Are Information Systems People Different? An Investigation of How They Are and Should Be Managed.

Author List: Ferratt, Thomas W.; Short, Larry E.;
MIS Quarterly, 1988, Volume 12, Issue 3, Page 427-443.
This study, based on seven different samples involving 1005 employees, examines whether IS and non-IS people are or should be managed differently. How IS and non-IS people are managed is measured by three sets of managerial activities: (1) enriching the job, (2) attending to interpersonal relations, involving the employee, and reinforcing work behavior, and (3) attending to production and targeting work behavior. Two research questions are asked: (1) Do work-unit environments differ for IS and non-IS people? (2) Is the relationship of work-unit environment to productivity different for IS and non-IS people? The findings of this study support the conclusion that IS and non-IS employees at the same occupational level are not and should not be managed differently.
Keywords: Management; productivity
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#145 0.290 differences analysis different similar study findings based significant highly groups popular samples comparison similarities non-is variety reveals imitation versus suggests
#146 0.193 work people workers environment monitoring performance organizations needs physical useful number personal balance perceptions create computer-based technological technologies investigation achievement
#25 0.183 relationships relationship relational information interfirm level exchange relations perspective model paper interpersonal expertise theory study effects literature role social identify
#298 0.121 job employees satisfaction work role turnover employee organizations organizational information ambiguity characteristics personnel stress professionals conflict organization intention variables systems
#82 0.078 case study studies paper use research analysis interpretive identify qualitative approach understanding critical development managerial elements exploring points positivist presents
#148 0.067 productivity information technology data production investment output investments impact returns using labor value research results evidence spillovers industries analysis gains