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This study aims to validate the link between production manipulation and a firm’s performance variability (fundamentals and stock returns). It explores whether executives' risk-taking incentives encourage production deviations around the normal level during uncertainty.

Utilizing panel data of manufacturing firms from Compustat over three decades, the study investigates production management practices during economic uncertainty. The Economic Policy Uncertainty Index (EPU) is employed as a key metric. The empirical strategy involves documenting the effect of economic uncertainty on overproduction and underproduction, examining the role of executive compensation and assessing the impact on risk.

The research finds that risk-taking incentives increase over/underproduction, particularly amplifying the extent of underproduction during uncertainty. Production deviation rises, indicating that firms take greater risk by engaging in abnormal business operations. The study’s results are robust against various econometric methods, emphasizing the influence of risk-taking incentives on corporate production decisions.

While providing valuable insights, the study acknowledges inherent limitations, including factors influencing production decisions beyond risk-taking incentives. Further research could explore additional determinants for a comprehensive understanding.

The findings highlight the potential dark side of executive compensation that motivates suboptimal risk-taking decisions, impacting risk, cost of capital and firm performance. Policymakers and compensation committees can use these insights to design efficient systems that mitigate moral hazard problems associated with productivity changes.

The study emphasizes the broader social implications of production manipulation under uncertainty. It prompts discussions on the ethical considerations of managerial opportunism, its potential consequences for stakeholders and market dynamics.

This study contributes to the literature by examining the role of economic uncertainty on production manipulation and the influence of risk-taking incentives. It extends the earnings management literature by considering real activity manipulation and emphasizing the importance of decomposing production deviation into positive and negative values.

This study explores the integration of smallholder farmers into the export market in Vietnam, an emerging economy. By introducing a prospective framework, we seek to provide insight into factors that influence this integration process.

This study examines the expected growth and entry of Vietnamese smallholder farmers into high-value export markets. We collected information from 200 independent farmers as well as from five local extension workers, who provided information on 50 farmers.

The study reveals that the adoption of new business models is more influential than the variables traditionally included in models of export-market integration in predicting expected growth and entry into high-value export markets. In addition, the results highlight divergent views between farmers and extension workers regarding the role of collectors, with farmers perceiving collectors as potential partners, while extension workers see them as impediments to growth.

The prospective model presented in this study highlights the importance of policy interventions aimed at promoting new business models and addressing infrastructure and capital constraints for the sustainable transformation of agricultural sectors in emerging markets.

This is one of the first articles to apply a prospective approach to export-market integration and demonstrate its efficacy through an empirical study. The suggested prospective approach could facilitate the design of policies aimed at export-market integration within the context of dynamic, emerging markets.

COVID-19 has affected the economies adversely from all sides. The sudden halt in production has impacted both the supply and demand sides. It calls for analysis to quantify the impact of the reduction in economic activity on the economy-wide variables so that appropriate steps can be taken. This study aims to evaluate the sensitivity of various sectors of the Indian economy to this dual shock.

The eight-sector open economy general equilibrium Global Trade Analysis Project (GTAP) model has been simulated to evaluate the sector-specific effects of a fall in economic activity due to COVID-19. This model uses an economy-wide accounting framework to quantify the impact of a shock on the given equilibrium economy and report the post-simulation new equilibrium values.

The empirical results state that welfare for the Indian economy falls to the tune of 7.70% due to output shock. Because of demand–supply linkages, it also impacts the inter- and intra-industry flows, demand for factors of production and imports. There is a momentous fall in the demand for factor endowments from all sectors. Among those, the trade-hotel-transport and manufacturing sectors are in the first two positions from the top. The study recommends an immediate revival of the manufacturing and trade-hotel-transport sectors to get the Indian economy back on track.

The present study has modified the existing GTAP model accounting framework through unemployment and output closures to account for the impact of change in sectoral output due to COVID-19 on the level of employment and other macroeconomic variables.

The development of green manufacturing has become essential to achieve sustainable development and modernize the nation’s manufacturing and production capacity without increasing nonrenewable resource consumption and pollution. This study investigates the effect of green industrial practices on technical efficiency for Thai manufacturers.

The study uses stochastic frontier analysis (SFA) to estimate the stochastic frontier production function (SFPF) and inefficiency effects model, as pioneered by Battese and Coelli (1995).

This study shows that, on average, Thai manufacturing firms have experienced declining returns-to-scale production and relatively low technical efficiency. However, it is estimated that Thai manufacturing firms with a green commitment obtained the highest technical efficiency, followed by those with green activity, green systems and green culture levels, compared to those without any commitment to green manufacturing practices. Finally, internationalization and skill development can significantly improve technical efficiency.

