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Journal articles on the topic 'Labor productivity'

Author: Grafiati
Published: 4 June 2021
Last updated: 1 August 2024

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1

Uskova, T. "Labor Productivity." Problems of Economic Transition 53, no. 1 (May 1, 2010): 51–62. http://dx.doi.org/10.2753/pet1061-1991530104.

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2

Kapeliushnikov, Rostislav I. "Labor Productivity and Labor Compensation." Problems of Economic Transition 57, no. 11 (November 2, 2015): 1–34. http://dx.doi.org/10.1080/10611991.2014.1121083.

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3

Shcherbakov, A. I. "MEASURING LABOR PRODUCTIVITY." Social & labor researches 52, no. 3 (2023): 80–86. http://dx.doi.org/10.34022/2658-3712-2023-52-3-80-86.

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The subject of the study is the types of labor productivity, as well as the essential differences between individual ways of measuring it, including measuring the result and costs of labor activity, the nature and content of the corresponding labor productivity indicators. The purpose of the article is to argue the unacceptability of some methods of measuring labor productivity proposed in the scientific discussion and to identify scientifically sound approaches and parameters that reflect the return of living labor as one of the factors of production. The relevance of this paper is related to the need for measures to activate the economy mainly on the basis of increasing labor productivity in the face of foreign economic challenges and the aggravation of military threats to Russia. The scientific novelty of the article consists in substantiating the refutation of proposals on the use of purely monetary parameters and material components in measuring labor productivity, as well as in arguing the expediency of using the costs of living labor for this and better accounting of its results. The idea of a certain monetary-conjunctural labor efficiency is introduced. The research methods are analysis, systematization, synthesis, induction and deduction. As a result, the scientific parameters of the priority methodological and practical tools for measuring labor productivity for the purposes of state socio-economic policy and corporate governance were determined. The article also formulates the author’s positions on a number of debatable issues related to the inevitability of reducing the cost of production with an increase in labor productivity at the enterprise, the concepts of “productivity” and “labor productivity”, generally accepted standards for measuring the latter, etc.
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4

Burtseva, T. A., A. A. Frenkel, and A. A. Surkov. "Statistical Modeling of Regional Labor Productivity." Voprosy statistiki 29, no. 4 (September 6, 2022): 62–70. http://dx.doi.org/10.34023/2313-6383-2022-29-4-62-70.

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The article from the perspective of interregional comparative analysis methodology substantiates the system of labor productivity factors and presents the results of statistical modeling of labor productivity in the regions of Russia in 2020.The shortcomings of the existing measures of labor productivity in international and domestic practice are noted, namely, the ambiguity and inconsistency of the assessment results. The authors propose a technique for constructing an integral index of regional labor productivity and substantiate a four-factor econometric model of the dependence of the integral index of regional labor productivity, which allowed for an improved system of labour productivity factors to be applied in regional economic analysis. Estimates are given of the relative impact of both traditional and new factors of regional labor productivity, which are the increasing incidence rate and the growing share of unprofitable enterprises (organizations), investments and industrial output per capita in the regions of Russia in 2020.The need to monitor regional labor productivity factors annually to help bring forward problems in the regions is justified. The reasons that led to the insufficient level of labour productivity (compared to Russian average) were identified. According to the authors (following the results of socio-economic development in 2020), they should include low growth rates of investment and production volumes, as well as an increase in the incidence and in the share of unprofitable enterprises and organizations.
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5

Yilmaz, Rasim. "THE RELATIONSHIP BETWEEN EXPENDITURE AND LABOR PRODUCTIVITY." Southeast European Review of Business and Economics 3, no. 1 (June 2022): 65–74. http://dx.doi.org/10.20544/serbe.05.01.22.p04.

