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As one of its major strategies, China has made a new plan to further expand High Standard Farmland (HSF) to all permanent basic farmland (80% of total farmland) for grain security over the next decade. Yet, what will be the impact of farmland infrastructure investment on agrifood systems? The paper aims to systematically evaluate the multiple effects (food security, economy, nutrition and environment) of expanding HSF construction under the context of the “Big Food vision” using an interdisciplinary model.

An interdisciplinary model – AgriFood Systems Model, which links the China CGE model to diet and carbon emission modules, is applied to assess the multiple effects of HSF construction on agrifood systems, such as food security and economic development, residents’ diet quality and carbon emissions. Several policy scenarios are designed to capture these effects of the past HSF investment based on counterfactual analysis and compare the effects of HSF future investment at the national level under the conditions of different land use policies – restricting to grain crops or allowing diversification (like vegetables, and fruit).

The investments in HSF offer a promising solution for addressing the challenges of food and nutrition security, economic development and environmental sustainability. Without HSF construction, grain production and self-sufficiency would decline significantly, while the agricultural and agrifood systems’ GDP would decrease. The future investment in the HSF construction will further increase both grain production and GDP, improve dietary quality and reduce carbon emissions. Compared with the policy of limiting HSF to planting grains, diversified planting can provide a more profitable economic return, improve dietary quality and reduce carbon emissions.

This study contributes to better informing the impact of land infrastructure expanding investment on the agrifood systems from multiple dimensions based on an interdisciplinary model. We suggest that the government consider applying diversified planting in the future HSF investment to meet nutritional and health demands, increase household income and reduce carbon emissions.

The paper intends to show why farms as we know them today may soon be a thing of the past and that organisational behaviour research has an important contribution to make in assisting the upcoming transformation.

Two strains of literature are reviewed and then synthesised: the literature on robots replacing humans in agricultural production and the literature on vertical integration that shifts decisions to agribusiness. Then the potential contribution of organisational behaviour research is outlined.

It is shown how the farm is likely to lose both roles for which their geographic entity is important: making decisions and carrying out production. This requires contributions from organisational behaviour research in the realms of decision designs and social systems.

It can be anticipated that the most profitable strategy for farmland owners in the future will be collaboration with contractors. Farms as organisations, are increasingly losing their importance. This not only has grave social implications for farmworkers and landowners but also for scholars in organisational behaviour research.

The paper challenges an organisational unit that is so familiar to us that it is rarely questioned.

This paper explores the relationship between state-led urbanization and primary industry development using the difference-in-differences (DiD) method.

The study uses the DiD method.

Exploiting county-city mergers during 2010–2018, the key strategy to expand the city outward and promote urbanization on the urban fringe by local government, the authors find that county-city mergers led to the growth of primary industry decline by 4.23%. The result can be explained by the loss of essential production factors, including land and labor used for farming. In addition, the negative effect is more pronounced for counties with more substantial manufacturing. The results indicate that urbanization in China relocates land and labor; however, it does not improve the efficiency of agricultural output.

This paper contributes to the understanding of urbanization and rural development from the perspective of the primary industry by showing production factor redistribution. Second, this study complements the literature on local government mergers.

This study aims to examine the value orientations of New Zealand agribusiness investors and how these orientations influence their reactions to the environmental and social implications of agribusinesses.

In the context of the New Zealand agricultural sector, the views of investors as published in print and broadcast media between 2018 and 2022 are gathered. The study uses qualitative content analysis to analyse the data. The study is based on the value-belief-norm theory.

The study reveals that New Zealand agribusiness investors express concern about the environmental (biospheric) and social (altruistic) impacts of the agribusiness sector, prompting calls for greater transparency, climate adaptation and ethical investment options. Additionally, they actively support local businesses to benefit their communities and preserve cultural heritage. Despite these biospheric and altruistic tendencies, investors also prioritise financial and non-financial interests (egoistic). This highlights a nuanced perspective guiding their investment choices – a balance between self-interest and contributing to the greater good. This signals a shift towards socially and environmentally responsible investment practices driven by multifaceted values.

The findings of this study highlight the role of non-pecuniary motives, like values, in determining the relevance of environmental and social information.

The study’s findings offer insight to agribusinesses on how investors’ value orientations shape their investment decisions. This understanding can guide businesses in framing a reporting strategy that enhances the likelihood of investors perceiving reporting as relevant and persuasive, thereby attracting more investments. In turn, this tailored reporting approach assists investors in making well-informed decisions in assessing the environmental and societal risks of agribusinesses.

The study offers a framework explaining how agribusinesses can increase the likelihood of investors finding firms reporting relevant and persuasive, leading to increased investments in environmentally and socially sustainable practices.

