Manufacturing Labor Research Articles

Labor share decline across US manufacturing sectors: 1979–2019

ABSTRACT This paper studies the sectoral contributions to aggregate manufacturing labour share decline in the US between 1979 and 2019. Using the Log Mean Divisia index (LMDI) decomposition, the decline in the manufacturing sector’s labour share is decomposed into contributions from real wage growth, labour productivity growth, changes in employment shares, and relative prices arising from the constituent sectors across three business cycles. The primary findings of the paper suggest that the downward decoupling of real wages from labour productivity is the primary contributor to the labour share decline in manufacturing. Moreover, low labour share sectors (especially chemical products, food and beverage and tobacco products, and petroleum and coal products) have experienced an increase in their employment shares, contributing negatively to aggregate manufacturing labour share. This paper advances insights related to sectoral heterogeneity and possible mechanisms behind the decline in aggregate manufacturing labour share.

Benchmarking for platform-aggregated manufacturing service collaboration: Methodology and implementation

In light of the global economic downturn and the intricate division of labor in manufacturing, the imperative for advanced manufacturing services and Manufacturing Service Collaboration (MSC) has escalated significantly. As manufacturing services gravitate towards aggregation on manufacturing service platforms, platform-aggregated MSC has emerged as an inevitable and compelling trend, capturing the attention of researchers worldwide. However, despite the existence of numerous frameworks, models, operational mechanisms, and algorithms proposed for the platform-aggregated MSC, drawing comparisons between these studies remains a complex endeavor. To address this predicament, this article proposes and explores a novel benchmarking methodology for platform-aggregated MSC. By employing complex network theory, a comprehensive model of platform-aggregated MSC is constructed and supplemented with corresponding methodologies for data generation and the configuration of optimization algorithms. Moreover, pertinent performance evaluation metrics are scrutinized to assess their applicability in the context of platform-aggregated MSC. The article culminates with the execution of a series of platform operation experiments designed to test the effectiveness and practicality of the proposed benchmarking system, thereby contributing to the ongoing evolution of the MSC domain.

Structural Change, Elite Capitalism, and the Emergence of Labour Emancipation

Abstract This study argues that the decline of coercive labour institutions over the course of industrialization was partly driven by complementarity between physical capital and effective labour in manufacturing. Given the difficulty of extracting labour effort in care-intensive industrial tasks through monitoring and punishment, capital-owning elites ultimately chose to emancipate workers to induce their supply of effective labour and, thus, boost the return to physical capital. This hypothesis is empirically examined in the context of serf emancipation in nineteenth-century Prussia. Exploiting variation in proto-industrialization across Prussian counties, the analysis finds that, consistent with the proposed hypothesis, the initial abundance of elite-owned physical capital is associated with a higher pace of serf emancipation and lower redemption payments to manorial lords.

THE IMPACT OF ADVANCED ROBOTICS AND AUTOMATION ON SUPPLY CHAIN EFFICIENCY IN INDUSTRIAL MANUFACTURING: A COMPARATIVE ANALYSIS BETWEEN THE US AND BANGLADESH

