Knowledge that Transforms

Recently, there have been calls for research in information systems to be relevant in the eyes of practitioners, not just rigorous in the eyes of researchers.Prescriptions include the following: writing up research in practitioner-friendly ways, investigating topics of interest to practitioners, using managers instead of students as experimental subjects, doing field studies instead of laboratory studies, and other sensible and laudable remedies.These tactics only involve, for the most part, how to do and present research differently.I predict that these tactics, alone, will fail.They comprise a necessary condition, but not a sufficient condition, for relevant research to take place on a significant scale.Research involves more than just the intellectual dimension of working with theory, method, logic, and evidence.Research also involves the social and political context of the researchers.In the academic discipline of information systems, we have (for better or worse) adopted the manner of research that we believe scientists use (not only natural scientists, but also social scientists such as psychologists and economists).A property of such research is that no individual scientist exercises complete free will in choosing his or her theory, methods, and research puzzles, but is constrained by what his or her scientific research community would consider to be the theories, methods, and research puzzles that are worthy of attention.In such research, the starting point for a new investigation is what current theory does not explain or predict adequately (a research puzzle) where the next step is the refinement or improvement of the current theory or method in order that it may explain and predict adequately (a solution to the puzzle).This approach to research is sometimes described as basic research or pure research: the driving force is the development and refinement of theory, not the everyday problems or long-term objectives of individuals, organizations, or society.

This paper reports on a survey of North American IS programs and secondary data assessing the supply and demand of Information Systems (IS) doctorates. The data document a large and growing lack of supply to meet current and future demand. Demographic factors—including the number of university students, their selection of majors, and retirements among IS faculty—favor a probable scenario for continuing strong demand for IS faculty in the longer term. We argue that the severe imbalance will continue if the current state of the economy and businesses’ need for technically-savvy managers continues. Implications and recommendations are presented for ensuring the long-term health of the IS discipline in addressing this imbalance.

Aging information systems are expensive to maintain and most are eventually retired and replaced. But what determines (in the choices made by managers) whether and when a system reaches end-of-life? What shapes managers’ judgements about a system’s remaining life expectancy and do these judgments influence the maintenance effort itself? System maintenance and prospective replacement are examined here in new terms, positing that managers “equilibrate” (balance) their allocation of maintenance effort with their expectations of a system’s remaining life. Drawing from data on 758 systems among 54 organizations, support is found for an exploratory structural equation model in which the relationship between maintenance effort and remaining life expectancy is newly explained. A “portfolio effect,” reflecting a system’s familial complexity, is also found to be directly and positively related to the maintenance effort. A further finding is that a system’s size is directly and positively associated with its remaining life expectancy. Notwithstanding normative research suggesting the contrary, larger systems may tend to be longer-lived than smaller systems. Practically, the suggestion is made that better documented and monitored portfolios, together with regular, periodic performance assessments, can lead to better management of systems’ life cycles.