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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 role of Technology Transfer Units, examined in this study, was found to be vital to expedite the process of disseminating new varieties and their production technology.

A total of 1,000 households were surveyed in the sampled states. A probit model was used to analyse.

Age, education, land holding, tractor use and number of working family members in agriculture were found to significantly affecting adoption of the new seed varieties. Technology transfer through licensing has impacted the adoption of new seed varieties positively by highlighting Punjab possessing the highest adoption and western Uttar Pradesh was majorly adopting the old variety.

The authors believed in farmers’ memory to recall the varietal information of wheat.

The study recommended various incentives to attract the seed industry in UP to minimize the economic loss potentially suffered by them.

Quality seeds are germane to increase the productivity of crops, and it is paramount to disburse the seed varieties to the end users in an efficient way to achieve the overall objective of productivity enhancement.

In this context, a study was conducted in three states of India, namely, Punjab, Haryana and Uttar Pradesh (UP) to find out the adoption rate of newly developed varieties of wheat, HD 3086 after three years (2014–2015) of its commercialization by IARI as well as HD 2967, which was released in 2011.

Achieving tenure security is a global challenge impacting cities of the global south. The purpose of this paper is to evaluate the role of technology-enabled solutions as an enabler for the tenure rights of slum dwellers.

In this paper, we adopted a case study approach to analyze the use cases for technologies aiding India’s securitization of land tenure. The flagship state mission of Odisha, named the Jaga Mission, and that of Punjab, named BASERA – the Chief Minister’s Slum Development Program – were used as cases for this paper.

It was found that technologies like drone imagery and digital surveys fast-tracked the data collection and helped in mapping the slums with accuracy, mitigating human errors arising during measurement – a necessary condition for ensuring de jure tenure security. The adoption of a technology-based solution, along with a suitable policy and legal framework, has helped in the distribution of secure land titles to the slum dwellers in these states.

Odisha’s and Punjab’s journey in using technology to enable tenure security for its urban poor residents can serve as a model for the cities of the global south, dealing with the challenges of providing secure tenure and property rights.

Land transactions are a key indicator of urban sustainable development and urban space expansion. Therefore, this paper aims to study the spatial correlation of different types of land transactions.

Based on the big data of land micro transactions in Yangtze River Delta urban agglomeration, this paper uses the generalized forecast error variance decomposition (GFEVD) method to measure the correlation level of urban land markets. Also, social network analysis (SNA) is used to describe spatial correlation network characteristics of an urban agglomeration land market. In the meantime, the factors that influence the spatial correlation of urban land markets are investigated through a quadratic assignment procedure (QAP).

The price growth rate of urban residential land was higher than that of industrial land and commercial land. The spatial relevance of urban residential land is the highest, while the spatial relevance of the urban commercial land market is the lowest. The urban industrial land market, commercial land market and residential land market all present a typical network structure. Population distance (POD) and Engel coefficient distance (EGD) are negatively correlated with the correlation degree of the urban residential land network; traffic distance (TRD) and economic distance (ECD) are negatively correlated with the correlation degree of the urban industrial land network and commercial land network.

This paper uses a systematically-integrated series of problem-solving models to better explain the development path of urban land markets and to realize the integration of the interdisciplinary methods of geography, statistics and big data analysis.

Family farms, in which business and family life are intricately interwoven, offer an interesting context for better understanding the interdependence between the family and business system. Many family farms struggle to survive, and the succession process is a key period in which the low returns on investment become evident but also the emotional attachment of the family to the farm and the willingness to transfer the business to the next generation. We take the perspective of non-succeeding siblings since they are crucial for a successful succession but their role and position in this process is far from clear. This study will help to increase our knowledge of how fairness is perceived by non-successors and of the impact of perceived (in)justice on the family business system.

To analyze the effect on sibling relationships of an unequal outcome of the succession process, we choose the family farm context. We used interview data from multiple family members from several family farms in the Netherlands in different stages of succession. We utilized a framework based on justice theory to analyze perceptions of fairness among non-succeeding siblings. The central research question for this study is as follows: How do non-succeeding siblings perceive justice with regard to family firm succession?

The acceptance of the outcomes of the succession process by non-succeeding siblings is influenced by their perception of the fairness of the process itself and decisions made by the incumbent and successor with regard to these outcomes. It seems that stakeholders who occupy multiple roles with conflicting justice perspectives handle these contradictions with the help of an overarching goal—in this study, preserving the continuity of the family farm—and by prioritizing and adjusting the justice perspectives accordingly. The findings further show that both distributive justice and procedural justice are important and interact with each other.

