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Nowadays, informed decision-making is catching up. Technological advancements and computing ability further fuel and facilitate this tilt toward informed decision-making. In such a scenario, data is cynosure. Therefore, the ability to gather data by a nation (incredibly accurate public data) becomes equally important and relevant, as measured by statistical performance indicators (SPI). This study aims to explore the association of financial inclusion (FI); environmental, social and governance (ESG); poverty; and SPI.

The panel data of 140 nations for nine years are gathered to explore the association of FI, ESG and poverty with the SPI. Panel data estimation is conducted to arrive at the results.

The findings of this study highlight mixed outcomes for FI. ESG is positively associated with SPI, but poverty is not associated with SPI. These findings imply that an increase in FI may reduce the statistical capacity of the nations. An increase in ESG increases the capacity. However, change in poverty does not influence the SPI. The recommendation based on this study’s outcome suggests auditing the FI and poverty vis-à-vis SPI to ensure SPI’s veracity and robustness in the long run.

The way in which the individual social, economic and environmental indicators influence the SPI needs to be tested to establish the veracity and robustness of the SPI, which is barely researched as observed in the literature.

The compressive strength of concrete depends on many interdependent parameters; its exact prediction is not that simple because of complex processes involved in strength development. This study aims to predict the compressive strength of normal concrete and high-performance concrete using four datasets.

In this paper, five established individual Machine Learning (ML) regression models have been compared: Decision Regression Tree, Random Forest Regression, Lasso Regression, Ridge Regression and Multiple-Linear regression. Four datasets were studied, two of which are previous research datasets, and two datasets are from the sophisticated lab using five established individual ML regression models.

The five statistical indicators like coefficient of determination (R²), mean absolute error, root mean squared error, Nash–Sutcliffe efficiency and mean absolute percentage error have been used to compare the performance of the models. The models are further compared using statistical indicators with previous studies. Lastly, to understand the variable effect of the predictor, the sensitivity and parametric analysis were carried out to find the performance of the variable.

The findings of this paper will allow readers to understand the factors involved in identifying the machine learning models and concrete datasets. In so doing, we hope that this research advances the toolset needed to predict compressive strength.

The study aims to pioneer an innovative approach for the evaluation of government portal websites (GPWs) by introducing an eye-tracking-based method. The research meticulously pinpoints and analyses the distinct usability issues and challenges that users encounter while navigating and interacting with GPWs.

This study devises an eye-tracking-based GPW usability evaluation approach, which focuses on the major functions (i.e. government information disclosure, government services and interactive responses) of GPWs. An Entropy Weighted Technique for Order Preference by Similarity to an Ideal Solution (EW-TOPSIS) method is employed to process eye-tracking indicator results for deriving GPW usability results.

The proposed approach is demonstrated to assess the usability of 12 GPWs in pilot smart cities in China, and it is found that most GPWs have lower-than-average usability. GPWs with low usability require more cognitive load that exhibit increased fixation and saccade. The comparisons among the GPW usability results from (1) the eye-tracking experiment, (2) questionnaire surveys and (3) the ready-made performance evaluation report validate the effectiveness of eye-tracking-based GPW usability evaluation.

The work contributes to shifting the GPW usability evaluation approach from a subjective judgment paradigm to an objective paradigm, as well as provides implications for enhancing GPW usability, including improving search function, reducing website complexity and prioritizing user needs.

While the Chinese securities market is booming, the phenomenon of listed companies falling into financial distress is also emerging, which affects the operation and development of enterprises and also jeopardizes the interests of investors. Therefore, it is important to understand how to accurately and reasonably predict the financial distress of enterprises.

In the present study, ensemble feature selection (EFS) and improved stacking were used for financial distress prediction (FDP). Mutual information, analysis of variance (ANOVA), random forest (RF), genetic algorithms, and recursive feature elimination (RFE) were chosen for EFS to select features. Since there may be missing information when feeding the results of the base learner directly into the meta-learner, the features with high importance were fed into the meta-learner together. A screening layer was added to select the meta-learner with better performance. Finally, Optima hyperparameters were used for parameter tuning by the learners.

An empirical study was conducted with a sample of A-share listed companies in China. The F1-score of the model constructed using the features screened by EFS reached 84.55%, representing an improvement of 4.37% compared to the original features. To verify the effectiveness of improved stacking, benchmark model comparison experiments were conducted. Compared to the original stacking model, the accuracy of the improved stacking model was improved by 0.44%, and the F1-score was improved by 0.51%. In addition, the improved stacking model had the highest area under the curve (AUC) value (0.905) among all the compared models.

