Labor Shortage Research Articles

Is using combined tillage implements the solution?

The fuel consumption, The energy requirement, the time of prepare seedbed, the tractor wheel slippage and the number of passes in the field, all of this factors make farmer choose more efficient method of plowing. Compound tillage is the solve and the method means that two, three or more different plowing tools are work at one time for plowing soil, pulverization, seeding and fertilize, the aid of this way, reduce the drudgery, number and saving time of the field operation. The primary (conventional) and secondary tillage implements are becoming expensive time, fuel and cost, additional, need several passes to prepare seedbed, which increase compaction and damage of the soil and leads to formation the hard pan in the soil due to tractor and machines movement. The farmer size of the field holdings in Iraq is middle or usually small, the way of increase the the width of tools or speed is less useful and effective, therefore, reduce and shorten the number of traffic or passes by use a combination tillage implements consider better solution. Compound tillage saving cost of 44-55%, time of 50-55% and enable the farmers to reduce the number of trips over the field, also, shortage of farm labor. Carrying out the tillage process by compound tillage with two or more equipment to reduce time, fuel consumption and power requirement foe prepare the best seedbed. In this review, various paper researches on combination tillage implement will be discussion.

Making airports attractive workplaces again: Perspective from the private aviation security services

Why is it so difficult to find the right people to work in aviation security jobs and retain them, especially post-COVID-19? And how can we make these jobs attractive (again)? While this paper focuses on security screeners, most of the points can be extrapolated to aviation security staff, and airport staff in general. This paper takes the view that most of the reasons why we are facing staff shortages in airports were already present before the pandemic but were accelerated and amplified by it, with an additional worsening factor due to the unexpectedly quick and steep restart in passenger flights. It discusses the ‘old’ mindset and the fact that it cannot continue to prevail and should be replaced by a more positive, quality-oriented, human-centric one. To substantiate these opinions, the paper uses the findings of a European Union (EU)-funded project on skills and labour shortages intelligence (the INTEL project1) led by the Private Security Social Partners, illustrated by three business cases and various sources of information on best practice in attracting the younger generation.

The Evidence Gap in Labour Shortage Assessments

The Evidence Gap in Labour Shortage Assessments

3D Printing Technology and Future of Construction: A Review

Abstract Historically characterised by its labour-intensive nature and low productivity, the construction industry is witnessing a technological revolution. Among these advancements, 3D printing stands out as a frontrunner, offering the potential to automate construction processes, reduce material waste, shorten project timelines, and mitigate risks associated with manual labour. This study explores the transformative capacity of large-scale 3D printing in construction, examining current progress, potential trajectories, and inherent limitations. Furthermore, it assesses the impact of expanded 3D printing adoption on the construction labour market. Our findings highlight 3D printing’s potential to significantly diminish the need for manual labour, addressing labour shortages, particularly in countries reliant on immigrant labour forces. However, its effectiveness may vary in regions with competitive labour costs where manual labour remains prevalent. Integrating 3D printing in construction necessitates cultivating a specialised workforce with expertise in this innovative technology. In conclusion, this study underscores the transformative influence of 3D printing in construction, offering increased efficiency, reduced labour dependency, and solutions to industry challenges. Adapting 3D printing adoption to regional labour dynamics and workforce upskilling is essential for maximising its benefits. As the construction industry evolves, embracing 3D printing emerges as a pivotal factor in shaping its future landscape.

Abusing the unprotected ‘poor’: The prevalence of povertyist stigma and hate speech on unmoderated newspaper comment threads

The UK-wide Equality Act 2010 forbids discrimination based on age, sex, race, religion/belief, disability, gender reassignment, sexual orientation, marriage and civil partnership, and pregnancy and maternity – yet no such protections apply to people experiencing poverty and/or class-based inequalities. This legislative ‘blind-spot’ extends to UK media regulation, with most industry ethical codes prioritizing the same ‘protected characteristics’ as the law. As a result, legacy print news outlets and their audiences can freely publish statements about people in poverty that would be defined as hate speech; ruled in breach of ethical codes; and liable for potential prosecution if directed at protected groups. This article explores the prevalence of povertyist hatred on comments published on two conservative-leaning news-sites (www.telegraph.co.uk and www.dailymail.co.uk) in response to articles about rising labour shortages and ‘economic inactivity’ rates during the post-COVID-19 ‘cost-of-living crisis’. It exposes serious gaps in the legal and regulatory framework(s) around protected characteristics, while also posing difficult questions for editors and moderators about the (in)adequacy of their existing policies for safeguarding groups already protected by law.

