# Exploring perceived changes in the frequency of private trips and local trips after telework adoption in France

Anne Aguiléra, Eléonore Pigalle, Leslie Belton Chevallier

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Anne Aguiléra, Eléonore Pigalle, Leslie Belton Chevallier. Exploring perceived changes in the frequency of private trips and local trips after telework adoption in France. Transportation Research Interdisciplinary Perspectives, 2025, 31, pp.101478. 10.1016/j.trip.2025.101478. hal-05098793

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# Exploring perceived changes in the frequency of private trips and local trips after telework adoption in France

Anne Aguiléra*, Eleonore Pigalle, Leslie Belton Chevallier

LVMT, Univ Gustave Eiffel and Ecole des Ponts IP Paris, 6-8 Avenue Blaise Pascal 77420 Champs-sur-Marne France

## ARTICLE INFO

### Keywords:

- Teleworking

- Private trips

- Trip frequency

- Local trips

- Rebound effects

- France

## ABSTRACT

This article analyses how teleworking arrangements and the characteristics of the teleworkers influence the perceived changes in the frequency of private trips and local trips (i.e. trips with a destination located close to the homeplace) after telework adoption. The data comes from an online survey in mainland France in spring 2022. The private trips considered here include firstly regular activities (errands, accompanying children, etc.), secondly weekend departures, and thirdly local trips. The results show that most teleworkers perceive no change before and after teleworking adoption. However, teleworking is more often associated with a reduction in errands trips than their increase. The extent of the decrease vary depending on the place of residence. On the other hand, the perceived frequency of other personal and family activities is mainly on the rise. Our results also show the influence of teleworking frequency and commuting duration on these trends. Finally, we find a positive relationship between teleworking and the frequency of local trips. In particular, the presence of amenities around the place of residence encourages an increase in local travel. These results show the diversity and complexity of the rebound effects of teleworking on private trips, and the need to support its current development with appropriate transport and land-use policies.

## 1. Introduction

By reducing the frequency of commuting and increasing the time spent at home, the adoption of teleworking is contributing to transform the activity-travel patterns of workers in ways that are still being debated (Giménez-Nadal et al., 2019; Kiko et al., 2024; Pabilonia and Vernon, 2022; Pigalle, 2024; Restrepo and Zeballos, 2020). In particular, telework would be associated with an increase in the frequency of trips for private activities (shopping, accompanying children or someone else, and other non-work activities), which would offset or even cancel out the reduction in commuting journeys (Kim et al., 2015; Wöhner, 2022). Changes would also concern the geography of private trips: if several studies show that more trips are made closer to the place of residence, others come to the opposite conclusion (Asgari et al., 2016; Cerqueira et al., 2020; Elldér, 2022; Hook et al., 2020; Hostettler Macias et al., 2022; Huang et al., 2023). In recent years, these so-called rebound effects of telework adoption have played an increasingly important role in academic debates on the ability of telework to favour more

sustainable mobility practices (Cerqueira et al., 2020; Halefom et al., 2024; Kiko et al., 2024; Wöhner, 2023; Zhu et al., 2018).

Following on from these ideas, this article investigates the relationship between teleworking adoption and the frequency of private trips and local trips (i.e. trips which destination is located close to the place of residence) in France. In this country, teleworking can be formalized individually by an agreement between the employer and the employee, or collectively by an agreement within the establishment or company, or even via a charter defining its terms for all the employees of the structure. Regular teleworking concerned about 4 % of the workforce before the pandemic, compared with 22 % now. Data come from a questionnaire distributed online in the spring of 2022¹ and aimed at gathering the perception of teleworkers on the changes that have occurred in the frequency of their private trips and local trips since they started teleworking, whether it was before or after the start of the pandemic. Compared to most existing literature on the topic, we use post-pandemic data (Halefom, 2024). In addition, we do not compare the travel patterns of teleworkers with non-teleworkers, or the travel patterns of

<footnote>* Corresponding author.</footnote>

<footnote>E-mail addresses: anne.aguilera@univ-eiffel.fr (A. Aguiléra), eleonore.pigalle@univ-eiffel.fr (E. Pigalle), leslie.belton-chevallier@univ-eiffel.fr (L.B. Chevallier).</footnote>

<footnote n="1">¹ At that time, the practice of teleworking had risen sharply compared with 2019 (from 3% in 2019 to around 20%), but was no longer compulsory or strongly recommended by the government. We can therefore consider that the practice of teleworking was beginning to enjoy a certain stability in the country, which is confirmed by 2023 data.</footnote>
teleworkers between teleworking and non-teleworking days. We rather explore their perception of the changes in the frequency of their private and local trips after telework adoption.

In line with existing literature, we have two main assumptions. Firstly, we assume that the teleworkers' perception of changes in the frequency of private and local trips will vary depending on their characteristics (such as gender, residential location, etc.) and teleworking arrangements (such as seniority and weekly frequency). Secondly, we assume that the changes will vary according to the activity under consideration. Private activities include, on the one hand, everyday activities (errands, accompanying children, etc.), and, on the other hand, weekend departures, which have been little considered up to now in the literature on the effects of teleworking on private trips frequency. Yet teleworking could make weekend departures easier to organise (for example, by allowing people to leave outside rush hours or by reducing the prices of airplane tickets), and also more desirable for people who spend a lot of time at their place of residence during the week.

The article is organised into six parts. The first part summarises the literature on telework and its effects on private or local trips. The second part presents the data and methodology. The results are then presented in the three following sections, looking successively at the frequency of private trips, local trips, and the relationships between changes in private trips and local trips. The final section summarises the main findings of this work, as well as its limitations. It also suggests ways in which these important issues can be pursued by those responsible for transport and land-use in a context of unprecedented growth in teleworking.

## 2. Literature review

In line with long-standing questions about the nature of the links (substitution, induction, complementarity or neutrality) between information and communication technologies and mobility patterns (Mokhtarian, 2002), it is now widely accepted that, while teleworking reduces commuting frequency, it is accompanied by complex changes in the frequency of private trips (Cerqueira et al., 2020; Hook et al., 2020; Kim, 2017; Wang and Ozbilen, 2020; Wöhner, 2022; Zhu, 2012). Even if the results are mixed, most of these studies show that teleworking is associated with more private trips. In addition, some studies suggest that the relationship between teleworking and private trips frequency depends on the profile of teleworkers, teleworking arrangements such as weekly frequency, and the purposes of the private trips considered (Halefom, 2024). Finally, the relationship between teleworking and local trips have been less analysed, but some studies underline that teleworking days are conducive to local trips.

### 2.1. Private trips frequency

Teleworking offers new opportunities to carry out activities that were previously either unthinkable (due to lack of time, scheduling problems, etc.), or grouped together, or were carried out at other times of the week, especially during the weekend. Most studies conclude that teleworking is associated with more private trips compared to non-teleworking: the home-work journeys avoided are somehow replaced by trips for private activities, just as numerous, if not more (Halefom et al., 2024). In detail, private trip frequency vary from day to day, with teleworkers making fewer trips on telework days than on days when they go to their main workplace (Elliédér, 2020).

This literature also highlights differences between the private activities considered, and also between teleworkers depending on individual and family characteristics and teleworking arrangements. Differences in trip frequency between teleworkers and non-teleworkers are important for accompaniment (of children or other people) and leisure activities, limited for personal affairs and non-existent for purchases (food and non-food) (Budnitz et al., 2020). On the basis of survey carried out in Norway in 2021, W. Ma et al. (2023) also noted that the planned changes for shopping trips after the pandemic were very

moderate. However, their analysis does not differentiate teleworkers from non-teleworkers. J. Liang (2024) confirms that the majority of Japanese teleworkers are unlikely to alter their shopping frequency post-pandemic, while there are more numerous to expect an increase in the frequency of sports and leisure activities.

