Search Results (269)

Persistent inflation has intensified uncertainty in the construction industry, particularly in volatile economies. Inflation-driven risks affecting Turkish residential projects are examined in this study, focusing on rising costs, fluctuating labor and material prices, and associated risks. The power-based linguistic hedges were used to quantify dominant severity levels under uncertainty based on descriptive statistics and standard deviation thresholds. Results indicate that inflation mostly impacts projects through budget overruns and wage inflation, which exhibit the highest severity and crisis-level risk behaviors. A number of factors drive material price volatility, particularly macroeconomic instability, currency depreciation, and supply-chain disruptions. There is a sustained pressure on contractor profitability due to wage inflation. In contrast, inflation-related effects on schedule, quality, safety, and contractual disputes are secondary and context-dependent. The findings indicate a structural shift in the risk profile of Turkish residential construction, indicating a need for inflation-resilient cost management, adaptive contracting, and proactive labor planning. Full article

Rural communities in developing countries face rising livelihood vulnerability due to climate change, agricultural price volatility, and dependence on linear production systems. This study examines whether circular utilization of cashew by-products can strengthen rural economies through a field-based case study in rural Cambodia. Primary data were collected through on-site observations, semi-structured interviews with farm owners and rural workers, and farm-level economic assessments. The results indicate that cashew apple juice processing is not financially viable as a standalone activity under prevailing wage and market conditions, producing negative net profits across all examined processing volumes. By contrast, integrating cashew apple utilization with other by-products shows more favorable outcomes. Cashew nut shells and pruning residues generate relatively stable supplementary income for farm operators, while cashew apple collection creates additional employment opportunities, particularly during off-harvest periods and low-yield years, helping to stabilize household labor income. Rather than relying on capital-intensive technologies, the observed practices represent low-cost and locally feasible circular economy approaches suitable for medium-sized commercial farm-based systems, with potential analytical transferability to smallholder contexts. Overall, these findings suggest that integrated by-product utilization may reduce income volatility and support sustainable rural community development in similar cashew-producing contexts. Full article

Workplace weight stigma is a form of discrimination affecting equality, health, and careers, yet occupational research remains fragmented. This gender-sensitive systematic review synthesizes evidence on workplace weight stigma among adult workers and job applicants since 2000. Following PRISMA procedures, we searched psychological, medical, sociological, and economic databases, identifying 25 included studies examining work outcomes. The corpus includes experimental vignette and correspondence studies, surveys, and qualitative designs, predominantly from high-income Western countries. Higher body weight is consistently associated with disadvantages across the employment life cycle: reduced callbacks and hiring, lower wages and wage growth, fewer promotions, and negative performance evaluations. Penalties are systematically stronger for women; intersectional analyses remain rare. Weight-based teasing, unfair treatment, and stereotype threat are linked to poorer self-rated health, psychological distress, burnout, reduced work ability, lower job satisfaction and commitment, and stronger turnover intentions. Organizational-level evidence is indirect but suggests detrimental effects on engagement and citizenship behaviors. Findings support conceptualizing workplace weight stigma as both a psychosocial hazard and a structural driver of labor-market inequality, underscoring the need for size-inclusive HR practices, leadership, and occupational risk-prevention policies. Full article

Background/Objectives: Japan introduced a certification system for Advanced Practice Nursing Workforce (APNW) in 1996. The Japanese Nursing Association formally certified two types of the APNW: Certified Nurses (CNs) and Certified Nurse Specialists (CNSs). Little is known about the geographic distribution of CNs and CNSs. Methods: We conducted an ecological panel analysis using prefecture-level data from 1996 to 2022. To assess the degree of inequality of CN and CNS among prefectures, we calculated the Gini overall coefficients, as well as those by categories of CN and CNS, number of hospitals, number of hospital doctors, and hospital nurses. Using data available from 2000 to 2017, we examined factors associated with CN and CNS density through fixed-effects panel data analyses of log-transformed overall and category-specific densities. Results: During the study period, the number of CNs and CNSs consistently increased, and geographic disparities in their distribution decreased until around 2010. After 2010, however, geographic disparities in prefectures with persistently low CN and CNS densities persisted without significant change. For overall CN and CNS density, significant associations were observed with population aging, per capita income, hospital density, hospital doctor density, hospital nurse density, and study year, whereas hospital nurse wages showed a positive but not statistically significant association. When stratified by clinical category, the directions of associations for several regional factors varied; however, hospital nurse density and hospital nurse wages tended to be positively associated with CN and CNS density in most categories. Conclusions: This study highlighted the need for targeted strategies to increase CN and CNS numbers specifically in prefectures with persistently low densities, tailored to each clinical category. Full article

