Non-routine Tasks Research Articles

NEUROBICS: A VITAL ADJUNCT TO PHYSICAL THERAPY IN IMPROVING COGNITIVE AND PHYSICAL FUNCTIONS IN A PREGNANT WOMAN WITH WERNICKE'S ENCEPHALOPATHY - A CASE REPORT.

Background: Wernicke’s Encephalopathy (WE) is a neurological disorder caused by thiamine deficiency, leading to cognitive and physical impairments like confusion, ataxia, and ophthalmoplegia. Pregnant women with WE face additional challenges due to pregnancy demands. This case report examines the use of neurobics—cognitive exercises to stimulate brain function - as an adjunct to physical therapy in enhancing cognitive and physical recovery in a pregnant woman with WE. Objective: This report aims to demonstrate the benefits of combining neurobics with physical therapy to improve cognitive and physical outcomes in a pregnant woman with WE. Case Presentation: A 28-year-old pregnant woman in her second trimester, diagnosed with WE, presented with confusion, ataxia, and visual disturbances. After stabilization with intravenous thiamine, a rehabilitation program combining neurobics and physical therapy was initiated. Physical therapy targeted balance, coordination, and strength, while neurobics engaged the brain with unusual sensory stimuli and non-routine tasks to enhance cognitive function. Results: After four weeks, the patient’s cognitive function improved, with her MoCA score increasing from 4 to 17. Significant gains were seen in executive function, attention, language, visuospatial skills, and orientation, though memory remained unchanged. Ataxia symptoms also improved, with her SARA score reducing from 22 to 14. Conclusion: The integration of neurobics with physical therapy offered a comprehensive approach to rehabilitation in this pregnant woman with WE. Neurobics enhanced cognitive recovery alongside physical rehabilitation, suggesting its potential as a valuable adjunct in managing WE.

Tasks, wages and new technologies

AbstractThis paper addresses the role of technology in shaping worker‐level task prices, exploiting within‐occupation variation using a unique survey linked to administrative data for over 180,000 Dutch workers between 2014 and 2020. Nonroutine abstract and interactive tasks are related to wage premia, and routine tasks to wage penalties. However, these task returns vary according to exposure to the types of (new) technology, such as computers, robots and artificial intelligence. Overall, wages are higher in technology‐intensive industries, but newer technologies target non‐routine tasks differently. This may have profound implications for the nonroutine wage premium given the rise of artificial intelligence.

Contract labour in mining and occupational health and safety: A critical review

Abstract In recent decades, there has been a global growth of the use of contract labour in the mining industry, primarily driven by cost/flexibility considerations. At the same time, contracting has been associated with poorer occupational health and safety (OHS) outcomes across a range of industries. Drawing on published research, theses, and government reports, this paper critically reviews the available evidence on the OHS effects of contract labour in mining and the likely implications of further growth in this trend. This evidence confirms that the use of contract labour is associated with worse OHS outcomes, and that the Ten Pathways and Pressure, Disorganisation, and Regulatory failure (PDR) models are both valuable in explaining this. The latter point is confirmed by a more detailed examination of four serious mine incidents in NSW and Queensland. The paper identifies some gaps and areas for further research as well as the actions that mining companies, regulators, and unions could take to improve contractor safety. Notwithstanding the latter, the paper argues that the most effective way of improving contractor safety in mines is reducing the use of contractors overall and concentrating their activities in areas such as major shutdowns/repairs, where contractors have specialised expertise to undertake non-routine tasks. Despite oft-repeated phrases such as zero-harm and management systems, the corporate shift to using contractors is primarily driven by cost-cutting and highlights how OHS is compromised by such priorities.

Effect of automation of routine and non-routine tasks on labour demand and wages

Artificial intelligence and associated technology advances have progressively diffused from routine tasks to non-routine tasks, causing disruptions in the labour market. In this work, we study the effect of automation on the labour market outcomes for low-skilled and high-skilled workers. We use the agent-based modelling approach to model firms and workers as rational agents with defined objective functions, endowments, and interactions. Using extensive simulations, we analyse the emergent phenomenon of employment levels and wage inequality in the labour market under varying scenarios. The key findings of our simulations indicate that automation of routine tasks increases wage inequality, whereas automation of non-routine tasks reduces it. Based on our results, we propose policy prescriptions regarding the job categories in which automation can be introduced for societal benefits, the skill enhancement programme needed for the workers, and guidelines on the redeployment of labour displaced through automation.