With regard to individual and family characteristics, female teleworkers have a greater propensity to increase their private trips for domestic purposes than male teleworkers, in line with the gendered division of household tasks (Halefom et al., 2024; Khaddar et al., 2023; Viana Cerqueira and Motte-Baumvol, 2022). Teleworkers with children make more escorting trips than teleworkers living in households without children, while the latter make more leisure trips (Viana Cerqueira and Motte-Baumvol, 2022). The number of private journeys made by teleworkers is also positively related to the frequency of teleworking (Caldarola and Sorrell, 2022) and to teleworking full days rather than half days (Asgari et al., 2016). Finally, private activities are encouraged by a greater accessibility to nearby destinations (Khaddar et al., 2023).

Long-distance private mobility (e.g. going away for the weekend) is rarely considered in this literature, even though it could also become more frequent with the spread of teleworking, which allows people to work from a holiday location (Hostettler Macias et al., 2022). On this subject, H. Budnitz et al. (2020) note that English teleworkers make more holiday trips than non-teleworkers. In Norway, W. Ma et al. (2023) show similar proportions of people who plan to travel more and those who plan to travel as much for weekend-trip abroad after the pandemic (compared to pre-pandemic times). A minority of respondents expect to travel less. However, their analysis focuses only on weekend-trip abroad, and, as we already said before, does not differentiate teleworkers from non-teleworkers.

### 2.2. Local trips frequency

The literature on the influence of telework adoption on local trips, and more broadly on the geography of trips, is scarce. Existing studies primarily focus on the distances covered (weekly or daily) by teleworkers more that on the destinations reached and their distance to the homeplace. In their majority, this literature shows longer weekly distances for teleworkers compared to non-teleworkers (Halefom, 2024). B. Caldarola and S. Sorrell (2022) also highlight that medium-frequency (once or twice a week) teleworkers travel longer distances than high-frequency (3 or more times a week) teleworkers. It is worth noting that longer distances are not incompatible with more trips around the place of residence, but this aspect has been rarely explored.

Some studies compare teleworking with non-teleworking days, with mixed results: some highlight that teleworkers make shorter trips on teleworking days compared to on-site days (Elliédér, 2020), but more authors come to the opposite conclusion (Halefom, 2024). Residential contexts, and in particular conditions of accessibility to the various amenities, seem to be key aspects (Kim and Shimizu, 2022; Halefom, 2024; Hook et al., 2024; Victoriano-Habit and El-Geneidy, 2024). Living in a municipality or neighbourhood offering a mix of activities and services seem to encourage teleworkers, on days when they telework, to make their activities closer to their place of residence compared to on-site working days, contrary to low-density municipalities or neighbourhoods (Chakrabarti, 2018; Caulfield and Charly, 2022; Elliédér, 2020; Lara-Pulido and Martinez-Cruz, 2023; Vaddadi et al., 2022).

## 3. Data and method

### 3.1. Data

The latest national household travel survey was carried out in 2019 in France, one year before the start of the pandemic, when only 3 % of French employees teleworked regularly or occasionally. In the absence of more recent data on mobility behaviour and of longitudinal data which would allow to measure the impact of teleworking adoption on
changes in travel patterns at the level of individuals, the data used in this article comes from an online questionnaire survey about travel behaviour of employees. One part of the questionnaire focused on teleworkers, and especially on the perceived changes in trip frequency after teleworking adoption.

The survey was carried out in spring 2022 in mainland France, two years after the beginning of the pandemic and when teleworking was no longer compulsory. At this period of time, about one fifth of French workers teleworked at least once a week according to the Insee, the National Institute of Statistics and Economic Studies (Pénicaud, 2023). Our survey was first tested on a panel, then distributed widely via professional and personal networks, mailing lists of associations, political parties, companies and newspapers, with suggestions that they in turn share the online survey with their own personal and professional networks. The questionnaire was aimed solely at employees.

The data collected concerned: (1) the respondent's characteristics such as age, level of education, gender, household size, number of cars owned, household income, municipality of residence, etc, (2) the respondent's professional activity (professional status, main place of work, etc.), and, when relevant, (3) the respondent's practice of teleworking (frequency, length of time, practice by days or half-days, days in the week, etc.). Another series of questions aimed to measure the respondent's perception of the changes on the frequency and geography (in terms of proximity to the homeplace) of his or her private trips (by purpose) since teleworking adoption. The answers to these questions are analysed in this article.

In detail, eight categories of private trips are distinguished. Three of these relate to errands, according to the following typology of commercial formats: purchases in supermarkets, in local shops (e.g. grocery shops, butchers, greengrocers, etc.), and in fresh markets. Leisure, cultural and community activities, escorting children to school and extracurricular activities, personal appointments (hairdresser, doctor, etc.) and visiting family and friends are the four other trip purposes. For each of these seven activities, the respondent had to answer the following question: "Since you started teleworking, would you say that the frequency with which you travel for [reason for travel] ..." by choosing one the five following answers: it has decreased a lot, it has decreased, it is unchanged, it has increased or it has increased a lot. Finally, weekend departures formed an eighth category of private trips purposes. The question asked was: "Since I have been teleworking, I have been going away at the weekend ..." with five response options given in ascending order of change in frequency: much less often, less often, as often, more often, much more often. The effect of teleworking on the intensity of local trips, i.e. trips in the area close to the place of residence, was assessed by answering the following question: "Since I have been teleworking, have I travelled around my home (to do an errand, go to an appointment, etc.)?", again with 5 response options in ascending order of change in frequency: much less often, less often, just as often, more often, much more often. Since people were only asked about changes in trip frequency (and not about the mode they use or if their trips are more ecological), we believe that there was few risk of social desirability bias. There may be a gap between their perception and the way they effectively change their trips, as pointed by other studies. Nonetheless, the analyses of their perception of change remain useful to understand how teleworking contributes to change their travel patterns.

1,412 people (teleworkers and non-teleworkers) responded to the questionnaire. The analyses presented below concern only full-time employees who telework from home. People who had always teleworked were excluded. The final sample is made up of 815 people, 80 % of whom say they telework on a regular basis, i.e. at least one day a week, and nearly three-quarters 1 or 2 days a week (Table 1). The representativeness of this sample is challenging to fully assess due to the lack of detailed statistics on the profile of teleworkers (and among them, of employees) in France after the pandemic. However, our sample reflects broader trends among French teleworkers to some extent. 83 % of our respondents telework 1–2 days per week, closely mirroring the 71 %

