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

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.

2021 ◽  
Author(s):  
Slim ZIDI ◽  
Nadia Hamani ◽  
Lyes Kermad

Abstract The reconfiguration of supply chain is becoming a crucial concept used to deal with market disruptions and changes such as COVID 19 pandemic, demand uncertainty, new technologies, etc. It can be defined as the ability of the supply chain to change its structure and functions in order to adapt to new changes. Its assessment requires an understanding of its quantitative factors to provide indicators that are easy to interpret. Effective reconfigurability assessment can be achieved by measuring quantitatively its six characteristics (modularity, integrability, convertibility, diagnosability, scalability and customization). This paper aims at identifying the quantitative factors of each characteristic and their inter-relationships by using Total Interpretive Structural Modelling (TISM). The structural model obtained by TISM is applied to understand the dependency quantitative factors. Based on TISM results, a classification of quantitative factors is determined using « Matrice d'Impacts Croisés, Multiplication Appliquée à un Classement » (MICMAC) analysis. This paper may be helpful to understand the previously mentioned characteristics of reconfigurable supply chain in order to facilitate the measuring and the assessment of reconfigurability.


2019 ◽  
Vol 25 (7) ◽  
pp. 1198-1223 ◽  
Author(s):  
Rohit Agrawal ◽  
Vinodh S.

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.


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Aqueeb Sohail Shaik ◽  
Sanjay Dhir

Purpose The purpose of this study is to explain the interrelationships between the elements of strategic thinking, technological change and strategic risks. The main objective of this research is to identify the hierarchy for the elements of thinking, technological change and strategic risk and also to identify the driving powers of these elements. Design/methodology/approach The methodology used in this study is modified total interpretive structural modelling and MICMAC analysis which gives the interrelationships and also the driving powers of the elements by analysing the relationships between the elements from the existing literature. This method helps us in answering/understanding the “what”, “how” and “why” of the research. Modified total Interpretive structural modeling is considered in this study, which helps in doing both the paired comparisons and transitivity checks simultaneously. A digraph is constructed at the end of the analysis, which shows the links between the elements, and a driver dependence matrix is constructed, which shows the driving powers. Findings This study gives an understanding of the role of the elements, the relationships between them and the hierarchy of addressing these elements, and also the driving and dependence power. Findings of this research give us an understanding of how strategic thinking/technological change/strategic drives the performance of the firm. Research limitations/implications This study is conducted with the help of existing literature; this can be further extended by considering the expert opinion. Practical implications The model explains the direct and transitive links of the elements and the strength of the relation between them, which helps the researchers and the practitioners to understand the driving power and importance of these constructs. It also helps us to understand the role of these elements and, if implemented in an organisation, which elements need to be prioritised for enhancing the performance of the firm. Originality/value Research done in the past has individually analysed the elements effecting strategic thinking; this study identifies the relationships between the elements of all three constructs and helps in understanding the levels of hierarchy.


2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Maurice Brady

PurposeThe purpose of this research is to validate an industry-wide definition of supply chain resilience (SCRES) within the Irish supply chain sector and measure the key elements of SCRES and their relative importance for Irish firms in light of Brexit.Design/methodology/approachSurvey method is used in this research. Data were collected from supply chain managers in Irish firms. Findings were analysed in accordance with industry sector and exposure to Brexit.FindingsThe results from the respondents confirm a willingness to define and utilise SCRES under a four-phase cycle; ready, respond, recover and grow. Focus on SCRES enablers shifts in accordance with cycle position. Understanding cycle position is paramount for successful execution of a SCRES strategy. Findings can be used as a basis for the development, implementation and management of a SCRES strategy.Research limitations/implicationsResearch was conducted at one specific point during Brexit negotiations. Sector specific and longitudinal studies are required to build upon this exploratory study.Practical implicationsSupply chain managers must ensure that phase position and enabler implementation are aligned to maximise the investment in a SCRES strategy. As a disruption event and its associated response evolve, management must demonstrate an ability to deploy and focus efforts on different SCRES enablers throughout the four-phase cycle.Originality/valueThis is the first research focussing on an industry-wide accepted definition of SCRES and its key enablers within Irish supply chains.


2020 ◽  
Vol 31 (5) ◽  
pp. 1111-1145
Author(s):  
Surajit Bag ◽  
Sunil Luthra ◽  
V.G. Venkatesh ◽  
Gunjan Yadav

PurposeHumanitarian supply chains (HSCs) by their very nature require urgent reaction to unforeseeable needs, making it difficult to properly plan for the support of actual demands. As such, integrating sustainability into traditional HSC practices continues to present a challenge to governments, nongovernmental organizations (NGOs) and other humanitarian-related agencies. This study focuses on identifying and categorizing the leading enablers to green humanitarian supply chains (GHSCs) and proposes a model for improving the responsiveness based upon a fuzzy total interpretive structural modelling approach.Design/methodology/approachTotal interpretive structural modelling (TISM) uses group decision-making to identify contextual relationships among each pair of enablers and elucidates the nature of each underlying relationship. The fuzzy TISM shows the level of strength (very high influence, high influence, low influence and very low influence) of each enabler in relation to other enablers, which can help to inform management decision-making.FindingsGHSC management requires strategic planning of inventory and logistics management. The importance of collaborative relationship building with HSC partners for developing capability and the effective use of available resources are keys to success. These improved relationships also help to promote postponement and similar speculation-based logistics strategies, as well as advanced purchasing and pre-positioning strategies. Finally, the speed and quality of response is found to be the top enabler in GHSC management.Research limitations/implicationsOne noted shortcoming of the chosen research method is its reliance on subjective expert judgement. However, collecting judgements is at the basis of many research methods, and the research team took utmost care throughout the research process to allay biases. Future empirical research can further examine the relationships suggested herein. Managers can use the model developed in this research to consider impactful ways to design and execute sustainable HSCs.Originality/valueTo the best of the authors' knowledge, this is a novel attempt to identify enablers to GHSC management. Secondly, the research team has used an advanced methodology (fuzzy TISM) to develop the contextual inter-relationships among the enablers which has not been used earlier in this direction before and thus advances the GHSC literature.


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