Evaluation of supply chain resilience index: a graph theory based approach

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Nishtha Agarwal ◽  
Nitin Seth ◽  
Ashish Agarwal

PurposeThe present study aims at developing a model to quantify supply chain resilience as a single numerical value. The numerical value is called resilience index that measures the resilience capability of the case company's supply chain. The model calculates the index value based on the interactions between the enablers of supply chain resilience and its dimensions.Design/methodology/approachGraph theoretic approach (GTA) is used to evaluate the resilience index for the case company's supply chain. In GTA, the dimensions of resilience enablers and their interdependencies are modelled through a digraph. The digraph depicting the influence of each dimension is converted into an adjacency matrix. The permanent function value of the adjacency matrix is called the resilience index (RI).FindingsThe proposed approach has been illustrated in context of an Indian automobile organization, and value of the RI is evaluated. The best case and the worst-case values are also obtained with the help of GTA. It is noted from the model that strategic level dimension of enablers is most important in contributing towards supply chain resilience. They are followed by tactical and operational level enablers. The GTA framework proposed will help supply chain practitioners to evaluate and benchmark the supply chain resilience of their respective organizations with the best in the industry.Originality/valueA firm can compare the RI of its own supply chain with other's supply chain or with the best in the industry for benchmarking purpose. Benchmarking of resilience will help organizations in developing strategies to compete in dynamic market scenario.

2018 ◽  
Vol 29 (3) ◽  
pp. 478-514 ◽  
Author(s):  
Kavilal E.G. ◽  
Shanmugam Prasanna Venkatesan ◽  
Joshi Sanket

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.


2018 ◽  
Vol 24 (2) ◽  
pp. 517-536 ◽  
Author(s):  
Shishir Goyal ◽  
Srikanta Routroy ◽  
Harshal Shah

Purpose The purpose of this paper is to quantify, evaluate and compare the environmental sustainability performance of supply chain for Indian steel industry using graph theoretic approach (GTA). Design/methodology/approach Broadly 12 environmental sustainability enablers (ESEs) were identified and they were classified into four significant categories (SCs). Featuring these SCs and ESEs under each SC, a methodology was proposed using GTA for evaluating the environmental sustainability performance of Indian steel companies. The analysis was further extended to compare the results with performance in different situations and accordingly set the future targets. Findings In order to demonstrate the utility of the proposed methodology, it was applied to an Indian steel company. The results obtained indicated that there have been significant growths achieved in the environmental sustainability performance over a period of five years. It was also found that a performance gap exists and it will reach the target value after two years. Practical implications The proposed approach is aimed at providing a procedure for evaluating the environmental sustainability performance. This study is an attempt to assist a steel industry to assess its sustainability program and accordingly define its course of actions. Originality/value Although many issues related to environmental sustainability have been widely recognized and studied, there are no specific studies available in the literature to assess the environmental sustainability performance along the timeline. The proposed model has the ability to capture the performance and interdependencies of SCs, ESEs under each SC and also to quantify the environmental sustainability performance along the timeline.


Author(s):  
A Mohammad ◽  
R A Khan ◽  
V P Agrawal

Development of the methods for generating distinct mechanisms derived from a given family of kinematic chains has been persued by a number of researchers in the past, as the distinct kinematic structures provide distinct performance characteristics. A new method is proposed to identify the distinct mechanisms derived from a given kinematic chain in this paper. Kinematic chains and their derived mechanisms are represented in the form of an extended adjacency matrix [EA] using the graph theoretic approach. Two structural invariants derived from the eigen spectrum of the [EA] matrix are the sum of absolute eigen values EA∑ and maximum absolute eigen value EAmax. These invariants are used as the composite identification number of a kinematic chain and mechanism and are tested to identify the all-distinct mechanisms derived from the family of 1-F kinematic chains up to 10 links. The identification of distinct kinematic chains and their mechanisms is necessary to select the best possible mechanism for the specified task at the conceptual stage of design.


Kybernetes ◽  
2019 ◽  
Vol 49 (6) ◽  
pp. 1767-1782
Author(s):  
Goldina Ghosh ◽  
C.B. Akki ◽  
Nivedita Kasturi

Purpose The purpose of this study is data generated from any social networking sites may provide some hidden knowledge on a particular domain. Based on this concept the previous paper had proved that social connectivity enhancement takes place through triadic closure and embeddedness in terms of social network graph-theoretic approach. Further, the work was justified by genetic algorithm (GA) where observation showed how interdisciplinary work can occur because of crossover, and therefore, different groups of researchers could be identified. Further enhancement of the work has been focused on in this paper. Design/methodology/approach In continuation with the previous work, this paper detects other possible fields related to “high graded researchers” who can share the information with the other group of researchers (“imminent high graded” and “new researchers”) using particle swarm optimization (PSO) technique. Findings While exploitation was done using GA in the previous work, exploration is done in the current work based on PSO using the same grade score value to the objective function. Both the velocity and direction of high graded researchers in this extended work could be derived, which was not possible using GA. Originality/value This could help the next two levels of researchers (“imminent high graded researchers” and “new researchers”) in expanding their research fields in line with the fields of high graded researchers.