Autonomous mining through cooperative driving and operations enabled by parallel intelligence

Autonomous mining is promising to address several current issues in the mining sector, such as low productivity, safety concerns, and labor shortages. Although partial automation has been achieved in some mining operations, fully autonomous mining remains challenging due to its complexity and scalability in field environments. Here we propose an autonomous mining framework based on the parallel intelligence methodology, employing self-evolving digital twins to model and guide mining processes in the real world. Our framework features a virtual mining subsystem that learns from simulating real-world scenarios and generates new ones, allowing for low-cost training and testing of the integrated autonomous mining system. Through initial validation and extensive testing, particularly in open-pit mining scenarios, our framework has demonstrated stable and efficient autonomous operations. We’ve since deployed it across more than 30 mines, resulting in the extraction of over 30 million tons of minerals. This implementation effectively eliminates the exposure of human operators to hazardous conditions while ensuring 24-hour uninterrupted operation.

Peran Petani Jagung Dalam Meningkatkan Ekonomi Masyarakat Desa Margo Lestari

Corn farming holds immense potential in Margo Lestari Village. The community views it as a promising avenue for income generation and improved living standards. This study delves into the characteristics of corn farming experience, labor and capital allocation, and their impact on the community's economic well-being. Additionally, it identifies the obstacles faced by farmers in developing this lucrative crop. The qualitative data analysis reveals that farming experience, labor allocation, and capital play crucial roles in determining corn farming income. Land ownership and control also influence revenue levels. Labor is a vital factor, particularly during the harvest season. However, farmers encounter several challenges. Labor shortages during peak periods, pest and disease attacks, and limited access to eco-friendly pest control measures hinder progress. Even mild pest infestations can significantly impact corn production, leading to increased reliance on chemical pesticides. Furthermore, marketing through middlemen and lack of transportation facilities to reach traditional markets restrict profit margins. Based on these findings, the study proposes several solutions. Mobilizing and regulating labor allocation can optimize production and potentially increase revenue. Seeking environmentally friendly pest control alternatives can ensure the sustainability of corn farming. In conclusion, corn farming holds significant promise for Margo Lestari's economic development. By addressing the identified challenges and implementing the proposed solutions, the community can harness the full potential of this valuable crop and boost its collective prosperity.

A decision support framework to improve flow management in a supply chain subject to risks

ABSTRACT This research aims at developing an approach to assess the probability of meeting customer service level, while considering various risk factors present in a supply chain (supply disruptions, uncertainties in lead times, labour shortages, transport disruptions etc.). The work is conducted in tight collaboration with a leading actor of an aeronautical industry. Our model enables a better management of supply chain flows by improving two KPIs of interest for the company that operates in a MTO environment: on-time delivery (OTD) and depth of delay (DOD), by varying the repartition of flows between possible production and transportation modes. Change in transportation mode is indeed considered as a risk mitigation lever leading to sustainable operations. We first collect input data, which includes data related to the characteristics of the system under study (flow diagram, data pertaining to parameters such as lead time, cost, capacity…) and supply chain risks mapping. Then, we develop a discrete event simulation (DES) model considering supply chain risks to determine the best flow repartition enabling to satisfy KPIs considered. A performance evaluation module enables to calculate the probability distribution of the chosen KPIs. Finally, a multi-scenario analysis is conducted by varying different parameters that have an impact on OTD, DOD and the total cost.

Design and Development of Solar Operated Fodder Cutting and Collecting Machine

Abstract: This paper describes the design, manufacture and performance evaluation of a small modified forage cutter and harvester built with a very simple mechanism that is cheap and simple. Harvesting fodder is a necessary farming activity that requires considerable work. Labor costs and availability pose significant challenges during the cutting season. Due to shortage of labor and unpredictable weather during harvesting, farmers must use mechanized methods to ensure speed of harvesting and collection. We have used various techniques to analyze and design a very low-cost fodder cutter and harvester with solar system and battery. This machine is designed for small farmers who have less than 2 acres of agricultural land. This small machine can cut up to two stacks of fodder at once. The feed is cut by reciprocating blades that cut it like scissors. It uses a 12V electric motor for propulsion. This power is supplied to the cutter by an electric motor. After sowing, the feed is collected in a storage tank using a collection system. Because it was built using spare parts readily available in the area, this small machine is easy to maintain and operate. Small farmers can find this machine the answer to their labor and implementation cost problems

