Economics of robots and automation in field crop production

Abstract

This study reviewed research published after 1990 on the economics of agricultural mechatronic automation and robotics, and identified research gaps. A systematic search was conducted from the following databases: ScienceDirect, Business Source Complete, Wiley, Emerald, CAB Abstract, Greenfile, Food Science Source and AgEcon Search. This identified 4817 documents. The screening of abstracts narrowed the range to a dataset of 119 full text documents. After eligibility assessment, 18 studies were subjected to a qualitative analysis, with ten focused on automation of specific horticultural operations and eight related to autonomous agricultural equipment. All of the studies found some scenarios in which automation and robotic technologies were profitable. Most studies employed partial budgeting considering only costs and revenues directly changed by the introduction of automation or robotics and assuming everything else constant. None examined cropping system changes, or regional and national impacts on markets, trade and labour demand. The review identified a need for in-depth research on the economic implications of the technology. Most of the studies reviewed estimated economic implications assuming that technology design parameters were achieved and/or based on data from prototypes. Data are needed on the benefits and problems with using automation and robotics on farm. All of the studies reviewed were in the context of agriculture in developed countries, but many of the world's most pressing agricultural problems are in the developing world. Economic and social research is needed to understand those developing country problems, and guide the engineers and scientists creating automation and robotic solutions.

Unequal futures of rural mobility: Challenges for a “Smart Countryside”

“…Rural areas are seeing widespread trials of agri-robotics, including self-driving tractors and smaller-scale harvesting robots. As with urban vehicles, these encounter legal barriers when using public roads or footpaths (Basu et al., 2020; Brodsky, 2016) but in controlled and monitored field spaces, their potential to reduce agricultural labour requirements is considerable (Lowenberg-DeBoer, 2020). Focusing on personal mobility and community needs, the scope for other forms of automation in rural areas is limited by commercial realities of scale and rates of return on investment (National Bus Operator) and a range of environmental factors.…”

Robots in tourism: A research agenda for tourism economics

“…As already mentioned, a TTH company would invest in robotic (and any other type of) technologies if only such an investment improves its financial results through increased sales, decreased costs or higher revenue growth than costs growth. Studies so far have focused on hospital robots (Cutillas et al, 2017), agricultural robots (Lowenberg-DeBoer et al, 2019), and industrial robots (Mehrez and Felix Offodile, 1994), among others. Currently, no study has empirically tested whether the adoption of service robots by TTH companies improves their financial results, although this link has been identified conceptually in the literature (Ivanov, 2019a; Kuo et al, 2017); hence, the following research questions for tourism economics are formulated: RQ 6.1: Do robots improve the financial bottom line of TTH companies? RQ 6.2: What factors influence robots’ impact on the financial bottom line of TTH companies? …”

An Extensive Review of Mobile Agricultural Robotics for Field Operations: Focus on Cotton Harvesting

“…The initial investment in row crop robotics systems may become very big for an average farmer [10]. As much as USD 319,864 for an 850 ha farm is required for investment in intelligent machines to achieve maximum break-even point [104].…”

“…Robots can work like a swarm of small robots to accomplish farm operation at a very competitive cost compared to current machines [106]. Non-horticultural crops like maize, soybean, barley, potato, wheat, and cotton have not been given priority in economic studies on robotic systems after evaluating several studies in databases such as GreenFILE, Business Source Complete, AgEcon Search, Food Science Source, Emerald, CAB Abstract, ScienceDirect, and [10]. Fortunately, the same challenges in agricultural robotics cut across different farming operations and crops.…”

“…However, advancements of machine vision, machine learning (especially deep learning), sensing, and end effector manipulation have fueled the application of robots in an unstructured agricultural environment. However, most of these machines have been deployed in horticultural crops only [10].…”