LANZAMIENTO DEL MODELO EAD EN CARRIER PLANTA A Formación de Equipos

This study seeks to shed light on the IT encountering process, as defined earlier in this document. This means that by means of the empirical study, I set off to explore the various ways in which small business owners encounter events indicating IT as a plausible course of action, interpret these events and respond to them. Because people’s interpretation of events is central to the study, appropriate methods need to give voice to the individuals facing these events in order to learn from them, rather than imposing the researcher’s voice from the start. In general, qualitative methods lend themselves better to questions of meaning, and are known to generate rich data with which to support the development of theories concerned why and how questions (Eisenhardt 1989; Strauss and Corbin 1998; Yin 2009).

A wide diversity of qualitative methods and sources exist. Most common sources of qualitative data include interviews, participant observation, and archival data. The last two were not feasible in my research context. Pollock and Williams (2007) have noted that IT procurement decisions are infrequent, short-lived and ad-hoc. Low frequency and

short duration, coupled with the relative laconism and isolation within which some of these cognitive processes might occur, made participant observation extremely impractical and of potentially limited value. The use of participant observation could even compromise the quality of gathered data if behaviours were affected by the sole presence of the researcher. Further, formal documentation around these events is very limited in small businesses, which means that archival data are virtually non-existent. Interviews, on the other hand, could yield abundant data specifically concerned with the cues, interpretations and responses around the topic of interest.

But a design based solely on interviews would not be free of methodological concerns. In this setting, a first concern is that collected data be distorted by cognitive biases

associated with retrospective data collection. Retrospective self-reports are vulnerable to recall difficulties, as well as rationalization and hindsight biases (Huber and Power 1985). This observation has been particularly made in contexts that are relevant to this work, such as adoption of innovations (Rogers 2003), entrepreneurial action (Davidsson and Honig 2003), and social networks use (Borgatti and Cross 2003). To partly guard against those biases, the interview questions were centred on concrete events, following critical incident technique guidelines (Chell 2004; Flanagan 1954). Asking participants to report on specific events, rather than asking them broad questions that force them to make composite “complex inferences or judgements about themselves based on many past events” (Judd et al. 1991 p. 214), should diminish the cognitive effort required to answer questions, and should enhance recollection of specific details (Chell 2004). Likewise, to abate the effects of memory failures on the data, I sought to capture a combination of past events (happening during the three years preceding the interview) with events taking

place at the time of data collection. Although I cannot ignore the risk of those biases being present in the data, I did notice that asking repeated questions around the same event helped some participants remember some details more precisely. Further, memory failures are most problematic in variance studies, especially in experimental and survey research, when differences in recall across time or among subjects may artificially distort the magnitude of statistical effects (Raphael 1987). Memory failures are still a concern for this study, but a less severe one.

A second concern is that using interviews as a single data source negatively impacts the quality of the results. The argument against using a single data source is that doing so cannot render the rigour reassurance that comes from triangulating across various types of data sources and obtaining convergent findings (Jick 1979). However, a similar reassurance can be obtained from having multiple informants, comparing their accounts and arriving at convergence of findings in this way, a variant known in the literature as source triangulation (Denzin 1970). That was the path I followed in this study.

In the context of small businesses, opting for a multiple-informant design is analogous to having a multiple case study design (Yin 2009), since each informant can arguably speak for only one company and most companies will not have more than one knowledgeable informant, usually the business owner. In these designs, it is recommended that

researchers follow a sampling strategy based on theoretical replication, and attempt a number of four to ten cases (Eisenhardt 1989; Yin 2009). Yet, theoretical sampling strategies presuppose a level of knowledge about the sites which is not necessarily achievable ex-ante when the research sites are small businesses. Specifically, seemingly relevant sampling criteria for this study, such as individual IT knowledge background or

criticality of the event, cannot be known before the interview. I decided to use a larger, diverse sample in terms of owners’ demographics and business characteristics, in order to facilitate replication and extension via comparative analysis, in spite of the limited knowledge I had of the cases at the moment they were included in the sample. A larger sample could also strengthen source triangulation, as explained above.

Finally, the choice of a longitudinal design is explained by my interest in looking into the processual aspects of IT encountering, which demands empirical attention to the

unfolding of events over time (Langley 1999; Langley et al. 2013; Newman and Robey 1992).