The coordinated development of food security and agricultural carbon emission efficiency is a key sustainable agriculture goal. However, the mechanisms remain unclear amid large-scale urban-rural integration, especially with rapid artificial intelligence (AI) advancement. Leveraging panel data from China spanning 2010-2023, a coupled coordination model is employed to evaluate regional coupled coordination development (CCD) between food security index (FSI) and agricultural carbon emission efficiency (ACEE). The relationship between urban-rural integration (URI) and CCD, along with AI's moderating effect, is analyzed using two-way fixed effect, moderated effect, difference grouping, and threshold regression models, thereby establishing an "AI-URI-FSI-ACEE" analytical framework. Coordinated development paths are identified via dynamic qualitative comparative analysis, examining technology, agricultural conditions, social environment, and policies. Research findings: URI significantly promotes CCD with long-term effects. further amplifies this effect, particularly in regions characterized by major production areas, low economic development levels, and robust policy support. As AI progresses, urban-rural spatial, economic, and social integration further enhances CCD, while ecological integration exhibits a transition from hindering to facilitating CCD. Under scenarios prioritizing FSI, the promotional effect of URI significantly intensifies, with greater priority yielding stronger promotion effects, while AI exerts a pronounced positive moderating influence. Under scenarios prioritizing ACEE, the promotional effect exhibits a diminishing trend until it becomes insignificant. Although AI shows no significant main effect, it continues to play a crucial moderating role by empowering the URI process. Four typical paths emerged: market-driven AI efficiency enhancement pathways, insurance-backed stable production and efficiency improvement pathways, domestic circulation-oriented ecological intensification pathways, and policy-coordinated comprehensive safeguarding pathways. Differences exist among these policy priority pathways. This research provides policymakers with references for adopting tailored strategies to achieve a win-win outcome of food security and low-carbon development.

The development of China’s marine food production system is receiving increasing attention, as its developmental level and obstacle factors will profoundly impact the nation’s future food security and nutritional supply. This study establishes a theoretical framework for evaluating the development level of marine food production systems based on three dimensions—resources, benefits, and governance—structured around the logical framework of “exogenous safeguard, endogenous drive, goal oriented”. First, a three-tier coding method based on grounded theory was employed to construct a Chinese marine food production system evaluation framework encompassing 28 specific indicators. Subsequently, a comprehensive weighting of these indicators was achieved by integrating fuzzy comprehensive evaluation with the entropy weighting method. Finally, based on the evaluation results and obstacle degree modeling, a comprehensive assessment study was conducted on 11 coastal provinces and cities, focusing on developmental level investigation and obstacle factor analysis. The results indicate that China’s marine food production system development level exhibits a trend of slow, fluctuating growth overall, maintaining an average annual growth rate of 3.23%. However, significant differentiation characteristics are emerging, with high regional heterogeneity and substantial variation in obstacle factors. Currently, the main constraints hindering the development of the marine food production system are insufficient human resource supply, uneven production resource distribution (higher in the north, lower in the south), and intensified fluctuations in comprehensive output. Finally, this study proposes three strategic recommendations: ecological restoration coupled with strict controls, comprehensive restructuring of the human resource support system, and establishing a multi-scale comprehensive evaluation mechanism. These strategies aim to disrupt the transmission mechanisms of different obstacle factors and accelerate the rapid development of the marine food production system.

Generative AI and agentic systems are reshaping platform competition and its long-run welfare consequences. Existing research, however, does not explain why similar AI interventions can produce concentration, costly quality races, cyclical repricing, and different welfare outcomes. A dynamic model distinguishes traditional consumers from AI-mediated consumers and characterizes adoption thresholds, recommendation-driven quality boundaries, price-feedback bifurcations, and welfare across long-run regimes. AI adoption interacts with network effects to narrow the range of stable symmetric competition. Recommendation amplification lowers the threshold for asymmetric quality states and causes profit-eroding quality competition to arise earlier. Price feedback can generate stable local cycles around the symmetric state and resilience thresholds around asymmetric leadership states. When quality and price feedback coexist, more dispersed or more active competition need not improve the model-implied welfare measure. Subject to the focal-episode assumptions, the model identifies adoption, recommendation amplification, and price feedback as distinct sources of regime divergence. It thereby explains why otherwise comparable AI-platform environments can develop different market structures and welfare rankings.

