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The purpose of this study is to present validation evidence of a Portuguese version of the Multidimensional Work Motivation Scale, an instrument within the framework of the Self-Determination Theory, suitable for both Brazil and Portugal.

The current study demonstrates the suitability of this version in both Portugal (N = 999) and Brazil (N = 720). The authors applied confirmatory factor analyses (CFA) and tested the invariance between samples.

Results from CFA found the same structural dimensions as in the original study, invariant across both samples. Convergent and discriminant validity were shown through correlations between motivation subscales with affective commitment and emotional exhaustion.

Overall, the data provided strong evidence for the reliability and validity of the Portuguese version of the scale and reinforces the instrument as a cross-culturally valid measure of work motivation.

O objetivo deste estudo é apresentar evidências de validação de uma versão portuguesa da Escala Multidimensional de Motivação para o Trabalho, um instrumento enquadrado na Teoria da Autodeterminação, apropriado para utilização no Brasil e em Portugal.

O presente estudo demonstra a adequação desta versão da escala tanto em Portugal (N = 999), quanto no Brasil (N = 720). Realizámos Análise Fatorial Confirmatória e testámos a invariância da medida entre as amostras.

Os resultados da Análise Fatorial Confirmatória mostram a mesma estrutura fatorial encontrada no estudo original, assim como invariância entre as presentes amostras. As validades convergente e discriminante foram evidenciadas pelas correlações com as escalas de comprometimento organizacional afetivo e exaustão emocional.

Em geral, os dados mostraram forte evidência de confiabilidade e validade da versão da escala para português e reforça a validade intercultural desta medida de motivação para o trabalho

motivação para o trabalho, Escala multidimensional de motivação para o trabalho, Teoria da autodeterminação.

Artigo de pesquisa

El objetivo de este estudio es presentar evidencia de validación de una versión portuguesa de la Escala Multidimensional de Motivación Laboral, un instrumento en el marco de la Teoría de la Autodeterminación, adecuado tanto para Portugal como para Brasil.

El presente estudio demuestra la adecuación de esta versión de la escala tanto en Portugal (N = 999) como en Brasil (N = 720). Realizamos un análisis factorial confirmatoria y probamos la invariancia de medición entre muestras.

Los resultados del análisis factorial confirmatorio muestran la misma estructura factorial encontrada previamente en el estudio original, así como la invariancia entre las medidas. La validez convergente y discriminante se mostró mediante correlaciones con las escalas de compromiso organizacional afectivo y de agotamiento emocional.

En general, los datos mostraron una fuerte evidencia de confiabilidad y validez de la versión en portugues de la escala y refuerza la validez intercultural de la medida de motivación laboral.

motivación laboral, Escala multidimensional de motivación labora, Teoría de la autodeterminación

Artículo de investigación

Factors like bid price, submission time, and number of bidders influence the procurement process in public projects. These factors and the award criteria may impact the project’s financial compliance. Predicting budget compliance in construction projects has been traditionally challenging, but Machine Learning (ML) techniques have revolutionised estimations.

In this study, Portuguese Public Procurement Data (PPPData) was utilised as the model’s input. Notably, this dataset exhibited a substantial imbalance in the target feature. To address this issue, the study evaluated three distinct data balancing techniques: oversampling, undersampling, and the SMOTE method. Next, a comprehensive feature selection process was conducted, leading to the testing of five different algorithms for forecasting budget compliance. Finally, a secondary test was conducted, refining the features to include only those elements that procurement technicians can modify while also considering the two most accurate predictors identified in the previous test.

The findings indicate that employing the SMOTE method on the scraped data can achieve a balanced dataset. Furthermore, the results demonstrate that the Adam ANN algorithm outperformed others, boasting a precision rate of 68.1%.

The model can aid procurement technicians during the tendering phase by using historical data and analogous projects to predict performance.

Although the study reveals that ML algorithms cannot accurately predict budget compliance using procurement data, they can still provide project owners with insights into the most suitable criteria, aiding decision-making. Further research should assess the model’s impact and capacity within the procurement workflow.

Previous research predominantly focused on forecasting budgets by leveraging data from the private construction execution phase. While some investigations incorporated procurement data, this study distinguishes itself by using an imbalanced dataset and anticipating compliance rather than predicting budgetary figures. The model predicts budget compliance by analysing qualitative and quantitative characteristics of public project contracts. The research paper explores various model architectures and data treatment techniques to develop a model to assist the Client in tender definition.

Based on the goal content theory (GCT), the purpose of this paper is to focus on the essence of goals and examine the associations between different work goal contents (intrinsic and extrinsic goals) and work performance.

The data were collected from 279 employees and their immediate supervisors, and the theoretical hypotheses were tested by correlation and hierarchal regression analyses.

The results of the analyses showed that intrinsic goal content positively predicted task performance, dedicative performance, interpersonal performance, and adaptive performance and that extrinsic goal content positively predicted the task performance and adaptive performance; intrinsic goals were also found to enhance the relationship between extrinsic goals and task performance.