This study explores the contrasting approaches to robotics integration in manufacturing processes employed by Bangladesh and the United States. By examining three distinct case studies – garment manufacturing, high-tech manufacturing, and agriculture – the analysis reveals significant variations in adoption rates, technological focus, and strategic implementation. These disparities stem from each nation's unique economic landscape, industrial structure, and labour market dynamics. Bangladesh, characterised by low-wage labour in garment manufacturing, cautiously incorporates automation technologies like Sewbots to enhance long-term efficiency and product quality. Conversely, the U.S. garment industry strategically utilises robots for specialised tasks in niche markets, seeking a competitive advantage through precision and design innovation. In high-tech manufacturing, the U.S. leverages readily available commercial solutions and a skilled workforce for extensive robotics adoption, ensuring precision and consistency in complex processes. Bangladesh acknowledges these benefits but faces challenges related to cost and skills gaps, necessitating capability building and strategic partnerships for future integration. Both countries recognise the high potential of robotics in agriculture; however, the U.S. combats labour shortages and enhances efficiency through advanced solutions like farming robots and UAVs. Bangladesh explores automation to increase yield and reduce manual labour dependence. This comparative analysis contributes to understanding global manufacturing and supply chain optimisation by highlighting the diverse factors influencing robotics adoption across nations. The research suggests a future where the U.S. refines and expands advanced robotics use. Bangladesh strategically invests in and develops its workforce, potentially forming partnerships to integrate robotics into high-tech manufacturing and agriculture. As robotics and automation technologies evolve, both countries stand to benefit by embracing these advancements while navigating the challenges to ensure a smooth transition toward a more automated and efficient future for their manufacturing sectors.

The transition to electrified vehicles: Evaluating the labor demand of manufacturing conventional versus battery electric vehicle powertrains

The shift from traditional internal combustion engine vehicles (ICEVs) to electric vehicles (EVs) has raised concerns about displacement of automotive manufacturing labor. Prior studies have mixed findings, and have been hindered by a lack of shop floor-level data on the labor hours required for ICEV and EV manufacturing. We collect detailed data from leading automotive manufacturers on the production process steps and labor inputs required to build key ICEV and battery electric vehicle (BEV) powertrain components. Our novel data set covers 252 process steps, with data on a further 78 process steps from the existing literature. We build a production process model that estimates the labor hours required to produce ICEV and BEV powertrain components at different production volumes and labor efficiency levels. We find that, accounting for production and assembly of battery packs, the labor intensity required for the manufacturing of BEV powertrain components is larger than for ICEV powertrain components. This difference in labor intensity holds even when comparing the highest-efficiency estimates for BEV production with the lowest efficiency-estimates for ICEVs. This finding depends on our shop-floor operations modeling approach and could not be derived from recent approaches focusing on part counts. Our results imply that vehicle electrification could lead to more automotive manufacturing jobs, at least in the short- to medium-term. While there are potential jobs to support transitions for incumbent automotive workers, the feasibility of these transitions will depend on geographic co-location of new battery production capacity with current ICEV production sites, and on matching between the skills of the automotive workforce and the demands of new EV jobs.

Supply Chain Simulation of Manufacturing Shirts Using System Dynamics for Sustainability

In supply chain management (SCM), goods and services flow from the raw materials stage to the end user with complexities and uncertainty at each stage. Computer modeling and simulation is a particularly useful method to examine supply chain operational issues because it can solve operational complexities that are challenging and time consuming to analyze. Manufacturing companies fear losing valuable time and assets during the manufacturing process; the inaccurate estimation of raw materials, human capital, or physical infrastructure not only leads to monetary loss for the manufacturing unit, but also has a detrimental effect on the environment. The purpose of this paper is to demonstrate that system dynamics modeling (SDM) in sustainable supply chain management (SSCM) can be applied to apparel manufacturing to optimize materials, labor, and equipment usage. Utilizing system dynamics (SD), the manufacturing unit can improve sustainability by reducing materials, labor, and equipment usage, which in turn reduces energy use. In our literature review, we did not identify any study addressing supply chain simulation of the manufacturing of shirts using SDM. We chose shirt manufacturing to demonstrate the model because of its relatively simple manufacturing process. In our study, we conclude that SDM simulation is an efficient way to optimize materials, labor, and equipment in apparel manufacturing. This leads to a more sustainable manufacturing process, as the model simulates different manufacturing supply chain scenarios in a risk-free environment, thereby minimizing waste and resources. Further, the outputs from the STELLA® model can be used as inputs into a subsequent life cycle assessment (LCA) model to determine the quantitative environmental impacts.

