Search Results (119)

Sustainable education requires addressing the challenges posed by digital transformation, including technostress among university students. This study evaluates technostress levels in higher education through the validation of the TS4US scale and its implications for sustainable learning environments. A cross-sectional study was conducted with 328 university students from four districts in Lima, Peru, using an online survey to measure technostress. Confirmatory factor analysis (CFA) was performed to assess the psychometric properties of the TS4US scale, resulting in a refined model with two latent factors and thirteen validated items. Findings indicate that 28% of students experience high technostress levels, while 5% report very high levels, though no significant associations were found between technostress and sociodemographic variables such as campus location, employment status, gender, and academic level. The TS4US instrument had been previously validated in Chile; this study confirms its structure in a new sociocultural context, reinforcing its cross-cultural applicability. These results highlight the need for sustainable strategies to mitigate technostress in higher education, including institutional support, digital literacy programs, and policies fostering a balanced technological environment. Addressing technostress is essential for promoting sustainable education (SDG4) and enhancing student well-being (SDG3). This study directly contributes to the achievement of Sustainable Development Goals 3 (Good Health and Well-being) and 4 (Quality Education) by providing validated tools and evidence-based recommendations to promote mental health and equitable access to digital education in Latin America. Future research should explore cross-country comparisons and targeted interventions, including digital well-being initiatives and adaptive learning strategies, to ensure a resilient and sustainable academic ecosystem. Full article

This entry explores the multifaceted intersections of gender and digital technologies, offering a comprehensive analysis of how structural inequalities are reproduced, contested, and transformed in digital contexts. It is structured into six interrelated sections that collectively address key dimensions of gendered digital contexts. It begins by addressing the gender digital divide, particularly in the Global South, emphasizing disparities in access, literacy, and sociocultural constraints. The second section examines gendered labor in the tech industry, highlighting persistent inequalities in Science, Technology, Engineering, and Mathematics (STEM) education, employment, and platform-based work. The third part focuses on gender representation in digital spaces, revealing how algorithmic and platform design perpetuate biases. The fourth section discusses gender bias in AI and disinformation, underscoring the systemic nature of digital inequalities. This is followed by an analysis of online gender-based violence, particularly its impact on marginalized communities and participation in digital life. The final section considers the potentials and limitations of digital activism in advancing gender justice. These sections collectively argue for an intersectional, inclusive, and justice-oriented approach to technology policy and design, calling for coordinated global efforts to create equitable digital futures. Full article

The transition to clean energy is not inherently positive or negative, and its impacts depend on the social context, power relations, and mechanisms to include marginalized voices. India, with its ambitious climate targets and commitment to the UN SDG Agenda, is a key country for ensuring an inclusive and sustainable transition. This paper aims to understand whether India’s commitment to the SDG Agenda’s overarching principle of ‘leaving no one behind’ is reflected in the design of its domestic solar policies. It analyzes how energy justice concerns are addressed in state-level solar policies. To that end, a pragmatic framework was developed to identify key justice dimensions and indicators, linked to the SDG targets, that are essential for an inclusive transition. This research conducted a qualitative interpretive content analysis of 29 solar energy policies, using the three identified framework dimensions—income growth, enhancing inclusion, and equal opportunities. We found that the themes around energy access, employment, and skill development are reflected in policies, while those around the inclusion of the poor, women, and community remain limited. The findings indicate that the policies have focused on low-impact justice concerns, lacking structural transformation. To address these gaps, the study proposes targeted subsidies, community ownership, and gender-inclusive mechanisms. The framework offers a pragmatic tool for the evaluation of clean energy policies in the Global South, and the empirical results provide insights for the synergistic implementation of the climate and sustainable development agenda. Full article

