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This study investigates the optimum size for manufacturing firms and the impact of subcontracting on firms' likelihood of achieving their optimal scale in Vietnam.

Using data from the enterprise census in 2017 and 2021, the paper first estimates the production function to identify the optimum firm size for manufacturing firms and then, applies the logit model to investigate factors associated with the optimal firm size.

The study reveals that medium-sized firms exhibit the highest level of productivity. Nevertheless, a consistent trend emerges, indicating that nearly 90% of manufacturing firms in Vietnam operated below their optimal scale in both 2017 and 2021. An analysis of the impact of subcontracting on firms' likelihood to achieve their optimal scale emphasizes its crucial role, especially for foreign firms, exerting an influence nearly five times greater than that of the judiciary system.

The paper's findings offer crucial policy implications, suggesting that initiatives aimed at enhancing the overall productivity of the manufacturing sector should prioritise facilitating contract arrangements to encourage firms to reach their optimal size. These insights are also valuable for other countries with comparable firm size distributions.

This paper provides the first empirical evidence on the relationship between firm size and productivity as well as the role of subcontracting in firms' ability to reach their optimal scale in a country with a right-skewed distribution of firm sizes.

This paper aims to examine the impact and mechanism of digital development on enterprise labor productivity. In addition, this study empirically analyzes the nonlinear impact of digitalization on labor productivity.

This paper uses a fixed effect model, a mediation effect model and a panel threshold model to test the theoretical hypothesis of this study.

The results demonstrated that digitalization had a promotional effect on labor productivity, with approximately 18% of this effect achieved through transmission and influence on human capital. In addition, the novelty of this study lies in the discovery that digitization has an obvious nonlinear positive effect on corporate labor productivity. The results suggest that companies should increase investment in data-driven innovation capabilities, improve the implementation of digital talent training plans, improve their financing capacity and strengthen corporate internal management, while the government should provide appropriate policy support differently for various enterprises.

This study takes China’s Shanghai and Shenzhen A-share listed companies as the research object, systematically examines the impact and mechanism of digital development on enterprise labor productivity and explores the nonlinear relationship between digitalization and enterprise labor productivity, which is a new angle.

本文旨在探讨数字化发展对企业劳动生产率的影响及其机制。此外, 本研究实证分析了数字化对劳动生产率的非线性影响。

本文采用固定效应模型、中介效应模型和面板门槛模型来检验本研究的理论假设。

结果表明, 数字化对劳动生产率有促进作用, 其中约 18% 是通过对人力资本的传导和影响来实现的。此外, 本文的新颖之处在于发现了数字化对企业劳动生产率具有显著的非线性正效应。结果表明, 企业应加大对数据驱动创新能力的投入, 完善数字化人才培养计划的实施, 提高融资能力, 加强企业内部管理, 政府应针对各类企业提供差异化的政策支持。

本研究以中国沪深A股上市公司为研究对象, 系统考察了数字化发展对企业劳动生产率的影响和机制, 探讨了数字化与企业劳动生产率之间的非线性关系, 这是一个新的研究角度。

The aim of the paper is to explore within-firm vertical pay inequality and its relation to firm size and firm performance.

Using firm-level microdata for Kazakhstan, the authors measure within-firm pay inequality as the wage differential between the top- and the bottom-level job occupations. The authors carry out their analysis based on panel regression models.

The authors find that within-firm pay inequality increases as firms grow. Further, they identify that this trend is mainly driven by top-occupation workers receiving more significant wage increases compared to lower-level workers as firms expand. Once the authors address concerns about endogeneity, they find that pay inequality is negatively associated with firm performance.

Developing strategies and policies that prioritize fairness and transparency in compensation practices is crucial during the expansion process of firms. By actively discouraging rent-seeking behavior, firms can create a work environment that promotes productivity and sustainability, ultimately leading to improved firm performance. The research findings highlight the importance of implementing context-specific interventions, recognizing that different environments may require tailored approaches to address pay inequality effectively.

This study contributes to the study of within-firm pay inequality, firm size and performance in an emerging economy, an area that has been largely overlooked in previous empirical research. The contrasting findings show the importance of the structural and industrial characteristics of emerging markets that contribute to broader and deeper impact of pay inequality compared to developed economies.

The aim of the research is to examine in depth the relationship between financial support, entrepreneurship and economic growth in emerging African economies.

The study adopts the system-generalized methods of moments (sys-GMM) technique for data analysis and hypothesis testing on a sample of 34 African emerging economies (340 observations) from 2010 to 2019.

The results show that there is significant positive correlation between financial support, entrepreneurship, and economic growth. Moreover, entrepreneurship served as a partial mediator between financial support and economic growth in African emerging economies.

This research suggests that African governments should focus on entrepreneurial systems, which are essentially networks driven by the pursuit of individual opportunities and the promotion of new business creation; and introduce other forms of financial assistance, such as loans, loan guarantees, interest subsidies, technical assistance, insurance, etc.

The main novelty of the paper is that the authors empirically investigate the mediating role of entrepreneurship in the association between financial support and economic growth in 34 African emerging economies.

The success of construction projects can be indicated by measuring their performance. For effective project performance (PP), the successful execution of a construction projects is very important. A systematic review of the literature on performance areas and performance assessment models was undertaken. The purpose of this paper is to develop a mathematical formulation for construction PP areas to suit the Indian context by modifying the current project quarterback rating (PQR) model.

Based on the literature, the PQR model has not been validated for suitability in the Indian context. To validate the PQR model and modify the same for the Indian context, a survey instrument was used to collect data on performance areas and a multivariate data analysis technique was carried out to develop a modified model. Delphi technique was used to assign the weights for each performance metric in performance areas.

