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# The new geography of “third places” in France: Explaining a deconcentration process outside metro areas

Clément Marinos, Sébastien Bourdin, Guy Baudelle

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Clément Marinos, Sébastien Bourdin, Guy Baudelle. The new geography of “third places” in France: Explaining a deconcentration process outside metro areas. Applied Geography, 2025, 175, pp.103493. 10.1016/j.apgeog.2024.103493. hal-04865983

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# The new geography of “third places” in France: Explaining a deconcentration process outside metro areas

Clément Marinos<sup>a,∗</sup> <sup>†</sup>, Sébastien Bourdin<sup>b,‡</sup>, Guy Baudelle<sup>c</sup>

## ARTICLE INFO

### Keywords:

Third place

Spatial diffusion

Geographical location dynamics

Deconcentration process

Non metro areas

France

## ABSTRACT

The article examines the spatiotemporal diffusion of third places (TPs) in France. Based on the observation of the growing extension of the phenomenon, it relies on an unprecedented database to provide an analysis by urban strata and time intervals, with particular attention to the period 2020-2022, the years of COVID-19. In line with our hypotheses, the results show a classical hierarchical top-down diffusion process. After a metropolitan surge until 2017, third places tend to establish themselves more diffusely across the territory, with a turning point correlated to the emergence of the COVID-19 crisis. Across all periods, the probability of creating a third place in a large metropolitan area is only slightly higher than that observed in smaller municipalities.

## 1. Introduction

Historically, the American sociologist Ray Oldenburg (1989) has introduced the term "third place" (TP) in the context of the desocialization of American society, linked to a trend of individualization (sub-urban expansion, individual transportation, increasingly dematerialized means of communication). In his analysis of social interactions and their deficiencies, he discussed the decline of these TPs, which facilitated informal meetings and the exchange of non-commercial services — essentially, places where people could meet outside of the home (first place) and work (second place). In this paper, we refer to this initial definition, which retains all its meaning (Burret, 2023; Krauss & Tremblay, 2024b).

However, since then, the rise of collaborative spaces, a form of TP, such as coworking spaces and fablabs in the 2000s (starting in 2005 in San Francisco), has spurred numerous research studies primarily in management, economics, sociology, and urban geography (Scaillez & Tremblay, 2017). Some of these studies emphasize their potential for fostering collaborative innovation within territories (Le Nadant et al., 2018), while others focus on the broader implications for local development (Moriset, 2017) and mobility (Flipo & Lejoux, 2020). For some

authors, TPs are characterized not only by their physical location but also by their unique social configuration: informal meetings, social interactions, flexibility, conviviality, community hubs, initiatives, projects, etc., and their openness to their environment (Burret, 2017; Fredriksson & Duriaux, 2018). Eventually, the concept became both clearer and more complex, particularly in relation to territorial development issues (Nadou et al., 2023).

Third places (TPs), especially coworking spaces, are part of the telecommuting dynamics observed before the COVID-19 crisis. Globally, there were 18,000 such spaces in 2018, and projections estimate around 40,000 by the year 2024.¹ This expansion can be attributed to several factors: an increasing number of remote workers prefer TPs as an alternative to traditional offices or home offices, while the growth of the gig economy contributes to a rise in freelancers, solopreneurs, and digital nomads seeking to develop social or professional connections through such spaces (Lee et al., 2019; Stam & van de Vrande, 2017). It is also known that some find access to more or less generic material resources (high-speed internet, printer, private office, etc.) necessary for their work (Gerdenitsch et al., 2016; Le Nadant et al., 2018).

The phenomenon of TPs is no longer exclusively metropolitan. In France, 46% were located outside metropolitan areas as early as 2018.²

This article is part of a special issue entitled: New Working Spaces published in Applied Geography.

* Corresponding author.

E-mail address: clement.marinos@univ-ubs.fr (C. Marinos).

¹ www.statista.com/statistics/554273/number-of-coworking-spaces-worldwide/.

² francetierslieux.fr/wp-content/uploads/2022/08/carte-ou-sont-les-TL-Rapport-France-tiers-lieux-2021.pdf.

<footnote><sup>a</sup> LEGO Research Unit, Southern Brittany University, Campus Tohannic-BP 573, 56017 Vannes Cedex, Vannes, France</footnote>

<footnote><sup>b</sup> EM Normandie Business School, METIS Lab, Caen, France</footnote>

<footnote><sup>c</sup> ESO-CNRS Research Unit, Department of Geography and Planning, Rennes 2 University, Rennes, France</footnote>
This share reached 53% in 2020 and 62% in 2023. TPs are now present in a wide range of geographical contexts, from large metropolises to small towns and rural areas, thanks to their flexible model and adaptability to local needs. Outside major urban centers, their emergence is often associated with specific dynamics such as responding to a lack of offerings in the area or forming a community in search of a space (Edouard, 2024; Krauss & Tremblay, 2019, 2024a).

