Flood disaster has gained global attention due to the huge impact it has on human lives, economies, and sustainable environments. Flood disaster preparedness, which can significantly be influenced by disaster risk perception, has been highlighted as an effective way to manage flood disaster risk, as many other means have proved futile, yet no study has attempted using multiple dimensions to analyze this relationship in Ghana. Therefore, this study, using a survey of 369 households in the most flood-prone region, Accra Metropolis, analyzed the influence of flood disaster risk perception on urban households’ flood disaster preparedness. Based on the Protective Action Decision Model, the empirical models were constructed and estimated using the Tobit and binary logistic regression models. The results show that the majority of households (60.16%) were unprepared for flood disasters, and the perception of flood disaster risk and the sustainability risk posed by floods significantly affect flood disaster preparedness behaviours of households in a positive direction. The total number of flood disaster preparedness behaviours adopted was significantly related to probability, the threat to lives, sense of worry, and sustainability risk perceptions. Finally, income, education, and house ownership, among other household and individual characteristics, had significant positive effects on preparations for flood disasters. These findings suggest that effective policies to mitigate flood disasters must incorporate risk communication to boost households’ flood disaster preparedness.

Purpose: The purpose of this research is to examine the validity of the agriculture-induced environmental Kuznets curve (EKC) hypothesis with evidence from an autoregressive distributed lag (ARDL) approach with a structural break including real income and energy consumption in the model for Ghana over the period 1980–2014.Design/methodology/approach: The ARDL approach with a structural break was used to analyze the agriculture-induced EKC model which has not been studied in Ghana. The dynamic ordinary least squares (DOLS), canonical cointegration regression (CCR) and fully modified ordinary least squares (FMOLS) econometric methods were further used to validate the robustness of the estimates, and the direction of the relationship between the study variables was also clarified using the Toda–Yamamoto Granger causality test.Findings: The ARDL results revealed that GDP, energy consumption and agricultural value added have significant positive effects on CO₂emissions, while GDP²reduces CO₂emissions. The Toda-Yamamoto causality test results show a bidirectional causality running from GDP and energy consumption to CO₂emissions whereas a unidirectional long-term causality runs from GDP²and agriculture value-added to CO₂emissions.Practical implications: This finding validated the presence of the agriculture-induced EKC hypothesis in Ghana in both the short run and long run, and the important role of agriculture and energy consumption in economic growth was confirmed by the respective bidirectional and unidirectional causal relationships between the two variables and GDP. Thus, a reduction in unsustainable agricultural practices is recommended through specific policies to strengthen institutional quality in Ghana for a paradigm shift from rudimentary technology to modern sustainable agrarian technologies.Originality/value: This study is novel in the EKC literature in Ghana, as no study has yet been done on agriculture-induced EKC in Ghana, and the other EKC studies also failed to account for structural breaks which have been done by this study. This study further includes a causality analysis to examine the direction of the relationship which the few EKC studies in Ghana failed to address. Finally, dynamic ordinary least squares (DOLS), canonical cointegration regression (CCR) and fully modified ordinary least squares (FMOLS) methods are used for robustness check, unlike other studies with single methodologies.

Based on the survey data of 540 peasants in Sichuan Province, the probit and unordered multi-classification logistic model regression models were used to explore peasants’ differentiation on the transformation of willingness and behavior of land transfer and to provide a theoretical and empirical basis for promoting land intensification and large-scale management. The results show the following: (1) There is a significant negative correlation between the intention and behavior of part-time peasants, multiple occupations peasants, and non-agricultural peasants. (2) Part-time peasants and non-agricultural peasants promoted the change in willingness and behavior of land transfer out; part-time peasants, multiple occupations peasants, and non-agricultural peasants all promoted the willingness and behavior transformation of land transfer in. (3) The heterogeneity analysis results show that different household heads ages, the proportion of labor force in the total population of the household, and the terrain of cultivated land significantly impact peasants’ willingness and behavior of land transfer. Peasants’ non-agricultural differentiation is an important way to promote the rapid development of land transfer. The government should strengthen skills training and guidance services, broaden the channels for peasants to increase income, optimize the market environment of land transfer, and improve the social security system related to land transfer in order to promote the industrialization and large-scale development of agriculture.

Land use decision-making is a vital livelihood strategy associated with the rational collocation of livelihood asset endowments by rural households. Based on the perspective of livelihood heterogeneity, this paper collected the data from 540 farm households in 27 villages in three Sichuan Province counties to identify the land use decision-making characteristics of the household groups. A land use decision-making framework (LUDF) based on the sustainable livelihood framework (SLF) was established and dynamic and dual indicators were developed to divide the sample into six household groups. The household livelihood capital, livelihood strategies, and livelihood diversity were then analyzed at the regional and household group level, and the land use decisions of these household groups were explored, from which the following was found. (1) Overall livelihood capital in the study area was low, and except for human assets, there were few other assets, with households in the survey areas being more inclined to engage in non-farming livelihood activities; however, households in Nanjiang and Qionglai had greater livelihood activities choices than Luxian. (2) The LL-type household was the chief household group; the household group distribution in Qionglai was well-proportioned but uneven in Nanjiang and Luxian; and the HL-type, ML-type, and LL-type household livelihood strategy choices were polarized. (3) Most households were involved in land self-cultivation, followed by land transfer-in, land transfer-out, and land abandonment households. Specifically, there were more households that cultivated fragmented landholdings than specialized households with large-scale landholdings, the land transfer rate was relatively low, the transfer-in land area was far greater than the transfer-out land areas, and a small number of households that had abandoned their land were still involved in agricultural production. (4) There were obvious discordant human–land relationships and inefficient land uses in the study area. Based on these findings, relevant policy recommendations are given to improve farm household livelihood capital, optimize livelihood strategies, and assist in land use decision-making.