The manufacturing sector of any country is considered as the backbone of any economy, in Malaysia it is the second largest sector in economic contribution and highest in productivity level. The aim of this study is to provide a reliable tool to assess the overall supply chain risks of Malaysian manufacturing through a systematic process. | A novel classification of supply chain risks: Scale development and validation Journal of Industrial Engineering and Management JIEM, 2019 – 12(1): 201-218 – Online ISSN: 2013-0953 – Print ISSN: 2013-8423 A Novel Classification of Supply Chain Risks: Scale Development and Validation Muhammad Saeed Shahbaz , Raja Zuraidah RM Rasi , MD Fauzi Bin Ahmad Universiti Tun Hussein Onn Malaysia (Malaysia) , rzuraida@, mohdfauzi@ Received: November 2018 Accepted: January 2019 Abstract: Purpose: Supply chain has become an essential element for any organization but risks are the major obstacles in achieving the performance even it can disrupt not only the organization but a whole system. Thus, it is compulsory to manage the risks efficiently and effectively. Risk cannot be managed until properly identified, there are numerous studies on risk identification, after comprehensive literature, it has been revealed that the study that identifies overall supply chain risk is scaring. The manufacturing sector of any country is considered as the backbone of any economy, in Malaysia it is the second largest sector in economic contribution and highest in productivity level. The aim of this study is to provide a reliable tool to assess the overall supply chain risks of Malaysian manufacturing through a systematic process. Design/methodology/approach: A detail literature review has been done for categorization of overall supply chain risk sources. Then an instrument has been developed from a pool of items. The questionnaire was purified through pretesting, pilot testing (by the exploratory view) and reliability and validity tests. The data were collected by email from Federation of Malaysian Malaysia (FMM-2017) through systemic probability sampling. Total 132 final responses have been considered for exploratory factor analysis through SPSS 23. .
