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This study investigates the ability of crime management expenses, recognised external quality certification and ownership structure to describe the cross-sectional changes in the capital and labour efficiencies of manufacturing firms in middle income economies. It controls for the potential effects of graft incidence and firm age on firm-level efficiency.

The study adopts a state space model approach within the context of cross-sectional regressions. Data for the study are obtained from the World Bank Enterprise Survey for 2006, 2009, 2013, 2016 and 2019.

The study provides evidence that crime management expenses impact labour efficiency negatively. Also, its effect on capital efficiency is positive in 2019 and negative in 2013 and 2016 eras. Additionally, external auditor services and internationally recognised quality certification increase labour and capital efficiencies. Graft incidence exerts negative and positive effect on capital efficiency in the recent and earlier periods respectively. In addition, older firms tend to have higher labour efficiency, whilst younger firms have higher capital efficiency. There is evidence of firm size and export orientation effects in the drivers of efficiency.

Policies aimed at creating graft and crime-free business environment will enhance the efficiency and growth of firms' particularly for small firms. Also, the market rewards recognised quality assurance and good reputation.

Using a large sample of diversified firms from 38 countries we investigate the influence of several national-level institutional factors or “institutional voids” on the value of corporate diversification. Specifically, we explore whether the presence of frictions in a country’s capital markets, labor markets, and product markets, affects the excess value of diversified firms. We find that the value of diversified firms relative to their single-segment peers is higher in countries with less-efficient capital and labor markets, but find no evidence that product market efficiency affects the relative value of diversification. These results provide support for the theory of internal capital markets that argues that internal capital allocation would be relatively more beneficial in the presence of frictions in the external capital markets. In addition, the results show that diversification can be beneficial in the presence of frictions in the labor market.

The purpose of this paper is to show that intentional demand forecast bias can improve warehouse capacity planning and labour efficiency. It presents an empirical methodology to detect and implement forecast bias.

A forecast model integrates historical demand information and expert forecasts to support active bias management. A non-linear relationship between labour productivity and forecast bias is employed to optimise efficiency. The business analytic methods are illustrated by a case study in a consumer electronics warehouse, supplemented by a survey among 30 warehouses.

Results indicate that warehouse management systematically over-forecasts order sizes. The case study shows that optimal bias for picking and loading is 30-70 per cent with efficiency gains of 5-10 per cent, whereas the labour-intensive packing stage does not benefit from bias. The survey results confirm productivity effects of forecast bias.

Warehouse managers can apply the methodology in their own situation if they systematically register demand forecasts, actual order sizes and labour productivity per warehouse stage. Application is illustrated for a single warehouse, and studies for alternative product categories and labour processes are of interest.

Intentional forecast bias can lead to smoother workflows in warehouses and thus result in higher labour efficiency. Required data include historical data on demand forecasts, order sizes and labour productivity. Implementation depends on labour hiring strategies and cost structures.

Operational data support evidence-based warehouse labour management. The case study validates earlier conceptual studies based on artificial data.

The purpose of this paper is to empirically investigate the impact of economic policy uncertainty on firms' labor investment decision, which includes labor investment level and efficiency, especially human capital allocation.

This paper uses Economic Policy Uncertainty Index for China and Chinese A-share listed firms in the period 2002–2016 to constructs a sample of 20,779 firm-year observations and applies the methods of pooled OLS regressions to do an empirical study.

This paper finds that firms' labor investment is negatively correlated with economic policy uncertainty. And firms' labor investment efficiency (and overinvestment in labor) is positively (negatively) correlated with economic policy uncertainty, which is more significant for non-SOEs and firms with less government intervention. Further, the positive relation between economic policy uncertainty and labor investment efficiency is more significant for labor-intensive firms, firms in competitive industry, firms in developed labor market and firms under strong labor law protection. In addition, economic policy uncertainty induces firms to make adjustment on human capital structure and allocate more employees with high human capital, which eventually helps firms achieve higher total factor productivity.