Digital-agriculture programmes are increasingly central to public-sector modernization, but governments cannot usually roll them out everywhere at once. This article examines Vietnam as a territorially heterogeneous planning case and asks how public agencies can stage provincial rollout when productivity opportunity, equity need, low-greenhouse-gas (low-GHG) baseline advantage, and implementability do not peak in the same places. The study develops an ex-ante decision-support framework that links baseline forecasting, multi-criteria decision analysis (MCDA), exact 0–1 integer-programming portfolio selection, and regret diagnostics under weight uncertainty. The framework is not an ex-post causal evaluation of concrete policy packages; rather, it provides a transparent sequencing architecture for bounded public allocation. The results show that a neutral Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) baseline produces a territorially mixed priority set rather than a single readiness block, while feasibility-constrained optimization expands the selected frontier from 23 provinces under the narrow B0 envelope to 37 under B1 and 48 under B2. Robustness checks based on Dirichlet weight draws, rank-reversal tests, alternative feasibility proxies, and alternative MCDA methods show that the broad sequencing logic is not driven by one arbitrary weight vector or one isolated readiness proxy. The contribution is a practical public-sector planning framework for converting spatially misaligned objectives into defensible rollout tiers under administrative constraints.

PurposeDigital technology adoption has become an important means for manufacturing firms to manage the supply chain by enhancing information processing and cross-firm coordination. However, it remains underexplored how firms' digital agility supports green supplier integration under dynamic environments. Based on dynamic capability theory, this study examines the relationship between digital agility and green supplier integration.Design/methodology/approachUsing survey data from 223 manufacturing firms in China, we conduct hierarchical regression and bootstrapping to examine the effect of digital agility on green supplier integration, the mediating role of supply chain traceability and the moderating role of market turbulence.FindingsThe results indicate that digital agility is positively associated with green supplier integration and that supply chain traceability mediates the relationship between digital agility and green supplier integration. In addition, market turbulence strengthens the positive relationship between digital agility and supply chain traceability.Originality/valueThis study advances research on the antecedents of green supplier integration in the era of digitalization by shifting focus from technology adoption to digital agility as a dynamic capability. By revealing that digital agility relates to green supplier integration through enhanced supply chain traceability, the study provides a nuanced theoretical perspective for understanding how digitalization affects green supplier integration. By identifying market turbulence as a boundary condition for the digital agility-traceability link, the study extends the understanding of when digital agility is more likely to translate into supply chain traceability.

This study examines how green organizational practices influence employees' pro-environmental behaviors. It further investigates the roles of environmental awareness and green advocacy in Moroccan organizations. A quantitative cross-sectional study was conducted with the employees working in various organizations in Morocco. Data were analyzed using SmartPLS 4 and IBM SPSS Statistics version 23 to assess relationships among green leadership, CSR, and employee behaviors. The findings indicate that green transformational leadership, CSR-e, and green empowerment significantly influence employee pro-environmental behavior. Environmental awareness also significantly mediated the effects of CSR and green leadership on employee sustainability actions. Organizations can adopt targeted incentives and educational initiatives to foster environmental awareness and green advocacy. Consequently, a more sustainable workplace culture can be established. In addition, this study provides empirical evidence regarding the effectiveness of green workplace practices in Morocco. The study provides insights into leadership and CSR strategies to enhance employees' sustainability efforts.

