Network effects in Business Ecosystems – Learnings from a CSA case study in India

While underscoring the prominent role technological innovations play in the transition to Climate Smart Agriculture (CSA), studies have also noted that technology providers depend on access to wider networks for enhancing their ability to diffuse technological innovations (Long et al, 2016). It is well established that technology diffusion in a network is influenced by the structure of the network itself and that decisions pertaining to technology adoption are taken by economic agents in the network. It is also established that these decisions are not taken by economic agents in isolation but are influenced by decisions of other agents in the network (Abrahamson & Rosenkopf, 1997). However, the need for more research for gaining a better understanding of social influences, especially the influence of network structure on innovation diffusion was pointed out by Erik et al (2004) in their seminal paper “Business Ecosystems: A research framework for investigating the relation between network structure, firm strategy and pattern of innovation diffusion”. The present study has been contemplated in cognizance of the above and aims to find out the key network effects and social interaction effects that can influence diffusion of a technological innovation in a given business ecosystem. By identifying and analysing network effects and social interaction effects resulting out of interactions between agents in the specific context of CSA, our study also attempts to develop a new conceptual framework for CSA technology driven business ecosystems. For our research, we have adopted a case study approach wherein a start-up company which recently launched a unique, on-call irrigation service model in two regions of India, namely Rayalaseema region of Andhra Pradesh state and Vidarbha region of Maharashtra state was selected. The company introduced this irrigation service model by successfully re-engineering the “traveller irrigation” system and targeted the small and marginal farmers growing rainfall dependent crops such as groundnuts and soybeans for their business. This technological innovation has been positioned as a “climate-smart” adaptive water management solution that benefits farmers by ensuring efficient and timely delivery of irrigation to their crop fields. By applying the framework developed by Moore, (Moore, 1996a.) to our study, we were able to map the overall business ecosystem in which the company was operating at the “core business” level and “extended enterprise” level where there were interactions and exchanges taking place between the company and its direct and indirect customers and suppliers and also at the overall “business ecosystem” level where there were interactions and organizational arrangements between the company and government agencies as well as financial institutions and NGOs operating in the region. We also carried out a comparative analysis of the network and performance of the company in the two different regions it operates to gain better insights on the network effects. Our study found that network effects and social interaction effects such as network size and social risk did have an influence of diffusion of the climate-smart irrigation technology under study. Our study also brought out a conceptual framework for CSA technology driven business ecosystems where interrelationships and reciprocal interactions between agents viz.,CSA technology providers, farmers, policy makers, research institutes and financial institutions assume significance.