Experiencia y emociones, juntas de la mano

The purpose of this section is to outline the common approaches to research on IT and

competitive advantage and to discuss the methodological choice for this research. Academics from a wide variety of research backgrounds have investigated IT and its contribution to and impact on competitive advantage (Brynjolfsson 2003; Piccoli & Ives 2005; Wade & Hulland 2004). Hence, a diversity of research perspectives exists, with different approaches, meta-theoretic assumptions and paradigms on the research topic. The broad field of IT and competitive advantage research has been approached from a range of disciplines, including management science, computer science, information systems, organisation science, behavioural science and economics. This blend of research fields has resulted in a mix of research methodologies and approaches in IT and competitive advantage research.

5.3.1. Overview of data collection methods

It is not possible to determine the appropriate methodology par excellence. Methodological issues need to be resolved within a particular research setting. Most research methods can be utilised in both positivistic and interpretivistic research designs, although some are more appropriate to one research paradigm than the other. In the positivistic research paradigm, the four most common methods are the cross-sectional study, the experimental study, the longitudinal study and the survey (Collis et al. 2003). The experimental study concept involves the manipulation, via an experiment, of an independent variable and observation of the impact on the dependent variable. Experiments can be conducted in either a laboratory or the real world in a systematic way, which allow to draw conclusions (Lewis-Beck, Bryman & Liao 2004).

This research method poses several limitations for the purposes of this PhD research. Chief among them are the fact that it would be difficult to gain access to a huge number of companies to manipulate the independent variables, and it would not be possible to eliminate all of the other effects that might influence the dependent variable. Therefore, the experiment is not a suitable method for this research.

The main purpose of a cross-sectional study is to obtain information on variables within the same time frame (Collis et al. 2003; De Vaus 2001) (e.g. comparing success factors of companies in different countries). Often descriptive and exploratory studies are cross-sectional.

The main limitations of cross-sectional studies can be found in their inherent constriction to investigate phenomena at a specific point of time. This restricts the ability of cross-sectional studies to investigate causal processes that occur over time (Babbie 2007).

The longitudinal study, in contrast, is designed to look at variables in the same context over a period of time (Collis et al. 2003; De Vaus 2001) (e.g. investigating the change of success factors of companies over a 10-year period). Many in-depth interviews and field research projects involving direct observation are naturally longitudinal. While the longitudinal study is often the best way to study changes over time, it has its limitations also. Longitudinal studies can be more difficult in the case of quantitative studies such as large-scale surveys (Babbie

2007), especially anonymous surveys, as it is difficult to draw the same sample again for subsequent studies.

This current PhD research aims to determine the nature of the relationships among different constructs in the context of Australian medium- and large-sized companies within a given time frame. These constructs have been identified and operationalized through an extensive literature review of previous research. An appropriate method to quantify these measures and test the hypotheses is either the survey or structured interviews. The written survey can be subdivided into the subcategories of the traditional paper survey and the internet survey. If not further specified written surveys refer to both the paper survey and the internet survey. The section below discusses the survey (paper- and web-based) and structured interview as possible research methods for this research and argues for the web-based survey as the most appropriate method of data collection for this study.

5.3.2. Possible methods of inquiry for data collection

Three methods of quantitative data collection could be useful for this study: the written survey, the web-based survey and the interview. A scientific survey should be prepared, conducted and protocoled in a systematic way, so that it is clear in which environment and under what circumstances the data were collected so that the results can be reproduced (Collis et al. 2003).

The three different methods of data collection (interview, written and internet survey) each have advantages and disadvantages and the following points where taken into account in considering which to choose. Interviews, written surveys (paper- and internet-based) vary in a number of ways (Kumar 2005).

First, the suitability of questions depends on the mode of inquiry. In interviews participants can make enquiries if they do not understand the question, whereas in written surveys the questions have to be worded carefully because the participants do not have this opportunity (Blaikie 2000;

Neuman 2006). Participants of written surveys have the chance to stop the survey at any point and ask their colleagues for advice if they cannot answer the question themselves directly (Kumar 2005).

Second, the methods of inquiry vary in the ways in which filters can be utilised. Through filters the survey procedure can be controlled, especially the order and selection of questions (Sarantakos 2005). Filters can be utilised in all forms of a survey, the main difference in their usage being the complexity and amount of useable filters (Collis et al. 2003). In paper surveys, in order not to overstrain the participants, the amount and complexity of filters is limited. Careful design of internet surveys can handle a number of filters, without the participant even noticing.

In interviews, specially trained interviewers can handle a higher complexity and number of

filters. A limitation can arise with paid interviewers, in so far as they might choose inappropriate filters to finish the interview earlier (Sarantakos 2005).

Third, in relation to the above mentioned problems with inquiries and filters, the layout of written surveys must be well designed so that participants can understand the filters, questions and answer possibilities (Neuman 2006). Hence, useability issues will require more effort and time in written surveys (especially internet surveys).

Fourth, especially with regard to data about companies and managers themselves, anonymity is a concern. Although anonymity and nondisclosure can be assured in all methods, it can be realised either by using two envelopes or by conducting web surveys. Respondents might be reluctant to answer sensitive questions asked by an interviewer (Babbie 2007).

Fifth, interviews generate the issue of interviewer effects (Denzin & Lincoln 2000). Interviewer effects can be both positive and negative in nature. Negatively the participant can be misguided and/or misunderstood by the interviewer. Positively, the interviewer can ensure that all questions are answered, which is especially important with long questionnaires and in cases where the participant has no personal interest in participating in the survey (Sarantakos 2005).

Sixth, both methods vary in convenience for the participants and the researchers. In the case of interviews the participant must agree to an appointment time. Written surveys, in contrast, can be filled out, stopped and restarted at the respondent’s leisure (Neuman 2006). Written surveys in addition are not geographically based; no travel is required to meet all participants (Neuman 2006).

Seventh, recent studies investigating the difference in data collection methods between computerised and written surveys have discovered that both survey methods yielded similar outcomes in scale, internal reliability and descriptive statistics, but that the computerised survey was significantly better with regards to completeness of the questions (Wu & Newfield 2007).

Last, as data from both interviews and paper surveys have to be entered into a computer before they can be analysed via statistical programs, data entry can cause errors. Internet surveys can limit that problem, as the data is automatically transferred into a data file.

In summary, all methods of quantitative data collection—the interview, the paper-based and internet survey—have their advantages and disadvantages (Kumar 2005). The purpose of this current research is to measure various constructs, from the IT and business side. The participants can be defined as senior managers (CEOs, CIOs, and senior IT managers). This group normally operates under time pressures and as data analysis requires a large number of answers from across Australia, it would be hard to arrange interview appointments with a

sufficiently large number of participants. Therefore, the method of written surveys is more time efficient, convenient and easier to implement when using senior management participants.

Furthermore, since the questions relate to a wide spectrum of business and IT variables, it is beneficial that participants of written surveys have the chance to stop and ask their colleagues, specialists or subordinates for advice on the questions (Babbie 2007). Furthermore, as the survey includes sensitive questions about companies’ capabilities, confidentiality and nondisclosure issues, and the written survey method again seems most appropriate. Last, to choose between the two different options for written surveys, the paper-based or the internet-based survey, the claims of an expected higher rate of completion of the survey and for the elimination of the possibility of data entry errors speak in favour of an internet-based survey.

Therefore, considering all the points discussed above, a written internet survey is the appropriate data collection method for this research.