Skill Level Of Workers Research Articles

The Conflict Between Lefts and Rights Policies on Economic and Public Security Events

This article thoroughly examines the connection between political orientation and economic policies by analyzing the decision-making process and economic consequences of right-wing countries like the United States and left-wing countries such as Norway during the COVID-19 pandemic. Countries with a strong left-wing inclination might focus more on developing the public sector and social welfare, and their economic development mode tends to be closer to the welfare state model. In contrast, countries with a stronger right-wing tendency stress the function of free markets and private enterprises, and their economic development models are more similar to the free-market economy model. Nevertheless, international cooperation must be strengthened. Both left-wing and right-wing countries should discard ideological distinctions and jointly address the impact of the pandemic on the global economy to facilitate its recovery. Also, during the epidemic, vulnerable groups had been the most severely affected. The government should adopt measures to safeguard their basic livelihoods and rights, and prevent the wealth gap from further expanding. Additionally, it is essential to increase investment in education and training to enhance the skill level of workers and provide human resource support for the long-term economic development.

Neighbourhood-search-enhanced non-dominated sorting genetic algorithm-III for multi-objective assembly line balancing problem considering operator skill levels and carbon footprint

With growing consumer awareness of carbon footprints, manufacturers must achieve profitability while maintaining sustainability. This study introduces a multi-objective optimization model for production lines that emphasizes the balance rate, minimal emissions and profit maximization, incorporating worker skill levels as a key variable. To solve this model, an enhanced version of the non-dominated sorting genetic algorithm-III integrated with a neighbourhood search strategy (NSGA-III-LS) is proposed. The chromosome decoding process was reframed as a one-dimensional binning problem, enabling the rapid calculation of workstation cycle times for determining the relationship between processes and workstations. The experimental results and real-world case studies validate the effectiveness of NSGA-III-LS. It was found that the multi-objective model effectively balances diverse objectives and promotes sustainable production. Moreover, the model considering varying skill levels outperforms the model with fixed skill levels in terms of the balance rate. Finally, the proposed algorithm demonstrates superior performance in solving this complex problem.

An Integrated Stochastic Optimization and Simulation Approach to SERU vs. Assembly Line Manufacturing Systems

This research compares SERU manufacturing systems to traditional assembly lines, focusing on the impact of uncertainty in task processing time on production output. The study considers worker skill levels and team identity, using a stochastic mixed integer linear programming approach to model uncertainty and optimize workforce allocation. Discrete event simulation is then integrated to evaluate performance using five key performance indicators (KPIs). Results show that SERU systems outperform traditional lines in terms of throughput when uncertainty is considered. The integrated approach provides more reliable performance data than deterministic optimization alone. The study also highlights the advantages of SERU systems when worker skill levels and team identity are factored in. This research fills a gap in the literature by proposing a stochastic optimization approach that considers uncertainty and worker skill levels, and by integrating stochastic optimization with simulation for comprehensive analysis. This approach provides valuable guidance for production managers in optimizing production systems.

