Search Results (478)

People with disabilities face multiple challenges in the labor sphere, including barriers to access, discrimination, lower job stability, and limited opportunities for development, all of which restrict their economic and social participation. In response to this reality, public policies aimed at labor inclusion have gained increasing relevance due to their potential to reduce inequalities and strengthen social sustainability. The aim of this study was to analyze public policies designed for the labor inclusion of people with disabilities by identifying their main characteristics, target populations, implementation barriers, and their relationship with social sustainability. The PRISMA methodology was applied, and, as a result of the search, selection, and evaluation process, 75 primary studies were included in the analysis. The results show that policies are mainly concentrated on measures to facilitate access to employment, incentives for employers, and vocational training, while entrepreneurship receives less attention. Most policies are directed toward people with disabilities in general, with limited attention to specific subgroups. Persistent barriers were identified, including prejudice, weak institutional coordination, and a gap between regulatory frameworks and their effective implementation. It is concluded that, although these policies show progress in terms of inclusion, their contribution to social sustainability depends on more effective, better coordinated, and more responsive implementation that takes into account the diversity of needs within this population. Full article

Feature prioritization in early-stage software startups is a critical yet poorly structured challenge, as prevailing frameworks rely predominantly on expert intuition and fail to exploit patterns latent in historical delivery data and labor market dynamics. This study proposes a deep learning framework that explores labor-market signals as a reproducible proxy for market-driven feature prioritization. The framework encodes two complementary information sources: internal sprint delivery history processed by a Bidirectional Long Short-Term Memory network with attention, and external market signals from LinkedIn job postings processed by a Convolutional Neural Network encoder; the resulting representations are fused via a cross-modal layer to classify job postings as proxies for High or Low feature-priority market demand. The model is evaluated on the publicly accessible LinkedIn Job Postings dataset (2023–2024, approximately 124,000 records) and achieves an Area Under the Receiver Operating Characteristic Curve of 0.961 on the proxy classification task, outperforming classical baselines including gradient Boosted Trees, Random Forest, Support Vector Machine, and Logistic Regression. SHapley Additive exPlanations analysis identifies industry sector and geographic location as the two most influential market-signal predictors. These results suggest that jointly encoding internal delivery dynamics and external market signals offers a promising, scalable decision-support tool to assist startup product teams in data-driven roadmap prioritization, subject to further validation against direct expert priority labels. Full article

Background: Battery Electric Vehicles (BEVs) are often proposed as a promising solution to increase sustainability in the transport sector. Whilst BEVs may solve some of the negative effects of traffic problems in cities, those models predominantly sold nowadays do not alleviate, among other things, congestion or parking pressure in cities, and may not offer the most affordable mode of transport available. Methods: The effective accessibility levels provided by BEVs and quadricycles (i.e., L6e and L7e) were compared in England and Wales. Effective accessibility not only includes driving time as an impedance but also accounts for the hours required to earn the funds to pay for the commute. Results: The lower speeds of L6e and L7e quadricycles certainly limits the number of jobs reachable when compared to a BEV in a time-based accessibility comparison. However, once the time spent at work is taken into account, then L6e and L7e quadricycles often win the ‘competition’—especially for people with modest means. Conclusions: This study shows that for some, commuting by BEV is the most time-efficient mode of transport. For individuals constrained by time or income, L6e and L7e quadricycles may serve as a more expedient choice of travel. Full article

Why are essential workers (also known as key workers) priced out of the urban areas where essential services are concentrated? This paper addresses that question by linking residential sorting to the governance of land and housing markets in Auckland, New Zealand. Drawing on bid rent theory and motivated by Crane’s theoretical framework, this study examines how households trade off urban accessibility against housing costs with varying degrees of job location uncertainties and time pressure. The analysis uses the micro-level household data from Statistics New Zealand (Stats NZ)’s Integrated Data Infrastructure (IDI) to examine how key-worker households position themselves within the city’s rental market relative to other working households. The results show a clear urban land rent gradient: rents fall with distance from the city centre. However, access to the central location is not evenly distributed across workers. Key workers, whose jobs are typically tied to more fixed workplaces, are more inclined to live farther from the city centre to lower housing costs. By contrast, workers facing tighter time constraints, especially those working longer hours, show a stronger preference for living near the CBD to improve work proximity and reduce commuting burdens. This pattern remains evident among private vehicle commuters, suggesting that time pressure, rather than transport mode alone, is an important factor shaping residential location choice. The paper argues that this is not simply a housing market outcome but also a land-governance problem. When central land values rise without corresponding housing options for key workers, cities risk pushing socially necessary labour towards peripheral areas. The findings highlight the need for land-use and housing interventions that improve the spatial match between where key workers live and where urban services are most needed. Full article