This study aims to clarify the impact of agriculture–tourism integration (ATI) on in situ urbanization (ISURB) of rural residents, to highlight the role of industrial integration in the process of China's ISURB and to provide industrial integration suggestions for promoting urbanization quality in Chinese counties.

By sorting out the panel data of China's 1868 counties, the evaluation index system of ISURB was constructed. Difference in difference (DID) and spatial Durbin-difference in difference (SDM-DID) model is used for estimate the relationship between ATI and ISURB.

First, ATI can improve ISURB by 11.4% higher than other regions. Second, theoretical analysis model of ATI on ISURB is constructed from four aspects of “drive–push–pull–block.” The results show that ATI can promote ISURB by increasing upgrading of rural industries, rural employment demand and income capacity, whereas ATI may inhibit ISURB by reducing farmland. Third, considering changes in institutional, hard and soft factors, rural collective economy, information infrastructure and digital finance all promote positive impact of ATI on ISURB. Fourth, ATI will produce spillover effects on ISURB in neighboring regions, which is more pronounced in the central and western regions.

This study lacks quantification of ATI, so future studies are encouraged to further quantify ATI at the county level.

This study has policy significance for constructing ATI demonstration counties and promoting ISURB in China's counties.

It is of great practical value to promote China's ISURB. By stimulating ATI, it can improve income and employment capacity of rural residents and stimulate ISURB of China.

This study enriches the theoretical and practical research on industrial integration behaviors during the process of ISURB.

1. Use county data to measure in situ urbanization (ISURB)

2. Agriculture–tourism integration (ATI) can increase ISURB

3. Constructs a “drive-push-pull-block” model to explain the influence mechanism

4. Use spatial Durbin-difference in difference (SDM-DID) models

5. Consider collective economy, rural information infrastructure and digital finance

Use county data to measure in situ urbanization (ISURB)

Agriculture–tourism integration (ATI) can increase ISURB

Constructs a “drive-push-pull-block” model to explain the influence mechanism

Use spatial Durbin-difference in difference (SDM-DID) models

Consider collective economy, rural information infrastructure and digital finance

Conflicts between herders and farmers in Nigeria in the last five years have been destructive to the corporate existence of Nigerian society and the Nigerian State, especially in Northcentral, Northwestern and Southern Nigeria. This paper aims to investigate the relationships between state responses and peace-building in rural grazing communities in Nigeria using a National Survey on Peace-building in Nigeria conducted by this team using a cross-sectional survey of 1,711 farmers and herders.

The study adopted the political economy of the herder–farmers conflict in Africa to contextualise the problem. Data generated from the study were analysed using chi-square test and binary logistic regression model.

The results showed that protection of victims of herder–farmers conflict (P = 0.024), blockage of sources of illicit weapons (P = 0.000), arrest of leaders (P = 0.043), provision of shelter (P = 0.030), provision of food (P = 0.037), protection of women from sexual exploitation and abuse (P = 0.019) and use of the media were positively related to peace-building in the rural grazing areas. The study further found that when the Federal Government (ß= 0.452, P = 0.018), State Government (ß= 0.522, P = 0.018), private individuals (ß = 0.855, P = 0.000) and cooperative societies (ß = 0.744, P = 0.021) established ranches, peace was likely to be guaranteed as opposed to where herders (ß= –0.355, P= 0.029) were allowed to establish ranches in the rural grazing communities in Nigeria implying that the Federal and State Government must be cautious in the implementation of the Livestock Transformation Plans not to create an impression that it is designed to favour the herders.

To the best of the authors’ knowledge, this study is original and the paper has not been submitted to any journal.

As China has pressed ahead with rural revitalization in recent years, its rural financial sector has also developed rapidly and the financial environment has been greatly improved. But compared with urban areas, the rural financial sector makes rather limited contributions to rural economic development for a variety of reasons, including single types of service providers, narrow coverage, and lack of services and products. The underdevelopment of the rural financial system is closely related to the characteristics of its target customers and the economic system. The deficient rural financial credit system, the low level of IT application, the difficulty in data collection and integration, and the insufficient collateral of farmers pose high costs and huge risks for financial institutions when providing credit and other financial services.

In the present case, fintech and financial innovation complement each other: The application of fintech makes innovation possible, and the need for financial development fuels the development of fintech. Leveraging fintech and new business models, MYbank has overcome the main obstacles in the development of rural finance to provide convenient financial services for farmers and rural MSEs. Fintech is the abbreviation of “financial technology.” It can be understood as the combination of finance and technology for easier understanding, but it is more than that. Fintech refers to the innovation of traditional financial products and services with various technologies to improve efficiency and reduce operating costs. The emergence and development of fintech have led to the creation of new business models, applications, and processes, which have triggered major changes in financial markets, financial institutions, and the ways financial services are delivered, and are reshaping the financial landscapes of countries and even the world.