THE IMPACT OF PAEDIATRIC EMERGENCY MANAGEMENT SKILLS ON PATIENT OUTCOMES IN ZARIA

Paediatric emergencies represent a critical challenge in Nigeria, where approximately 2,300 children under the age of five die daily, predominantly from preventable and treatable conditions such as pneumonia, malaria, and diarrheal diseases. Mortality rates are disproportionately higher in rural areas, where primary health care (PHC) centers often serve as the only point of access to medical services. The effectiveness of these centers is largely dependent on the emergency management skills of their healthcare workers. Despite their importance, there has been limited research on how the skills of PHC workers in managing paediatric emergencies impact patient outcomes. This study aimed to assess the proficiency of healthcare workers in primary healthcare centers in Zaria in managing common paediatric emergencies. A cross-sectional descriptive study was conducted among 139 health workers selected through a multi-stage sampling technique in Sabon Gari and Zaria Local Government Areas. Data collection was carried out using a pre-tested semi-structured self-administered questionnaire. The data were analyzed using SPSS version 21, and associations were tested using the chi-square test, with results presented in tables and charts. The findings revealed a significant deficiency in the emergency management skills of healthcare workers. A majority of respondents demonstrated inadequate skills in handling paediatric emergencies, with 66 (48.5%) exhibiting very poor competency in the management of common paediatric emergencies, and 32 (23.5%) displaying poor competency. Only a small fraction, 4 (2.9%) of respondents, demonstrated excellent skills in emergency management. Similarly, 46.7% of the respondents had very poor skills in the treatment of common paediatric emergencies, while only 3.0% exhibited excellent treatment skills. A statistically significant relationship was observed between the level of academic qualification and emergency management skills (p < 0.05). The results underscore the critical need to enhance the skill levels of healthcare workers in PHCs through continuous professional development. This could be achieved through collaborative efforts between the Department of Paediatrics at Ahmadu Bello University Teaching Hospital and the Primary Health Care Departments of Zaria and Sabon Gari local governments, focusing on regular training and workshops. Improving the skills of healthcare workers in managing paediatric emergencies is essential for reducing child mortality and improving health outcomes in the region.

Factors Influencing the Skill Level of Primary Healthcare Workers in Managing Paediatric Emergencies

Paediatric emergencies continue to be a significant public health concern in Nigeria, particularly in rural areas where primary healthcare centers (PHCs) often serve as the sole source of medical care. The ability of healthcare workers in these settings to effectively manage paediatric emergencies is crucial for improving child health outcomes. This study aimed to assess the factors influencing the skill level of primary healthcare workers in managing paediatric emergencies in Zaria, Nigeria. A cross-sectional descriptive study was conducted among 139 randomly selected healthcare workers in Sabon Gari and Zaria Local Government Areas. A pre-tested questionnaire was used to collect data on socio-demographic characteristics, work experience, and skills in managing paediatric emergencies. Data were analyzed using SPSS version 21. The results revealed that healthcare workers in PHCs in Zaria exhibited varying levels of skills in managing paediatric emergencies. Several factors were identified as influencing their skill levels. Healthcare workers with higher academic qualifications demonstrated significantly better skills in managing paediatric emergencies. This suggests that formal education plays a crucial role in developing the necessary competencies. While experience can be a valuable asset, the study did not find a strong association between years of experience and skill levels. This may indicate that experience alone is not sufficient for developing the necessary skills, and additional training and support may be required. Healthcare workers who had received recent training or participated in continuing medical education (CME) programs related to paediatric emergency management tended to have higher skill levels. This highlights the importance of ongoing professional development in maintaining and improving skills. The findings of this study suggest that a combination of factors influences the skill level of primary healthcare workers in managing paediatric emergencies. While academic qualifications are important, ongoing training and access to resources are also essential. It is crucial to address these factors through targeted interventions to improve the skills of healthcare workers and enhance the quality of care provided to children in need. This study highlights the critical need for targeted interventions to improve the skills of primary healthcare workers in managing paediatric emergencies in Zaria, Nigeria. By addressing factors such as academic qualifications, training, resource availability, and work environment, policymakers and healthcare providers can significantly enhance the quality of care provided to children in need.

Evaluating impacts of ICT development on wages of workers

At the provincial level, there is a research gap in discussing the causality and internal mechanism between ICT development and wages of workers. The study utilizes the province-level balanced panel data over the period 2006–2021 in China, clarifies the impact and internal mechanism of ICT development on wages of workers, and uses the DID method to identify the causality between the two. This study found that there is a positive correlation between ICT development and workers’ wages, and skill level is a mediate transmission channel. Moreover, ICT development has a positive impact on workers’ wages in the central and western regions. Besides, compared to low-wage workers, high-wage workers gain more information dividends. The findings of this study have reference significance for policymakers. First, for the central and western provinces in China, it is necessary to actively develop the ICT industry, cultivate high-tech enterprises, and improve local ICT development levels. Second, we should improve the skill level of workers and enhance their competitive advantage in employment. Third, each province should continue to expand the enrollment scale of higher education institutions, and improve the quality of labor force.