However, despite this rapid expansion, there are still gaps in understanding their spatial diffusion, especially in the changing context of evolving work dynamics, particularly the acceleration of remote working (Leclercq-Vandelannoitte & Isaac, 2016). Indeed, most research has focused on the location factors of TPs (Mariotti et al., 2023; Méndez-Ortega, Smit & Micek, 2024), their impacts at the local level (Mariotti et al., 2017; Akhavan & Mariotti, 2018; Jamal, 2018; Mariotti et al., 2021; Di Marino et al., 2023; Konecka-Szydlowska & Sikorska-Długaj, 2023), or their specificities in metropolitan areas (Di Marino et al., 2023; Mariotti & Pacchi, 2021). However, studies on the spatial diffusion of TPs are lacking, often due to the unavailability of data, especially at the national level. Yet, the COVID-19 pandemic had a significant impact on the acceleration of telecommuting and new forms of work outside "traditional" offices (Belzunegui-Eraso & Erro-Garcés, 2020). Several studies have highlighted that some employees sought to "go green" and work remotely, with some permanently settling in rural areas (Colomb & Gallent, 2022; Willberg et al., 2021). Consequently, it can be assumed that communities sought to attract these workers by developing a TP offering (Mariotti & Manzini Ceinar, 2021).

In this context, this study aims to make a significant contribution to the understanding of the geography of work and its contemporary evolution through original geographical analysis. It seeks to address identified gaps by examining the spatial diffusion of TPs in France based on systematically collected national-scale data, considering their creation date and the size of the hosting localities. Furthermore, we aim to determine if the COVID-19 pandemic has had a significant impact on their diffusion, particularly by fostering an expansion from large cities to smaller ones. Our research question therefore is: to what extent do we observe a hierarchical spatial diffusion pattern of TPs in France, and how has the pandemic accelerated this process? To achieve this, we use an original and comprehensive database geolocating TPs in France and adopt a logit model to assess their probability of occurrence based on the size of hosting localities.

Relying on a public database of 1532 TPs provided by France Tiers-Lieux, this research aims to contribute to the spatial analysis of TPs and enrich the literature on hierarchical spatial diffusion of innovations. By providing a new empirical framework, it sheds light on how TPs, as a territorial innovation (Doloreux et al., 2019; Ross & Ressia, 2015), spatially diffuse within an urban and rural hierarchy. This study also examines the impact of shocks such as the pandemic on the dynamics of this diffusion. It explores how such a disruptive event can accelerate or modify diffusion trajectories, thus providing a fresh perspective on theories of spatial spread of innovations (Bokányi et al., 2022; Hagerstrand, 1965; Saint-Julien, 2007). For policymakers, our results offer essential insights for designing more inclusive and adaptive planning policies to strengthen the resilience of territories in the face of future crises.

We present the literature review and methodology, then introduce and discuss the results before concluding and making recommendations for public action.

# 2. Literature review

## 2.1. The TP as a multifunctional place and a territorial innovation

The concept of TP emerged within American society in a context of increasing individualism, attributed to various factors such as the widespread use of information and communication technologies, the rise of individual transportation, urban sprawl (Konecka-Szydlowska &

Sikorska-Długaj, 2023), and the decline of traditional socialization places like cafes, bookstores, lounges, bars, libraries, civic associations, and religious organizations. In its broadest sense, TPs are defined as physical proximity spaces where friends, neighbors, and strangers can regularly and sociably gather, sharing a common space (Rhubart et al., 2022). This extensive understanding of the concept is less predominant in France, where TPs are often assimilated to spaces dedicated to specific activities. The scientific community has widely embraced this concept since the 2010s, thanks in part to the pioneering work of sociologist Burret, who defines it as a "social configuration where the encounter between individualized entities intentionally engages in the conception of common representations" (2017).

The literature dedicated to TPs is characterized by the diversity of explored perspectives depending on the period of time and countries considered. Some researchers have focused on examining their role in promoting collaborative innovation, notably concentrating on coworking spaces (Cabral & Van Winden, 2016; Clifton et al., 2014; Marchegiani & Arcese, 2018). These works highlight their ability to facilitate idea exchange, stimulate entrepreneurial creativity, and foster the emergence of collaborative projects. Other research has scrutinized their technological aspect through makerspaces or hacklabs (Zheng, Lu, & Tianhong, 2022; Smith, 2017). These studies have brought to light the central role of TPs in promoting technology, collaborative manufacturing, and hands-on learning. It is also important to underline that several researchers study TPs in a very broad manner, including cafes, barbershops, and shopping malls (Crick, 2011; Finlay et al., 2019; Rice, 2009; Saey & Fross, 2015).

Another field of study has focused on their contribution to territorial development and urban planning (Mariotti et al., 2021; Avdikos & Merkel, 2020; Jamal, 2018). This research emphasizes their significant impact on neighborhood revitalization, local economic stimulation, and the creation of more inclusive urban spaces (Leducq et al., 2019). Finally, other works have investigated them as spaces for access to culture, highlighting their ability to foster artistic creativity and cultural exchange (Lippman, 2015). TPs are, therefore, multifunctional entities, transcending the traditional boundaries of spaces dedicated to a specific activity to encompass a variety of functions and social impacts.

## 2.2. TPs in the French context

In the French context, authors like Leducq et al. (2019) indicate that, unlike foreign collaborative spaces, TPs emerge from both private and public sectors. Additionally, even if most of these spaces in intermediate urban areas are quite modest in size and influence, they tend to be growing, especially since the COVID-19 health crisis (Bourdin et al., 2024). It could explain the fact that TPs receive special attention from public institutions. Since 2017, local authorities and the central government have been conducting promotion and collaboration campaigns accompanied by project calls to support their development, with the priority of creating a network across the national territory, from metropolises to the smallest localities.

