Analysis of supply chain complexity drivers for Indian mining equipment manufacturing companies combining SAP-LAP and AHP. (December 2018)

• Record Type: Journal Article
• Authors: Chand, Pushpendu; Thakkar, Jitesh J.; Ghosh, Kunal Kanti
• Is Part Of: Resources policy. Volume 59(2018)
• Page Start: 389
• Page End: 410
• Publication Date: 2018-12
• Subjects: Mining equipment -- Analytic hierarchical process -- Supply chain complexity driver -- Supply chain management; Mines and mineral resources -- Periodicals; Ressources minérales -- Périodiques; Ressources naturelles -- Gestion -- Périodiques; Environnement -- Politique gouvernementale -- Périodiques; 333.8
• DOI: 10.1016/j.resourpol.2018.08.011
• Languages: English
• ISSNs: 0301-4207

Abstract

Abstract: In today's world supply chain has become more complex due to the multiplicity of drivers created by globalization, global geopolitical risk, technological disruption, market uncertainty, mass-customization and changing laws and regulations. Supply Chain Complexity (SCC) is one of the most difficult problems in today's global supply chains and assumed as the key impediment to business performance. SCC has the significant adverse impact on competitiveness, cost efficiency, customer satisfaction, product innovation and market share. It is imperative for the focal firm and its supply chain managers to know SCC drivers causing supply chain complexity. Identification and prioritizing of SCC drivers are required for effective monitoring and controlling of supply chain management. SCC drivers can be categorized based on the origin of their generation as upstream, operational, downstream and external. This paper presents the study conducted in leading earthmoving and mining equipment manufacturing firms in India, to understand the supply chain complexities for off-road & mining equipment industries. Qualitative situation-actors-process (SAP) and learning-action-performance (LAP) model has been applied to understand and analyze the concept of supply chain complexity drivers and its dynamic behavior. Quantitatively multi-criterion decision making (MCDM) is used in prioritizing SCC drivers due to the subjectivity of drivers. An AHP (Analytic Hierarchy Process) study has also been done to quantify and prioritize SCC drivers for managerial decision making. This study contributes towards developing a priority ranking of SCC drivers based on its impact on overall SCC which have significant importance in supply chain strategic planning. The current research investigates evolving SCC drivers like supplier resourcing risk, supplier competence, regional strategies, shortening product life-cycle, changing customer service expectation which were not adequately addressed in existing literature. Our research findings provides practical insights to managers in understanding the role of SCC drivers like market uncertainty and risk, changing laws and regulations, constant change in customer requirement, multiplicity of customers, forecast inaccuracy, sustainable supply chain practices in the overall outcome of ranking. The outcome of this study also enriches the existing literature of SCC with practitioners' insight from manufacturing industry. Highlights: Supply Chain Complexity (SCC) is one of the most difficult problems in today's global supply chains. This research investigates SCC drivers and sub-drivers in developing priority ranking. Research findings provides practical insights to managers in understanding the role of SCC drivers. Study enriches existing literature of SCC with practitioners' insight from manufacturing industry.