Twenty-First Century Competencies; about Competencies for Industry 5.0 and the Opportunities for Emerging Economies

The philosophy of Industry 5.0 recognises the transformative power of the industrial sector to add value to society and employees. Industry 5.0 is distinct from its predecessors because it relies on a tripod of sustainability, human centricity, and resilience. These three thematic principles aim to improve work safety, research, and innovation and strengthen industrial resilience and competitiveness. However, a perfect storm is brewing for the future of work, brought about by the concerning trends of displacement and low skill levels of workers’ competencies in handling the new technologies of Industry 5.0 in emerging economies. This conceptual paper will describe Industry 5.0 and provide historical insights on the importance of acquiring the desired twenty-first-century competencies needed in the workforce for Industry 5.0 and how these competencies can be cultivated. Two research questions guided the study in identifying these twenty-first-century competencies, how these competencies can be cultivated and taught in the education curriculum and policies of emerging economies, and the crucial importance of adapting Industry 5.0 to these emerging economies. The study concluded that emerging economies must play an active role in shaping the future by creating policies that will advance social stability, resource preservation, and climate objectives, which will enable more productive production processes with lower waste and energy usage.

Primary Healthcare Workers' Awareness of Acute Rheumatic Fever & Rheumatic Heart Disease: A Study in Public Health Facilities in South Western Uganda.

Timely identification and treatment of a streptococcal throat infection prevents acute rheumatic fever (ARF) and its progression to Rheumatic Heart Disease (RHD). However, children in developing countries still present with established RHD, due to either missed, untreated or sub-optimally treated sore throats and ARF. We aimed to determine the level of knowledge, skills, and practices of primary health workers in South Western Uganda in providing care such children. We conducted a comparative quantitative cross-sectional study to assess knowledge, practices, and skills regarding the care of a child with a sore throat, ARF, and RHD. The responses were scored against a structured guide. The Fisher's exact test and the chi-squared test with level of significance set at 0.05 were utilized to compare differences in knowledge, skills, and practices among health workers in private and public health facilities about ARF and RHD. Eighty health workers from health facilities were interviewed in Mbarara district with a median age of 29.5 years (IQR 27.34) and median duration in practice of 5 years (IQR: 2, 10). On average, there were at least 3 children with sore throats weekly. At least 95% (CI: 87.25%-98.80%) of the health worker had awareness about ARF and RHD. Only 43.75% (95% CI: 33.18%-54.91%) had good knowledge about ARF and RHD. Majority, 61.25% (95% CI: 50.03%-71.39%) did not know the proper prophylaxis and investigations for a child with ARF. There were no statistically significant differences but a clinically meaningful differentials in the level of knowledge among health workers in public and private facilities. The knowledge and skill level of health workers in primary healthcare facilities about ARF and RHD in South Western Uganda remains low, with no difference between practitioners in public and private facilities.

