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This research presents a novel microlevel (i.e., project-level) construction productivity framework aimed at measuring and benchmarking productivity consistently within and between projects, work packages, and activities. Using a design science research approach, the framework was rigorously developed with data collected from UK-based construction projects and refined through several cycles of implementation and industry engagement. The framework is useful in providing new insights into project performance, helping understand process variability, setting benchmarks, and conducting data analytics for improved decision making. This framework can be used for industrywide measurement both within and across subsectors of construction in the UK and internationally. [ABSTRACT FROM AUTHOR]

Productivity assessment plays a key role in successful earthwork projects and is primarily achieved by monitoring key construction equipment such as excavators and dump trucks. Vision-based methods are widely adopted to analyze the productivity of construction equipment in earthwork projects. These methods are inexpensive and easy to implement and maintain. However, previous studies on vision-based productivity analysis of earthmoving equipment have predominantly demonstrated its effectiveness under favorable conditions characterized by stable lighting, areas devoid of shadows, and high-visibility environments free from significant occlusion by other objects or terrain. There is a significant illumination difference and limited visibility under harsh low-visibility conditions at earthwork construction sites, which makes it difficult to achieve reliable identification accuracy using these already developed methods. To address this problem, this study proposes an automatic vision-based dump truck productivity measurement method based on a deep learning illumination enhancement algorithm combined with transfer learning for low-visibility, harsh conditions at earthwork construction sites. This method uses an internet of things (IoT) system equipped with a camera to capture the image and a deep learning illumination enhancement algorithm, trainable deep hybrid network (TDHN), to enhance the image quality under low-light conditions at earthwork sites. Then, a deep convolutional neural network image recognition algorithm, ResNet50, was combined with a transfer learning technique to extract information from the image. Through the IoT, this processed information is sent to the earthwork platform to perform productivity analysis and make timely decisions regarding equipment allocation schemes. To validate the effectiveness of the proposed methodology, it was implemented in a real-time earthwork project. This study results show that image recognition accuracy of 99.6%, 95.67%, and 94.77% under normal lighting, low lighting, and extremely low lighting conditions, respectively. The dump truck recognition accuracy increased by 1.10%, 3.62%, and 21.19%, leading to a significant improvement in productivity measurement of 1.08%, 3.54%, and 20.71% for the above-mentioned lighting conditions, respectively. [ABSTRACT FROM AUTHOR]

Estimation of the actual size of an object from its digital image can help to automate processes and increase productivity. One example of object-size measurement is evaluation of the pavement condition by estimating crack length. As input images taken by different cameras are often inconsistent, a robust method of automatically measuring objects is necessary. Here, the crack size has been estimated by combining the proposed 'asphalt crack length extractor' (ACLE) method and an object-size conversion method called 'pixel to actual size conversion engine' (PACE). In ACLE, image segmentation is performed to detect the object and extract its pixel-wise length from the image. In PACE, the pixel-wise measurements are converted to metric units. Several experiments were conducted to evaluate the proposed methods. The combined PACE/ACLE module showed an average error of less than 3%. Thus, it is proposed for use in crack length determination and condition assessment of asphalt pavements. [ABSTRACT FROM AUTHOR]

Despite its significance, net primary productivity is rarely used as an indicator of climate change. The purpose of this study was to assess the spatiotemporal dynamics of vegetation net primary productivity and its response to climate variability in the Welmel watershed, southeastern Ethiopia. The investigation utilized data from the Moderate Resolution Imaging Spectroradiometer, and the Climate Hazards Group Infrared Precipitation with Stations accessed through the Google Earth Engine cloud computing platform. To evaluate the trend and response of net primary productivity to climatic factors, the Mann-Kendall and Theil Sen's tests, the Pearson correlation coefficient, and stability analysis through the coefficient of variation of net primary productivity were utilized. The analysis of the temporal trend of net primary productivity revealed that the entire watershed, forest, wood, and cultivated land areas exhibited decreasing trends with net primary productivity values of -0.681, -4.361, -1.41, and − 3.25 g C m− 2/year, respectively. On the other hand, shrubs and grazing land displayed increasing trends of 1.15 and 2.04 g C m− 2/year, respectively. The wood and shrubland trends were statistically significant (p < 0.05). In the spatial analysis, an area of 64.6% showed a decreasing trend, whereas 33.78% displayed an increasing trend in net primary productivity values. The areas with stable and unstable variations in net primary productivity accounted for 26.47% and 8.02%, respectively. The net primary productivity of the land cover types and entire watershed were positively correlated with rainfall, however, only forests and woodlands were statistically significantly correlated (p < 0.05). The net primary productivity and land surface temperature were negatively correlated, except for forests and cultivated land, which were positively correlated. The results of this study provide essential information for managing ecosystems, supporting agricultural practices, and enhancing community resilience in a changing climate. [ABSTRACT FROM AUTHOR]

The article discusses the recent outperformance of the US economy in terms of productivity compared to other advanced economies (AEs). It highlights factors such as high rates of investment, R&D, a favorable regulatory environment, and dominance in the tech sector contributing to the US's structural outperformance. The text also mentions potential challenges such as slow technological transfer and the impact of government policies on productivity. Overall, the US is expected to continue to outperform most AEs in terms of per capita growth, but the sustainability of this productivity growth remains uncertain. [Extracted from the article]

