An integrated fuzzy approach for prioritizing supply chain complexity drivers of an Indian mining equipment manufacturer

An integrated fuzzy approach for prioritizing supply chain complexity drivers of an Indian mining equipment manufacturer

The complexities in present day supply chain are numerous and are evolving due to globalization, customisation, innovation, flexibility, sustainability and uncertainties. The growing supply chain complexity results in negative consequences on cost, customer service and reputation. Managing supply ch...

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Bibliographic Details
Published in:Resources policy Vol. 51; pp. 204 - 218
Main Authors: Kavilal, E.G., Prasanna Venkatesan, S., Harsh Kumar, K.D.
Format: Journal Article
Language:English
Published: Kidlington Elsevier Ltd 01-03-2017
Elsevier Science Ltd
Subjects:
Analytic hierarchy process
Complexity
Criteria
Customer service
Customer services
Customers
Decision making
Flexibility
Fuzzy AHP
Fuzzy ISM
Fuzzy logic
Fuzzy PROMETHEE
Globalization
Hierarchies
Industrial equipment
Information dissemination
Information sharing
Innovations
Interdependence
Management
Manufacturers
Mining
Mining equipment
Mining industry
Prioritizing
Profitability
Program evaluation
Quality of service
Ratings & rankings
Reputations
Suppliers
Supply
Supply chain complexity drivers
Supply chains
Uncertainty
Visibility
India
Mining equipment
Supply chain complexity drivers
Fuzzy AHP
Fuzzy ISM
Fuzzy PROMETHEE
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Summary:The complexities in present day supply chain are numerous and are evolving due to globalization, customisation, innovation, flexibility, sustainability and uncertainties. The growing supply chain complexity results in negative consequences on cost, customer service and reputation. Managing supply chain complexity without compromising the profitability is a challenging task. Supply chain complexity (SCC) management involves identifying, prioritizing, measuring, analysing and controlling/eliminating the drivers of complexity. The SCC drivers denote number and variety of suppliers, customers, products, processes and uncertainties which are highly interdependent. Firms need to prioritize the drivers in order to manage and simplify SCC. Models and methods to prioritize the complexity drivers considering their interdependence are limited in literature. Prioritizing the complexity drivers requires a subjective approach and it is a multi criteria decision making (MCDM) problem. In this research, at first a fuzzy ISM (Fuzzy Interpretive Structural Modelling) is used to establish the interdependence of SCC drivers. A fuzzy AHP (Analytic Hierarchy Process) and fuzzy PROMETHEE (Preference Ranking Organization Method for Enrichment Evaluation) are then used to quantify and prioritize the complexity drivers considering the strength of interdependence obtained using the fuzzy ISM. A case example of a mining equipment manufacturer located in India is presented to illustrate the proposed approach. From the results it is identified that unreliability of suppliers, forecast inaccuracy, lack of visibility /information sharing and number/variety of processes are the significant drivers. [Display omitted] •An integrated fuzzy model to prioritize supply chain complexity (SCC) drivers for an Indian mining equipment manufacturer.•We identify 14 SCC drivers and use Fuzzy ISM to establish the contextual relation among the SCC drivers.•We use a fuzzy AHP and fuzzy PROMETHEE to prioritize the SCC drivers considering interdependence.•Supply base and internal manufacturing complexities are identified as the dominant SCC drivers for the case company.
ISSN:0301-4207
1873-7641
DOI:10.1016/j.resourpol.2016.12.008