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Increasing carbon productivity is an effective way to reduce carbon emissions, while boosting economic prosperity. For appropriate formulating and enforcement of energy saving and carbon emissions reduction policies in various sectors, it is of great significance to investigate the evolution characteristics and convergence modes of carbon productivity across the manufacturing sectors.

Using slack-based measure directional distance function (SBM-DDF) and global Malmquist–Luenberger (GML) productivity index, this paper measures the carbon productivities of 29 manufacturing subsectors in Shanghai, China, from 2001 to 2016 under the total factor framework. Furthermore, based on the convergence theories, it empirically examines the convergence of carbon productivity across these manufacturing sectors.

The measurement results suggest that the carbon productivities of the manufacturing sectors in Shanghai show an increasing tendency on the whole, and technical efficiency instead of technological change makes a main contribution to the increase. It is found that there is no obvious σ convergence across the manufacturing sectors in Shanghai, but there exist both absolute ß convergence and conditional ß convergence. Moreover, there is heterogeneity in convergence characteristics between the clean sectors and polluting sectors. The findings also show that firm size and industry structure have significant positive impacts on the growth of carbon productivities of the manufacturing sectors, whereas the impacts of capital deepening and energy consumption structure are significantly negative.

This paper measures the carbon productivities of the manufacturing subsectors by applying SBM-DDF and GML index, so as to improve the accuracy. It provides an insight into the convergence of carbon productivity across the manufacturing sectors.

The aim of this paper is to disentangle the contemporaneous and non-contemporaneous relationship between regional business cycles and manufacturing productivity in a developing country, namely Colombia.

The methodology is quantitative. To deal with the problems of endogeneity in the production function and with the law motion of productivity (the Markov process), the authors obtain Total Factor Productivity (TFP) through the Wooldridge’s two equations system that can be jointly estimated under the generalized method of moments framework (GMM). Secondly, to avoid bias we estimate regional business cycles through the Kalman filter. Subsequently, we implement an instrumental variables/generalized method of moments regression (IV/GMM) to capture the contemporaneous and endogenous TFP–GDP cycles’ linkage at the regional level. Lastly, to deal with the non-contemporaneous link, the authors estimate a vector autoregressive model with exogenous variables (VARX) for each region. We also present the corresponding impulse–response functions.

The authors’ general results suggest a remarkable causality, both contemporary and non-contemporary, from productivity to GDP (but not vice versa) in the most developed regions of the country. This implied productivity could influence in the economic growth of regions in short and long runs. These results are different than those expected by economic theory and should be considered by local economic policy makers.

The authors consider that a more detailed analysis should be carried out at the level of each sector within the manufacturing industry to further clarify these findings.

The policy should be oriented to obtaining cutting-edge technologies through subsidies, and also should facilitate the access to financial capital and the investment in R&D laboratories. On the other hand, the link with international trade also must be reinforced because the importing of intermediate inputs and exporting of output allow the firms to obtain embodied technologies, also to incur on learning by exporting and importing processes and finally to gain experience and competitiveness in foreign markets.

The causality in the region that provides more than 50% of economic activity within the country (Third region) is only in one directional, from TFP towards gross domestic product (GDP) and not vice versa. As the influence from GDP towards TFP is minimal in the remaining regions, the manufacturing productivity influences both short and long run regional economic growth in Colombia. This implies that economic policy at the level of macro-region must be modified; the government should give additional support to the manufacturing sector, especially in developed regions and for the small and medium-sized enterprises (SMEs) (wich represent 92% of manufacturing firms) to increase economic growth in the future.

The authors’ contribution is threefold. First, they pay special attention to the contemporaneous cyclical relationship (i.e. pro-cyclical, counter-cyclical or acyclic) and the non-contemporaneous causality with productivity. Second, they estimate productivity with the GMM two equation system considering an endogenous Markov process. Third, to the best of their knowledge, at least in the case of Latin America, there are no studies in this direction combining these statistic methods, including that of Colombia.

This paper aims to study whether Peruvian manufacturing firms that implement innovation have positive performance and whether R&D activities moderate these relationships.

Using a data set of Peruvian manufacturing firms from the 2018 National Survey of Innovation, a LOGIT model analysis was applied to 774 companies. In addition, the authors fitted different models into subsamples to explore the moderating effects of R&D on manufacturing firms. Finally, the regression models were computed using R software.