As evidence of this commitment, the non-profit association France Tiers-Lieux, a public interest organization mandated by the Government, has conducted several inventories of TPs since its creation in 2017 to measure the evolution of the phenomenon. It should be noted that for France Tiers-Lieux, TLs share the common traits of pooling spaces and skills, blending activities, and bringing together an engaged citizen collective to foster cooperation in addressing the challenges of their territory. An excellent map has been published in 2022 (Fig. 1). To our knowledge, no other country benefits from such a reliable official inventory, regularly updated. The state of affairs in 2023 provided us with even more exceptional data, including creation dates, on which this research is based. The case of France is particularly interesting to study because, like Italy, it is often considered not to be very innovative, although both countries stand out for the intensity of fablabs creation (Ramella & Manzo, 2018).
Furthermore, TPs can be considered a form of territorial innovation of a social or organizational nature. These "micro-clusters" (Clifton, 2022; Doloreux et al., 2019; Ross & Ressia, 2015) are characterized by their hybrid nature between work and leisure, mixing professionals, citizens, and users (Oldenburg, 1989), and the episodic interaction between participants, where "relational assets" are created (Torre, 2018). In other words, they are various and not limited to technological or disruptive innovations (Capdevila, 2017; Scaillerez & Tremblay, 2024).

## 2.3. The spatial diffusion dynamics of TPs at a national scale: theoretical perspectives to address empirical knowledge gaps

This research started from the observation that very little work has been done on the geography of TPs on a national scale, and even less in terms of spatio-temporal dynamics, as successive reviews of the literature have noted (Baudelle, Bourdin, et al., 2023; Leducq & Ananian, 2019; Liefooghe, 2018; Liefooghe et al., 2024; Waters-Lynch et al., 2016). The few analyses conducted on a national territory provide little explanation of the distribution of TPs, whether for Switzerland (Patt, 2019), Slovakia (Holienka & Racek, 2015) or Japan (Uda & Tomokazu, 2016). A study of large Russian conurbations alone suggests some explanatory factors, but without testing them (Rutkauskas et al., 2019). An article on four Central European countries confines itself to observing the initial implantation in capital cities and a close correlation between city size and the number of TPs (Rafaj et al., 2024). For Spain, the high concentration of TPs in economic centers has been similarly demonstrated in connection with economic agglomeration factors (Coll-Martínez & Méndez-Ortega, 2024). Conversely, lower real estate costs outside major centers have been put forward in relation to Greece (Avdikos & Kalogeresis, 2016) and Switzerland (Patt, 2019), but this explanation appears somewhat reductive (Merkel, 2015). A number of studies have examined the effect of the COVID-19 pandemic on the possible deconcentration of TPs in a number of countries (Akhavan et al., 2023), including Ukraine, where war is a powerful but very specific explanatory factor (Zhurbas et al., 2024). Naturally, apart from France, the only country to have undergone in-depth explanatory analysis appears to be Italy (Mariotti & Di Matteo, 2020; Akhavan et al., 2022; Mariotti et al., 2023).

This deficiency of studies—even only empirical— at the national level is due to the relatively recent nature of the phenomenon, the lack of reliable and regularly updated data at this scale, and the various legal forms that TPs can adopt. Noteworthy, however, are the works of Méndez-Ortega et al. (2023), seeking to identify the main location factors in four European countries (Germany, Spain, France, and Poland). Baudelle et al. (2024) and Liefooghe et al. (2024) have raised questions about the diffusion in the French territory but, due to a lack of available information on the creation dates of TPs, were unable to develop a diachronic study of their diffusion.

The second point that prompted this investigation is that few papers focus on the location factors of TPs from a theoretical point of view, all the more so on a national scale. Regardless of their theoretical orientation (neoclassical, behavioral, institutional or evolutionary), most location studies focus on a single conurbation (Baudelle, Bourdin, et al., 2023; Di Marino et al., 2023; Mariotti & Micek, 2024; Tomaz & Henriques, 2023). However, the results of Mariotti et al. (2023) show that suburban areas near large cities attract TPs, as do peripheral and inland areas, although to a lesser extent. At the regional level (NUTS 2), Méndez-Ortega et al. (2022) analyzed the location of TPs relying on several factors such as GDP, internet access, population density and so on. Similarly, several publications have set out to identify the various socio-economic factors influencing location outside metro areas: Vogl et al. (2024) from the available literature, Tomaz et al. (2022) empirically on the basis of surveys in France, Belgium and Portugal, and Bourdin et al. (2024) using a spatial durbin model applied to the French territory. A very original study on Germany demonstrates the close relation between the precise location of TPs on one side and land use and

so-called "points of interest" accessible in their vicinity on the other side (Hölzel et al., 2022). These various authors conclude on the importance of some of these factors in their analyses but do not consider so much, as we will try to manage, the dynamics of diffusion over time.

Therefore, with the aid of newly available data, this article aims to introduce the expansion of the phenomenon on a national scale and shed light on its theoretical underpinnings. To achieve this, within the field of location theory studies (1998), the article employs the theory of the propagation of innovation waves (Hägerstrand, 1952). This very fruitful classical theory has been somewhat neglected by space studies (Dicken & Lloyd, 1990; Marianov & Eiselt, 2024-a; Pumain, 2023; Raimbault, 2021). According to it, any object emerging in space and subsequently diffusing geographically is considered an innovation, in the common sense of a new localized phenomenon (Crescenzi et al., 2007; Caragliu & Nijkamp, 2016). In this context, we consider the TP as an innovation whose dissemination in space and time will be studied whereas most recent studies consider only spatial diffusion and not temporal diffusion in their models.