<table><caption>**Table 1**

Description of variables used in the models (n = 815).</caption><thead><tr><th>Variable</th><th>Description</th><th>Min.</th><th>Max.</th><th>Mean (Proportion)</th><th>SD</th></tr></thead><tbody><tr><td><strong>Characteristics of telework</strong></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Frequency</td><td>Nb of day(s) a week<br>. Less than 1 = 0.5<br>. 1<br>. 2<br>. 3<br>. 4<br>. 5</td><td></td><td></td><td>150<br>(18.4%)217<br>(26.6%)341<br>(41.8%)75<br>(9.2%)9<br>(1.1%)23<br>(2.8%)</td><td></td></tr><tr><td>Flextime</td><td>Composite score from 3 questions</td><td>0</td><td>100</td><td>74.84</td><td>21.79</td></tr><tr><td>Seniority</td><td>. Less than 2 years<br>. Between 2 and 5 years<br>. More than 5 years</td><td></td><td></td><td>510 (62.6 %)<br>248 (30.4%)57<br>(7 %)</td><td></td></tr><tr><td>Weekly organisation</td><td>. Half day only<br>. Full day only<br>. Mixed<br>. Variable</td><td></td><td></td><td>49 (6%)600<br>(73.6%)30<br>(3.7%)136<br>(16.7 %)</td><td></td></tr><tr><td><strong>Socio-demographic characteristics</strong></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Gender</td><td>. Male = 0<br>. Female = 1</td><td></td><td></td><td>372 (45.6 %)<br>443 (54.3 %)</td><td></td></tr><tr><td>Education</td><td>In years (compared to the Baccalaureate)<br>. No diploma = -7<br>. Junior school certificate = -3<br>. CAP, BEP, vocational diploma = -2<br>. Baccalaureate = 0<br>. Bac + 2 = 2<br>. Bac + 3 or Bac + 4 = 3<br>. Bac + 5 = 5<br>. Bac + 8 = 8</td><td></td><td></td><td>2<br>(0.2%)1<br>(0.1%)7<br>(0.9%)36<br>(4.4%)75<br>(9.2%)124<br>(15.2%)435<br>(53.4%)135<br>(16.6 %)</td><td></td></tr><tr><td>Car access</td><td>Number of cars in the household and/or if the car is used to get to work<br>. No = 0<br>. Yes = 1</td><td></td><td></td><td>175<br>(21.5%)640<br>(78.5 %)</td><td></td></tr><tr><td>Lifecourse</td><td>. 22–45 years old, without children or dependent children = > 45<br>. Parents with children under 10 = Parents 0–10<br>. Parents with children between 11 and 18 = Parents 11–18<br>. 45 + with no children or dependent children = < 45</td><td></td><td></td><td>283 (34.7 %)<br>198<br>(24.3 %)<br>134<br>(16.4 %)<br>200<br>(24.5 %)</td><td></td></tr><tr><td><strong>Economic and professional characteristics</strong></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Perception of living standards</td><td>. Very difficult = -2<br>. Difficult = -1<br>. Good = 0<br>. Comfortable = 1<br>. Very comfortable = 2</td><td></td><td></td><td>8 (1%)12<br>(1.5%)179<br>(22%)440<br>(54%)176<br>(21.6 %)</td><td></td></tr><tr><td>Occupation</td><td>. Executive in the private sector</td><td></td><td></td><td>279 (34.2 %)<br>319</td><td></td></tr></tbody><tfoot><tr><td colspan="6" style="text-align: right;">(continued on next page)</td></tr></tfoot></table>
<table><caption>**Table 1 (continued)**</caption><thead><tr><th>Variable</th><th>Description</th><th>Min.</th><th>Max.</th><th>Mean (Proportion)</th><th>SD</th></tr></thead><tbody><tr><td rowspan="10">Place of residence and commuting</td><td>Executive in the public sector</td><td></td><td></td><td>(39.1)%24</td><td></td></tr><tr><td>Company manager</td><td></td><td></td><td>(2.9)%44</td><td></td></tr><tr><td>Employee in the private sector</td><td></td><td></td><td>(5.4)%25</td><td></td></tr><tr><td>Employee in the public sector</td><td></td><td></td><td>(3.1)%44</td><td></td></tr><tr><td>Technician in the private sector</td><td></td><td></td><td>(5.4)%80</td><td></td></tr><tr><td>Technician in the public sector</td><td></td><td></td><td>(9.8)%</td><td></td></tr><tr><td>Centre</td><td></td><td></td><td></td><td>311 (38.1%)</td><td></td></tr><tr><td>Suburbs</td><td></td><td></td><td></td><td>291</td><td></td></tr><tr><td>Periphery</td><td></td><td></td><td></td><td>(35.7)%213 (26.1)%</td><td></td></tr><tr><td rowspan="3">Commuting time</td><td>&lt; 30 min</td><td></td><td></td><td></td><td>331 (40.6)%</td><td></td></tr><tr><td>31-59 min</td><td></td><td></td><td></td><td>326</td><td></td></tr><tr><td>&gt; 60 min</td><td></td><td></td><td></td><td>(40)%158 (19.4)%</td><td></td></tr><tr><td colspan="6">Changes in frequency of non-work trips (Dependent variables)</td></tr><tr><td rowspan="5">Supermarkets</td><td>Decreased a lot = -2</td><td></td><td></td><td></td><td>139 (17%)</td><td></td></tr><tr><td>Decreased = -1</td><td></td><td></td><td></td><td>78 (9.6%)</td><td></td></tr><tr><td>Unchanged = 0</td><td></td><td></td><td></td><td>541 (66.4%)</td><td></td></tr><tr><td>Increased = 1</td><td></td><td></td><td></td><td>52 (6.4%)</td><td></td></tr><tr><td>Increased a lot = 2</td><td></td><td></td><td></td><td>5 (0.6%)</td><td></td></tr><tr><td rowspan="5">Local shops</td><td>Decreased a lot = -2</td><td></td><td></td><td></td><td>266 (32.6)%</td><td></td></tr><tr><td>Decreased = -1</td><td></td><td></td><td></td><td>8 (1%)</td><td></td></tr><tr><td>Unchanged = 0</td><td></td><td></td><td></td><td>394 (48.3%)</td><td></td></tr><tr><td>Increased = 1</td><td></td><td></td><td></td><td>133 (16.3%)</td><td></td></tr><tr><td>Increased a lot = 2</td><td></td><td></td><td></td><td>14 (1.8%)</td><td></td></tr><tr><td rowspan="5">Fresh markets</td><td>Decreased a lot = -2</td><td></td><td></td><td></td><td>222 (27.3)%</td><td></td></tr><tr><td>Decreased = -1</td><td></td><td></td><td></td><td>4 (0.5%)</td><td></td></tr><tr><td>Unchanged = 0</td><td></td><td></td><td></td><td>522 (64%)</td><td></td></tr><tr><td>Increased = 1</td><td></td><td></td><td></td><td>56 (6.9%)</td><td></td></tr><tr><td>Increased a lot = 2</td><td></td><td></td><td></td><td>11 (1.3%)</td><td></td></tr><tr><td rowspan="5">Leisure</td><td>Decreased a lot = -2</td><td></td><td></td><td></td><td>17 (2.1%)</td><td></td></tr><tr><td>Decreased = -1</td><td></td><td></td><td></td><td>59 (7.2%)</td><td></td></tr><tr><td>Unchanged = 0</td><td></td><td></td><td></td><td>556 (68.2%)</td><td></td></tr><tr><td>Increased = 1</td><td></td><td></td><td></td><td>167 (20.5%)</td><td></td></tr><tr><td>Increased a lot = 2</td><td></td><td></td><td></td><td>16 (2%)</td><td></td></tr><tr><td rowspan="5">Personal appointments</td><td>Decreased a lot = -2</td><td></td><td></td><td></td><td>6 (0.7%)</td><td></td></tr><tr><td>Decreased = -1</td><td></td><td></td><td></td><td>24 (2.9%)</td><td></td></tr><tr><td>Unchanged = 0</td><td></td><td></td><td></td><td>629 (77.2%)</td><td></td></tr><tr><td>Increased = 1</td><td></td><td></td><td></td><td>148 (18.2%)</td><td></td></tr><tr><td>Increased a lot = 2</td><td></td><td></td><td></td><td>8 (1%)</td><td></td></tr><tr><td rowspan="5">Escorting children (n = 370)</td><td>Decreased a lot = -2</td><td></td><td></td><td></td><td>16 (4.3%)</td><td></td></tr><tr><td>Decreased = -1</td><td></td><td></td><td></td><td>4 (1.1%)</td><td></td></tr><tr><td>Unchanged = 0</td><td></td><td></td><td></td><td>261 (70.5%)</td><td></td></tr><tr><td>Increased = 1</td><td></td><td></td><td></td><td>64 (17.3%)</td><td></td></tr><tr><td>Increased a lot = 2</td><td></td><td></td><td></td><td>25 (6.8%)</td><td></td></tr><tr><td rowspan="5">Friends and family</td><td>Decreased a lot = -2</td><td></td><td></td><td></td><td>10 (1.2%)</td><td></td></tr><tr><td>Decreased = -1</td><td></td><td></td><td></td><td>45 (5.5%)</td><td></td></tr><tr><td>Unchanged = 0</td><td></td><td></td><td></td><td>690 (84.7%)</td><td></td></tr><tr><td>Increased = 1</td><td></td><td></td><td></td><td>62 (7.6%)</td><td></td></tr><tr><td>Increased a lot = 2</td><td></td><td></td><td></td><td>8 (1%)</td><td></td></tr><tr><td rowspan="5">Local trips</td><td>Much less often = -2</td><td></td><td></td><td></td><td>13 (1.6%)</td><td></td></tr><tr><td>Less often = -1</td><td></td><td></td><td></td><td>12 (1.4%)</td><td></td></tr><tr><td>As often = 0</td><td></td><td></td><td></td><td>325 (39.9%)</td><td></td></tr><tr><td>More often = 1</td><td></td><td></td><td></td><td>378 (46.4%)</td><td></td></tr><tr><td>Much more often = 2</td><td></td><td></td><td></td><td>87 (10.7%)</td><td></td></tr><tr><td rowspan="3">Weekend departures</td><td>Much less often = -2</td><td></td><td></td><td></td><td>27 (3.3%)</td><td></td></tr><tr><td>Less often = -1</td><td></td><td></td><td></td><td>22 (2.7%)</td><td></td></tr><tr><td></td><td></td><td></td><td></td><td>683 (83.8%)</td><td></td></tr></tbody></table>

