Social Indicators Research最新文献

In promoting China’s comprehensive modernization in pursuit of the grand revitalization of the Chinese nation, the relationship between industry and cities has become increasingly interconnected. National central cities, as the country’s economic, cultural, and financial centers, play a pivotal role in driving the development of their surrounding regions. Therefore, this paper focuses on nine national central cities in China and constructs an assessment index framework for urban–rural integration and modernization. This index system covers two aspects: industrial modernization (with a focus on the modernization of the service sector and industry) and urban modernization (with a focus on the harmonious development of people and nature). Using data from 2021, we determine the weights of individual indicators through the entropy weight method. Moreover, the coupling coordination model is utilized to compute the coupling coordination degree for each city, assessing the level of urban–rural integration and modernization. Using Hubei Province as an illustration, we incorporate the measured coupling coordination degree into the analysis of urban–rural integration effects. Spatial autocorrelation using Global Moran's I is applied to explore the spatial radiation effects of the national central city, Wuhan, on its surrounding cities. Simultaneously, 13 prefecture level cities in Hubei Province were selected as radiation areas, and relevant data from 2017 to 2021 were collected. The Durbin, robust regression, and panel model were employed to analyze the economic radiation impact, learning effect, and transportation accessibility effect of Wuhan as a national central city on surrounding cities. Our findings unequivocally demonstrate the paramount role of the service sector in shaping urban–rural integration, as evidenced by Shanghai emerging with the highest level of such integration and modernization, while Zhengzhou lags with the least progress. Moreover, the innovative prowess inherent in Wuhan, which functions as a national central city, exerts a positive influence on the innovation capacity witnessed in its radiating vicinity. Concurrently, the transportation accessibility quotient between peripheral cities and the central city manifests a positive correlation with the economic development level within the radiation zone. These results furnish invaluable insights into strategies aimed at elevating the echelon of urban–rural integration and modernization within national central cities.

Aim of the paper is to analyse the occurrence of occupational stress across European Union countries, considering gender and job sustainability as determinants, with a specific attention to the effects of home-based work. Although COVID-19 pandemic has brought such issues into a novel spotlight, to detect the response pattern towards occupational stress we chose to employ the latest official data collected by the Sixth European Working Condition Survey developed and carried out in a pre-COVID-19 scenario. This information may provide a reliable picture of working conditions, which are likely to become the “new normal” across Europe, at least for a subset of workers. Descriptive analyses do not seem to help disclosing any different response behaviour with specific respect to reported stress by gender, even when combined with the condition of working from home. Whereas a noteworthy finding of our study is that results from the implemented ordered probit model display that some differences in the response pattern do exist and are even substantial. A question still arises about whether and to what extent hybrid forms of work are here to stay and even to grow in the post-pandemic period. Some of the critical features of teleworking-from-home emerged during the epidemic indicate that the implementation of policies at a national and, ideally, even supra-national level is clearly necessary. However, since both occupations and company organizations are strongly differentiated, it seems also that the enterprises are allowed some flexibility in defining corporate policies for teleworking practices, especially aiming at providing workers with improved and more sustainable working conditions, such as a less distressing environment and more supportive managerial styles.

The spatial clustering of life satisfaction scores noted in recent empirical research suggests that ‘happier’ people may live in specific neighbourhoods or regions. This prompts the questions: Do ‘happier’ people choose to move to specific places? Does living in specific places make people ‘happier’? To answer these questions, this paper explores possible occurrences of selective mobility, and social and ecological influence. Using panel data collected in Australia from 2013 to 2021, we examine the association between life satisfaction scores and selective geographic mobility, and the possible influence that living at specific locations may have on individual life satisfaction trajectory, while controlling for individual personality traits and socio-demographic factors. Our results indicate that urban residents reporting lower life satisfaction scores before the move have a higher probability of moving to a rural area. Similarly, lower life satisfaction scores are associated with a higher probability of moving to a region with a different climate. We also find evidence that moving from the city to the country is associated with an uplift of the life satisfaction trajectory for the individual. A similar conclusion is reached for people who moved to a warmer climate, but not for a move to a cooler climate. To our knowledge, this is the first time the concepts of selective mobility and social and ecological influence have been applied in life satisfaction research. Our work provides an indicator that can be important to demographers predicting population movements. It can also inform policy development around assisting regional and rural areas attract/ retain residents to support regional sustainability.