With the rapid advancement of artificial intelligence and smart manufacturing technologies, the penetration of industrial robots into Chinese markets has profoundly reshaped the structure of the labor market. However, existing studies have largely concentrated on the employment substitution effect and the diffusion path of these technologies, while systematic analyses of how industrial robots affect labor resource allocation efficiency across different regional and industrial contexts in China remain scarce. In particular, research on the mechanisms and heterogeneity of these effects is still underdeveloped, calling for deeper investigation into their transmission channels and policy implications. Drawing on panel data from 280 prefecture-level cities in China from 2006 to 2023, this paper employs a Bartik-style instrumental variable approach to measure the level of industrial robot penetration and constructs a two-way fixed effects model to assess its impact on urban labor misallocation. Furthermore, the analysis introduces two mediating variables, industrial upgrading and urban innovation capacity, and applies a mediation effect model combined with Bootstrap methods to empirically test the underlying transmission mechanisms. The results reveal that a higher level of industrial robot adoption is significantly associated with a lower degree of labor misallocation, indicating a notable improvement in labor resource allocation efficiency. Heterogeneity analysis shows that this effect is more pronounced in cities outside the Yangtze River Economic Belt, in those experiencing severe population aging, and in areas with a relatively weak manufacturing base. Mechanism tests further indicate that industrial robots indirectly promote labor allocation efficiency by facilitating industrial upgrades and enhancing innovation capacity. However, in the short term, improvements in innovation capacity may temporarily intensify labor mismatch due to structural frictions. Overall, industrial robots not only exert a direct positive impact on the efficiency of urban labor allocation but also indirectly contribute to resource optimization through structural transformation and innovation system development. These findings underscore the need to account for regional disparities and demographic structures when advancing intelligent manufacturing strategies. Policymakers should coordinate the development of vocational training systems and innovation ecosystems to strengthen the dynamic alignment between technological adoption and labor market restructuring, thereby fostering more inclusive and high-quality economic growth. Full article

European integration aims to achieve spatially sustainable development across the member states. However, the success of socio-economic integration is conditioned by structural features of the economies, which, hitherto, appear highly diversified across the EU countries. The paper focuses on the structural conditions of the process of income inequality convergence. It aims to identify differences in the convergence regarding the structural conditions of the economies. To fulfil the research tasks the paper classifies the 27 European member states according to their sectional employment structures using the Ward method. It then tests the appearance of beta convergence using FE panel models for the specified clusters of economies. It also considers structural change, measured by the NAV (norm of absolute value), as a determinant of income inequality convergence. The main research period covers 2009–2021. The findings of the paper confirm that income inequality convergence occurs within the groups of economies specified by different structural conditions. Importantly, the clustering according to the similarity of the employment structure overlaps with the division along the lines of the ‘new’ and ‘old’ member states, which proves the importance of historically shaped institutions for development. However, the observed convergence does not lead to improved social cohesion. Social policy, especially in the ‘new’ member states, is not able to offset the growth in market income inequality additionally stimulated by the structural changes. It can be concluded that an urgent need to design new solutions for social policy concerning structural transformation in employment in the EU emerges. Full article

The digital transformation of enterprises constitutes a crucial element of modernization processes in the countries of the European Union, supporting the achievement of sustainable development goals through increased innovation, economic efficiency and the development of high-tech sectors and knowledge-intensive services. In empirical analyses, multidimensional statistical analysis methods were applied, with particular emphasis on linear ordering, classification methods and regression analysis. Ten monitoring indicators adopted by the European Union constitute the basis for assessing the digital transformation advancement of enterprises. The study classified EU countries into three groups according to the level of digital transformation: low, medium and high. Based on the employment structure in high-tech manufacturing, medium–high-tech manufacturing and knowledge-intensive services, four distinct types of employment structures were identified. A positive relationship was found between the level of digital transformation and the share of employment in knowledge-intensive services, while no significant relationship was observed for the other sectors. The study shows that the EU countries are clearly differentiated both in terms of the level of digital transformation of enterprises and the structure of employment in high-tech manufacturing, medium–high-tech manufacturing and knowledge-intensive services. A higher level of digital transformation supports the growth of employment in knowledge-intensive services, while its impact on high-tech and medium–high-tech manufacturing remains limited. Full article

Low-carbon transformation and common prosperity are critical pillars of China’s economic growth. To explore the mechanism relating the two, this paper analyzes how carbon efficiency influences the urban–rural income gap, including its transmission mechanism and heterogeneity, and uses panel data from 240 Chinese prefectural cities (2006–2019). The results reveal an “inverted U-shaped” relationship between the low-carbon transition and urban–rural income gap. Specifically, as the carbon emission efficiency improves, the impact of the low-carbon transition on the urban–rural income gap changes from positive to negative. This finding remains robust under robustness tests. The heterogeneity test indicates that the “inverted U-shaped” relationship exhibits regional heterogeneity, resource endowment heterogeneity, economic development stage heterogeneity, and urban–rural income gap level heterogeneity. Furthermore, urban low-carbon transition influences the urban–rural income gap through industrial structure, employment structure, and human capital. This paper discusses the combination of low-carbon transformation and common prosperity, and takes into account both ecological sustainability and social sustainability. The findings of this paper offer policy proposals for advancing the achievement of dual-carbon goals and common prosperity, and provide references for developing countries. Full article

