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The increasing rates of forest cover change and heightened vulnerability to deforestation present significant environmental challenges in Northeast India. This study investigates the dynamics of forest cover change and susceptibility to deforestation in this region from 2001 to 2021, utilizing data from the Hansen Global Forest Change (HGFC) product on the Google Earth Engine (GEE) platform. A suite of multicriteria decision-making (MCDM) models—including VlseKriterijumska optimizacija I Kompromisno Resenje (VIKOR), Simple Additive Weighting (SAW), Evaluation Based on Distance from Average Solution (EDAS), and Weighted Aggregates Sum Product Assessment (WASPAS)—was employed to assess changes in forest cover and deforestation susceptibility across varied zones. Multicollinearity tests confirmed the relevance of the factors influencing deforestation. Statistical validations, such as the Wilcoxon Signed Ranks Test, underscored the models' robustness, revealing statistically significant outcomes. Additionally, Receiver Operating Characteristic (ROC) curve and Area Under the Curve (AUC) analysis demonstrated the superior fit of the VIKOR model (AUC = 0.938) compared to SAW (AUC = 0.901), EDAS (AUC = 0.895), and WASPAS (AUC = 0.864) in predicting current deforestation susceptibility. Validation affirmed the reliability of all MCDM methods, with VIKOR displaying high sensitivity (True Positive Rate, TPR = 0.878) and optimal AUC (0.938). Correlation analyses among the models identified significant inter-relationships, notably a positive correlation between EDAS and SAW, and a negative correlation between VIKOR and SAW. The regions of Assam, Nagaland, Mizoram, and Arunachal Pradesh were identified as experiencing significant forest cover loss, indicating a pronounced susceptibility to future deforestation. These findings underscore the need for immediate intervention to address this critical environmental issue. [ABSTRACT FROM AUTHOR]

The aim of this research was to assess the physical self-esteem of albinos in the Democratic Republic of Congo (more specifically, those living in the city-province of Kinshasa), and to identify the most explanatory factors. With this in mind, a physical self-esteem inventory was applied to 70 albinos living in Kinshasa, members of the Mwimba Texas Association. Following the administration of this inventory, it was found that the albinos surveyed had positive physical self-esteem. This positive self-esteem manifested itself in a positive perception of: (1) overall self, (2) physical value, (3) physical appearance and (4) strength. The study of explanatory determinants made it possible to target two factors that influenced all the dimensions of the self-esteem of the subjects surveyed (support of entourage and perception of albinos by entourage).

In recent decades, city councils have become a powerful tool used to "motivate" entrepreneurship. Through a content analysis of the webpages of 50 Spanish city councils corresponding to the period 2015–2019, the evolution of the degree of disclosure of information on entrepreneurship has been analysed. A series of population, economic and political explanatory factors have researched the disclosure of this type of information in two ways. First, a cluster analysis was carried out based on a previously calculated disclosure index. Second, an analysis of variance was performed to verify the existence of an association between the proposed determining factors. The results show that the information disclosed on entrepreneurship by municipalities is related to the size of the population, municipal debt, institutional capacity, the unemployed population and political competition. [ABSTRACT FROM AUTHOR]

Abstract Background Despite benefits of exclusive breastfeeding (EBF) and its strategic place in the national guidelines for infant and young child feeding, its practice remains insufficient in Cote d’Ivoire. It is therefore important to identify its early stopping associated factors. We aimed to (i) assess the extent of children’s exposure to exclusive breastfeeding and the associated explanatory factors for discontinuation before six months, and (ii) to profile non-exclusively breastfed children and interrelationships between these factors. Methods A secondary analysis of data from the 2016 Cote d’Ivoire Fifth Multi Indicator Cluster Survey (MICS5) of 980 children under six months of age was conducted in this study. Data were analyzed using the actuarial method of survival hazard estimation combined with the Wilcoxon (Gehan) test, discrete time proportional hazards regression models, and Multiple Correspondence Analysis (MCA) to profile the children. Results Maternal exposure to counseling session, age at delivery, and child sex were significantly associated with the likelihood of discontinuing exclusive breastfeeding before the first six months of life. Children deprived of EBF resided in urban areas, in high and very high economic welfare households. Their mothers had a secondary education or higher and had three or fewer children. Logistic analysis showed that health status and sex of the child were significantly associated (P

This research adds to the assessment of the causal relationships between residential electricity consumption and its explanatory factors. Johansen cointegration, autoregressive distributed lag model, the vector error correction model, and Wald causality tests are used. In both the short and long run, a unidirectional causality towards electricity consumption is identified. The sustainable development of the electricity sector in Cameroon, as defined by the national development strategy for 2030 and the long-term electricity sector development plan for 2030, requires an increase in GDP per capita, the adoption of a compact less energy-intensive urban model, the strengthening of control over the evolution of the number of subscribers on the distribution networks, and the reduction of CO2 emissions from thermal electricity generation.