Labor market forecasting relies heavily on economic time-series data, often overlooking the “health–wealth” gradient that links population health to workforce participation. This study develops a machine learning framework integrating non-traditional health and social metrics to predict state-level employment density. Methods: We constructed a multi-source longitudinal dataset (2014–2024) by aggregating county-level Quarterly Census of Employment and Wages (QCEW) data with County Health Rankings to the state level. Using a time-aware split to evaluate performance across the COVID-19 structural break, we compared LASSO, Random Forest, and regularized XGBoost models, employing SHAP values for interpretability. Results: The tuned, regularized XGBoost model achieved strong out-of-sample performance (Test $R^2$ = 0.800). A leakage-safe stacked Ridge ensemble yielded comparable performance (Test $R^2$ = 0.827), while preserving the interpretability of the underlying tree model used for SHAP analysis. Full article

Existing experience-based methods cannot effectively assist commercial building operators in allocating workforce resources according to contracts and balance multiple workforce management objectives under resource constraints, leading to misaligned allocation strategies. To address this issue, this study develops a workforce resource allocation optimization model based on BERT and the NSGA-II. First, a natural language processing (NLP) model is trained to extract operational tasks from contracts and match required workforce types, thereby establishing the framework for workforce allocation schemes. Second, a mathematical optimization model for workforce allocation strategies is constructed with the objectives of minimizing workforce wage costs (B1), maximizing average service levels (B2), and maximizing average digital technology acceptance (B3). An algorithm based on NSGA-II is then designed to solve the model and obtain the optimal Pareto solution set of allocation schemes. Third, the CRITIC–VIKOR method evaluates the Pareto set and determines the final recommended schemes. A case study was conducted on a university campus in Shandong, China, to validate the model’s effectiveness. The results show that the NLP model successfully identified 14 operational tasks and 13 required workforce types from the contract. Compared with the operator’s expected values (B1 = 46,0000 CNY, B2 = 65 points, B3 = 50 points), the optimal allocation scheme calculated using NSGA-II and the CRITIC–VIKOR method reduces B1 by 10.79%, increases B2 by 18.02%, and improves the B3 by 16.79%. This study formulates the workforce allocation problem in the operation stage as a mathematical optimization model and, for the first time, incorporates the workforce’s digital technology acceptance as an optimization objective, thereby filling a theoretical gap in workforce management for commercial building operations. The proposed model provides operators with a semi-automated decision-support tool to enhance workforce management, thereby promoting the sustainable operation of commercial buildings. Full article

Minimum wage is an important tool for reducing income inequality and supporting social welfare. Consequently, governments around the world have established minimum wage systems. As such, minimum wage policies connect distributive justice with the economy’s capacity to sustain broad-based welfare over time, placing the equity–efficiency trade-off at the center of societal sustainability. However, the micro-level impact of the minimum wage system on firms has always been an important topic for scholars. This study uses panel data from listed Chinese manufacturing firms over a period from 2005 to 2021 to construct an indicator of the minimum wage standards implemented in the firm locations. Employing the multiple linear regression model, this paper empirically examines the effects of minimum wage on labor productivity. The empirical findings demonstrate that minimum wage significantly reduced the sample firms’ labor productivity. Moreover, the negative impact of the minimum wage was primarily concentrated among non-state-owned firms, labor-intensive firms, firms operating in industries characterized by intense product market competition, firms situated in regions with strong legal protections, firms with comparatively low average employee wages, and export-oriented firms. Subsequently, this study delves into the mechanism through which minimum wage negatively affects labor productivity. We find that implementation of minimum wage leads to a reduction in corporate investment, indicating that there is no significant substitution relationship between capital and labor. These adjustment margins provide microfoundations through which statutory wage floors can influence the resilience and inclusiveness of development, indicating that the pace and design of wage increases should balance income protection with the preservation of productive capacity to support sustainable human development—grounded in steady productivity growth, equitable income distribution, and stable firm investment. Our findings contribute to a better understanding of the mechanism through which minimum wage affects labor productivity in theory, while concurrently furnishing policy insights for the optimization of the minimum wage system and maintaining sustainable societal development in practice. Full article

