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The purpose of this paper is to bridge the gap in knowledge of Jamaican householders’ housing choices and to provide empirical research that will support the inclusion of the householders’ perspectives in developing housing policies and programmes in Jamaica.

A questionnaire survey of 430 householders drawn from public housing developments in 6 of 14 parishes in Jamaica was conducted. A pragmatic approach was taken in this study. As such, both qualitative and quantitative data were used to investigate the factors influencing householders’ housing choices. The data were analysed using exploratory factor analysis to extract the main factors influencing the householders’ housing choices.

The research revealed that the dwelling features and its environment, accessibility and neighbourhood attributes are three factors influencing householders’ housing choice. Notably, the dwelling and its immediate environment explained the majority of the variance in housing choice. This suggests that if householders are given a choice between a larger more desirable dwelling in a clean, safe and well-maintained community and housing with proximity to work, job opportunities, urban services and other proximity variables, they are less likely to choose the latter.

The factors obtained from this study provide some insights into the scale of preference of the household heads and desired attributes of affordable housing solutions. They also shed some light on what might have caused some past affordable housing solutions to be undesirable. In addition to this, there is some intuition that there may be efficacy in adopting a community development approach to housing. These results have strong implications for housing planning. However, given the island’s challenge with the proliferation of squatter settlements, it is recommended that further research, which includes these householders’ be carried out.

This research is the first to examine the views of Jamaican householders’ with the purpose of understanding what influences their choice of housing. The findings provide new insights into the trade-off that householders may be willing to make in choosing their housing. The results provide a source of reference in reviewing the performance of past policies and programmes.

After the Collective Forest Tenure Reform (CFTR) in China, the enthusiasm of farmers for forestry management is stimulated. However, the forest tenure security varies among farmers, making the research conclusions of its impact on forestry management efficiency inconsistent. Based on the survey data of 1,627 households from the collective forest regions in 6 provinces of China in 2017, this paper not only discusses the differences of farmers' forestry management efficiency after the reform, but also further explores the heterogeneous impact of forest tenure security on forestry management efficiency in combination with different forest management types.

This study employed the stochastic frontier production function model to measure the forestry management efficiency of farmers. Then, Tobit models were used to discuss the influencing factors of farmers' forestry management efficiency.

The results demonstrate that the improvement of farmers' forest tenure security can effectively improve forestry management efficiency, but the effect is affected by forest management types. For farmers who manage economic forests and non-timber forests, safe tenure promotes the forestry management efficiency; while for those who manage ecological public welfare forests, tenure security plays an opposite role.

Therefore, satisfying farmers' differentiated demands for forest tenure according to forest management types to improve forest tenure security and further refining supporting policies of collective forestry reform is of great significance to improve the efficiency of farmers' forestry management in collective forest regions.

Farmers’ selection of vegetable marketing channels directly affects their income and is important to stable vegetable supply and food control. The purpose of this paper is to investigate the farmers’ selection behavior of vegetable marketing channels, and to determine the key factors which affected farmer’ decision making.

A total of 191 valid questionnaires were collected from 50 villages in seven main vegetable production districts in Beijing urban areas from September to December 2015, yielding a response rate of 86.8 percent. The multinomial logit model was used for analysis in this study.

The results revealed that the farmers mainly selected farmers’ market, cooperative, and wholesaler to sell their vegetables, which comprised 96.57 percent of total vegetable sales. Estimation results showed that cooperative, vegetable acreage, price satisfaction, and slow sales were most important factors which influence positively the probability of opting to sell vegetables at a cooperative rather than at the farmer’s market. For wholesalers, gender of the household head and cooperative had most significantly negative effect, and age had a positive impact on farmer’s choice of market channels.

The results and implications obtained in the present study could help policymakers to establish a scientific-based and reasonable policy to encourage vegetable producers to participate in the circulation of vegetables in Beijing and guarantee their income in vegetable supply chain. The suggestions of this study could also be used for the improvement of the vegetable sector in other cities facing similar issues.

The purpose of this paper is to fill a knowledge gap by examining the changes in fruit and vegetable consumption of Chinese households.

Using 1993 and 2001 household survey data from three selected provinces in China, the authors estimated a quantile regression (QR) model to demonstrate how changes of fresh fruit and vegetable consumption over time may differ across regions, and additionally, how these changes may differ over the entire distribution.

Results show significant increases in fresh fruit consumption for all provinces; in addition, the pattern of changes over time differs across the entire distribution. In contrast, significant decreases of fresh vegetable consumption are evident, and results are robust across regions; however, the disparities of fresh vegetable consumption across regions are not significant.

The results may shed some light on the national food policy. First, any food policy that may affect prices of fresh fruits and vegetables will likely affect households in lower percentiles more than those in upper percentiles. In addition, based on the findings, households in Guangdong may have a higher risk of inadequate fruit consumption. Lower level consumption of fruits in Guangdong may be caused by its relatively high prices of fruits and perhaps the shifting consumption pattern to a more meat‐based diet as income increases.

There has been considerable interest in estimating food demand structure in China due to its huge market for food products. However, little is known about the fruits and vegetables products. In addition, most of the previous studies used the linear regression‐type model for analysis, which fails to capture the effects of the exogenous factors on the entire distribution. To fill the knowledge gap, this paper uses a QR model with the different‐in‐difference method to examine the changes in fruit and vegetable consumption of Chinese households.