As China continues to develop its marine resources, marine carbon emissions and their efficiency have become a focal point and risk of growing concern within both economic and environmental systems. However, due to the complexity of marine economic systems and the unique nature of marine carbon sink functions, existing research in this area remains limited and incomplete. We took 11 coastal provinces and regions in China as the research object, conducted carbon sink accounting and marine economic input-output analysis to precisely calculate marine carbon emissions (MCE) in China's coastal areas, and further analyzed marine carbon emission efficiency using the super-efficiency slacks-based measurement (SBM) model. The results show that the total MCE is decreasing year by year, with the tertiary sector replacing the secondary sector as the largest emission source. However, there is significant regional disparity in development, and the carbon sink function is showing a declining trend. A combined analysis of MCE and MCEE reveals that the two dangerous emission patterns—high-carbon-low-efficiency and low-carbon-low-efficiency—are primarily concentrated in the Bohai Rim region. The main causes of this phenomenon include industrial overcapacity, outdated industrial models, insufficient technological updates, lagging ecological protection, and inadequate resource endowments. Based on the endowments and limitations of different regions, we recommend promoting the sustainable development of China's marine carbon emissions through regional task division, setting MCEE red lines, and fully leveraging the regulatory roles of technology markets and carbon trading markets.

Food production and farmers' incomes are the most scrutinized topics in China's development, especially in the context of climate change, farmers' food production and farm incomes are under attack. there are new challenges to continue to safeguard farmers' incomes and yields from the perspective of agricultural production, and Climate-Smart Agriculture technology (CSAT) offers the possibility to address this dilemma, which is crucial for achieving sustainable agricultural development. Focusing on the Climate-Smart Agricultural Technology Practices (CSATP) program in China, this study explores the impact of CSATP on farmers' incomes and yields using a difference-in-difference (DID) methodology with a unique panel dataset collected from a research study conducted in Anhui Province, China. The results show that farm households in the study area that adopted CSATP experienced a significant increase in income and yield, a result that still holds after applying robustness tests such as propensity score matching(PSM). Further exploration of the mechanisms and heterogeneity reveals that CSATP can increase farmers' willingness to cultivation food crops and cash crops, and thus increase their farm income, which is more significant for large-scale and experienced farmers, and that the combination of both technologies in CSATP can increase farmers' food production, which is more effective among small-scale and inexperienced farmers. Based on the results of the empirical study, this study proposes several technology recommendations at three levels: technology application, technology design and technology diffusion. The findings contribute to a better understanding of the impact of CSATP on farmers' income and yield and its mechanism of action in China, complement the gaps in related research.

Many antecedents of radical green innovation (RGI) have been documented independently, without considering their synergistic effects. Combining the configurational approach with resource orchestration theory, this study explores the configurations of realizing RGI by considering environmental and resource factors. Drawing upon data on 332 manufacturing firms in China's strategic emerging industry and using fuzzy-set qualitative comparative analysis (fsQCA), we determine that combining environmental pressures and resource strategies can promote RGI. We find that three configurational patterns lead to high RGI, including "market-exploratory", "regulatory-exploitative", "dual pressure-ambidexterity", and three configurational paths lead to non-high RGI. This study complements and extends existing RGI literature from the configurational perspective, enriches the understanding for shaping RGI based on resource orchestration theory, and has important implications for managerial practice.

The study is based on the exploration of the strength of green external motivation and green autonomous motivation on the pro-environmental behaviours (PEBs) by organization members in Morocco. It explores three specific aspects of PEBs of employees of Morocco organization. The study followed a mixed methodology where a mixture of survey and country-based statistics were sourced for implementation of structural equation modelling (SEM) and long-short memory network (LSTM). Through the integration of both approaches, the study uncovered direct relationships between green autonomous and green external motivation with pro-environmental behaviours in three dimensions: green idea generation behaviour, green idea activation behaviour and green idea promotion behaviour. Along with this, the study also implied the significant mediating role of moral reflectiveness and co-worker environmental efficacy and significant moderation of organizational tenure only for moral reflectiveness and insignificance for co-worker environmental efficacy. With these findings, it highlighted the beneficiary role of green motivation irrespective of organizational tenure, a significant predictor of pro-environmental behaviour. Furthermore, the study justified the resilient setting of SDT theory and offered many useful suggestions for the theoretical and practical field.