This article examines labor market dynamics in Bulgaria, Italy, and the United Kingdom by integrating demographic pressures, wage and labor cost adjustment, redistribution mechanisms, inequality outcomes, and digital readiness into a single comparative framework. This study first applies hierarchical clustering to a harmonized EU country panel for 2017–2024, using GDP per capita in PPS, average annual wage, and unemployment rate to position the three countries within the European convergence space and income–labor cost groupings. The results show that Bulgaria belongs to a low-income, fast-converging group, with nominal wages and hourly labor costs more than doubling, strong real-wage growth from a low base, and an improving price level index. At the same time, unemployment fell to below the EU average, yet income inequality remains persistently high. Italy represents a high-income but slow-growing labor market, in which real wages have declined, and labor costs per hour remain above the EU mean with a significant non-wage component. Unemployment remains relatively elevated, indicating divergence in workers’ purchasing power despite high income levels. The UK has labor costs in the mature high-income range, low unemployment, and the lowest tax wedge for low-wage workers, but with relatively high and volatile inequality. This study shows that wage dynamics, labor cost composition, and tax–benefit structures jointly mediate the translation of macroeconomic performance into household outcomes, generating distinct policy trade-offs across the three labor market configurations. Digital indicators further suggest that income level is not a sufficient predictor of digital engagement and that the observed aggregate labor market trends do not indicate a sharp employment contraction contemporaneous with the diffusion of technical innovations, such as generative AI. Full article

This research aims to evaluate how socio-economic and environmental factors influence the development of electromobility. To this end, the research was applied to regions of the Czech Republic, divided into metropolitan, urban and rural types. Based on a panel multiple linear regression with fixed effects of regions and years, the influence of socio-economic and infrastructure variables, in particular average gross wages, the development of charging points by region type and other factors, is analysed. The results show that average wages are a consistently statistically significant factor in the growth of new electric vehicle registrations across the regions. In contrast, the current level of charging infrastructure has no direct effect; its influence is only felt after a delay. Interaction models further confirm that the influence of income is relevant in both urban and rural areas. The study provides new insights into the temporal dynamics of electromobility adoption and formulates recommendations for targeted regional transport policy with an emphasis on proactive infrastructure planning. Full article

This study examines the influence of agricultural labor policies on the sustainability and productivity of farming enterprises in Türkiye, with a particular focus on the sector’s increasing reliance on foreign labor. Using primary data collected through face-to-face surveys with 73 agricultural enterprises in the Çumra District of Konya Province during the 2023–2024 production year, supplemented by secondary data from national and international institutions, the research explores how workforce composition, policy regulations, and socio-economic factors affect farm performance. Descriptive and comparative statistical analyses were conducted using SPSS to evaluate demographic characteristics, employment patterns, wage structures, and satisfaction levels among local and foreign workers. The findings indicate that as farm size expands, the use of foreign labor—mainly from Afghanistan, Uzbekistan, and Turkmenistan—significantly increases, generating cost and productivity advantages but also raising concerns related to social integration and legal employment barriers. Local labor demonstrates greater competence in mechanization but remains insufficient in quantity, deepening the existing labor shortage. A substantial majority (91%) of producers consider current labor regulations restrictive and emphasize the need for government incentives, vocational training programs, and simplified permit procedures for foreign workers. The results highlight the importance of inclusive and adaptive labor policies that harmonize economic efficiency with social cohesion, supporting the achievement of Sustainable Development Goals (SDG) 2, 8, and 11—Zero Hunger, Decent Work and Economic Growth, and Sustainable Cities and Communities. Full article

The Trump administration signalled a shift toward protectionism in U.S. trade policy, imposing tariffs on imports from both strategic partners and competitors, which generated renewed uncertainty in international trade relations and the future of existing frameworks such as the African Growth and Opportunity Act (AGOA) and the Generalised System of Preferences (GSP). Earlier analysis has shown that a Free Trade Agreement (FTA) between the Southern African Customs Union (SACU) and the United States can be trade-creating and lead to improved macroeconomic outcomes in SACU countries. However, these positive effects decline over time, with varying impacts across different industries, influenced by initial tariff levels and export orientation relative to the US. This paper examines whether there are economic and strategic incentives for SACU to negotiate a more beneficial agreement than a simple across-the-board elimination of ad valorem import tariffs. Using a dynamic computable general equilibrium (CGE) model, the paper examines the outcomes if cereals, poultry, dairy products, red meat, and sugar products—often classified as sensitive due to their labour intensity, food security implications, and exposure to import competition—were to retain some level of protection under a SACU–US Free Trade Agreement. The results suggest that while the FTA boosts key macroeconomic indicators in the short run, gains taper off over time. Crucially, real wages and employment remain stagnant, and terms of trade deteriorate, raising questions about the inclusivity and sustainability of such a deal. Shielding vulnerable sectors initially enhances SACU’s exports and supports some industry growth, particularly in agriculture. However, without broader reforms and export diversification, long-term competitiveness remains weak. A nuanced FTA design, combined with structural support policies, is essential to unlock lasting and inclusive trade benefits. Full article

