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Business models of SMEs as a mechanism for scaling climate smart technologies: The case of Punjab, India

handle: 10568/100278
Many Climate Smart Agricultural (CSA) technologies fail to achieve their full potential impact due to low levels of adoption by smallholder farmers and difficulties in scaling CSA. This paper presents how small and medium-sized enterprises (SMEs) can act as change agents for the uptake of CSA technologies where their business models may be seen as adoption and scaling mechanisms. Drawing upon our fieldwork in Punjab (India) during which over 100 respondents have been interviewed, critical issues and enabling factors for the business model of two types of SMEs, i.e. farmer cooperatives and individual service providers of climate smart technologies have been identified. Enabling factors supporting adoption are driven by scientific and practical evidence of CSA technologies, good partnership between SMEs and research institutes, good customer relationships and effective channels through farmers’ field trials. Critical issues consist of distortive government subsidies on energy and the lack of market intelligence affecting the profitability of the business model. Scaling is enhanced through market intelligence and a favouring regulatory landscape. However, difficult socio-economic circumstances and distortive government subsidies limit the role of SMEs business model as mechanism for scaling
- Wageningen University & Research Netherlands
- CGIAR Consortium France
- Central Soil Salinity Research Institute India
- CGIAR France
- CGIAR France
food security, Climate smart agriculture, Business models, climate change, smes, agriculture
food security, Climate smart agriculture, Business models, climate change, smes, agriculture
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).51 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 1% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Top 10% impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 10%