Structural Optimization of 4-DOF Agricultural Robot Arm

The shortage of human labor is increasing; thus, more agricultural machinery and equipment are expected to enter the agricultural sector. One of the agricultural machinery widely studied nowadays involves robot arms. Therefore, developing robot arms is a hot issue in this field. The ideal structure of the robot arm with optimal length is currently gaining popularity and being used in many sectors, such as manufacturing and agriculture. This is closely related to the dynamic structure of agricultural areas. Therefore, this study uses the forward kinematic modeling method to design an optimal robot arm to achieve a specific coordinate in a dynamic environment. The robot in this study arm mimics the boom and arm installed on a tractor. The forward kinematic problem in this study is defined using the Denavit-Hartenberg (DH) convention method. The DH convention is commonly used to solve kinematic analysis problems of a robot arm. Simulation of kinematic modeling is performed using MATLAB software. This study studies various optimization algorithms to compare the performance of algorithms that can achieve the optimal length with minimum errors. The comparison between artificial bee colony (ABC) and particle swarm optimization (PSO) is studied. At the end of the study, the best algorithm was selected for the robot arm design with a four-degree-of-freedom (4-DOF). The best algorithm, i.e., the PSO algorithm, is evaluated by calculating mean square error (MSE of 0.00108527), root mean square error (RMSE of 0.01678), mean absolute error (MAE of 0.004286081), and end-effector position error (error of 0.080557045), where the best algorithm has the lowest value of error.

Strategies to alleviate Canada’s impending construction labour shortage: a critical review

Strategies to alleviate Canada’s impending construction labour shortage: a critical review

The impact of COVID-19 on the financial performance of the UK construction firms

The COVID-19 outbreak was deemed a pandemic by the World Health Organization (WHO), and the associated travel restrictions led to an unprecedented fall in the UK economic growth including the construction sector. Nevertheless, few quantitative studies assessing the impact of COVID-19 on the UK construction sector have been conducted as of now. So, this research aims to quantitatively assess the COVID-19 pandemic’s effects and causally evaluate its influence on the UK construction industry. We utilize panel data comprising financial information from listed UK construction firms spanning from 2015 to 2021. The findings reveal a substantial adverse impact of COVID-19 on business performance, with a notable improvement in performance in 2021 compared to 2020. It also proves that the supply chain disruption, labour shortage, and financial dilemma are the main reasons for the negative effect of COVID-19 in 2020 and 2021, and increased vaccination rate, domestic policy changes, and potential for construction development are the possible reasons for the 2021 recovery. Despite the gradual easing of the epidemic situation, the construction industry must enhance its resilience to sudden disasters to effectively facilitate a robust economic recovery. It is essential to further examine the economic fluctuations caused by the pandemic emergency and the mechanisms for its recovery.

Redefining Japan’s Tourism: Post-COVID Challenges and Cultural Dynamics

The global tourism landscape has undergone considerable transformation owing to the COVID-19 pandemic, which has altered its dynamics and created new challenges. Previously, travel was linked to well-being, fostering social connections, and a sense of belonging. However, the pandemic has caused substantial disruptions, leading to job losses and changes in travel behavior. Japan, which was already grappling with overtourism pre-pandemic, faced challenges such as strained infrastructure and environmental impact. Post-pandemic challenges include issues regarding tourist etiquette and labor shortages within the industry. Japan’s deeply rooted mask-wearing culture, driven by social responsibility, may lead to social stigma if norms are ignored, thus affecting tourism. Owing to an aging population and unattractive job profiles, the industry faces labor shortages, which lead to difficulties in recruiting during peak seasons. Therefore, understanding these challenges is crucial for the recovery and revival of tourism in Japan. Strategies must align with evolving societal values and sustainable practices to address behavioral norms and labor shortages. Using tweet-derived data, this study revealed an unexpected increase in discussions regarding mask use, highlighting Japan’s societal emphasis on harmony and consideration of others. This study highlights the challenges faced by tourists and industry professionals, particularly regarding foreign visitors’ comprehension of Japanese cultural norms. The results emphasize the critical factors affecting post-pandemic tourism in Japan, with the aim of exploring cultural influences on sustainable tourism in subsequent research. This endeavor aligns with the vision of the United Nations World Tourism Organization to reconstruct the industry and ensure equitable benefits for all stakeholders.