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Theoretically, the relationship between health expenditures and labour productivity is ambiguous. On the one hand, health expenditures can enhance labour productivity by improving health of workers. Poor health impairs both the working hours and productivities of workers. When workers are healthy, they become physically and mentally more energetic and they have higher incentive to develop new skills and knowledge. On the other hand, increase in health expenditures may deteriorates labour productivity by crowding out physical capital investment. Causality between health expenditures and labour productivity is also ambiguous. This paper investigates the long-run relationship between health expenditures and labor productivity by utilizing a panel data covering the period between 2000 and 2015 and 35 OECD countries. Results of the study displays that there is a positive and statistically significant long-run association between health expenditures and labor productivity. Findings indicate that an increase in per capita health expenditure leads to a rise in labor productivity in terms of GDP per person employed. Results of the study also suggest that there is a mutual (bi-directional) causality relationship between health expenditures and labor productivity indicators.
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6

Lee, Youngjae. "Labor Outsourcing and Labor Productivity Illusion." Journal of Industrial Economics and Business 35, no. 5 (October 31, 2022): 1029–51. http://dx.doi.org/10.22558/jieb.2022.10.35.5.1029.

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7

Jaroszewska, Joanna, and Włodzimierz Rembisz. "SOURCES OF THE DYNAMICS OF LABOR PRODUCTIVITY CHANGES IN AGRICULTURE IN EUROPEAN UNION COUNTRIES BASED ON ECONOMIC ACCOUNTS FOR AGRICULTURE (EAA)." Annals of the Polish Association of Agricultural and Agribusiness Economists XX, no. 2 (May 7, 2018): 72–77. http://dx.doi.org/10.5604/01.3001.0011.8118.

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The purpose of this analysis is to illustrate sources of dynamics of labour productivity factor performance based on the analytical approach adopted. The dynamics of gross value added and employment in agriculture were shaped to the dynamics of labor productivity changes. Derived analytical approach to the sources of dynamics of changes in labour productivity has been illustrated empirically. The empirical analysis was based on EU ROSTAT data. Economic Accounts for Agriculture and Statistics of Agricultural Labor Inputs. The positive impact of both sources of labor productivity growth and gross value added a tendency towards greater stability for the EU -15 countries has been demonstrated, the neutral nature of direct payments for changes in labor productivity was found.
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8

Gołaś, Zbigniew. "Przemiany i uwarunkowania wydajności pracy w rolnictwie Unii Europejskiej w latach 2005-2016." Roczniki Naukowe Ekonomii Rolnictwa i Rozwoju Obszarów Wiejskich 106, no. 1 (June 27, 2019): 22–35. http://dx.doi.org/10.22630/rnr.2019.106.1.2.

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The main aim of the work was to present the changes observed in the labour productivity in EU agriculture in years 2005-2016. The author proposed also the methodical decomposition of the labor productivity ratio in agriculture. Seven factors (ratios) have been taken into account in three models of labor productivity decomposition. These factors are: inputs productivity, land productivity, value added index, production taxation, production subsidies, equipment employed in agricultural land and the level of agricultural production intensity. The use of the deterministic method allowed to analyse the changes in labour productivity from the perspectives both in the EU agriculture (EU-28) and in the Polish agriculture. Performed studies seems to prove that in the years 2005-2016 the labor productivity measured by gross value added increased in case of EU-28 by average 2.13% and in the case of EU-15 only by 0.98%. At the same time, higher increase was observed in the case of EU-13 which equal to 3.45%. It may suggest that can be observe the ongoing process of the labor productivity convergence in EU agriculture. In the light of deterministic analysis, it was possible to specify the main factors contributing to the increase in labor productivity in agriculture in the EU-28 and in Poland, which are the increase in production intensity and the increase in agricultural land/labour relation. However, it should be also noted that the favorable direction of changes in labour productivity was weakened by the decreasing efficiency of production measured by the inputs productivity and the share of value added in revenues.
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9

Burtseva, T. A. "Measures of Regional Labour Productivity." Voprosy statistiki 28, no. 1 (February 19, 2021): 18–27. http://dx.doi.org/10.34023/2313-6383-2021-28-1-18-27.

