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An integrated fuzzy approach for prioritizing supply chain complexity drivers of an Indian mining equipment manufacturer
یک رویکرد فازی یکپارچه برای اولویت دادن به رانندگان پیچیدگی زنجیره تامین یک تولید کننده تجهیزات معدن هند-2017 The complexities in present day supply chain are numerous and are evolving due to globalization, customisa
tion, 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.
Keywords: Supply chain complexity drivers | Fuzzy ISM | Fuzzy AHP | Fuzzy PROMETHEE | Mining equipment |
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