Hops are grown mainly for the brewing market due to the rich chemical composition that gives beer aroma and bitterness. Brazil is one of the largest beer producers and consumers in the world and one of the largest hop importers. There is growing demand and interest in producing hops for domestic supply; however, as this crop originates from a temperate climate and the Northern Hemisphere, it is important to carry out research that describes the development of hops in a tropical climate to provide information on its cultivation in Brazil, as well as to determine its behavior in organic cultivation. A randomized block design was adopted, the treatments consisted of two cropping systems, conventional and organic, for Hallertau Mittelfrueh variety cultivation, with four blocks and three plants per plot. Gas exchange analyzes of plants under both cultivation systems were performed to obtain measurements of A, gs, Ci, E, WUE and A/Ci, morphometric and yield analyzes were also carried out. In comparison with the plants of the organic system, the plants of the conventional cultivation had greater photosynthetic efficiency; however, the practices adopted in the organic cultivation system provided the plants with greater productive capacity. [ABSTRACT FROM AUTHOR]

Intangible capital is a key input to production that is distinct from tangible capital. Most forms of tangible and intangible capital have observable, pecuniary values. Their complement is non‐marketed capital. This paper studies non‐marketed capital from the points of view of an investor contemplating investing in a project and of a manager running the project. At the point of investment, an apparent positive net present value is realized through the marshalling of non‐marketed capital. When capital is viewed all‐inclusively, a full accounting reveals that (1) optimally timing investment serves to maximize the value of the non‐marketed capital eventually associated with an investment project, (2) the "full" net present value at investment is zero, (3) the internal rate of return is identically equal to the external interest rate, (4) Tobin's q is identically equal to one, and (5) marginal analysis is inapplicable to non‐marketed capital and thus to all capital. [ABSTRACT FROM AUTHOR]

While the product and labour market imperfections reveal efficiency losses, they may influence technology adoption and its change, raising the endogeneity issue of productivity and efficiency estimates. Using a two-step approach, this work offers the endogeneity-corrected stochastic frontier for such a contemporaneous relation and accounts for efficiency and productivity losses due to market imperfections. A modified frontier function, defined as the residue per capital unit, has been drawn from the Cobb–Douglas function to estimate the terms containing the product and labour market imperfections along with other factors capturing the levels of technology, scale and technical efficiency. First, a standard frontier panel model estimates technology and technical efficiency terms with a proxy function in polynomials of market imperfection terms used for the contemporaneous relation, and then a GMM approach applies to the residue to estimate the parameters containing market imperfections. The estimated results using the three-digit industries across 17 major Indian states for 2008–2016 reveal a strong presence of product and labour market imperfections and associated efficiency losses. The efficiency in the product market has been lower and has further deteriorated in most industries, but not in the labour market. [ABSTRACT FROM AUTHOR]

Gelatinous filter feeders (e.g., salps, doliolids, and pyrosomes) have high filtration rates and can feed at predator:prey size ratios exceeding 10,000:1, yet are seldom included in ecosystem or climate models. We investigated foodweb and trophic dynamics in the presence and absence of salp blooms using traditional productivity and grazing measurements combined with compound-specific isotopic analysis of amino acids estimation of trophic position during Lagrangian framework experiments in the Southern Ocean. Trophic positions of salps ranging 10–132 mm in size were 2.2 ± 0.3 (mean ± std) compared to 2.6 ± 0.4 for smaller (mostly crustacean) mesozooplankton. The mostly herbivorous salp trophic position was maintained despite biomass dominance of ~10-µm-sized primary producers. We show that potential energy flux to >10-cm organisms increases by approximately an order of magnitude when salps are abundant, even without substantial alteration to primary production. Comparison to a wider dataset from other marine regions shows that alterations to herbivore communities are a better predictor of ecosystem transfer efficiency than primary-producer dynamics. These results suggest that diverse consumer communities and intraguild predation complicate climate change predictions (e.g., trophic amplification) based on linear food chains. These compensatory foodweb dynamics should be included in models that forecast marine ecosystem responses to warming and reduced nutrient supply. Food-web and isotope-based trophic analyses suggest that blooms of salps (gelatinous grazers) can increase ecosystem efficiency and energy transfer to large organisms. These compensatory food-web dynamics may offset predicted trophic amplification. [ABSTRACT FROM AUTHOR]

Activity-level productivity measurement often overlooks losses due to poor construction flows—that is, the flows of workers, materials, and equipment. Using data from 138 locations and 33 crews, correlation and regression analyses were conducted on several flow metrics. The results showed that excess work-in-progress time, representing handoffs among crews, and work discontinuities, representing stoppages between locations, had the most significant association with productivity. These findings led to the development of a novel framework for measuring activity-level construction productivity. In this framework, productivity is decomposed into efficiency (measured through work sampling) and effectiveness (measured as increased output). We applied our framework to a building construction project featuring four structural work crews operating across multiple levels. The results indicate that productivity losses due to crew handoffs and work discontinuities decrease as work becomes more repetitive. Additionally, inefficiencies or idling occur when moving equipment is unavailable, whereas ineffectiveness occurs with high rework. Our framework enables the identification of various sources of productivity loss. It also helps understand that the direct work rate is just one component of overall productivity. [ABSTRACT FROM AUTHOR]

This study estimates the relative contribution of different factors to the wide variation in agricultural economic water productivity (EWP) across Colorado River Basin counties. It updates EWP measures for Basin counties using more detailed, localized data for the Colorado River mainstem. Using the Schwarz Bayesian Information Criterion for variable selection, regression analysis and productivity accounting methods identified factors contributing to EWP differences. The EWP was USD 1033 (USD 2023)/acre foot (af) for Lower Basin Counties on the U.S.–Mexico Border, USD 729 (USD 2023)/af for other Lower Basin Counties, and USD 168 (USD 2023)/af for Upper Basin Counties. Adoption rates for improved irrigation technologies showed little inter-county variation and so did not have a statistically significant impact on EWP. Counties with the lowest EWP consumed 25% of the Basin's agricultural water (>2.3 million af) to generate 3% of the Basin's crop revenue. Low populations/remoteness and more irrigated acreage per farm were negatively associated with EWP. Warmer winter temperatures and greater July humidity were positively associated with EWP. When controlling for other factors, being on the Border increased a county's EWP by USD 570 (2023 USD)/af. Border Counties have greater access to labor from Mexico, enabling greater production of high-value, labor-intensive specialty crops. [ABSTRACT FROM AUTHOR]