<table><caption>**Table 1 (continued)**</caption><thead><tr><th>Variable</th><th>Description</th><th>Min.</th><th>Max.</th><th>Mean (Proportion)</th><th>SD</th></tr></thead><tbody><tr><td rowspan="3"></td><td>As often = 0</td><td></td><td></td><td></td><td>64 (7.9%)</td><td></td></tr><tr><td>More often = 1</td><td></td><td></td><td></td><td>19 (2.3%)</td><td></td></tr><tr><td>Much more often = 2</td><td></td><td></td><td></td><td></td><td></td></tr></tbody></table>

Note: Obs. = number of observations, min = minimum, max = maximum, SD = standard deviation. *These categorical variables have been converted to numeric.

of French teleworkers who do the same (Pénicaud, 2023). In addition, 63 % of French teleworkers were executives in 2022 according to the data provided by Insee, which seems to be consistent with our sample where 70 % of respondents have a Baccalaureat + 5 years level. Our sample also shows evidence of a selection bias, with a higher proportion of public servants: 40 % in our sample compared to 32 % among French teleworkers in 2021 (Jauneau, 2021).

## 3.2. Method

The statistical processing of the data was based on R software. To analyse the effects of adopting telework on the perception of changes in the frequency of private trips and the use of the local area, linear regressions were carried out for each of the responses to the questions described above. The variable to be explained concerned the answer to the corresponding question, the modalities of which were numerically coded as follows: -2 (much reduced) / -1 (reduced) / 0 (unchanged) / +1 (increased) / +2 (much increased). Those who indicated that they did not travel to the proposed activities, before and after adopting telework, were considered as “unchanged”. Those who indicated that they had started since adopting telework were considered as “+2 much increased”. Conversely, those who indicated that they had stopped since teleworking were considered to be “-2 much reduced”.

The explanatory variables tested concerned the respondent's characteristics, teleworking arrangements, residential location and average commuting time (Table 1). Residential location was defined in three categories, according to the position of the respondent's municipality of residence within French urban areas, which is closely linked with its density and accessibility to local shops and supermarkets: the central municipality (centre), suburban municipalities (suburbs) and peripheral municipalities (periphery). Average commuting time (declared by the respondent) is classified in 3 categories: less than 30 min, between 31 and 59 min, more than 60 min. The socio-demographic variables include: gender, education, access to a car and position in the life cycle. Access to a car is a binary variable coded 1 if the respondent declared that he/she drives to work or if there are at least as many cars as adults in the household, and 0 otherwise. Position in the life cycle crosses the respondent's age and the number of children in the household. Economic and professional characteristics relate to the respondent's professional status and how he/she perceives his/her standard of living (from very difficult to very comfortable). Teleworking arrangements are described in terms of frequency, seniority, weekly organization (half-day and/or full-day each week, or systematically variable from week to week), and flexibility. Flexibility is measured by a score ranging from 0 (no flexibility) to 3 (maximum flexibility) converted into a percentage (flexibility rate). It is derived from the sum of the answers to the following three questions:

(1) “Who set the teleworking days? 0 (employer) / 1 (employee) / 0.5 (both)

(2) “On teleworking days, what type of time control are you subject to?” 0 (Yes: Clock, badge, time clock (on-line or off-line) or control by management) / 1 (No: No type of control)
(3) "On teleworking days, can you adapt your working hours whenever you want?" 0 (No) / 0.33 (Rather no) / 0.66 (Rather yes) / 1 (yes)

For each model, we have reported the main effects (aimed at deter-
mining whether a linear link exists between a modality and the change
in frequency of an activity) as well as the results of equivalence tests
(aimed at determining whether a sub-group is significantly different
from "0", meaning that it has changed its practices). Marginal means
were also reported. Finally, in order to understand the inter-
relationships and possible offsetting effects between changes in travel
frequency for each of the purposes considered, correlations were carried
out on the basis of the residuals extracted from the regression models (i.
e. correcting the values for all the effects incorporated in the models).
The p-values were corrected using the Bonferroni method, with a sig-
nificance threshold set at p < 0.05. Fig. 1 illustrates how the results of
the models should be interpreted.

This figure helps to clarify the understanding of Tables 2 and 3 with
two cases. The first (Fig. 1a) shows the existence of a linear relationship:
when the frequency of teleworking increases, so does changes in trip
frequency [p = 0.04]. It also shows that there are differences between
observations, indicated by the stars on the graph (and in the tables): the
result is not significant for occasional teleworkers (less than one day a
week), but significant for workers teleworking more than 2.5 days a
week. The second (Fig. 1b) shows no general effect: the frequency of
teleworking has no effect on how teleworkers appreciate changes in
travel frequency [p = 0.72]. On the other hand, it shows that tele-
workers feel that they have reduced their travel, regardless of their
telework frequency.

4. Changes in the frequency of private activities and local trips

Table 1 indicates that most respondents consider that they did not
change the frequency of private trips since they started teleworking.
However, in line with our assumption, there are differences in the in-
tensity and nature (increase or decrease in travel frequency) of
perceived changes depending on the activity considered. Among the
ones who associate telework adoption and changes in errands trips,
more people perceive a decrease than an increase. It is exactly the
opposite for leisure, personal appointments, escorting children and

above all trips around the homeplace (local trips). Finally, our data show
no clear trend for weekend departures and visit to friends and family.
The models allow us to explore in greater details the influence of
different variables on the changes perceived by teleworkers.

4.1. Errands

The results of the models are presented for each of the three com-
mercial formats in Table 2. Regardless of the format considered, the
teleworkers surveyed more often believe that they have reduced the
frequency of their errand trips since they started teleworking, regardless
of their telework arrangements (frequency, flexibility, etc.), their
gender, their access to a car, their commuting time, their position in the
life cycle, their occupational category or their perception of their living
conditions. This decrease could be linked to the increasing use of online
shopping (Javadinasr et al., 2022; Motte-Baumvol and Schwanen, 2024;
Shah et al., 2024), to reorganisations of family tasks within households
or to larger societal changes, but our survey does not allow us to
document these points. Another result, which is just as difficult to
interpret in the absence of more qualitative data, is that the less
educated people are, the more they feel they have reduced their travel to
fresh markets since teleworking.