Corporate Tax Cuts and the Decline of the Manufacturing Labor Share

We document a strong empirical connection between corporate taxation and the manufacturing labor share, both in the US and across OECD countries. Our estimates associate 30 percent to 60 percent of the observed decline in labor shares with the fall in corporate taxation. Using an equilibrium model of an industry where firms differ in their capital intensities, we show that lower corporate tax rates reduce the labor share by raising the market share of capital-intensive firms. The tax elasticity of the labor share depends on the joint distribution of labor intensities and value added at the micro level. Given the empirical distribution in the US manufacturing sector, our quantitative analysis suggests that corporate tax cuts explain a significant part of the decline in the manufacturing labor share since the 1950s. The shift away from traditionally large, labor-intensive production units raised the concentration of market shares and reduced the concentration of employment.

A Comparison of Capital and Labor Incomes in Finance and Manufacturing Sectors in OECD Countries: 1995–2019

Using data from 31 OECD countries, this study analyzes labor and capital incomes in the international manufacturing and finance sectors during the years 1995 to 2019. The study examines three periods: the years between 1995 and 2007, before the global crisis; between 2008 and 2019, during and after the global crisis; and the 1995–2019 period overall. In addition, the variables were subjected to general trend analysis, to analysis of the relative change between the beginnings and ends of the various periods, and to analysis of the annual average percentage changes. The results show that in both the manufacturing and financial sectors, the incomes of capital increased more than those of labor. Comparing the two sectors, it can be stated that between 1995 and 2019 the degree of class inequality in favor of capital saw a greater increase in the sector of manufacturing industry.

The Application of Machine Vision in Intelligent Manufacturing

Machine vision technology has a rapid development rate in recent year especially in intelligent manufacturing. The field of intelligent manufacturing will undergo a revolution. Machine vision technology is currently developing and becoming more sophisticated. The related hardware and software items are continuously improved. They increasingly became significant in the industrial production process. Machine vision can replace some human labor in intelligent manufacturing, which effectively increases production efficiency and product quality. As a result, it might help businesses achieve full production automation, quality control standardization, automation, and automation. This paper discussed the key technologies of machine vision technology used in intelligent manufacturing industry, as well as the application of machine vision in intelligent manufacturing. The Key technologies of machine vision include image acquisition, image segmentation, and image recognition. The current application of machine vision in intelligent mainly include manufacturing dimensional measurement, part inspection, and object localization.

Industrialization and Convergence of West Java Manufacturing Labor Productivity, Indonesia

West Java as a national manufacturing center has experienced industrialization since 1989. This is marked by the continuous increase in the manufacturing sector so that it is able to shift other sectors. Unfortunately, the industrialization that occurred in West Java was not followed by a reduction in the manufacturing labor productivity in West Java. The convergence of manufacturing labor productivity in West Java is an important phenomenon because inequality can lead to a different pace of development and exacerbate inequality. This study uses dynamic panel data regression with the first-different GMM (FD-GMM) method for inferential analysis and Location Quotient (LQ), Klassen Typology and the calculation of the coefficient of variation for descriptive analysis. The results showed that only 7 out of 27 regencies/cities in West Java had the economy dominated by the manufacturing sector and there were fluctuations in the productivity of the manufacturing workforce in these areas. Based on Klassen's Typology, there are still many areas that are categorized as developing and underdeveloped areas. However, there is a decrease in inequality between regions as seen from the results of the convergence analysis. Sigma convergence and beta convergence occurred in West Java with the time needed to close half the gap (half-life convergence) of less than one year. Factors that significantly affect the convergence process of manufacturing labor productivity are the manufacturing labor productivity lag, FDI, DDI, and real wages of manufacturing workers.