Managing classroom tablets involves more than electrical charging; it also requires repeated retrieval and return, storage, plug alignment, custody, and queue control. This article presents the human-centered engineering design and field validation of a drawer-type tablet/laptop charging cart for kindergarten-to-grade-12 digital learning infrastructure. Its main contribution is a bilateral drawer-access architecture that converts a conventional front-door, single-queue cabinet into a two-sided parallel-handling product, with design decisions linked to observed school workflows through Lean Product and Process Development, jobs-to-be-done inquiry, opportunity scoring, competitor benchmarking, product-essence mapping, and prototype testing. Field observations at three schools identified six critical handling events; effective storage with reduced queueing was the highest-priority opportunity (importance = 8.6, satisfaction = 5.7, opportunity score = 11.5). Among four access concepts, the drawer-type concept achieved the shortest handling time (4.4 s/device), outperforming front-opening fixed-shelf (7.2 s/device), front-opening movable-rack (8.2 s/device), and top-opening (6.8 s/device) concepts. In classroom validation, average handling time decreased from 10.9 to 4.8 s/device, and throughput increased from 5.5 to 12.5 devices/min. These design-stage, descriptive results indicate that bilateral drawer access can reduce serial queueing while preserving storage, charging, and custody functions. They support prototype refinement rather than population-level causal inference. Full article

Studentpreneurship has gained prominence in South Africa as universities are increasingly expected to foster innovation, job creation, and youth participation in the economy. However, despite the establishment of incubators, entrepreneurship centres, mentorship programmes, and EDHE-aligned initiatives, support for studentpreneurs remains unevenly implemented, poorly integrated, and inconsistently accessible, particularly within a historically disadvantaged university. This study examines how university support mechanisms shape the experiences, challenges, and business development trajectories of studentpreneurs in a South African university. Guided by Entrepreneurial Ecosystem Theory, the study adopts a qualitative research design involving in-depth interviews with 15 studentpreneurs. Thematic analysis reveals significant gaps in awareness, accessibility, and continuity of institutional support. While students valued motivational workshops, pitching opportunities, and limited mentorship, these interventions lacked sustained follow-up, sector-specific guidance, and financial or infrastructural resources necessary for business growth. The study contributes to South African entrepreneurship scholarship by highlighting the lived realities of studentpreneurs at a historically disadvantaged university and by proposing institutional reforms to build more coherent, equitable, and sustainable studentpreneurship ecosystems. Full article

Tourist guides remain understudied in tourism workforce research, particularly regarding the conditions shaping satisfaction and career retention. This study examines how cultural tourism itinerary characteristics are associated with tourist guides’ job satisfaction and career retention intentions. Data were collected through a convenience sample survey of 127 active tourist guides in Portugal. Grounded in the Job Satisfaction Survey and the Theory of Planned Behaviour frameworks, the study utilised exploratory factor analysis and multiple linear regression to analyse the data. Results indicate positive associations between itinerary characteristics, job satisfaction and career retention intentions, with Components (accommodation, meals, accessibility) and Sustainability emerging as the strongest predictors. These findings extend the Job Demands–Resources model to a supervisory-free work context and highlight itinerary design as a previously underexplored human resource management mechanism shaping workforce outcomes in tourism, with implications for tour operators, destination managers and policymakers. Full article

