From fun-lovers to institutionalists: uncovering pluralism in IT occupational culture

Abstract

PurposeThe study aims to explore whether there is diversity of occupational culture among IT workers. Prior work conceptualizes IT occupational culture (ITOC) as based around six distinctive values (ASPIRE) but has not explored whether there is variation in ITOC.Design/methodology/approachSurvey data from 496 New Zealand IT workers was used to create factors representing IT occupational values based on the ASPIRE tool. Hierarchical cluster analysis and discriminant analysis were applied to identify distinctive segments of ITOC.FindingsFour ITOC segments were identified: fun-lovers, innovators, independents and institutionalists. These differed in the relative emphasis ascribed to the ITOC values with each segment being distinguished by 1–2 dominant values. Segment membership varied according to level of responsibility and birth country. Institutionalists and innovators had higher concern about organizational and IT issues than fun-lovers and independents. Job satisfaction was lowest among innovators and highest along institutionalists.Research limitations/implicationsThis study challenges the concept of a unified ITOC, suggesting that ITOC is pluralistic. It also theorizes about interactions between ITOC, individual motivation and values and national culture.Practical implicationsManagement needs to be cognizant of the fact that IT occupational culture is not homogeneous and different IT occupational segments require unique management approaches, and that their own values may not match those of others in IT work. By understanding ITOC segments, managers can tailor support, assign tasks appropriately and design teams to optimize synergies and avoid conflict.Originality/valueThis study reveals the existence of ITOC segments and theorizes about the relationship of these to innovation-orientation, job satisfaction, individual motivation, work styles and national culture. The combination of cluster and discriminant analysis is a valuable replicable inductive method that is underrepresented in Information Systems (IS) research.