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.

The purpose of this paper is to empirically investigate the effect of rural finance on industrial integration of rural primary, secondary and tertiary industries.

Using household-level data collected by Third National Agricultural Census and the provincial-level data collected from Wind database, the authors estimated the impacts of rural finance on rural industrial integration using Logit and Probit regression models. Further, the authors examined how the effect of rural finance varies with the age and education of householders, and with household and provincial characteristics by investigating the moderating effect.

The findings show that rural finance has a significant and positive effect on promoting farmers’ participation in new agricultural management organizations. This effect is more obvious in families whose householders are 40–50 years old, or families that have more educated members. This is because the middle-aged or educated people are more willing to accept and take part in industrial integration. The results further indicate that rural finance has a greater effect on industrial integration in provinces with a high degree of marketization, and in provinces with the high output value of industries and services in agricultural intermediate input.

The authors investigated the impact of rural finance on rural industrial integration empirically, and this topic is rarely covered before. The findings of this study also enrich the literature on financial development and economic growth as well as provide policy suggestions on how to promote rural industrial integration.

The monograph argues that American racism has two colours (white and black), not one; and that each racism dresses itself not in one clothing, but in four: (1) “Minimal” negative, when one race considers another race inferior to itself in degree, but not in nature; (2) “Maximal” negative, when one race regards another as inherently inferior; (3) “Minimal” positive, when one race elevates another race to a superior status in degree, but not in nature; and (4) “Maximal” positive, when one race believes that the other race is genetically superior. The monograph maintains that the needs of capitalism created black slavery; that black slavery produced white racism as a justification for black slavery; and that black racism is a backlash of white racism. The monograph concludes that the abolition of black slavery and the civil rights movement destroyed the social and political ground for white and black racism, while the modern development of capitalism is demolishing their economic and intellectual ground.

Urbanization is driving the growth of China’s carbon footprint. It’s important to investigate what factors, how and to what extent, affect carbon footprints embedded in various categories of rural and urban households’ consumption.

We employ an environmental extended input-output model to assess and compare the rural-urban household carbon footprints and perform a multivariant regression analysis to identify the varying relationships of the determinants on rural and urban household carbon footprints based on the panel data of Chinese households from 2012 to 2018.

The results show evidence of urbanity density effect on direct carbon footprints and countervailing effect on indirect carbon footprints. The old dependency ratio has no significant effect on rural family emissions but has a significantly negative effect on urban direct and indirect carbon footprints. A higher child dependency ratio is associated with less rural household carbon emissions while the opposite is true for urban households. Taking advantage of recycled fuel saves direct carbon emissions and this green lifestyle benefits urban households more by saving more carbon emissions. There is a positive relationship between consumption structure ratio and direct carbon footprints while a negative relationship with indirect carbon footprints and this impact is less significant for urban households. The higher the price level of water, electricity and fuel, the lower the rural household’s direct carbon footprints. Private car ownership consistently augments household carbon footprints across rural and urban areas.

This paper provides comprehensive findings to understand the relationships between an array of determinants and China’s rural-urban carbon emissions, empowering China’s contribution to the global effort on climate mitigation.

The main objectives of collective forest tenure reform in China are to stimulate rural households to invest in forestry management, protect the ecosystem and improve their livelihood. By constructing the unbalanced panel data of household investment, this study discusses the dynamic changes and influencing factors of household investment, which will lay a foundation for further research and provide a reference for decision-making.

Based on 3,500 samples from rural households in the provinces of Fujian, Hunan, Yunnan, Shaanxi, Jiangxi, Gansu, and Liaoning collected during field investigations from 2010 to 2015, this study conducts an empirical analysis of the household investment in forestry management and its factors with nonbalanced panels.

According to the analysis, the average investment in forestry management per household from 2010 to 2015 fluctuates greatly; the age of the householder, increased forestry area, subsidies, joining professional cooperatives, and forest tenure mortgage show positive effects on achieving the objectives.

The discussions are drawn from the study that supporting policies such as the forest tenure transfer system, professional cooperatives, financial services and subsidies should be further improved to sustain a positive in the forestry industry.

The study examines the impact of the preferential credit provided by the Vietnam Bank for Social Policies on poverty reduction in Ninh Binh province, Vietnam. It also identifies and ranks the barriers of accessing the credit.

The study applies fixed-effects method to handle the panel data to examine the impact of the credit on poverty reduction. It also uses face-to-face interviews and group discussions to identify and rank the barriers of accessing to the credit.

The results show that the credit (represented by loan volume) positively and significantly helps improve household income, but does not help to improve household consumption. The major barriers include the time spent to get to the nearest bank branch, banking support services provided to clients and the transparency of household poverty status assessment.

Data are collected in three years and the number of the observations is limited to 300 households.

The VBSP preferential credit may need to be modified to significantly help reduce poverty and the VBSP and involved parties may need to eliminate the barriers so that the poor can have a better access to the credit.

The VBSP preferential credit is one of the reasonable sources that can help eliminate poverty though increasing household income.

The VBSP preferential credit can help increase household income, but does not really help improve household consumption due to the small volume of loans. In addition, banking support services and the household poverty assessment are seen as barriers to the access of the poor.