Following the 2008–2009 economic crisis, the issue of self-employed individuals’ access to social protection has gained increasing prominence at both supranational and national levels, often in relation to the rise of ‘bogus’ or economically dependent self-employment and its broader implications. More recently, the COVID-19 pandemic further exposed persistent gaps in the social protection of the self-employed, contributing to their comparatively more precarious position vis-à-vis wage earners. Against this backdrop, and drawing on a literature review alongside findings from a series of semi-structured interviews, this article uses Greece—a country where self-employment constitutes a structural feature of a highly fragmented labour market, and which records the highest self-employment rate in the EU-27 (and among the highest in the OECD)—as a case study to examine self-employment and access to social protection. This article contributes to the growing literature on the social protection of non-standard workers in a context marked by ongoing transformations in employment relations and the world of work. It illustrates, inter alia, the relative weakness of trade union representation for the self-employed, and how limited trust in state institutions among this group shapes their perceptions of social protection, thereby undermining the system’s sustainability. Full article

The rise of knowledge-based economies has positioned higher education institutions as key actors in human capital development, requiring them to engage more actively with labor markets through strategic partnerships. Within this context, university-affiliated science and technology parks (STPs) have evolved into integrated learning environments that support experiential learning and mentorship practices. This study aims to explore the lived experiences of undergraduate students who participated in these processes within an STP in İstanbul, Türkiye. Using a qualitative phenomenological approach, data were collected through semi-structured interviews with 15 students selected via purposive maximum variation sampling. Thematic analysis, supported by MAXQDA 2024, was used to examine the data. Two main themes were identified: (i) talent development through experiential learning and (ii) talent development through mentorship. The findings indicate that students reconstructed theoretical knowledge through real-world applications, developed a clearer professional identity, and gained strategic career awareness. Mentorship provided both technical and psychosocial support, fostering self-confidence, emotional security, and role modeling. This study concludes that STPs play a strategic role in aligning academic learning with employability and institutional talent development goals. These results contribute to broader educational and workforce development discussions and are closely aligned with Sustainable Development Goals 4 (Quality Education) and 8 (Decent Work and Economic Growth), highlighting STPs as transformative platforms in higher education. Moreover, this study offers practical implications for aligning higher education with employment systems through structured experiential learning and mentorship practices. Full article

With the advancement of global economic restructuring and China’s economic transformation, structural employment contradictions have intensified amid increasingly competitive labor markets. The frequent occurrences of “degree devaluation” and talent “downskilling” have made perceived overqualification increasingly prevalent in organizations. This study, based on the Cognitive–Affective Personality System theory, investigates the differential mechanisms through which perceived overqualification drives approach and avoidance job crafting via cognitive and affective pathways. Data from a two-wave survey of 556 Chinese employees produced several key findings: (1) Perceived overqualification significantly enhances approach job crafting while suppressing avoidance job crafting by elevating role breadth self-efficacy (cognitive pathway), demonstrating a proactive breakthrough effect. (2) Perceived overqualification inhibits approach job crafting and exacerbates avoidance job crafting through triggering emotional exhaustion (affective pathway), revealing a passive exhaustion trap. (3) Perceived overqualification exerts a positive and significant overall indirect effect on approach job crafting through the combined mechanisms of cognitive gains from role breadth self-efficacy and affective costs from emotional exhaustion, whereas the overall indirect effect on avoidance job crafting is non-significant. (4) Idiosyncratic deals (i-deals) function as a dynamic boundary mechanism that amplifies the positive impact of role breadth self-efficacy and mitigates the negative effects of emotional exhaustion, while moderating the mediating roles of both pathways. This research develops a dual-path integrated model of perceived overqualification and job crafting by classifying job crafting categories, incorporating cognitive–affective pathways, and introducing i-deals as a contextual element. These findings respond to scholarly demands for elucidating the intricate connections between perceived overqualification and job crafting through integrative perspectives; in addition, they offer theoretical and practical insights for organizations to leverage the potential of overqualified individuals appropriately. Full article

Millions of young Africans earn a variety of qualifications annually, yet the majority return without prospects for employment. This challenge has become a catalyst for inequality, poverty, crime involvement, and international migration. Empirical discourse points to education—such as a pedagogy that is chiefly theory-oriented rather than aligned with a knowledge economy, mismatched skills, and irrelevant qualifications—as constraints that contribute to the unemployment of the continent’s vibrant young graduates. Amidst this surging issue, the call for transformation in higher learning has never been clearer. Focusing on rural landscapes, this case study analysed the contextual employability potential of graduates pursuing an entrepreneurial university trajectory in Africa, illustrating why the paradigm should be implemented. The findings, based on qualitative data collected using a semi-structured questionnaire through one-on-one and remote approaches from stakeholders in universities across five African countries, highlight three dimensions central to this pathway. These include (1) curriculum alignment to advance cutting-edge qualifications and skill development that resonate with industrial demand and local economic priorities; (2) stakeholder embeddings in which universities strive to partner with local organisations and established alumni to provide mentorship, job leads, and referrals; and (3) innovation hubs that offer a variety of entrepreneurial support, real-world experience, and Indigenous entrepreneurship practices, leading to unique new ventures and employment opportunities. Implementing this strategy will enable rural-based universities in Africa to innovate in promoting graduate employability, socioeconomic advancements, and sustainable development, ultimately shaping a brighter future for the continent. Further studies could test the assumptions for broader application using statistical analysis. Full article

