Labor Productivity Research Articles

Analisis Produktivitas Pegawai terhadap Pelayanan Permasalahan Kinerja Aparatur Sipil Negara di Direktorat Status Kedudukan Kepegawaian Kantor Pusat Badan Kepegawaian Negara (BKN) Jakarta

This study aims to analyze the performance of human resources in the Directorate of Civil Service Status at the State Civil Service Agency in handling service problems or ASN status cases. Labor productivity is influenced by various factors related to the workforce itself as well as those related to the company environment and government policies as a whole, such as education, skills, discipline, attitude and work ethics. Research methods are classified based on the objectives and level of natural setting of the object, research methods can be classified into basic research objectives, applied research methods and research and development. In this study, the researcher chose the type of Qualitative research to present and describe in detail and in detail the analysis of employee productivity in serving ASN performance problems at the Directorate of Civil Service Status of the BKN. Research Results Overall, the quality of service at the Directorate of Civil Service Status of the State Civil Service Agency (BKN) can be categorized as very good, supported by clarity of information, ease of access through various communication channels, and employee responsiveness in handling complaints. The completeness of the files submitted by the proposing agency greatly affects the speed of the service process. When the files are complete, the process can run quickly and efficiently. However, incomplete files are often the cause of delays in service. and the use of technology, such as the ASN SI application, is very helpful in improving the efficiency and effectiveness of services. Technology allows ASN to access information and services more quickly and easily.

Effects of ICTs on Labor Productivity: A Re-examination of Solow’s Paradox Through the Prism of the Joint Use of ICT Tools in Cameroonian Firms

Effects of ICTs on Labor Productivity: A Re-examination of Solow’s Paradox Through the Prism of the Joint Use of ICT Tools in Cameroonian Firms

Technological employment: Evidence from worldwide robot adoption

Technological advances can automate many jobs, therby reducing the reliance on some workers, yet they can also create jobs. Determining the overall impact is not immediately evident and necessitaes empirical research. In this paper, we use data on worldwide robot adoption from 1993 to 2021 to explore whether robots increase labour productivity and employment in the 74 sampled economies. We find that robots lead to higher productivity and employment on a global scale. To gain more insights into the results, we also examine the effects both in the long run and the short run using labour market data from developed countries. Using error correction model, the findings show that robot adoption increases employment in the long run but has no effect on overall employment in the short run. This study argues that in spite of perpetual automation spanning many generations, there are still many occupational opportunities, a fact that is not likely to change with the increased robot use. In fact, robot adoption leads to more jobs in developed economies which by and large adopt robots to a greater degree, leading to ‘technological employment’. While economies of the developing countries which adopt robots to a lower degree, do not seem to experience a similar outcome.

Lean Manufacturing Tools as a Driver of the Company’s Digital Transformation

The article substantiates the impact of applying lean manufacturing tools on the digital company’s transformation. The study distinguishes the main lean manufacturing tools that contribute to the optimisation of production processes, reduce losses and improve staff efficiency. Special attention is paid to the synergy of lean methods and digital technologies, which allows companies to adapt to changing market conditions and remain competitive by accelerating and replicating production processes in their digital transformation. The case study of implementing lean manufacturing tools at the Russian food industry enterprises, participants in the national project “Labour Productivity,” demonstrates the feasibility of implementing the key 5 lean manufacturing principles (sorting, organising, standardising, keeping clean and improving), along with the Manufacturing Execution System (MES). The author concludes that companies need to combine lean manufacturing and digital technologies to improve efficiency. Given the fact that lean manufacturing and information technology can conflict, providing their integration will increase the success of the digital company’s transformation. A lean manufacturing approach simplifies production processes, improves the efficiency of digitalisation and increases the likelihood of successful adoption of Industry 4.0 technologies.

Spatial and interindustry interactions in labour productivity convergence: An Industrial Journey via Galician Shires, 2010–2018

Regions and industries are not isolated islands; so, when evaluating productivity growth, regional and sectoral growth paths should not be expected to generate independently. Moreover, accounting for spatial interactions via econometric models has become normal practice; but modelling interindustry dependencies has not. Thus, we expand labour productivity econometric convergence models by introducing interindustry spillovers in addition to spillovers that are spatial in nature. To illustrate our findings, we present an empirical application predicated upon Galicia (extreme northwest Spain), a region posing major challenges to such modelling. Our results point to the relevance of interindustry spillovers in explaining productivity growth. Furthermore, the approach allows us to better interpret covariates that explain the different growth paths across regions and industries, thus enabling more reliable policy recommendations. We find that interindustry dependencies transmit productivity shocks across regions. In addition, our results suggest that spatial and interindustry dependencies should be considered when formulating (sub)regional economic development policies. Finally, our approach corrects possible misspecification problems that arise from data scarcity. This makes it a viable alternative for multiregional econometric tests in which some sectoral detail is needed. It is particularly useful for sets of regions where data needed to populate such models is scarce.