Our study contributes to the literature by applying the theoretical framework of distributive and procedural justice to the context of family farm succession. This helps us to understand the position of non-succeeding siblings and their role and position in the succession process, which is important because sibling relationships have a significant impact on family harmony, with potential consequences for the business as well.

The purpose of this study is to analyze the horizontal expansion of Burayu Town between 1990 and 2020. The study typically acts as a baseline for integrated spatial planning in small- and medium-sized towns, which will help to plan sustainable utilization of land.

Landsat5-TM, Landsat7 ETM+, Landsat5 TM and Landsat8 OLI were used in the study, along with other auxiliary data. The LULC map classifications were generated using the Random Forest Package from the Comprehensive R Archive Network. Post-classification, spatial metrics, and per capita land consumption rate were used to understand the manner and rate of expansion of Burayu Town. Focus group discussions and key informant interviews were also used to validate land use classes through triangulation.

The study found that the built-up area was the most dynamic LULC category (85.1%) as it increased by over 4,000 ha between 1990 and 2020. Furthermore, population increase did not result in density increase as per capita land consumption increased from 0.024 to 0.040 during the same period.

As a result of financial limitations, there were no high-resolution satellite images available, making it challenging to pinpoint the truth as it is on the ground. Including senior citizens in the study region allowed this study to overcome these restrictions and detect every type of land use and cover.

Data on urban growth are useful for planning land uses, estimating growth rates and advising the government on how best to use land. This can be achieved by monitoring and reviewing development plans using satellite imaging data and GIS tools.

The use of Random Forest for image classification and the employment of local knowledge to validate the accuracy of land cover classification is a novel approach to properly customize remote sensing applications.

This study aims to analyze the short-, medium- and long-term impacts of natural-resources-seeking foreign direct investment (FDI) in the form of foreign multinational enterprise (MNE) land acquisitions on agricultural labor productivity in developing countries. The authors analyze if these land acquisitions disrupt fair and decent rural labor productivity or if the investments provide opportunities for improvement and growth. The influence of different country characteristics, such as economic development levels and governmental protection for the rural population, are acknowledged.

The study analyzes 570 land acquisitions across 90 countries between 2000 and 2015 via a generalized least squares regression. It distinguishes short- and long-term implications and the moderating role of a country’s economic development level and government effectiveness in implementing government protection.

The results suggest that natural resource-seeking FDI harms agricultural labor productivity in the short term. However, this impact turns positive in the long term as labor markets adjust to the initial disruptions that result from land acquisitions. A country’s economic development level mitigates the negative short-term impacts, indicating the possibility of finding alternative job opportunities in economically stronger countries. Government effectiveness does have no influence, presumably as the rural population in which the investment is partaking is in many developing countries, not the focus of governmental protectionism.

The findings provide interesting insights into the impact of MNEs on developing countries and particularly their rural areas that are heavily dependent on natural resources. The authors identify implications on employment opportunities in the agricultural sector in these countries, which are negative in the short term but turn positive in the long term.

Moreover, the findings also have utility for policymakers. The sale of land to foreign MNEs is not a passive process – indeed, developing country governments have an active hand in constructing purchase contracts. Local governments could organize multistakeholder partnerships between MNEs, domestic businesses and communities to promote cooperation for access to technology and innovation and capacity-building to support employment opportunities.

The authors urge MNE managers to establish new partnerships to ease transitions and mitigate the negative impacts of land acquisitions on agricultural employment opportunities in the short term. These partnerships could emphasize worker retraining and skills upgrading for MNE-owned land, developing new financing schemes and sharing of technology and market opportunities for surrounding small-holder farmers (World Bank, 2018). MNE managers could also adopt wildlife-friendly farming and agroecological intensification practices to mitigate the negative impacts on local ecosystems and biodiversity (Tscharntke et al., 2012).

The authors contribute to the debate on the positive and negative impact of FDI on developing countries, particularly considering temporality and the rural environment in which the FDI is partaking.

Artificial Intelligence-based smart farming technologies have brought impressive changes in farming. This paper aims at exploring the farmers’ intention to adopt smart farming technologies (SFT). Also, the authors intend to know how far the belief of farmers on land as God influences their decision to adopt SFT.