The results indicate that product, service and marketing innovation are associated positively with an increase in market share, while process and organizational innovations are associated positively with productivity. Moreover, companies with R&D are more productivity-oriented than companies without R&D.

This study contributes to the literature on innovation management by supporting the assumption that innovation results in increased productivity and expands market demand. In addition, findings highlight that R&D is essential for boosting firms’ productivity.

Managers should consider an appropriate combination of the innovation portfolio and R&D investments to make progress and increase performance in the company. In addition, policymakers should consider that investments to promote the development of R&D activities in manufacturing companies will likely lead to médium- or long-term returns.

The correct use of indicators to measure these relationships could help the policymaker to design and measure policy instruments more efficiently.

These results provide a deeper understanding of how the effects of innovations implemented by manufacturing firms, especially service and process innovation, improve their performance.

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 study aims to test the impact of the coronavirus (Covid-19) pandemic on large firms, with regard to a supply disruption, productivity, customer satisfaction and firm performance.

A cross-sectional survey design and stratified sampling technique were implemented for employee selection and data gathering. Confirmatory factor analysis (CFA) was used to examine the data and model fitness, while the structural equation model was used for hypotheses testing.

The pandemic triggered supply disruptions, but did not significantly impact the productivity of manufacturing firms directly. However, supply disruption positively and significantly impacted productivity. Organisational productivity had no significant impact on customer satisfaction, however, when mediating the relationship between Covid-19 and customer satisfaction, it produces a positive indirect effect. Finally, Covid-19 and supply disruption when mediated by organisational productivity both had negative significant relationships on performance.

Having a unique model, it creates a trail for future researchers to explore further. Though customer satisfaction was expected to be affected by the pandemic, it is interesting to find out that customer satisfaction when mediated by organisational productivity was positively influenced.

Disruptions are inevitable, managers must balance the pursuit of customer satisfaction and productivity so that one does not erode the other. Emphasis must be channelled towards managing the productivity of the firm to maintain customer satisfaction during these uncertain times. Deliberate steps like manufacturing flexibility investments should be initiated.

The first study to examine Covid-19, supply disruption, customer satisfaction, organisational productivity and performance in the Nigerian manufacturing sector.

This study empirically assessed the influence of foreign direct investment on the manufacturing sector growth in the Middle East and North African region using panel data of 18 countries covering the period of 1975–2017.

The study employed Levin et al. (2002) test (LLC) and Im et al. (2003) panel unit root test. Furthermore, Kao’s cointegration test was applied to examine the long-run relationship between the variables. Both the Dynamic OLS and Fully modified OLS were used in estimating the short-run relationship.

The results of the DOLS and FMOLS indicate that both inward and outward FDI influence the manufacturing sector growth positively. This shows that much of the manufacturing sector growth in the MENA region is driven by both inward and outward FDI. Our findings made a strong new proposition that aside from the negative influence proposed by Stevens and Lipsey (1992), outward FDI could also have a positive influence on the manufacturing sector of a country through effective utilization of domestic raw materials that are produced locally for production of goods in a foreign country.

MENA countries should concentrate more on making policies that will encourage the effective utilization of domestic resources for outward foreign direct investment in other countries of the world as it has the capacity to boost the manufacturing sector growth. Also, policies that will attract more inflows of FDI in the region should be encouraged. Both inward and outward FDI should be considered as an integral part of MENA economic policy in order to spur the manufacturing sector growth.

Previous empirical studies on the relationship between FDI and manufacturing sector growth have focused much on the influence of inward FDI. Thus, very little attention has been paid to the contribution that the outward FDI makes to the growth of the manufacturing sector of the host country. Our empirical study focused on the influence of both inward and outward FDI on the manufacturing sector growth with specific emphasis on the MENA region that remains the center of attraction of inward FDI and a source of inward FDI to most nonoil producing developing and developed countries given the oil-rich nature of the region.

This study aims to unlock the path of growth for sustainable economic development and accomplish the government's vision 2030 by ameliorating the productivity of the manufacturing sector in Laos.

This study applied cross-sectional data of 2,009 firms from the national firm survey, namely the Economic Census Survey (ECS), in 2012/13 in addition to employing the stochastic frontier analysis (SFA) to assess the production frontier and factors behind the technical inefficiency to arrive at policy recommendations.

