From fun-lovers to institutionalists: uncovering pluralism in IT occupational culture
研究基于496名新西兰IT工作者的调查数据，通过聚类分析识别出四种IT职业文化类型（玩乐者、创新者、独立者、制度主义者），发现其价值观差异显著，且与责任级别、出生国、工作满意度相关，挑战了IT职业文化同质化的假设。
Purpose The 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/approach Survey 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. Findings Four 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/implications This 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 implications Management 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/value This 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.