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In this article, in the form of publication, are presented key study findings that cover both methodological issues of measurement and comprehensive analysis of regional labor productivity, along with extended formulations of study results. Based on the experience of domestic and foreign statisticians, the author substantiates the system of regional labour productivity indicators required for its integrated assessment. In the author’s opinion, this system is needed in a formation of a single coordinated approach to the calculation of labour productivity from the perspective of branches, enterprises, and constituent entities of the Russian Federation.The introduction argues for the relevance of the issues related to measuring regional labour productivity, which is necessary to evaluate the progress of the Federal Project “Systemic Measures to Improve Labor Productivity” implemented under the national project “Labor Productivity and Employment Support”.The author justifies the solution to the problem of clustering regions by regional labour productivity indicator using a combined approach, which explains the trends in the economic development of the regions of Russia in the selected clusters.The final part of the article concludes that the study is relevant in assessing the factors of regional labour productivity needed to identify growth reserves or to prevent stagnation in economic development, measured, in particular, by means of a basic indicator of the economic production efficiency in constituent entities of the Russian Federation.
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10

Wahyuningsih, Yayuk Minta, and Muhamad Baparki. "ANALISIS EFISIENSI TENAGA KERJA USAHATANI PADI ( Oryza sativa L ) PADA LAHAN KERING DENGAN CARA TANAM JAJAR LEGOWO DI DESA SUNGAI LURUS." ZIRAA'AH MAJALAH ILMIAH PERTANIAN 45, no. 3 (September 28, 2020): 354. http://dx.doi.org/10.31602/zmip.v45i3.3479.

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This research was conducted to know, level of labor efficiency of rice farm effort. A survey with an observation technique was used as a method, where farmers follow the example of taken at random modestly as much as 29 farmers. Result of research obtained by the story, level of productivity equal to 2.081,44 kg/ha, and acceptance equal to Rp 16.651.538,46 /ha. Distribution of external labour family( TKLK) 88,73 % and family labour ( TKDK) 11,27 % from totalizing the labour effusing. while the allocation for labor cost equals to75,85 % to total cost representing a group of biggest expense rice. Count efficiency of labor from the facet of labor productivity obtained value17,18 kg/HKO, from facet labor Productivity Index Obtained Rp 84.046,71 /HKO and from wide facet equal to 82,54 m2/HKO.
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11

Kuzior, Aleksandra, Vitaliia Koibichuk, Serhii Drozd, Dymytrii Grytsyshen, and Tetiana Vasylieva. "Determinants of labor productivity in the USA." Problems and Perspectives in Management 21, no. 4 (December 27, 2023): 724–39. http://dx.doi.org/10.21511/ppm.21(4).2023.54.

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This study aims to examine whether the labor productivity of the US population directly depends on public or private insurance coverage of people, employment level, life expectancies, spending on the public health system as a percentage of GDP, and spending on the public health system in natural terms. Empirical testing was carried out on the USА statistical data for 1987–2021 using a regression model with the fitting procedure backward stepwise selection (in Statgraphics software), and a multivariate adaptive regression spline MARS (using Salford Predictive Modeler software). The research hypothesis was confirmed for only two indicators: life expectancies and spending on the public health system in natural terms. Their impact on labor productivity appeared to be directly proportional. As an indicator, spending on the public health system has a greater impact on the change in productivity (0.0058%), whereas life expectancy has a lesser effect (0.0047%). The study showed that the MARS model provides more objective and accurate results compared to the regression model with the fitting procedure – backward stepwise selection. This conclusion is based on a comparison of real data modeled by both methods. The study proved that labor productivity in the USA grew yearly from 1987 to 2021 (the constant term in the MARS model’s regression equation is +0.48428). To calculate the specific values of labor productivity for each year, a model was developed depending on the optimal basic functions (automatically generated by the MARS model depending on the current values of life expectancies and spending on the public health system in natural terms). AcknowledgmentThis study is funded by Department of Applied Social Sciences of the Faculty of Organization and Management of the Silesian University of Technology for the year 2023 (grant number 13/020/BK_23/0081).
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12

Kapeliushnikov, R. "Labor Productivity versus Labor Compensation:Some Simple arithmetic." Voprosy Ekonomiki, no. 3 (March 20, 2014): 36–61. http://dx.doi.org/10.32609/0042-8736-2014-3-36-61.