We use China's growth experience as a laboratory to study how reductions in administrative and regulatory entry barriers contribute to growth. We develop a model of endogenous productivity and market structure with heterogeneous firms and frictional entry and calibrate it to Chinese manufacturing firms. We show that the reduction of entry barriers brings about 1.05 percentage points of productivity growth over the 1990–2004 period, accounting for 18.3% of the productivity growth in the 2004–7 period. A decomposition exercise shows that entry mainly affects growth through promoting a more competitive market structure, which more than offsets the negative Schumpeterian effect. [ABSTRACT FROM AUTHOR]

The research delt with the effect of labour out-migration on output per hectare and efficiency of wheat and teff producers in Kembata-Tembaro and Hadiya zones of Ethiopia based on primary data gathered from 415 random sample of rural households. The multinomial endogenous switching model was used as an analytical model. According to the stochastic frontier model, the mean efficiency of wheat and teff are 82.98 and 66.43 per cent, respectively. According to the econometric results, rural–urban and international migration reduces wheat productivity by 110.94 and 179.11 kg, respectively. The average treatment effect on treated (ATT) also revealed that participation in international migration reduces Teff producers' technical efficiency by 5.51 per cent. However, teff productivity is reduced by 382.94 and 747.49 kg due to rural urban and international migration, respectively. The lost labour channel of the modern theory of migration is maintained by the result of the study. So as to minimise the negative impact of out-migration in the study area, policymakers must focus more on promoting access to credit, irrigation, land, off-farm employment and public services for rural households. [ABSTRACT FROM AUTHOR]

In the study of urban development, it is very important to evaluate the influence of production factors reasonably and efficiently for the region to achieve efficient development. The principal aim of this investigation is to amalgamate the conventional measurement model characterized by robust interpretability with the non-parametric model characterized by limited interpretability, thereby enhancing the precision of research outcomes. Towards this objective, the study employs an optimized directional distance function integrated with a global Malmquist–Luenberger index to formulate a comprehensive total factor productivity measurement framework. In elucidating the homogeneous attributes of regions, departing from prior methodologies reliant on manual or direct algorithmic partitioning, this paper employs the K-means clustering algorithm for index discernment, abstracting the concept of K-means clustering centroids to encapsulate regional homogeneity, thereby delineating results through the visualization of regional development potential maps and the evolution of centroid-based clustering trend maps. The findings of the investigation illuminate common patterns of change across disparate regions, proposing a strategy for leveraging regional resource endowments towards a cohesive framework, thereby transcending constraints imposed by production efficiency limitations. Amidst the backdrop of the COVID-19 pandemic, this study draws upon provincial-level data spanning from 2000 to 2018 in China. The conclusive analytical outcomes underscore the pivotal role of energy factors in regional development efficiency, particularly within high-potential development regions, followed by the capital and labor factors. Concurrently, the study discerns a discernible hierarchical pattern among areas of development potential, which exhibits correlation with factor mobility dynamics. [ABSTRACT FROM AUTHOR]

This article explores the relationships between faculty library use, their perceptions of the importance of library resources, and its impact on their research productivity at a public research university. The authors used a self-reported faculty survey and publication records from a faculty activity reporting system to answer this question. Findings showed that faculty’s perceptions of the library resource for their research had no relationships with faculty research productivity, whereas a positive correlation was found between the frequency of use of online journals and databases, and faculty research productivity. Qualitative findings revealed that faculty viewed the library as providing and purchasing the needed library resources, and that they valued the librarians and library services as essential to their teaching and research. [ABSTRACT FROM AUTHOR]

Purpose: This paper aims to discuss the firm productivity premium for servitized firms. It discusses servitization across the product value chain and estimates the effects of the range and extent of servitization on productivity premium in manufacturing firms. Design/methodology/approach: This paper develops a conceptual framework and tests the hypotheses on the effects of servitization on productivity premium using linear regression models with a sample of 20,837 Russian manufacturing firms gathered from the Ruslana Bureau van Dijk database and the Russian customs service. Findings: Servitized firms exhibit higher total factor productivity and labor productivity. The labor productivity premium increases with the number of services offered. However, the impact of services on productivity varies along the product value chain: postmanufacturing and postsales services enhance productivity premium, while manufacturing and back-office services diminish them. The effect of establishment services remains ambiguous. Practical implications: This paper offers an analytical framework for firms to assess their servitization strategies. These strategies should be gradual, focused on enhancing firm efficiency rather than being an end goal. Firms should initiate the process by introducing services at the postproduction and postsales stages of the product creation chain to achieve productivity premium. Originality/value: The paper extends the evidence on firm-level productivity drivers and contributes to the servitization theory. A servitization strategy should be portfolio-based, considering both the potential gains and losses in productivity resulting from the implementation of specific services. [ABSTRACT FROM AUTHOR]

This study measures productivity of private hospitals in Tanzania based on the hospitals size. Specifically, the study aims at evaluating technological change and efficiency change based on hospitals' size. The study also focuses on exploring factors deriving productivity in relation to hospitals size. The study employs Malmquist productivity index (MPI) to measure and decompose productivity growth into efficiency change and technological change in relations to the hospitals size. The study used secondary data extracted from annual report of 34 private hospitals for the period ranging from 20018/19 to 2021/22. Results show that small (0=beds=150) and large hospitals (250=beds) were experiencing productivity progress (improvement) while medium hospitals (151=beds=250) were experiencing regress over the study period. Analysis indicates that progress or regress of the hospitals was largely influenced by technical efficiency change which implies embracing or failure to embrace advanced technology, quality healthcare services, best management practices as well as investing in new operating methodologies. Large hospitals experienced deterioration in the productivity growth in year one as well as year two followed by a slight improvement in the subsequent two years. This study contributes quite relevant information for hospitals administrators and hospitals' owners as well as policy makers to make informed decision in the course of improving performance of private hospitals in Tanzania. The study also provides further guides on the efficiency utilization of the hospitals assets since the analysis is based on the size and what determine hospitals' productivity. [ABSTRACT FROM AUTHOR]