Geographers understand that within this theoretical framework, only the appearance at a specific point in geographical space at a given moment matters. Size or attendance, therefore, do not come into consideration. However, the date of introduction is crucial as the analysis aims to examine and explain the speed, vectors, and spatial modalities of the diffusion of the study object in space. It is known that, traditionally, this dissemination can take on several main theoretical configurations: hierarchical (from the top to the base of the settlement system), by contagion (neighborhood effect), or linear (along a transport axis) (Cliff & Haggett, 2005; Hägerstrand, 1967; Morril et al., 1988; Saint-Julien, 2007).

Within that field of spatial diffusion studies through time, we hypothesize a spatiotemporal dissemination of a hierarchical type, even though the process is naturally never exclusively or purely top-down, often combining with neighborhood contagion (Bokányi et al., 2022; Hägerstrand, 1965; Saint-Julien, 2007). Indeed, larger urban centers have a greater probability of being pioneering emission centers due to their size, which promotes socio-economic and spatial interactions (Saint-Julien, 1992). This downward hierarchical diffusion is particularly relevant for technological innovations, with the metropolis being the "archetype of the territory of innovation" (Aubry, 2020), its system being both integrated and open, explaining the "metropolitan advantage" (Halbert, 2010). Connectivity then facilitates the spread of innovations that have emerged within them, with propagation subsequently reaching other urban levels (Pred, 1977; Morril et al., 1988). Naturally, there are alternative forms of diffusion within urban systems, as medium-sized agglomerations can precede metropolises, as in the famous Beatles model (Haggett, 2001).

The hierarchical diffusion model (or waterfall or cascade model) is not only the most classical (Hägerstrand, 1952) but also the most common in the diffusion within a national space for many economic phenomena such as business services (Baudet-Michel, 2001; Daudé, 2001), technological innovations (Roche & Humeau, 1999), or socio-cultural phenomena like sports (Augustin, 2007), games (Huang & Gould, 1974), new forms of commerce (Benoit et al., 2002; Farag et al., 2006; Saint-Julien, 2007), divorces (Doignon et al., 2022), or non-marital births (Doignon, 2020). According to all these studies, hierarchical diffusion downward is particularly valid in the initial phase, precisely corresponding to our study, which is relatively recent.

The literature on TPs has indeed shown their initial establishment in the largest metro areas (Avdikos & Merkel, 2020; Moriset, 2017), with some even considering them exclusive to metropolitan areas (Bourdin, 2017). However, since then, the phenomenon has spread to other urban levels and even to rural areas (Flipo & Lejoux, 2020; Foertsch, 2022; Hölzel & De Vries, 2021; Jamgotchian & André, 2017; Kastner, 2020; Krauss & Tremblay, 2019; Leducq et al., 2019; Liefooghe, 2018). The "proliferation" of coworking spaces, notably the dominant form of TPs, logically results in a multiplication of their locations (Brinks, 2022). The
above-mentioned study covering four countries distinguishes three phases in the geographical expansion of coworking spaces (Méndez-Ortega, Smit & Micek, 2024): an initial metropolitan wave, a second wave outside large urban regions, and a final stage benefiting rural areas, linked to the Covid-19 pandemic (Amstad, 2019; Burret, 2021), which has favored "working from anywhere" (Kunze et al., 2021).

## 3. Methodology

The exploited public database provided by France Tiers-Lieux incorporates the 1542 TPs created and documented in France until October 2023. For each one, we have the creation date and address (and consequently, the municipal population). To measure the effect of hierarchical diffusion of TPs, we split our sample into several sub-periods, each comprising a quarter of the established establishments. The pioneering innovators cover a long initial launch period up to the year 2017, early adopters correspond to the years 2018–2020, the early majority coincides with 2021–2022, while the followers joined the movement with a delay, in the last year 2023. The terminology follows the descriptors used by Rogers (1995).

The explanatory variable of specific interest to us is the population size of the municipality (Pop), given that we are testing the hypothesis of hierarchical spatial diffusion. We have also added socio-economic variables that may explain the location of TPs based on their characteristics and functions presented above. Firstly, we have the variable "HigherEduC", representing the proportion of the population with higher education. As TPs often serve as hubs for intellectual and creative exchange (Capdevila, 2022), cities with a high percentage of educated individuals might experience a higher demand for such spaces, where networking, learning, and collaboration are encouraged (Yacoub & Haefliger, 2022). This correlation is supported by Florida's study (2002), linking the level of education to the prevalence of innovative spaces.

Next, the variable "Tertiary" refers to the importance of the tertiary sector in a given municipality. This sector is particularly relevant to office activities and has been most affected by the advent of telecommuting with Covid-19 (Belzunegui-Eraso & Erro-Garcés, 2020). The variable "BusinessCreation" measures the rate of business creation per municipality, as TPs are often catalysts for entrepreneurs and startups, providing a space for collaborative work and mutual support. A high level of business creation activity can stimulate demand for such spaces (Stam & van de Vrande, 2017).