Compared to previous models, the proposed FDP model has better performance, thus bridging the research gap of feature selection. The present study provides new ideas for stacking improvement research and a reference for subsequent research in this field.

The growing attention to business ethics, integrity and respect for human rights at work has become increasingly relevant. Decent work is an important concept representing the promotion of human rights at work and business, the fulfilling and productive work maintained with social dialogue. This study aims to present the adaptation and validation of the Spanish version of the Decent Work Questionnaire (DWQ), allowing the decent work assessment in Spanish. Initially developed and validated for Portuguese-speaking countries, the DWQ’s Italian version was also recently adapted and validated.

The 31-item scale was applied to a sample of 1,528 Spanish high-skilled workers. Confirmatory factor analysis (CFA) was performed. Convergent and discriminant validity was tested, examining the links of the DWQ to Work Engagement and Burnout measures.

CFA confirmed the original higher-order model with seven factors, a very good model fit and good internal consistency reliability (α = 0.94). Statistical analyzes also supported its convergent and discriminant validity.

The results confirmed the DWQ’s Spanish version as a reliable and valid multidimensional measurement tool and strengthened it as a good cross-cultural measure of decent work.

La creciente atención a la ética empresarial, la integridad y el respeto de los derechos humanos en el trabajo ha sido un tema cada vez más relevante. El trabajo decente es un concepto importante que representa la promoción de los derechos humanos en el trabajo y en las empresas, como un trabajo gratificante y productivo mantenido a través del diálogo social. El presente estudio presenta la adaptación y validación de la versión en español del Cuestionario de Trabajo Decente (CTD), que permite evaluar el trabajo decente en español. Inicialmente desarrollado y validado para los países de habla portuguesa, la versión italiana del CTD también se adaptó y validó recientemente.

La escala de 31 ítems se aplicó a una muestra de 1528 trabajadores españoles altamente cualificados. Se realizó un Análisis Factorial Confirmatorio. La validez convergente y discriminante se probó examinando los vínculos del CTD con las medidas de Work Engagement y Burnout.

El Análisis Factorial Confirmatorio confirmó el modelo original de orden superior con 7 factores, con un muy buen ajuste del modelo y buena consistencia de confiabilidad interna (α = 0.94). También se apoyó su validez convergente y discriminante.

Nuestros resultados confirmaron la versión en español del CTD como una herramienta de medición multidimensional confiable y válida. También reforzaron la idea de que este instrumento es una buena medida intercultural del trabajo decente.

A crescente atenção à ética empresarial, integridade e respeito aos direitos humanos no trabalho tem sido um tema cada vez mais relevante. O trabalho digno é um conceito importante que representa a promoção dos direitos humanos no trabalho e nas empresas, assim como o trabalho realizante e produtivo mantido com o diálogo social. O presente estudo apresenta a adaptação e validação da versão em espanhol do Questionário de Trabalho Digno (QTD), permitindo a avaliação do trabalho digno em espanhol. Inicialmente desenvolvido e validado para países de língua portuguesa, a versão italiana do QTD também foi recentemente adaptada e validada.

A escala de 31 itens foi aplicada a uma amostra de 1528 trabalhadores espanhóis altamente qualificados. A análise factorial confirmatória (AFC) foi realizada. A validade convergente e discriminante foi testada, examinando as ligações do QTD às medidas de Engajamento no Trabalho e Burnout.

AFC confirmou o modelo original de ordem superior com 7 fatores, com um ajuste de modelo muito bom e boa consistência interna de confiabilidade (α = 0,94). Também testamos sua validade convergente e discriminante. Ambas foram suportadas.

Nossos resultados confirmaram a versão em espanhol do QTD como uma ferramenta de medição multidimensional confiável e válida. Também reforçaram a ideia deste instrumento ser uma boa medida transcultural do trabalho digno.

The main aim of this paper is to establish a reasonable and scientific evaluation index system to assess the high quality and full employment (HQaFE).

This paper uses a novel Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) multi-criteria framework to evaluate the quality and quantity of employment, wherein the integrated weights of attributes are determined by the combined the Criteria Importance Through Inter-criteria Correlation (CRITIC) and entropy approaches.

Firstly, the gap in the Yangtze River Delta in employment quality is narrowing year by year; secondly, employment skills as well as employment supply and demand are the primary indicators that determine the HQaFE; finally, the evaluation scores are clearly hierarchical, in the order of Shanghai, Jiangsu, Zhejiang and Anhui.

A scientific and reasonable evaluation index system is constructed. A novel CRITIC-entropy-TOPSIS evaluation is proposed to make the results more objective. Some policy recommendations that can promote the achievement of HQaFE are proposed.

