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This study aims to clarify the influence of different CEO’s political orientation (liberal/conservative) and corporate political activity on ESG performance, considering contingencies related to CEO attributes and corporate governance mechanisms.

Using a sample of 131 companies from the Standard and Poor’s 500 index, this study employs fuzzy-set Qualitative Comparative Analysis (fs/QCA) to analyze combinations of conditions (i.e. configurations) that lead to greater ESG (i.e. environmental, social, and governance) performance.

Drawing on the upper echelon theory and the theory of social exchange, the findings show that different CEO’s political orientation (liberal/conservative) can contribute to ESG performance, depending on the combination of conditions. Furthermore, the results emphasize the importance of corporate political activity as a core condition to enhance ESG performance.

Taking a configurational approach, this study explores combinations of conditions that explain ESG performance, including CEO’s political orientation and corporate political activities as antecedent conditions. Unlike past research, this study examines possible complementarities between these two conditions and assumes that different CEO’s political orientation can have a positive influence on ESG performance, depending on the combination of conditions.

This paper aims to reconstruct the spatially varying orthotropic conductivity based on a two-dimensional inverse heat conduction problem described by a partial differential equation (PDE) model with mixed boundary conditions. The proposed discretization uses a highly accurate technique and allows simple implementations. Also, the authors solve the related inverse problem in such a way that smoothness is enforced on the iterations, showing promising results in synthetic examples and real problems with moving heat source.

The discretization procedure applied to the model for the direct problem uses a pseudospectral collocation strategy in the spatial variables and Crank–Nicolson method for the time-dependent variable. Then, the related inverse problem of recovering the conductivity from temperature measurements is solved by a modified version of Levenberg–Marquardt method (LMM) which uses singular scaling matrices. Problems where data availability is limited are also considered, motivated by a face milling operation problem. Numerical examples are presented to indicate the accuracy and efficiency of the proposed method.

The paper presents a discretization for the PDEs model aiming on simple implementations and numerical performance. The modified version of LMM introduced using singular scaling matrices shows the capabilities on recovering quantities with precision at a low number of iterations. Numerical results showed good fit between exact and approximate solutions for synthetic noisy data and quite acceptable inverse solutions when experimental data are inverted.

The paper is significant because of the pseudospectral approach, known for its high precision and easy implementation, and usage of singular regularization matrices on LMM iterations, unlike classic implementations of the method, impacting positively on the reconstruction process.

In 2011, Brazil introduced a national pay-for-performance (P4P) scheme called the National Program for Improving Primary Health Care Access and Quality (PMAQ), rolled out over three cycles and reaching more than 5,000 municipalities and 40,000 family health teams (FHTs). There is little evidence on how the PMAQ was implemented locally and whether this variation in implementation affects performance, particularly, in terms of work process indicators. This study compared different cases of municipal-level PMAQ implementation (bonuses paid or not to FHTs) over the last two program cycles to analyze the quality of the work processes, actions and services of FHTs.

This was a cross-sectional analytical study using secondary data from an external evaluation of the Brazilian PMAQ. In total, 27,500 FHTs participated in the evaluation. They were divided into four clusters based on whether or not municipalities paid bonuses to workers during cycles 2 and 3 of the program (2013–2019). Variables regarding work processes, actions and services were classified as “Quality Assurance – QA” or “Continued Quality Improvement – CQI”, and an individual score was assigned based on the average score of each variable.

The four clusters displayed an increase in overall QA and CQI scores between the two program cycles; though this increase was small between the set of primary health care teams that received bonuses and those that did not.

This paper contributes to bridging the gap in the scientific literature for evaluative studies on the relationship between direct payment for performance to health professionals and better quality actions and services in low and middle-income countries.