The study of this paper indicates that the government needs to consider economic policies' impact on firms when introducing and changing policies and guide firms to improve human capital allocation under different internal and external conditions to finally realize the optimal allocation of social resources.

This paper studies the influence of external economic policy environment on firms' labor investment decision, which lacks adequate attention in the literature and indicates that under economic policy uncertainty, firms actively decrease labor demand and increase labor investment efficiency by optimizing human capital allocation.

Dairy farms, along with livestock and specialty crop farms, face a tight labor supply and increasing labor costs. To overcome the challenging labor market, farm managers can increase labor-use efficiency through both human resource and capital investments. However, little is known about the relationship between such investments and farm profitability. The purpose of this paper is to examine the relationship between dairy farm financial performance and labor-use efficiency, as measured by labor productivity (milk sold per worker equivalent); labor costs (hired labor cost per unit of milk sold and hired labor cost per worker); and investment in labor-saving equipment.

Cluster analysis is applied to partition dairy farms into three performance categories (high/middle/low), based on farms’ rate of return on equity, asset turnover ratios and net dairy income per hundredweight of milk. Next, the annual financial rank is fitted into both random- and farm-level fixed-effects ordered logit and linear models to estimate the relationship between dairy farms’ financial performance and labor-use efficiency. This study also investigates the implications of using a single financial indicator as a measure of financial performance, which is the dominant approach in literature.

The study finds that greater labor productivity and cost efficiency (as measured by hired labor cost per unit of milk sold) are associated with better farm financial performance. No statistically significant relationship is found between farm financial performance and both hired labor cost per worker and advance milking systems (a proxy of capital investment in labor-saving technology). Future studies would benefit from better measurements of labor-saving technology. This study also demonstrates inconsistency in regression results when individual financial variables are used as a measure of financial performance. The greater labor-use efficiency on high-performing farms may be a combination of hiring more-skilled workers and managerial strategies of reducing unnecessary labor activities. The results emphasize the importance of managerial strategies that improve overall labor-use efficiency, instead of simply minimizing total labor expenses or labor cost per worker.

This study examines the importance of labor productivity and labor cost efficiency for dairy farm management. It also develops a novel approach which brings a more comprehensive financial performance evaluation into regression models. Furthermore, this study explicitly demonstrates the potential for inconsistent results when using individual financial variable as a measure of financial performance, which is the dominant measurement of financial performance in farm management studies.

The objective of this study is to investigate the simultaneity between farm couples’ decisions on labor allocation and production efficiency. Using an unbalanced panel data set of Norwegian farm households (1989–2008), we estimate off-farm labor supply of married farm couples and farm efficiency in a three-equation system of jointly determined endogenous variables. We address the issue of latent heterogeneity between households. We solve the problem by two-stage OLS and GLS estimation where state dependence is accounted for in the reduced form equations. We compare the results against simpler model specifications where we suppress censoring of off-farm labor hours and endogeneity of regressors, respectively. In the reduced form specification, a considerably large number of parameters are statistically significant. Davidson–McKinnon test of exogeneity confirms that both operator and spouse's off-farm labor supply should be treated as endogenous in estimating farming efficiency. The parameter estimates seem robust across model specifications. Off-farm labor supply of farm operators and spouses is jointly determined. Off-farm work by farm operator and spouses positively affects farming efficiency. Farming efficiency increases with operator's age, farm size, agricultural subsidises, and share of current investment to total farm capital stock.

The purpose of the paper was to establish the implications of globalisation for labour markets when efficiency wages create endogenous wage rigidity and to re‐examine the credibility of the arguments that call for deregulation, more wage flexibility and less social protection in this context.

The role of efficiency wages is reviewed in the traditional international economics theory, new economic geography and the neo‐Schumpeterian perspective towards international competitiveness.

First, taking into account endogenous sources of wage rigidity has different implications for employment, inequality, regional growth convergence and the role of the welfare state in the context of international competitiveness, from those derived when assuming them away or taking them as imposed by labour market institutions. Second, policies that would substantially reduce social security or lead to cost‐cuts may have an adverse effect on effort and thus on productivity.