Generative AI has the potential to significantly improve the medium-term growth outlook for the economy by automating tasks and increasing efficiency. The impact of GenAI on medium-term growth could lead to a rise in GDP by 1.8%-4% in the US by 2032, depending on the speed of adoption. However, the full benefits of GenAI will take time to unlock, as developments in human capital and infrastructure are needed. While higher productivity is expected, some workers may be displaced and face challenges finding alternative employment. GenAI is likely to be a disinflationary force in the medium term, as higher productivity may not be immediately matched by higher wage growth. The impact of GenAI adoption on productivity could be significant, with a potential rise of over 10% in workforce productivity. However, there may be some displacement of workers, particularly in computer and mathematical roles and office and administrative roles. The adoption of GenAI is expected to benefit wealthier countries more, as they have higher levels of human capital and a conducive regulatory environment. The impact of GenAI on inflation, interest rates, and asset prices is uncertain, but it could have both disinflationary and inflationary effects in the medium and near term. The implications for real assets, such as the industrial property sector, may be significant. Overall, the ripple effects of GenAI on the economy are difficult to predict but are likely to be profound. [Extracted from the article]

This paper assesses the robustness of the "natalist bias" of pollution control in de la Croix and Gosseries (J Environ Econ Manage 63:271–287, 2012), according to which taxing emissions encourage agents to shift from production to procreation, further deteriorating the environment and gradually impoverishing the next generations. We relax the assumptions that human capital does not depend on environmental quality and that society does not allocate resources to pollution control. Using a similar Overlapping Generations (OLG) growth model, our findings indicate that taxation does not necessarily encourage agents to permanently shift away from production because living under better environmental conditions enhances productivity through human capital formation. As the government increases the emissions price, agents reduce consumption and education spending, hurting output in the short term. However, in the long run, the reduction in emissions that follows taxation more than compensates for the initial adverse effects, provided that the sensitivity of human capital accumulation to environmental degradation is strong enough. Furthermore, as we increase the coefficient capturing such pollution externality, a Neimark–Sacker bifurcation occurs, making the system compatible with persistent endogenous fluctuations. [ABSTRACT FROM AUTHOR]

We examine the evolution of productivity and markups in US food and beverage manufacturing from 1959 through 2018. We account for non‐Hicks‐neutral (labour‐augmenting) productivity changes and compare markups with those in general manufacturing using the same dataset and model. We also compare our results with those of the increasingly popular De Loecker and Warzynski (2012, American Economic Review, 102, 2437) method, which does not account for non‐Hicks‐neutral productivity growth. Empirical results show that productivity growth in the food and beverage sector has been relatively slow and driven with equal intensity by Hicks‐neutral and labour‐augmenting productivity gains. General manufacturing shows higher productivity growth that is mostly labour‐augmenting, with markups comparable to those of food manufacturing. We find that accounting for labour‐augmenting productivity produces more moderate markup estimates than the De Loecker and Warzynski (2012) method. We also find no evidence of markups rising in either food manufacturing or general manufacturing in the last 20 years, in contrast to much of the recent economic literature. [ABSTRACT FROM AUTHOR]

Using Danish matched employer–employee data, I compare the relative pay of men and women to their relative productivity as measured by production function estimation. I find that the gender "productivity gap" is 8%, implying that almost two thirds of the residual gender wage gap is due to productivity differences between men and women. Motherhood plays an important role, yet it also reveals a puzzle: The pay gap for mothers is entirely explained by productivity, whereas the gap for non-mothers is not. In addition, the decoupling of pay and productivity for women without children happens during their prime-child bearing years. These estimates are robust to a variety of specifications for the impact of observables on productivity, and robust to accounting for endogenous sorting of women into less productive firms using a control-function approach. This paper also provides estimates of the productivity gap across industries and occupations, finding the same general patterns for mothers compared to women without children within these subgroups. [ABSTRACT FROM AUTHOR]

Assessing the contribution of intangible investment to growth is a challenging and complex task for any country. However, it has become increasingly difficult to determine both the exact magnitude of economic performance and its composition in the case of the Irish economy. This is mainly due to the impact of certain distortionary transactions by a select number of multinationals operating in the Irish jurisdiction. In this paper, we address this issue by assessing, in a detailed manner, the contribution of intangible and tangible assets to the Irish growth story. We control for distortions in the official investment data series while also incorporating intangible assets that are not currently included in the National Accounts. Our results show that the observed unprecedented increase in the official intangible investment has a relatively minor contribution to the actual Irish labor productivity growth. Once the distortions are filtered out, Irish labor productivity growth is driven by tangible capital. More interestingly, non‐national accounts intangible capital has a sizeable pro‐cyclical impact on labor productivity growth. [ABSTRACT FROM AUTHOR]

Amid the discourse on foreign influence investigations in research, this study examines the impact of NIH-initiated investigations starting in 2018 on U.S. scientists' productivity, focusing on those collaborating with Chinese peers. Using publication data from 2010 to 2021, we analyze over 113,000 scientists and find that investigations coincide with reduced productivity for those with China collaborations compared to those with other international collaborators, especially when accounting for publication impact. The decline is particularly pronounced in fields that received greater preinvestigation NIH funding and engaged more in U.S.-China collaborations. Indications of scientist migration and broader scientific progress implications also emerge. We also offer insights into the underlying mechanisms via qualitative interviews. [ABSTRACT FROM AUTHOR]