Digitalization has reshaped economic systems worldwide, yet its distributional consequences remain uneven and raise new challenges for sustainable development. China, where digital infrastructure has expanded rapidly, provides a critical setting to examine these effects and their implications for sustainable and inclusive growth. Using a balanced panel of 285 prefecture-level cities from 2007 to 2023, this study constructs a text-based index of digital infrastructure from government work reports and applies two-way fixed effects, instrumental variables, nonlinear models, placebo tests, heterogeneity analysis, and spatial Durbin models. The results show that digital infrastructure significantly widens the urban–rural income gap, with the effect becoming increasingly convex as digital development deepens. Two mechanisms drive this pattern: the concentration of innovation resources in urban areas, which crowds out rural R&D, and a modest degree of wage-structure polarization. Spatial spillovers also matter; digital development in neighboring cities partially offsets local inequality by enhancing interregional connectivity and knowledge diffusion. These findings provide city-level causal evidence on the unequal distributional impacts of digitalization in large emerging economies and highlight the need for sustainability-oriented digital governance, inclusive innovation systems, and regionally coordinated strategies to prevent digital infrastructure from reinforcing structural disparities. Strengthening these policies is essential for achieving more sustainable urban–rural integration in the digital era. Full article

Utilizing a panel of 125 economies spanning from 1970 to 2019, we examine the role of manufacturing as a fundamental pillar of development in the era of global value chains (GVCs). We employ a layered clustering approach that categorizes countries based on income per capita and structural characteristics, such as the share of manufacturing, export complexity, resource dependence, productivity, and wages while maintaining consistency over time. Prior to 1990, most trajectories exhibited a progression from early industrialization to diversification, enhanced industrialization, increased export complexity, rising income levels, and subsequently to deindustrialization. However, post-1990, deindustrialization began to permeate middle- and low-income economies, with export complexity frequently increasing in the absence of deeper domestic industrial development. Two distinct manufacturing pathways are evident: one characterized by functional specialization amid moderate manufacturing levels and another exemplified by the East Asian model, which demonstrates sustained high manufacturing intensity. Resource-driven growth has led to income increases without significant structural transformation, and such growth has not enabled economies to achieve high-income status without initial industrialization. Manufacturing remains essential as a domestic foundation; therefore, policy efforts should focus on securing this base, enhancing capabilities within higher-value GVCs, and strategically investing resource revenues to bolster industrial capacity. Full article

This research provides the first comprehensive analysis of the rural–urban wage gap in Colombia, with a focus on the coffee and cocoa sectors, over the past two decades. Using household survey microdata from 2001 to 2023 and international sources, we estimate wage differentials and apply econometric models—including Mincerian wage regressions and Blinder–Oaxaca decompositions. Results reveal a persistent and substantial wage gap: on average, rural coffee and cocoa workers earn roughly half as much as urban manufacturing workers. Even after controlling for education, experience, and other characteristics, a substantial share of the gap remains unexplained, indicating structural issues such as lower productivity, elevated levels of informality, and labor market segmentation in rural areas. Moreover, time-series evidence from the past two decades shows no significant convergence between rural and urban wages. Comparative analysis with Brazil, Mexico, and other Latin American countries highlights how policy interventions, such as rural social protection programs, labor formalization, and support for agricultural cooperatives, have helped narrow rural–urban wage disparities elsewhere. Drawing on these lessons, we discuss policy implications for Colombia and recommend measures to boost rural human capital, strengthen labor institutions, expand social safety nets, and promote rural economic development. These recommendations aim to gradually close the rural–urban wage divide, reduce rural poverty, and foster inclusive growth. Full article

This entry examines how wage-setting institutions (WSIs) shape wages across advanced economies. It focuses on four core mechanisms—minimum wages, collective bargaining, wage coordination, and wage centralization—drawing on theoretical insights, empirical evidence, and cross-country comparisons. The analysis shows that minimum wages safeguard low-paid workers but have heterogeneous employment effects depending on their level and enforcement. Collective bargaining raises average wages and compresses wage inequality, though it can reduce flexibility and create insider–outsider dynamics. Wage coordination stabilizes wage growth, prevents inflationary spirals, and fosters equity, while wage centralization promotes solidarity wages and macroeconomic discipline but may limit adaptability. Using The Organization for Economic Co-operation and Development (OECD) and Institutional Characteristics of Trade Unions, Wage Setting, State Intervention and Social Pacts (ICTWSS) data, the study highlights institutional diversity, ranging from coordinated Nordic models to fragmented liberal systems, and identifies trends toward “organized decentralization”. Policy implications suggest that WSIs should be viewed not as rigidities but as adaptable frameworks that can balance efficiency, equity, and stability when carefully designed. The conclusion emphasizes that the future of wage-setting lies in leveraging institutional complementarities to respond to globalization, technological change, and shifting labor market conditions. Full article