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The paper explores the “race” between wages and labor productivity in the contemporary Russian economy. It continues the author’s previous research where the same problem was examined for the earlier period of 1997-2007. The analysis focuses on dynamics in labor productivity and labor compensation during the economic crisis of 2008-2009 and subsequent years. The author shows that conventional wisdom implying that in Russia wages persistently increase at much higher annual rates than productivity is wrong: over 1997-2012 there was no stable relationship and waves of faster wage growth alternated with waves of faster productivity growth. However in the long run productivity outpaced labor compensation. As a result in 2011-2012 real unit labor costs for Russian firms were even lower than in the mid of the 1990s or in the beginning of the 2000s.
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13

Barbashova, T. P., A. G. Maistrenko, and B. V. Prasolov. "Labor productivity and discrimination in labor law." Voprosy trudovogo prava (Labor law issues), no. 5 (May 30, 2023): 280–85. http://dx.doi.org/10.33920/pol-2-2305-04.

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14

Hamid, Niazi. "Labor productivity growth factors." Normirovanie i oplata truda v promyshlennosti (Rationing and remuneration of labor in industry), no. 5 (May 14, 2021): 38–42. http://dx.doi.org/10.33920/pro-3-2105-04.

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The modern strategy of economic development of Russia, which is aimed at restructuring the economy, requires, first of all, the search for new and improvement of existing ways of increasing labor productivity at any domestic enterprise. That is why the issues of creating effective motives and incentives for increasing labor productivity as an important tool for the development of an industrial enterprise are relevant.
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15

Jorgenson, Dale, and Khuong Vu. "Technology And Labor Productivity." Development Outreach 13, no. 1 (April 2011): 45. http://dx.doi.org/10.1596/1020-797x_13_1_45.

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16

Romer, Paul M. "Capital, Labor, and Productivity." Brookings Papers on Economic Activity. Microeconomics 1990 (1990): 337. http://dx.doi.org/10.2307/2534785.

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17

Hu, Bo A., and Liping A. Cai. "Hotel Labor Productivity Assessment." Journal of Travel & Tourism Marketing 16, no. 2-3 (July 2004): 27–38. http://dx.doi.org/10.1300/j073v16n02_03.

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18

Enshassi, Adnan, Sherif Mohamed, Peter Mayer, and Karem Abed. "Benchmarking masonry labor productivity." International Journal of Productivity and Performance Management 56, no. 4 (May 2007): 358–68. http://dx.doi.org/10.1108/17410400710745342.

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19

Thomas, H. Randolph. "Benchmarking Construction Labor Productivity." Practice Periodical on Structural Design and Construction 20, no. 4 (November 2015): 04014048. http://dx.doi.org/10.1061/(asce)sc.1943-5576.0000141.

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20

THALMAN, J., and R. FORD. "Labor and productivity measures." Respiratory Care Clinics 10, no. 2 (June 2004): 211–21. http://dx.doi.org/10.1016/j.rcc.2004.01.005.

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21

Koehn, Enno, and Gerald Brown. "International Labor Productivity Factors." Journal of Construction Engineering and Management 112, no. 2 (June 1986): 299–302. http://dx.doi.org/10.1061/(asce)0733-9364(1986)112:2(299).

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22

Thomas, H. Randolph, William F. Maloney, R. Malcolm W. Horner, Gary R. Smith, Vir K. Handa, and Steve R. Sanders. "Modeling Construction Labor Productivity." Journal of Construction Engineering and Management 116, no. 4 (December 1990): 705–26. http://dx.doi.org/10.1061/(asce)0733-9364(1990)116:4(705).

