Can the field of MIS be disciplined?
Communications of the ACM
Empirical research in information systems: the practice of relevance
MIS Quarterly - Special issue on intensive research in information systems
Rigor vs. relevance revisited: response to Benbasat and Zmud
MIS Quarterly - Special issue on intensive research in information systems
Empirical research in information systems: on the relevance of practice in thinking of IS research
MIS Quarterly - Special issue on intensive research in information systems
Rigor and relevance in MIS research: beyond the approach of positivism alone
MIS Quarterly - Special issue on intensive research in information systems
The social and political context of doing relevant research
MIS Quarterly - Special issue on Intensive research in information systems: using qualitative, interpretive, and case methods to study information technology—third installment
An IS research relevancy manifesto
Communications of the AIS
On Becoming a Personal Scientist: Interactive Computer Elicitation of Personal Models of the World
On Becoming a Personal Scientist: Interactive Computer Elicitation of Personal Models of the World
Using Repertory Grids to Conduct Cross-Cultural Information Systems Research
Information Systems Research
Disciplining information systems: truth and its regimes
European Journal of Information Systems
Repertory grid: investigating personal constructs of novice programmers
Proceedings of the 11th Koli Calling International Conference on Computing Education Research
Journal of the American Society for Information Science and Technology
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Empirical research in any discipline is heavily dependent on the quality of data collected and the meaning which subsequent analysis reveals. This obvious statement underlies the debates on rigor, and less directly on relevance, which recur periodically in the journals devoted to Information Systems. Empirical research in Information Systems (IS) is largely based upon data collected by means of questionnaires, interviews, documentation and observation. Inexperienced researchers find questionnaires and interviews particularly attractive as a data gathering methodology as they can draw on their own experience of having to fill in forms and being interviewed. However, as many researchers have discovered, it is not as simple as it appears at first to draft a good questionnaire. Also, respondents are notoriously unenthusiastic when it comes to filling out questionnaires. The result is that their answers are very often superficial which impacts negatively on the quality of the research. Interviewing provides richer data and hence overcomes some of the problems of questionnaires, but still leaves the researcher with few guidelines. This paper explores the potential of a technique called the Repertory Grid as an alternative means of gathering meaningful empirical data. It traces it origins, describes how it works, analyses the strengths and weaknesses and looks at instances where it has already been used in IS research. It then describes the authors' experience in the use of this technique and concludes that it well worth considering by inexperienced and experienced IS researchers alike. Although the technique may initially appear to be positivist this is not the case. It can be used for both ideographic and nomothetic research. It uncovers perceptions, assumptions, and concepts from the research participants while striving to minimise the degree to which the researcher influences the outcomes.