There are three major problems in the development of rural finance: difficult access to data, difficult risk management, and difficult market penetration. In order to gradually remove the obstacles and guarantee sustainable business development, MYbank has created three new business models with the power of fintech: digital inclusive finance at the county level, industrial finance, and platform finance. With these models, MYbank is searching for a “Chinese solution” to the worldwide problem of rural inclusive finance.

This study aims to examine farmers' decision to use smartphone agricultural applications (SAAs) and how SAAs adoption impact their land transfer behaviors in terms of the current land transfer-in area (LTA) and the future willingness to renew land transfer-in after it expires (WTR).

This study provides empirical evidence on the relationship between farmers' use of SAAs and land transfer choice, using a field survey data of 752 rural farm households in 2020 from Sichuan province of China. The endogenous switching models are employed to address potential self-selection bias associated with voluntary SAAs use and to quantitatively examine the impacts of SAAs use on land transfer choice.

The empirical results reveal that SAAs significantly improves the probability of transfer-in of more land by 39.10%. We find SAAs use has heterogeneous impacts on land transfer-in choice in the groups of agricultural technology, extension service, marketing and credit. Besides, we also find that SAAs use exerts highly positive and significant impact on farmers with less land area transfer-in. Moreover, SAAs can increase the probability of farmers' willingness to renew the land transfer-in by 30%.

To the best of our knowledge, this study is the first to explore the quantitative relationship between the use of SAAs and farm households' land transfer choice. The findings of this work can provide policy-related insights to help government promote the development of digital applications in the agricultural sector.

Classification of remote sensing images (RSI) is a challenging task in computer vision. Recently, researchers have proposed a variety of creative methods for automatic recognition of RSI, and feature fusion is a research hotspot for its great potential to boost performance. However, RSI has a unique imaging condition and cluttered scenes with complicated backgrounds. This larger difference from nature images has made the previous feature fusion methods present insignificant performance improvements.

This work proposed a two-convolutional neural network (CNN) fusion method named main and branch CNN fusion network (MBC-Net) as an improved solution for classifying RSI. In detail, the MBC-Net employs an EfficientNet-B3 as its main CNN stream and an EfficientNet-B0 as a branch, named MC-B3 and BC-B0, respectively. In particular, MBC-Net includes a long-range derivation (LRD) module, which is specially designed to learn the dependence of different features. Meanwhile, MBC-Net also uses some unique ideas to tackle the problems coming from the two-CNN fusion and the inherent nature of RSI.

Extensive experiments on three RSI sets prove that MBC-Net outperforms the other 38 state-of-the-art (STOA) methods published from 2020 to 2023, with a noticeable increase in overall accuracy (OA) values. MBC-Net not only presents a 0.7% increased OA value on the most confusing NWPU set but also has 62% fewer parameters compared to the leading approach that ranks first in the literature.

MBC-Net is a more effective and efficient feature fusion approach compared to other STOA methods in the literature. Given the visualizations of grad class activation mapping (Grad-CAM), it reveals that MBC-Net can learn the long-range dependence of features that a single CNN cannot. Based on the tendency stochastic neighbor embedding (t-SNE) results, it demonstrates that the feature representation of MBC-Net is more effective than other methods. In addition, the ablation tests indicate that MBC-Net is effective and efficient for fusing features from two CNNs.

This paper's purpose is to explore the current interest and knowledge that UK consumers hold around agroforestry. Despite the many reported benefits of agroforestry systems, uptake in the UK, as well as other temperate nations, has been low. As the consumer has a role to play in the transition of agriculture to methods that are more environmentally friendly it is vital to have an understanding of their perceptions. Yet to date no work has looked at agroforestry from the perspective of the UK consumer.

An online survey was conducted using a convenience sample accessed by floating a link through social media and messaging apps. The survey was also shared to the members of a private Facebook group associated with an organic vegetable box service. A mix of multiple choice and open text boxes were used. The survey received 139 responses.

Non-parametric tests indicate that this sample of UK consumers would be mostly likely to buy, and willing to pay more for, agroforestry produce; and the sample showed a split group regarding familiarity. Inductive thematic analysis of the qualitative data highlighted some important barriers to the purchase as well as capturing a snapshot of this sample's perceptions.

This paper presents, to the authors knowledge, the first set of data regarding a sample of UK consumers' perspective of agroforestry produce. The findings could bolster producers' confidence in adopting agroforestry practices, but also highlight the need for policymakers to bolster consumer support through parallel means.