nishant Mukesh Agrawal
Keyword(s):  
Manufacturing Industry ◽  
Structural Modeling ◽  
Total Quality ◽  
Interpretive Structural Modeling ◽  
Content Type ◽  
Practical Applications ◽  
Micmac Analysis ◽  
Significant Relationships ◽  
Quality Principles ◽  
Quality Framework

Purpose The purpose of this paper is to study the 14 principles of Edwards Deming and create significant relationships between them. No research has been reported on the implementation of Total Quality Management (TQM) using Deming’s 14 principles. To fill this gap, Interpretive Structural Modeling (ISM) and MICMAC analysis have been developed to understand mutual interactions among variables and find both the dependence and driving power of these variables. Design/methodology/approach The research paper discusses a blend of practical applications and introduces a theoretical framework. An ISM-based methodology is used to study and examine interactions between identified variables, while MICMAC analysis is used to identify the dependence and driving power. Findings This research utilizes Deming’s 14 quality principles, with experts from academia and industry consulted to identify contextual relationships among variables. The result shows that the stated principles “take action to accomplish the transformation,” “institute training,” “encourage education to employees” and “institute leadership” are strategic requirements, while “drive out fear,” “break down barrier between staff areas” and “eliminate numerical quotas” are tactical requirements. “Adopt the new philosophy,” “create constancy in improvement of product and service” and “cease dependence on mass inspections” are operational requirements for TQM applications. Originality/value An ISM-based quality framework, dependence power and driving power of variables using MICMAC analysis have been recommended to the service and manufacturing industry as a new focus area in the implementation of TQM.

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.

Assessing sustainable supply chain enablers using total interpretive structural modeling approach and fuzzy-MICMAC analysis

2018 ◽  
Vol 29 (2) ◽  
pp. 216-239 ◽  
Author(s):  
Mahamaya Mohanty
Keyword(s):  
Supply Chain ◽  
Sustainable Supply Chain ◽  
Interpretive Structural Modeling ◽  
Policy Makers ◽  
Consumer Durables ◽  
Content Type ◽  
Micmac Analysis ◽  
Strategic Factors ◽  
Fuzzy Micmac ◽  
Integrated Logistics

Purpose The purpose of this paper is to model the enablers of an integrated logistics. The integration is accounted for incorporating sustainability, thereby aiming in its theory building. Existing models have focused on enablers of sustainable supply chain independently which lacks a holistic view in understanding the integrated logistics for sustainable supply chain. Design/methodology/approach An extensive literature review, expert opinion from both industry and academia based on questionnaire survey, is conducted to find the relevant enablers. The modeling of these enablers is done using total interpretive structural modeling (TISM). Finally, TISM along with its respective fuzzy-matriced impact croises multiplication applique (fuzzy-MICMAC) analysis is depicted. Findings The result of the survey and TISM model with its respective fuzzy-MICMAC has been used to evolve the mutual relationships among the important enablers of integrated logistics of consumer durables. The strategic factors obtained from TISM are integration and collaboration in the supply chain, vehicle type, and capacity; reduction in average length of haul; and real-time information system. Route selection and scheduling, reduction of fuel consumption, customer relationship management, green technology, cost reduction, etc., are some of the operational factors. Sustainable environment performance is obtained as the performance factor. Fuzzy-MICMAC is more responsive than the traditional MICMAC analysis. Research limitations/implications The study has limitation for the development of a conceptual framework for integrated logistics in uncertain environments. So it can be extended by combining soft computing methodologies. There is a lack of mathematical quantification of the proposed model where the enablers of sustainability can be measured. Practical implications The study on integrated logistics for sustainable supply chain is itself a new area to be explored, as very few studies on this relevant topic exist. The research concentrates on TISM for the integrated logistics and the movement of consumer durables through different distribution channels of a supply chain. The study has implications for practitioners, academicians, and policy makers. For practitioners, it provides a list of strategic factors, operational factors, and performance factors. For academicians, this methodology can be opted to conduct an exploratory study by identifying the essential enablers. For policy makers, the regulations can be developed using the above model. Originality/value It is an effort to model the important enablers and establish sustainability in integrated logistics of consumer durables.

Modeling the enablers of green supply chain management

2017 ◽  
Vol 24 (2) ◽  
pp. 536-568 ◽  
Author(s):  
Rakesh Kumar Malviya ◽  
Ravi Kant
Keyword(s):  
Supply Chain ◽  
Supply Chain Management ◽  
Action Plan ◽  
Green Supply Chain Management ◽  
Green Supply Chain ◽  
Interpretive Structural Modeling ◽  
Chain Management ◽  
Content Type ◽  
Micmac Analysis ◽  
Fuzzy Micmac