Finally, the variable "Unemploy", referring to the local unemployment rate, can explain another form of "necessity" entrepreneurship (Block et al., 2015; Faria, Cuestas, & Gil-Alana, 2009). According to van der Zwan et al. (2016), unemployed individuals may choose to start their own entrepreneurial activity to make ends meet. TPs can be preferred spaces to host this type of activity as they offer a place for socialization and networking and facilitate collaboration and knowledge sharing, creating an environment conducive to innovation and the development of new businesses (Jamal, 2018). Additionally, by providing resources such as shared facilities and expert advice, TPs reduce entry barriers for entrepreneurs from disadvantaged backgrounds or facing unemployment (Rudman & Aldrich, 2022).

To analyze the effect of these variables on the probability of the emergence of a TP, we opted for a Zero-Inflated Negative Binomial (ZI-NB) regression model, like others (Mariotti et al., 2023). This choice is motivated by the nature of our dependent variable, which is the count of TPs in a given municipality. The ZI-NB model is particularly suitable for our data due to the presence of overdispersion and a large number of zero counts (municipalities with no TPs). With this model, we can identify the factors that are statistically significant in predicting the presence of TPs and quantify the marginal effect of each variable on the probability of the emergence of these TPs.

In our ZI-NB model, the count of TPs Y in each municipality is modeled using two components: a logit model for the excess zeros and a

negative binomial model for the count data.

The logit part of the model predicts the probability $\pi_i$ that the count is always zero (structural zero) for a municipality i.

$$ \text{Logit} (\pi_i) = z_i\gamma $$

where: $\pi_i$ is the probability that municipality i belongs to the “certain zero” group; $z_i$ is a vector of covariates influencing the zero-inflation part; $\gamma$ is a vector of coefficients for the zero-inflation part. The count part of the model predicts the number of TPs $Y_i$ for municipalities that are not in the “certain zero” group.

$$ \text{Log} (\lambda_i) = x_i\beta $$

where: $\lambda_i$ is the expected count of TPs for a municipality i; $x_i$ is a vector of covariates influencing the count part; $\beta$ is a vector of coefficients for the count part.

The negative binomial distribution includes a dispersion parameter $\theta$ to account for overdispersion. The probability distribution of the observed count $Y_i$ is given by:

$$ P(Y_i = y) = \begin{cases} \pi_i + (1 - \pi_i) \left(\frac{\theta}{\theta + \lambda_i}\right)^{\theta} & \text{if } y = 0 \\ (1 - \pi_i) \frac{\Gamma(y + \theta)}{\Gamma(y + 1) \Gamma(\theta)} \left(\frac{\lambda_i^{\theta}}{(\theta + \lambda_i)^{\theta + y}}\right) & \text{if } y > 0 \end{cases} $$

where $\Gamma(\cdot)$ is the gamma function.

## 4. Results

In the context of our longitudinal analysis from the creation of the first TPs to the present day, the statistical results reported in Table 1 reveal significant trends related to various socio-economic indicators. The coefficients in Table 1 indicate the relationship between various predictors and the likelihood of establishing a TP. The variable representing the size of the municipality shows a coefficient of 0.007, statistically significant at the 5% level. This result suggests that the probability of establishing a TP is slightly increased with the growth of the municipality size, although this effect is relatively weak. The positive and significant coefficients across all periods suggest that municipalities with larger populations are more likely to host TPs. This is likely due to the higher demand for flexible working environments in densely populated areas.

Regarding the education level of the local population, the significant positive coefficients indicate that areas with a higher proportion of individuals holding higher education degrees are more likely to have TPs. This reflects the role of these spaces in attracting knowledge workers and fostering innovation. The study by Stam and van de Vrande (2017) highlights the role of TPs as spaces fostering innovation and networking for highly qualified individuals. Graduates of higher education are drawn to these spaces due to the flexibility, autonomy, and stimulating environment they offer, meeting the needs of knowledge workers and supporting entrepreneurship. TPs serve as platforms for knowledge exchange, creative collaboration, and professional development, making these spaces particularly suitable for populations with a high level of education.