Adapting to the Agricultural Labor Market Shaped by Robotization

Agriculture is being transformed through automation and robotics to improve efficiency and reduce production costs. However, this transformation poses risks of job loss, particularly for low-skilled workers, as automation decreases the need for human labor. To adapt, the workforce must acquire new qualifications to collaborate with automated systems or shift to roles that leverage their unique human abilities. In this study, 15 agricultural occupations were methodically mapped in a cognitive/manual versus routine/non-routine two-dimensional space. Subsequently, each occupation’s susceptibility to robotization was assessed based on the readiness level of existing technologies that can automate specific tasks and the relative importance of these tasks in the occupation’s execution. The qualifications required for occupations less impacted by robotization were summarized, detailing the specific knowledge, skills, and work styles required to effectively integrate the emerging technologies. It was deduced that occupations involving primary manual routine tasks exhibited the highest susceptibility rate, whereas occupations with non-routine tasks showed lower susceptibility. To thrive in this evolving landscape, a strategic combination of STEM (science, technology, engineering, and mathematics) skills with essential management, soft skills, and interdisciplinary competences is imperative. Finally, this research stresses the importance of strategic preparation by policymakers and educational systems to cultivate key competencies, including digital literacy, that foster resilience, inclusivity, and sustainability in the sector.

The Efficacy of Tournaments for Nonroutine Team Tasks

Previous articleNext article FreeThe Efficacy of Tournaments for Non-Routine Team TasksFlorian Englmaier, Stefan Grimm, Dominik Grothe, David Schindler, and Simeon SchudyFlorian Englmaier Search for more articles by this author , Stefan Grimm Search for more articles by this author , Dominik Grothe Search for more articles by this author , David Schindler Search for more articles by this author , and Simeon Schudy Search for more articles by this author PDFPDF PLUS Add to favoritesDownload CitationTrack CitationsPermissionsReprints Share onFacebookTwitterLinkedInRedditEmail SectionsMoreDetailsFiguresReferencesCited by Journal of Labor Economics Just Accepted Published for the Society of Labor Economists, Economics Research Center/ NORC Article DOIhttps://doi.org/10.1086/725553 HistoryAccepted April 19, 2023 © 2023 The University of Chicago. All Rights reserved.PDF download Crossref reports no articles citing this article.

Industrial robot applications and individual migration decision: evidence from households in China

The integration of industrial robot application (IRA) into various sectors has catalyzed significant transformations in the labor market, reshaping the dynamics of individual migration decision (IMD). As industries increasingly adopt automation, the implications for workforce distribution and migration patterns become critical areas of study. Based on the conditional logit model and using CMDS data, this paper explores the relationship between IRA and IMD, as well as the heterogeneity effect and influencing mechanism. The findings indicate that IRA reduces the probability of the floating population choosing the city, and the results are robust after considering endogeneity and further robustness test. The impact of IRA on IMD is heterogeneous. Relatively speaking, the floating population with high education levels, health, younger, unmarried, female, agricultural household registration, state-owned enterprises, and non-routine task work does not over-think the impact of IRA during the migration process. In addition, the floating population also considers geographical location, city size, marketization level, wage level, and environmental quality when making migration decisions. the mechanism test shows that IRA attracts or suppresses the floating population through factors such as wage levels, housing price level, difficulty in finding a job, etc., depending on the result of individual utility maximization. These insights reveal the complex interplay between technological advancements in robotics and labor migration, emphasizing the need for comprehensive policy frameworks to manage these transformations effectively.

Gendered wage returns to changes in non-routine job tasks: Evidence from Germany

The labor market exhibits persistent occupational segregation by gender, with women and men performing distinct job tasks within their occupations. Prior research suggests that non-routine job tasks generally lead to higher wages, especially in digitally advancing contexts. However, these findings are largely based on cross-sectional data and neglect gender as a relevant dimension of inequality. We analyze three-wave panel data over nine years from the German National Educational Panel Study to explore the relationship between changes in non-routine job tasks and wages by gender. Given the constrained wage-setting opportunities within German firms, we further examine whether the association between task changes and wages differs for employees with and without job changes, both within and across occupational segments. Our fixed-effect regression analyses reveal gender-specific associations between changes in non-routine job tasks and wage increases. Men benefit from performing more complex and autonomous tasks, with additional gains when an inter-segmental job change accompanies the increase in complex job tasks. Conversely, women do not see wage benefits from enhancements in either complex or autonomous job tasks. These findings underscore the gendered patterns of wage increases associated with advancements in non-routine job tasks, with men profiting intra-individually from shifts towards more non-routine job tasks.

