PLANTA DE TRATAMIENTO DE AGUAS RESIDUALES DE

This PhD dissertation relies largely on primary data collected in the organizational setting of the investigated digital payment platform ecosystem, MobilePay (Paper II, Paper V, and Paper VI). As Industrial PhD fellow, employed by Danske Bank for the duration of the PhD project (October 2015-September 2018), I entered the unit developing and managing MobilePay in October 2015 as part of the team, responsible for the proposing, conceptualizing and developing novel ideas (the Concepts team), and which determined to a large extent the future evolution of MobilePay. During the first two years of the project, I spent three days per week at MobilePay and were active member of the Concepts team. In September 2017, I embarked on a four-month research visit to the Center for Process Innovation (CEPRIN), part of Georgia State University, USA, where I collaborated with Prof. Lars Mathiassen and Prof. Arun Rai on Paper II and with Prof. Jonny Holmstrom on Paper III.

In October 2015, when I joined the company, MobilePay had operated for two and a half years and had successfully attracted significant number of both private and commercial customers (see above). As I was interested to gain insights into the initial success of MobilePay and to observe the next steps on its path toward maturity, the Concepts team constituted a suitable place to obtain first-hand knowledge. The team initially consisted of five people, each having different competences and being responsible for various projects. During the time I spent with them, some members left the team in pursuit of other employment, while other people joined. As part of an organizational restructuring in September 2017, part of the team members joined a different team, while, I, together with three other colleagues, remained part of a new team (The Venture team).

52 To collect data about the evolutionary journey of MobilePay, I used participant observation, semi-structured interviews and unofficial conversations with employees, supplemented with secondary data such as archival documents (presentations, memos, meeting notes, analysis, emails, posters, etc.) (Paper II, Paper IV, Paper VI) (Table 4). The preferred approach for data collection was participant observation as “a process enabling researchers to learn about the activities of the people under study in the natural setting through observing and participating in those activities” (Kawulich 2005, p. xxx). Although studies, which rely on participant observations, are rather scant in the IS field, such approach “can enhance our understanding of IS phenomena” (Moore and Yager 2011, p. 127). Participant observation is used when a researcher seeks to acquire profound knowledge about the events and actions, rooted in specific context, that shape a particular phenomenon (Iacono et al., 2009).

For the duration of my employment, the Head of the Concepts team supervised my work and helped me navigate through the organizational structure of both MobilePay and Danske Bank. In particular, I had one-to- one bi-weekly meetings with him discussing ongoing issues around MobilePay and receiving feedback on a number of tasks, in which I have been involved, together with the other members of the team, in my attempts to gain better insights into their work. I also participated in the bi-weekly team meetings, where the team members discussed current affairs, the tasks they were working on and future projects. As the MobilePay unit was relatively small (between 30-40 people), I also had frequent encounters with members of the other teams during weekly status meetings and bi-weekly, later monthly, department meetings, where the Head of MobilePay discussed key issues with all employees, semi-structured interviews, lunch breaks, breakout sessions, and more.

In my role as participant observer, I also contributed selectively to a number of projects, meetings and tasks during my stay at the company. The purpose was to obtain in-depth insights about events as they unfolded and to gain credibility from my colleagues, who would be more willing to share information if they perceived me as an active team member (Pettigrew, 1990; Van de Ven and Hubert, 1990). I engaged in variety of tasks, from initial development of innovation ideas and conducting research on latest developments in the domestic, regional and international payment sectors, to developing competitors’ analysis, presentations for legal authorities, and governance policies for working with third-party developers.

As result of my engagement in the company, I managed to collect vast amount of primary data (see Table 4). Throughout the duration of the participant observation (October 2015-September 2017), I kept a research diary, where I noted down on daily basis my observations (for a sample, see Figure 8).

53 Figure 8. Sample of the Research Diary

As a result, I documented the main events taking place within the company (launch of new features, competitors shift, new partnerships, change in strategic goals, working processes, organizational changes, and more) in the form of narrative spanning across 61 pages. In the research diary, I also captured the discourse around various events (opinions, comments, challenges, and developments) as they unfolded. Furthermore, I took extensive notes during the team meetings, department meetings, status meetings, workshops, and breakout sessions, which I attended. Collectively, these notes amount to 145 pages.

Participant observation as an approach to data collection, however, is not without limitations and thus, researchers advise for its combination with other techniques such as interviews and archival data (see e.g., Kawulich 2005). To complement the data gathered through empirical observations, I further conducted 16 semi-structured interviews with selected MobilePay employees in order to obtain additional insights. I conducted the interviews in English, with the duration of the interviews varying from thirty minutes to an hour and twenty minutes. As the obtained information from the interviews often overlapped with already documented insights (from meeting notes and informal conversations), I decided to engage primarily in observations and informal conversations with colleagues at MobilePay as my main method for collecting data (Leonard-Barton, 1990).

To supplement my data collection, I gathered large amount of archival data (presentations, strategic documents, emails, etc.). In particular, I archived 83 emails, which contained information about important events during the evolutionary journey of MobilePay (e.g., announcement of new product launches, strategic decisions, organizational changes, etc.). I also archived 60 presentations and 55 documents such as press releases, product

54 guidelines, strategic analysis, and release notes. The collected archived data, together with insights from semi- structured interviews and informal conversations, were the main source of information, which helped me restore the evolutionary path of MobilePay from its launch in May 2013 until I joined the unit in October 2015.

Table 4. Overview of MobilePay Data Sources

Type of Data Data Points Description

Primary

Research diary 61 pages

Notes from meetings 145 pages

Semi-structured interviews 16 (between 30 minutes to 1 hour and 20 minutes)

Secondary

Emails 83

Presentations 60

Documents 55

As Paper I and Paper III aim at reviewing relevant literature, the data collection for these papers encompasses identifying and reviewing of a number of studies (for more details, see respective studies). Paper I seeks to identify the various manners in which researchers conceptualized digital platform ecosystem evolution. As part of the adopted concept reconstruction method, I conducted a hermeneutic literature review by iterating between data collection and data analysis (see Boell and Cecez-Kecmanovic 2014). Utilizing extensive keyword strategy, I identified 98 articles across various fields (information systems, organizational studies, product management, innovation studies, etc.), which dealt with digital platform ecosystem evolution either explicitly or implicitly.

Although Paper III also utilizes extensive literature review to advance further our understanding of digital platform ecosystem evolution from dialectical perspective, the data collection process differed. The preferred approach for collecting data was snowballing, where the researcher selects a key article and uses its references to identify additional articles to include in the literature review (Atkinson and Flint, 2001). By looking at the references of a key article in the platform literature (Gawer (2014) on bridging the two streams in the platform literature – economic and engineering), we selected 29 out of the 91 references after reading the abstracts. To identify the final pool of articles, we used two criteria: 1) articles that investigate digital platform ecosystems, 2) articles, which focus on tensions and conflicts.

In order to capture relevant platform research after 2014 (after the publication of Gawer’s article), we identified all the articles citing Gawer (2014) in their references by using Scopus. We initially selected 38 articles. After identifying the articles, we went through their references and identified additional relevant articles to add to the final sampling. We then went through their respective references until we could not identify any new relevant articles. In the final sampling, we ended up with 65 articles from various fields of research.

55 Paper IV utilizes multi-case study informed by both primary and secondary data. To present the strategic challenges MobilePay faced and the strategies it used, we relied on primary data (see above). As we were not able to collect primary data for the other cases, the research utilized a significant amount of secondary data: press releases, annual reports, online news and interviews.