Search results

In Uganda, smallholder farmers produce about 70% of the food but receive very low prices on the sales channels they use. To improve farmers' livelihoods, other innovative sales channels such as farmers' markets (FMs) have to be explored. Therefore, the study aimed to determine the potential of establishing farmers' markets in Uganda, focusing on Kampala district.

A qualitative methodology was used to understand farmers' perceptions and the factors that could influence the success of the farmers' markets. In addition, the potential of FMs has been analyzed through the components of the Localized Agri-Food System (LAFS).

The respondents had a positive perception of the farmers' markets, and farmers have an urgent need for other sales channels that could be profitable for them. Factors that could influence the success of the FMs were highlighted, including infrastructure in the marketplace, transportation and taxation by the government.

The study had a limited sample size of the farmers, and it was carried out in 3 divisions of Kampala district, an urban area; thus, the findings cannot be generalized to fit the other regions of Uganda.

The LAFS showed that the foundation for establishing FMs is available; however, it has to be strengthened through the coordination of different stakeholders that work with the farmers.

Artificial Intelligence (AI) is a growing technology impacting several business fields. The agricultural sector is facing several challenges, which may be supported by the use of such a new advanced technology. The aim of the paper is to map the state-of-the-art of AI applications in agriculture, their advantages, barriers, implications and the ability to lead to new business models, depicting a future research agenda.

A structured literature review has been conducted, and 37 contributions have been analyzed and coded using a detailed research framework.

Findings underline the multiple uses and advantages of AI in agriculture and the potential impacts for farmers and entrepreneurs, even from a sustainability perspective. Several applications and algorithms are being developed and tested, but many barriers arise, starting from the lack of understanding by farmers and the need for global investments. A collaboration between scholars and practitioners is advocated to share best practices and lead to practical solutions and policies. The promising topic of new business models is still under-investigated and deserves more attention from scholars and practitioners.

The paper reports the state-of-the-art of AI in agriculture and its impact on the development of new business models. Several new research avenues have been identified.