Background: Despite benefits of exclusive breastfeeding (EBF) and its strategic place in the national guidelines for infant and young child feeding, its practice remains insufficient in Cote d’Ivoire. It is therefore important to identify its early stopping associated factors. We aimed to (i) assess the extent of children’s exposure to exclusive breastfeeding and the associated explanatory factors for discontinuation before six months, and (ii) to profile non-exclusively breastfed children and interrelationships between these factors. Methods: A secondary analysis of data from the 2016 Cote d’Ivoire Fifth Multi Indicator Cluster Survey (MICS5) of 980 children under six months of age was conducted in this study. Data were analyzed using the actuarial method of survival hazard estimation combined with the Wilcoxon (Gehan) test, discrete time proportional hazards regression models, and Multiple Correspondence Analysis (MCA) to profile the children. Results: Maternal exposure to counseling session, age at delivery, and child sex were significantly associated with the likelihood of discontinuing exclusive breastfeeding before the first six months of life. Children deprived of EBF resided in urban areas, in high and very high economic welfare households. Their mothers had a secondary education or higher and had three or fewer children. Logistic analysis showed that health status and sex of the child were significantly associated (P < 0.001) with exclusive breastfeeding. An extremely important and rarely studied factor is that children who were sick in weeks prior to the survey were more likely to remain exclusive breastfeeding (adjusted OR 1.80; 95% Confidence Interval (CI) 1.452, 2.234). Girls are less likely to be exclusively breastfed than boys (adjusted OR 1.48; 95% CI 1.22, 1.798). Low standard of living was associated with early cessation of EBF (adjusted OR 2.15; CI 1.325, 3.499). The duration of the exclusive breastfeeding was significantly longer among mothers with high exposure to medical discourse (adjusted OR 0.74; CI 0.595, 0.91). Conclusions: Improving the practice of exclusive breastfeeding in Cote d’Ivoire requires strengthening the capacities of health professionals in terms of advice and assistance to mothers for the practice of exclusive breastfeeding and its maintenance until six months of age, regardless of the health status and sex of the child. [ABSTRACT FROM AUTHOR]

The gaps observed in entities' traditional reports and accounts led to the emergence of the integrated report (IR), which includes several content elements, namely the component relating to risks and opportunities. Within this scope, the specific risks that may affect an organization's capacity to create value are disclosed, among others, which is information of interest to the different stakeholders. This paper aims to identify the explanatory factors that influence the disclosure of risks in IRs. For this purpose, the IRs of entities listed on the Brazilian stock exchange for the year 2020 were assessed. The study was based on the explanatory theories of risk disclosure usually found in the literature, namely, the legitimacy, the agency, the signaling, and the upper echelon theories. Linear regression models were used with the disclosure rates of different types of risk as dependent variables. The size, profitability, indebtedness, independence, and gender diversity in the board of directors (BD), audit, and activity sector comprised the selected explanatory factors. Associations were found between some of the types of risks disclosed and the size of the entity, the existence of an audit, the independence of the BD, and the activity sector. The paper contributes to the literature about the explanatory factors of risk disclosure by exploring its analysis with different typologies and attributes, having the IR as a source of information, which is still little explored. The scientific contribution encompasses proposing a new risk analysis model in the IR. The innovative elements also comprise the classification of risks related to sustainable development (SD), including environmental, social, and governance (ESG) factors. [ABSTRACT FROM AUTHOR]

Purpose: This study aims to analyse the factors that explain why Beninese companies exceed the deadline for filing financial statements with the General Tax Directorate (DGI). Design/Methodology: The data has been collected using a questionnaire with sample of 105 companies, target population was accountants of various companies. Two methods of analysis have been adopted in this paper, descriptive and econometric analysis. Findings: From the descriptive analysis, the majority (65%) of the companies surveyed often exceed the deadline for filing financial statements. The results obtained from the descriptive analysis show that all the explanatory variables are considered except (the deadline for filing accounting documents in accounting firms is respected and the payment of declarations of various taxes is respected by accounting firms in assisting companies). Implications/Originality/Value: Given these results, companies should work towards a good accounting organisation and collaborate with accounting firms.

