Search results

In rural areas, geographic location is key to market access and labor mobility of farm households. This paper aims to investigate the opportunities and constraints of smallholder rubber farmers in southwest China to adjust to the changes in economic and institutional conditions, namely the declining rubber prices, emerging land rental markets and growing off-farm job opportunities.

The empirical basis is a dataset of some 600 rubber farmers in Xishuangbanna Dai Autonomous Prefecture, Yunnan Province, collected in March 2015. The study uses instrumental variable and recursive bivariate probit models to account for possible endogeneity and selection bias.

With rubber prices in decline, the elevation of rubber plantations is an essential factor for the costs of access to the local factor markets and influences farm households' possibilities to adopt coping strategies. Notably, we find a U-shape type of relationship between the location and renting-out land due to the decline in rubber profitability. Rubber producers in low elevations are better bestowed with access to local markets. Households in high elevations, where rubber planting came in later, can shift to new crops like tea. However, the economic resilience of farmers in middle elevations is low due to their higher adjustment costs.

The paper provides a constructive basis for designing more location-specific development policies and can help avoid the past often ineffective blanket measures. Its implications have significant relevance for areas with similar conditions, for example, the remote, ethnic minority–dominated and mountainous rural areas in China.

The purpose of this paper is to examine the impact of farmers’ risk perceptions regarding rubber farming on their land use choices, including rubber specialization and crop diversification.

A cross-sectional survey data of some 600 smallholder rubber farmers in Xishuangbanna in Southwest China is employed. This paper develops a general conceptual framework that incorporates a subjective risk item into a model of farmers’ land use choices, thereby developing four econometric models to estimate the role of risk perceptions, and applies instrumental variables to control for the endogeneity of risk perceptions.

The results demonstrate that risk perceptions play an important role in smallholders’ decision-making regarding land use strategies to address potential risks in rubber farming. Smallholders with higher risk perceptions specialize in rubber farming less often and are more likely to diversify their land use, thereby contributing to local environmental conservation in terms of agrobiodiversity. The land use choices of smallholder rubber farmers are also associated with ethnicity, household wealth, off-farm employment, land tenure status, altitude and rubber farming experience.

This study contributes to a better understanding of the implications of farmers’ risk perceptions and shows entry points for improving the sustainability of rubber-based land use systems.

Urbanization is a main driver of the transformation from agricultural-based economies to service-based economies. At the same time, urbanization might also alter preferences and attitudes such as risk and time preferences that contribute to economic growth and foster this transition. To study the effect of urbanization, few studies have compared individual time or risk preferences in rural and urban settings, reporting mixed results. This study analyses how risk and time preferences alter along the rural–urban interface and assesses the correlation of socio-economic, socio-cultural and demographic characteristics with these preferences. Using such an approach provides insights how preferences are altered in areas of transition as the rural–urban interface mirrors different stages of urbanization.

Using experimental approaches, risk attitudes and time preferences of 1,117 agricultural and non-agricultural households were elicited along the rural–urban interface of the fast-developing Indian megacity Bengaluru in 2016/17. The study reports joint estimations of risk and time preferences and discusses the influence of urbanization on these preferences.

Results show that households are on average slightly risk-averse and highly impatient. The results also indicate a decline in discount rates towards rural areas while risk preferences do not considerably differ between those areas. This puzzling result may be explained by difference response of rural and urban areas to the Demonetization policy of the Indian government in 2016.

The research design compares jointly estimated risk and time preferences of agricultural and non-agricultural households of a rapidly urbanizing area in a low-medium income country.

Although prior studies have identified several technologies related to Industry 4.0 and their individual potential, it is still unclear how these technologies could be integrated to achieve better results. Based on this, we propose several collaborative networks combining technologies associated with Industry 4.0.

A literature review was performed using a research model to support the evaluation and identification of key and collaborative technologies related to Industry 4.0. We examined these technologies using hierarchical cluster analysis and principal components analysis, based on their characteristics.

The study identified big data, cloud computing, the internet of Things and cyber-physical systems as key technologies for Industry 4.0, and a further eight collaborative technologies that are strongly related to industrial performance. We found five collaborative networks with distinct goals in the context of Industry 4.0: (1) smart manufacturing; (2) technological platforms; (3) market reactiveness; (4) smart products and (5) flexibility.

The findings allowed us to create five pathways for future work on Industry 4.0 technologies via collaborative networks. In practice, this will help managers to improve their focus on priorities regarding the implementation of Industry 4.0 technologies.

This study provides insights into how to establish links between technologies through collaborative networks for certain purposes. In addition, we propose five future directions for these collaborative networks that require further investigation by researchers.