Lastly, residents of central municipalities reported a greater reduc-
tion in trips to supermarkets, while those living in the suburbs or pe-
ripHERies tended to reduce their trips to local shops. These results suggest
that the reorganisation of regular shopping practices following the
adoption of teleworking depends on the commercial amenities acces-
sible from the place of residence and also perhaps on the commercial
amenities available on the home-to-work trip.

4.2. Personal and family activities

As explained before, the questionnaire distinguishes five categories
of personal or family activities: leisure activities, visits to family and
friends and weekend trips (the last two categories may overlap in part),
personal appointments (doctor, hairdresser, etc.), and escorting children
(to school and extra-curricular activities).

In contrast to errands, an in line with the literature, teleworkers more
often associate the adoption of teleworking with an increase in travel for
leisure, personal appointments and escorting children, while they

<figure><img src="image_2.png" /><figcaption>Fig. 1. Illustrations for interpreting the results.</figcaption></figure>
<table><caption>**Table 2**
Explanatory factors for perceived changes in frequency of non-work trips by activity following adoption of telework.</caption><thead><tr><th></th><th>Supermarkets</th><th>Local shops</th><th>Fresh markets</th><th>Leisure</th><th>Non-business appointments</th><th>Escorting children</th><th>Friends and family</th></tr></thead><tbody><tr><td colspan="8"><strong>Characteristics of telework</strong></td></tr><tr><td>Frequency</td><td>F(1,790) = 0.13, p = 0.722</td><td>F(1,790) = 1.08, p = 0.299</td><td>F(1,790) = 0.99, p = 0.320</td><td>F(1,790) = 4.09, p = 0.0430</td><td>F(1,790) = 0.23, p = 0.633</td><td>F(1,288) = 0.04, p = 0.846</td><td>F(1,790) = 5.57, p = 0.019</td></tr><tr><td>0.5</td><td>-0.293**</td><td>-0.461***</td><td>-0.539***</td><td>0.0905</td><td>0.098</td><td>0.245</td><td>0.010</td></tr><tr><td>1 to 2.5</td><td>-0.317***</td><td>-0.370**</td><td>-0.462***</td><td>0.1904**</td><td>0.117*</td><td>0.261*</td><td>-0.074</td></tr><tr><td>3 to 5</td><td>-0.346*</td><td>-0.255</td><td>-0.365*</td><td>0.3152**</td><td>0.140</td><td>0.282</td><td>-0.179*</td></tr><tr><td>Flextime</td><td>F(1,790) = 0.00, p = 0.991</td><td>F(1,790) = 0.04, p = 0.834</td><td>F(1,790) = 0.01, p = 0.910</td><td>F(1,790) = 0.14, p = 0.708</td><td>F(1,790) = 1.80, p = 0.180</td><td>F(1,288) = 1.83, p = 0.177</td><td>F(1,790) = 0.08, p = 0.776</td></tr><tr><td>0%</td><td>-0.306*</td><td>-0.439*</td><td>-0.480**</td><td>0.179</td><td>0.195*</td><td>0.481*</td><td>-0.055</td></tr><tr><td>50%</td><td>-0.307***</td><td>-0.418***</td><td>-0.490***</td><td>0.158*</td><td>0.138**</td><td>0.333*</td><td>-0.044</td></tr><tr><td>100%</td><td>-0.307***</td><td>-0.398***</td><td>-0.499***</td><td>0.138*</td><td>0.080</td><td>0.184</td><td>-0.033</td></tr><tr><td>Seniority</td><td>F(2,790) = 0.95, p = 0.386</td><td>F(2,790) = 0.06, p = 0.938</td><td>F(2,790) = 0.07, p = 0.929</td><td>F(2,790) = 0.04, p = 0.962</td><td>F(2,790) = 0.14, p = 0.869</td><td>F(2,288) = 0.15, p = 0.860</td><td>F(2,790) = 0.05, p = 0.949</td></tr><tr><td>Less than 2 years</td><td>-0.247**</td><td>-0.392***</td><td>-0.480***</td><td>0.149*</td><td>0.103*</td><td>0.291*</td><td>-0.030</td></tr><tr><td>Between 2 and 5 years</td><td>-0.256**</td><td>-0.426***</td><td>-0.512***</td><td>0.160*</td><td>0.124*</td><td>0.248</td><td>-0.039</td></tr><tr><td>More than 5 years</td><td>-0.418**</td><td>-0.407*</td><td>-0.491**</td><td>0.136</td><td>0.101</td><td>0.225</td><td>-0.047</td></tr><tr><td>Weekly organisation</td><td>F(3,790) = 1.56, p = 0.199</td><td>F(3,790) = 2.47, p = 0.061</td><td>F(3,790) = 0.27, p = 0.850</td><td>F(3,790) = 0.22, p = 0.884</td><td>F(3,790) = 0.46, p = 0.71</td><td>F(3,288) = 0.63, p = 0.597</td><td>F(3,790) = 0.05, p = 0.983</td></tr><tr><td>Half day</td><td>-0.186</td><td>-0.596**</td><td>-0.575***</td><td>0.178</td><td>0.104</td><td>0.406*</td><td>-0.053</td></tr><tr><td>Mixed</td><td>-0.227</td><td>-0.147</td><td>-0.510*</td><td>0.176</td><td>0.065</td><td>0.230</td><td>-0.021</td></tr><tr><td>Variable</td><td>-0.467***</td><td>-0.326*</td><td>-0.446***</td><td>0.125</td><td>0.117*</td><td>0.187</td><td>-0.046</td></tr><tr><td>Whole day</td><td>-0.348***</td><td>-0.564***</td><td>-0.446***</td><td>0.114*</td><td>0.151***</td><td>0.196</td><td>-0.034</td></tr><tr><td colspan="8"><strong>Socio-demographic characteristics</strong></td></tr><tr><td>Gender</td><td>F(1,790) = 3.66, p = 0.056</td><td>F(1,790) = 0.65, p = 0.422</td><td>F(1,790) = 0.02, p = 0.891</td><td>F(1,790) = 0.64, p = 0.422</td><td>F(1,790) = 5.72, p = 0.017</td><td>F(1,288) = 1.17, p = 0.280</td><td>F(1,790) = 2.62, p = 0.106</td></tr><tr><td>Male</td><td>-0.246**</td><td>-0.374**</td><td>-0.489***</td><td>0.129*</td><td>0.064</td><td>0.304*</td><td>-0.066</td></tr><tr><td>Female</td><td>-0.368***</td><td>-0.443***</td><td>-0.500***</td><td>0.167**</td><td>0.154**</td><td>0.206</td><td>-0.011</td></tr><tr><td>Education</td><td>F(1,790) = 0.40, p = 0.525</td><td>F(1,790) = 0.99, p = 0.321</td><td>F(1,790) = 4.54, p = 0.033</td><td>F(1,790) = 5.38, p = 0.021</td><td>F(1,790) = 0.13, p = 0.720</td><td>F(1,288) = 2.66, p = 0.104</td><td>F(1,790) = 0.62, p = 0.431</td></tr><tr><td>No