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23

Thomas, H. Randolph, Steve R. Sanders, and Suha Bilal. "Comparison of Labor Productivity." Journal of Construction Engineering and Management 118, no. 4 (December 1992): 635–50. http://dx.doi.org/10.1061/(asce)0733-9364(1992)118:4(635).

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24

Michl, Thomas R. "Capital and Labor Productivity." Review of Radical Political Economics 24, no. 2 (June 1992): 45–50. http://dx.doi.org/10.1177/048661349202400206.

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25

DVORNYK, Inna. "LABOR PRODUCTIVITY IN AGRICULTURE." Ukrainian Journal of Applied Economics 6, no. 2 (June 30, 2021): 245–51. http://dx.doi.org/10.36887/2415-8453-2021-2-30.

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The essence of labor productivity is substantiated in the article. It is determined that it is the production of a certain amount of products (or work performed of the established quality) per unit of working time. Labor productivity is one of the main indicators that determines the development of the industry, enterprise. The analysis of agricultural products showed that in general there is a positive trend, in particular crop production. Livestock production is characterized by a decrease. Enterprises produce the most agricultural products - 66% (11.6% of farms), respectively households – 34%. Analysis of the dynamics of labor productivity per employee in agriculture of Ukraine showed positive results. The growth rate in the industry over the past 5 years is 48.81%, including in crop production - 44.61%, in animal husbandry - 61.78%. However, the achieved level does not meet modern requirements. Factors of labor productivity growth are singled out: organizational-economic, technical-economic, socio-economic, natural-climatic. Correlation-regression analysis was used to study the influence of individual factors on labor productivity. It is established that the following have the greatest direct impact: the average engine power of the tractor, the cost of fixed assets, the average monthly salary. The following have the opposite effect: population, number of employees in the agriculture. A positive financial result in agriculture does not increase labor productivity. Investments, wage growth in the agricultural sector, predictability of state regulatory policy, improved land relations, mechanisms of state support for farmers and improving the efficiency of public administration will help increase labor productivity in agriculture. Keywords: labor productivity, agriculture, wages, production volume, investments.
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26

Polopolus, Leo C. "Labor productivity and agribusiness." Agribusiness 2, no. 3 (1986): 269–77. http://dx.doi.org/10.1002/1520-6297(198623)2:3<269::aid-agr2720020302>3.0.co;2-#.

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27

Pletnev, Dmitri A. "Digitalization and Labor Productivity." Bulletin of Chelyabinsk State University 482, no. 12 (February 14, 2024): 5–7. http://dx.doi.org/10.47475/1994-2796-2023-482-12-5-7.

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28

Alabdullah, Saad Farhan Ibrahim, and Lina Shaher Abu-Al Sondos. "Key Factors Affecting the Efficiency and Achievement of Labor Productivity in Some Public Construction Projects in Jordan." European Journal of Business and Management Research 8, no. 3 (June 7, 2023): 233–38. http://dx.doi.org/10.24018/ejbmr.2023.8.3.1922.

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Over some years, many public projects in Jordan have experienced delays due to an inappropriate initial work management plan. The performance of labor in construction projects is affected by many factors and has a direct interrelationship with the triple constraint of the project time, cost, and scope. This study aims to analyze the factors affecting labor productivity in some public projects in Jordan, labors achievements and motivation. To achieve the purpose of the study a questionnaire was developed to observe the impact of critical factors on labor productivity and the traffic intersections: Al-Ersal /Al-Hurryah intersection and Marj Al-Hamam intersection project was selected to be the study sample. The data from the questionnaire were statistically analyzed using the (SPSS) program, to analyze the data collected from the survey, this study used the method of Relative Importance Index (RII) to measure the impact of the critical factors affecting labor productivity. From the analysis of 32 Factors that were identified from literature review affecting the labor productivity, it is concluded that the top ten factors affecting labor productivity in The Traffic Intersections in Amman: Al-Ersal /Al-Hurryah Intersection and Marj Al-Hamam Intersection Project are as follows: (1) Payment delays to labor, (2) Material Shortage, (3) Tools and equipment shortage, and Low wages in the same rank, (4) Allocate tasks to labors fairly and according to specialization, (5) Job Security, (6) Deficiency of motivation, (7) Labor absenteeism, (8) Incompetence of site supervisor, (9) Poor communication of supervisor with labors, (10) Lack of labor skilled and experience.
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A. Kamalova, Alina, and Wilfred Isioma Ukpere. "Problems of statistical study of labor productivity in construction." Problems and Perspectives in Management 14, no. 1 (April 11, 2016): 235–39. http://dx.doi.org/10.21511/ppm.14(1-1).2016.12.