Understanding the characteristics that shape mobility could help to achieve more sustainable transport systems. A considerable body of scientific studies tries to determine these characteristics at the urban level. However, there is a lack of studies analyzing those factors for the heterogeneous zones existing in the suburbs of big cities. The study presented in this paper intends to fill this gap, in the context of two metropolitan corridors in the Madrid Region. Correlation analyses are used to examine how mobility patterns are affected by socioeconomic and urban form variables. Then, a cluster analysis is carried out to classify the types of zones we may find in the suburbs. Results show that the main characteristics leading towards higher car use are low urban density, few local activities, a high percentage of children, and a low percentage of seniors. As for the variable distance to the city center, it does not explain car use. Moreover, some remote areas have many walking trips. This is well understood in the cluster analysis; there are zones far away from the city center but that are dense and well provided for, which work as self-sufficient urban centers. Results reinforce the theories underlying polycentrism as a solution to the urban sprawl challenge. [ABSTRACT FROM AUTHOR]

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ABSTRACT This paper aims to identify the explanatory factors of mandatory disclosure (MD) and voluntary disclosure (VD) levels related to discount rates, based on disclosure theories. The size, leverage, profitability, and audit firms were selected from different theories, namely agency theory, signaling theory, positive accounting theory, including the political cost hypothesis, and the cost of capital theory. Furthermore, the materiality (weight of the items) and the relevance (nature) of the topic were also considered, based on the evidence already obtained in the literature. Research on disclosures related to discount rates has been assessed either as an incidental topic or from a limited-scope analysis, particularly with respect to MDs. This paper assesses this topic as its specific object of analysis for both MD and VD. The use of the discount rate has been assuming growing importance within financial reporting. Therefore, this topic should deserve particular attention from international standard-setting bodies. The understanding of the proper set of items to be disclosed and understanding the factors that explain its disclosure, aligned with the efforts to assure its compliance by legal authorities, may contribute to reducing asymmetries and increasing transparency in entities' financial reporting. This study uses the method of archival research and content analysis of consolidated reports and accounts for the year 2020 of listed entities in Euronext Lisboa. Regression models were used, having disclosure indices related to discount rates as dependent variables. This paper finds a positive association between disclosures related to discount rates and the entity’s size, as well as the materiality and the relevance, assessed by the weight of the items and the nature of the topic under assessment, respectively. It adds new explanatory factors on the VDs and MDs related to discount rates in a broader perspective of analysis.

The aim of this paper is to analyze the participation in the global textile and apparel value chain with special attention, first, to the case of three dynamic and interrelated economies (Mexico, the United States, and China); and second, to a general approach to a larger sample of countries through the analysis of trade in value added. From the descriptive analysis, a high domestic share in each country's exports is found. However, China is the leading exporter in the industry, accounting for around a third of the domestic value added in the global textile final demand. An econometric estimation has also been carried out to observe the effects of tariffs, FDI, and labor costs on the total and backward participation in the textile GVC. In this case, the sample has been extended to 39 developed and 22 developing countries. The results reveal tariff protection as a determinant of the degree of participation of the sector, especially when backward participation and developing economies are considered. However, FDI and labor costs only show the expected results in the case of developing countries. This may be due to the different tasks performed by developing economies (primarily manufacturing) versus developed economies (branding, design) within the sector's value chain. [ABSTRACT FROM AUTHOR]

The gaps observed in entities’ traditional reports and accounts led to the emergence of the integrated report (IR), which includes several content elements, namely the component relating to risks and opportunities. Within this scope, the specific risks that may affect an organization’s capacity to create value are disclosed, among others, which is information of interest to the different stakeholders. This paper aims to identify the explanatory factors that influence the disclosure of risks in IRs. For this purpose, the IRs of entities listed on the Brazilian stock exchange for the year 2020 were assessed. The study was based on the explanatory theories of risk disclosure usually found in the literature, namely, the legitimacy, the agency, the signaling, and the upper echelon theories. Linear regression models were used with the disclosure rates of different types of risk as dependent variables. The size, profitability, indebtedness, independence, and gender diversity in the board of directors (BD), audit, and activity sector comprised the selected explanatory factors. Associations were found between some of the types of risks disclosed and the size of the entity, the existence of an audit, the independence of the BD, and the activity sector. The paper contributes to the literature about the explanatory factors of risk disclosure by exploring its analysis with different typologies and attributes, having the IR as a source of information, which is still little explored. The scientific contribution encompasses proposing a new risk analysis model in the IR. The innovative elements also comprise the classification of risks related to sustainable development (SD), including environmental, social, and governance (ESG) factors.

