This paper aims to propose improvements to plastic waste management performance via Partial Least Squares Structural Equation Modeling (PLS-SEM) using a survey’s structured questionnaire and hypothesis testing. The methodology has been applied to the metropolis of Salvador, Brazil’s third most populated city, although it can be used for other cities worldwide. All the indicators, constructs, and hypotheses concerning collection, sorting, and recycling came from a literature review. The dependence of the performance on efficiency, effectiveness, the municipality’s socioeconomic aspects, and the municipality’s infrastructure was evaluated, and both academic and practitioner public representatives were surveyed. Since almost double the minimum number of respondents answered the questionnaire and the PLS-SEM statistics showed that the modeling presents consistency, the discussion is relevant. The final results show that the respondents rated the volume of processing to be slightly more significant than the market maturity for the effectiveness of plastic waste management, which in turn contributes to performance. Once the positive influence of the municipality’s infrastructure on performance has also been verified, the Deposit-Return Systems (DRSs) should be considered for improvement, in addition to an increase in the availability of selective collection systems, contributing to the growth of both the recycling rate and business profitability, reflections of performance.

This paper aims to propose improvements for plastic waste management in Salvador – the Brazilian third most populated metropolis – via Partial Least Squares Structural Equation Modeling (PLS-SEM). All indicators, constructs, and hypotheses regarding collection, sorting, recycling, and disposal in the proposed PLS model were derived from the literature review, and the dependence of the performance construct on efficiency, effectiveness, municipality's socioeconomic aspects and municipality infrastructure is evaluated. Academic and practitioner publics were surveyed, and after analysis in both SmartPLS and RStudio software, suggestions for improvement regarding plastics recycling rate, market maturity, and infrastructural aspects for optimized reverse logistics were made. Since almost double the minimum number of respondents answered the survey questionnaire and the PLS-SEM statistics showed that the modeling presents consistency, the discussion is relevant. The model can and will evolve, but examples of suggested improvement are the installation of Deposit-Return Systems (DRS) in parks, streets, and avenues for increasing selective collection and the direct purchasing of waste from residents by municipal administration, compensating them with vouchers for food. The model can be a basis for other cities worldwide sharing analogous characteristics. By considering it, organizations can contribute to both reduced Greenhouse Gas (GHG) emissions and reduced terrestrial pollution.

Purpose: This study aims to suggest improvements to the performance of a developing plastic waste management (PWM) system by integrating partial least squares structural equation modeling (PLS-SEM), interpretive structural modeling (ISM),and matrix of impact cross-multiplication applied to classification (MICMAC). Design/methodology/approach: Data were collected through questionnaires targeting recycling stakeholders. The first asked about the importance of various indicators from the literature; the second asked about the relationships between constructs. Findings: Urban infrastructure and organizational features correlate with effectiveness and are driving constructs influencing the dependent constructs of efficiency, effectiveness and performance. Efficiency correlates with performance, highlighting the importance of cost-effective recycling. Research limitations/implications: This integration eliminates statistically insignificant indicators and constructs, focusing on key performance drivers. The required sample size is fulfilled, but the methodology’s application to Brazil may restrict the results’ generalizability to PWM systems in developing countries. Practical implications: To enhance PWM systems’ performance, municipal authorities should increase the provision of recycling bins, voluntary drop-off points, eco-points and papa-plásticos. Organizations should focus on personnel training, marketing and advertising and incentive-based schemes. Social implications: Improving PWM systems reduces pollution for people’s health and increases employment. Efficient waste separation and higher-performance recycling foster sustainability. Originality/value: This novel mixed-methods research offers insights towards SDGs 11, 12, and 13, contributing to performance-driving factors under plans like Planares in Brazil, given the methodology’s applicability.