The tertiary sector shows a positive and significant coefficient of 0.033, indicating that municipalities with a higher proportion of activities in the tertiary sector (services, finance, and information technology) have a moderately increased probability of hosting TPs, as these spaces offer environments conducive to the interactive nature of these industries (Marchegiani & Arcese, 2018). This finding aligns with the characteristics and needs of industries within the tertiary sector, which often require flexible, collaborative, and innovative working environments. Coworking spaces are particularly well-suited to the interactive nature of tertiary sector activities. The service, finance, and IT industries thrive on collaboration and networking, and coworking spaces facilitate
<table><caption>**Table 1**
Zero-inflated binomial estimation results.</caption><thead><tr><th rowspan="2"></th><th>Model (1) ZI-NB</th><th>Model (2) ZI-NB</th><th>Model (3) ZI-NB</th><th>Model (4) ZI-NB</th><th>Model (5) ZI-NB</th></tr><tr><th>Total</th><th>Innovators<br>before 2018</th><th>Early adopters<br>2018-2020</th><th>Early majority<br>2021-2022</th><th>Followers<br>after 2022</th></tr></thead><tbody><tr><td>Pop</td><td>0.007**<br>(0.005)</td><td>0.009**<br>(0.002)</td><td>0.012***<br>(0.001)</td><td>0.002**<br>(0.005)</td><td>0.002**<br>(0.001)</td></tr><tr><td>HigherEdu</td><td>0.003***<br>(0.04)</td><td>0.008**<br>(0.039)</td><td>0.01***<br>(0.007)</td><td>0.006***<br>(0.006)</td><td>0.005***<br>(0.012)</td></tr><tr><td>Tertiary</td><td>0.033**<br>(0.001)</td><td>0.021**<br>(0.000)</td><td>0.042**<br>(0.01)</td><td>0.034**<br>(0.019)</td><td>0.029**<br>(0.002)</td></tr><tr><td>BusinessCreation</td><td>0.012**<br>(0.008)</td><td>0.024**<br>(0.001)</td><td>0.019**<br>(0.004)</td><td>0.015**<br>(0.005)</td><td>0.021***<br>(0.031)</td></tr><tr><td>Unemploy</td><td>0.062**<br>(0.005)</td><td>0.074**<br>(0.012)</td><td>0.069***<br>(0.003)</td><td>0.057**<br>(0.009)</td><td>0.073***<br>(0.005)</td></tr><tr><td>Pseudo R2</td><td>0.522</td><td>0.546</td><td>0.561</td><td>0.479</td><td>0.53</td></tr><tr><td>Log Likelihood</td><td>-784.55***</td><td>-747.69***</td><td>-738.67***</td><td>780.56***</td><td>-729.63***</td></tr><tr><td>Vuong Test</td><td>2.99***</td><td>2.56***</td><td>2.48**</td><td>2.67***</td><td>2.44***</td></tr></tbody></table>

Source: authors

this by providing open, shared environments that encourage interaction among professionals from diverse fields (Méndez-Ortega, Micek & Malochleb, 2022).

Furthermore, municipalities characterized by entrepreneurial dynamism have a greater probability of hosting TPs. This can be explained by the fact that TPs are often seen as catalysts for innovation and entrepreneurship (Yacoub & Haefliger, 2022). They naturally attract entrepreneurs, startups, and creatives seeking stimulating spaces to develop their ideas and projects. The presence of a thriving entrepreneurial ecosystem creates a need for flexible and collaborative work environments, which are the defining characteristics of TPs. These spaces offer vital resources and a supportive community that can greatly boost the growth and success of new ventures (Jamal, 2018). Moreover, TPs cultivate an atmosphere of innovation by promoting the exchange of ideas and expertise among diverse groups of professionals. This environment is especially advantageous for startups and creative individuals who depend on networking and collaboration to advance their projects (Howell, 2022).

Finally, an increase in the unemployment rate in a municipality is associated with a significantly higher probability of establishing a TP. This is a less commonly observed result in the literature. Several explanations can be put forward. Firstly, in contexts of high unemployment, individuals may be more inclined to explore entrepreneurship as an alternative to traditional employment (Faria et al., 2009). This is then a form of constrained entrepreneurship, known as "necessity entrepreneurship" (van der Zwan et al., 2016). TPs provide essential collaboration and networking spaces for those looking to launch new businesses or independent initiatives. Moreover, entrepreneurs facing constraints often seek small office spaces to get started. From this perspective, TPs can be considered suitable spaces. Secondly, TPs provide a social and professional framework that can address the isolation often associated with necessity entrepreneurship (Block et al., 2015). TPs promote the creation and maintenance of such networks, facilitating the exchange of information and access to unexpected professional opportunities (Gerdenitsch et al., 2016). Finally, local authorities in areas with high unemployment may support the creation of TPs as a strategy for local economic development and revitalization (Ross, 2018). These spaces can be perceived as investments in human capital and social innovation, leading to a more resilient and diversified economic fabric (Tomaz & Henriques, 2023).

If we focus on our explanatory variable (Pop) and compare the coefficients across different periods, several elements stand out. In the period before 2018, we observe a positive and significant coefficient of 0.009, suggesting that in the early stages of TP development, urban areas with larger populations were favored, likely due to their stronger economic and entrepreneurial activity. As for the period from 2018 to

2020, we observe a slight decrease in the coefficient to 0.012. This indicates that although population size continues to have a positive influence on the probability of TP emergence, the effect is less pronounced. This trend may reflect a gradual diffusion of TPs to less populated areas, following a hierarchical diffusion model where innovations spread from urban centers to less central areas. Our results clearly highlight the impact of Covid. Indeed, for the periods 2021-2022 and after 2022, we observe a further decrease in the coefficient to 0.002. This suggests that population size is no longer a major determinant of new TP emergence during these periods. Therefore, we would have a more uniform distribution that does not necessarily favor municipalities with larger populations. This shift may be attributed to the increased acceptance and implementation of remote work during and after the Covid-19 pandemic, which reduced the need for individuals and businesses to be located in densely populated urban areas. Consequently, coworking spaces started to establish themselves in more diverse and less populated regions, catering to the new demand for flexible and remote working environments. From this perspective, our results confirm the idea that after an initial wave in metropolitan areas, TPs tend to establish themselves more widely. This pattern aligns with the observations of Burret (2021), Kunze et al. (2021), and Méndez-Ortega, Smit & Micek (2024), who noted similar trends in the diffusion of coworking spaces. This diffusion is likely driven by the increasing need for flexible workspace solutions across different types of municipalities, regardless of their population size, and reflects a broader trend towards decentralization of TPs.