Despite its widespread trajectory and global presence, studies on Economic and Social Councils (ESCs) are not frequent. Thus, this study aims to review the existing scientific literature on this institution to identify the main thematic nuclei, agreements, and discrepancies, and detect research gaps and outline future research lines. Based on the application of the PRISMA Protocol, three emerging thematic nuclei on ESCs have been detected: the factors that explain their creation; the factors that influence their effectiveness (and condition their success), and the criteria used to evaluate their effectiveness (related to these institutions' success or failure). In short, this is the first qualitative synthesis of the international literature on ESCs, focusing on their effectiveness and evaluation. It offers elements for future intervention and studies on these institutions, especially those newly created. [ABSTRACT FROM AUTHOR]

This article aims to identify the explanatory factors of collective competencies in fashion design teams using a survey of 22 fashion designers from Santa Catarina. Exploratory factor data analysis and analysis of variance techniques were applied. The results showed four explanatory factors: collective spirit, interaction, cooperation, and relationship. Our findings made evident how relevant these factors are in the composition and formation of groups, manifesting themselves as descriptive and essential attributes for collective competencies. The synergistic combination of the factors allows the teams to develop shared actions in favor of work organization based on interactions and visions, which, although distinct, can be shared.

We examined whether material and psychosocial resources may explain socioeconomic differences in diet quality. Cross-sectional survey data from 1461 Dutch adults (42.5 (SD 13.7) years on average and 64% female) on socio-demographics, diet quality, psychosocial factors and perceptions of and objective healthiness of the food environment were used in a structural equation model to examine mediating pathways. Indicators for socioeconomic position (SEP) were income, educational, and occupational level and the 2015 Dutch Healthy Diet (DHD15) index assessed diet quality. Material resources included food expenditure, perceptions of healthy food accessibility and healthfulness of the food retail environment. Psychosocial resources were cooking skills, resilience to unhealthy food environments, insensitivity to food cues and healthy eating habits. Higher SEP was associated with better diet quality; Beducation 8.5 (95%CI 6.7; 10.3), Bincome 5.8 (95%CI 3.7; 7.8) and Boccupation 7.5 (95%CI 5.5; 9.4). Material resources did not mediate the association between SEP and diet quality and neither did the psychosocial resources insensitivity to food cues and eating habits. Cooking skills mediated between 13.3% and 19.0% and resilience to unhealthy food environments mediated between 5.9% and 8.6% of the relation between SEP and the DHD15-index. Individual-level factors such as cooking skills can only explain a small proportion of the SEP differences in diet quality. On top of other psychosocial and material resources not included in this study, it is likely that structural factors outside the individual, such as financial, work and living circumstances also play an important role.

This article aims to identify the explanatory factors of collective competencies in fashion design teams using a survey of 22 fashion designers from Santa Catarina. Exploratory factor data analysis and analysis of variance techniques were applied. The results showed four explanatory factors: collective spirit, interaction, cooperation, and relationship. Our findings made evident how relevant these factors are in the composition and formation of groups, manifesting themselves as descriptive and essential attributes for collective competencies. The synergistic combination of the factors allows the teams to develop shared actions in favor of work organization based on interactions and visions, which, although distinct, can be shared. [ABSTRACT FROM AUTHOR]

Understanding the characteristics that shape mobility could help to achieve more sustainable transport systems. A considerable body of scientific studies tries to determine these characteristics at the urban level. However, there is a lack of studies analyzing those factors for the heterogeneous zones existing in the suburbs of big cities. The study presented in this paper intends to fill this gap, in the context of two metropolitan corridors in the Madrid Region. Correlation analyses are used to examine how mobility patterns are affected by socioeconomic and urban form variables. Then, a cluster analysis is carried out to classify the types of zones we may find in the suburbs. Results show that the main characteristics leading towards higher car use are low urban density, few local activities, a high percentage of children, and a low percentage of seniors. As for the variable distance to the city center, it does not explain car use. Moreover, some remote areas have many walking trips. This is well understood in the cluster analysis; there are zones far away from the city center but that are dense and well provided for, which work as self-sufficient urban centers. Results reinforce the theories underlying polycentrism as a solution to the urban sprawl challenge.