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The article focuses on the problems of statistical measurement of labor productivity in construction, as recent years saw the most significant changes in the methodology of calculating construction products. The study examined the factors affecting the dynamics of labor productivity in construction, calculated by the volume of work at estimate piece that is at the index known as “average output per worker” in the practice of planning and statistics. Labor productivity is a complex qualitative index, which is influenced by numerous factors. Therefore, the most effective method for studying the dynamics of labor productivity is the use of the index method. The index method seems to be widely used in statistical research of labor productivity in construction
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Baeza and González. "Labor Productivity and Marxist Theory of Labor Value." World Review of Political Economy 11, no. 3 (2020): 377. http://dx.doi.org/10.13169/worlrevipoliecon.11.3.0377.

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31

Breit, Emily, Xuehu (Jason) Song, Li Sun, and Joseph Zhang. "CEO power and labor productivity." Accounting Research Journal 32, no. 2 (July 1, 2019): 148–65. http://dx.doi.org/10.1108/arj-05-2016-0056.

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Purpose This paper aims to examine how Chief Executive Officer (CEO) power affects firm-level labor productivity. Design/methodology/approach The authors rely on regression analysis to examine the relation between CEO power and labor productivity. Findings Following prior research (i.e. the sequential rank order tournament theory), the authors predict that powerful CEOs lead to high labor productivity. They find a significant and positive relationship between CEO power and labor productivity. They further decompose labor productivity into labor efficiency and labor cost components and find a positive (negative) relationship between CEO power and labor efficiency (cost) component, suggesting that more powerful CEOs better manage labor efficiency and control labor cost. The results are also robust to various additional tests. Originality/value This study contributes to two streams of research: the CEO power literature in finance and the labor productivity and cost literature in accounting. To the best of the authors’ knowledge, it is the first study that performs a direct empirical test on the relation between CEO power and labor productivity.
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Mose, Jared Isaboke. "Drivers of Labour Productivity in Flower Farms in Naivasha, Kenya." Sustainable Agriculture Research 6, no. 4 (October 8, 2017): 117. http://dx.doi.org/10.5539/sar.v6n4p117.

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Although Kenya is the most successful producer and exporter of fresh produce and flowers in sub-Saharan Africa, other countries both in Africa and elsewhere, offer strong competition that could erode export market share in future. Increased labor productivity is crucial for Kenya’s competitiveness. This study aimed at examining the key drivers of labour productivity in flower farms in Naivasha, Kenya. Descriptive survey design was employed and stratified proportionate random sampling technique used to select 381 respondents from who data was collected using a questionnaire. A log-linearized Cobb-Douglas model was used examine determinants of labour productivity. The results showed that workers’ participation in Labor unions, Information & Communication Technology and workers’ skills acquired through training were the major factors that determined labour productivity by 35.4 percent, 19 percent and 14.7 percent respectively. While worker’s wage increase and tools used by a worker influenced labour productivity by 9 percent and 11.4 percent respectively. Worker’s level of education and worker’s experience also increased labour productivity by 5.1 percent and 4 percent respectively. The study recommends that; the Kenyan government should give special attention to education to produce skilled and innovative workers. Flower Farms should invest more in training of workers to acquire relevant skills, acquisition of appropriate tools; improve ICT infrastructure and support labor union in the flower farms.
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33

Vinh, Nguyen Tan. "The Impact of Foreign Direct Investment, Human Capital on Labour Productivity in Vietnam." International Journal of Economics and Finance 11, no. 5 (April 15, 2019): 97. http://dx.doi.org/10.5539/ijef.v11n5p97.

