| dc.description.abstract | Everyday, companies seek to improve their productive efficiency and, thus, increase their profitability and competitiveness. For both, there are several ways to discover the critical factors of competitiveness that may be present in various manufacturing sectors. Thus, the use of robust techniques to assess and measure these factors is essential to support decision making. This study aims to analyze the influence of the processes of continuous improvement and learning in terms of efficiency and production volume in a manufacturing company. To achieve the proposed objective, the research conducts a case study using Data Envelopment Analysis (DEA), combined with the Linear Regression test and the ANOVA test. At this stage, a conceptual model with four main hypotheses and eight secondary ones is formulated. To evaluate the DEA efficiency, the model uses Variable Scale Returns (VSR) with input orientation considering the main raw materials used by the company based on the total variable cost. The Linear Regression test performs the evaluation of the impact of the improvement process and learning efficiency (DEA). In turn, the ANOVA test evaluates the average efficiency of each production line for each year analyzed. The study is carried out longitudinally, by reviewing six years of manufacturing. The survey results show that only one of the production lines increased efficiency over time. In addition, the results indicate that two production lines have been impacted by the actions of improvement in the volume of production. Therefore, the variables related to Kaizen programs, to the hours of training and to employees ́ experience significantly influenced the model. It can be concluded that the projects focused on continuous improvement and learning were not sufficient to increase efficiency in two major production lines. Furthermore, the study shows that the production volume negatively impacts the efficiency of the production lines. With the analysis, it is possible to identify which factors are representative to increase production efficiency. Therefore, it can be conclude that the technology upgrade is an important factor to be followed by the company studied. | en |