Green industry policy mixes will be vital for driving structural reforms toward a more environmentally friendly and sustainable economic system. Furthermore, circular economy processes can promote firms' production efficiency and resource use.

To the best of the authors' knowledge, this study is the first to investigate the effect of green industry practices on the technical efficiency of Thai manufacturing enterprises. This study also encompasses analyses of the roles of internationalization, innovation and skill development.

This study aims to examine the impact of Lean 4.0 practices on value co-creation in the dairy ecosystem.

Data collection were carried out through a questionary application with 126 professionals linked to the dairy ecosystem, including milk producers, milk cooperatives and milk transporters. The data were analyzed using Cluster Analysis, Mann-Whitney test and Chi-Square test.

A strong relation was found between the use of Lean 4.0 tools and the increase in operational performance, in addition to milk quality. Moreover, it can be noted that the use of digital technologies from Industry 4.0 has a strong relation with dairy production optimization, in other words, it is possible to be more efficient in the dairy process via Lean 4.0 adoption.

The study is limited to analyzing the Brazilian dairy ecosystem. The results presented may not reflect the characteristics of the other countries.

Once the potential empirical impacts of the relation between Lean 4.0 and value co-creation are elucidated, it is possible to direct strategies for decision-making and guide efforts by researchers and professionals to deal with the waste mitigation present in the dairy sector.

Lean 4.0 proves to be a potential solution to improve the operational performance of the dairy production system. Lean 4.0, linked to value co-creation, allows the integration of the production sector with consumers, through smart technologies, so new services and experiences can be provided to the consumer market. Additionally, the consumer experience can be stimulated based on Lean 4.0, once the quality specification is highlighted based on data science and smart management control.

To the best of the authors’ knowledge, this is the first study that analyzes the interrelationship between the Lean 4.0 philosophy and the value co-creation in the dairy ecosystem. In this sense, the study reveals the main contributions of this interrelation to the dairy sector via value co-creation, which demonstrates a new perspective on the complementarity of resources, elimination of process losses and new experiences for the user through digital technologies integrated with the Lean Thinking approach.

Climate change-related weather events significantly affect rice production. In this paper, we investigate the impact of and interrelationships between agriculture inputs, climate change factors and financial variables on rice production in India from 1970–2021.

This study is based on the time series analysis; the unit root test has been employed to unveil the integration order. Further, the study used various econometric techniques, including vector autoregression estimates (VAR), cointegration test, autoregressive distributed lag (ARDL) model and diagnostic test for ARDL, fully modified least squares (FMOLS), canonical cointegrating regression (CCR), impulse response functions (IRF) and the variance decomposition method (VDM) to validate the long- and short-term impacts of climate change on rice production in India of the scrutinized variables.

The study's findings revealed that the rice area, precipitation and maximum temperature have a significant and positive impact on rice production in the short run. In the long run, rice area (ß = 1.162), pesticide consumption (ß = 0.089) and domestic credit to private sector (ß = 0.068) have a positive and significant impact on rice production. The results show that minimum temperature and direct institutional credit for agriculture have a significant but negative impact on rice production in the short run. Minimum temperature, pesticide consumption, domestic credit to the private sector and direct institutional credit for agriculture have a negative and significant impact on rice production in the long run.

The present study makes valuable and original contributions to the literature by examining the short- and long-term impacts of climate change on rice production in India over 1970–2021. To the best of the authors’ knowledge, The majority of the studies examined the impact of climate change on rice production with the consideration of only “mean temperature” as one of the climatic variables, while in the present study, the authors have considered both minimum as well as maximum temperature. Furthermore, the authors also considered the financial variables in the model.

In this paper, we aim to provide an extensive analysis to understand how various factors influence electricity prices in competitive markets, focusing on the day-ahead electricity market in Romania.

Our study period began in January 2019, before the COVID-19 pandemic, and continued for several months after the onset of the war in Ukraine. During this time, we also consider other challenges like reduced market competitiveness, droughts and water scarcity. Our initial dataset comprises diverse variables: prices of essential energy sources (like gas and oil), Danube River water levels (indicating hydrological conditions), economic indicators (such as inflation and interest rates), total energy consumption and production in Romania and a breakdown of energy generation by source (coal, gas, hydro, oil, nuclear and renewable energy sources) from various data sources. Additionally, we included carbon certificate prices and data on electricity import, export and other related variables. This dataset was collected via application programming interface (API) and web scraping, and then synchronized by date and hour.