The given document is an editorial from the journal Accounting History. It announces the May issue of the journal and expresses gratitude to contributors and reviewers. The issue includes articles on various topics, such as the commercialization of the university system, the development of aptitude testing in accounting, the transfer of accounting knowledge between Italy and Romania, the spread of ideas in Britain after WWI, and the role of accounting in supporting American slavery. The articles highlight the flexibility of accounting in representing both positive and negative aspects of historical events. [Extracted from the article]

This article shows that contemporaneous and lagged air pollution negatively affects the likelihood of German individual investors to log in and trade in their brokerage accounts, using intraday data and controlling for investor-, weather-, traffic-, and market-specific factors. A 1 SD increase in air pollution leads to a 1.3 percent reduction in the probability of logging in, which is larger than the response to a 1 SD increase in sunshine. We argue that changes in air pollution affect productivity in cognitively demanding tasks, such as trading. Our results are robust to macroeconomic productivity shocks, nonlinearities, or measurement error. [ABSTRACT FROM AUTHOR]

Purpose: The paper develops a model for enhancing R&D productivity for Indian public funded laboratories. The paper utilizes the productivity data of five Council of Scientific and Industrial Research (CSIR) laboratories for analysis and to form the constructs of the model. Design/methodology/approach: The weighted average method was employed for analyzing the rankings of survey respondents pertaining to the significant measures enhancing R&D involvement of researchers and significant non-R&D jobs. The authors have proposed a model of productivity. Various individual, organizational and environmental constructs related to the researchers working in the CSIR laboratories have been outlined that can enhance R&D productivity of researchers in Indian R&D laboratories. Partial Least Squares-Structural Equation Modeling (PLS-SEM) was used to find the predictability of the productivity model. Findings: The organizational factors have a crucial role in enhancing the R&D outputs of CSIR laboratories. The R&D productivity of researchers can be improved through implementing the constructs of the proposed model of productivity. Research limitations/implications: The R&D productivity model can be adapted by the R&D laboratories to enhance researchers' R&D involvement, increased R&D outputs and achieving self-sustenance in long run. Practical implications: The R&D laboratories can initiate exercises to explore the most relevant factors and measures to enhance R&D productivity of their researchers. The constructs of the model can function as a guideline to introduce the most preferable research policies in the laboratory for overall mutual growth of laboratory and the researchers. Originality/value: Hardly any studies have been found that have focused on finding the measures of enhancing R&D involvement of researchers and the influence of significant time-intensive jobs on researchers' productivity. [ABSTRACT FROM AUTHOR]

Purpose: Training has been an important tool for enhancing the skills and productivity of employees. Having productive employees helps organizations sustain themselves. Today, the authors organisations have an increasing number of employees on third-party payroll performing core as well as noncore business functions. However, due to the lack of ownership and moral obligation of employers, these employees are often not provided training, resulting in skills obsolesce and less productivity. The present study is a systematic literature review (SLR) on client organizations' roles in training third-party employees (TPEs) and its related outcomes. Design/methodology/approach: The present study is a SLR on client organizations' roles in training TPEs and their related outcomes. Using the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) approach, this study presents a review of 217 research papers on training of TPEs and its related outcomes. Findings: The study identifies the outcomes of providing training to TPEs and presents the findings and suggestions made by researchers. The study concludes that TPEs are an important investment for the client organization. Training them would benefit the client organization, TPEs and the economy as a whole. The paper also suggests some avenues for future research. Research limitations/implications: This paper tries to answer an important question: What could drive productive behavior among TPEs? Based on the literature reviewed, the answer is that TPEs could be offered training opportunities with a view to enhancing their employability. This could induce, among them, a sense of being valued and supported while contributing to organizational performance and creating a feeling of reciprocal obligation. This is an important contribution to literature. Low investment in these employees affects their employability, i.e. be it in the same organization for another term or another organization and thus the need for training and development, for sustained productivity among TPEs, in organizations. Practical implications: Training and development, for them, would result in enhanced employability within as well as outside the organization. These employees could also be a good source for regular positions within the organization, if required, benefiting both the organization and the employee. Additionally, the economy would also benefit from a pool of skilled workforce. Therefore, it is suggested that governments initiate some policy framework regarding mandatory training of TPEs to increase their competencies, resulting in increased organizational productivity, especially for TPEs at lower and middle levels of management. Originality/value: The paper is an original contribution by the researcher. An attempt has been made to highlight the training needs of TPEs and their related outcomes. [ABSTRACT FROM AUTHOR]

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In the data envelopment analysis (DEA) literature, productivity change captured by the Malmquist productivity index, especially in terms of a deterministic environment and stochastic variability in inputs and outputs, has been somewhat ignored. Therefore, this study developed a firm-specific, DEA-based Malmquist index model to examine the efficiency and productivity change of banks in a stochastic environment. First, in order to estimate bank-specific efficiency, we employed a two-stage double bootstrap DEA procedure. Specifically, in the first stage, the technical efficiency scores of banks were calculated by the classic DEA model, while in the second stage, the double bootstrap DEA model was applied to determine the effect of the contextual variables on bank efficiency. Second, we applied a two-stage procedure for measuring productivity change in which the first stage included the estimation of stochastic technical efficiency and the second stage included the regression of the estimated efficiency scores on a set of explanatory variables that influence relative performance. Finally, an empirical investigation of the Iranian banking sector, consisting of 120 bank-year observations of 15 banks from 2014 to 2021, was performed to measure their efficiency and productivity change. Based on the findings, the explanatory variables (i.e., the nonperforming loan ratio and the number of branches) indicated an inverse relationship with stochastic technical efficiency and productivity change. The implication of the findings is that, in order to improve the efficiency and productivity of banks, it is important to optimize these factors. [ABSTRACT FROM AUTHOR]