2016 ◽  
Vol 28 (4) ◽  
pp. 663-682 ◽  
Author(s):  
Srikanta Routroy ◽  
Sudeep Kumar Pradhan ◽  
C.V. Sunil Kumar

Purpose The purpose of this paper is to quantify, evaluate and compare the implementation performance of a supplier development (SD) program using graph theoretic approach (GTA). Design/methodology/approach Broadly 13 critical success factors (CSFs) were identified and they were classified into four significant categories (SCs). Featuring these SCs and CSFs under each SC, GTA was proposed for evaluating the implementation performance of SD programs. The analysis was further extended to evaluate the performance of a SD program along the timeline to capture the other influences (if any), eventually compare the results with different performance situations and accordingly set the future targets. Findings In order to demonstrate the utility of the proposed approach it was applied to an Indian manufacturing company. The results obtained shown that there has been a significant growth achieved in the implementation performance of a SD program over a period of three years (i.e. 12 quarters) along the chosen SCs and CSFs under each SC. It was also found that still there was a performance gap and scope for improvement in the SD program of the case company. Practical implications The proposed approach is aimed at providing a procedure for evaluating the implementation performance of a SD program. This study is an attempt to assist a manufacturer to assess its SD program and accordingly define its course of actions. Originality/value Although many issues related to SD have been widely recognized and studied, there are no specific studies available in the literature to assess the implementation performance of SD programs along the timeline. The proposed model has the ability to capture the performance and interdependencies of SCs, CSFs under each SC and also to quantify the implementation performance of a SD program along the timeline.


2018 ◽  
Vol 25 (8) ◽  
pp. 2611-2634 ◽  
Author(s):  
Abhishek Jain ◽  
Harwinder Singh ◽  
Rajbir S. Bhatti

Purpose The purpose of this paper is to identify the key enabler for total productive maintenance (TPM) implementation in Indian small and medium enterprises (SMEs) by using graph theoretic approach (GTA). There are certain enablers for TPM implementation which helps the organization to implement it successfully. It is very essential to identify the nature and impact of these key enablers. Design/methodology/approach A large number of the enablers (27) have identified for TPM implementation in Indian SMEs from the available literature, questionnaire survey and expert opinion. These TPM enablers have categorized into six major categories. Findings In this research work, the intensity of identifying enablers has been calculated to show their impact or influence in TPM implementation. The value of intensity of TPM enablers shows the role or impact of individual enabler in the implementation of TPM in Indian SMEs. Practical implications This study provides an easy-to-use methodology for the practical decision makers in the manufacturing industry to improve their performance by implementing TPM in Indian SMEs. A detailed methodology has prepared to identify the enablers for TPM implementation in Indian SMEs by using GTA. This study also explains that how to check the feasibility of an organization to implement TPM in Indian SMEs successfully. Originality/value TPM is an improvement concept which holds the potential to improve manufacturing organizations, but its implementation is not easy in Indian SMEs. The reason behind the unsuccessful implementation of TPM in most of the organizations is the ignorance of impact of innumerable enablers and barriers.


2006 ◽  
Vol 13 (4) ◽  
pp. 447-468 ◽  
Author(s):  
Sandeep Grover ◽  
V.P. Agrawal ◽  
I.A. Khan

PurposeTo represent the effect of ‘human factors in total quality management (TQM) environment’ in terms of a single numerical index by considering their inheritances and interactions.Design/methodology/approachVarious human factors affecting the TQM culture in an organization are identified and discussed for the sub factors affecting them. These factors are interacting with each other and their overall effect helps an organization in attaining TQM enabled needs. The paper attempts to represent the overall effect of human factors quantitatively by developing a mathematical model using graph theoretic approach. In this approach, interaction among identified human factors is represented through digraph, matrix model and a multinomial.FindingsThe extent of human aspects present in an organization, conducive to TQM culture is represented in terms of the “human index”. It provides an insight into the human factors at system and subsystem level. The developed procedure may be useful for self‐analysis and comparison among organizations.Research limitations/implicationsSince, human behaviour is difficult to predict, so are the human factors. The paper considers general factors, which may vary depending on type of organization, size of organization and geographical location. There is a scope of research in factor specific organizations.Practical implicationsIt provides a useful methodology for organizations to assess human aspects and improve upon therein. Procedure for stepwise application of methodology is given with example that may help an industry to implement it.Originality/valueThe paper attempts to quantify the intangibles through systematic approach and is of value to industries to improve upon their work environment.


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