To the author's knowledge, this paper is the only review in the literature that concentrates on efficiency wages applied in international trade.

This research paper examines the information content and managerial incentives for labour cost voluntary disclosures for a sample of United States publicly traded companies. We focus on labour productivity and managerial efficiency in labour usage and argue that these human capital indicators could provide valuable information to capital market participants seeking human resource‐type of performance measures and signals. Labour productivity and efficiency indicators are estimated following a production function approach and are included in logistic regressions to help explain and predict labour cost voluntary disclosure decisions. We find that labour productivity and managerial efficiency in labour use indicators are generally different between disclosing and non‐disclosing firms, and that proprietary information costs and political cost proxies are significantly related to labour costs voluntary disclosure, consistent with previous literature. These empirical results corroborate the ‘proprietary information’ hypothesis of voluntary disclosure where the strategic costs of disclosure outweigh the signaling benefit from disclosing human capital information.

The objective of this study is to evaluate the overall technical efficiency, labor efficiency, capital efficiency and equipment efficiency of 30 Chinese construction sectors to foster sustainable economic growth in the construction industry.

This study employed the super-efficiency data envelopment analysis (SE-DEA) and artificial neural network model (ANN) to evaluate the industrial performance and improvement potential of the Chinese regional construction sectors from 2000 to 2017.

Results showed that the overall technical and capital efficiencies displayed relatively stable patterns. Equipment efficiency presented a relatively huge fluctuation during the sample period. Meanwhile, labor, capital and equipment efficiencies could potentially improve in the next five years. A spatial examination of efficiencies implied that the economic level was still a major factor in determining the efficiency performance of the regional construction industry. Beijing, Shanghai and Zhejiang were consistently the leading regions with the best performance in all efficiencies. Shandong and Hubei were critical regions with respect to their large reduction potential of labor, capital and equipment.

The study focused on the regional efficiency performance of the construction industry; however, it failed to further deeply discover the mechanism that captured the regional inefficiency. In addition, sample datasets used to predict might induce the accuracy of prediction results. Qualitative policy implications failed to regress the efficiency performance of the industrial policy variables. These limitations will be discussed in our further researches.

Enhancing the overall performance of the Chinese construction industry should focus on regions located in the western areas. In comparison with labor and capital efficiencies, equipment efficiency should be given priority by eliminating outdated equipment and developing high technology in the construction industry. In addition, the setting of the national reduction responsibility system should be stratified to account for regional variations.

The findings of this study can provide a systematic understanding for the current and future industry performance of the Chinese construction industry, which would help decision makers to customize appropriate strategies to improve the overall industrial performance with the consideration of regional differences.

Labour efficiency is the key component for the long-term sustainability of construction firms. Recent studies show that modernising organisational/managerial processes is necessary to raise labour efficiency in many emerging nations. Construction supervision is a crucial element in organisational/managerial practices, which provide blood circulation to the project operations by directing labour. Accordingly, this study aims to quantify the impacts of crucial organisational/managerial elements on the efficiency of labour in building construction projects based on the viewpoint of construction supervisors.

A total of 28 factors were determined as critical, where lack of labour motivation, poor labour training facilities, poor performance evaluation practices, no labour rewarding mechanism and poor communication/cooperation between parties were judged to be the top five key issues in the list. The validity and reliability of the study findings were ensured through statistical tests and the experts' discussion outcomes. In view of the evolving challenges facing the industry, the results indicate that the organisational policies of construction enterprises in place addressing financial procedures, communication strategies, resource management and performance management practices must be enhanced.

The study findings will make a substantial contribution to reducing the disparity between organisation/management policies and labour practices towards changing how the sector operates to increase labour efficiency in construction projects.

This study contributes to addressing the knowledge gap in the industry associated with the organisational protocols, especially to understand/predict how such elements are significant, how much they influence the efficiency of construction practices and what steps can be made to limit their effects on labour efficiency in construction. These could be crucial in modernising organisational policies and procedures for construction management.