Climate change and extreme weather threaten food security and farmers' livelihoods in several regions, and are increasingly affecting production. Climate-smart agriculture (CSA) approaches, which attempt to strike a balance between food security, climate change resilience, and agricultural carbon emissions, have achieved significant results in many parts of the world but are still in urgent need of replication in China. In this study, we developed a protector-victim-perpetrator (PVP) analytical framework to analyse the complex links between climate change and agricultural production for the first time and constructed the first climate-smart agriculture development index (CSADI) in China through a modified GPCA-EWM methodology. The evaluation results showed that the CSA development level in most provinces and regions in China continuously improved from 2010 to 2020 but that the overall level was still low, with only four provinces and regions reaching a highly distinct level. The development level of climate-smart agriculture in China was constrained by the insufficient adaptation of agriculture to climate change, the overreliance of most regions on the innate advantages brought about by resource endowment, and the lack of acquired management and protection. Food security was often negatively correlated with agricultural carbon emissions, but the potential for reducing carbon emissions was quite limited, with ecological degradation and livestock overload in Tibet being of particular concern. In summary, mitigating agricultural carbon emissions by improving adaptability, drawing a bottom line for natural resource protection, popularising climate-smart agricultural technologies, and cross-regional integrated ecological management will help enhance the development of climate-smart agriculture in China.

Owing to the contradiction between agricultural production and environmental development, the issues of food security and carbon mitigation cannot be isolated, and achieving coupled and coordinated development is the key to agricultural sustainability. This study adopted the coupled coordination model and dynamic qualitative comparative analysis (dynamic QCA) method to measure the coupled coordination degree (CCD) of the food security index (FSI) and agricultural carbon emission efficiency (ACEE) in 31 provinces of China from 2010 to 2021, seeking paths to achieve high coupled coordination from Climate-Smart Agriculture technology, external environment, and incentive dimensions, and simulating path selection differences under various CSA priority scenarios. The results indicated that the CCD of the FSI and ACEE in China significantly increased year-on-year increase, with significant regional differences primarily reflected in the Northeast > East > West > Central regions. Based on the CSA orientation, the "technology-environmental safeguard" linkage path and the "technology-environment-incentive" hybrid path are proposed. There are differences in CSA practices across regions, which require customization based on their unique socioeconomic, ecological, and political landscapes. When priorities favour food security, the "technology-environment-incentive" hybrid pathway supports high CCD, and as priorities increase, the contribution of CSA technologies, centred on water-saving irrigation, increases and the role of the external environment diminishes. When the priority tendency is to mitigate emissions, both paths can achieve high CCD. As the priority tendency for carbon emissions increases, urbanisation and CSA technologies such as water-saving irrigation and straw return become essential factors contributing to higher coupling coordination, and the role of agriculture-related financial expenditures diminishes. These findings provide policy support for safeguarding food security and low-carbon agriculture.

Organizations have widely begun to adopt remote working since the COVID-19 pandemic. However, the effect of remote work on team performance remains unknown. A multi-layer interaction system based on organizational systems theory was designed to assess how remote working affects team performance. Individual performance was computed using a positively skewed stochastic performance model and a modified NK model was used to simulate the team performance under specialized and collaborative conditions. The results showed a complex relationship between task complexity and remote rate and that collaborative teams require a higher remote rate when the probability of employees benefiting from remote work is low to avoid potential detriments from excessive competition. Further results considering agent heterogeneity suggest that individual-level gains are magnified or reduced at the team level and that assessing individual heterogeneity and task complexity is sig-nificant for designing remote strategies. In addition, differential mechanisms in team structure and the hierarchy of authority are discussed. This study presents the design and application of a novel business system that helps teams make optimal remote decisions in addition to responding to conflicting discussions in the literature and in practice and providing new insights into decision-making systems in a digital context.

Despite numerous enterprises embracing crowdsourcing to access several innovative solutions, the prevalence of information asymmetry among different participants has led to an increase in the submission of low-quality solutions and payment disputes. To improve the efficiency of crowdsourcing solutions for innovation, this study aims to employ an evolutionary game model to capture the dynamic interaction and decision-making process of the requesters, platforms, and solvers. Initially, we dissect the relevant factors influencing the behavioral decisions of participants to construct a tripartite evolutionary game model. Subsequently, we analyze five potential evolutionarily stable strategies and conditions. Ultimately, we simulate the dynamic evolution of participant decision-making behavior and the sensitivity of related parameters. The simulation results depict that the initial selection probabilities of populations bear no correlation to the system stability, which only influences the time required to reach equilibrium. The participant's behaviors are affected by price, loss, penalty, compensation, cost, and reputation recognition. Reward and punishment mechanisms help effectively mitigate the emergence of free-riding and collusion. These findings provide important implications for the sustainable development of crowdsourcing solutions for innovation.