This study concluded the importance of three additional performance areas, namely, productivity, stakeholder satisfaction and environment for assessing PP for Indian construction projects. It also identified the interrelationship between the performance areas and the PP.

The developed modified PQR model (MPQR) will guide the concerned stakeholders to take corrective actions for improving the performance of construction projects.

The MPQR proposed in this paper covers ten areas and is a comprehensive single score that can be used to benchmark and compare performance over different projects to achieve continuous improvement.

In recent times, there has been a lot of research focused on performance measurement (PM) in project-based sectors. However, there are very few studies that were reported on the significance of PM in the construction sector. Keeping track of an organization in achieving organizations goals and objectives seems an important way. One of the major challenges faced by the industry is unavailable of an appropriate PM system for assessing organizational performance. Most of the PM approaches consider the traditional project triangle assessment of project success. Based on the limitations identified in existing PM models, the purpose of this paper is to develop a comprehensive PM model, i.e. Modified Project Quarter Back Rating (MPQR) applicable for construction projects.

A detailed list of performance areas as a method for PM is analyzed in the construction industry context. Also, industry-specific professionals conducted semi-structured interviews to assess whether these performance areas are sufficient to measure and understand the PM systems.

The research finding focuses on developing the MPQR model that considers both financial and non-financial areas for performance assessment to provide a holistic assessment of project performance.

MPQR model provides an opportunity to set the benchmark for overall performance for construction organizations.

The findings of the study are expected to provide guidelines to construction professionals for implementing the performance model that will improve performance in the construction industry.

The purpose of this study is to develop a novel general mathematical model to find the optimal product mix of commercial graphite products, which has a complex production process with alternative sub-processes in the graphite mining production process.

The network optimization was adopted to model the complex graphite mining production process through the optimal allocation of raw graphite, byproducts, and saleable products with comparable sub-processes, which has different processing capacities and costs. The model was tested on a selected graphite manufacturing company, and the optimal graphite product mix was determined through the selection of the optimal production process. In addition, sensitivity and scenario analyses were carried out to accommodate uncertainties and to facilitate further managerial decisions.

The selected graphite mining company mines approximately 400 metric tons of raw graphite per month to produce ten types of graphite products. According to the optimum solution obtained, the company should produce only six graphite products to maximize its total profit. In addition, the study demonstrated how to reveal optimum managerial decisions based on optimum solutions.

This study has made a significant contribution to the graphite manufacturing industry by modeling the complex graphite mining production process with a network optimization technique that has yet to be addressed at this level of detail. The sensitivity and scenario analyses support for further managerial decisions.

Using the Shanghai pilot free trade zone (SPFTZ) as the testing ground for further reform and opening up,the links between global value chain (GVC) and pilot free trade zone (PFTZ) programs are mutually reinforcing. GVC creates opportunities for companies to use PFTZ to reduce their costs and increase their competitiveness, while PFTZ can facilitate the movement of goods within GVC and promote the development of GVC by attracting foreign investment. Overall, in SPFTZ, the industrial structure is promoted due to trade and investment facilitation, innovation promotion, and comprehensive service platform inside SPFTZ.

This study examined industrial upgrading in GVC (IUGVC) using five indicators under three quantitative dimensions: product, process, and skill upgrading. Difference-in-Differences (DID) model is employed for the impact assessment of SPFTZ. Parallel trend analysis and Granger causality analysis are performed to check the reliability of DID outcome. Finally, robustness test using exogenous control variables are carried out.

A positive impact of SPFTZ is found on IUGVC, which is due to promoting effect of SPFTZ on foreign direct investment and technological innovation. Based on the study's findings, policy recommendations are given, such as providing business support to enterprises operating inside a PFTZ.

From a GVC perspective, the impact of theSPFTZ establishment on IUGVC cannot be ignored, and is so far missing in the literature.

This article investigates the validity of the different types (conditional, unconditional, deterministic, stochastic) of ß-convergence in per capita GDP for EU-28 and EU-19 between 1990 and 2019.

The study uses nonstationary heterogeneous panel-data methodology.

The panel data reveal that both conditional and unconditional ß-convergence are valid in EU-28 countries However, only conditional convergence exists in EU-19 countries; group-specific findings show that the income levels of 10-EU countries converge toward the EU-19 average and 11-EU countries converge to the EU-28. The convergence speed to EU average varies between 15 and 18%. The robustness of the augmented mean group (AMG) findings are checked with common correlated effects mean group (CCEMG) and are consistent. Moreover, panel unit root tests are applied to examine the stochastic and deterministic convergence of the average EU per capita income in the two groups of EU economies. The findings show no evidence of deterministic or stochastic convergence in EU countries. Besides, conditional convergence has not been experienced in countries such as Bulgaria, Croatia, Czech Republic, Hungary, Latvia, Malta, Romania, Slovakia and Slovenia, which are new members of the EU. As a remarkable aspect of the study, the evidence suggests that the Brexit is economically rational for the UK.

The growth and convergence processes of economies differ from each other. Convergence studies in the literature are generally based on the cross-section OLS methodology. In this context, the study is one of the rare studies to examine convergence using heterogeneous panel techniques and allows the convergence of countries to the EU average to be analyzed individually.

This paper aims to investigate the performance of OECD countries' long-term productivity during the period of 1975–2018.

This study employed different approaches to evaluate how efficiency scores vary with changes in inputs and outputs: Data Envelopment Analysis (CRS, VRS and FDH), TOPSIS and TOPSIS of these scores.

The findings suggest that, during the period of this study, countries with higher freedom of religion and with Presidential democracy regimes are positively associated with higher productivity.

To the best of the authors’ knowledge, this is the first study that uses efficiency models to assess the productivity levels of OECD countries based on several contextual variables that can potentially affect it.