Total Interpretive Structural Modelling of Factors Affecting Labour Productivity in Road Construction

2021 ◽  
Vol 15 (7) ◽  

With the automobile sector pacing the tracks among their competitors to lead the market and adopting eco-friendly technologies, a much economic and vital field of making use of the manufactured product beyond its useful life span is widely neglected. This paper throws light on the necessity for implementing and highlights the various reasons for which these guidelines have not come to the attention of the responsible organizations including law making agencies, automobile manufacturers and as well the consumers. An interpretive structural modelling analysis is made to point out ten driving factors in consultation with various experts from the relevant fields and the results provide guidance to how far the idea of design for dis-assembly and re-manufacturing has sought the world for the sustainability of the automobile manufacturers in the industry, for the days to come.


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.


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