We discover that the competitiveness significantly affected electricity prices in Romania. Furthermore, our study of electricity price trends and their determinants revealed indicators of economic health in 2019 and 2020. However, from 2021 onwards, signs of a potential economic crisis began to emerge, characterized by changes in the normal relationships between prices and quantities, among other factors. Thus, our analysis suggests that electricity prices could serve as a predictive index for economic crises. Overall, the Granger causality findings from 2019 to 2022 offer valuable insights into the factors driving energy market dynamics in Romania, highlighting the importance of economic policies, fuel costs and environmental regulations in shaping these dynamics.

We combine principal component analysis (PCA) to reduce the dataset’s dimensionality. Following this, we use continuous wavelet transform (CWT) to explore frequency-domain relationships between electricity price and quantity in the day-ahead market (DAM) and the components derived from PCA. Our research also delves into the competitiveness level in the DAM from January 2019 to August 2022, analyzing the Herfindahl-Hirschman index (HHI).

The research objective of this paper is to investigate the direct and indirect impacts of green finance on agricultural carbon total factor productivity (ACTFP) within the framework of the carbon peaking and carbon neutrality (dual carbon) goals, while also identifying the driving factors through an exponential decomposition of ACTFP, aiming to provide policy recommendations to enhance financial support for low-carbon agricultural development.

In this paper, the Global Malmquist Luenberger (GML) Index method was employed to analyze and decompose the ACTFP, while the direct and spillover effects of China’s green finance pilot policy (GFPP) on ACTFP were assessed using the difference-in-differences (DID) method and the spatial differences-in-differences (SDID) method, respectively.

After the implementation of the GFPP, the ACTFP in the pilot area has experienced significant improvement, with the enhancement of technical efficiency serving as the main driving force. In addition, the GFPP exhibits a positive low-carbon spatial spillover effect, indicating it benefits ACTFP in both the pilot and adjacent areas.

Within the framework of the dual carbon goals, the paper highlights agriculture as a significant carbon emitter. ACTFP is assessed by considering the agricultural carbon emission factor as the sole non-desired output, and the impact of the GFPP on ACTFP is investigated through the DID method, thereby providing substantial validation of the hypotheses inferred from the mathematical model. Subsequently, the spillover effects of GFPP on ACTFP are analyzed in conjunction with the spatial econometric model.

The purpose of this paper is to define the local integration rate and how it is calculated to assess its relevance as a national performance indicator for the Moroccan automotive industry.

The research methodology first followed a systematic review approach through the analysis of published research articles and academic works. This study then followed a qualitative approach based on semi-structured interviews with various actors in the Moroccan automotive industry. Finally, the findings of this work were reinforced by a case study to analyze the supply chain of a locally produced vehicle.

The results indicate that the local integration rate as calculated today overestimates the performance of the automotive industry and does not systematically guarantee a significant creation of value added.

Due to the confidentiality of the data in terms of turnover, payroll and purchase prices as well as the large number of suppliers in the different supply chains of the car manufacturer, the case study focused on only one of the six existing ecosystems.

On the basis of research work on the Moroccan automotive industry as well as interviews with various actors, the local integration rate is unanimously considered as a viable performance indicator. This study has not only led us to the method of calculating this rate by the Ministry of Industry but also demonstrated its limitations while proposing a new method of calculation to increase the value added.

This study aims to explore the diverse sources of electricity generation (coal, natural gas, oil and hydroelectricity) and their respective associations with economic growth and environmental quality.

This study uses static panel data analysis with a random effects model for six selected ASEAN countries (Indonesia, Malaysia, Filipina, Thailand, Vietnam and Myanmar) from 1994 to 2014.

This study reveals that economic growth in six selected ASEAN countries is enhanced by electricity generation from all sources, while the contribution of electricity production from hydroelectricity remains the largest and strongest. There is no environmental impact of electricity production from hydroelectric, whereas fossil fuel-based electricity production emits carbon dioxide, with coal sources being the largest contributor, followed by natural gas and oil.

Based on the results, these six ASEAN countries should invest more in hydropower projects, reduce the coal mix in power generation and promote clean coal technology to improve economic efficiency and environmental sustainability.

To the best of the authors’ knowledge, no research has examined the relationship between electricity production, environmental quality and economic growth in Southeast Asian nations. Therefore, the outcome of this study is expected to provide insightful results to supplement the framing and implementation of national and collective regional strategies for sustainable electricity generation in ASEAN countries.