The contribution of the current study is that it explores whether both extrinsic goals and intrinsic goals can contribute to predicting work performance. Moreover, different from previous studies that focus on discussing the separate effects of intrinsic and extrinsic goals on outcomes, the authors aim to study the interaction effect between these goals, which enriches GCT.

Despite rising incomes and reduction of extreme poverty, the feeling of being poor remains widespread. Support programs can improve well-being, but they first require identifying who are the households that judge their income is insufficient to meet their basic needs, and what factors are associated with subjective poverty.

Households report the income level they judge is sufficient to make ends meet. Then, they are classified as being subjectively poor if their own monetary income is inferior to the level they indicated. Second, the study compares the performance of three machine learning algorithms, the random forest, support vector machines and least absolute shrinkage and selection operator (LASSO) regression, applied to a set of socioeconomic variables to predict subjective poverty status.

The random forest generates 85.29% of correct predictions using a range of income and non-income predictors, closely followed by the other two techniques. For the middle-income group, the LASSO regression outperforms random forest. Subjective poverty is mostly associated with monetary income for low-income households. However, a combination of low income, low endowment (land, consumption assets) and unusual large expenditure (medical, gifts) constitutes the key predictors of feeling poor for the middle-income households.

To reduce the feeling of poverty, policy intervention should continue to focus on increasing incomes. However, improvements in nonincome domains such as health expenditure, education and family demographics can also relieve the feeling of income inadequacy. Methodologically, better performance of either algorithm depends on the data at hand.

For the first time, the authors show that prediction techniques are reliable to identify subjective poverty prevalence, with example from rural China. The analysis offers specific attention to the modest-income households, who may feel poor but not be identified as such by objective poverty lines, and is relevant when policy-makers seek to address the “next step” after ending extreme poverty. Prediction performance and mechanisms for three machine learning algorithms are compared.

The development of the Amazon region depends on the organisation and improvement of production chains able to benefit forest species and animals. The purpose of this paper is to map and categorise the studies developed on the Arapaima gigas, a commercialisable fish native to the Amazon, responding to the following research questions: first, which links of the production chain have most of the studies on the pisciculture of the Amazon region? Second, is environmental performance being approached in studies on production chains in the Amazon region? To reach the objective, the authors used the systematic literature review (SLR) method. The authors analysed a sample of 121 articles published in 95 journals between 1981 and 2018. The research contains bibliometric and contents analyses. The main conclusions include the identification of various possibilities of studies throughout the different production chains in the Amazon region; the multidisciplinarity of research on a single species in the Amazon region; the importance of empirical studies in the construction of knowledge about the natural behaviour of the species; the need for integration and sharing of knowledge to create an efficient and competitive production chain. As a limitation, this study encompasses a broad spectrum of issues in the literature, therefore, it was only possible to offer a general overview of these issues. At the same time, this broad and intentional approach presents a comprehensive framing of the themes and phenomena that occur at each link of the production chain of Amazon fish farming.

This research consists in an SLR with organised, transparent and replicable procedures as recommended in the literature (Littell et al., 2008). The SLR is suited to the mapping of areas where there is a high level of uncertainty and new studies are necessary (Petticrew and Roberts, 2006). This research method is especially useful when dealing with a large volume of information (Tranfield et al., 2003). The use of SLR limits researcher bias by trying to evaluate and select relevant studies on the study theme (Petticrew and Roberts, 2006).

There are a number of possibilities for studies of the different production chains in the Amazon region; the results of mapping the production chains help to prioritise “what” should be researched in the Amazon region to promote more effective impacts for all stakeholders; research on pisciculture in the Amazon region can be used as a diagnostic tool for public policy formulators; the development of corporate environmental management is intrinsically linked to the process of analysis and understanding of the operations and costs that arise in different links of the production chain.

As a limitation, this study encompasses a broad spectrum of issues in the literature, therefore, it was only possible to offer a general overview of these issues.

In terms of practical implications, it is possible to note that the dispersion of themes found in this study confirms the plurality of the richness of the Amazon and suggests that research institutions should be able to commit to the drafting of integrated planning of science, as well as compilation of the results reached. It is also important to highlight Brazil’s role in the leadership of research in the Amazon region compared to other countries.

The aim of the paper was twofold: to supply a focussed review of the literature on the production chain of a species in Amazon pisciculture and to identify a research agenda capable of overcoming the gaps that impede the development of this chain. More specifically, this study reviewed the available research on the chain in question to analyse the links that have the largest volume of studies and to orient future research.

The practice of field burning has been used for many years in the south regions of Brazil as an ideal way to maintain pastures. The purpose of this paper is to understand if such activity is logically explicable or if it is the result of a cultural reality, being “prisoner” of this technique because of path dependence, within the paradigm of the path dependence theory.

This present research is exploratory. The use of cases study was the most appropriate technique to explore the field burning practices and their impact in this specific region of Brazil, while describing its context, for which limits are not clearly defined. Thus, this research carries out a multi-case study that provides a greater perception than a single case and has an identical methodological structure.

