An empirical model for identifying and controlling operational and environmental risks in spinning industry in an emerging economy

Abstract

Effective risk management has become more crucial than ever, given the strategic economic growth of the industrial sector. Diverse threats from various sources are simultaneously present in many industries. Like other industries, the spinning sector of Bangladesh is bestowed with numerous operational and environmental risks. However, from our knowledge, it is completely ignored by the researchers and management of this sector to identify and control those risks. This study's main motivation is to fill the knowledge gap by using a real-world case study to identify and quantify operational and environmental risks in the spinning industry. To quantify risk variables, the application of the fuzzy synthetic evaluation methodology is a completely new approach in the spinning industry, as well as in other industries. This method determines the probability and magnitude of each risk factor and risk group, as well as the overall risk. This study identifies sixteen operational and environmental risk variables within two risk groups. One of the key findings of this study is that air pollution from flying fibers, excessive noise, inappropriate materials handling, power failure, and frequent machine breakdown are the top five risk concerns. Another important finding is that the overall risk criticality value of this sector is high, with a value of 3.97, indicating a significant level of risk. The study also offered a cause-effect diagram to identify the leading causes of risks to manage those risks effectively in the future. Overall, this study will assist real-life practitioners in identifying, ranking, managing, and controlling operational and environmental hazards in the Bangladeshi spinning sector towards minimizing such hazards and promoting cleaner production.