Coding the Data - Data Analysis

CHAPTER 3: METHODOLOGY Conducting a PARTicipative Inquiry

3.5 Research Methods

3.5.2 Data Analysis

3.5.2.1 Coding the Data

To conduct the above form of Foucauldian discourse analysis, the researcher began with an inductive and iterative process of ‘open coding’ in NVivo. At this phase, instances of problematisations, technologies (i.e. power struggles), subject positions and subjectification (i.e. self-care practices) were extracted from the verbal and written data. The texts were “broken down into discrete parts, closely examined and compared for similarities and dissimilarities”

(Babbie, 2013: 397), with each grouping of (related) extracts being coded under an appropriately titled code (or, in NVivo, ‘node’) (see Table 3.2, column 1).

Extracts were coded more than once if the subject matter crossed over several codes. It is noted that this process of open coding did not separate the extracts by theoretical construct, but by similarities in content. This was because there were instances where more than one theoretical construct was evident within an extract (as captured in the conceptual framing, Figure 2.2). Appendix 7 provides an example NVivo coding summary for the code, ‘lack of alternative’; see Figure 3.2, column 1, row 4 for the code’s placement in the overall coding process.

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‘Didn’t see…’ Unavailable Infrastructural

availability

Pragmatic Utility

‘Can’t do…’

‘No access to…’

‘Lack of alternative…’

‘Difficult to do…’ Hard to do/find

‘Struggled to find…’

‘Can’t rely on…’

‘Not local practice…’ ‘Home’/‘away’

differences in availability

‘Assumed it would be the same…’

‘Determined to speak’ Interacting with host Language

(barriers)

‘Hard when don’t have the language’

‘Hard off beaten track…’

‘They start speaking English’

‘Hard to understand’ Understanding others

‘Accents can be difficult’

‘Stressed with understanding different language’

‘Easier when can speak language’

102 Table 3.2 Coding process for ‘Pragmatic Utility’

First round of Open Coding (Codes)

Second round of Open Coding (Categories)

Axial Coding (Higher Order

Categories)

Title of Theme (Core Category)

‘Language proficiency makes it easier to navigate’ Confidence Language (barriers)

Pragmatic Utility

‘Language proficiency increases confidence to travel independently’

‘Financial restrictions’ Budget Finance

‘Not got a lot of money’

‘Pay more for ethics’ Expensive

‘Price factor’ Cost/price

‘Already paid’

‘X enjoys…’ Conflict Fellow travellers

‘X prefers…’

‘X wanted to do…’

‘X didn’t want to…’

‘X was in charge of plans…’

‘We compromise’ Compromise

‘We do/did this instead’

‘X is young’ Other considerations

‘X is pregnant’

‘Grim’ Bad conditions Weather

‘Pouring down’ / ‘soaking wet’

‘Plans depend on weather’ Influences activities

‘Drove more due to bad weather’

Cont’d

103 To demonstrate, the following passage from June’s Reflective interview provides an example of how one extract was coded twice (i.e. under ‘can’t do’

and ‘lack of alternative’, Table 3.2, column 1, rows 2 and 4):

All the time we had to buy bottles of water. So the whole time we were contributing to this heap of plastic, because there was absolutely no way to obtain water that was safe for us to drink unless we bought bottles.

But if there was some sort of water purification, or something where we could have filled up bottles, we would have happily done that. But there just wasn’t the opportunity.

Despite not wanting to continually drink from plastic bottles, June and her friends had to as “there was absolutely no way to obtain water” (e.g. ‘can’t do’);

there was not even “some sort of water purification” which would have allowed them to re-fill old bottles (‘lack of alternative’). This excerpt further evidences two theoretical constructs, in that given her ‘problematisation’ (see underlined section), she offers a ‘subjectification’ narrative (see italicised section) as a form of ‘self-care’. More specifically, to remedy her anxiety over her mass use of plastic, she makes it known that she would have “happily” acted more ethically, and resorted to refilling the same bottle, had she been able to do so.

