Research on agile software development (ASD) has so far primarily focused on processes and tools. Recently, researchers have started to investigate the social dimensions of ASD. The authors contribute to this and examine the largely invisible psychological factor of age stereotypes as one important social dimension of ASD. Driven by demographic change, employees of different age groups will need to work closely together in ASD in the future. However, age stereotypes can hinder many aspects of communication, cooperation and coordination in these self-managed teams. The purpose of this paper is to identify and differentiate age stereotypes in ASD.
A quantitative survey at the individual level was conducted with 464 employees in two software development companies. The authors developed an age stereotype model for ASD and developed two scales to measure performance expectations (PEs) in ASD.
Employees in ASD show a bias in general PEs, favoring middle-aged employees over both younger and older employees. The perceived PE of a developer decreases over working life. Furthermore, the data show a complex interplay of age and job role in both the research participants and the group evaluated. Younger developers hold the strongest negative age stereotypes and older developers suffer most from stereotypes.
Management should enact formal or informal measures against stereotypes when an older or younger employee joins a team of members of other age groups, or when a new team is formed. In addition, the authors propose human resources to create permeable career paths.
The study extends the stereotype content model by adding additional age groups and including job role as a moderating variable. It identifies obstacles in daily employee interactions in agile development, and proposes ways of incorporating invisible psychological aspects in ASD-specific theories.
Schloegel, U., Stegmann, S., Maedche, A. and van Dick, R. (2018), "Age stereotypes in agile software development – an empirical study of performance expectations", Information Technology & People, Vol. 31 No. 1, pp. 41-62. https://doi.org/10.1108/ITP-07-2015-0186
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