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Promoting the coordinated development of digitalization and greening has become an important pathway for firms to achieve high-quality growth. Using panel data for A-share listed firms in China’s Yangtze River Basin from 2010 to 2022, this study examines the effect of supply chain innovation policy on firms’ digital–green development. We measure the synergy between digitalization and greening using a composite system synergy approach and identify the policy effect through a quasi-natural experiment based on the supply chain innovation policy, combined with a synthetic difference-in-differences model. The results show that the policy significantly improves the coordinated development of firm digitalization and greening, and the findings remain robust across a series of tests. Mechanism analysis indicates that this effect operates through three channels: easing financing constraints, increasing supply chain diversification, and promoting industrial chain modernization. Moderating effect tests further show that supply chain efficiency, supply chain resilience, and entrepreneurship strengthen the policy’s positive effect on digital–green development. Heterogeneity analysis suggests that the policy effect varies systematically with firm size, market competitiveness, and information asymmetry. This study provides micro-level evidence on how supply chain innovation policy can promote firms’ digital–green transformation and offers useful implications for policies aimed at improving firm competitiveness and supporting sustainable development.

As the advanced productivity of the traditional productivity butterfly, the new quality productivity is the core driving force to promote the transformation and upgrading of the whole chain of key industries, and it is also the important material and technological basis for realizing the Chinese modernization. This paper constructs a new quality productivity evaluation index system by selecting 20 specific indicators from the three dimensions of scientific and technological innovation, industrial upgrading and development conditions of financial new quality productivity, and measures the development level of China’s financial new quality productivity from 2008 to 2022. On this basis, the entropy weight Topsis method, Dagum’s Gini coefficient and β-convergence were further applied to analyze the regional differences in the development of financial new quality productivity and the convergence of the development level. Based on this, the panel data of Chinese provinces are used as the research samples, and various econometric models are constructed to empirically investigate the relationship between the new financial productivity and the modernization of the rural industrial chain supply chain as well as the mechanism of the role of the new financial productivity. It is found that the development level of financial new quality productivity in China and the four major regions is on an upward trend, and the differences between and within groups in China and the four major regions are on a decreasing trend, and the changes in the overall differences mainly depend on the inter-regional differences. Meanwhile, the development level of financial new quality productivity in China and the four major regions is characterized by β-convergence, but there are differences in the speed of convergence. The empirical test concluded that financial new quality productivity has a positive promotion effect on the modernization of the rural industrial chain supply chain.

IntroductionChina’s fisheries industry chain (FIC) modernization faces bottlenecks such as weak infrastructure, insufficient regional coordination, and limited resilience, with prominent issues of uneven regional development. However, there is currently a lack of systematic research on its regional disparity patterns and dynamic evolution mechanisms. This research gap restricts the in-depth understanding of high-quality fisheries development pathways and the formulation of effective policies.MethodsTo systematically reveal the regional differentiation and evolution laws of the modernization level of China’s FIC, this study constructed a comprehensive evaluation index system covering four dimensions: foundation, resilience, coordination, and sustainability. Based on panel data from 27 provinces in China from 2016 to 2023, it comprehensively applied methods including the entropy weight method, Dagum Gini coefficient, Local Moran’s I, kernel density estimation, and spatial Markov chain to conduct multi-dimensional analysis of the modernization level, regional differences, spatial correlation, and dynamic evolution of the FIC.Results and discussionThe results show that: (1) The national modernization level of the FIC has steadily improved but with fluctuations, and the development of each dimension is unbalanced; (2) The overall regional differences show a narrowing trend, and inter-regional differences are the main source; (3) The modernization level of the FIC exhibits significant positive spatial agglomeration; (4) The modernization level of the FIC presents a stepped distribution of “Eastern China > Central China > Western China”; (5) The hierarchical structure of the modernization level of the FIC is generally stable, with a low possibility of cross-level transfer, and high-level regions have a positive spatial spillover effect on adjacent regions.Research significanceTheoretically, this study constructs a comprehensive evaluation framework for the modernization of the industrial chain applicable to the fishery field, providing methodological reference for related research. Practically, it accurately identifies the sources of regional differences and the mechanism of spatial dependence, offering empirical basis for optimizing regional resource allocation, formulating differentiated coordination policies, and promoting high-quality and sustainable development of the fishery industry. It also provides reference value for other developing countries in advancing the modernization of the agricultural industrial chain.