Advancing Robotic Fruit Picking: Adaptive End-Effector Approach

In modern agriculture, the demand for efficient fruit picking methods is constantly increasing due to labor shortages and the need to improve productivity. Traditional fruit picking methods often rely on manual labor, which is labor-intensive, time-consuming, and prone to inconsistency. This study aims to develop a novel end effector for agricultural fruit picking robots, which improves the efficiency and accuracy of fruit picking through highly flexible and adaptive design. It can effectively handle fruits of diverse types, shapes, and hardness. By adopting a three-finger scheme and independent servo motor control, the simulated movements of human hands are realized. Shape memory alloy (SMA) and electroactive polymer (EAP) as intelligent driving materials, as well as flexible materials such as silicone, are explored to optimize the grip performance and fruit protection of the actuator. High-precision visual and tactile sensors are also integrated to support the accurate identification of fruits of different maturity. The performance of the actuator is evaluated through advanced data analysis techniques, including descriptive statistics, hypothesis testing and regression analysis. The findings suggest that the proposed design optimization measures based on data analysis results can further enhance the adaptability and efficiency of the robot in future applications, thereby addressing the challenges faced in modern agricultural practices and contributing to increased productivity and sustainability in the agriculture sector.

Russian Enterprises at the End of 2023: Recovery Growth against the Backdrop of Sanctions, Worsening Labor Shortages and Rising Credit Costs

Russian Enterprises at the End of 2023: Recovery Growth against the Backdrop of Sanctions, Worsening Labor Shortages and Rising Credit Costs

An Analysis of Reemployment Pathways for China's Young Elderly

With the increasing scale of population aging, China may face the situation of labor shortage. Exploiting the social potential of the elderly group, stimulating the social vitality of the elderly group, and letting younger elderly join the reemployment team play an important role in effectively making up for the lack of labor force and coping with the aging population. By exploring the feasibility of reemployment of the young elderly in China, it is found that the reemployment of the young elderly in China is facing a double dilemma at the personal and social levels. The growth of age, the decline of physical function, and other related factors make the young elderly unable to adapt to digitalization, few employment channels, and the impact of the traditional concept of intergenerational care on the reemployment of the young elderly, while the vulnerability of the elderly group itself brings challenges to their social participation. To effectively solve these dilemmas, this paper puts forward the optimization scheme from the three dimensions of the state, society, and the elderly themselves.

Farmer typology and drivers of agricultural mechanization use in Haiti

Agricultural mechanization is recognized as an important technology to increase agricultural productivity, face labor shortages, and reduce post-harvest loss. However, variations among farms’ characteristics and agricultural production systems suggest adopting a targeted strategy in mechanization programs for farmers. This research aimed to answer the following questions in the particular case of Haiti: are there different types of smallholder farmers in terms of mechanization use and socio-economic characteristics? What types of mechanization are used by farmers, and what drives their use among different types of farmers? What are the different types of farms in terms of mechanization use? We used typology construction methodology (principal component analysis (PCA) and hierarchical cluster analysis (HCA)) for a sample of 637 farmers and have identified four different clusters of farmers according to the characteristics of the farms they managed: “Little rain-fed farms” (cluster 1), “Little lowlands farms” (cluster 2), “Medium-sized farms in irrigated plains” (cluster 3), and “Large fragmented mountain farms”. Farms in cluster 3 were those who used more agricultural mechanization, and the results of multinomial logistic regression (MNLR) model revealed that the significant drivers of this use were location, access to credit and low food security status. Mechanization use of farms in clusters 1 and 4 was distinctively driven by saving behavior and off-farm income, respectively. In the pooled sample, the drivers of mechanization were: regions or location, age of the farmers, irrigation, livestock, access to credit, off-farm income and food security status. This study contributes to the literature by testing new drivers of agricultural mechanization such as food security status, and off-farm income. The findings can be used to design appropriate mechanization strategies to increase productivity and face labor price/scarcity challenges. They suggest that mechanization policies should focus on agricultural equipment that are adapted to the specificities of the production systems of each farm type, and strengthen access to credit. Otherwise, mechanization will be predominantly used only in irrigated lowlands.