Following this first round of open coding, a second round of open coding was conducted. This involved grouping the initial codes into “abstract concepts termed categories” (Babbie, 2013: 397) (see Table 3.2, column 2). The researcher then engaged in a process of ‘axial coding’, whereby these categories were developed into higher order categories (Table 3.2, column 3). Klenke (2016: 100) suggests that these “axial categories are enriched by their fit with as many passages as possible”. Table 3.3 provides example data to show how the first-round codes (e.g. ‘financial restrictions’ and ‘not a lot of money’) evolved

104 Table 3.3 Open and axial coding

Codes

“When I was camping in the States, like I could have bought sort of local, you know, food from with the area I was staying that was kind of from local produce. And maybe gone to local restaurants. But just because of, you know, sort of financial restrictions and ease of doing it, I instead just bought a Calor gas stove and some Ramen noodles and just cooked them. Which is like...

which is just really bad” of responsible tourism. I plan to be better in the future, but right now on a budget”

(Giovanna, Prospective Phase, subject position and subjectification) Pay more for ethics:

“Bit miffed with the [Name] Cafe...very popular..VERY EXPENSIVE...why do we have to pay through the nose for eating ethically?”

(Barbara, Active Phase, problematisation)

Expensive

Price factor:

“Some choices maybe appear more ethical (like walking or eating at local places) - but are actually based on cost”

(Sam, Active Phase, subject position)

Cost / price Already paid:

“Money tension again, yeah absolutely.

That, you know, if you’ve paid for one thing, going and spending money elsewhere doesn’t feel right”

(Sophie, Reflective Phase, problematisation)

105 into a category (e.g. ‘budget’); and how these categories (e.g. ‘budget’,

‘expensive’ and ‘cost/price’) combined to form a higher-order category (e.g.

‘finance’).

The final stage of the analysis consisted of the researcher categorising the higher order categories into a set of ‘core’ categories (Strauss, 1987) – such as

‘pragmatic utility’ (see Table 3.2, column 4) – that demonstrate the main, overarching ways in which tourists exert their ethical agency. These core categories tended to provide the foundations for the results chapters; for example, ‘walking the talk’, ‘reflexive inertia’ and ‘pragmatic utility’ form the building blocks for Chapter 6, Self-Reflexivity.

It is highlighted that, while data was collected from the Prospective, Active and Reflective phases of the tourism experience (3.5.1), Chapters 4, 5 and 6 do not consistently present an analysis of excerpts from each phase. This is because, data pertaining to each code or category might not transpose across all three phases. For example, a participant might only reflect (post-holiday) on the importance of ‘cost/price’ after noting the expense of a particular product or service on holiday; while in the pre-holiday interview financial concerns were not alluded to as a potential impedance of ethical action. In instances such as this, it was not for the researcher to automatically assume that ‘cost/price’ was not deemed an issue in the Prospective Phase, simply that it wasn’t brought to her attention. In this regard, data was only explicitly triangulated in instances where the availability of data permitted.

106 3.5.3 Sampling

Initially, purposive sampling was employed with the aim of generating a research sample of circa sixteen subjects, wherein each participant: (1) self-identified as an ‘ethical’ or ‘responsible’ tourist (and/or consumer), and; (2) was holidaying within the 12-month period of June 2015 – June 2016. This form of sampling was chosen to ensure that the recruited participants had sufficient experience or knowledge in ethical and responsible tourism practices to

“facilitate an investigation” (Adler & Clark, 2008: 121).

In April-July 2015, the researcher contacted and/or disseminated a Participant Information Sheet to: 13 tour operators and companies that market themselves as specialising in responsible (and/or sustainable, eco, green etc.) tourism; 1 tourism network on LinkedIn (i.e. Responsible Travel and Tourism, 16,000+

members at the time of sampling); 5 travel forums; 3 responsible tourism associations; 1 ethical consumption forum; 5 Facebook pages; 1 sustainable association; and 1 charity. In total, the research was promoted via thirty outlets, however only two participants were recruited; one from the Responsible Travel and Tourism group on LinkedIn (i.e. Maria, see Table 3.4), and one from the Ethical Consumer Forum (i.e. Lina).