This study examines the impact of structural characteristics of agricultural holdings on their agricultural performance and contribution to rural development in EU countries over the past decade to identify potential measures to enhance rural development. The results of the paired samples t-test reveal a structural shift in EU agriculture between 2010 and 2020 toward larger, more productive, and capital-intensive farms alongside a decline in small-scale and subsistence farming, improved agricultural incomes, and rural economic growth. However, persistent challenges such as rural depopulation, declining employment, and ongoing poverty remain. A cluster analysis identified five distinct agricultural models and reflects some notable transitions: Eastern European countries increasingly moved toward mixed farming (e.g., Latvia, Lithuania, and Hungary) or large-scale commercial farming (e.g., the Czech Republic, Estonia, and Slovakia), subsistence and small-scale farming became more concentrated in Bulgaria and Romania, and Western and Northern countries maintained high levels of modernization, with Ireland progressing and the Netherlands standing out as a distinct high-tech agricultural model. The five distinct agricultural clusters identified underline the need for regionally tailored policies. Hierarchical regression shows that while improvements in agricultural performance, particularly increased labor productivity, contribute to rural GDP per capita growth, they have a limited impact on rural poverty. Therefore, enhancing sustainable rural development requires more comprehensive and integrated strategies that not only promote productivity-driven agricultural reforms and innovation in advanced systems but also address the specific needs of lagging countries through structural transformation, capacity building, and targeted support. Full article

Setúbal Peninsula (SetPe) has played a critical role in Portugal’s industrial history, symbolizing economic growth in the 1960s and serving as the centre of the working-class movement during the Carnation Revolution. This study examines the impacts of deindustrialisation and integration into Global Network and Chain Structures (GNCS) on the region’s daily life and urban areas. Despite the decline in industrial employment and the challenges posed by abandoned industrial areas, the region has remained connected to GNCS through existing industrial facilities. The study utilised both quantitative and qualitative methods to analyse these transformations and highlighted the region’s vulnerability in the face of these global processes. The findings suggest that integration into GNCS in SetPe has led to economic dependence on multinational companies, social and cultural decline, and challenges in urban redevelopment. Full article

In this article, we examine the theoretical concept of hybrid masculinities from a praxeological perspective, focusing on fathers as caring parents. Examining the development of parenting practices and parental knowledge exchange, we conducted couple interviews with 42 couples (n = 42, 2021 and 2022) and analyzed how fathers’ and couples’ motivations for sharing parental leave (PL) and childcare allowance (CA) in Austria shape fatherhood practices. All interviewees had claimed CA for a minimum duration of five months. Since infant care has only recently been incorporated into normative constructions of masculinity, our praxeological analysis centers on fathers. By applying the theoretical concept of hybrid masculinities, we examine these practices which are still perceived as “new”. In the couple interviews we conducted, we analyzed the reports and views of both parents, which tended to be more fully expressed when the parents interviewed were in conversation with each other. We applied topic-specific content analysis and Informed Grounded Theory to analyze the empirical data, guided by semi-structured interview protocols and coded with MAXQDA. Our findings indicate that fathers successfully take on and embody caregiving responsibilities. However, they also continue to conform to traditional constructions of masculinity, particularly in their long-term reconciliation of childcare and employment. Considering international PL and CA policies, we discuss the relationship between parents’ dual PL uptake and social sustainability in the transformation of gendered parenting norms and the reduction in gender inequalities. Full article

The quality of employment is significantly impacted by the transformation of global labor markets resulting from artificial intelligence (AI). This study investigates the impact of AI on employment quality in China, with an emphasis on regional disparities between prefecture-level cities. Using panel data and a two-way fixed-effects model, we investigate how AI adoption affects employment outcomes, taking into account industrial structure and economic development. The findings show that while AI adoption increases productivity, it has varying implications on employment quality due to geographical differences. Relevant government rules and focused policies are critical for reducing negative impacts and encouraging long-term employment. This research makes concrete recommendations for policymakers and contributes to the worldwide conversation about AI and labor market developments. Full article