In-situ scalable manufacturing of Epstein\u2013Barr virus-specific T-cells using bioreactor with an expandable culture area (BECA)

The ex-vivo expansion of antigen-specific T-cells for adoptive T-cell immunotherapy requires active interaction between T-cells and antigen-presenting cells therefore culture density and environment become important variables to control. Maintenance of culture density in a static environment is traditionally performed by the expansion of the culture area through splitting of culture from a single vessel into multiple vessels—a highly laborious process. This study aims to validate the use and efficacy of a novel bioreactor, bioreactor with an expandable culture area—dual chamber (BECA-D), that was designed and developed with a cell chamber with expandable culture area (12–108 cm2) and a separate media chamber to allow for in-situ scaling of culture with maintenance of optimum culture density and improved nutrient and gas exchange while minimizing disturbance to the culture. The performance of BECA-D in the culture of Epstein–Barr virus-specific T-cells (EBVSTs) was compared to the 24-well plate. BECA-D had 0.9–9.7 times the average culture yield of the 24-well plates across 5 donor sets. BECA-D was able to maintain the culture environment with relatively stable glucose and lactate levels as the culture expanded. This study concludes that BECA-D can support the culture of ex-vivo EBVSTs with lower manufacturing labour and time requirements compared to the use of the 24-well plate. BECA-D and its adaptation into a closed system with an automated platform (currently being developed) provides cell therapy manufacturers and developers with a closed scale-out solution to producing adoptive cell therapy for clinical use.

The Contribution of Agricultural Manufacturing in the Egyptian Economic Growth: Kaldor's Hypotheses

This research uses a Kaldor’s hypotheses to estimate the contribution of the agricultural manufacturing sector to increase the economic growth of the Egyptian agricultural sector during the period 1997-2018. It based on the three "hypotheses" of growth. Kaldor model depends on three hypotheses related to the relationship between the growth of manufacturing sector and the economic growth. The study used the growth rate, dummy variable, Ordinary Least Square (OLS) test, and used CUSUM squares test and Chow breakpoint test. In addition to, testing the stability of time series depended on E-view 11.0. The food, beverage, tobacco industries and textiles industry are the largest two sectors in the Egyptian agricultural manufacturing industries, as they represent about 83.58% of the total value of the agricultural manufacturing industries output during the period 1997-2018. The results shows that the increase of real growth rates of food, beverage, tobacco industries and textile production lead to increasing in the real growth rate of agricultural output. According to CUSUM Sq test and Chow test, the year 2003 is considered as the switch point for the study variables. Also, if the real agricultural manufacturing production growth rate increases, the real agricultural manufacturing labor productivity growth rate will increase. And if the real growth rate of agricultural manufacturing production value increases, the real growth rate of agricultural non-manufacturing labor productivity will increase. The results of the research assist decision-makers in the field of manufacturing industry and agriculture in Egypt, especially in the stages of economic development.

PENGARUH PENURUNAN TARIF IMPOR TERHADAP PERMINTAAN TENAGA KERJA MANUFAKTUR DI INDONESIA

Abstract In the last two decades the trading system in developing countries has become more open with reduced trade barriers through decreasing import tariffs. Based on previous research, there is a theoretical and empirical relationship between the reduction in import tariffs and the demand for labor. This study examines the relationship between the reduction in import tariffs and the demand for formal labor at the district / city level in the medium term. Meanwhile, workers need time to move between sectors and between regions to be absorbed in sectors that are experiencing an increase in exports. Therefore, in analyzing the demand for manufacturing labor due to a reduction in import tariffs, this research is conducted in the medium term, namely in a five-year period. By using data on labor in the manufacturing sector at the district / city level in Indonesia from 2000 to 2015, this study estimates the effect of reducing import tariffs on the demand for formal manufacturing labor with weighted regression. In contrast to previous studies, this study uses the measurement of exposure to the reduction in import tariffs by Dix-Carneiro Kovak (2017) for the manufacturing sector at the district / city level and covers 22 manufacturing subsectors. The estimation results show that the reduction in import tariffs in the manufacturing sector in the medium term increases the demand for formal manufacturing labor. This needs to be supported by the formation of industrial areas with diverse manufacturing sectors. However, this empirical evidence contradicts the policy of forming industrial estates that are specialized with regional superior potential in accordance with Presidential Regulation Number 28 of 2008.