The aim of this paper is to analyze the participation in the global textile and apparel value chain with special attention, first, to the case of three dynamic and interrelated economies (Mexico, the United States, and China); and second, to a general approach to a larger sample of countries through the analysis of trade in value added. From the descriptive analysis, a high domestic share in each country’s exports is found. However, China is the leading exporter in the industry, accounting for around a third of the domestic value added in the global textile final demand. An econometric estimation has also been carried out to observe the effects of tariffs, FDI, and labor costs on the total and backward participation in the textile GVC. In this case, the sample has been extended to 39 developed and 22 developing countries. The results reveal tariff protection as a determinant of the degree of participation of the sector, especially when backward participation and developing economies are considered. However, FDI and labor costs only show the expected results in the case of developing countries. This may be due to the different tasks performed by developing economies (primarily manufacturing) versus developed economies (branding, design) within the sector’s value chain.

Urban expansion is a spatio-temporal process that reflects the localization patterns of the population and its activities, which can cause irreversible impacts on the territory. The construction of narratives and the subsequent mapping of future scenarios has been revealed as a planning technique, which can help in the management and planning of land use and transport. The Corridor of Henares (Madrid) has been chosen as a case study, representing the spatial evolution of five urban land uses in three disruptive scenarios for 2050. The present research aims to determine which explanatory factors influenced the process of spatialization of the five uses that was projected in a previous mapping workshop. In this way, the aim is to provide more precise information about the driving factors of use changes in each scenario, which could later be applied to new spatial models of urban simulation. Thus, given the ubiquitous nature of urbanization processes, Geographically Weighted Logistic Regression (GWLR) was used as it enables a spatial analysis of the relationships between the explanatory factors that global models do not allow to study. The outcomes showed coincidences between the most significant factors of the model and the scenario narratives. [ABSTRACT FROM AUTHOR]

Studies on stability and change in modes of environmental governance often remain implicit regarding the conceptualisation, nature and causes of stability and change. Moreover, they are selective in the addressed explanatory factors. Theorising of stability and change in modes of environmental governance could be brought to the next level by enhancing the comparability and alignment of explanatory studies. This paper aims to contribute to this effort using insights regarding the definition and explanation of change processes gained in the policy and political sciences. Based on these insights, we provide a systematic approach for conceptualising “stability” and “change” in modes of governance and introduce six categories of explanatory factors: physical circumstances, infrastructures, institutional settings, discourse, characteristics of agency and shock events. The case of Dutch flood risk governance shows the usefulness of the proposed approach. We conclude by reflecting on the approach's potential for providing richer and more nuanced explanations.

Effective and thorough credit-risk management is a key factor for lending institutions, as significant financial losses can arise from the borrowers' default. Consequently, machine learning methods can measure and analyze credit risk objectively when at the same time they face increasingly attention. This study analyzes default payment data from a credit cards' portfolio containing some 30,000 clients from Taiwan with twenty-three attributes and with no missing information. We compare prediction accuracy of seven classification methods used, i.e. KNN, Logistic Regression, Naïve Bayes, Decision Trees, Random Forest, SVC, and Linear SVC. The results indicate that only few out of most of the typical variables used can adequately analyze default characteristics in terms of lending decisions. The results provide effective feedback to credit evaluators, lending institutions and business analysts for in-depth analysis. Also, they mention to the importance of the precautionary borrowing techniques to be used to better understand credit-card borrowers' behavior, along with specific accounting, historical and demographical characteristics. [ABSTRACT FROM AUTHOR]

While the principal objective of outsourcing was to reduce costs, organizations are now using this process to focus, their financial and managerial resources, on value-creating activities and improving the logistics performance for the company adopting it. Based on this observation, the objective of this paper is to wonder about the decision of logistics outsourcing: what factors explain why a company will choose to outsource its logistics activity rather than maintaining it internally knowing that other companies show a cautious position compared to the idea of outsourcing? And what contributions does each company hope to receive in return for the decision to outsource its logistics?

