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Lightweight building systems have emerged as alternatives to reduce the high environmental impact of conventional masonry. However, in subtropical climates, the low thermal inertia of lightweight envelopes negatively affects energy performance. The purpose of this paper is to investigate the thermophysical parameters that influence heating and cooling energy consumption in lightweight residential buildings under subtropical climates and develop a model to predict these parameters using statistical and machine learning tools.

A database was created with computer simulation data on the energy performance of 2048 building conditions generated by factorial combination of 10 parameters. Sensitivity analysis was performed to identify which parameters contribute most to energy performance indicators. Subsequently, decision trees were created using a classification and regression tree (CART) algorithm to visualize parameters and improve energy performance indicators, particularly cooling energy consumption.

Low thermal transmittance and ground contact are interesting strategies for low thermal capacity buildings. Furthermore, the findings showed that relying only on the most influential properties does not ensure good energy performance; rather, it is the adequate combination of envelope properties that leads to good energy efficiency. The tree developed by CART can be used as a guide to assist designers and researchers in the initial selection of building envelopes, demonstrating the impact of each choice on electrical energy consumption for indoor climate control.

By adopting a global approach to assess the thermal performance of lightweight buildings, this study makes a significant contribution to synthesizing the results of a complex and time-consuming methodology into a guide for optimizing envelope design decisions and directing efforts and resources toward efficient strategies.

The present research aims to understand how the literature on lean leadership is currently structured. For this, the thematic subdivisions within the subject (thematic clusters) are analyzed as well as the networks between authors and the authors' countries and the chronological co-occurrence of terms over the years.

The research strategy chosen was a bibliometric analysis conducted with documents collected from the Scopus scientific database. After screening, 192 documents were analyzed using the Vosviewer software.

The main result is related to identifying four thematic clusters. The first cluster is connected to the manufacturing and supply chain industry, and this showed an increasing concern with sustainability, agile manufacturing and digitalization. The second is related to small and medium-sized companies in which Lean concepts, often associated with Six Sigma ideas, present as differentials for competitive advantage. The third one is associated with the civil construction segment, in which there is a great need for cultural and organizational change. The fourth cluster focuses on health organizations. In all clusters, leadership plays a key role.

Besides the contributions to the literature on the theme, this study provides interesting insights for managers regarding the path the managers' sectors are taking in the Lean leadership context.

There are no studies that critically examine Lean leadership literature. This research identifies clusters on the theme, showing how Lean leadership is being addressed by international research.