A case study of whale optimization algorithm for scheduling in C2M model

With the continuous upgrading of industrial technology and information technology, consumers can deeply participate in the whole life cycle of products and realize customized production. These unprecedented changes have brought consumers and manufacturers closer together, resulting in the intelligent business model of "Internet + Customized Production" and "Customer to Manufacturer (C2M)". C2M has been adopted by more and more companies. However, the transition from traditional business models to C2M is a problem that every company must face and solve. Personalized orders of many varieties and small lots put enormous pressure on the production of mainly labor-intensive electronic assembly companies. The theoretical findings of Industry 4.0 and Lean Manufacturing show that people play a central role in assembly operations. As an important element of the production system, worker scheduling has a direct impact on delivery time and cost. Worker scheduling requires not only matching people to jobs, but also considering flexible employment. According to the "Learning Curve" theory, workers with learning potential can continuously enrich their skills and work efficiency will show dynamic changes. Therefore, under the condition of shortest order delivery time and lowest cost, worker scheduling considering the learning effect becomes a challenge for enterprise decision makers. Firstly, the production method of manufacturing industry in C2M environment is studied. Then, based on single-skill task and multi-skill task, respectively, a learning curve-based model of dynamic change in worker skill level is constructed. And this model is used as the input of the assembly line worker scheduling model. Secondly, an Elite Non-dominant Sorting Whale Optimization Algorithm (ENS-WOA) is designed for this multi-objective optimization problem. The correctness and feasibility of the proposed algorithm are verified by selecting classical arithmetic cases for experimental comparison with other algorithms. Finally, the established worker efficiency change model, worker scheduling model and the proposed algorithm are applied to optimize the assembly line of water pump products of Company B, which is being transformed to C2M, and solved by MATLAB software. The results show that the model proposed in this paper is effective, stable and practical compared with the worker costs and delivery period required to complete the order in the original assembly line. Worker costs were reduced by 29.02% and orders were completed approximately 10 days earlier.

Research on Construction Safety Management Measures for Building Sites

With the rapid development of China's construction industry, the scale of construction projects is getting bigger and bigger, and the degree of specialization is also increasing. In order to gain a competitive advantage in the market, construction enterprises must focus on construction safety management and optimization of construction processes. In addition, in order to promote the long-term and stable development of the project, project contractors must also focus on the quality, efficiency, and safety of the construction environment in order to protect the lives and properties of workers. Therefore, construction safety management of building projects has become an important element in engineering construction. Comprehensive analysis of construction safety hazards strengthening the construction of safety management systems, improving the safety awareness and skill level of workers, and adopting scientific construction technology and equipment are the important strategies for the current construction safety management of construction projects.

Integration of deep reinforcement learning and multi-agent system for dynamic scheduling of re-entrant hybrid flow shop considering worker fatigue and skill levels

In real-life manufacturing systems, production management is often affected by urgent demands and unexpected interruptions, such as new job insertions, machine breakdowns and operator unavailability. In this context, agent-based techniques are useful and able to respond quickly to dynamic disturbances. The ability of agents to recognize their environment and make decisions can be further enhanced by deep reinforcement learning (DRL). This paper investigates a novel dynamic re-entrant hybrid flow shop scheduling problem (DRHFSP) considering worker fatigue and skill levels to minimize the total tardiness of all production tasks. An integrated architecture of DRL and MAS (DRL-MAS) is proposed for real-time scheduling in dynamic environments. Two DRL models are proposed for different sub-decisions, where a reward-shaping technique combining long-term and short-term returns is proposed for the job sequence and machine selection sub-decisions, and an attention-based network is proposed for the worker assignment sub-decision for efficient feature extraction and decision making. Numerical experiments and case studies demonstrate the superior performance of the proposed DRL models compared with existing scheduling strategies.

Analysis of Temporary Works Interest Protection by Negotiation

According to some experts, temporary workers are becoming less willing to speak out when they have made a loss as previously they were. Nonetheless, when their benefits are being infringed, temporary workers will bargain with the employer to safeguard their own interests. However, there is no unified explanation for the reasons behind the formation and solutions. Therefore, this paper collects data on temporary workers employed by some companies and analyzes the correlation between the data and the case of "temporary workers employed by Meituan Takeaway" to investigate the topic of how temporary workers should negotiate with companies to protect their own interests. The study found that there are two reasons why temporary workers are not valued by the company, including the low skill level of temporary workers and the high risk of quitting; the company hires temporary workers not only because it can save human resources costs, but also shows higher motivation for temporary workers. The company should insist on "equal pay for equal work", which is beneficial to the development of the company and establish a good corporate image. In view of the above findings, this paper proposes that the company should actively cooperate with the negotiation process and the temporary workers should use such negotiation skills to communicate with the company.