Productivity drivers and pro-productivity policies: G20 economies, India and South Korea

In this article we look at productivity trends, drivers of productivity growth and pro-productivity policies across the G20 economies since 1970. We distinguish between three sub-groups of G20 economies: a “leading but slowing” group of the most developed economies, a “lagging but growing” group of economies that have shown rapid growth and a “muddling through” group of economies with no sustained improvement in productivity performance. We find distinctly different dynamics between the sub-groups regarding the contributions of capital deepening and total factor productivity (TFP) to labour productivity growth. The slowdown in labour productivity growth since the 2010s has been underpinned by lower TFP growth. India is the only G20 economy which has experienced a significant improvement in TFP growth over the past few decades. We develop a typology distinguishing five domains of pro-productivity policies (accumulation of the factors of production, markets and resource allocation, technological and structural change, internationalisation, and foundational policies) and explore how these have been applied across countries and over time. We also provide a more detailed analysis of productivity and related policies for two G20 countries: India and South Korea. We argue that a revival of productivity growth in the G20 requires a greater focus on policies which balance technological progress with knowledge diffusion; more investment in intangibles and public assets; and improvements in the quality of human capital.

Temperature and corporate industrial robot adoption: evidence from China

ABSTRACT Our study explores the impact of temperature changes on corporate industrial robot adoption using data from Chinese non-financial listed firms in the manufacturing sector between 2009 and 2019. We find that an increase in temperature positively affects corporate adoption of industrial robots. This positive relationship between temperature increases and corporate adoption of industrial robots is significant in the years following the introduction of China’s high-temperature subsidy policy and for non-state-owned firms, eastern-located firms, firms with low equity concentration, and firms with high financial constraints. A mechanism analysis reveals that rising temperatures decrease labour productivity and increase the employee cost.

FEATURES OF SMALL AND MEDIUM-SIZED BUSINESSES IN RUSSIA

The article examines the features of small and medium-sized businesses in Russia since 2019. Its role in the modern market economy and directions of development are revealed. The article examined statistical data on the small and medium-sized business sector: employment, profitability, share in GDP, dynamics of the number of enterprises, and also analyzed the state of the business climate of small and medium-sized enterprises in Russia using the RSBI index. The dynamics of these indicators over the past four years are considered. It is noted that the main point of development of the sector is the increase in its share in GDP; in developed countries this figure is significantly higher than in Russia: in our country it has been at a low level throughout 2019-2021. The article also analyzes the role of small and medium-sized businesses in the economy of the Udmurt Republic: indicators such as the share of small and medium-sized businesses in the republic’s GRP, as well as the share of loans to small and medium-sized businesses in the total issuance of loans by banks are considered. The topic of the efficiency of economic activity of small and medium-sized enterprises in Russia and labor productivity in them is considered. The directions for the development of measures to support small and medium-sized enterprises are analyzed. A comparison has been made of some aspects of running and features of small and medium-sized businesses in the USA. The main directions for the development of SMEs have been identified and disclosed. The importance, weaknesses and strengths of small and medium-sized businesses in Russia, as well as ways to improve the situation of small and medium-sized businesses in Russia are analyzed. New directions for the development of small and medium-sized enterprises have been studied.

The impact of industrial robots on low-carbon green performance: Evidence from the belt and road initiative countries

Global warming is intensifying, with Belt and Road Initiative (BRI) countries accounting for over two-thirds of global carbon dioxide emissions. As a pivotal technology in advanced manufacturing, industrial robots significantly impact the overall carbon footprint through their role in production processes. This study examines how the use of industrial robots influences the Low-Carbon Green Performance (LCGP) across BRI nations, utilizing a dataset spanning from 2004 to 2020. The findings reveal that the integration of industrial robots notably boosts the LCGP within these countries, a conclusion supported by extensive robustness evaluations. The novelty of this study lies in uncovering the underlying mechanism by which industrial robots improve LCGP through the promotion of technological innovation. Specifically, we find that industrial robots have a pronounced effect on technological progress (TC), an impact that is further amplified by increases in labor productivity and human capital levels. This discovery provides policy implications for BRI governments, suggesting that actively promoting the development of industrial robots can accelerate energy transformation and upgrading, thereby reducing carbon emissions. Our research fills a significant void concerning the environmental impact of industrial robots and offers new perspectives and strategies for BRI countries to achieve low-carbon development goals. These findings contribute significant theoretical and practical value to global environmental protection and sustainable development.