Evaluation of airborne asbestos concentrations associated with the maintenance of brakes on an industrial overhead crane

Objectives To evaluate potential airborne asbestos exposures during brake maintenance and repair activities on a P&H overhead crane, and during subsequent handling of the mechanic’s clothing. Methods Personal (n = 27) and area (n = 61) airborne fiber concentrations were measured during brake tests, removal, hand sanding, compressed air use, removal and reattachment of chrysotile-containing brake linings, and reinstallation of the brake linings. The mechanic’s clothing was used to measure potential exposure during clothes handling. Results All brake linings contained between 19.9% to 52.4% chrysotile asbestos. No amphibole fibers were detected in any bulk or airborne samples. The average full-shift airborne chrysotile concentration was 0.035 f/cc (PCM-equivalent asbestos-specific fibers, or PCME). Average task-based personal air samples collected during brake maintenance, sanding, compressed air use, and brake lining removal tasks ranged from 0 to 0.48 f/cc (PCME). The calculated 30-minute time-weighted average (TWA) airborne chrysotile concentration associated with 5-15 minutes of clothes handling was 0–0.035 f/cc PCME. Conclusion The results indicated that personal and area TWA fiber concentrations measured during all crane brake maintenance and clothes handling tasks were below the current OSHA 8-h TWA Permissible Exposure Limit for asbestos of 0.1 f/cc. Further, no airborne asbestos fibers were measured during routine brake maintenance tasks following the manufacturer’s maintenance manual procedures. All short-term airborne chrysotile concentrations measured during non-routine tasks were below the current 30-minute OSHA excursion limit for asbestos of 1 f/cc. This study adds to the available data regarding chrysotile exposure potential during maintenance on overhead cranes.

Academic or vocational education? A comparison of the long-term wage development of academic and vocational tertiary degree holders

Education is a key determinant of wage development. The relationship between education and wages is particularly strong in countries with vocationally oriented educational systems and a clear distinction between general and vocational education, such as Germany and Switzerland. However, whether general and vocational education offer the same returns to education is an ongoing debate. Previous findings from international research are still inconclusive. Against this background and based on theoretical arguments from human capital and signalling theory and the task-specific learning-by-doing approach, our paper examines the long-term wage development of Swiss university and professional education degree holders from the time they obtain their tertiary degree until their late career. It asks how differences between the two groups in wage development may be explained. Our results, produced with regression decomposition methods, show that within the first 20 years after graduation, university degree holders experience steeper wage growth. An important reason for this difference is that university graduates move more often than vocational tertiary degree holders into well-paid labour market positions endowed with formal authority, management responsibility, and a large proportion of cognitive nonroutine tasks.

Estimating the Wage Premia of Refugee Immigrants: Lessons from Sweden

This article examines the wage earnings of refugee immigrants in Sweden. Using administrative employer–employee data from 1990 onward, approximately 100,000 refugee immigrants who arrived between 1980 and 1996 and were granted asylum are compared to a matched sample of native-born workers. Employing recentered influence function (RIF) quantile regressions to wage earnings for the period 2011–2015, the occupational-task-based Oaxaca–Blinder decomposition approach shows that refugees perform better than natives at the median wage, controlling for individual and firm characteristics. This overperformance is attributable to female refugee immigrants. Given their characteristics, refugee immigrant females perform better than native females across all occupational tasks studied, including non-routine cognitive tasks. A notable similarity of the wage premium exists among various refugee groups, suggesting that cultural differences and the length of time spent in the host country do not have a major impact.

