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This research investigates the barriers impeding innovation within small- and medium-sized enterprises (SMEs) in Brazil, exploring 54 innovation-related barriers categorized into six distinct groups to offer substantial insights and analyses pertinent to the decision-makers, researchers and SMEs.

This research employed a mixed quantitative and exploratory approach, utilizing fuzzy Delphi, fuzzy analytic hierarchy process (AHP) and fuzzy decision-making trial and evaluation laboratory (DEMATEL) methods. The fuzzy Delphi method confirmed the categories and barriers through quantitative analysis, the fuzzy AHP ranked the validated obstacles and the fuzzy DEMATEL method identified causal connections among the top-priority barriers.

Out of 54 barriers, 23 significantly impacted SMEs. The “Financing and Financial” category was the most significant barrier, with “Access to Financing” being the most critical impediment. The barrier with the most influence was “Instability of Fiscal Policies,” and the highest causal priority was “Survival of the Priority Business,” identifying the government’s unstable fiscal policy as the principal barrier confronting SMEs in Brazil.

The primary challenges for Brazilian SMEs center on financing, fiscal policies and maintaining ongoing operations. By addressing these barriers and fostering a resilient business environment, SMEs’ innovation capabilities and competitiveness can be enhanced, serving as key drivers for sustainable economic growth in fluctuating economic conditions. This study contributes to the literature by highlighting and validating the main barriers to SME innovation, providing highly relevant information about the innovation process.

The purpose of this research is to establish a robust numerical framework for the calibration of macroscopic constitutive parameters, based on the analysis of polycrystalline RVEs with computational homogenisation.

This framework is composed of four building-blocks: (1) the multi-scale model, consisting of polycrystalline RVEs, where the grains are modelled with anisotropic crystal plasticity, and computational homogenisation to link the scales, (2) a set of loading cases to generate the reference responses, (3) the von Mises elasto-plastic model to be calibrated, and (4) the optimisation algorithms to solve the inverse identification problem. Several optimisation algorithms are assessed through a reference identification problem. Thereafter, different calibration strategies are tested. The accuracy of the calibrated models is evaluated by comparing their results against an FE2 model and experimental data.

In the initial tests, the LIPO optimiser performs the best. Good results accuracy is obtained with the calibrated constitutive models. The computing time needed by the FE2 simulations is 5 orders of magnitude larger, compared to the standard macroscopic simulations, demonstrating how this framework is suitable to obtain efficient micro-mechanics-informed constitutive models.

This contribution proposes a numerical framework, based on FE2 and macro-scale single element simulations, where the calibration of constitutive laws is informed by multi-scale analysis. The most efficient combination of optimisation algorithm and definition of the objective function is studied, and the robustness of the proposed approach is demonstrated by validation with both numerical and experimental data.

Administrative processes play a crucial role in various sectors, often contributing to cost overruns and delays. While lean concept has been extensively applied in many industries, there is a recognized need for further research on the integration of lean in administrative processes. To address this research gap, this study aims to systematically analyse the implementation of lean in administrative processes, providing a sector-wise comparison to explore its prospects for the construction industry.

A systematic literature review was conducted by adapting the Preferred Reporting Items for Systematic Reviews and Meta-Analyses method. Eighty-six research papers are subjected to descriptive and content analysis on different tools applied in lean integrated administrative processes in health care, education, public administration and other sectors.

The research study reveals common lean tools irrespective of sector. Moreover, specific tools used for a particular sector are analysed. Out of the various lean tools and techniques, value stream mapping, 5S and Kaizen are highly acknowledged tools in every sector of lean intervention. Furthermore, ECRS is applied explicitly in the education sector. Furthermore, it is noted that Suppliers, Inputs, Process, Outputs and Customers (SIPOC), 5whys, load levelling and control charts are identical to administrative processes in lean health care. Furthermore, Spaghetti charts and Kaikaku are only adapted to administrative processes in the public administration sector, and causal loop diagrams are used explicitly in administrative processes in the construction sector.

This study contributes to research by developing a guideline to design lean intervention for a lean-integrated administrative process in any sector which still needs to be transformed into lean. Hence, this study will be a cornerstone for incorporating lean principles for administrative processes in construction sector.