## 5. Conclusion

The study presented in this article explored the diffusion dynamics of TPs in France by examining the hypothesis of hierarchical spatial diffusion. Our results demonstrate that TPs are not confined to large urban agglomerations but also spread to less populated municipalities, clearly reflecting downward hierarchical diffusion dynamics. This is the main contribution of our analysis, which also highlights how the COVID-19 crisis has disrupted this diffusion from large metropolises to small municipalities and even rural areas. Another significant contribution is that we have demonstrated that the probability of a TP appearing in a large city is zero for post-2020 periods. Therefore, we observe a more diffuse phenomenon that no longer adheres to the initial metropolitan logic.

The level of education, activity in the tertiary sector, entrepreneurial dynamism, and the unemployment rate are explanatory variables significantly influencing the probability of establishing TPs. We know that TPs are key spaces for collaboration, innovation, and networking, characteristics more typically associated with metropolises due to their
higher relational density. Nevertheless, since 2020, statistically, as many TPs are being created in smaller urban units, which now also appear attractive, especially to newcomers leaving metropolises in search of a Lifestyle of Health and Sustainability (LOHAS) (Choi & Feinberg, 2021). As some authors have already revealed (Méndez-Ortega, Smit & Micek, 2024), other factors can also be mentioned, such as remote work facilitated by the recent deployment of high-speed internet in sparsely urbanized areas in France.

Unexpectedly, we show that the characteristics of the labor market stimulate the emergence of TPs. The presence of high unemployment in a municipality is linked to a greater likelihood of establishing TPs, often driven by "necessity entrepreneurship," where individuals pursue self-employment due to limited job opportunities. TPs provide vital spaces for collaboration, networking, and small-scale business development, helping entrepreneurs overcome isolation and build social and professional networks. They also act as strategic tools for local governments aiming to revitalize economies, fostering innovation, human capital investment, and resilience in regions with economic challenges. This dual role—supporting individual entrepreneurship and promoting economic revitalization—highlights TPs' unique value in high unemployment contexts.

Furthermore, the chosen spatial scale constitutes both a strength and a limitation of our analyses. Unlike other studies that consider the regional level, we have utilized data at the local scale, providing more precise results. However, some variables, such as GDP, could not be included due to their lack of relevance at the municipal level.

Considering these observations, several recommendations can be made for territorial planning policies. First, considering the link with business creation and unemployment, local and regional authorities have an interest in actively supporting TPs in areas facing social and economic decline to promote innovation and business development. As the literature has shown, it is crucial to keep in mind that TPs are not just work and socialization spaces; they are also idea incubators, change catalysts, and drivers of local development. Furthermore, supporting their development in small and medium-sized cities and rural areas would enhance territorial social cohesion, especially as the debate on the necessary revitalization of territorial planning gains momentum in France (Sueur, 2023).

Consequently, our results support the growing interest of public authorities in TPs to promote the development of 'left behind' spaces, which are of increasing concern to many developed countries (MacKinnon et al., 2024; Demazière & Sykes, 2021; Nadou et al., 2023). In this respect, TPs appear to be promising tools. This is exemplified by the recent Austrian federal policy 'Pop-up Dorfbüros' ["village offices"], inspired by federal and regional German policies (Baudelle, Bourdin, et al., 2023; Fels, 2022; Hölzel & De Vries, 2021; Wiedemann & Klug, 2021). Applied studies carried out for the Nordic Council have confirmed the benefits of TPs for low-density areas (Ormstrup Vestergård, 2022; Guðmundsdóttir et al., 2024). More generally, they are considered as a way to boost inland regions, increase the attractiveness of remote areas for both people and companies, reduce travel needs, and improve the quality of life (Desjardins & Estève, 2019; Tomaz & Gato, 2023). Recently Portuguese public authorities have launched a new policy dedicated to third spaces (Tomaz & Gato, 2023) as well as Waltonia (Moyart & Pecqueur, 2023).

In France, spatial planning that has focused for several decades on strengthening metro areas has recently been supplemented by greater consideration of the assets of non-metro areas (Demazière, 2021). In this new context, the organization "France Tiers-Lieux" has high hopes for their contribution to the revitalization of territories far from metropolises (Levy-Waitz, 2018). Baudelle, Tremblay, et al. (2023) have shown in a comparison with Germany and Canada that this high degree of involvement is a French specificity, with the pursued objective falling within the public interest of revitalizing regions facing economic, social, and demographic challenges. The "Nouveaux lieux, nouveaux liens" ("New places, new links") program launched in 2020 by the Agence

néationale de la cohésion des territoires (ANCT), the distant successor of the now-defunct famous DATAR, aims to encourage the finest possible network of TPs in territories and support their development by involving public and private partners (Nadou et al., 2023). Already in 2019, the "Fabriques de territoire" scheme had been launched to identify TPs that are driving regional development, half of which are located in rural areas. In total, almost 180 million euros (£152 million) have been invested by the French government, and 382 TPs have been awarded the label. Similarly, the €45 million (£38 million) "Fabriques de Territoires" program, launched in 2020, is temporarily subsidizing 150 rural TPs to the tune of €50,000 (£42,000) a year to help them achieve economic balance.

