Author List: Dean, Douglas L.; Lowry, Paul Benjamin;
MIS Quarterly, 2011, Volume 35, Issue 1, Page 1-A8.
How many articles in highly rated journals do Information Systems research faculty publish to earn tenure? Which journals are highly rated outlets? Tenure candidates, promotion and tenure committees, and those who are asked to write external letters are frequently called upon to answer such questions. When Dennis et al. (2006) examined all IS Ph.D. graduates entering academic careers, few faculty had published enough articles in 20 "elite" journals in six years to meet tenure research expectations at research-intensive schools. Our study builds on the dialog started by Dennis et al. In our study, we counted the number of journal articles at the point of tenure for faculty who earned tenure within five to seven years after their Ph.D. graduation date. We also examined the effect of acknowledging different sets of journals as highly rated on the publication rates of faculty who earned tenure. Specifically, we examined the effects of expanding on Dennis et al. by including MIS Quarterly, Information Systems Research, Journal of Management Information Systems, Journal of the AIS, Information Systems Journal, European Journal of Information Systems, Journal of Information Technology, and Journal of Strategic Information Systems in the journal basket. We also looked at the effect of acknowledging highly rated non-IS business journals and highly rated computer science and engineering journals. Finally, we present journal publication benchmarks based on these findings for different types of research institutions.
Keywords: Tenure standards; publication standards; publication benchmarks; faculty productivity; scientometrics; Carnegie classification
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#169 0.747 research journals journal information systems articles academic published business mis faculty discipline analysis publication management tenure authors publications disciplines years
#145 0.119 differences analysis different similar study findings based significant highly groups popular samples comparison similarities non-is variety reveals imitation versus suggests