Technopolitics from Below: A Framework for the Analysis of Digital Politics of Production

This article develops a multi-level framework for the analysis of a bottom-up politics of technology at the workplace. It draws on a multi-case study on algorithmic management of manual labor in manufacturing and delivery platforms in Germany. In researching how workers influenced the use of algorithmic management systems, the concept of technopolitics is developed to refer to three different arenas of negotiation: (1) the arena of regulation, where institutional framings of technologies in production are negotiated, typically between state actors, employers’ associations, and unions. (2) The arena of implementation, where strategies of technology deployment are negotiated—in the German production model typically between management and works council. (3) The arena of appropriation, in which different organizational technocultures offer contesting schemes for the actual use of technology at work. Whereas most recent research on digitalization of work conceptualizes workers as mere objects of digitalization processes, this paper focuses on worker agency as a “technopolitics from below.” It thus demonstrates how workers influence the concrete outcome of digitalization projects.

The costs of “blue sky”: Environmental regulation, technology upgrading, and labor demand in China

To cope with the stricter environmental regulation, manufacturing firms need to carry out pollution reduction activities and change their optimal production decisions, which may affect their labor demand. Using a ten-year firm-level panel dataset (1998–2007), we use an estimation technique pairing propensity score matching (PSM) with a difference-in-differences (DID) estimator to examine the impacts of a national air pollution control policy on employment in China. We find that China's Key Cities for Air Pollution Control (KCAPC) policy effectively lowered sulfur dioxide (SO2) emissions by approximately 26%. The new environmental regulation significantly reduced manufacturing labor demand by approximately 3%. Most importantly, firms reduce pollution emission mainly by upgrading production technology so the decline in labor is partly due to the increase in labor productivity brought about by technological progress. As a result of pollution reduction, low-skilled employees and workers in domestic manufacturing firms are more affected by environmental regulation in China.

Not a Typical Firm: The Joint Dynamics of Firms, Labor Shares, and Capital–Labor Substitution

The decline in the U.S. labor share is far from uniform across firms. While the aggregate labor share has declined, especially in manufacturing, retail, and wholesale, the labor share of a typical firm in these industries has risen. This paper studies the dynamics of the substitution of capital for labor at the firm level and its implications for market structure and labor shares. We introduce a model of firm dynamics where firms make costly upfront investments to adopt the capital-intensive technologies required to automate additional tasks. Following a decline in the price of capital, large firms automate more of their tasks and become more capital intensive; while the median firm continues to operate a more labor-intensive technology. In line with firm-level data, our model generates transitions in which the labor share of the median firm increases at the same time as the aggregate labor share declines. We use an extension of our model that allows for endogenous markups to study the role of rising competition and reallocation towards more productive and higher-markup firms as another driver of the decline in the labor share during 1982–2012. We provide a quantitative decomposition showing that reallocation played a minor role in explaining the decline in the labor share in U.S. manufacturing but an important role in retail and other sectors. The substitution of labor with cheaper capital in a widening range of tasks played a more dominant role in explaining the decline of the manufacturing labor share.

“Scrap-Heap Storiesˮ: Oral Narratives of Labour and Loss in Scottish Mining and Manufacturing