This paper analyzed the reasons why the producers insist with the procedure and identified these reasons are not merely economical. The study demonstrates a clear path dependent process and it became obvious that once the technique is part of the family use history, it anchors a strong conviction that field burning is actually the best technique to be used for land maintenance.

This work suggests a need for other specific researches to substantially complement field burning practices to other phenomenon.

The fact that alternative techniques are rejected, giving priority to field burning, it may suggest that other situations and practices may be tied to inadequate or less profitable technologies as well (milk, confined raising, pasturing). The study raises the question on the validity of such practice as a paradigm of reason and pragmatism, or as a “Platoons Cavern” in which they are “trapped” in their decision process developed over time.

Presence and implications of environmental laws, which tend to be observed by the producers much more because they fear punishment than because they really understand the benefits of its application; showing the government’s failure in teaching and informing the producers about environmental laws.

This study aims to identify opportunities and constraints of community forestry in the context of forest decentralization in Cameroon and what can be capitalized on for sound REDD+ design and implementation.

A qualitative approach to data collection was used through content analysis of 1994 forestry law, reports and publications related to decentralized forest management, community forestry and REDD+ in Cameroon. Principles that govern community forest and REDD+ were highlighted and opportunities and constraints of community forestry for REDD+ projects were discussed.

Community forestry was developed principally to protect forests in order to support the subsistence and income-generating extractive activities of forest-dependent communities. Community forestry governance arrangements were not designed with the objective of achieving verifiable emissions reductions or carbon stock values. Hence, existing community forestry institutions may not address all the specific demands of REDD+ programs. However, existing community institutions and practices can be strengthened or modified to align better with climate change mitigation goals and to achieve REDD+ objectives in community forestry sites. On the other hand, REDD+ was developed principally to mitigate climate change by reducing emissions from deforestation and forest degradation principally within developing countries where the livelihoods of forest-dependent people are a central component of all forest management policies. However, despite fundamental differences between community forestry and REDD+, there is substantial synergy between their objectives, and the dual forest conservation and livelihood development focus of both programs means that policies that strengthen and support existing community forestry institutions and sites will advance REDD+ objectives. As such, REDD+ will likely to be more successful if it builds on lessons learned from community forestry.

This paper demonstrates how REDD+ is more likely to succeed if it builds on the lessons learned from community forestry over the past 20-plus years in Cameroon. It also discusses how REDD+ can benefit from community forestry and how some of the many challenges related to community forestry can be directly addressed by the REDD+ mechanism. Further, this paper also argues how the congruence between community forestry and REDD+ can effectively facilitate the direct use of community forestry as a tool to achieve REDD+ goals.

This paper seeks to summarize humanity's growing appraisal of cumulative transgressions against nature and how these may be proving reversible.

The paper describes some of the current literature on environmental failure and the reasons therefor, and what, in global terms, activists are doing to rectify systemic breakdown.

The wrecking of nature is not new, but it is only recently that the conservationists, scientists, engineers and political activists of civil society have undertaken repairs and begun to meet the challenges of maintenance.

The application of rational, well‐intended corrective strategies (motivated beyond moralizing) are shown to undo some of the past's grossest misdemeanors.

Aside from oil, the Nigerian economy is largely agrarian, which is rain-fed. Hence the criticality of understanding climate change and its impact on agricultural output is more pressing than ever. This is in line with Sustainable Development Goal 13 which is to take urgent action to combat climate change and its impacts. Regardless, Nigeria has in the past five decades experienced a significant increase in temperature, in the range of 10 to over 30 degree Celsius. Therefore, managing the effect of climate change on agricultural output now has the colouration of a developmental challenge.

In light of this, this study gives due consideration to the impact of climate change on agricultural output between the years 1986 and 2015. For the purpose of analysis, descriptive statistics, unit root test and the ordinary least square (OLS) estimation technique were employed.

Findings from the study reveal that the average annual rainfall, temperature and forest area positively influence agricultural output, whereas drought, floods and agricultural nitrous oxide (N₂O) emissions have negative impact on agricultural output. The study suggests the need for a regulatory framework and also an explicit national agricultural policy essential to offset the negative effects of climate change especially on agricultural output.

As Nigeria look to diversify her economy which relied on oil, agriculture is among the alternative sector hoping to drive her economic growth, therefore, it is pertinent to examine the current output in the sector given the effects of climate change.

Specific examples or brief case-histories in different fields or disciplines illustrate the inventive process from conception to realization.

The authors examine predictions made in 2007 by “China experts” about what the Chinese business environment would look like in 2017. Their predictions were accurate in respect of around two-thirds of the issues they were asked to consider. The authors focus on the one-third of issues about which they were wide of the mark and examine the likely reasons.

The newly named Anthropocene is a time of increasing conception, research, design, development, evaluation and exploitation of new artifacts and services. Objectivity: careful problem-analysis assures the authors’ understanding of innovating pathways.

Trial-and-error methods may be disorderly, log-type research records are not kept, accidents not considered relevant.

Examples cited are transdisciplinary, often requiring inputs from other economic or cultural sectors. These complexities should be of incalculable value to innovators with single-field backgrounds.