The Effects of Labor-Saving Technological Progress on Capital Accumulation: Evidence from NASDAQ-100 Firms

This study delves into the impact of labor-saving technological progress on the capital accumulation of technology companies that have a substantial workforce consisting of highly skilled workers over the sample period from 2000/Q2 to 2021/Q3. To begin with, we estimate a three-equation system of the normalized-CES production function to derive labor-saving technical progress and the elasticity of substitution between capital and labor for NASDAQ-100 firms. Secondly, two linear regression models are estimated by using parameters acquired in the initial step to assess the impacts of labor-saving technological progress on capital accumulation. Based on the estimation results, labor-saving technological progress and the elasticity of substitution between capital and labor mitigate the upward trend of capital accumulation despite their stimulating impacts on economic value added in the NASDAQ-100 firms. These two adverse results are consistent with the concept of skill intensity in technology firms, referring to the difficulties of replacing automation with non-routine tasks and highly skilled workers. In this sense, along with the insufficient replacement of technological progress with labor, the detrimental effects of technological progress on capital accumulation widen the gap between labor productivity and labor compensation during profit expansion periods. These negative consequences are mitigated by worker layoffs during profit-downsizing periods, despite its accelerating impact on economic value added.

The impact of Robots on Labour market transitions in Europe

We study the effects of robot exposure on worker flows in 16 European countries between 2000 and 2017. Overall, we find small negative effects on job separations and no effects on job findings. We detect significant cross-country differences and find that labour costs are a major driver: the effects of robot exposure are generally larger in absolute terms in countries with relatively low or average levels of labour costs than in countries with high levels of labour costs. These effects are particularly pronounced for workers in occupations intensive in routine manual or routine cognitive tasks but are insignificant in occupations intensive in non-routine cognitive tasks. A counterfactual analysis suggests that robot adoption increased employment and reduced unemployment, especially in European countries with relatively low or average levels of labour costs, and that these effects were driven mainly by lower job separations.

How ChatGPT shapes the future labour market situation of software engineers: A Finnish Delphi study

ChatGPT is changing our working lives, conjuring visions of revolutionary shifts ahead. ChatGPT is a chatbot based on generative artificial intelligence, which can, e.g., write computer code. This article explores how it might shape the future labour market situation of software engineers. A Delphi study with 14 experts was conducted in Finland. The first round identified possible futures, and the second round assessed their probabilities. Five scenarios prevailed: the unlikely scenario that the status quo persists; the ambivalent scenario that ChatGPT can replace software engineers to a large extent; the likely scenario that computer departments in startups embrace ChatGPT; the likely scenario that ChatGPT use proliferates among software engineers to increase productivity; and the highly likely scenario that ChatGPT makes computer programming accessible to the masses. Findings contradict previous discussions that technological advancements might take over especially routine tasks. ChatGPT can also take over non-routine tasks. Moreover, findings underline that digitalisation does not only bring about a choice between upskilling and employability loss, but also a democratisation of knowledge and expertise. Software engineers and companies might use the findings as an impetus for upskilling, while universities might feel nudged to incorporate ChatGPT more strongly into their curricula.

Measuring the routine and non-routine task contents: a comparative study between state and industrial sector employees

PurposeThis study developed new measures of the routine and non-routine task contents of managerial, professional, technical, and clerical occupations from a workload perspective. Here, we present a comparative analysis of the workload structures of state and industrial sector employees.Design/methodology/approachOur method involves detailed descriptions of work processes and an element-wise time study. We collected and analysed data to obtain a workload structure that falls within three conceptual task categories: (i) non-routine analytic tasks, (ii) non-routine interactive tasks and (iii) routine cognitive tasks. A total of 2,312 state and industrial sector employees in Kazakhstan participated in the study. The data were collected using a proprietary web application that resembles a timesheet.FindingsThe study results are consistent with the general trend reported by previous studies: the higher the job level, the lower the occupation’s routine task content. In addition, the routine cognitive task contents of managerial, professional, technical, and clerical occupations in the industrial sector are higher than those in local governments. The work of women is also more routinary than that of men. Finally, vthe routine cognitive task contents of occupations in administrative units are higher than those of occupations in substantive units.Originality/valueOur study sought to address the challenges of using the task-based approach associated with measuring tasks by introducing a new measurement framework. The main advantage of our task measures is a direct approach to assessing workloads consisting of routine tasks, which allows for an accurate estimation of potential staff reductions due to the automation of work processes.

High levels of air pollution reduce team performance

Teams play a key role in tackling complex societal challenges, such as developing vaccines or novel clean energy technologies. Yet, the effect of air pollution on team performance in non-routine problem-solving tasks is not well explored. Here, we document a sizable adverse effect of air pollution on team performance using data from 15,000 live escape games in London, United Kingdom. On high-pollution days, teams take on average 5% more time to solve a sequence of non-routine analytical tasks, which require collaborative skills analogous to those needed in the modern workplace. Negative effects are non-linear and only occur at high levels of air pollution, which are however commonplace in many developing countries. As team efforts predominantly drive innovation, high levels of air pollution may significantly hamper economic development.