Low productivity growth in a low interest rate environment is a perennial problem for both UK monetary policy and the UK economy more generally. Through a comparative case study of eight firms across two economic sectors during 2012–6 we identify two shortcomings in the current productivity literature. The first is the importance of the order in which firms make investment and funding decisions. Investment decisions tend to predate questions of firm financing, implying loose monetary policy does not drive investment, but rather facilitates it. Secondly, we emphasise the importance of investment quality for funding choices. External financing such as credit or stock issues is predominantly used to fund expansionary but not productivity focussed investments. This implies monetary policy may have worsened the UK's productivity problem by facilitating expansionary over productivity enhancing investment strategies. Our findings are broadly consistent with the political economy literature on the UK economy, but we argue that research framed by the 'growth model' concept has not successfully illuminated firm-level dynamics, and relies on mainstream macroeconomics to explain low productivity. We therefore argue for a research agenda that moves beyond aggregate measures and incorporates questions about the quality of economic activity. [ABSTRACT FROM AUTHOR]

Structural change is an important driver of productivity growth at the aggregate level. While previous productivity decompositions account for the contributions of market entry and exit, they overlook continuing firms that switch from one industry to another. We develop an improved productivity decomposition that accounts for both intra-industry and inter-industry switching, is applicable to both static and inter-temporal settings, and ensures consistent aggregation of firm-level productivity to the industry level. The proposed decomposition is applied to Finland's information and communication technology (ICT) industry in the first two decades of the 21st century. This industry experienced major structural changes due to the rapid downfall of Nokia, the world's largest mobile phone manufacturer at the beginning of our study period. Our results reveal that the sharp decline of labor productivity was associated with structural changes, whereas the surviving firms that continued in the same industry managed to improve their productivity. Our results indicate that industry switching can dampen or enhance the productivity impacts of structural change, especially during times of crisis and recession. [ABSTRACT FROM AUTHOR]

In the article, Assessment of local and foreign soybean varieties transpired during 2020-2022, for yield-related traits, at the Samarkand and Navoi regions of Uzbekistan. The soybean cultivars, grown in a randomized complete block design, had a factorial arrangement with three replications. The data were documented on ten plants selected at random from each entry of each replication for the number of pods per plant, the number of seeds per plant, 1000-seed weight and seed yield. The data were scrutinized statistically using the analysis of variance of Fisher's technique and least significant difference (LSD) test at the 5% level of probability. When the yield and yield attributes of local and foreign soybean varieties in the Samarkand and Navoi regions were studied, local Ustoz-MMAn-60 and Tomaris-MMAn-60 soybean varieties showed positive results compared to other varieties for the field conditions of the Samarkand region, while Navoi For the field conditions of the region, Sparta and Oyjamol varieties showed higher indicators compared to other varieties. In the experiment, it was found that some foreign soybean varieties are positive in yield traits of productivity in the region of Uzbekistan. [ABSTRACT FROM AUTHOR]

The unsatisfactory performance of public sector made the Government introduce Memorandum of understanding and disinvestment. This study has been undertaken to analyze the performance of memorandum of understanding signed firms over the years. In addition, the performance of MoU-signed disinvested and MoU-signed non-disinvested firms have also been examined. Performance has been analysed using different ratios; return on equity, return on assets, net income productivity per employee and sales productivity per employee. In-line to analyze the effectiveness of data, random effect panel regression has been used to study the performance of sixty MoU signed PSEs for 15 years (2004-2018). The results indicate that the profitability of MoU signed non-disinvested firms is better than MoU signed disinvested firms. This could be possibly due to the more substantial managerial autonomy impact on the performance. Assets turnover ratio, leverage, and age have a significant effect on the performance of firms. [ABSTRACT FROM AUTHOR]