Purpose The purpose of this paper is to identify and develop the relationships among the green supply chain management enablers (GSCMEs), to understand mutual influences of these GSCMEs on green supply chain management (GSCM) implementation, and to find out the driving and the dependence power of GSCMEs. Design/methodology/approach This paper has identified 35 GSCMEs on the basis of literature review and the opinions of experts from academia and industry. A nationwide questionnaire-based survey has been conducted to rank these identified GSCMEs. The outcomes of the survey and interpretive structural modeling (ISM) methodology have been applied to evolve mutual relationships among GSCMEs, which helps to reveal the direct and indirect effects of each GSCMEs. The results of the ISM are used as an input to the fuzzy Matriced’ Impacts Croisés Multiplication Appliquéeá un Classement (MICMAC) analysis, to identify the driving and the dependence power of GSCMEs. Findings Out of 35 GSCMEs 29 GSCMEs (mean⩾3.00) have been considered for analysis through a nationwide questionnaire-based survey on Indian automobile organizations. The integrated approach is developed, since the ISM model provides only binary relationship among GSCMEs, while fuzzy MICMAC analysis provides precise analysis related to driving and the dependence power of GSCMEs. Research limitations/implications The weightage for ISM model development and fuzzy MICMAC are obtained through the judgment of few industry experts. It is the only subjective judgment and any biasing by the person who is judging might influence the final result. Practical implications The study provides important guidelines for both practitioners, as well as the academicians. The practitioners need to focus on these GSCMEs more carefully during GSCM implementation. GSCM managers may strategically plan its long-term growth to meet GSCM action plan. While the academicians may be encouraged to categorize different issues, which are significant in addressing these GSCMEs. Originality/value Arrangement of GSCMEs in a hierarchy, the categorization into the driver and dependent categories, and fuzzy MICMAC are an exclusive effort in the area of GSCM implementation.

The changing dynamics in the worldwide mobile phone market: creating excellence through innovation management and collaborative relationships

2015 ◽  
Vol 5 (1) ◽  
pp. 1-7 ◽  
Author(s):  
Pankaj Kumar Medhi ◽  
Sandeep Mondal
Keyword(s):  
Supply Chain ◽  
Supply Chains ◽  
Mobile Phone ◽  
Innovation Management ◽  
World Market ◽  
Global Market ◽  
High Tech ◽  
Global Supply Chains ◽  
Content Type ◽  
Market Dominance

Subject area Supply chain management (SCM). Study level/applicability Graduate students. Case overview In recent times, the world market of mobile phone is in a flux due to many phenomena of importance like strong emergence of smartphones, Nokia losing market share in all segments of market and fast technological and supply chain innovation by players like Apple and Google. Elements of SCM and the way technology is acquired have assumed a place of importance to compete in the global market. A new standard of innovation and SCM is emerging together as the rules of market dominance are re-written all-over again. Expected learning outcomes After completion of the case study, the students will understand: role of technological innovation in high-tech industry and global supply chains in changing the consumer behavior world over; the classic battle for market dominance with a new way of innovation management in technology and processes to create most efficient global supply chains; importance of SCM practices of collaboration like tighter partner integration, use of power asymmetry and contract by dominant players to create efficient supply chains; and how visionaries like late Steve Job are shaping the new era of technology. Supplementary materials Teaching Notes are available for educators only. Please contact your library to gain login details or email: [email protected] to request teaching notes.

Modeling the factors affecting the quality of life in diabetic patients in India using total interpretive structural modeling

2019 ◽  
Vol 26 (3) ◽  
pp. 951-970 ◽  
Author(s):  
Puneeta Ajmera ◽  
Vineet Jain
Keyword(s):  
Quality Of Life ◽  
Diabetes Mellitus ◽  
Structural Modeling ◽  
World Health ◽  
Psychological State ◽  
Diabetic Patients ◽  
Interpretive Structural Modeling ◽  
Content Type ◽  
Micmac Analysis

Purpose Diabetes mellitus has become a major world health problem that has unenviable impacts on health of the people including quality of life (QOL) also and in which person’s physical and psychological state, social commitments and relationships and his interaction with the environment is affected. This shows that there is an urgent need for behavior change and considerable educational strategies for proper management and rehabilitation (Reddy, 2000). This research has identified and ranked the significant factors which affect the QOL in diabetic patients in India. The paper aims to discuss these issues. Design/methodology/approach In this paper, nine factors which affect the QOL in diabetic patients in India have been identified through review of the literature and evaluated by total interpretive structural modeling (TISM) approach, i.e. an extended version of ISM. In this approach, interpretations of the interrelationship among factors have been discussed. Therefore, TISM approach has been used to develop the model and the mutual interactions among these factors. Findings The results of the model and MICMAC analysis indicate that diet restriction, body pain and satisfaction with treatment are the top-level factors. Practical implications Identification of the factors that have a remarkable effect on the QOL in diabetic patients is very important so that the doctors and other healthcare professionals may handle these factors efficiently and proper rehabilitation can be provided to such patients. Originality/value This paper has used an application of the TISM approach to interpret the mutual relationship by using the tool of interpretive matrix and has developed a framework to calculate the drive and the dependence power of factors using MICMAC analysis. The issues related to QOL are extremely important, as they can strongly anticipate a person’s capability to govern his lifestyle with disease like diabetes mellitus and maintain good health in the long run. This shows the urgent requirement of an optimized model which can predict and interpret the relationships among these factors. In this research, the interrelationships among these factors have been developed and interpretations of these interactions have been given to develop a comprehensive model so that QOL of diabetic patients may be improved.

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