Optimizing worker productivity and the exposure to hand-arm vibration: a skill-based job rotation model

ABSTRACT Productivity and concerns regarding the well-being of workers exposed to vibrations stand as significant topics within labor-intensive sectors. In particular, this study contributes to the existing research by analyzing the problem with linkages among worker skill level, production rates, and vibration exposure. A bi-objective mixed integer linear programming model was employed to optimize both productivity and the exposure to hand-arm vibration in the manufacturing workplace. A sensitivity analysis was carried out to examine the impact of key parameters on the trade-off between productivity and vibration exposure. The results demonstrate the model’s effectiveness in determining the best job rotation schedules by achieving optimal productivity and vibration exposure for low and medium problem sizes. Moreover, the numerical case study points out that strengthening the workforce by adding more proficient skilled workers can maintain a good level of productivity with a decreased likelihood of excessive vibration exposure.

Realization and Scheduling of Free Spot Assembly Method for Machine Tools Using Cooperative Industrial Robots

The manufacturing industry is increasingly demanding flexible manufacturing and existing manufacturing methods with fixed equipment do not meet this requirement. The free spot assembly system is an ultra-flexible method that responds to this demand, enabling spatiotemporal free assembly by conveying all necessary resources with automated guided vehicles (AGVs). Although some studies have proposed free spot assembly, free spot assembly feasibility for assembling heavy objects, such as machine tools, by aligning them at high precision has not been verified. Work hour shifts, differences in worker skill levels, and cooperative work with robots have also not been considered in free spot assembly scheduling. This paper presents elemental technologies for realizing a free spot assembly system, with a scheduling method where a genetic algorithm is supported by dispatching rules with six genes. The computational results reveal the effectiveness of the proposed algorithm.

A case study for 3D scanning-based quantitative quality control during key stages of composite small craft production

Composite small crafts are manufactured in a job-shop system that prioritizes delivery times and creates various small-scale products using flexible equipment and worker operations. The process involves layering composite materials onto a mold to form the product through molding. Three intermediate stages must be completed before the final product, including mock-up, mold, and small craft. The stability and performance of the small craft rely on the accuracy of the mock-up and mold production. However, repeated molding can cause deformation and worker skill level affects product quality, leading to inconsistent results. This study aimed to improve the quality control of composite small crafts in leisure boat shipyards. We propose developing a high-precision digital shape model using 3D scanning of intermediate products such as the ship body frame, finished mold, and shaped hull of the FRP small craft to enable quantitative quality control and identify shape deviations.

Ranking critical success factors for implementation of lean-industry 4.0: a methodology based on DEMATEL and ANP

ABSTRACT Many firms have been performing a variety of organizational reforms to achieve long-term manufacturing sustainability. Industry 4.0 (I4.0) and Lean techniques have attracted much attention in this context. Although the potential benefits of implementing Lean and I4.0 in an integrated manner (Lean-I4.0) have been recognized, the studies addressing the practical issues for their integrated implementation, in particular the factors affecting the successful implementation, are missing. Therefore, this study is to determine the critical success factors (CSFs) that will enable the manufacturing industry in India to successfully implement the Lean-I4.0, thus obtaining manufacturing sustainability. The CSFs identified through a literature review were first validated by industrial experts. The Decision-Making Trail and Evaluation Laboratory technique was subsequently adopted to analyze the interdependence of the factors and classify them as either cause or effect. Finally, the Analytical Network Process technique in SuperDecisions was employed to rank the factors considering their interdependence scores. The results stress that i) the maturity of I4.0 and its relationship with lean and ii) the skill level and experience of workers are very important in the successful implementation of the Lean-I4.0. Besides, the study highlights that all the factors affect, at varying degrees, the successful implementation of the Lean-I4.0.