This research provides an overview of the challenges in analyzing multidimensional social exclusion data using multiple indicators. It highlights the importance of composite indicators in simplifying the understanding of complex realities. Grounded in this literature, the research proposes a new approach to address the issues related to the multispatial and multitemporal analysis of composite indicators, contributing to the existing body of knowledge in this area. To illustrate its potential, social exclusion measures proposed by the Center for Studies and Mapping of Social Exclusion for Public Policies are used for two southern Brazil municipalities. This framework considers demographic, economic, educational, and household dimensions and fourteen variables. The proposed approach offers two significant contributions: firstly, it prevents outliers from heavily influencing the normalized sub-indicators and composite indicators during the scale transformation process. Secondly, it provides a solution compatible with the three-dimensional nature of the problem, thereby enhancing the multitemporal analysis of composite indicators.

Interest in the study of economic insecurity has grown in recent years. However, the ongoing debate about how to measure it remains unresolved. On the assumption that economic insecurity is related both to the forward-looking perception of future outcomes based on past experience and to the perception of one’s own situation compared to others in the present, we propose a class of objective individual composite inter-temporal indices of economic insecurity. The indices are obtained by combining two components, one longitudinal and one cross-sectional. In order to combine the two components, we propose a novel method that takes advantage of the availability of subjective self-assessments of one’s own economic conditions. The composite inter-temporal index is applied to the European Union-Statistics on Income and Living Conditions (EU-SILC) Longitudinal Dataset, encompassing a selection of European countries. Our analysis shows that the proposed class provides new insights into individual perceptions of well-being that are not captured by poverty and inequality measures. It also provides individual measures that can be used to study the relationship between economic insecurity and other phenomena.

Cities, in order to develop, should acquire data from various sources, properly process it, and skillfully use it for sustainable development. One such source is data from the surveys of residents’ quality of life. When processed as appropriate, the data may be a valuable source of information concerning sustainable development for the city. However, the very fact of carrying out the quality-of-life surveys does not guarantee that the information obtained from them will be used to manage the city. Based on studies entailing a sample of 29 city offices in Poland which declared regular studies of the residents’ quality of life, it was proved that the preparation and organization of such studies influences later use of such information for sustainable development purposes. Relying on the method of examining the quality of life and the number of specific indicators, the cities studied were divided into two groups. One was involved, and the other was not in the process of preparing quality-of-life surveys. A comparison was made between these groups of cities in terms of the areas included in the quality of life surveys, the decisions and actions taken based on the analysis of the results of these surveys, and the purposes for which the information is used. The areas in which the local government declares an impact on the quality of life of its residents were also compared. Attention was paid to significant differences between the two groups of cities and the effects of each of those two approaches were specified.

The digital transformation, in which we have actively participated over the last decades, involves integrating new technology into every aspect of the business and necessitates a significant overhaul of traditional business structures. Recently there has been an exponential increase in the presence of Artificial Intelligence (AI) in people’s daily lives, and many new AI-infused products have been developed. This technology is relatively young and has the potential to significantly affect both industry and society. The paper focuses on the Intelligent Voice Assistants (IVAs) and the User eXperience (UX) evaluation. IVAs are a relatively new phenomenon that has generated much academic and industrial research interest. Starting from the contribution to systematization provided by the Artificial Intelligence User Experience (AIXE^®) scale, the idea is to develop an easy UX evaluation tool for IVAs that decision-makers can adopt. The work proposes the Partial Least Squares-Path Modeling (PLS-PM) to investigate different dimensions that affect the UX, and to verify if it becomes possible to quantify the impact and performance of each dimension on the general latent dimension of UX. The Importance Performance Matrix Analysis (IPMA) is utilised to evaluate and identify the primary factors that significantly influence the adoption of IVAs. IVA developers should examine the main aspects as a guide to enhancing the UX for individuals utilising IVAs.