This paper deals with analyzing the relationships between the domains of the Sustainable Development Goals (SDGs) and the Missions envisaged by the National Recovery and Resilience Plan (NRRP). Specifically, the authors refer to Mission 2 (Green revolution and ecological transition) and to the statistical indicators related to the M2C1 component (Circular economy and sustainable agriculture).

The numerous data available were analyzed at a regional level using multivariate statistical methodologies (Totally Fuzzy and Relative method) capable of summarizing the various information to evaluate the current situation relating to the “circular economy and sustainable agriculture” component. The presence of multiple updated data allows for the development of a holistic approach to the evaluation of the local government policies in place and to be able to monitor the progress of the subsequent intervention policies of the Italian government.

No Findings.

NRRP represents an opportunity for development for the area, providing for reforms and substantial investments for the promotion of circular economy solutions, the improvement of the capacity for efficient and sustainable waste management, the strengthening of the infrastructures for treatment of waste and separate collection, the reduction of the North/South gap.

In this study, a novel framework was proposed to assess the trust in e-government (e-Gov) services under an uncertain environment. The proposed framework was applied in Iranian municipality websites of e-Gov services to evaluate the readiness score of trust in e-Gov services.

A unique hybrid research methodology was proposed. In the first phase, a comprehensive set of indices were determined from an extensive literature review and finalized by employing the fuzzy Delphi method. In the second phase, interval-valued intuitionistic fuzzy set (IVIFS) -was utilized to model the problem's uncertainty with analytic called IVIFS- hierarchy process (AHP) to determine the importance of indices and indicators by assigning the weights. In the third phase, the fuzzy evaluation method (FEM) is followed for assessing the readiness score of indices in case studies.

The findings indicated that “Trust in government” is the most significant index affecting citizen's trust in e-Gov services while “Maintenance and support” has the least impact on user's intention to use e–Gov services.

The study contributes by introducing a unique research methodology that integrates three phases, including fuzzy Delphi, IVIFS AHP and fuzzy evaluation method. Moreover, the fuzzy sets theory helps to reach a more accurate result by modeling the inherent ambiguity of indicators and indices. Interval-valued intuitionistic fuzzy models the ambiguity of experts' judgments in an interval.

The study helps policy makers to monitor wider aspects of trust in e-Gov services as well as understanding their importance. The study enables policy makers to apply the framework to any potential case studies to evaluate the readiness score of indices and recognizing strengths and weakness of trust dimensions as well as recommending advice for improving the situation.

The study is one of the few to indicate significant indices of trust in e-Gov services in developing countries. The study shows the importance of indicators and indices by assigning a weight. Additionally, the framework can assess the readiness score of various case studies.

This paper seeks to assess the capabilities and maturity of supply chain planning and product quality management systems implemented by the dairy industries in three different countries: Russia, Kazakhstan, and Lithuania.

Through a systematic analysis of statistical information, the descriptors of the logistics supply chain efficiency were identified. Directions for dairy supply chain management improvement were also highlighted. The study uses secondary statistics from open sources as a basis for the comparative analysis across a range of indicators, including the Logistics Performance Index (LPI), the dairy products quantity, the production volume of milk and dairy products, and other indicators characterizing the dairy industry.

The results of this study suggest the inconsistency and narrowness of single indexes and ranking, which are traditionally used to evaluate the logistics system. LPI values confirmed that the internal efficiency of the Lithuanian logistics system exceeds similar systems in Russia and Kazakhstan.

In this paper, ways to improve supply chain management of dairy products in the context of globalization have been determined, the prerequisites for the formation of the perishable goods market according to the balance of supply and demand and the institutional mechanism of this process, which represents important information for all interested economic agents, have been analyzed.

The proposed approach points to the importance of having detailed information on the supply chain infrastructure and the need to introduce a single information space based on modern information and communication technologies.

The transformation towards the Green Economy (GE) in Poland is a relatively new topic for researchers, policymakers and business practitioners. A comprehensive picture of the shift towards the GE can help mentioned groups translate theoretical assumptions into practice.

This chapter presents the assessment of Poland's shift towards the GE, measured by the proposed Green Transformation Index (GTI).

The set of GE indicators was elaborated in Structured Literature Review (SLR) variation method. Then, this set of indicators was compared with the Statistics Poland (GUS) secondary data and employed in the taxonometric calculation methods.

In the result, the GTI for the Polish economy was proposed and calculated between 2007 and 2020. The GTI allowed us to present a dynamic analysis of the transformation towards GE in Poland.