diploma</td><td>-0.431*</td><td>-0.669*</td><td>-0.986***</td><td>0.488**</td><td>0.150</td><td>0.704*</td><td>0.044</td></tr><tr><td>Baccalaureat</td><td>-0.356***</td><td>-0.511***</td><td>-0.689***</td><td>0.283***</td><td>0.125*</td><td>0.432**</td><td>-0.006</td></tr><tr><td>Bac + 8</td><td>-0.270**</td><td>-0.332*</td><td>-0.350**</td><td>0.049</td><td>0.097</td><td>0.121</td><td>-0.063</td></tr><tr><td>Car access</td><td>F(1,790) = 0.60, p = 0.437</td><td>F(1,790) = 0.02, p = 0.879</td><td>F(1,790) = 0.09, p = 0.760</td><td>F(1,790) = 1.23, p = 0.269</td><td>F(1,790) = 0.15, p = 0.699</td><td>F(1,288) = 0.20, p = 0.651</td><td>F(1,790) = 4.55, p = 0.033</td></tr><tr><td>No</td><td>-0.275**</td><td>-0.400**</td><td>-0.509***</td><td>0.114</td><td>0.099</td><td>0.22</td><td>-0.086</td></tr><tr><td>Yes</td><td>-0.339***</td><td>-0.417***</td><td>-0.479***</td><td>0.183**</td><td>0.118**</td><td>0.29**</td><td>0.009</td></tr><tr><td>Lifecourse</td><td>F(3,790) = 0.49, p = 0.685</td><td>F(3,790) = 0.72, p = 0.541</td><td>F(3,790) = 0.51, p = 0.674</td><td>F(3,790) = 6.38, p = 0.001</td><td>F(3,790) = 4.54, p = 0.004</td><td>F(1,288) = 38.63, p = 0.001</td><td>F(3,790) = 7.29, p = 0.001</td></tr><tr><td>&gt; 45 years old</td><td>-0.366***</td><td>-0.323**</td><td>-0.476***</td><td>0.053</td><td>0.022</td><td>/</td><td>-0.050</td></tr><tr><td>&lt; 45 years</td><td>-0.321***</td><td>-0.476***</td><td>-0.571***</td><td>0.314***</td><td>0.172**</td><td>/</td><td>0.090</td></tr><tr><td>Parents 0-10</td><td>-0.278**</td><td>-0.459***</td><td>-0.460***</td><td>0.144</td><td>0.183**</td><td>0.5251***</td><td>-0.057</td></tr><tr><td>Parents 11-18</td><td>-0.262*</td><td>-0.375**</td><td>-0.471***</td><td>0.081</td><td>0.060</td><td>-0.0154</td><td>-0.137*</td></tr><tr><td colspan="8"><strong>Economic and professional characteristics</strong></td></tr><tr><td>Living standards</td><td>F(1,790) = 2.32, p = 0.128</td><td>F(1,790) = 3.61, p = 0.058</td><td>F(1,790) = 0.55, p = 0.460</td><td>F(1,790) = 0.39, p = 0.534</td><td>F(1,790) = 0.41, p = 0.520</td><td>F(1,288) = 0.86, p = 0.354</td><td>F(1,790) = 7.59, p = 0.006</td></tr><tr><td>Very difficult</td><td>-0.113</td><td>-0.733***</td><td>-0.605***</td><td>0.208</td><td>0.061</td><td>0.084</td><td>0.150*</td></tr><tr><td>Well</td><td>-0.245**</td><td>-0.512***</td><td>-0.530***</td><td>0.167**</td><td>0.094</td><td>0.200</td><td>0.022</td></tr><tr><td>Very comfortable</td><td>-0.377***</td><td>-0.291*</td><td>-0.454***</td><td>0.127</td><td>0.126*</td><td>0.317*</td><td>-0.107*</td></tr><tr><td>Occupation</td><td>F(6,790) = 0.51, p = 0.794</td><td>F(6,790) = 0.29, p = 0.937</td><td>F(6,790) = 1.41, p = 0.206</td><td>F(6,790) = 0.76, p = 0.603</td><td>F(6,790) = 0.71, p = 0.644</td><td>F(6,288) = 0.89, p = 0.505</td><td>F(6,790) = 0.30, p = 0.937</td></tr><tr><td>Executive (private sector)</td><td>-0.322***</td><td>-0.322**</td><td>-0.548***</td><td>0.116</td><td>0.082</td><td>0.224</td><td>-0.024</td></tr><tr><td>Executive (public sector)</td><td>-0.342***</td><td>-0.398***</td><td>-0.473***</td><td>0.140*</td><td>0.138**</td><td>0.249*</td><td>-0.026</td></tr><tr><td>Company manager</td><td>-0.376*</td><td>-0.443</td><td>-0.732**</td><td>0.335*</td><td>-0.029</td><td>0.224</td><td>-0.064</td></tr><tr><td>Employee or worker (private sector)</td><td>-0.260</td><td>-0.401*</td><td>-0.298</td><td>0.060*</td><td>0.162</td><td>0.645*</td><td>-0.063</td></tr><tr><td>Employee or worker (public sector)</td><td>-0.304</td><td>-0.536*</td><td>-0.767***</td><td>0.021</td><td>0.180</td><td>0.283</td><td>-0.091</td></tr><tr><td>Technician or supervisor (private sector)</td><td>-0.138</td><td>-0.285</td><td>-0.266</td><td>0.175</td><td>0.114</td><td>0.119</td><td>0.040</td></tr><tr><td>Technician or supervisor (public sector)</td><td>-0.407**</td><td>-0.473**</td><td>-0.376*</td><td>0.191*</td><td>0.116</td><td>0.040</td><td>-0.042</td></tr><tr><td colspan="8"><strong>Place of residence and commuting</strong></td></tr><tr><td>Place of residence</td><td>F(2,790) = 3.43, p = 0.038</td><td>F(2,790) = 3.21, p = 0.041</td><td>F(2,790) = 1.69, p = 0.184</td><td>F(2,790) = 0.40, p = 0.669</td><td>F(2,790) = 0.24, p = 0.789</td><td>F(2,288) = 2.03, p = 0.133</td><td>F(2,790) = 0.05, p = 0.953</td></tr><tr><td>Centre</td><td>-0.413***</td><td>-0.272*</td><td>-0.457***</td><td>0.177**</td><td>0.094</td><td>0.179</td><td>-0.031</td></tr><tr><td>Suburbs</td><td>-0.223*</td><td>-0.398**</td><td>-0.429***</td><td>0.146*</td><td>0.124*</td><td>0.205</td><td>-0.043</td></tr><tr><td>Periphery</td><td>-0.285**</td><td>-0.555***</td><td>-0.597***</td><td>0.122</td><td>0.110</td><td>0.381**</td><td>-0.041</td></tr><tr><td>Commuting time</td><td>F(2,790) = 1.91, p = 0.149</td><td>F(2,790) = 0.70, p = 0.495</td><td>F(2,790) = 1.30, p = 0.274</td><td>F(2,790) = 6.98, p = 0.001</td><td>F(2,790) = 2.66, p = 0.071</td><td>F(2,288) = 2.02, p = 0.135</td><td>F(2,790) = 3.51, p = 0.030</td></tr><tr><td>&lt; 30 min</td><td>-0.374***</td><td>-0.419***</td><td>-0.520***</td><td>0.040</td><td>0.052</td><td>0.130</td><td>-0.100*</td></tr><tr><td>30-59 min</td><td>-0.236**</td><td>-0.339**</td><td>-0.564***</td><td>0.117</td><td>0.142**</td><td>0.261*</td><td>-0.039</td></tr><tr><td>&gt; 60 min</td><td>-0.311**</td><td>-0.467***</td><td>-0.399**</td><td>0.288***</td><td>0.133*</td><td>0.373*</td><td>0.024</td></tr></tbody></table>
Note: \* p < 0.05, \*\* p < 0.01, \*\*\* p < 0.001; bold: significant (differences between groups).