As data volumes grow and business requirements become increasingly complex, Hybrid Transactional/Analytical Processing (HTAP) technologies, capable of handling both Online Transaction Processing (OLTP) and Online Analytical Processing (OLAP) workloads on a single platform, have gained prominence. HTAP databases typically maintain dual data storage formats and dual query engines: one row-oriented for OLTP, and another column-oriented for OLAP. Query plans, known as hybrid plans, can be segmented and pushed down to execute on these different formats. However, existing HTAP solutions still face challenges in optimizing these hybrid plans, struggling to explore the vast space of potential execution strategies effectively. To address these issues, this study introduces a learning-based query optimizer for row–column dual store HTAP database systems, which automatically generates multiple high-quality query optimizer hints (HINTs) to derive candidate plans. To balance plan generation efficiency with plan quality, a lightweight, learning-based algorithm using Monte Carlo Tree Search (MCTS) for generating hybrid access HINTs is proposed. Moreover, a Transformer-based neural network model coupled with a hybrid plan feature representation method is developed to select the candidate execution plan with the lowest predicted execution time. This work focuses on latency-oriented hybrid-plan selection for analytical queries in a row–column dual-store HTAP architecture; the current evaluation does not cover full mixed OLTP/OLAP workload scheduling, transactional interference, or concurrency control, which are left as future work. Experimental results on AlloyDB Omni, a recent row–column dual-store HTAP database, using the real-world IMDB dataset and JOB benchmark demonstrate that our system reduces execution time by 75.02% compared to the Cost-Based Optimizer (CBO) and by 62.23% compared to the state-of-the-art row-store-based learning query optimizer in this evaluated analytical-query setting. Full article

The digital economy has changed the way agricultural production is organized and how rural households access markets, jobs, and information. Yet it remains unclear whether these changes translate into higher income for rural residents, especially in major agricultural regions. This study examines the income effect of digital infrastructure development by using the rollout of the Broadband China policy as a quasi-natural experiment. The analysis draws on panel data for 77 prefecture-level administrative units in the Yellow River Basin, one of China’s major agricultural regions, from 2009 to 2021. A staggered difference in differences model is used to estimate the policy effect. The results show that digital infrastructure development significantly increases rural residents’ income. Under the log income specification, the baseline coefficient indicates an average income increase of about 8.33%. The mechanism analysis shows that innovation capacity and nonfarm employment both serve as positive partial transmission channels, with innovation capacity explaining a larger share of the total effect. The heterogeneity results suggest that the income effect is stronger in regions with higher GDP and larger population size. These findings indicate that digital infrastructure can support rural income growth when it is linked with local innovation capacity, employment opportunities outside agriculture, and rural development policies suited to local conditions. Full article

Although Non-Wood Forest Products can offer interesting economic opportunities for rural communities, little is known about their commercial harvesters. Our work aims to shed light on the labour profiles, their accessibility to new entrants, and attractiveness for future green jobs. Through in-depth interviews, we explored the five-capitals profile of commercial resin, cork, mastic foliage, chestnut, pine nut, and wild mushroom harvesters in Spain. We found either freelance harvesters or entrepreneurs with a small gang. Our data show a typical male collector, who started the activity through his social networks (Social Capital), and whose origin depends on the product and Spanish region. Some commercial female harvesters were found in mushroom, chestnut and resin harvesting. Social constructs around the masculinization of these activities may explain their limited attractiveness for women. The ratio of non-Spanish commercial harvesters correlates with the weight of migrants in the analysed regions. Only a subgroup of resin harvesters devotes most of their year to this single activity. The rest complement NWFP income with a main forestry (cork and pinenut) or non-forestry occupation (mushroom, chestnut and mastic). For the latter products, access to Natural Capital was found to be crucial for job progress, as non-landowners require administrative and/or negotiation capacities to secure harvesting permits. Human Capital differs across NWFPs, from simpler skills such as recognising marketable produce and handling easy tools (mushroom, chestnuts, pine nut ground gathering and mastic), to complex abilities needed to balance efficiency with minimising tree damage (in resin tapping, pinenut shaking, and cork extraction). Such specialised tools and machinery (Built Capital) typically act as a barrier to entry and advancement. These profiles are expected to help decision-makers to design instruments promoting and regulating commercial harvesting, and tackle their risks: local landowners in allocating harvesting rights to external collectors; regional policymakers as competent authorities in forest legislation; and state-level administration concerning cultural, fiscal and labour-permit aspects. Full article

Higher education institutions (HEIs) play a significant role in shaping young people’s perceptions, thus making European and civic education a valuable asset in promoting European Union (EU) values. Previous research suggests that socio-political and socio-economic developments in the Western Balkans may influence educational aspirations and language learning goals. In this context, English learning motivation increasingly appears to be driven by instrumentality-promotion orientations. During the 2024/2025 academic year, 141 students from Croatian and Serbian universities took part in research aimed at determining the relationship between their self-perceived knowledge of the EU and their motivation to use English to ensure better education and EU job market competitiveness. Students in both countries consider English an important asset for future education and employability. At the same time, they perceive themselves as insufficiently informed about the EU, suggesting possible disparities in access to civic and EU-related knowledge. The findings tentatively suggest that HEIs may benefit from reconsidering aspects of their civic and EDE policies, particularly in terms of ensuring equitable access to EU-related knowledge and fostering inclusive pathways toward global readiness. Full article

