Relationship between lean tools and operational and environmental performance by integrated ISM–Bayesian network approach

Purpose: Existing studies suggested that there is a nonlinear relationship between lean production adoption and organizational performance. Lean production adoption is a gradual process, and the application status of lean tools will affect enterprise performance. The existing literature has insufficiently explored the nonlinear relationship of the lean tools application status on operational performance and environmental performance using the same theoretical framework. A combination approach of interpretative structural modeling (ISM) and Bayesian networks was proposed in this paper, which was used to analyze the complex relationship between lean tools application status with operational and environmental performance. Design/methodology/approach: ISM was used to analyze the inter-relationship of 17 lean tools identified from the lean literature and construct the lean tools structure model providing reference for building Bayesian network. By calculating the prior and conditional probabilities within the lean tools and between the lean tools with the operational and environmental performance, a Bayesian simulation model was constructed and used to analyze the performance outcomes under different lean tools application status. Findings: The performance simulation result – representing by the probability of three performance levels as good, average and poor – shows inconsistent changes with the changing of lean tools application status. By comparing the changes of operational performance and environmental performance, it can be found that environmental performance is less sensitive to the change of lean tools application status than operational performance. Originality/value: Using the integrated ISM–Bayesian network approach, the results indicated a nonlinear relationship between lean tools with operational and environmental performance and provided a reference for the exploration of the nonlinear relationship between lean tools and performance. This research further calls for exploring the S-curve relationship between lean tools and environmental performance.