Not so ‘placeless’ after all. Understanding the spatial implications of the digital economy

Empirical studies on the geography of digital economic activities are currently lacking. This is due to digital economic activities remaining largely undefined in official economic statistics. This paper introduces a novel empirical pipeline to examine the spatial characteristics of the digital economy while addressing the challenges of data missingness. Firstly, we identify digital economic activities by using commercial websites and Natural Language Processing (NLP). Secondly, we study the geographical distribution of digital firms, as well as the mechanisms causing this distribution, through considering firms as the realisation of a latent spatial Poisson Point Process. In doing so, this paper enhances our understanding of urban processes by combining data created through advanced NLP techniques with spatial econometrics. Focusing on the case of London, UK, we identify digital economic activities by applying contextualized weak supervision to text scraped from firms’ websites. By doing so, we showcase how websites can complement, or even substitute official economic statistics, leading to a more complete understanding of the digital economy. Using this data, we proceed to inferring the causes of firms’ locations in space: indeed, firms can locate in space for exogenous reasons, such as the presence of infrastructure and public incentives, or endogenous reasons, such as knowledge spillovers. We base our analysis on estimating the inhomogeneous K-function, quantifying the spatial dependency between firms. Our study reveals a tendency for digital firms to cluster due to the importance of in-person interactions that cannot be explained simply by exogenous factors such as the attractiveness of the location. To our knowledge, the paper provides the first empirical evidence uncovering the persisting relevance of space and face-to-face interactions in the digital economy, prompting reflections on the geographical footprints of digitality.

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Publication Details

Journal
Environment and Planning B Urban Analytics and City Science
Published
2025-11-14
DOI
https://doi.org/10.1177/23998083251398897
Primary Topic
Human Mobility and Location-Based Analysis
Type
article
Field-Weighted Citation Impact
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article

Not so ‘placeless’ after all. Understanding the spatial implications of the digital economy

Emmanouil Tranos, Giulia Occhini, Levi John Wolf
Environment and Planning B Urban Analytics and City Science
Human Mobility and Location-Based Analysis
article

Not so ‘placeless’ after all. Understanding the spatial implications of the digital economy

Emmanouil Tranos, Giulia Occhini, Levi John Wolf
article en

Abstract

Empirical studies on the geography of digital economic activities are currently lacking. This is due to digital economic activities remaining largely undefined in official economic statistics. This paper introduces a novel empirical pipeline to examine the spatial characteristics of the digital economy while addressing the challenges of data missingness. Firstly, we identify digital economic activities by using commercial websites and Natural Language Processing (NLP). Secondly, we study the geographical distribution of digital firms, as well as the mechanisms causing this distribution, through considering firms as the realisation of a latent spatial Poisson Point Process. In doing so, this paper enhances our understanding of urban processes by combining data created through advanced NLP techniques with spatial econometrics. Focusing on the case of London, UK, we identify digital economic activities by applying contextualized weak supervision to text scraped from firms’ websites. By doing so, we showcase how websites can complement, or even substitute official economic statistics, leading to a more complete understanding of the digital economy. Using this data, we proceed to inferring the causes of firms’ locations in space: indeed, firms can locate in space for exogenous reasons, such as the presence of infrastructure and public incentives, or endogenous reasons, such as knowledge spillovers. We base our analysis on estimating the inhomogeneous K-function, quantifying the spatial dependency between firms. Our study reveals a tendency for digital firms to cluster due to the importance of in-person interactions that cannot be explained simply by exogenous factors such as the attractiveness of the location. To our knowledge, the paper provides the first empirical evidence uncovering the persisting relevance of space and face-to-face interactions in the digital economy, prompting reflections on the geographical footprints of digitality.

Environment and Planning B Urban Analytics and City ScienceVol. 53(1)
University of Bristol (GB)
Openalex Percentile: Top 65%
Human Mobility and Location-Based Analysis
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