The COVID-19 pandemic contributed to more severe and frequent intimate partner violence (IPV) among victims, and less availability of services; however, this research has largely been conducted on only female victims. We investigated the COVID-19 pandemic’s contribution to more severe and frequent IPV among male victims, barriers to getting help, and factors contributing to both increased severity/frequency and barriers. Participants included 318 male IPV victims from English-speaking Western countries who reported being the victim of IPV during the pandemic. They completed a Qualtrics questionnaire asking about their IPV experiences, mental health, COVID-19-related experiences in general and IPV experiences in specific. Overall, 47.8% of the participants experienced an increase in frequency and/or severity of IPV victimization, with help-seeking barriers, job loss, being confined to the house with their aggressor, and prior trauma independently predicting increases. Also, 75.5% reported one or more barriers to accessing help; such barriers were independently predicted by increased severity/frequency of IPV, financial strain, relationship length, being married, using marijuana, severe depression, prior trauma, IPV stigma, and coercive control victimization. Results are discussed in terms of their consistency with the literature on female victims, and the need for gender inclusive research, service provisions, and service recommendations in light of crises such as the COVID-19 pandemic. Full article

Whether urban park supply effectively responds to residents’ actual use remains a critical issue for public service provision, residents’ health and well-being, and spatial equity in high-density cities. Conventional assessments based on static population data may fail to capture dynamic patterns of human activity, potentially obscuring mismatches between service provision and real demand. This study integrates mobile phone signaling data into a supply–demand assessment framework to evaluate urban park systems from a dynamic population perspective. The framework is applied to Shenzhen as a representative high-density megacity. Park supply is measured by service capacity, coverage, and accessibility, while demand is derived from observed visitation behavior. A Supply–Demand Ratio (SDR) index, combined with Getis-Ord Gi* analysis, is employed to identify spatial patterns of mismatch. The results reveal substantial supply–demand imbalances that are not captured by traditional static indicators, with approximately 30.9% of communities identified as significant cold spots. High-density central areas exhibit a persistent deficit in park services despite relatively high coverage levels, whereas peripheral areas with abundant ecological resources show relative surpluses. These patterns are closely associated with urban functional structure, population mobility, and jobs–housing separation. By uncovering the divergence between nominal accessibility and actual use, this study highlights the limitations of place-based planning approaches and underscores the need for a people-centered perspective. The findings point to the importance of shifting from “opportunity equity” to “outcome equity” in evaluating and improving urban public service provision to foster sustainable urban development. Full article

Entrepreneurs represent a key piece in the generation of jobs and contribution to the economy through the performance of their businesses. Taking into account that literacy and financial inclusion constitute a business facilitator for the development of businesses, this study was based on analyzing the three variables, aiming to identify whether inclusion and financial literacy influence business performance. Through a non-experimental, quantitative study based on structural equations, a sample of 469 entrepreneurs from Peru, Bolivia, and Colombia was studied. The hypotheses were supported by observing the positive effect of one component of financial literacy (Cash Forecasting) and three components of financial inclusion (Access, Barriers, and Use) on Business Performance. However, the proposed model shows that the direct effect of two components (Bookkeeping and Financial Education) of financial literacy is not statistically significant. Therefore, these factors are vital tools that can help Latin American entrepreneurs make informed financial decisions, manage resources effectively, and build solid and sustainable businesses. Full article

Historically, technological progress has driven shifts in the labour market, leading to the disappearance of certain jobs while simultaneously creating new roles fueled by the need to work with emerging technologies. The technological advancements of the early 2020s are inherently linked to Artificial Intelligence (AI) and the rise in chatbots, whose accessibility and ease of use have become paramount for business development. Given this context, the aim of this study is to analyse frameworks describing the AI competencies of students who will constitute the future workforce. Based on an analysis of existing frameworks, a new framework is formulated through synthesis and operationalized into survey items representing AI-related competencies. These survey items are measured by primary research focused on a sample of undergraduate students at a selected faculty and university. The research provides valuable insights for curriculum development policy by highlighting competencies that students perceive as significant versus those they find less important. Building on these findings, the study offers policy recommendations for curriculum designers. The proposed recommendations enable the creation of educational programmes with relevance to the practical needs of the business sector, increasingly impacted by the emergence of AI. Full article