by Dr. Tarlan Ahmadov – Society for Inclusive and Collaborative Entrepreneurship (S4ICE), Stuttgart, Germany
I was looking for patterns in how researchers have thought about technology and rural development over the past fifty years. I expected to find growth — more papers, more journals, more buzzwords. What I didn’t expect was to find a field that has essentially reinvented itself four times, each time with a different answer to the question: Why does this matter?
This is what I found.
The 1970s: Three Papers and a Satellite
In 1974, the entire field produced three papers. Three. They were about using satellite imagery — what we now call remote sensing — to help farmers in developing countries. That was the technological horizon. Remote sensing and, a decade later, GIS. Those were the only tools that showed up in any measurable way.
But it wasn’t just the technology that was narrow. The framing was too. Research was positioned as something done to rural communities, not with them. The dominant narrative was development aid: wealthy countries sending technology to poor ones. “Rural development” was the big theme, appearing in 45.6% of papers from this era. Sustainability was already there at 56.0%, but it wasn’t the sustainability we talk about today — it was pre-SDG, pre-climate crisis, pre-digital-everything.
For thirty-six years, this was a quiet field. Sixty papers a year, on average. Scattered. Uneven. The kind of research that gets published in conference proceedings rather than top-tier journals. The kind of research that doesn’t make headlines.
2010: The Year Something Clicked
Around 2010, I noticed a shift. Not a dramatic one — output jumped from roughly 250 to 400 papers per year — but a qualitative one. The term “digital agriculture” started appearing. Not as a buzzword, but as an umbrella. Three streams that had been running parallel — precision agriculture, ICT for development, and sustainable agriculture — suddenly started converging.
IoT entered the vocabulary at 2.3%. Machine learning appeared at 5.0%. Drones — or UAVs, as the literature prefers — made their first appearance at 0.8%. These numbers sound small, but they matter because they represent the first time the field began imagining a technological toolkit beyond satellite imagery.
Methodologically, something interesting happened too. Survey and questionnaire research grew from 13.9% to 18.3%. Researchers were no longer just building tools; they were asking whether people would actually use them. That shift from can we to will they is subtle but profound.
2015: The SDG Moment
The United Nations adopted the Sustainable Development Goals in 2015, and rural research changed almost overnight. I don’t mean gradually. I mean the following year, the Sustainability and SDG theme was present in 67.8% of papers. It had been 56.0% in the early period. This was a structural reorientation, not a trend.
The journal landscape shifted with it. Sustainability (Switzerland) became the dominant venue. Not because it was the most prestigious, but because it was fast, accessible, and perfectly aligned with the new normative frame. Journal of Rural Studies and Journal of Cleaner Production rose alongside it. The old engineering and remote-sensing venues didn’t disappear, but they were no longer setting the agenda.
AI and machine learning crossed a threshold in this period too — from 6.8% to 12.0%. Still not dominant, but no longer fringe. The Digital Transformation discourse appeared at 1.8%. The Circular Economy discourse at 1.6%. The vocabulary was expanding, and the questions were getting bigger.
2021: The Floodgates Open
And then came the exponential phase. I knew the numbers would be large, but seeing them still surprised me: 1,786 papers in just six years. A mean of 2,672.8 per year. A peak of 5,433 in 2025.
AI and machine learning became the fourth-most prevalent theme at 24.8%. Deep learning reached 5.6%. Big data as a technology reached 4.0%. Blockchain, digital twins, and 5G all appeared in the literature for the first time. The technological imaginary of rural research has gone from satellite imagery to a full stack of computational tools.
But here’s what gave me pause: the methods shifted decisively too. Modelling and simulation crossed 50% for the first time — 51.5% of all recent papers. Machine learning and data mining reached 14.8%. Together, computational approaches now account for roughly two-thirds of how this field studies itself.
Field experiments declined to 17.0%. Case studies to 11.9%. The Type–Token Ratio in abstracts dropped from 18.4% to 7.2%, meaning the language has become more standardised, more technical, more repetitive.
I don’t know whether to call that progress or not. The data don’t tell me. They just tell me it happened.
The Conversation That Changed
The most striking finding, for me, was not a number. It was a narrative shift.
The Development Aid discourse — the idea that technology is something wealthy countries send to poor ones — declined from 13.6% to 4.1%. That’s a 70% relative drop. In its place, the Sustainability and Smart Agriculture framings have risen to dominate. The language shifted from “technology as intervention” to “technology for global goals.”
The Digital Divide discourse tells its own story. It dipped to 0.3% in the Foundation period, then resurged to 2.5% in the Exponential phase. That U-shaped curve suggests the field had a moment of techno-optimism, then remembered that access and equity still matter.
And the Rural Development theme? It declined as an explicit category from 45.6% to 30.0%, even as the field exploded in size. Maybe the concept has become so pervasive it no longer needs naming. Maybe the focus has shifted from place-based communities to technology-mediated systems. The data raise the question. They don’t resolve it.
What I Take From This
Rural digitalisation research has transformed from a small, aid-focused niche into a mainstream, computationally intensive, sustainability-driven field. The volume is exponential. The methods are computational. The framing is global. The vocabulary is standardising.
But the connection to actual rural practice — to farmers, to communities, to the messiness of real places — is increasingly mediated by models and algorithms rather than field observation. That doesn’t mean it’s lost. The Socioeconomic factors theme held steady at 25.8%. The Food Systems discourse grew from 0.3% to 3.9%. The social dimensions are still there.
They’re just not as loud as the technology.
What happens next depends on whether the field can keep its polycentric character — its ability to hold multiple questions, multiple methods, multiple framings — while absorbing wave after wave of external innovation. The data show a field that has grown fast, shifted hard, and is still finding its balance.
I find that hopeful, in a way. Because fields that are still finding their balance are fields that are still alive.
