The COVID-19 pandemic and the quarantine period determined that university students (human resource) in Mexico had adopted the online class modality, which required them to adapt themselves to new technologies and environmental conditions that are different from classrooms at their university. Specifically, these new environmental conditions can be uncomfortable and have an impact on the students’ academic performance. Consequently, the present study aims to determine the impact that the lighting, noise, and temperature levels (independent variables) have on academic performance (dependent variable) in university students during the COVID-19 pandemic. To do this, a questionnaire was developed, which was applied to 206 university students online, and a structural equation model was built that integrates the four variables through three hypotheses, which were statistically validated through the partial least squares method. Results showed that temperature, lighting, and noise have significant direct effects on university students’ academic performance. As a conclusion, it was obtained that the three independent variables have an impact in the sustainability of university students (human resource).

Managers implement several Green Supply Chain Management (GSCM) practices to improve sustainability and economic performance, such as environmental management systems (EMS), eco-design (ED), source reduction (SR) and attending to external environmental management (EEM) requirements; however, the relationship among them requires a deep study. This paper reports the case of the Mexican maquiladora industry, analyzing the main relationships among GSCM practices with environmental impact (EI) and environmental cost savings (ECS). The analysis reports three structural equation models (SEM) developed as simple, second-order, and mediating models. Those relationships are tested using 160 responses to a survey applied to the Mexican maquiladora industry and with partial least squares algorithms (PLS), where conditional probabilities for different scenarios in latent variables are also reported. Findings indicate that EMS has a direct effect on EI (β = 0.442) and ECS (β = 0.227), indicating that EMS reduces EI and cost associated with the production process; however, ED has no direct effect on EI (β = 0.019) and ECS ((β = 0.006), and it can be due to the maquiladora nature as foreign companies focused on manufacturing and not to product design.

Remanufacturing is a production practice that requires the work of producers, consumers, and the government. There are benefits associated with this production model, such as improving the environment, opportunities for cost savings, and others. However, it is essential to identify the factors that affect the possibility of acceptance of this production model. This research proposes a model based on different analysis methodologies and techniques of SEM (Structural Equations Modeling) and the method of PLS (Partial Least Squares). A total of 403 responses to the survey were collected from 1 November 2021 to 15 January 2022. For the data treatment, SPSS, Excel, and WarpPLS software were used to identify the variables, factors, and their direct and indirect effects among the latent variables, referring to a scheme focused on consumer perception based on the acquisition remanufactured products. This created model served as a reference to create and develop a design and repair strategy for White goods or similar products in handling, logistics, and repair. This design strategy was transformed into a business model based on a circular economy, particularly on a Product–Service System with social, economic, and environmental benefits for producers and consumers.