5.2 About the Empirical Data
5.2.1 Selection of Study Cases
The research findings that are presented in this chapter are based on 10 sampled cases and are summarised in Table 5.1. Although 15 cases were observed in the entire study, a K. Mijinyawa
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Case Business Area Server Apps Enterprise
Apps and API Databases Email and
Web Apps Workstations Business Location
C01 Consultant OpenOffice.org,
SugarCRM, and Vim editor
PostgreSQL Firefox and
Thunderbird Debian London
C02 Server and
PhP, and Ruby Thunderbird Ubuntu (Mac) Manchester
C04 Developers Apache PhP5 MySQL Debian, Gnome,
and Slackware Wakefield C05 Developers of ARM
chip software Apache OpenOffice.org and embedded
and (MS IIS) (Visual Studio) (MS SQL) (Outlook) (MS Win OS) Uxbridge
C08 Developers,
OpenOffice.org PostgresSQL KMail Suse Bucking
hamshire
and PhP MySQL Firefox Linux Scotland
Key:(Application) – All applications in parenthesis are nonOSS candidate small businesses. The small businesses identified in the local directories were contacted through telephone calls and invited to participate in the study. Again, non of the small businesses contacted responded that they used OSS for their business.
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To improve the chances of finding enterprises using OSS, it was decided to focus on IT companies because (I) they are more likely to use diverse software systems and (ii) this extended the search beyond the local county. This initiative led to a search for IT companies listed in telephone directories and online small business directories. Although many businesses were identified, a consideration of costs (where site visits would be necessary) led to a shortlist of IT companies around the local area including the city of London.
An attempt was made to contact these businesses by telephone and invite the shortlisted IT companies in the nearby counties to participant in the study. Difficulties were encountered as many of the phone numbers were no longer valid and some numbers had changed ownership.
In other situations, the company was no longer in business but had retained the telephone number. However, two organisations proved to be useful for this study as they responded positively and were able to participate fully in the study.
Following a very low successrate with the shortlist of IT companies in the nearby counties, it was decided to consider using a telephone media for the interview rather than relying on site visits as the only mode of contact. This led to further consideration of other IT companies outside the local and nearby counties, as illustrated in the diversity of business locations in Table 5.1. Based on this sampling approach, many IT companies using OSS were identified.
Some of this tranche of companies were again also no longer in business, but many others were successfully contacted. However, a high proportion of the companies contacted turned down the invitation to participate on the grounds that they had limited staff and time to accommodate research surveys and interviews, and some responded that they had a company policy to not participate in student research or survey. For companies that responded that they were busy or had limited time, efforts were made to negotiate appropriate times to contact them and a maximum time limit for the interview was also suggested. This initiative proved useful as some of the contacts were able to use the flexible arrangement and participate in the study. The participants were mainly key figures in the organisations including general managers/owners and IT manager or IT teamleaders. The majority of the interviews lasted for around one hour with the participant responding to all questions of the inquiry. A few interviews ran for up to two hours because the participant was happy to provide broad contexts and their personal experiences of issues related to the interview questions. Another interview also ran into a two hour period owing to long pauses during the interview as the participant attended to other issues in their environment, while the researcher waited patiently. All cases featured had a single participant, often an organisational figure head such
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as the general manger/owner, or the IT manager. Owing to limited availability of participants and the need to manage the volume of qualitative data, a single participant case was deemed to suffice. This was also on the understanding that the initial participant responded to all the interview questions.
As discussed in Chapter 4, a theoretical sampling strategy (Eisenhardt 1989; Meredith 1998;
Yin 1994) was applied for selecting the cases in this study. The use of a theoretical sampling strategy has allowed us to compare factors identified across the study cases. This comparison is important because it is central to the crosscase analysis processes which, as discussed later in this chapter, involves the comparison of factors across all cases to establish their analytical generalisability (Eisenhardt 1989) and thus support theorisation in this study. The use of a theoretical sampling strategy has also allowed us to select cases that provide rich information, in terms of maximum variation in technological, organisational and environmental issues (see, for example, Chapter 2).
Another important point on the use of theoretical sampling was the targeting of IT managers or the small business mangers/owners for participation as interviewees. Such figures were targeted because they were seen as the key decision makers and change agents in the adoption of OSS in the organisation and, they could provide a diverse and rich sources of information as participants providing answers to specific interview questions and also as informants providing access or information that leads to other sources of information. The scope of comparison and the variation of the selected cases will now be discussed.
The summary of selected cases, as shown in Table 5.1, shows a variation in SME profiles including software in use, business area and geographical location of the IT SMEs. The variations across the selected cases allow us to explore a variety of technological, organisational and environmental issues that influence the adoption of OSS by the IT SMEs.
As explained below, the cases contribute differently to the variation of the factors identified in this study.
Various selected cases allowed the capture of the influences of variation in SMEs' IT environments. For example, cases C01, C04, C05, C06 and C08 used OSSonly platforms;
cases C02, C03, C09 and C10 used mixed software platforms; and case C07 used a nonOSS platform. As shown in Table 5.1, the nonOSS applications recorded in this study are shown in brackets. The relevance of case 07 in this study is explained later in this section. The
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variations in IT environment also allow us to explore a variety of technological issues that influence the adoption of OSS by the selected IT SMEs.
The selected cases also allowed the capture of variations in business speciality within the IT industry. For example, cases C04, C05, C07, C08, C09 and C10 are software developers of business applications; cases C01, C03, C06 and C08 are IT consultants; and cases C02 and C05 operate in software development for embedded systems. The variations in business area allow us to explore a variety of organisational issues that influence the adoption of OSS by the IT SMEs.
As shown in Table 5.1, the selected cases also allow us to capture data from geographically dispersed locations: cases C01, C02, C03, C04, C05, C07 and C08 are SMEs based in England;
case C10 is based in Scotland; and case C06 is based in Wales. These variations in business location provide an, albeit limited, opportunity to explore the organisational and environmental issues that influence the IT SMEs in this study.
The variations in the selected cases provided rich information in this study. However, the cases were also selected because they satisfy the condition for unit of analysis for this study.
Thus, with the exception of case 07, as explained below, all cases are IT SMEs using OSS (see Table 5.1). The business area in Table 5.1 shows that all the selected cases operate in the IT industry in the UK. The variation in the technological, organisational, and environmental factors across the cases also provides a profile for comparison of the factors that emerge from the selected cases. This comparison is particularly important in the crosscase analysis stage, reported in section 5.5.
Case C07 is an exception to the rule for unit of analysis, as mentioned above. As shown in Table 5.1, case C07 is a nonOSS adopter. This case provided alternative views to some factors identified in the study, and thus enhances the understanding of such issues. This case was selected as an opportunistic and negative instance sampling (Coyne 1997; Patton 1990;
Sandelowski 1995; Yin 1994).
Although the variation in the selected cases provides an opportunity to explore rich information, the variations in the SMEs, their technologies and their business environment also manifest during the interview sessions and this was noticed during the transcription of the interview recordings. In order to manage the variations in the interview dialogues with
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different participants, a standard for developing highquality interview transcripts for all 10 cases was applied, and this is discussed in the next section.