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Purpose This study aims to comparatively discuss the effect of lean manufacturing (LM) implementation in the manufacturing sectors of developing and developed countries. Design/methodology/approach An in-depth literature review focused on previous research published between 2015 and March 2020. The papers published by the databases such as Google Scholar, Scopus, ProQuest and Web of Science were used in the study. A total of 63 studies that focused on LM application in manufacturing industries in developing and developed countries were used in the research. Findings It was observed that LM improves operational performance for manufacturing organizations in developing and developed countries. Small and medium-sized enterprises in both developed and developing countries have difficulties transforming their organizations into lean organizations compared to large enterprises. Furthermore, the review also found that there seems to have been no paper had reported the negative impact of implementing LM in manufacturing industries in developing and developed countries from 2015 to March 2020. Research limitations/implications The study used research papers written between January 2015 and March 2020 and only considered manufacturing organizations from developed and developing nations. Practical implications The study provides more insight into LM implementation in developing and developed countries. It gives the LM practices and the implications of applying these practices in manufacturing organizations for developing and developed countries. Originality/value A preliminary review of papers indicated that this seems to be the first paper that comparatively studies how LM implementation has affected manufacturing organizations in developed and developing countries. The study also assessed the LM practices commonly used by the manufacturing industries in developing and developed countries.

The impact of Lean Manufacturing (LM) implementation on organizational performance is an ongoing discussion. The effect of implementing LM tools on operational performance across various industries in Zimbabwe, a country with an unstable real gross domestic product is evaluated. A structural model of LM that is aligned with the Toyota Production System (TPS) house was proposed. A structured survey questionnaire was used for the collection of data in identified companies. Of the 600 companies contacted, 214 useful responses were obtained implying a response rate of 35.6%. The structural and operational models were tested using the Statistical Package for Social Sciences and SmartPLS 3. The result indicated that operational performance was improved by implementing the selected LM tools.

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Background. Response time is viewed as a key performance indicator in most emergency medical services (EMS) systems. Objective. To determine the effect of increased emergency vehicle numbers on response time performance for priority 1 incidents in an urban EMS system in Cape Town, South Africa, using discrete-event computer simulation. Method. A simulation model was created, based on input data from part of the EMS operations. Two different versions of the model were used, one with primary response vehicles and ambulances and one with only ambulances. In both cases the models were run in seven different scenarios. The first scenario used the actual number of emergency vehicles in the real system, and in each subsequent scenario vehicle numbers were increased by adding the baseline number to the cumulative total. Results. The model using only ambulances had shorter response times and a greater number of responses meeting national response time targets than models using primary response vehicles and ambulances. In both cases an improvement in response times and the number of responses meeting national response time targets was observed with the first incremental addition of vehicles. After this the improvements rapidly diminished and eventually became negligible with each successive increase in vehicle numbers. The national response time target for urban areas was never met, even with a seven-fold increase in vehicle numbers. Conclusion. The addition of emergency vehicles to an urban EMS system improves response times in priority 1 incidents, but alone is not capable of the magnitude of response time improvement needed to meet the national response time targets.