Search results

People with disabilities (PWD) produce aids using 3D printing in an inclusive MakerSpace in Germany. This study aims to demonstrate the pathways enabling people with disabilities to be “makers” of aids, creating a “medium-quality market”.

This study conceptualizes the foundation of the MakerSpace as a social innovation and traces supporting and hindering factors on three different layers: normative, structural and functional contexts.

3D printing can empower PWD to design and construct aids by themselves. The emerging “medium-quality” market offers potentials for availability for individualized aids. The design-thinking method used and the developed scalable approach empower PWD to create aids that best meet their own needs. The study found three arguments for printing aids that involve 3D printers: “New”: objects that are not available without a 3D printer. “Better”: objects that are available through established channels but were produced either more cheaply, quickly or on a more individualized level. “More”: objects that are available through other channels, but where 3D printing allows more of them to be produced for more people.

The qualitative study has limitations because of sample size and context dependency. Research has only been carried out in Germany. Future research should be conducted in other countries to generalize the results.

The article allows to understand the emergence of a new market for aids. It can steer producers (including PWD or sheltered workshops) in producing new aids and making them available to more people.

Understanding the functioning of the “new market for aids” can boost the accessibility of aids. Empowering PWD to produce aids can support their independence, self-determination and self-esteem. Supporting PWD to become producers of aids can support them in becoming experts and boost the quality and availability of aids.

All data presented has been collected by the authors.

The purpose of this paper is to analyze the hedging efficiency (HE) of weather index insurances (WII) based on a whole-farm approach. The aim is to identify how different types of WII affect the economic performance risk of real farms in the light of the heterogeneity of farm operations and natural conditions.

Using historic simulation, the HE of various hedging strategies is computed for 20 farms in regions with moderate natural conditions. A priori defined “standardized” WII and hedge ratios as well as ex post “optimized” strategies are analyzed. The latter is identified through a risk programming approach that determines the strike level and hedge ratio that would have minimized the volatility of each farm’s historic total gross margins (TGMs) ex post.

(i) The correlations between the weather indexes and the yields of the farms’ main crop (wheat) do not provide useful insights regarding the whole-farm HE because farms’ performance risk is considerably affected by volatile factors other than wheat yield; (ii) Standardized WII are ill-suited to hedge performance risk for the majority of studied farms; (iii) A considerable positive whole-farm HE could have been obtained on average if farmers had been able to use the “optimized” risk management strategy. Using farm-specific information thus seems to be essential for identifying meaningful hedging strategies.

This study provides added value by analyzing the HE of WII for 20 German crop farms in “moderate” regions. The results show that exemplary tests of WII in extreme conditions provide no decision support for farmers in other regions.

Drought-related climate risk and access to credit are among the major risks to agricultural productivity for smallholder farmers in Kenya. Farmers are usually credit-constrained due to either involuntary quantity rationing or voluntary risk rationing. By exploiting randomized distribution of weather risk-contingent credit (RCC) and traditional credit, the authors estimate the causal effect of bundling weather index insurance to credit on uptake of agricultural credits among rural smallholders in Eastern Kenya. Further, the authors assess farmers' credit rationing, its determinants and effects on credit uptake.

The study design was a randomized controlled trial (RCT) conducted in Machakos County, Kenya. 1,170 sample households were randomly assigned to one of three research groups, namely control, RCC and traditional credit. This paper is based on baseline household survey data and the first phase of loan implementation data.

The authors find that 48% of the households were price-rationed, 41% were risk-rationed and 11% were quantity-rationed. The average credit uptake rate was 33% with the uptake of bundled credit being significantly higher than that of traditional credit. Risk rationing seems to influence the credit uptake negatively, whereas premium subsidies do not have any significant association with credit uptake. Among the socio-economic variables, training attendance, crop production being the main household head occupation, expenditure on food, maize labour requirement, hired labour, livestock revenue and access to credit are found to influence the credit uptake positively, whereas the expenditure on non-food items is negatively related with credit uptake.

The study findings provide important insights on the factors of credit demand. Empirical results suggest that risk rationing is pervasive and discourages farmers to take up credit. The study results also imply that credit demand is inelastic although relatively small sample size for RCC premium subsidy groups may be a limiting factor to the authors’ estimation.

By implementing a multi-arm RCT, the authors estimate the factors affecting the uptake of insurance bundled agricultural credits along with eliciting credit rationing among rural smallholders in Eastern Kenya. This paper provides key empirical findings on the uptake of RCC and the effect of credit rationing on uptake of agricultural credits, a field which has been majorly theoretical.