Introduction Theoretically in relation to economic growth and methods of calculating value added, the four factors of labor, capital, labor productivity, and capital productivity are considered, and the amount of value added will be the final product of the state and direct performance of these four factors. Since investment is an available option and has faster execution capability than the change in the quality of agricultural labor and the driver of changes in the productivity of other production factors, it is inevitable to focus on it by statesmen and macro and sector planners to realize the target economic growth in the agricultural sector. With this description, the macroeconomic planners of the agricultural sector have not determined the required amounts of investment, labor and productivity of labor and capital in the agricultural sector to realize the economic growth target in the 7th development plan. The role of investment as the driver of this (realization of the economic growth goal of the 7th development plan years) is not hidden from anyone, and determining the amount of investment required in this process will be very important for the policymaker. The main question of this study is, what is the amount of annual investment needed to realize the economic growth of Iran's agricultural goal in the 7th development plan? For this reason, the present study aims to estimate the amount of investment needed to realize the economic growth of the country's agricultural target (assumed) in the seventh development plan (2024-2028). Materials and Methods The current research is analytical-descriptive and with a computational approach, it deals with the estimation of the investment needed to realize the economic growth of the agricultural sector of Iran in the 7th Development Plan (2024-28). The time period considered in this study is 2011-2028. The estimation of the required investment of the agricultural sector in order to realize the economic growth of this sector in the 7th development plan has been done parametrically (algebraically) and by using the capital elasticity in the studies, the increasing ratio of capital to production (ICOR) and the average productivity of the net capital balance. Considering that the target economic growth for economic sectors including the agricultural sector in the 7th Development Plan has not been specified, therefore, in the form of different scenarios, three different economic growths (3.5 percent, 5.5 percent, and 8 percent) as The target (assumed) economic growth for the agricultural sector is considered in the years of the 7th development plan. Results and Discussion Climate changes and destruction of basic production resources are the most important challenges facing Iran's agriculture. In the 7th Development plan bill, economic growth of 8% is defined for the entire country's economy. In order to avoid over-reliance on basic resources in the agricultural production process and increase its resilience, a sustainable leap in targeted agricultural investment will be the most important choice of the government in the mid-term (7th development plan) and long-term. The aim of this study is to estimate the annual investment required in the agricultural sector in the 7th development plan, and in this regard, three approaches have been used to estimate the amount of annual investment required in the agricultural sector of Iran to achieve the target (assumed) economic growth. Examining the average of different approaches to estimate the annual investment for the target (assumed) value added growth of agriculture showed that according to the assumptions of the study and based on the prices of the base year 2016 (2016=100) to realize the growth of the value added of 3.5% necessary with a growth rate of 4.5%, an average of 183 thousand billion rials will be invested in Iran's agricultural sector annually. These figures will be 6.1% and about 234 thousand billion rials respectively to achieve 5.5% value added growth and 8.2% respectively and about 304 thousand billion rials to achieve 8% value added growth. There is no doubt that in addition to making the necessary investment, the realization of each of the target (assumed) growth of value added in the agricultural sector in the years of the 7th plan, on the one hand, depends on the existence of suitable and stable climatic conditions (as the main prerequisite for the production of agricultural products) and on the other hand, it is not imposing new shocks or crises on the agricultural economy of our country. Conclusion The destruction of basic resources and climate changes in Iran's agricultural field are taking place in such a way that it has made it difficult to produce agricultural products in a large area of Iran in the field (the need to develop greenhouse crops) and on the other hand, the development of capital in the process of agricultural production (as a supplement or substitute for other production inputs) in order to increase productivity and preserve the limited and deteriorating production resources has made agriculture more necessary than in the past. Past experiences show that changing the financing approach for investing in Iran's agricultural sector is inevitable. Therefore, it is necessary that in the seventh development plan while separating investment facilities and agricultural working capital facilities during the 7th development plan, improving the environment for agricultural investment and the mechanism for transferring savings to this sector, optimal allocating domestic financial resources (National Development Fund, banking system, support fund for The development of investment, microagricultural funds, etc.) and foreign financial resources (foreign direct investment) should be planned in such a way that the investment made in the agricultural sector is coordinated and proportionate with the economic growth of the program. [ABSTRACT FROM AUTHOR]

The three main components of productivity change are technical change, change in technical efficiency, and returns to scale effects. Solow measured productivity change at the macroeconomic level as the difference between the growth rates of output and input which, under constant returns to scale and in the absence of any technical inefficiency, is a measure of technical change. The focus in this monograph is on the individual firm and both technical inefficiency and variable returns to scale are accommodated. In neoclassical production economics, productivity change can be measured alternatively from the production, cost, profit, or distance functions. In continuous time analysis, one measures therates of productivity and technical change. In discrete time, one measuresindexes of productivity and technical change over time. This work describes the Tornqvist, Fisher, and Malmquist productivity indexes along with the Luenberger productivity indicator and a Geometric Young index and how they relate to one another. The relevant nonparametric DEA models for measuring the different productivity indexes are formulated for nonparametric analysis of productivity, technical change, and change in efficiency. [ABSTRACT FROM AUTHOR]

This paper carries out an empirical study to examine the contribution of urban areas in generating tax revenue and growth at 28 Indian state levels. The study is based on the hypothesis that the productivity and agglomeration externality effects present in cities, known as "wider economic benefits", lead to enhanced tax bases of State Governments. The cross-sectional estimation has confirmed that urbanization and state gross domestic product per capita significantly contribute to the tax bases of State Governments, such as sales tax, stamps, registration duty and motor vehicle tax. These three agglomeration taxes (including goods and services tax) are recommended for sharing with urban local bodies. [ABSTRACT FROM AUTHOR]

For a long period of the 20th Century, industrialization was seen as the quickest and more effective path for progress and productive diversification, influencing the choice of public policies adopted by Latin American governments since the inter-war period up until the debt crisis and the lost decade of the 1980s. Using a long-term macroeconomic database for the period 1913–2013 and 11 Latin American countries, complemented with a dataset of exports by product for the same countries and years, a positive relationship between industrialization and economic growth was found, both for the long run and for episodes of acceleration and deceleration. This correlation seems to be stronger for large than for small economies, reflecting the importance of the size of the domestic market in order to take advantages of economies of scale in the process of industrialization. Three economic channels that may explain this positive correlation are empirically tested. The first one is the contribution of manufacturing to the different components of productivity growth (within- and shift-effects), for which a shift-share decomposition was estimated, both for the long-run, for subperiods and for acceleration and deceleration episodes. The second channel is the contribution of industrialization to gross capital accumulation, where a positive relationship was found between the change in the share of employment in manufacture with the rate of growth of physical capital. Finally, the learning-by-doing hypothesis is tested using the skill-level composition of manufacturing exports, finding a positive relationship between cumulative manufacturing production and the share of mid- and high-skill products in the exports' matrix. The main contributions of the paper are twofold: the empirical identification of the mechanisms through which industrialization can promote economic development, and the extension of the analysis of Latin American economies to the first half of the 20th Century, which is scarce in the literature because of lack of reliable data. [ABSTRACT FROM AUTHOR]

Paul Schreyer, the Chief Statistician and Director of Statistics and Data at the OECD, discusses the importance of high-quality statistics and evidence-based analysis in policy-making. He highlights the role of the Committee of Statistics and Statistical Policy (CSSP) in supporting policy-making based on internationally comparable data. Schreyer also emphasizes the need for trust in statistics, but only if they meet certain criteria for quality, reliability, neutrality, and independence. He mentions the positive review of the statistical systems of Bulgaria and Croatia as an important step towards their accession to the OECD. Schreyer also discusses his career at the OECD and the organization's efforts to ensure the quality of its statistics through internal review processes and coordination with other international organizations. He concludes by stating that trust should be placed in good statistics. [Extracted from the article]