Digital Technologies Adoption and Economic Benefits in Agriculture: A Mixed-Methods Approach

Governments globally aim to boost productivity and enhance farmers’ livelihoods, addressing challenges like climate change, food security, and labor shortages through digital technologies. However, adoption rates in developing countries remain low due to uncertainties regarding expected returns and obstacles stemming from subjective and objective factors among farmers. This study takes China as a case study to examine the internal and external factors influencing growers’ adoption intensity of digital technology and its impact on enhancing economic benefits, aiming to provide valuable insights for the promotion of digital technology in other countries and regions. This study employs a mixed-methods approach, integrating qualitative and quantitative methodologies, utilizing data from Shandong and Liaoning provinces. The findings underscore the significant role of growers’ knowledge, technology compatibility, government support, and competitive pressure in driving the adoption of digital technology among growers, with male growers and those managing larger cultivation areas demonstrating higher adoption intensity. Digital technologies can enhance growers’ economic benefits by reducing labor and input costs, increasing yields, and improving quality, with a 30.4% increase in economic benefits for each unit increase in adoption intensity of digital technologies. Technology promoters can use these findings to enhance growers’ awareness, highlight the practical benefits, and offer agricultural socialized services to promote digital technology adoption.

Linking types of East Javanese rice farming systems to farmers' perceptions of complex rice systems

CONTEXTComplex rice systems (CRS) are polycultures in which rice is grown together with one or more plant or animal species using combined methods of practices from indigenous knowledge and modern science in augmenting ecological processes to foster ecosystem services in rice agroecosystems. However, their implementation faces challenges due to farmers' knowledge gaps, high capital outlay and labour shortages. OBJECTIVEThis study aims to link types of rice farming and farmer perceptions to facilitate recommendations to scale up CRS. METHODSWe constructed a farm typology based on a survey of 111 farm households and aggregated cognitive maps (ACMs) based on fuzzy cognitive maps developed in focus group discussions in Malang and Lamongan, East Java Province, Indonesia. RESULTS AND CONCLUSIONSThe farm typology classified farm households into three types: (a) small farms with high inputs of agrochemicals (SH, n = 29) which were all identified in Malang; (b) medium-size farms with high input intensity of agrochemicals (MH, n = 43), distributed across Malang and Lamongan; and (c) medium-size farms with low inputs of agrochemicals (ML, n = 39), all detected in Lamongan. ACMs revealed the differences in farmer group's perceptions on farm input-output relations, agroecosystems processes and CRS component interactions. SH and MH farmers prioritised economic benefits over ecosystem services and crop-livestock components. SH farmers were locked into high-input and high-output systems, while MH farmers failed to obtain high output despite high input use. Intervention schemes could be developed such as thorough training on economics for SH farmers and efficient use and on-farm production of fertilisers for MH farmers. Meanwhile, with the majority of ML farmers having adopted CRS, their priorities were more evenly distributed across all components, implying their more holistic understanding of the interacted components. However, technical assistance on agronomic, post-harvest management and marketing were still considered to be needed to ensure a long-term sustainability of CRS practices by ML farmers. SIGNIFICANCECombining farm typology and fuzzy cognitive mapping could facilitate a comprehensive understanding of farming system types, their characteristics and farmer perceptions as a key to formulate appropriate interventions for a specific farm type. Therefore, these methodological approaches could provide guidance to accelerate transitions toward complex agroecosystems.

WORKING CAPACITY FOR PERSONS WITH MUSCULOSKELETAL DISORDERS

Musculoskeletal disorders (MSDs) are prevalent globally and result in substantial personal distress and significant social expenses for businesses and society. The ageing population and labor shortages exacerbate these effects. The aim of this study is to investigate the impact of MDS on employment absenteeism and presenteeism. Two instruments, the EQ-5D and the iPCQ, were used to quantitatively survey the Latvian population. 949 respondents of working age were surveyed. From this group, 553 respondents with MSD were selected, averaging 47 years old, 50.6% of whom were men. The results showed that 7.23% experienced absenteeism in the last month. Additionally, 45.9% reported discomfort at work due to MSDs. The EQ-5D-5L questionnaire revealed a decline in health-related quality of life with increasing age, highlighting the significance of addressing the aging workforce and promoting health preservation. 38.3% of respondents with MSDs received rehabilitation interventions, which showed a moderate association with health-related quality of life. The study showed that there is a negative correlation between health-related quality of life and productivity loss. This highlights the importance of comprehensive interventions that address both the physical and psychological aspects of MSDs. The findings offer valuable insights for policymakers, employers, and healthcare professionals to design targeted interventions that improve the health and productivity of individuals with MSDs.