Sampling frame

The core sample included a group of 20 respondents who had become users of the metro after its Line 2 (or Line 1 extension) reached them in 2012. 13 of the 20 participants started commuting by metro as soon as the new Line 2, or the new Line 1 stations, opened, and the remaining seven adopted the metro extension as commuting mode within 6 months of the launch. 10 out of the 20 lived in the northern Sofia neighbourhood of Nadezhda. While the sample size was relatively small, a total of 82 core interviews, between 35 and 90 minutes in length, were conducted, generating a wealth of data. In addition to the core sample, ride-along interviews were carried out with 11 commuters who did not use the 2012 metro extension.

The most important question to address when determining the sampling frame for the repeated ride-along interviews was the question of who ‘commuters’ were. Rather than a process of straightforward application, the practical realisation of the research design

involved repeatedly moving between theoretical issues and emerging empirical findings.

For example, what at first appeared to be issues of sampling (“Should respondents include freelancers with no permanent offices?”) quickly became important conceptual questions about the focus and limits of research on commuting infrastructures. Was it the regularity of route, destination, time, that made the ‘everydayness’ of everyday travel? How habitual is a journey undertaken on most days, but at different times? The process of thinking through the sampling frame was indivisible from the process of continuous refinement of the conceptual framework (Becker 1998:109-121). To capture the ‘routine-ness’ of routine mobilities, which is central to a study of change, commuting journeys had to be defined in relation to other types of journeys. As will be discussed in the coming chapters, there is in practice substantial variability intrinsic to routine journeys to work, and the commute incorporates many and frequent changes related to travel mode, journey purpose, duration and time, among others. Origins and destinations can exhibit variability too, as commuters occasionally stayed with family members or friends in a place other than their home, moved house, or changed jobs. However, for all participants, a regular, non-discretionary, recognisable commute could be identified among all journeys undertaken – both by me, and by themselves. For sampling purposes, in order to explore the interplay between routine and change, a cut-off was established of a minimum of three such non-discretionary journeys per week, taking place between (any) origin of regular overnight stay, and any non-one-off destination involving paid or unpaid work activities.

Such a definition of routine trips, based around a weekly cycle, allowed me to incorporate the commutes of respondents who worked part-time, or combined work, care, volunteering, and study in a range of (often very complex) arrangements. While complex mobility arrangements can be found across socio-economic and demographic groups, gender has been found to be especially influential in this respect (Kwan and Kotsev 2014) . Defining commuting around a 5-day working week, and a 9-to-5 working pattern would have left out many commuters, and many women in particular, and especially groups for whom public transport services are likely to be important.

Where initial contact with participants was made via email, they were directed to a web-based information sheet, providing details of the purpose of the study, the repeat ride-along interview procedure, as well as data protection and confidentiality procedures (see Appendix 2). In cases where I met prospective participants face-to-face, verbal consent was obtained, based on me providing verbally the information detailed on the study website. Because of the longitudinal research design, I re-iterated the key points from the previously obtained consent at the start of each repeat ride-along interview. These included: recording of interview; freedom to not answer specific questions or to withdraw at any point without giving a reason; secure storage of data; anonymity of findings.

All participants were recruited from friends’ social circles using a snowball technique. My attempts to recruit people to the study who I did not have at least a tentative social connection to, did not yield any results. Such attempts were made online, via social media and a dedicated website, and through leafleting outside metro stations. The two participants who eventually responded to these recruitment drives dropped out after the first ride-alongs and had to be excluded from the sample. I suspect that this was due to the combined effect of two factors. First, the topic of commuting habits, while interesting to some, was probably perceived as somewhat trivial in a place faced with many serious and urgent socio-economic issues. Second, the research method of repeated ride-alongs over the course of several months could be perceived as unnecessarily intrusive. Privacy is no small matter in a post-socialist society with living memory of secret police departments and civilian informers (Kremakova 2014). I expect that a stranger waiting outside of one’s house and asking questions all the way to one’s place of work may look suspicious to people in any context, but especially in this one. By contrast, the introduction by a mutual acquaintance provided reassurance and credibility, and thus quickly became the only recruitment strategy. I addressed some of the limitations of this approach by having 12 different entry points into the core sample of new Line 2 commuters, and aiming for some diversity of locations, occupations, socio-economic and household situations, age, gender, without aiming for a representative sample.

An open-ended approach to change and causality meant there could be no presumption that demographic characteristics such as gender or residence would have a particular type of influence on commuting habits. Thus, while sampling aimed for diversity, the subsequent stages of data collection and analysis very deliberately ‘suspended’

assumptions about each of these groups. This approach is advocated by Barr and Prillwitz (2014) for research which focuses on social practices and the circumstances of their performance, rather than on individuals and ‘lifestyles.’

Nevertheless, the core sample was fairly diverse in terms of gender, household type, age, residence and employment status. Figure 4-2 below shows some basic characteristics of the participants in the core and additional samples.

Figure 4-2. Sample characteristics

When I recruited the 11 additional participants, I chose some of them quite deliberately:

they were people who had mentioned plans to move house, or change jobs. I expected that should their relocations lead them to become Line 2 commuters, I would be able to include them in the core sample. However, my secret plan did not come to be realised. Instead, one of the core respondents moved from her home on Line 2 to a new one on Line 1. Because her workplaces remained near a new metro station on Line 2, I was able to retain her as a

Age at start

of study Gender Nearest metro to home

Nearest metro to

work/study Occupation(s)

Anton 37 m Mladost-3 NDK Project manager in NGO

Assya 26 f James Bourchier Joliot-Curie Assistant accountant Nikolay 30 m Expo Centre James Bourchier Call centre operative

Emma 33 f Beli Dunav / K.

Velichkov European Union Account manager in design agency Stella

55 f Central Station Serdika Project manager in government department

35 m James Bourchier Central Station Shop assistant, part-time photographer

Maya 29 f European Union Opalchenska Accountant

Christo 29 m European Union Expo Centre IT programmer

Natalia 37 f Mladost-3 Sofia University University researcher

core participant. But I also considered it a warning: trying to pre-empt participants’ life events amounted to bad research karma.