Accordingly, while maintaining the initial ‘purposive’ criteria, snowball sampling was then employed. The researcher contacted several individuals who she knew to self-identity as responsible tourists to ask if they would like to participate, and, from this, “asked those individuals to provide the information needed to locate other members of [the target] population whom they happen to know” (Rubin & Babbie, 2010: 149).

107 Table 3.4 Characteristics of sample

Code Pseudonym Age Occupation Destination Travelled with

B16 Barbara 59 Personal assistant Cambridge,

Alone Long weekend break 2 nights

C8 Connor 37 Dietician Peru Partner Sight-seeing holiday 2 weeks

E2 Edward 58 IT/Management consultant France Partner Relaxation holiday 1 week

F6 Freddie 54 Financial advisor Lanzarote Friends Fitness holiday 1 week

G1 Giovanna 25 Charity administrator

Spain Boyfriend Road trip / sight-seeing holiday 1 week

J12 Josh 32 Doctor Seychelles Wife Late honeymoon 2 weeks

J14 June 58 Retired India Husband /

friends

Sight-seeing holiday 3.5 weeks

L4 Lina 24 Student Morocco Family Family holiday 1 week

M7 Mabel 77 Semi-retired yoga teacher Northumbria, UK

Partner Long weekend break 2 nights

M9 Maria 32 Administrator Spain Partner Family holiday 1 week

S15 Sam 51 Local government officer New Zealand Wife Sight-seeing holiday (coinciding with wife’s study abroad)

1 month

S11 Sophie 33 Physiotherapist and student Seychelles Husband Late honeymoon 2 weeks

W13 William 24 Student Cairngorms,

Alone Activity holiday 1 week

108 Figure 3.3 PARTicipative inquiry timeline (N.b. _P and _R denote Prospective and Reflective phases; shading denotes month of Active Phase)

2015 2016

109 Overall, as shown in Figure 3.3, it took thirteen months to form a research sample in this way, and one year and three months to collect the data of all sixteen participants (i.e. extending 3 months beyond the initial June 2015-2016 timeframe). Seven participants were recruited in the summer of 2015; five were recruited in the autumn of 2015; two were recruited prior to their winter holidays in 2015-16; one was recruited in the spring of 2016; and one in the summer of 2016. As the timeline indicates, the frequency with which participants were recruited slowed down over time. Out of the sixteen participants, nine were female and seven were male, and the spread of domestic (4), European (5) and international travel (7) was relatively even. Table 3.4 provides the age, occupation, destination, travel partners, holiday type and duration for each participant.

As responsible tourism is a niche area (Sharpley, 2013), the sample size was considered acceptable due to the smaller ‘population’ of potential respondents (Bailey, 2008). The sample size was equal to, or greater than, that within recent studies into the tourist experience (e.g. Small, 2016 (n=16); Brown & Osman, 2010 (n=14)), especially literature which specifically focuses on the experience of ethical and responsible tourists (e.g. Malone et al, 2014 (n=13); Caruana et al, 2014 (n=16)).

The sample size was further deemed appropriate given that the focus of the thesis was on providing in-depth and ‘thick descriptions’ (Guba, 1981) of the tourist experience. The nature of PARTicipative inquiry meant that the researcher accumulated three bodies of data for each participant (one per phase), ultimately resulting in a large, rich dataset. Table 3.5 itemises the data by participant, listing

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Freddie 0:48:21 99 2,178 Hotel’s weekly activity programme 1:08:44

Giovanna 0:40:38 39 852 Leaflets (e.g. for her canoeing activity, wine tasting

experience, and Praia das Catedrais)