Daily mobility patterns of small business owners and homeworkers in post-industrial cities
Introduction
Key fixed geographical locations of people's daily activities associated with work-related activities are undergoing radical changes (even before the onset of COVID-19 travel restrictions), at least partially due to the proliferation of information and communication technologies (ICTs) and new modes of work (Choo & Mokhtarian, 2007; Kwan, 2007). ICTs have blurred the boundaries between home and work as they allow people to work partially or exclusively in their own home. More recently, we are seeing widespread shift to remote and home-based working as a result of COVID-19 (Reuschke & Felstead, 2020). Telecommuting of employees, defined as working from or at home, has received much attention in the transportation literature even before the COVID-19 pandemic. Primary focus has been understanding residential choices and changes in total travel distance and time through the reduction of commuting trips (Helminen & Ristimäki, 2007; Ory & Mokhtarian, 2006; Zhu, 2013) and the timing of the commute (Lachapelle, Tanguay, & Neumark-Gaudet, 2018). However, much less attention has been given to homeworking by workers who are self-employed or run their own businesses (rather than employees).
In many post-industrial economies, self-employment and small business ownership have increased substantially in its share of the overall workforce as a result of parallel processes shaping the nature of work: structural changes in the economy (e.g., changing supply chains and, outsourcing), and the rise of the gig economy (Wood, Lehdonvirta, & Graham, 2018), new technologies that enable small businesses to access distant markets and compete with larger firms (Clark & Douglas, 2011), and a changing workforce that places more emphasis on non-monetary values of work such as work-life balance (Baumberg & Meager, 2015; Burchell, Sehnbruch, Piasna, & Agloni, 2014). For women especially, self-employment and small business ownership appears to offer opportunities to combine work and family (Craig, Powell, & Cortis, 2012; Walker, Wang, & Redmond, 2008; Wellington, 2006).
Men and women who are self-employed or run their own businesses may work from commercial premises (e.g. shops, offices, art studios); but many work from home (Mason, Carter, & Tagg, 2011) or various other places (Liegl, 2014) such as co-working spaces (Clifton, Füzi, & Loudon, 2019). Thus, the diversity in both worker types and work locations has become profoundly higher in contemporary post-industrial economies than was the case in industrial economies – even before the COVID-19 pandemic that resulted in a surge in homeworking in mature economies. The COVID-19 pandemic has underlined that an increased level of workers who are less bound to employer's premises will have a profound impact on urban travel and city systems (Tranos, Reggiani, & Nijkamp, 2013). Those who mainly work from home may travel less or may spend more time in their neighbourhood or in proximate areas, when compared with premise-based workers (Saxena & Mokhtarian, 1997; Zenkteler, Darchen, Mateo-Babiano, & Baffour, 2019). While current research in homeworking has attracted a lot of attention, to date very little research has focused on the daily travel patterns of self-employed workers and those running a small business, that are workers who are not working for an employer. With few exceptions (Mokhtarian & Henderson, 1998; Shin, 2019), transport studies have rarely disaggregated workers by their employment status and whether they run their own business and have thus paid little attention to the transformations being observed in in the workplace.
The overall objective of this paper is to use detailed GPS tracking data to study the daily mobility of under-researched socio-economic groups. Our first research question is whether the daily mobility of individuals in cities is significantly influenced by whether workers are employees or business owners (including as self-employed). Our second research question addresses how individuals who work partly or mainly from home differ (or not) in their daily mobility from those who do not work from home. We further break down these travel patterns by gender and ask in our third research question, whether the daily mobility of homeworkers and business owners/the self-employed is shaped by gender differences. With this approach, we reveal, for the first time, the complexity of homeworking, employment status or small business ownership and gender in cities. With an interest in small business ownership (an established category in business research defined as businesses with 0–49 employees including sole proprietors and owner managers), we specifically investigate the extent to which small business owners are associated with daily mobility patterns that diverge from the daily mobility of ‘traditional’ workers (i.e. employees with separate employer's premises), whether homeworking is producing new daily mobility patterns in cities, and whether this is shaped by differences between men's and women's travel. Specifically, we ask whether small business ownership reproduces established gender differences in daily mobility.
