Key questions on the use of big data in farming: An activity theory approach

Lioutas, Evagelos D.; Charatsari, Chrysanthi; Rocca, Giuseppe La; Rosa, Marcello De

doi:10.1016/j.njas.2019.04.003

Cited by 65 publications

(71 citation statements)

References 117 publications

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“…Due to the increasing connectivity and transparency future digital agricultural systems will likely involve (Lioutas et al 2019 ), such a framework can help to relieve individual and collective anxieties about the unknown and embrace the process of, and aspirations to, transform human imagination (Dowd et al 2014 ). The absorptive capacity, or ability to turn information into beneficial decision making (Turner et al 2017 ), built through engagement with the technologies and individual learning through a design-process including the digi-MAST framework can be repeatedly and strategically drawn upon whenever new digital challenges to understanding present themselves (Calcagni et al 2019 ; Rauschmayer et al 2015 ).…”

Section: Discussion: Becoming a Digi-master On The Quest For Digital mentioning

confidence: 99%

Grasping at digitalisation: turning imagination into fact in the sugarcane farming community

et al. 2021

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Nutrient runoff from catchments that drain into the Great Barrier Reef (GBR) is a significant source of stress for this World Heritage Area. An alliance of collaborative on-ground water quality monitoring (Project 25) and technologically driven digital application development (Digiscape GBR) projects were formulated to provide data that highlighted the contribution of a network of Australian sugar cane farmers, amongst other sources, to nutrient runoff. This environmental data and subsequent information were extended to the farming community through scientist-led feedback sessions and the development of specialised digital technology (1622™WQ) that help build an understanding of the nutrient movements, in this case nitrogen, such that farmers might think about and eventually act to alter their fertilizer application practices. This paper reflects on a socio-environmental sustainability challenge that emerged during this case study, by utilising the nascent concept of digi-grasping. We highlight the importance of the entire agricultural knowledge and advice network being part of an innovation journey to increase the utility of digital agricultural technologies developed to increase overall sustainability. We develop the digi-MAST analytical framework, which explores modes of being and doing in the digital world, ranging from ‘the everyday mystery of the digital world (M)’, through digital ‘awareness (A)’, digitally ‘sparked’ being/s (S), and finally the ability of individuals and/or groups to ‘transform (T)’ utilising digital technologies and human imaginations. Our digi-MAST framework allows us to compare agricultural actors, in this case, to understand present modes of digi-grasping to help determine the resources and actions likely to be required to achieve impact from the development of various forms of digital technological research outputs.

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Section: Discussion: Becoming a Digi-master On The Quest For Digital mentioning

confidence: 99%

Grasping at digitalisation: turning imagination into fact in the sugarcane farming community

et al. 2021

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“…Intelligent technologies and big data offer farmers and other actors involved in the agrifood production and supply systems the opportunity to access enormous datasets that collect and store data derived from different sources, thus transforming agriculture from process-driven to data-driven. Such a shift alters the structure of physical-social farming systems, transforming them into cyber-physical-social systems [10].…”

Section: Introductionmentioning

confidence: 99%

“…Arguably, digital technologies and big data change the ways farming is practiced, affecting not only farm labor but also the social dimension of agriculture [9,37,38]. In this vein, the digitalization process also affects all the organizations that are variously connected with farming [10].…”

Section: Introductionmentioning

confidence: 99%

Extension and Advisory Organizations on the Road to the Digitalization of Animal Farming: An Organizational Learning Perspective

Charatsari

Lioutas

Rosa

et al. 2020

Animals

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Agricultural digitalization emerged as a radical innovation, punctuating the gradual evolution of the agrifood sector and having the potential to fundamentally restructure the context within which extension and advisory organizations operate. Digital technologies are expected to alter the practice and culture of animal farming in the future. To suit the changing environmental conditions, organizations can make minor adjustments or can call into question their purposes, belief systems, and operating paradigms. Each pattern of change is associated with different types of organizational learning. In this conceptual article, adopting an organizational learning perspective and building upon organizational change models, we present two potential change and learning pathways that extension and advisory organizations can follow to cope with digitalization: morphostasis and morphogenesis. Morphostatic change has a transitional nature and helps organizations survive by adapting to the new environmental conditions. Organizations that follow this pathway learn by recognizing and correcting errors. This way, they increase their competence in specific services and activities. Morphogenetic change, on the other hand, occurs when organizations acknowledge the need to move beyond existing operating paradigms, redefine their purposes, and explore new possibilities. By transforming themselves, organizations learn new ways to understand and interpret contextual cues. We conclude by presenting some factors that explain extension and advisory organizations’ tendency to morphostasis.

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“…For example, if there are loopholes in the network security firewall settings, third parties may access sensitive data, steal data, and/or destroy equipment. Finally, when compared to small farmers and other entities with weak abilities to defend their rights, large companies with more negotiating power are more be able to integrate their data and make decisions based on the information [70][71][72].…”

Section: Discussionmentioning

confidence: 99%

How Are Smallholder Farmers Involved in Digital Agriculture in Developing Countries: A Case Study from China

Xie

Luo

Zhong

2021

Land

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Digital transformation in agricultural practices may lead to a "digital divide" between small and large farms, owing to the characteristics and availability of digital technology. This paper sought to use a case study in Chongzhou County, Sichuan Province in China, to analyze how smallholder farmers in developing countries access such digital agriculture and share the benefits of digital agricultural transformation. Small farmers may own a larger scale farm through forming cooperatives; they are also indirectly involved in digital agriculture through agriculture outsourcing. The outsourcing market is expected to grow, which will allow for the evolution of a digital agricultural service platform, the development of a digital agricultural business organization consortium, and the continued expansion of a healthy digital ecology. This paper revealed important policy implications, stemming from the fact that the implementation of inclusive digital agriculture relies on two key shifts: (1) transformation from land scale operations to service scale operations and (2) from inclusive technological progress to inclusive organization innovation.

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Key questions on the use of big data in farming: An activity theory approach

Cited by 65 publications

References 117 publications

Grasping at digitalisation: turning imagination into fact in the sugarcane farming community

Grasping at digitalisation: turning imagination into fact in the sugarcane farming community

Extension and Advisory Organizations on the Road to the Digitalization of Animal Farming: An Organizational Learning Perspective

How Are Smallholder Farmers Involved in Digital Agriculture in Developing Countries: A Case Study from China

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