Carbon emissions pose a significant challenge to sustainable development, particularly for China, which is the world’s largest emerging economy and is under pressure to achieve carbon neutrality and reduce emissions amid escalating human activities. The variation in economic development levels and carbon sequestration capacities among its provinces poses a significant hurdle. However, previous research has not adequately examined this dual discrepancy from the perspective of spatial heterogeneity, resulting in a lack of differentiated management of forest carbon sinks across diverse regions. Therefore, to mitigate this discrepancy, this study presents an assessment methodology that analyzes over 100 types of natural and plantation forests using forest age and biomass expansion factors. This study presents a model that can significantly support the efforts of both China and the whole world to achieve carbon neutrality through the improved management of forest carbon sinks. This approach facilitates the assessment of carbon offsets required to meet reduction targets, the development of a provincial framework for carbon intensity and sequestration, and the exploration of their potential for trading markets. Analysis is conducted using MATLAB. Key achievements of this study include the following: (1) The collection of a comprehensive carbon stock dataset for 50 natural and 57 plantation forest types in 31 provinces from 2009 to 2018, highlighting the significant role of new forests in carbon sequestration. (2) The development of a provincial carbon status scoring system that categorizes provinces as carbon-negative, carbon-balancing, or carbon-positive based on local forest sink data and carbon credit demand. (3) The formulation of the carbon intensity–carbon sink assessment (CISA) model, which suggests that provinces with middle- to upper-middle-level economies may have a prolonged need for carbon sink credits during their peak carbon phase. Furthermore, the results show that carbon trading may benefit Guangxi and Yunnan, but may also bring opportunities and risks to Hunan and Hubei. To address regional imbalances, this study advocates tailored policies: carbon-negative and carbon-balancing provinces should enhance carbon sink management, while carbon-positive provinces must focus on energy structure transformation to achieve sustainable development goals.

Seeking a balance between food security and carbon mitigation is key to achieving sustainable agricultural development. This study evaluates the coupling coordination degree (CCD) between the food security index (FSI) and agricultural carbon emission efficiency (ACEE) in China from 2010 to 2021 using the coupled coordination model. By adjusting the model coefficients, different government priority scenarios are simulated to explore their impact on CCD. The Geodetector method is employed to identify the influencing factors of CCD, investigate their interactions, and assess the differences in these factors across various government priority settings. The average CCD between FSI and ACEE exhibits a notable upward trend, rising from 0.4583 in 2010 to 0.6595 in 2021. Furthermore, regional disparities are widening, particularly in the major production areas. Catch-up effects exist within regions. Policy simulations showed staged interactions between food security and agricultural carbon efficiency, shifting from food security to balanced production and ecology, then to prioritizing low-carbon production for food security. Adjusting policy priorities can effectively improve coupling coordination in the short term, with increasing impact as priority shifts. CCD is influenced by policy, technology, economy, and society, varying with policy priorities. In the baseline scenario, key factors for CCD include the urban-rural income gap, technological advancement, urbanization, and farmers' education level. When the government prioritizes food security, the impact of narrowing income gaps and agricultural industry agglomeration becomes more pronounced. Conversely, emphasizing carbon emission efficiency enhances the influence of technological advancements and urbanization on CCD. Tailoring agricultural production strategies to local conditions and emphasizing interactive effects among factors is crucial for achieving environmentally friendly and high-quality agricultural development goals.