perceive no change for visits to family and friends and weekend trips (Tables 2 and 3). The explanatory variables vary by trip purpose, but teleworking arrangements have little influence except in terms of weekly frequency (Tables 2 and 3). Indeed, the perceived increase in leisure trips increases with the number of days teleworked per week, having a low level of education, being under 45 in a household without children, and taking more than 60 min to get to work. Leisure travel therefore increases above all when the time saved by teleworking is significant, because of the frequency of teleworking and/or the time saved on commuting, in line with the literature on the specificity of activity-travel patterns on teleworking days. Logically, leisure trips also seem to increase more for young households without children, who have fewer family constraints.

The adoption of teleworking is also associated by the respondents with a (slight) increase in travel for personal appointments. This is more common among women, the under-45 s and parents of young children (aged 0–10). Logically, the latter also report a greater increase in the frequency of their trips to and from school and for after-school activities. Overall, these results confirm that teleworking is a tool for combining people’ private and professional activities, particularly for women and parents of young children. This increase in private travel could be explained by couples (particularly those with children) shifting family tasks, although this cannot be documented using our data.

Furthermore, the more people telework, the more they indicate they have reduced the frequency of trips to visit family or friends. This reduction is more common among those who telework at least 5 days a week, parents of teenage children (aged 11–18), people who consider themselves to have a comfortable income and those who live less than 30 min from their workplace. A plausible explanation is the decline in outings with colleagues or friends after the day at work (Pigalle, 2024).

Finally, the adoption of teleworking does not seem to have had any impact on the frequency of weekend departures. However, there is an age effect in households without children: the over-45 s more often consider that they have reduced the frequency of their weekend trips, whereas the opposite is true for the under-45 s (Table 3). These results are probably linked to changes in lifestyles and the size of social networks as a function of age, that could be enhanced by teleworking (Bidart and Lavenu, 2005).

### 4.3. Local trips

The majority of respondents feel that, since they started teleworking, they have made more trips around their place of residence. This result directly echoes the increase in journeys for leisure-related activities, personal appointments and accompanying children (Table 2 and Fig. 2). With teleworking, people have better access to local amenities during the week, as they save time by avoiding one or more commuting journeys. They are also more likely to be at home during the opening hours of shops and schools (Pigalle, 2024). Logically, the frequency of teleworking and the duration of the commute accentuate the perception of a positive link between the adoption of teleworking and the use of their place of residence. Interestingly, the seniority of teleworking does not change the perception of the teleworkers about the increase in trips located close to the homeplace.

The under-45 s and parents of young children also make the link between teleworking and local trips more often, the former probably especially for leisure activities, and the latter for accompanying their children. Finally, in line with the literature, we find that local amenities also play an important role: the perception of an increase in the number of trips in the proximity of the place of residence is greater for people living in the city centres and suburbs than for those living in the periphery.

## 5. Correlations between private activities, and with local trips

Analysis of the correlations between the answers to the various questions reveals some of the rationale behind the perceived reorganizations of mobility in terms of frequency of private trips and local trips since the adoption of teleworking (Fig. 2).

Our survey highlights substitution phenomena between supermarkets and local shops, and conversely, complementarities between local shops and fresh markets: respondents who say they have increased (or decreased) trip frequency to supermarkets tend to have decreased (or increased) those to local shops. Conversely, those who declared that teleworking adoption had increased (or decreased) their trips to local shops tended to consider that they went to the fresh markets more (or less) often. Logically, there is also a positive link between an increase in visits to local shops and an increase in local trips.

In addition, while the survey shows no correlation between changes in errands trips and those linked to other private activities, it does reveal complementarities between other personal and family activities, as well as between the latter and local trips. The more teleworkers feel that they have increased their leisure trips, those related to accompanying children, visiting family and friends and personal appointments since they started teleworking, the more often they say they travel more frequently around their homeplace. Teleworking therefore encourages family and personal activities to take place closer to the place of residence. Finally, weekend departures appear to be positively associated with an increase in trips for leisure, personal appointments, visits to family and friends, and local trips. This last result might suggest that the increase in weekend trips by some teleworkers is encouraged by an increased desire to ‘get out’ of the home area, linked to a particularly strong refocusing of day-to-day activities within this area as a result of teleworking adoption.

## 6. Discussion and conclusion

This research, carried out at a time when the practice of teleworking in France is gradually becoming normalised, explores the influence of teleworking adoption on activity-travel patterns and especially private travel. Contrary to most studies, it is based on perceived changes since the adoption of teleworking and not on travel data. Therefore, it provides additional information, but is not completely comparable with previous literature.

Firstly, our results show that most teleworkers feel that they have not changed their private travel habits since adopting teleworking. This result refers to the recent research by Wang et al. (2024) and Wang and Mokhtarian (2024) which highlight, on the one hand, that the adoption of telework is not only related to travel issues and, on the other hand, that there is a close relationship between teleworking-related motives and changes in travel behavior. More precisely, our results encourage the exploration of teleworkers’ perceptions of how telework can help them to reorganize their activities and travel patterns, and in particular to reorganize them in such a way as to reduce the environmental impact of their mobility. The results could help companies and public authorities to set up awareness-raising campaigns to encourage teleworkers to change their behaviour, and especially make more local trips and reduce the use of the car for their everyday activities.

Secondly, our research shows that the perceived changes in the frequency of private trips and local trips vary according to the purpose of the trip, the characteristics of the teleworkers, particularly in terms of residential location and commute duration, and their frequency of teleworking. In detail, errands trips follow a very different logic to other family and personal activities. Whatever the commercial format (supermarkets, local shops and fresh markets), teleworkers more often perceive a decline in errands trips than an increase. Moreover, people living in central municipalities consider that they tend to go less often to
<table><caption>**Table 3**
Effects of teleworking adoption on the perceived changes in the frequency of local trip and weekend departures.</caption><thead><tr><th>Characteristics of telework</th><th>Local trips</th><th>Weekend departures</th></tr></thead><tbody><tr><td>Frequency</td><td>F(1,790) = 11.10, p &lt; 0.001</td><td>F(1,790) = 1.45, p = 0.228</td></tr><tr><td>0.5</td><td>0.384***</td><td>0.012</td></tr><tr><td>1 to 2.5</td><td>0.571***</td><td>-0.040</td></tr><tr><td>3 to 5</td><td>0.805***</td><td>-0.105</td></tr><tr><td>Flextime</td><td>F(1,790) = 0.89, p = 0.346</td><td>F(1,790) = 0.38, p = 0.536</td></tr><tr><td>0 %</td><td>0.404***</td><td>-0.062</td></tr><tr><td>50 %</td><td>0.463***</td><td>-0.033</td></tr><tr><td>100 %</td><td>0.521***</td><td>-0.003</td></tr><tr><td>Seniority</td><td>F(2,790) = 0.55, p = 0.577</td><td>F(2,790) = 0.52, p = 0.594</td></tr><tr><td>Less than 2 years</td><td>0.516***</td><td>0.010</td></tr><tr><td>Between 2 and 5 years</td><td>0.537***</td><td>0.009</td></tr><tr><td>More than 5 years</td><td>0.422***</td><td>-0.072</td></tr><tr><td>Weekly organisation</td><td>F(3,790) = 0.13, p = 0.942</td><td>F(3,790) = 3.41, p = 0.02</td></tr><tr><td>Half day</td><td>0.526***</td><td>0.008</td></tr><tr><td>Mixed</td><td>0.429**</td><td>-0.117</td></tr><tr><td>Variable</td><td>0.501***</td><td>0.107</td></tr><tr><td>Whole day</td><td>0.511***</td><td>-0.068</td></tr><tr><td><strong>Socio-demographic characteristics</strong></td><td></td><td></td></tr><tr><td>Gender</td><td>F(1,790) = 0.66, p = 0.416</td><td>F(1,790) = 0.08, p = 0.775</td></tr><tr><td>Male</td><td>0.470***</td><td>-0.024</td></tr><tr><td>Female</td><td>0.514***</td><td>-0.012</td></tr><tr><td>Education</td><td>F(1,790) = 1.32, p = 0.251</td><td>F(1,790) = 1.52, p = 0.218</td></tr><tr><td>No diploma</td><td>0.683***</td><td>0.141</td></tr><tr><td>Baccalaureat</td><td>0.568***</td><td>0.045</td></tr><tr><td>Bac + 8</td><td>0.436***</td><td>-0.064</td></tr><tr><td>Car access</td><td>F(1,790) = 2.18, p = 0.141</td><td>F(1,790) = 0.34, p = 0.561</td></tr><tr><td>No</td><td>0.440***</td><td>-0.034</td></tr><tr><td>Yes</td><td>0.544***</td><td>-0.002</td></tr><tr><td>Lifecourse</td><td>F(3,790) = 6.97, p &lt; 0.001</td><td>F(3,790) = 6.65, p &lt; 0.001</td></tr><tr><td>&gt; 45 years old</td><td>0.337***</td><td>-0.122*</td></tr><tr><td>&lt; 45 years</td><td>0.655***</td><td>0.125*</td></tr><tr><td>Parents 0–10</td><td>0.555***</td><td>-0.024</td></tr><tr><td>Parents 11–18</td><td>0.420***</td><td>-0.050</td></tr><tr><td><strong>Economic and professional characteristics</strong></td><td></td><td></td></tr><tr><td>Living standards</td><td>F(1,790) = 1.97, p = 0.160</td><td>F(1,790) = 0.45, p = 0.504</td></tr><tr><td>Very difficult</td><td>0.339**</td><td>-0.074</td></tr><tr><td>Well</td><td>0.443***</td><td>-0.036</td></tr><tr><td>Very comfortable</td><td>0.457***</td><td>0.003</td></tr><tr><td>Occupation</td><td>F(6,790) = 1.60, p = 0.144</td><td>F(6,790) = 1.47, p = 0.185</td></tr><tr><td>Executive (private sector)</td><td>0.584***</td><td>0.040</td></tr><tr><td>Executive (public sector)</td><td>0.558***</td><td>-0.025</td></tr><tr><td>Company manager</td><td>0.135</td><td>-0.225</td></tr><tr><td>Employee or worker (public sector)</td><td>0.562***</td><td>0.015</td></tr><tr><td>Employee or worker (private sector)</td><td>0.419*</td><td>0.140</td></tr><tr><td>Technician or supervisor (public sector)</td><td>0.566***</td><td>0.018</td></tr><tr><td>Technician or supervisor (private sector)</td><td>0.618***</td><td>-0.088</td></tr><tr><td><strong>Place of residence and commuting</strong></td><td></td><td></td></tr><tr><td>Place of residence</td><td>F(2,790) = 3.16, p = 0.04</td><td>F(2,790) = 0.68, p = 0.507</td></tr><tr><td>Centre</td><td>0.559***</td><td>0.010</td></tr><tr><td>Suburbs</td><td>0.527***</td><td>-0.046</td></tr><tr><td>Periphery</td><td>0.389***</td><td>-0.017</td></tr><tr><td>Commuting time</td><td>F(2,790) = 13.15, p &lt; 0.001</td><td>F(2,790) = 1.30, p = 0.272</td></tr><tr><td>&lt; 30 min</td><td>0.295***</td><td>-0.030</td></tr><tr><td>30–59 min</td><td>0.542***</td><td>0.029</td></tr><tr><td>&gt; 60 min</td><td>0.638***</td><td>-0.052</td></tr></tbody></table>