This study examines spatial disparities and associations between the social deprivation index (SDI) and Type 2 Diabetes, Dementia, and Heart Failure in Italy’s Lazio Region. The primary goal is to assess how social deprivation impacts health inequalities by analysing SDI-disease correlations. This retrospective study uses 2020 socioeconomic data and 2021 epidemiological indicators in Lazio Region, Italy. The SDI, constructed following established guidelines, measures social deprivation. Statistical tools, including regression models, Moran’s I test, and LISA techniques, are used to analyse spatial patterns. Utilizing a retrospective approach, we merge 2020 socioeconomic and 2021 epidemiological data for analysis. The SDI is computed using established methods. Spatial disparities are explored through regression models, Moran’s I test, and LISA techniques. The study reveals significant disparities in disease incidence. District V in Rome exhibits high Type 2 Diabetes (113.75/1000) and Heart Failure (37.98/1000) rates, while Marcetelli has elevated Dementia incidence (19.74). Southern municipalities face high unemployment (up to 25%), whereas bordering areas have higher education levels (30–60%). Disease hotspots emerge in Rome and centre-north municipalities, aligning with social deprivation patterns. Regression models confirm the link between disease incidence and socioeconomic indicators. SDI ranges from − 1.31 to + 10.01. This study underscores a correlation between social deprivation and disease incidence. Further national-level research is essential to deepen our understanding of how social deprivation influences health outcomes, with potential implications for addressing health disparities both regionally and nationally.

Given recent controversies about the existence of a gender wellbeing gap we revisit the issue estimating gender differences across 55 SWB metrics—37 positive affect and 18 negative affect—contained in 8 cross-country surveys from 167 countries across the world, two US surveys covering multiple years and a survey for Canada. We find women score more highly than men on all negative affect measures and lower than men on all but three positive affect metrics, confirming a gender wellbeing gap. The gap is apparent across countries and time and is robust to the inclusion of exogenous covariates (age, age squared, time and location fixed effects). It is also robust to conditioning on a wider set of potentially endogenous variables. However, when one examines the three ‘global’ wellbeing metrics—happiness, life satisfaction and Cantril’s Ladder—women are either similar to or ‘happier’ than men. This finding is insensitive to which controls are included and varies little over time. The difference does not seem to arise from measurement or seasonality as the variables are taken from the same surveys and frequently measured in the same way. The concern here though is that this is inconsistent with objective data where men have lower life expectancy and are more likely to die from suicide, drug overdoses and other diseases. This is the true paradox—morbidity doesn’t match mortality by gender. Women say they are less cheerful and calm, more depressed, and lonely, but happier and more satisfied with their lives, than men.

This article examines the association between institutional quality, natural resources and multidimensional well-being in Saudi Arabia from 1990 to 2021, filling a notable gap in the existing literature on the linkage between human well-being and natural resources in a country with significant global energy influence. By integrating Sen's capabilities approach and constructing comprehensive indices of human well-being, including quality of life (QL) and standard of living (SL), this study specifically investigates the direct effects of natural resources wealth on these two indices and emphasizes the role of institutional quality as a transmission channel. The results show that natural resources, particularly total natural resource rents and oil rents, have positive direct effects on QL and SL, suggesting that effective resource management can enhance human well-being and economic prosperity. Furthermore, institutional quality plays a key role in shaping this relationship, with factors such as institutional quality index, government stability, and law and order having net positive effects on QL and SL. The study also identifies critical thresholds for controlling corruption, beyond which the positive effects of natural resource rents on QL and SL become more pronounced. These results highlight the importance of accountable and strong institutions to ensure equitable distribution of benefits from natural resources for human well-being.