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The imperative to conserve resources and minimize operational expenses has spurred a notable increase in the adoption of lean manufacturing within the context of the circular economy across diverse industries in recent years. However, a notable gap exists in the research landscape, particularly concerning the implementation of lean practices within the pharmaceutical industry to enhance circular economy performance. Addressing this void, this study endeavors to identify and prioritize the pivotal drivers influencing lean manufacturing within the pharmaceutical sector.

The outcome of this rigorous examination highlights that “Continuous Monitoring Process for Sustainable Lean Implementation,” “Management Involvement for Sustainable Implementation” and “Training and Education” emerge as the most consequential drivers. These factors are deemed crucial for augmenting circular economy performance, underscoring the significance of management engagement, training initiatives and a continuous monitoring process in fostering a closed-loop practice within the pharmaceutical industry.

The findings contribute valuable insights for decision-makers aiming to adopt lean practices within a circular economy framework. Specifically, by streamlining the process of developing a robust action plan tailored to the unique needs of the pharmaceutical sector, our study provides actionable guidance for enhancing overall sustainability in the manufacturing processes.

This study represents one of the initial efforts to systematically identify and assess the drivers to LM implementation within the pharmaceutical industry, contributing to the emerging body of knowledge in this area.

Assembly lines are widely employed in manufacturing processes to produce final products in a flow efficiently. The simple assembly line balancing problem is a basic version of the general problem and has still attracted the attention of researchers. The type-I simple assembly line balancing problems (SALBP-I) aim to minimise the number of workstations on an assembly line by keeping the cycle time constant.

This paper focuses on solving multi-objective SALBP-I problems by utilising an artificial bee colony based-hyper heuristic (ABC-HH) algorithm. The algorithm optimises the efficiency and idleness percentage of the assembly line and concurrently minimises the number of workstations. The proposed ABC-HH algorithm is improved by adding new modifications to each phase of the artificial bee colony framework. Parameter control and calibration are also achieved using the irace method. The proposed model has undergone testing on benchmark problems, and the results obtained have been compared with state-of-the-art algorithms.

The experimental results of the computational study on the benchmark dataset unequivocally establish the superior performance of the ABC-HH algorithm across 61 problem instances, outperforming the state-of-the-art approach.

This research proposes the ABC-HH algorithm with local search to solve the SALBP-I problems more efficiently.

This paper aims to present a model to incentivize sustainable performance (SUP) in small- and medium-sized tourism by strengthening inner relations to adapt to a complex environment.

The authors adopted the systemic approach complementing analytic, tourism, partial least squares path modeling (PLS-PM), social network analysis (SNA) and systemic approach tools as follows: frame the problem through the soft systems methodology and SNA and identify the conflicting relationships; apply PLS-PM to validate the model; and propose new interactions for small- and medium-sized enterprises conducive to SUP based on the viable system model.

Considering the results, the authors pinpointed factors and relationships managers can address to foster SUP, highlighting the need to reinforce feedback loops and reduce inconsistencies between primary operations with coordination and management mechanisms.

This work is limited to the organizational domain. Although the results apply to the Mexican context, this could be overcome using methodological complementarity to extend the ideas to other organizations.

This study invites discussing methods and viewpoints for rethinking SUP because of multiple factors. This requires adopting methodological complementarity to generate alternatives and reconfiguring inner organizational interactions.

The model captures minimum but sufficient components advising leaders about SUP. This proposal differs from previous studies because it suggests exploiting methodological complementarity to capture the insights of key operative actors to conceive the model. Hence, the authors suggest new relations among organizational factors so managers can develop strategies for adaptability.