Labor Skill, Trade and Capital Intensity, and the Fall of Manufacturing Real Wages: Panel Evidence from Mexican Industries

Abstract The paper studies the fall in manufacturing real wages that took place in Mexico after the China shock of 2001. It shows, first, that the wage reductions reflected a significant transmission of the China shock, plus a weak link between labor-productivity and real-wage growth; and second, that the weight of these two factors was conditioned by the skill level of workers and the trade and capital intensity of industries in Mexico. Thus, while the China shock hit harder medium and high-skilled workers in capital-intensive industries, the weak link between productivity and wage growth affected more the low-skilled in trade-intensive industries. Results come from the estimation of wage equations by skill level for an annual panel of 20 manufacturing industries at NAICS three-digit level, for different periods but focusing on 1996–2017 (the NAFTA period) and 2003–2017 (the post-China shock period).

Development of a rolling angle estimation algorithm to improve the performance of implement leveling-control systems for agricultural tractors

Agricultural tractors are connected with various implements such as plow, baler, rotovator, and loader for performing agricultural work. In particular, the rotovator is used to crush and uniformly spread the soil after plowing operations. However, achieving uniformly spread soil and flattened fields using rotovator can be extremely challenging, because the soil is often pushed to a particular side or remains on a slope owing to the variations in soil composition, plowing depth, and the skill level of workers, which consequently affects the transplantation work. This study aims to analyze the prediction accuracy of the implement and tractor attitudes as a reference standard by (a) developing an algorithm to predict the implement attitude based on the hitch height, support points of the lower link and lift rod, and distance between the lower links, through four-section link mathematical modeling for a three-point hitch system, and (b) using an observer to predict the tractor attitude using a Kalman filter with gyroscopic and acceleration sensors. We developed a control algorithm using the gyroscopic and acceleration information from the sensor to improve the precision and adjustment speed of the conventional tractor–implement leveling-control system. In addition, the performance improvement was verified by comparing the conventional and proposed systems. The results revealed that the error rates in the proposed system were up to 72% less than those of the conventional system, implying that the control performance of the stated system could be improved by reducing the implement attitude estimation error and tractor attitude measurement delay.

Foreign direct investment and product quality in host economies

AbstractWe examine, both theoretically and empirically, how the presence of FDI affects product quality of domestic firms through worker mobility. Mobility of more productive workers from foreign‐invested to domestic firms lowers the cost of production and contributes to improvement in the quality of goods produced by domestic firms. Profit maximisation by firms yields a structural relationship between unobserved product quality and observed revenue, which allows us to identify the impact of FDI on product quality. We use the theoretical model to frame empirical estimation, where we propose a novel approach to correct for sample selection bias. Under some mild assumptions, a set of population moments are derived and estimated using firm‐level data from China's beverage manufacturing industry. We find that, on average, (i) working for foreign‐invested firms boosts the skill level of workers by 11.12 per cent and (ii) the probability that an FDI‐trained worker will move to a domestic firm is approximately 0.3. Estimation of the structural parameters shows that a one per cent increase in FDI leads to approximately 1.4 per cent improvement in product quality of domestic firms in China's beverage manufacturing industry.

Blas as sites for the meso-level dynamics of institutionalization: A cross-sectoral comparison

Abstract In this Article we seek to shift the focus from the texts of bilateral labor agreements (BLAs) to the context of their emergence and materialization. We argue that to study BLAs and evaluate their consequences and potential relevance, they must be read from the perspective of processes of institutionalization that shape the paths of different agreements. In Israel, a cross-sectoral comparison of the agricultural and construction sectors reveals that different agreements did not follow the same path and institutionalization process. The Israel-Thailand agreements for the agricultural sector and the agreements regulating migration to the construction sector did not generate similar dynamics of institutionalization. In both sectors, BLAs transformed recruitment practices and led to a sharp decrease of illicit migration costs extracted in the process. Yet due to differences in the structure of the sectors and the expected skill level of workers, significant variations remain, most notably in the effect of BLAs on the permit and quota system and in the rise of paths to import labor outside BLAs. Based on this cross-sectoral comparison, we offer in this Article a grounded analytical perspective for examining and evaluating BLAs in context. In discussing our suggestions, we will project our analysis to the more recent agreement covering the live-in care sector that is currently the largest employing sector of guest-workers in Israel.