The data were gathered from 500 farmers chosen purposively. A well-crafted survey instrument was employed to amass data from farmers for measuring their adoption of SFT. As the authors sought to measure the farmers’ behavioural intention (BI) towards the adoption of SFT, the technology acceptance model developed by Davis (1989) came in handy, including perceived usefulness (PU), perceived ease of use (PEU) and BI. The authors have adopted this model as it was considered a superior model. The items on the attitude of confidence (AC) were adapted from Adrian et al. (2005). Survey instruments of Thompson and Higgins (1991) and Compeau and Higgins (1995) were also referred to finalize the statements relating to attitude towards use. Moreover, the authors developed items relating to the perceived belief of land as God based on frequent interaction with the farmers.

The study results divulged that attitude to use (AU) is directly influenced by the rural farmers’ PU, PEU and AC. Similarly, this investigation has observed behaviour intention directly influenced by the AU of farmers. It is observed that AU was the most influential variable, which ultimately influenced the BI to use SFT.

This study has an important limitation in the form of representing only the culture, belief and value system of farmers in India.

The outcome of this study will facilitate the policymakers to draw suitable policy measures keeping the sensitivities of the farmers in mind in their technology adoption drive. The agricultural officers can encourage farmers to take logical decisions by supplying adequate information in a time-bound manner. Marketers can make suitable adjustments in their sales and promotion activities that focus on farmers.

The belief of farmers on land as God has a small yet unmissable influence on farmers’ AU and BI in their technology adoption decision. Based on the above evidence, the authors recommend that marketers fine-tune their product design, product packaging and promotional activities keeping the belief and sensitivities of farmers at the core of their marketing campaign.

This article provides original insights by demonstrating the positive influence of PU, PEU and AC on technology adoption by farmers. This research is the first of a kind linking the belief of farmers on land as God with smart farming technology adoption in farming.

This study aims to reconstruct how smallholder farmers implement livelihood adaptation strategies to survive and escape poverty, thereby mitigating or eliminating potential livelihood risks by utilizing their available assets.

This research employed a qualitative approach. For the collection of primary data, the researcher conducted observations and in-depth interviews and engaged with the lives of smallholder farmers during the data collection period.

Among the various livelihood adaptation strategies, only migration and profit-sharing strategies enable smallholder farmers to escape poverty. However, migration is an unsustainable adaptation strategy. When farmers move to new locations, they often resort to slash-and-burn methods for clearing land, which can lead to forest degradation and deforestation. Profit sharing is a sustainable livelihood adaptation strategy that falls into a different category. This approach can lift farmers out of poverty, increase their income and have no negative environmental impact. Other adaptation strategies include adjustments to traditional agriculture, both on and off-farm diversification, involving the family in income generation, reducing farming costs, practicing frugality in post-harvest processes, converting land from coffee cultivation to other crops and borrowing money and selling owned assets. Smallholder farmers implement these strategies to survive the existing economic conditions.

The profit-sharing strategy was a novel livelihood adaptation approach that previous studies had yet to uncover at the research site. In this strategy, farmers assume the roles of both managers and laborers simultaneously during farming, while toke (the capital owners) play the role of farming funders. The generated profit is then shared between farmers and toke based on the agreement established at the outset of their collaboration.

The purpose of this study is to examine the effects of market-based approach to provision of housing to low-income households in urban Malawi.

This study was conducted in Blantyre, Malawi, between 2019 and 2022 and used both quantitative (household survey) and qualitative (in-depth interviews and document study) methods of data collection. Interviews were conducted with key players and investors in the housing sector. Household survey data were analyzed through descriptive statistics, which allowed the generation of descriptive housing valuables, whereas qualitative data were analyzed through content analysis.

This paper demonstrates that, rather than ameliorating the housing problems facing low-income households, the market approach to provision of housing in Malawi has worsened the housing situation in the country. This is so because the market approach to the provision of housing in Malawi is not only enforcing the logic of capitalistic accumulation in the housing sector but also supporting mechanisms of exclusion based on economic stratification within the community.

Completeness of data over time as there is no market data bank available in the country.

The findings from this study suggest that some degree of state intervention in addressing the housing problem in Malawi is required.

The study findings suggest that a market approach to the provision of housing can increase social inequality as low-income households face challenges in accessing housing.

There is a paucity of research on the effects of the market approach on the provision of affordable housing to low-income households in Malawi. This paper assesses this important policy gap and provides significant policy directions.