The study found that the efficiency level varied across subindustries with an average of 72.51% in full potential production. Out of the five classified groups, Sub4 (chemical and plastic) was found to be the most efficient manufacturer, while the rest in order are Sub1 (food and beverage), Sub5 (furniture and others), Sub2 (garment and textile), and Sub3 (paper and printing), providing the evidence to improve the technical efficiency. This study discovered that the firm's size, accounting system and credit access are crucial to enhancing the production efficiency of all sampling firms. However, these factors might be subject to specific industries.

For the implication to the business community and policymakers, the findings of this study could be a reference in terms of which areas they should concentrate on to improve the technical efficiency as a part of productivity in the manufacturing industry. For instance, it suggests that firms could improve their production efficiency by introducing the accounting system, laborers' skills (education of managers) and engaging in international trade activities. Additionally, it asks policymakers to help private firms by improving the infrastructure, credit access, training and trade facilitation.

It is believed that, as the major contribution in Lao literature, this study is the first research applying the largest data from the national survey – the Lao ECS – examining the technical efficiency in the manufacturing sector in the country, and overcoming the gap of the previous research which recruited few policy variables and applied a small sample size in one specific industry. Therefore, the findings of this study impart more insights into the analysis, providing more effective and credible recommendations to policymakers and firms to improve their technical efficiency and, consequently, their competitiveness.

This paper aims to overcome the inability of both comparing loss costs and accounting for production resource losses of Overall Equipment Effectiveness (OEE)-related approaches.

The authors conducted a literature review about the studies focusing on approaches combining OEE with monetary units and/or resource issues. The authors developed an approach based on Overall Equipment Cost Loss (OECL), introducing a component for the production resource consumption of a machine. A real case study about a smart multicenter three-spindle machine is used to test the applicability of the approach.

The paper proposes Resource Overall Equipment Cost Loss (ROECL), i.e. a new KPI expressed in monetary units that represents the total cost of losses (including production resource ones) caused by inefficiencies and deviations of the machine or equipment from its optimal operating status occurring over a specific time period. ROECL enables to quantify the variation of the product cost occurring when a machine or equipment changes its health status and to determine the actual product cost for a given production order. In the analysed case study, the most critical production orders showed an actual production cost about 60% higher than the minimal cost possible under the most efficient operating conditions.

The proposed approach may support both production and cost accounting managers during the identification of areas requiring attention and representing opportunities for improvement in terms of availability, performance, quality, and resource losses.

This study attempts to examine the missing middle (MM) phenomena in the context of the Indian manufacturing sector using the unit level information from the database of Ministry of Corporate Affair, Government of India.

Unlike the previous studies, the present study first bifurcated the missing enterprises into two categories such as “permanently” dropped and “reappeared,” in order to pursue a meaningful analysis and derive conclusions with policy insights. Various financial indicators were used to explain the causes of MM phenomena during 2009–2010 and 2016–2017, in a logistic framework.

The study found that profit margin ratio is higher for the group of medium sized enterprises which continued in comparison to the units which dropped out permanently. Similar is the case with the ratio of investment turnover. The econometric results, however suggest that the relationship between the chances of a firm being dropped out and financial indicators is weak as the coefficients of various financial indicators are found to be statistically significant only for a few years.

The study suggests that the missing middle phenomenon is not a myth in India as very large number of medium-sized firms have been disappearing from the market over the years. Based on firm level data it identifies the factors which resulted in such a phenomenon.

This study aims to examine the premature deindustrialization risk in Vietnam.

This study uses a manufacturing–income relationship to conduct an empirical estimation. The latecomer index is adopted in the regression model to identify a downward shift of latecomer's relationship.

The empirical analysis indicates that there is a risk of premature deindustrialization in the Northern Midlands and Mountain Areas. The provinces with low trade openness or foreign direct investment may experience risk of premature deindustrialization.

This study proposes technology diffusion as a policy direction to prevent premature deindustrialization. Furthermore, the Vietnamese government should improve the business environment in the Northern Midlands and Mountain Areas by promoting and attracting export-oriented foreign direct investment.

This study is the first to examine premature deindustrialization in Vietnam based on provincial-level data.