Supply Chain Performance Appraisement and Benchmarking for Manufacturing Industries: Emphasis on Traditional, Green, Flexible and Resilient Supply Chain along with Supplier Selection

Sahu, Anoop Kumar (2015) Supply Chain Performance Appraisement and Benchmarking for Manufacturing Industries: Emphasis on Traditional, Green, Flexible and Resilient Supply Chain along with Supplier Selection. PhD thesis.



Supply chain represents a network of interconnected activities starting from raw material extraction to delivery of the finished product to the end-user. The main constituents of supply chain are supplying/purchasing, inbound logistics, manufacturing, outbound logistics, marketing and sales. In recent times, the traditional supply chain construct is
being modified to embrace various challenges of present business needs. Today’s global market has become highly volatile; customers’ expectations are ever-changing.
Fierce competition amongst business sectors necessitates adapting modern supply
chain management philosophies. Agility, greenness, flexibility as well as resilience have become the key success factors in satisfying global business needs. In order to remain competitive in the turbulent marketplace, industries should focus on improving overall performance of the supply chain network. In this dissertation, supply chain performance assessment has been considered as a
decision making problem involving various measures and metrics (performance indicators). Since most of the performance indices are subjective in nature; decisionmaking relies on active participation of a group of decision-makers (DMs). Subjective human judgment often bears some sort of ambiguity as well as vagueness in the
decision making; to overcome uncertainty in decision making, adaptation of grey/fuzzy set theory seems to be fruitful. To this end, present work deals with a variety of decision support tools to facilitate supply chain performance appraisement as well as benchmarking in fuzzy/grey context. Starting from the traditional supply chain, this work extends appraisement and benchmarking of green supply chain performance for a set of candidate case companies (under the same industry) operating under similar supply chain construct. Exploration of
grey-MOORA, fuzzy-MOORA, IVFN-TOPSIS, fuzzy-grey relation method has been illustrated in this part of work.
Apart from aforementioned empirical studies, two real case studies have been reported in order to estimate a quantitative performance metric reflecting the extent of supply chain flexibility and resilience, respectively, in relation to the case company under consideration.
Performance benchmarking helps in identifying best practices in perspectives of supply chain networking; it can easily be transmitted to other industries. Organizations can follow their peers in order to improve overall performance of the supply chain. vi Supplier selection is considered as an important aspect in supply chain management. Effective supplier selection must be a key strategic consideration towards improving
supply chain performance. However, the task of supplier selection seems difficult due to subjectivity of supplier performance indices. Apart from considering traditional supplier selection criteria (cost, quality and service); global business scenario encourages emphasizing various issues like environmental performance (green concerns), resiliency etc. into evaluation and selection of an appropriate supplier. In this context, the present
work also attempts to explore fuzzy based decision support systems towards evaluation and selection of potential suppliers in green supply chain as well as resilient supply chain, respectively. Fuzzy based Multi-Level Multi-Criteria Decision Making (MLMCDM) approach, fuzzy-TOPSIS and fuzzy-VIKOR have been utilized to facilitate the said decision making.

Item Type:Thesis (PhD)
Uncontrolled Keywords:Performance Appraisement, Performance Benchmarking, Green Supply Chain
Subjects:Engineering and Technology > Mechanical Engineering > Production Engineering
Divisions: Engineering and Technology > Department of Mechanical Engineering
ID Code:6893
Deposited By:Mr. Sanat Kumar Behera
Deposited On:07 Jan 2016 17:32
Last Modified:07 Jan 2016 17:32
Supervisor(s):Datta, Saurav

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