The Aembu access to land and labour systems on food crop production and food security up to 1906

This study sought to analyse how the pre-colonial Aembu organised their land and labour systems in food crop production for guaranteed household food security up to 1906. The pre-colonial African societies had either matrilineal or patrilineal systems of land ownership, while labour was gender specific. The study employed a descriptive research design. The study was conducted in Embu East, Embu West and Embu North sub-counties of the larger Embu County. Purposive sampling with a snowballing technique was applied to get 50 respondents who were interviewed from a target population of 16,144. The study corroborated data from oral, archival records and secondary sources. The findings were that the pre-colonial Aembu food crop producers had elaborate systems of land rights and land use under clan heads. The land access system accommodated practices like shifting cultivation and intercropping; the pre-colonial division of labour in food crop production combined all household members and those other forms of labour like communal, paid and corporate were sourced from outside the household. The study concluded that the pre-colonial Aembu were food secure in spite of occasional rainfall failure, locust invasion and warfare, while the articulation of pre-colonial and capitalist land and labour systems exposed the society members to food insecurity. The study contributed to the pre-colonial social, political and economic historiography of the Aembu people. The study recommends that the post-colonial government should employ strategies that can be effectively used to mitigate food crop production insecurity by focusing on the adoption of various traditional methods of land and labour access.

Colonial transformation of the Aembu land access and labour division systems in food crop production from 1906-1963

This study examined the colonial transformation of the Aembu access to land and labour division in food crop production from 1906-1963. Colonial practices and policies undermined the Aembu land and labour systems in food crop production. Methodologically, the study used descriptive research design and Articulation of Modes of Production Theory. The study was conducted in Embu East, Embu West and Embu North sub-counties of Embu. The study targeted a population of 16,144 people based on the 2019 census. Corroborated data was obtained from oral, archival and secondary sources to establish the reliability and validity of the research. The study’s findings were that the creation of African reserves to pave way for white settlement and labour supply from Africans led to the abandonment of crop farms since they were far away; the reserves had limited land sizes with poor soils for the production of enough food while most of the food storage facilities were destroyed in the process of migration and that during the political crisis of World Wars and Mau Mau, labour in food crop production was reduced. It concluded that colonialism transformed the Aembu land and labour systems while the co-existence of pre-colonial and colonial access to land and labour systems on the production of food crops exposed the community to famines. The study recommends that policymakers should come up with strategies for promoting traditional forms of access to land and labour to ensure adequate food crop production.

Artificial intelligence as a core of the new industrial revolution: prospects and limitations

The purpose of the article is to define prospects and limitations of artificial intelligence as a core of in the new industrial revolution. The definition of the concept of AI in the scientific community remains the subject of heated debate. At the same time, in the regulatory and legal plane, a trend is being formed towards unification of the concept of AI. Based on the analysis conducted and literary sources, the following prospects for AI can be identified on theoretical and practical levels. On theoretical level: (1) alienation of tacit knowledge from the individual (employee and entrepreneur); (2) optimization of the planning system; (3) revision of the socialist-calculation debate; (4) decreasing information asymmetry. On practical level: (1) formation of new products and markets; (2) increasing labor and capital productivity; (3) massive creation of new jobs; (4) optimization of business processes; (5) opportunity for rapid growth for small businesses and startups. Limitations: (1) long-term structural unemployment; (2) inflated expectations from AI and, as a consequence, the possible formation of a speculative bubble in the global stock market; (3) energy consumption of AI; (4) outdated pre-AI corporate culture and regulatory environment. Further improvement of AI (including the transition from AI to AGI) and the expansion of its use can make a significant contribution to solving problems related to economic calculation and minimizing information asymmetry, and therefore optimizing transaction costs in the economy. AI, certainly acting as a locally useful tool at the level of individual enterprises and organizations, causes the acceleration of attracting funds to the stock market, which can lead to the formation of a bubble on global level. If this bubble bursts, expectations about the economic efficiency of AI will be revised, and some AI-related companies will experience significant margin reductions (perhaps losses and bankruptcies). But this, in turn, will initiate the next stage of AI development, will accelerate its transition from the current narrow specialization to the creation of full-fledged general artificial intelligence (artificial general intelligence), which has a greater potential to change the economy at all levels. As a result, AI will become established as the core of the new industrial revolution.