For water companies, benchmarking their performance relative to other companies can be an effective way to identify the scope for efficiency gains to be made through infrastructure investment and operational improvements. However, a key limitation to benchmarking is the confounding effect of exogenous factors, which may not be factored in to benchmarking methodologies. The purpose of this study was to provide an unbiased comparison of efficiency across a sample of water and sewage companies, accounting for important exogenous factors. Bias-corrected economic and environmental efficiency estimates with explanatory factors were evaluated for a sample of 13 water and sewage companies in the UK and Ireland, using a double-bootstrap data envelopment analysis (DEA) approach. Bias correction for economic and environmental efficiency changed the rankings of nine and eight companies, respectively. On average, companies could reduce economic inputs by 19% and carbon outputs by 16% if they performed at the efficiency frontier. Variables explaining efficiency were: source of water, leakage rate, per capita consumption and population density. Population density showed statistical significance with both economic (p-value 0.002) and environmental (p-value 0.001) efficiency. Consequently, a rurality factor was defined for each company's operational area, which was then regressed against normalised water company performance data. More rural water companies spend more per property (R2 of 0.633), in part reflecting a larger number of smaller sewage treatment works serving rural populations (R2 of 0.823). These findings provide new insight into methods for benchmarking, and factors affecting, water company efficiency, pertinent for both regulators and water companies. • Economic and environmental inputs could reduce by 19.4% and 15.8%. • Bias correction changed the rankings of over 65% of companies. • Population density and surface water % significantly linked to higher efficiencies. • Rurality has relationship with increased spending (R2 of 0.63). • No. of sewage treatment works linked to rurality/spending relationship (R2 of 0.82). [ABSTRACT FROM AUTHOR]

The study objective is to determine the explanatory factors' joint interaction related to the decision-maker and the organizational environment in the asymmetry of costs. Through confirmatory factor analysis and empirical regression model, the results suggest that the two clusters positively affect, in similar magnitudes, the asymmetry of general and administrative expenses, which proves the existence of the explanatory factors effects that overlap in the sticky behavior explanation and corroborate the contemporary view on cost management caused by the managers' deliberate decision. Still, through exploratory analysis, 6 constructs were revealed that summarize the interactions of the cost asymmetry explanatory factors. Finally, it is concluded that this research contributes to the understanding of cost behavior based on a broader view, and not isolated in relation to explanatory factors, by providing subsidies for new theories and practical models of profit forecasting to analysts. [ABSTRACT FROM AUTHOR]

This research adds to the assessment of the causal relationships between residential electricity consumption and its explanatory factors. Johansen cointegration, autoregressive distributed lag model, the vector error correction model, and Wald causality tests are used. In both the short and long run, a unidirectional causality towards electricity consumption is identified. The sustainable development of the electricity sector in Cameroon, as defined by the national development strategy for 2030 and the long-term electricity sector development plan for 2030, requires an increase in GDP per capita, the adoption of a compact less energy-intensive urban model, the strengthening of control over the evolution of the number of subscribers on the distribution networks, and the reduction of CO2 emissions from thermal electricity generation. • Residential electricity consumption and its associated explanatory factors are analysed. • Unidirectional causality towards electricity consumption is highlighted. • The long run relationship between explanatory factors and electricity consumption is investigated using ARDL and VECM. • Mastering changes in specific explanatory factors is required for long run sustainability. [ABSTRACT FROM AUTHOR]

Based on public governance and information disclosure by public managers, this study aimed to verify which factors may explain the transparency level of the cities. The sample comprised cities of the Rio Grande do Sul with population over 50 thousand inhabitants, totaling 43 cities. An index composed of 36 itens was developed based on the Fiscal Responsibility Law and the Access to Information Law. Methodologically, the transparency level of the cities was identified through a descriptive analysis, being the average of 71%. Subsequently, to identify the factors that explain the transparency level the cities obtained, a multiple linear regression was methodologically developed, comparing the explanatory variables of the transparency level addressed in the literature. The results of the statistical model indicate the Firjan Index of Municipal Development as the only factor with significance to explain the transparency level of the cities, assuming that citizens with better health and education conditions and good employability have better conditions to exert social control over municipal governance. [ABSTRACT FROM AUTHOR]