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Vietnam is a country which has an attractive level of attracting foreign direct investment (Hereafter FDI) in the region with many preferential policies for investors. FDI attraction aims to help economic growth as well as increase the country&#39;s labour productivity. Therefore, the author conducted research to the impact of FDI and human capital on labor productivity of Vietnam. With data analysis techniques using ARDL model with data collected from 1990 to 2017, research result shows that FDI has a positive impact on labor productivity in short term and long term. The factor of university qualification (human capital) only has a positive impact on labor productivity in the long term.
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34

Walheer, Barnabé. "Labor productivity and technology heterogeneity." Journal of Macroeconomics 68 (June 2021): 103290. http://dx.doi.org/10.1016/j.jmacro.2021.103290.

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35

Obuschenko, T. N. "LABOR PRODUCTIVITY OF REMOTE WORKERS." Вестник Алтайской академии экономики и права 2, no. 10 2021 (2021): 160–66. http://dx.doi.org/10.17513/vaael.1882.

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36

Valenzuela Feijóo, José. "Labor productivity and its determinants." Gestión y Estrategia 23 (January 1, 2003): 21–35. http://dx.doi.org/10.24275/uam/azc/dcsh/gye/2003n23/valenzuela.

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37

Kapeliushnikov, R. "Productivity and Cost of Labor." Problems of Economic Transition 53, no. 1 (May 1, 2010): 17–40. http://dx.doi.org/10.2753/pet1061-1991530102.

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38

Machek, Martin. "Job security and labor productivity:." European Journal of Management Issues 27, no. 3-4 (December 25, 2019): 82–89. http://dx.doi.org/10.15421/191909.

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Purpose – to investigate the relationship between job security and labor productivity among 45,506 companies from the Czech Republic, Slovakia, Croatia, Slovenia, and Latvia. Design/Method/Approach. This article uses linear regression analysis based on data from the period of 2013-2017. Findings. The study indicates an inverse U-shaped relationship between employment volatility, as measured by the coefficient of variation, and labor productivity. Labor productivity increases along with employment fluctuation up to a certain point; however, when employees feel insecure, their labor productivity deteriorates. Surprisingly, for most companies, the relationship between employment fluctuation and labor productivity remains positive. Labor productivity gets affected positively by the security feeling rather than by guaranteeing the job position. Originality/Value. The results are consistent within the subsamples of the five individual countries in the sample and robust to two alternative measures of fluctuation, the mean absolute deviation, and the studentized range. Paper type – empirical.
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39

Subaeva, Asiya K., Marat M. Nizamutdinov, Leysan M. Mavlieva, and Marat N. Kalimullin. "Labor productivity in digital agriculture." BIO Web of Conferences 17 (2020): 00226. http://dx.doi.org/10.1051/bioconf/20201700226.

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The article provides information on the labor productivity level in the agricultural sector, reveals aspects of innovations in production, analyzes the education level in human resources of rural workers, reveals the prospects for digitalization of the agricultural sector.
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Marchante, Andrés J., and Bienvenido Ortega. "Human Capital and Labor Productivity." Cornell Hospitality Quarterly 53, no. 1 (December 19, 2011): 20–30. http://dx.doi.org/10.1177/1938965511427698.

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41

Lee, Elena. "Personnel Management: Affecting Labor Productivity." Spatial Economics 3 (2008): 63–85. http://dx.doi.org/10.14530/se.2008.3.063-085.

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42

Castellanos-Sosa, Francisco A. "Labor Productivity Convergence in Mexico." International Journal of Political Economy 49, no. 3 (August 26, 2020): 243–60. http://dx.doi.org/10.1080/08911916.2020.1824733.