We extend the ecological component (ECOGEM) of the carbon-centric Grid-Enabled Integrated Earth system model (cGEnIE) to include a diatom functional group. ECOGEM represents plankton community dynamics via a spectrum of ecophysiological traits originally based on size and plankton food web (phyto- and zooplankton; EcoGEnIE 1.0), which we developed here to account for a diatom functional group (EcoGEnIE 1.1). We tuned EcoGEnIE 1.1, exploring a range of ecophysiological parameter values specific to phytoplankton, including diatom growth and survival (18 parameters over 550 runs) to achieve best fits to observations of diatom biogeography and size class distribution as well as to global ocean nutrient and dissolved oxygen distributions. This, in conjunction with a previously developed representation of opal dissolution and an updated representation of the ocean iron cycle in the water column, resulted in an improved distribution of dissolved oxygen in the water column relative to the previous EcoGEnIE 1.0, with global export production (7.4 Gt C yr -1) now closer to previous estimates. Simulated diatom biogeography is characterised by larger size classes dominating at high latitudes, notably in the Southern Ocean, and smaller size classes dominating at lower latitudes. Overall, diatom biological productivity accounts for ∼20% of global carbon biomass in the model, with diatoms outcompeting other phytoplankton functional groups when dissolved silica is available due to their faster maximum photosynthetic rates and reduced palatability to grazers. Adding a diatom functional group provides the cGEnIE Earth system model with an extended capability to explore ecological dynamics and their influence on ocean biogeochemistry. [ABSTRACT FROM AUTHOR]

Trust, safety, and quality are among the most important factors in the agri-food supply chains. Traceability is a powerful tool to ensure them, but implementing a transparent and effective system is a complex operation. As a result, innovative systems, like blockchain, could be introduced. Although research on its impacts in the agri-food is recent, the literature appears fragmented. The objective is to investigate the studied aspects of the blockchain adoption in agri-food, with the purpose of retrieving meaningful considerations about the current state of the art about strategic high-value supply chains, such as wine and olive oil, particularly subjected to fraudulent behaviors. A productivity measurement was applied to retrieve the evolution of the number of documents through the years, the most productive countries, the sources, the research areas, and the most significant papers in terms of number of citations received. To understand the research trends, a co-occurrence analysis was employed. Results show that most of the existing studies focus on the role of blockchain in the resolution of some critical issues as food safety and frauds. While wine is currently an emerging sector in which this approach can be implemented, olive oil still needs more attention. In both cases, blockchain could potentially help to support the profitability and sustainability of the production. The research underlines the importance of focusing on the environmental and social dimension of the blockchain phenomenon and the use of technology to improve the efficiency of agri-food chains and reduce waste and resource use. [ABSTRACT FROM AUTHOR]

The article delves into the economic perspective of artificial intelligence (AI), particularly focusing on the impact of ChatGPT's commercial release in 2022. It explores the challenges of measuring AI's diffusion in the economy, discusses economic modeling of AI as a factor of production, and presents various ways to conceptualize AI in macroeconomic models. The article also touches on the EU's AI Act and the complexities of measuring AI technologies in national accounts.

We use the 2012 Green Credit Guidelines as a quasi-natural experiment and data from A-share listed companies from 2008–2020 to examine the effect of green credit policy on firm productivity and its mechanism of action. The results show that the green credit policy significantly inhibits improvements in firm productivity. The inhibitory effect still holds after a series of robustness tests, such as the difference-in-differences propensity score matching method, placebo test, and change in the timing of policy shocks. The mechanism of action test reveals that credit resource allocation, financing constraints and business credit are important channels through which green credit policy can reduce firm productivity. The heterogeneity test reveals that the inhibitory effect of green credit policy on firms' productivity improvements in restrictive industries is more significant for private firms, smaller firms, and inland regions. The policy implication of the findings of this paper is mainly to improve the green credit policy guarantee mechanism and policy implementation using the market as the main body, with the goal of realizing the synergistic development of policy implementation and environmental protection and of promoting rational resource allocation. [ABSTRACT FROM AUTHOR]

Few lake-wide, seasonal primary production measurements have been made in Lake Erie. None more recent than 1997 have been reported in the literature. In 2019 we used 13C uptake to measure production at 11 stations across the lake during three surveys in May, July, and September and at four of these stations during two additional surveys in April and August. Samples were collected at two depths (2 m and 6 m) and incubated on deck using eight levels of irradiance. We fit the resultant photosynthesis-irradiance curves with models that included the initial slope at low light levels, the maximum photosynthesis rate at light saturation, and when warranted, the negative slope at high irradiance. During May, there was little variation in chlorophyll-normalized volumetric productivity with sample depth, and productivity generally was higher nearshore and in the western basin than it was offshore. The distinction between nearshore and offshore stations was less pronounced in July, but nearshore productivity was higher than offshore in September. Using the photosynthesis data from all five surveys, chlorophyll concentration profiles, and estimated clear-sky solar insolation, we calculated time series of vertically integrated daily production at a western basin station, two central basin stations, and an eastern basin station. Central basin production was highest during August, estimated to be 748 mg C m-2 d-1 and 779 mg C m-2 d-1 at our two stations. Production peaked in July in the western basin (510 mg C m-2 d-1) and September in the eastern basin (421 mg C m-2 d-1). Whole-lake seasonal areal phytoplankton photosynthesis was estimated as 1.661E6 tonnes, about half of estimates made in the 1990s using 14C methods. These results inform our understanding of spatial-temporal trends in Lake Erie productivity and highlight the need for continued measurements of Lake Erie primary production. [ABSTRACT FROM AUTHOR]