Making sense of the digital growth machine

Abstract

I respond here to the ‘digital growth machine’ and its five sites of extraction, or hinterland types, as proposed by Jovanna Rosen and Luis Alvarez Leon. The five dimensions they outline cover both the domains of production and consumption. This is refreshing as contemporary scholarship too often focuses on one or the other, rarely combining the two. The five sites capture a wide array of practices defining digital capitalism. Here I raise questions about the metaphor of the ‘hinterland’ asking if it inadvertently grants a fixity to a highly unsteady and volatile field. I also ask how we might introduce organisational analysis to these discussions. I end by placing special emphasis on the task of uncovering the inner workings of the growth machine.

Holding the specificities of digital capitalism with the more general aspects of old-fashioned capitalism is not easy. Attending to both continuities and discontinuities however is easier said than done. Digital capitalism continues to involve the production and distribution of things. Production networks and consumption processes remain central. Raw materials, factories, offices, warehouses, labour processes, transport systems, telecommunications, regulatory rules, and finance are as crucial as ever. Having said that, the rise of internet platforms, the proliferation of new networked devices, and the constant introduction of new technologies have inarguably resulted in an increase in digital composition of accumulation processes and outputs.

To contend with this Jovanna Rosen and Luis Alvarez Leon outline five sites of extraction they call ‘hinterland types’. These include physical, highly tangible sites as well as sites that are more intangible. As noted, the production of things is no less important under digital capitalism. The extraction of natural resources and their transformation through a capitalist production network continues and indeed, expands. The first two types of hinterlands account for this: Material hinterlands and manufacturing hinterlands. The next three hinterland types account for the unique drivers and dynamics at the heart of digital capitalism: Fulfilment hinterlands make rapid, on-demand consumption possible. Computation hinterlands represent the infrastructural backbone of the digitalised economy, and signalising hinterlands take the form of social media activity which helps inscribe places and things with meaning. Widespread digitisation, as the authors note, shifts the organisational logics of global production networks and shifts spatial dynamics.

Hinterlands have long existed. Colonialism and industrialisation transformed the role of cities which quickly became critical spaces of mass production and consumption, and rural and peri-urban sites became spaces of extraction and disposal. Invoking several centuries of urban–hinterland relationships, the authors introduce the idea of the digital growth machine, contending with the newfound power of the tech sector and its digital bemouths. The digital turn results in new ways of mapping, controlling, optimising, and monitoring everything from weather to agricultural output to animals. It also requires new patterns of extraction that fit the always growing demand for new gadgets. The explosion of digital devices requires new and expanded production systems, which in turn have spawned new supply chain relations and manufacturing regions. On-demand consumption is also a defining aspect of life under digital capitalism or more specifically: platform capitalism. The authors discuss the spatial and logistics transformations driven by the mushrooming of large fulfilment centres outside cities to enable online orders. In simultaneously highlighting new production and consumption logics, they write alongside a tradition of speaking of accumulation regimes, capturing the tenuous unity between production and consumption without which capitalism swings towards crises (Harvey, 1982; Vidal, 2013).

I would submit that computational and signalling hinterlands represent two aspects of the digital growth machine that scholars tend to under-emphasise, and therefore the true contribution of the article lies here. Computational arrangements have undergone several transformations over the last 80 odd years. With the advantage of hindsight, it appears that each transformation resulted in computational infrastructure becoming more and more entwined with capitalist production, distribution, and consumption. In addition to what is outlined by the authors here, I would add that the most recent transformation – the rise of cloud infrastructure – has altered capitalist logics, rather than just increased computational demand. Cloud infrastructure, complete with its vast regionally distributed data centres, virtual machines and microservices architectures introduces new methods to take products to markets faster, lowers barriers to entry, and enables rapid scaling at minimal marginal cost (Narayan, 2022, 2026). Cloud as a hardware–software infrastructural assemblage certainly operates because of the vast tracts of land upon which the world's data centres exist, the energy and water guzzling cooling mechanism that prevent the data centres from combusting or malfunctioning, as well as the physical base of the internet. The authors join others in pointing out the deep tensions within new computational hinterlands (Edwards et al., 2025; Kollar, 2026). The competing claims on power grids, water sources, and land are cast in new light in this platform and AI-driven world where Big Tech makes enormous demands on planetary resources and urban hinterlands. I wonder, however, if we might flip the narrative – computational hinterlands produce new dynamics rather than simply consume resources. What are the active processes by which computational infrastructure generates new logics within firms and industries? My concern is that hinterlands as a frame may not fully capture the unsteady dynamism of digital capitalism that cloud infrastructure, speculative finance and asset-light platform business models catalyse.

Speaking of platforms, the fifth and final hinterland refers to social media platforms where content is produced, user-generated reviews submitted, and geolocated data is captured. The authors argue that various urban businesses – restaurants, cafes, shops, etc. – make themselves and their reputations known via digitally enabled signalling, something best seen as the generation of aesthetic markers. Platform users produce sanitised imaginaries of physical places in their pursuit of online and offline influence. Returning to cities and their insides and outsides, this form of signalling shapes expectations and decisions of economic actors (investing firms) and individuals (tourists). The authors, in crafting a frame that connects resource extraction, production, fulfilment, computation, and signalling, offer an interesting way of joining various dots, altogether broadening the scope of analysis.

Here I must make explicit that I am technically a sociologist, rather than an urban geographer, although I sometimes forget this given my compulsive tendency to engage the work of geographers. My comments are most certainly shaped by my disciplinary location (disciplinary hinterland?).

The authors situate their framework within the analysis of global production networks. Global production networks remain more or less the only space within critical geography that seriously engages with firm practices. A core question raised by the article merits deeper engagement: What are the organisational logics of this digital growth regime? How do we make organisational logics knowable? What are ‘old’ organisational logics and how do these get datafied, cloudified, and platformised? Classic literature on the rise of the post-fordist firm did explore organisational logics (Schoenberger, 1997). Does this remain useful or do we need new approaches? What of organisational form (in this particular digital age)? In other words: Is there a point where economic/urban geography might explicitly meet organisation studies?

It is important to examine the constitution of the digital growth machine and also its material effects. The risk is that our fields fixate on the impacts rather than the hard-to-see nature of the growth machine. The authors here do both. They also write more extensively about the machine – literally and metaphorically elsewhere (Alvarez León 2024; Rosen and Alvarez León, 2022). Nonetheless, this remains a reminder to myself and my fellow travellers to keep an eye on the machine as it gets more abstracted, more distributed, and more adamant of its invisibility. Effects are easier to see. They are all around us. The growth machine and its confused, contradictory logics, remains elusive, caught up in the shrouded domains of finance, management, technology, and the state.