Development of decision support systems towards supply chain performance appraisement

Sahu, Santosh Kumar (2014) Development of decision support systems towards supply chain performance appraisement. MTech by Research thesis.



Purpose: The aim of this research is to develop various Decision Support Systems (DSS) towards supply chain (SC)
performance appraisement as well as benchmarking. The purpose of this work is to understand multi-level (measures
and metrics) performance appraisement index system to evaluate overall supply chain performance extent, monitor
ongoing performance level and to identify ill-performing areas of the supply chain network.
Design/methodology/approach: Fuzzy logic as well as grey theory has been explored in developing a variety of SC
performance appraisement modules (evaluation index systems). Generalized fuzzy numbers, generalized intervalvalued fuzzy numbers theory have been utilized in order to tackle decision-makers’ linguistic evaluation information towards meaningful and logical interpretation of procedural hierarchy embedded to the said appraisement modules. Fuzzy-grey relation theory, MULTIMOORA method coupled with fuzzy logic as well as grey theory have also been adapted to facilitate overall SC performance assessment, performance benchmarking and related decision making.
Findings: Supply chain performance index has been computed in terms of fuzzy as well as grey context, suggesting the present performance status of the said organizational supply chain. Ill-performing areas of the SC have been identified too. Fuzzy as well as grey based MULTIMOORA (MOORA: Multi-Objective Optimization by Ratio Analysis),
fuzzy-grey relation analysis, thus adapted, appeared helpful in evaluating performance ranking order (and selecting the best) of various candidate alternatives (industries/enterprises) operating under similar supply chain architecture according to the ongoing SC performance. Empirical illustrations exhibited the fruitful application potential of the developed decision support tools.
Practical implications: The decision support tools thus proposed may be proved fruitful for companies that are trying to identify key business performance measures for their supply chains. Ill-performing areas can easily be identified; companies can seek for possible means in order to improve those SC aspects so as to improve/enhance overall SC performance extent. Benchmarking may help in identifying best practices in relation to the SC which is performing as ideal (benchmarked practices). Best practices of the ideal organization need to be transmitted to the others. Companies can follow their peers in order to improve overall performance level of the entire supply chain. In view of this, the work reported in this dissertation may be proved as a good contributor for effective management of organizational SC.
Research limitations: The methodology and presentation is conceptual, yet the tool can provide very useful interpretations for both researchers as well as management practitioners. Accessibility and availability of data are the main limitations affecting which model will be applied. Procedural steps towards implementing the said decision
support tools have been demonstrated through empirical research. The decision support tools tools have neither been
validated by practical case study nor have these been tested for assessing their reliability.
Originality/value: This work articulates various approaches for supply chain performance evaluation considering multiple evaluation criteria (subjective evaluation indices), with a flexibility to modify and analyze using the available data sets collected from a group of experts (decision-makers). The approaches of performance evaluation index system are attempted due to structure and fuzzy (as well as grey) sets. The work is aimed at operational researchers, engineers and special managers.

Item Type:Thesis (MTech by Research)
Uncontrolled Keywords:Decision Support Systems (DSS); supply chain (SC) performance appraisement; benchmarking; Fuzzy logic; grey theory; Fuzzy-grey relation theory; MOORA: Multi-Objective Optimization by Ratio Analysis
Subjects:Engineering and Technology > Mechanical Engineering > Production Engineering
Divisions: Engineering and Technology > Department of Mechanical Engineering
ID Code:6575
Deposited By:Hemanta Biswal
Deposited On:09 Dec 2014 10:40
Last Modified:09 Dec 2014 10:40
Supervisor(s):Datta, S and Patel, S K

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