To capture daily mobility patterns of small business owners and contrast them with those of employees, we collected a detailed primary GPS dataset from a survey of workers in two cities in England (United Kingdom). Data were collected pre-COVID-19 but our findings have rather increased in relevance since more and more people started to work from home during the global COVID-19 pandemic, and it is predicted that homeworking is here to stay (Felstead and Reuschke, 2020). GPS tracking data are particularly well-suited to capture highly detailed records of individual daily mobility activity (places visited, travel routes, and timing) without incurring recall error associated with daily travel diaries (Stopher & Shen, 2011). The GPS data we collected cover several days of a standard working week of the surveyed workers thus it contains sufficient variability in daily activity patterns (Kang & Scott, 2010). The GPS data are augmented by an extensive individual questionnaire allowing us to investigate daily mobility patterns related to personal, work and location factors of each individual in our study. We derive four measures of overall daily travel (number of trips, trip duration, trip distance, maximum distance from home) and model each measure against a range of individual and neighbourhood-level covariates believed to be associated with individual-level daily mobility. Findings demonstrate that differences in daily mobility patterns of business ownership/self-employment become apparent most strongly in the intersection with gender.
Section snippets
Self-employment, small business ownership and individual mobility
Economic geographers have highlighted the importance of local social ties and knowledge spill-overs for entrepreneurship and developing a business (Andersson & Larsson, 2016). It is assumed that entrepreneurs and small business owners are strongly embedded in place through their networks (Hanson, 2005). However, there is little research on the daily mobility of small business owners.
Few transport studies exist that have investigated the commutes of the self-employed (rather than small business
Participant recruitment and study groups
We study daily mobility of workers in two cities in England (United Kingdom): Brighton & Hove and Leeds, chosen based on their geographical attributes and their employment characteristics drawn from the 2011 Census of Population data. Brighton & Hove was selected as a medium-sized city (2018 population; 290,400) in the economically strong South East. Brighton & Hove has high proportions of self-employed workers (13.4%; 2018 data) and homeworkers (11%; 2011 data), directly relating to our
Daily number of trips
Daily number of trips showed very little variation between study group types (Fig. 2). After controlling for individual and neighbourhood-level covariates (Table 2; R2GLMM = 0.436), we found no significant differences in the daily number of trips taken between the different worker type groups. However, when more closely analysed by gender, we found that among men, business owners/the self-employed with the home as their base made significantly more trips (about 20% more; exp(β) = 1.213) than
Summary and discussion
Using a longitudinal primary GPS survey augmented by a questionnaire-based survey, we tested for differences in daily mobility of small business owners (including the self-employed) versus employees further disaggregated by whether they work primarily in the home or from separate premises and by gender. In the case of small business owners, we further differentiated between those who run their business from home or use their home as the base for the business but the activities are performed
Acknowledgements
This study was funded by the European Research Council, the Starting Grant WORKANDHOME (ERC- 2014-STG 639403). The authors would like to acknowledge the thoughtful and constructive feedback of the 5 reviewers and the associate editor, whose comments greatly improved the presentation of the manuscript.
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2021, Computers, Environment and Urban SystemsCitation Excerpt :Most studies that utilize this data collection paradigm are focused on presenting a proof of concept or discussing methodological issues, and they tend to rely on limited samples. Prominent research fields that have already started to utilize this approach more substantially in an urban context include environmental health and health geography research in which the level of individual exposure to physical and social environmental factors and their impact on people's physical and mental health and wellbeing is measured at high resolutions (Kou et al., 2020; Kwan et al., 2019; Roberts & Helbich, 2021; Zhang, Zhou, et al., 2020); urban and transportation management and planning (Long & Reuschke, 2021; and Millar et al., 2021 in this special issue); and health monitoring including measuring mobility, physical activity, and physiological status (Li et al., 2017). The study of urban subjective experiences and emotions using portable sensors is another field that has emerged in recent years (Birenboim, 2018; Osborne & Jones, 2017; Shoval, Schvimer, & Tamir, 2018).
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