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43

Bjuggren, Carl Magnus. "Employment protection and labor productivity." Journal of Public Economics 157 (January 2018): 138–57. http://dx.doi.org/10.1016/j.jpubeco.2017.11.007.

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44

Czumanski, T., and H. Lšdding. "Integral Analysis of Labor Productivity." Procedia CIRP 3 (2012): 55–60. http://dx.doi.org/10.1016/j.procir.2012.07.011.

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45

Konyukh, V. L. "Mine robotics and labor productivity." Soviet Mining Science 26, no. 6 (November 1990): 532–38. http://dx.doi.org/10.1007/bf02499451.

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46

Peri, Giovanni. "Immigrants, Productivity, and Labor Markets." Journal of Economic Perspectives 30, no. 4 (November 1, 2016): 3–30. http://dx.doi.org/10.1257/jep.30.4.3.

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Immigration has been a steady force acting on population and employment within countries throughout human history. Focusing on the last four decades, we show that the mix of immigrants to rich countries has been, overall, rather balanced between college and non-college educated. The growth of immigration has been driven by immigrants from nonrich countries. The economic impact of immigration on receiving economies needs to be understood by analyzing the specific skills brought by immigrants. The complementarity and substitutability between immigrants and natives in employment, and the response of receiving economies in terms of specialization and technological choices, are important when considering the general equilibrium effects of immigration. In the United States, a balanced composition of immigrants between college and noncollege educated, together with the adjustment of demand and technology, imply that general equilibrium effects on relative and absolute wages have been small.
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Delmas, Magali, and Sanja Pekovic. "Environmental Standards and Labor Productivity." Academy of Management Proceedings 2012, no. 1 (July 2012): 15248. http://dx.doi.org/10.5465/ambpp.2012.15248abstract.

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Smirnova, Elena, and Marina Postnova. "INTEGRAL ASSESSMENT OF LABOR PRODUCTIVITY." Vestnik of Kazan State Agrarian University 15, no. 1 (May 14, 2020): 123–29. http://dx.doi.org/10.12737/2073-0462-2020-123-129.

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To assess the level and dynamics of labor productivity, quite a lot of different indicators are used, which complicates the process of analysis and monitoring. Often they have multidirectional trends and meanings, which makes it difficult to formulate recommendations for increasing labor productivity. To smooth out these differences, it is necessary to conduct an integrated assessment of labor efficiency. The purpose of our study is to evaluate the productivity of agricultural labor in the municipal regions of Ulyanovsk region on the basis of an integral indicator to identify areas of leaders and outsiders. The evaluation was carried out using two methods based on the calculation of various indices. The value of the integral indicator of labor productivity, which was determined taking into account the indices of productivity, intensity and productivity, in the municipal districts of Ulyanovsk region varied from -0.01 in the Baryshsky District (negative value) to 3.5 in Ulyanovsk district. According to the results of ranking and differentiation according to integral assessment, the group with high and average labor productivity (IPT ≥ 0.76) included six regions, or only 30% of the study population. In half of the districts, its low level was noted (IPT 0.1 ... 0.76), labor is inefficient in four districts of the region. The leading regions in labor productivity are Tsilninsky and Ulyanovskiy (IPT ≥1.5), outsiders are Baryshskiy, Inzenskiy and Starokulatkinskiy (IPT ≤ 0.1). An integrated assessment of the level of labor productivity can be used to develop recommendations for its increase for areas lagging behind industry average indicators and leading regions in their development
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Sanders, Steve R., and H. Randolph Thomas. "Factors Affecting Masonry‐Labor Productivity." Journal of Construction Engineering and Management 117, no. 4 (December 1991): 626–44. http://dx.doi.org/10.1061/(asce)0733-9364(1991)117:4(626).

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FEASEL, EDWARD M. "EXPLAINING INDUSTRY LABOR PRODUCTIVITY MOVEMENTS." Economic Inquiry 36, no. 4 (October 1998): 654–69. http://dx.doi.org/10.1111/j.1465-7295.1998.tb01743.x.

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