Employment and wage dynamics in the electricity sector: Evidence from Portugal 2002–2020

Exploring a rich administrative matched employer-employee longitudinal dataset over the 2002–2020 period and a task-based approach, this study investigates to what extent the recent paradigm shift in the electricity sector has affected the structure of employment and wages in the Portuguese case. Our results show that the liberalization in the sector led to the entry of new players and firms' downsizing of the workforce, most notably in occupations involving routine cognitive tasks and non-routine manual tasks. In two decades, the employment share of occupations involving non-routine cognitive tasks (abstract or interactive) doubled, from 29.7% in 2002 to 58.1% in 2020. Regarding wage premiums, the results reveal a clear positive trend in real hourly wages for all types of occupations in the sector. However, we observe a lower wage growth acceleration for workers employed in routine (cognitive or manual) occupations, when compared with similar workers employed in non-routine occupations (cognitive or manual). Our findings are partly consistent with the skill-biased and routine-biased technological change hypotheses in the sense that we observe, respectively, a skill up-grading translated into an increase in employment share in non-routine cognitive occupations and a substantial decline in employment share in routine cognitive occupations.

Building and sustaining competence in maintenance: a prescriptive training model

In the dynamic landscape of industrial workplaces, the demand for maintenance personnel capable of handling non-routine tasks has become increasingly crucial. However, traditional training programs, structured in pre-established sessions and relying on real equipment with expert technicians working alongside learners, are limited in their ability to establish a connection with the moment of effective performance and maintain effectiveness, which may diminish over time due to the forgetting phenomenon if conducted well in advance. Recognizing the pivotal roles of experience and training in mitigating human errors during maintenance tasks, as well as the limitations in current training practices, this study aims to propose a novel prescriptive training model and discuss practical managerial implications. This model leverages prescriptive analytics and cognitive-based learning models with the aim of generating training sessions tailored to the specific needs of maintenance tasks and calibrated to the operator’s expertise level. The ultimate goal is to develop the basic model for an adaptive training system, utilizing advanced technologies to enhance the performance of workers and reduce the risk of errors in non-routine tasks.

Robot revolution and human capital accumulation: implications for growth and labour income

AbstractWe develop a model of endogenous growth with automation to study the impact of industrial robots on growth and labour income. We incorporate human capital accumulation into that framework to examine the role of human capital in sustaining growth without displacing low-skilled labour. While automation replaces low-skilled labour with industrial robots in conducting routine tasks, horizontal innovation creates new varieties in which low-skilled labour has an employment advantage. Labour-augmenting technology takes place to improve productivity of low-skilled labour. As such, those latter types of innovation help counterbalance the adverse effect of automation on low-skilled labour. Human capital, the essential production factor that takes part in every economic activity, including conducting non-routine tasks, accumulates over time through education and training. We show that there exists a long-run equilibrium at which either robots or low-skilled workers are employed, together with human capital, to produce varieties. In the fully endogenous model, final output grows at the rate of human capital accumulation. An improvement in the quality of education and training leads to an acceleration of both automation and variety expansion, but not human capital growth. Our numerical exercise indicates that a permanent increase in automation entails a permanent impact on the range of automated varieties, long-run output level and human capital wage. The shock lowers long-run growth and low-skilled workers’ wage and their effective income share. However, it has no effect on the effective income share of human capital.

Routine and non-routine sectors, tasks automation and wage polarization

ABSTRACTRecent and detailed data point to a polarization of wages with regard to the distribution of skills, particularly in developed countries over the past three decades, requiring the literature to address modelling approaches focused on automating different types of tasks. In the DTC literature, the technological-knowledge bias leads to an increase in the wage of skilled workers relative to unskilled workers. Motivated by this literature, this paper considers three types of workers (skilled, medium-skilled and unskilled) but retain the economic mechanisms that produce the results. Thus, wage inequality continues to result from the technological-knowledge bias, which, in the face of automation dynamics, reveals that medium-skilled workers are the relatively most penalized, generating wage polarization. Furthermore, as in the directed technical change literature, the relative supply of skilled workers continues to affect the skill premium.