This article is an attempt to comprehend deindustrialisation and the impact of plant downsizing and closures in Scotland since the 1970s through listening to the voices of workers and reflecting on their ways of telling, whilst making some observations on how an oral history methodology can add to our understanding. It draws upon a rich bounty of oral history projects and collections undertaken in Scotland over recent decades. The lush description and often intense articulated emotion help us as academic “outsidersˮ to better understand how lives were profoundly affected by plant closures, getting us beyond statistical body counts and overly sentimentalised and nostalgic representations of industrial work to more nuanced understandings of the meanings and impacts of job loss. In recalling their lived experience of plant run-downs and closures, narrators are informing and interpreting; projecting a sense of self in the process and drawing meaning from their working lives. My argument here is that we need to listen attentively and learn from those who bore witness and try to make sense of these diverse, different and sometimes contradictory stories. We should take cognisance of silences and transgressing voices as well as dominant, hegemonic narratives if we are to deepen the conversation and understand the complex but profound impacts that deindustrialisation had on traditional working-class communities in Scotland, as well as elsewhere.

Alternative measure of border effects across regions: Ripley's K‐function method

AbstractThis study uses Ripley's K‐function to examine the diversity in cross‐region labor mobility under various border effects from heterogeneous policies. Based on manufacturing labour data for Chinese cities, we emphasize the importance of border effects in the formation of regional integration with a Ripley's K‐function analysis. The statistical measures indicate that the amount of labour mobility involves distance‐decay effects of the border. However, the variety in the distance‐decay of the border effects differs considerably between each pair of adjacent regions. For this reason, transport costs caused by natural or economic geography probably explained most of the differences in border effects.

Deindustrialisation and health: mapping the mechanism of impact in the Hungarian rust belt

Abstract Background Industrial countries are undergoing a prolonged period of deindustrialisation, characterised by declining labour in manufacturing and extractive industries. Considering the urgent need to decrease humanity's overall environmental footprint, industrial transformation is imperative. Research showed that deindustrialisation correlates with worsening ill health; yet, little attention has been paid to mapping the complexity of the mechanism of impact. Methods Hungary experienced significant deindustrialisation in the 1990s and a parallel decline in life expectancy. Four medium-sized towns were identified in the Hungarian rustbelt: two moderately (25-50%), and two severely (>50%) deindustrialised. Between September 2016 and January 2017, 82 semi-structured interviews were conducted in these towns with subjects who were working-age adults in 1989 and who lived and worked in the interview towns in the following decades. The 816,118 words-long interview-corpus was analysed with qualitative thematic analysis using NVivo. Findings The interviews revealed that deindustrialisation affects health through multiple channels. Short-term mechanisms impact individuals directly, such as unemployment, deprivation and increased work-related stress. Medium-term mechanisms impact health through disrupting social hierarchies, social capital, local services, and workplace identities. Long-term impacts are latent, and influence health through territorial stigma, loss of working-class culture, and accumulated perceptions of injustice. Conclusions Deindustrialisation is a crucial contextual factor affecting ill health over the short, medium and long term. Going beyond the direct individual channel, involving communities and localities, the health effect of deindustrialisation represents a complex and layered mechanism with multiple explicit and latent components. Complex research approaches and policy responses are needed to address explicit and latent structural mechanisms alike. Key messages The study maps the mechanism of impact that links deindustrialisation and ill health in four Hungarian towns using thematic analysis of 82 qualitative interviews. Deindustrialisation affects health over the short, medium and long term going beyond the direct individual channel, necessitating complex research approaches and policy responses.

FACTOR MISALLOCATION, INDUSTRIAL STRUCTURE AND LABOR INCOME SHARE IN CHINA

By presenting a two-sector DGE model, this paper investigates the relative misallocation coefficients for capital and labor within three industries in China from 1993 to 2018, then discusses the effect of factor misallocation and factor substitution elasticity on the labor income share. The following three conclusions were reached. (1) The overall labor income share reduced due to the industrialization before 2007, but after 2007 it increased by promoting the proportion of services. (2) Compared with the situation without barriers, the cross-industry factor misallocation reduced the proportion of labor in manufacturing by 44% during industrialization and in services by 5.05% during de-industrialization, respectively. (3) Eliminating the factor misallocation could raise the labor income share by 4.6% in industrialization, but it shows a weak effect during de-industrialization.