Note: * p < 0.05, ** p < 0.01, *** p < 0.001; bold: significant (differences between groups).

<figure><img src="image_3.png" /><figcaption>**Fig. 2.** Correlation matrix between variables relating to private travel.</figcaption></figure>

supermarkets, and those living in the suburbs and peripheral areas visit local shops less. For other personal and family activities, the trend is rather upwards, confirming, like other studies before ours, the role of telework as a factor in the re-articulation of private and professional activities. In detail, the increases concern family activities more in the case of households with children, if not personal activities. While the length of time people have been teleworking and its flexibility do not seem to have any influence on changes in private trips frequency, the weekly frequency of teleworking and commuting time do matter: the greater the increase in time spent at home, the greater the increase in the frequency of personal and family trips. These changes tend to favour the area of residence, particularly in the areas with the best amenities (central and suburban municipalities), although the periphery is also concerned. Residential characteristics therefore play a central role in the impact of teleworking on local trips. These results suggest that the development of telecommuting offers both opportunities and risks for more sustainable mobility. The threat of increased urban sprawl carries the seeds of greater dependence on the car, and an increase in the distances covered by this highly polluting mode (Denham, 2021). But our results also confirm that telecommuting can also encourage more short trips to shops, services and leisure activities close to home (Ellder, 2020). Therefore, teleworking could support land-use and transportation policies aimed at reducing emissions from everyday mobility. While the policies to be implemented to achieve this have not changed radically from the pre-pandemic period, they could, thanks to this new organization of work, which is now important for some of the working population, be better accepted by public authorities and the general public.

By reducing commuting trips on certain days of the week and increasing the demand for mobility in certain areas and during off-peak hours, teleworking complicates the management of networks and poses serious risks to public transportation. A drop in ridership has already been observed in some major urban networks. It varies according to the day of the week, reflecting the non-uniformity of preferences in terms of teleworking days (Motte-Baumvol et al., 2024). In the longer term, there is also a risk that some teleworkers who use public transport will switch to cars. Timetable adjustments and specific fare offers are beginning to
be developed to retain them. In a context of high fuel prices, they could also help convince solo car teleworkers to switch to public transport. By changing daytime presence in many areas, the development of teleworking implies, more broadly, more or less significant adjustments in the local mobility offer. While some business districts are suffering from a massive exodus, on the other hand, districts or municipalities that were previously empty during the day are once again attracting residents and therefore new travel needs throughout the day. However, their management is crucial in the transition to more sober practices. Finally, the development of teleworking requires, more than ever, the continuation of policies to control urban sprawl in favor of territories that are better served and better equipped with shops and services. It is indeed there that remote working is accompanied by a return to daily journeys close to the place of residence, which is known to be favorable to active modes of transport. The challenge for the public authorities is also to provide the connections between these areas and the major employment and commercial zones with transport solutions that are either alternative or enable a connection to rail transport: dedicated lanes for public transport and car-sharing, express coach services, self-service bicycle hire at stations, etc.

The challenge is also for employers to seize telecommuting more concretely as a lever towards more sober mobility (Hernández-Tamurejo et al., 2024). The aim should be as much to prevent the reduced frequency of commuting from encouraging a modal shift to the car, as to make the adoption of telecommuting a privileged moment for switching to alternative modes of transport via information campaigns and incentive measures (accompaniment, subsidies for bicycle use, etc.). Indeed, the lack of consideration for commuting issues when adopting telecommuting is one of the obstacles to the adoption of more sustainable practices (Wang et al., 2024).

This research also needs to be updated, as the practice of teleworking has evolved in France since 2022 towards a reduction in the weekly frequency of the practice. Our analysis also raises a number of questions that cannot be answered with our data. These include the role of e-commerce (for errands trips), the role of the characteristics of the workplace and the home-work commute (which may or may not allow a certain number of private activities to be included), and the probable intra-family reconfigurations which may lead, depending on the case, to activities and therefore trips being transferred to the teleworker(s) or other members of the household. In addition, the links between the adoption of telework and family and friendships deserve better analysis, distinguishing between family and friends, the close and the more distant. Weekend trips, discussed here in terms of weekend trips, also requires further analysis in relationship with the literature on workation (Voll et al., 2023). New surveys are needed to make progress in understanding the effects of adopting telework on activity-travel patterns, over the long term (including the question of residential strategies) and on a family scale. In that regard, longitudinal data (Reiffer et al., 2023) and mobility biographies approach (Rau and Manton, 2016) would be very useful.

## CRediT authorship contribution statement

**Anne Aguiléra:** Writing – review & editing, Writing – original draft, Validation, Supervision, Project administration, Methodology, Investigation, Funding acquisition. **Eleonore Pigalle:** Writing – review & editing, Visualization, Software, Methodology, Formal analysis, Data curation. **Leslie Belton Chevallier:** Writing – review & editing, Validation, Supervision, Methodology, Conceptualization.

## Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

## Data availability

Data will be made available on request.

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