The digital economy is an important way to relieve current pressure on resources and the environment. Based on ecological modernization theory and global value chain theory, this paper adopts panel data of 17 manufacturing industries from 2000 to 2014, uses the non-radial directional distance function and the meta-frontier method to measure China’s green total factor productivity (GTFP) and its sub-indices, and takes the embedding degree and embedding position as moderating variables and threshold variables to construct an econometric model to explore the relationship among the digital economy, global value chain, and GTFP. The results show that (1) the digital economy has a positive effect on GTFP in both time and space. And in terms of time, the digital economy mainly enhances GTFP by improving technical efficiency and narrowing the technology gap. (2) Global value chain embedding position positively moderates the relationship between the digital economy and GTFP; In terms of sub-samples, labor-intensive and capital-intensive industries show the same impact characteristics as the total sample. (3) Further, it is found that the digital economy and GTFP have nonlinear characteristics. There is a single threshold effect on the embedding position. When the embedding position is low, the digital economy is positively correlated with GTFP but not significant; when the threshold value is crossed, the digital economy can significantly promote GTFP. The conclusions of this paper are helpful to realize the digital economy to promote the green development of the manufacturing industry, and provide an effective reference for the realization mechanism of China’s green economy transformation and ecological civilization construction in the post-pandemic era.

In developing countries, promoting sustainable income growth for farmers is a major priority. This study constructs an evaluation index system for the whole agricultural industry chain from the perspective of synergy among the innovation chain, supply chain, value chain, and capital chain. It also empirically tests the enabling mechanisms and spatial effects of the whole agricultural industry chain on farmers’ income. The entropy value method was used to measure the development level of the whole agricultural industry chain. Two-way fixed effects, mediation effects, and spatial Durbin models were applied to investigate the impacts, mechanisms, and spatial characteristics of the whole agricultural industry chain on farmers’ income. The whole agricultural industry chain significantly promotes farmers’ income growth, with the expansion of the non-agricultural employment scale and the improvement of urbanization levels serving as the main pathways through which the whole agricultural industry chain drives increases in farmers’ income. The heterogeneity analysis reveals that the innovation chain and capital chain contribute the most prominent marginal effects; the effect intensity of the whole agricultural industry chain on farmers’ income presents a spatial gradient pattern of “Central > Western > Eastern”; and its income-increasing effect is more noticeable for middle- and low-income farmers, demonstrating significant pro-poor characteristics. Further analysis indicates that the whole agricultural industry chain exerts a significant positive spatial spillover effect on farmers’ income. Therefore, it is essential to optimize the layout of the whole agricultural industry chain, smooth the transmission channels of non-agricultural employment and urbanization, and enhance the benefit linkage mechanism targeting middle- and low-income farmers.

Over the last few years, the world has been facing dramatic changes due to a condensed period of multiple crises, including climate change, the COVID-19 pandemic, and the Russian–Ukrainian war. Although different, these consecutive crises share common characteristics (e.g., systemic shocks and non-stationary nature) and impacts (e.g., disruption of markets and supply chains), questioning food safety, security, and sustainability. The current article analyses the effects of the noted crises in the food sector before proposing target mitigation measures to address the different challenges. The goal is to transform the food systems to increase their resilience and sustainability. This goal can only be achieved if all relevant actors within the supply chain (e.g., governments, companies, distributors, farmers, etc.) play their role by designing and implementing target interventions and policies. In addition, the transformation of the food sector should be proactive concerning food safety, circular (valorizing several bioresources under the principles of climate neutral economy and blue bioeconomy), digital (based on Industry 4.0 applications), and inclusive (ensuring that all citizens are actively engaged). Food production modernization (e.g., by implementing emerging technologies) and developing shorter and more domestic supply chains are also critical to achieving food resilience and security.

Unexpected instances have posed challenges to production lines over the last few years. The latest COVID-19 global epidemic is one notable example. In addition to its social impact, the virus has destroyed the traditional industrial production system. Industry 4.0 requires adapting to changing prerequisites with adaptability. However, the next movement, Industry 5.0, has emerged in recent years. Industry 5.0 takes a more coordinated approach than Industry 4.0, with increased collaboration among humans and machines. With a human-centered strategy, Industry 5.0 improves Industry 4.0 for greater sustainability and resilience. The concept of Industry 4.0 is the interconnection via cyber-physical systems. Industry 5.0, also associated with systems enabled by Industry 4.0, discusses the relationship between “man and machine,” called robots or cobots. This paper discusses the industry 5.0 possibilities, the restrictions, and future analysis potentials. Industry 5.0 is a new paradigm change that tends to bring negotiated settlement because it places less prominence on technology and assumes that the possibilities for advancement are predicated on collaboration between humans and machines. This paper aims to examine the potential implementations of Industry 5.0. Once the current progress and problem were discovered, the previous research on the investigated topic was reviewed, research limitations were found, and the systematic analysis procedure was developed. The classifications of industry 5.0 and the sophisticated technology required for this industry revolution are the first subjects of discussion. There is additional discussion of the application domains enabled by Industry 5.0, such as healthcare, supply chain, production growth, cloud industrial production, and so on. The research also included challenges and problems investigated in this paper to understand better the issues caused by organizations among some robotic systems and individuals on the production lines.

