Qualitative Modeling of Offshore Outsourcing Risks in Supply Chain Management and Logistics

What are the biggest challenges facing those managing supply chains? Qualitative Modeling of Offshore Outsourcing Risks in Supply Chain Management and Logistics is intended to benefit the stakeholders in client organizations by raising their understanding and awareness about the most dominant risks. This will equip supply chain managers to give more emphasis to mitigating these risks. It further showcases the development and validation of a conceptual framework that depicts the relationship among key offshore outsourcing risks. The text explores modelling various risks which disrupt the automotive supply chain and cybersecurity breaches in digital supply chains.

This book:

• Covers structural modelling of key offshore outsourcing risks for understanding their driving and dependence power
• Presents a conceptual framework and hierarchical structural model for perfect order fulfilment in both upstream and downstream supply chains
• Explores the challenges in handling operational risks associated with poor delivery performance or service quality
• Models dimensions which affect vendor selection in offshore outsourcing environment
• Investigates cultural influences on the management of geographically distributed operations in offshore outsourcing
• Addresses the workforce-related offshore outsourcing risk such as loss of key professionals
• Discusses the risk associated with selection of location, viz. distribution centres/warehouses in supply chain and logistics
• Models dimensions related to cybersecurity breaches in digital supply chains because of IT offshoring

It is aimed at senior undergraduate and graduate students, and academic researchers in the fields of manufacturing engineering, industrial engineering, mechanical engineering, supply chain management and production engineering.

Dr. Rajiv Kumar Sharma is presently working as Associate Professor in Mechanical Engineering department at NIT Hamirpur. Also, served as Head of Department of Mechanical Engineering. He has done Bachelor's degree in Mechanical Engineering with (Hons), Master's degree in Industrial and Production Engineering with Gold Medal from Thapar University Patiala. Thereafter, obtained his doctoral degree (PhD) from Indian Institute of Technology; IIT Roorkee, Uttrakhand. Till so far he has guided 06 PhD thesis, 28 M.Tech Thesis and More than 70 U.G projects in various fields of engineering. He has research and teaching experience of more than 20 years and about 100+ publications in International journals of repute such as Int Jou of Prod Res., Int Jou Qlty Reliab. Mgmt, Indl Mgmt Data Syst., Int Jou Syst. Sci, Jol Loss Prev. in Process Indust., Reliab. Engg. Syst. Safety, Quali. Reliab. Engg Intern., Int. Jou of Mfg Tech Mgmt, Total Quality Management & Business Excellence, Proceedings of the Institution of Mechanical Engineers, Part B & C: Journal of Engineering Manufacture published by well known academic publishers such as Elsevier, Taylor & Francis, Wiley, Emerald, Sage and Inder-science. He has delivered expert talks in faculty development programs, short term training programs under the aegis of AICTE ATAL ACADEMY organized by NIT Warangal, NIT Calicut, MNIT Jaipur, NIT Jalandhar, NIT Hamirpur, SVNIT Surat. He is also on Editorial Board of many reputed Journals such as International Journal of Quality and Reliability Management, TQM Journal, Emerald Publishers; International Journal of Strategic Business Alliance, Inderscience Publishers, Advances in Production Engineering & Management, Production Engineering Institute (PEI), University of Maribor, Maribor, Slovenia European Union (EU). He has authored a book on Quality Management Practices in MSME Sectors for practicing engineers and research scientists published by Springer. He has completed sponsored project from UGC and DST. His research interests include Supply chain and Logistics, Flexible manufacturing systems, statistical quality control system reliability and maintenance, quality engineering, six sigma, lean manufacturing and Industry 4.0.