The world faces several problems related to natural gas resource rents and energy production from renewable sources. One of the main problems is the influence of energy imports, manufacturing exports, and alternative energy sources on natural gas and electricity production from renewable sources. Energy imports, manufacturing exports, and alternative energy sources can impact natural gas and electricity production. This paper examines natural gas resource rents and electricity production from renewable sources nexus from 1971 to 2021, using energy imports, manufacturer’s exports, and alternative energy sources in China. Electricity production from renewable sources and manufacturing exports are negatively associated with natural gas resource rents. Energy imports and alternative energy sources positively relate to natural gas resource rents in China. These results suggest that the energy sector in China is highly interconnected and that policies that seek to promote renewable energy sources and other alternatives can positively affect natural gas resource rents. China needs to develop an energy policy considering the policy implications of energy imports and natural gas resource rents. Such a policy should focus on increasing domestic production, reducing energy imports, and ensuring adequate revenue from natural gas resource rents. Additionally, regulations could be implemented that support the development of alternative energy sources, such as requiring utilities to purchase a certain percentage of their power from renewable sources.

This study investigates the direct impact of technological sophistication (TS), international entrepreneurial orientation (IEO), and a culture of innovation (OCI) on organizational performance, as well as the moderating role of open innovation (OI) in influencing the relationship between TS, IEO, OCI, and the performance of Multinational corporations (MNCs) operating in emerging markets in Africa. Specifically, this study seeks to unravel the dynamic interplay between collaborative innovation strategies and corporate success in rapidly evolving economies, providing valuable insights for both academic research and practical business strategies in the global landscape. Data analysis was conducted with data collected from 352 individuals who completed a study questionnaire. A key aspect of this analysis is the utilization of Structural Equation Modelling (SEM to analyse quantitative primary data that was collected via a structured questionnaire from a diverse sample of manufacturing and service-oriented Multinational Corporations (MNCs) serving in emerging African markets, to elucidate the tangible effects of open innovation on corporate achievement indicators. First, a content validity served as a prerequisite estimation strategy and then a confirmatory factor analysis was later conducted for the robustness of results and key findings. As an analytical strategy, first the study conducted a pilot test and then set up a minimum criterion for the questionnaire distribution based on some certain indicators such as the number of operational branches across regions, market presence, advertising capacity, and staff strength were considered in this determination The findings reveal that IEO, TS, and OCI significantly affect performance, and OI moderates the relationships between these factors and performance. Specifically, OI enhances the strength of this process with the presence of high degree. Notably, MNCs with an international entrepreneurial orientation in African markets can influence government market policies, contributing to the understanding of dynamic abilities in international business within emerging economies. These results offer valuable insights for enhancing MNC performance in emerging economies by systematically integrating advanced technologies and a unique international entrepreneurial orientation within their organizational culture of innovation. The study also underscores the originality and value of exploring the impact of technology, culture of innovation, and IEO on business continuity in international emerging markets.

Enterprises leverage business intelligence (BI) to promote competitive advantages. However, there is still a lack of understanding of BI quality and innovation performance. This research constructed a model of the impact of BI's system quality and information quality on innovation performance through the IS success and dynamic capabilities framework. This research also investigated the mediation effect of knowledge sharing and absorptive capability and examined heterogeneity with potential IT differences between industries. The results with Chinese enterprise data show that both system quality and information quality are positively related to knowledge sharing, and system quality is positively related to absorptive capability, while information quality is not. Through the mediation effect of knowledge sharing and absorptive capability, system quality partially facilitates innovation performance, while information quality completely facilitates innovation performance, although indirectly. There is no significant relationship between system quality and knowledge sharing among traditional industries. These findings contribute new insights into BI-enabled innovation.

Co-innovation between digital platforms and complementors is motivated by their interactions, especially on content creation platforms that emphasise creativity. With the platform monopoly, creators are increasingly dependent on the platform thus making the interaction directional. As the long-term effect of the dependency effect on co-innovation under multi-agent networks is currently under-researched, a novel asymmetric NK model is proposed in this paper to evaluate creators' dependence on the platform through agent-based simulation. The results show that the internal interaction of creators has an inverted U-shaped effect on co-innovation, and the external dependency effect has a negative effect on co-innovation. Further results considering global complexity constraints show that there is a substitution effect between internal interaction and external dependency and that relying on a platform can facilitate co-innovation by reducing potential external risks under high environmental complexity. Moreover, exploratory innovation is equally conducive to co-innovation and enables creators to be less dependent. This study extends a new model for digital platform research and responds to discussions between interaction, exploration, and innovation in the literature.