Aquaculture is a growing industry with an annual growth rate that is far superior to the population growth rate. Most production occurs in lower‐ and middle‐income countries, and therefore, they can improve the efficiency and modernize the production systems to increase exports to earn foreign exchange earnings for economic and social development. The institutional arrangements should be part of the mechanisms that ensure sustainable aquaculture growth, through the participation of all stakeholders. Sustainability is possible with good and dynamic governance through which the industry embraces the basic principles of governance, equity, accountability, efficiency, and predictability. Over the past decade, several countries made changes in governance and implemented regulations through their action plans to improve aquaculture productivity, and stakeholders profited from the changes made along the value chain. For the producers to benefit from the value‐added products, they complied with the regulations imposed by the importing countries, international regulatory bodies, or their own consumers. Standards increased, and the implementation of certification resulted in changes in the industrial structure. These standards, which inflict regulatory cost on producers, stimulated an improvement in productivity and product quality. However, during the last decade, production growth declined from 5.8% from 2001 to 2010 to 4.5% from 2011 to 2018, resulting in the elusive realization of the potential of meeting the sustainable development targets. There is a need for a paradigm shift that encourages small‐scale producers to engage in sustainable intensive aquaculture. The challenge is, therefore, to move toward production intensification and expansion, and the harmonization of national and international regulations to ensure the supply of safe and adequate fish to consumers, while maintaining a sustainable production system, and at the same time conserving the environment and maintaining social and economic stability. With good governance and political will, the social, economic, and environmental objectives for attaining the Sustainable Development Goals during the period 2020–2030 are possible if governments integrate sustainable aquaculture developments within an expanded aquatic and terrestrial food security policy framework using systems thinking and open innovation approaches.

The environmental and construction legislations are not modernized to control the adverse impacts of construction activities in Bangladesh. A large volume of Construction and Demolition (C&D) waste and carbon are annually released from this sector. This research was undertaken to investigate the Green Supply Chain Management (GSCM) practices and its implications during the implementation in constructions. Three construction industries and three related material manufacturers were selected for case study, and thirty industries combing both categories were investigated through questionnaire survey to unravel current GSCM practices, and its challenges and effect on constructions. Results revealed that market (76.67%) and supplier (91.03%) pressures promoted GSCM practices in construction industries, additionally internal factors played significant role (74.44%), whereas 60% regulations as external pressure. As GSCM elements, green manufacturing (90.83%), green purchasing (85.83%), internal environmental management (82.5%), investment recovery (86.66), and eco-design (93.33%) respondents agreed to improve the construction industry to reduce C&D waste and carbon emission. About 89% and 79% respondents acknowledged the environmental and economic performances, respectively improved by GSCM practices. Furthermore, 70–90% respondents opined financial/technical/human application as key barriers in GSCM practices. Finally, the GSCM practices reduced C&D waste and carbon emissions; however, it was not maintained regularly and strictly.

The integrated development of rural industries is a primary method to accelerate rural revitalization, a practical path to promote agricultural and rural modernization, and an important means to build a strong agricultural nation. Based on the super-efficiency EBM model, rural industrial integration efficiency in the east, central and west regions of 31 provinces (municipalities and autonomous regions) in China from 2012 to 2022 is measured, and the spatial differentiation, dynamic distribution and influencing factors of rural industrial integration efficiency are analyzed by using Dagum Gini coefficient, Kernel density estimation and Tobit model, respectively. The study shows that the core driving forces of rural industrial integration efficiency in the east, central and west regions are pure technical, comprehensive and pure technical efficiency, respectively; hyper-variable density is the main source of spatial differentiation; serious divergence in rural industrial integration efficiency in the east; there is regional heterogeneity in the impact of different factors on the efficiency of rural industrial integration. It is necessary to strengthen the structure of financial inputs, establish an efficiency assessment system, and enhance the infrastructure and public services.