Directional nature of technological progress in the petrochemical industry prompting energy marginal substitution

Technological progress does not uniformly benefit all industries or factors' productivity levels. The energy productivity and labour employment situation in the Chinese petrochemical industry have not witnessed substantial improvements in the last decade. The literature has overlooked the importance of recognizing the directional nature of technological progress, which could enable a more strategic approach to economic development, resource allocation, and policy formulation. This study, guided by the core principles of endogenous economic growth theory, aims to uncover the influencing mechanisms and effects of technological progress bias on energy and employment by extending a theoretical model to account for energy, capital, and labour factors. The results reveal: (1) From 2000 to 2021, the relationship between labour, capital, and energy factors in the Chinese petrochemical industry has been predominantly complementary, with technological progress favouring labour-augmenting that is increasing labour productivity; (2) The gross complementarity of production factors leads to labour-augmenting technological progress, ultimately biased towards energy and capital factors; (3) Energy-capital-biased technological progress encourages producers to invest more energy and capital to substitute for labour factors, leading to a limited improvement in energy productivity and a consistent decline in labour employment since 2011. This study further corroborates that without government intervention, it would lead to improper factor allocation in the industry, resulting in market failure. Finally, corresponding policy recommendations are proposed.

Market Regulation, Cycles, and Growth Dynamics in a Monetary Union

AbstractWe build a two‐country currency union dynamic stochastic general equilibrium (DSGE) model with endogenous growth to assess the role of product market regulation (PMR) and labor market regulation (LMR) for growth and the adjustment to shocks. We show that with endogenous growth, there is no reason to expect real income convergence. Large shocks can lead to permanent changes of output and real exchange rates. Differences are exacerbated by different PMR and LMR. Less regulated economies have higher trend growth and recover faster from negative shocks. Results are consistent with higher inflation, lower employment, and disappointing total factor productivity (TFP) growth rates experienced in more regulated euro area members.

Effects of public procurement on corporate total-factor carbon productivity: evidence from China

Using balanced panel data for listed Chinese industrial firms from 2016 to 2021, this study examines the effect of public procurement (PP) on corporate total-factor carbon productivity (CTFCP) and the related mechanisms. The results show that (1) there is a positive correlation between PP and CTFCP. (2) PP exerts a more pronounced incentivizing effect on CTFCP for state-owned enterprises, larger corporations, and those with weaker financing constraints. (3) We decompose CTFCP into technological progress (TECH), pure technical efficiency (PTE), and scale efficiency (SE) and find that PP improves TECH and PTE, and the effect differs according to firm ownership, scale, and financing constraints. (4) PP promotes CTFCP through labor productivity (LP), capital productivity (CP), and corporate green innovation (CGI) while the mediating role of environmental productivity (EP) is not significant. This study contributes to theoretical discourse on PP’s influence on CTFCP and has practical implications for PP agencies and enterprises.

Sparking leadership and perceived organizational support as predictors of cyberloafing

Alongside numerous benefits in business life (such as additional business opportunities, increased labour productivity), the Internet is responsible for adverse effects like cyberloafing in the workplace. Accessing the Internet for personal purposes during work hours is a prominent reason for counterproductive employee behaviour. The current theoretical background, however, is not sufficient to explain the causes of such behaviour. The article aims to identify the role of such factors as sparking leadership and perceived organizational support in preventing employees’ willingness to use their work time to engage in nonwork-related internet activities. To do so, five dimensions of cyberloafing are discussed: sharing, shopping, real-time updating, accessing online content, and gaming/gambling. Leadership theories, social exchange theory, and organizational support theory constitute the methodological basis of the research. The methods used are confirmatory factor analysis, and the PLS-SEM technique to reach a path model revealing the direct, indirect, and total relationships between the given dimensions. The data were collected from March to September 2023 through a face-to-face survey with 95 respondents from over 40 SMEs operating in Türkiye. The results revealed that perceived organizational support mediates the relationship between sparking leadership and sharing, shopping, and real-time updating dimensions of cyberloafing. The results point to the need for reconsidering organizational practices, values, and policies in a way that would foster employees’ well-being and happiness within the organization and mitigate their cyberloafing behaviour.

Collaborative activities and flexible working

Digitalization and globalization have radically affected work organization and interaction between workers in the course of performing job duties. Co-creation activity on digital labour platforms is a new phenomenon that has been little studied. The paper aims to explore collaboration as a driving force in the evolution of work organization patterns and investigates its main effects on the labour market. Theory of cooperation and organizational theory constitute the methodological basis of the study. The research methods used are evolutionary analysis, statistical and regression analysis. The empirical evidence is comprised of open data from the European Social Survey (ESS) Round 10 (2020/23). The study identifies the directions for altering the forms of collaborative activities: the key ones are associated with the enhancement of individual value, accumulation of human capital and a rise in worker autonomy. It is shown that organization of work, which is also undergoing significant changes, promotes flexible working practices. The empirical analysis indicates that high-frequency Internet use among self-employed workers significantly increases the probability of engaging in co-creation activities, particularly as education levels rise. The growing intrinsic motivation of participants to such activities leads to higher labour productivity. The findings highlight a critical issue regarding the lack of human resource management practices in platform employment. Designing a new (flexible) model of work organization aligned with the characteristics and effects of co-creation activities can serve as a promising direction for further research.