Several other french development schemes reflect "the political revenge of small towns" (Edouard, 2024), as evidenced by ambitious territorial policies explicitly targeting them ("Revitalization des centers bourgs"/"Revitalization of town centers" (2014), "Action Coeur de Ville"/"City center initiative" (2018–2022) (Nadou & Kemdji, 2023), "Pétites villes de demain"/"Small towns of tomorrow" (2020) (Offner, 2021) or sectoral programs ("France très haut débit" (2012), "Territoires zéro chômeurs"/"Zero Unemployed Areas" (2016), "Société numérique"/"Digital society" (2018), "France mobile" (2018), "Incubateur des territoires" (2020)), sometimes with the help of European LEADER funds (2023–2027) (Demazière, 2022; Edouard, 2024; Fol, 2020).

Several other European countries are increasingly interested in their small and medium-sized towns and rural areas. This trend began earliest in the Nordic countries (Gløersen, 2012), but others have followed, such as Germany (Bailleul et al., 2019; BBSR, 2021), Spain –where small towns are seen as a "new key player for territorial cohesion" (Farinós Dasí & López Pagán, 2024)– and a growing number of other European countries (Demazière, 2023; Gareis et al., 2023; Redlich, 2023). That said, some researchers caution against overestimating the potential contribution of TPs alone to the revitalization of non-metropolitan areas (Baudelle, Tremblay, et al., 2023; Leducq, 2023; Moyart & Pecqueur, 2023).

In terms of future research perspectives, exploring the effects of proximity, i.e., considering the geographical distance between each TP, represents a complementary short-term avenue, especially given its frequent combination with the hierarchical model (Liefooghe et al., 2024). Further studies should also enable us to continue leveraging census data by analyzing other available variables such as TP size (floor area and capacity), legal status, offered services, etc. Additional research efforts should guide us in continuing longitudinal tracking to analyze hierarchical diffusion over time, with particular attention to controlling for the type of TP (fab labs, living labs, etc.).

### CRediT authorship contribution statement

**Clément Marinos:** Writing – review & editing, Writing – original draft, Visualization, Validation, Supervision, Software, Resources, Project administration, Methodology, Investigation, Funding acquisition, Formal analysis, Data curation, Conceptualization. **Sébastien Bourdin:** Writing – review & editing, Writing – original draft, Visualization, Validation, Supervision, Software, Resources, Project administration, Methodology, Investigation, Funding acquisition, Formal analysis, Data curation, Conceptualization. **Guy Baudelle:** Writing – review & editing, Writing – original draft, Visualization, Validation, Supervision, Software, Resources, Project administration, Methodology, Investigation, Funding acquisition, Formal analysis, Data curation, Conceptualization.

### Declaration of competing interest

The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Clement Marinos reports was provided by UBS University. If there are
other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

## Acknowledgements

The authors express their gratitude to the "France Tiers-Lieux" organization for their trust and benevolence regarding the use of data derived from their 2023 census.

## Appendix

<figure><img src="image_4.png" /><figcaption>Fig. 1. Location of third spaces in France (2021).</figcaption></figure>
## Descriptive statistics

<table><thead><tr><td>Variable</td><td>Description</td><td>Data source</td><td>Min</td><td>Max</td><td>Mean</td></tr></thead><tbody><tr><td>Pop (nb inhab.)</td><td>The population size of the municipality (number of inhabitants).</td><td>INSEE</td><td>2</td><td>2,133,111</td><td>1800</td></tr><tr><td>HigherEduc (%)</td><td>The proportion of the population with higher education degrees.</td><td>INSEE</td><td>0</td><td>84,4</td><td>43,31</td></tr><tr><td>Tertiary (%)</td><td>The percentage of the municipality's workforce employed in the tertiary sector.</td><td>INSEE</td><td>0</td><td>100</td><td>76,1</td></tr><tr><td>BusinessCreation (%)</td><td>The rate of new business creations per municipality.</td><td>INSEE</td><td>0</td><td>46,7</td><td>17,48</td></tr><tr><td>Unemploy (%)</td><td>The local unemployment rate.</td><td>INSEE</td><td>0</td><td>46,1</td><td>9,3</td></tr></tbody></table>

## Correlation matrix

<table><thead><tr><td></td><td>Pop</td><td>HigherEduc</td><td>Tertiary</td><td>BusinessCreation</td><td>Unemploy</td><td>TP</td></tr></thead><tbody><tr><td>Pop</td><td>1.00</td><td>0.45</td><td>0.50</td><td>0.35</td><td>0.22</td><td>0.25</td></tr><tr><td>HigherEduc</td><td>0.45</td><td>1.00</td><td>0.55</td><td>0.48</td><td>0.30</td><td>0.32</td></tr><tr><td>Tertiary</td><td>0.50</td><td>0.55</td><td>1.00</td><td>0.52</td><td>0.25</td><td>0.28</td></tr><tr><td>BusinessCreation</td><td>0.35</td><td>0.48</td><td>0.52</td><td>1.00</td><td>0.40</td><td>0.30</td></tr><tr><td>Unemploy</td><td>0.22</td><td>0.30</td><td>0.25</td><td>0.40</td><td>1.00</td><td>0.18</td></tr><tr><td>TP</td><td>0.25</td><td>0.32</td><td>0.28</td><td>0.30</td><td>0.18</td><td>1.00</td></tr></tbody></table>

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