Prediction of childbearing tendency in women on the verge of marriage using machine learning techniques

The declining fertility rate and increasing marriage age among girls pose challenges for policymakers, leading to issues such as population decline, higher social and economic costs, and reduced labor productivity. Using machine learning (ML) techniques to predict the desire to have children can offer a promising solution to address these challenges. Therefore, this study aimed to predict the childbearing tendency in women on the verge of marriage using ML techniques. Data from 252 participants (203 expressing a "desire to have children" and 49 indicating "reluctance to have children") in Abadan, and Khorramshahr cities (Khuzestan Province, Iran) was analyzed. Seven ML algorithms, including multilayer perceptron (MLP), support vector machine (SVM), logistic regression (LR), random forest (RF), J48 decision tree, Naive Bayes (NB), and K-nearest neighbors (KNN), were employed. The performance of these algorithms was assessed using metrics derived from the confusion matrix. The RF algorithm showed superior performance, with the highest sensitivity (99.5%), specificity (95.6%), and receiver operating characteristic curve (90.1%) values. Meanwhile, MLP emerged as the top-performing algorithm, showcasing the best overall performance in accuracy (77.75%) and precision (81.8%) compared to other algorithms. Factors such as age of marriage, place of residence, and strength of the family center with the birth of a child were the most effective predictors of a woman's desire to have children. Conversely, the number of daughters, the wife's ethnicity, and the spouse's ownership of assets such as cars and houses were among the least important factors in predicting this desire. ML algorithms exhibit excellent predictive capabilities for childbearing tendencies in women on the verge of marriage, highlighting their remarkable effectiveness. This capacity to offer accurate prognoses holds significant promise for advancing research in this field.

Искусственный интеллект глазами российских студентов: настоящее и будущее

The study, which involves 265 respondents, is aimed at identifying student youth’s attitude to using artificial intelligence in various spheres of life and ideas about it. To collect data, the authors use a questionnaire, including open questions and multiple-choice tasks in its main part. To process the data the paper applies content analysis, descriptive statistics and Pearson’s 2 criterion. It is found that students understand the phenomenon of artificial intelligence differently, interpreting it as an imitator of the human brain, a tool or a practice-oriented solution, a certain algorithm or scientific knowledge. Some students do not clearly understand the essence of the term “artificial intelligence” or find it difficult to interpret it. Students associate the main functionality of artificial intelligence with the increased labour or study productivity, with assistance in performing routine; less often, they associate it with creative tasks. However, some students cannot determine the functionality of artificial intelligence or do not see any prospects for its development for humans. Most students, considering artificial intelligence as their assistant, which reduces the time of obtaining data and creates certain conveniences, turn to it to solve their problems often or rarely. They are ready to use only free services or determine the budget for such expenses taking into account the tasks they are to solve. Students find the main barriers to using artificial intelligence in the issuance of standard, stereotypical solution options and the limitation on the data volume. Students see the prospects for the artificial intelligence development in its limitation in the legal field and possible superiority over the human mind. It is advisable to include knowledge of the artificial intelligence concept and the ability to determine its functionality in the list of universal competencies mastered at the university, and understanding the essence of artificial intelligence and the ability to use it in the context of solving applied problems should be included in professional competencies.

СУБЪЕКТИВНОЕ БЛАГОПОЛУЧИЕ НА РАБОЧЕМ МЕСТЕ: ПОДХОДЫ К МОНИТОРИНГУ САМОЧУВСТВИЯ ПЕРСОНАЛА

A direct correlation between the level of staff well-being and the company’s profitability has been proven by both foreign and Russian studies. However, one of the unresolved problems today remains the fact that well-being at work is still not considered as a factor and resource for the productivity and efficiency of employees. The reality of modern life highlights the need for a rapid rethinking of the nature and patterns of connections between well-being at work and the state of labour productivity, socio-economic assessments of this relationship, and the development of management and digital solutions for monitoring and maintaining an adequate level of staff well-being. The article presents the results of a survey of representatives of the expert community conducted by the authors to identify the current aspects of well-being at work, as well as a brief description of the concept of a digital service developed by the authors for monitoring the well-being of employees through self-assessment.