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Control in Software Project Portfolios: A Complex Adaptive Systems Approach

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Agile Methods. Large-Scale Development, Refactoring, Testing, and Estimation (XP 2014)

Part of the book series: Lecture Notes in Business Information Processing ((LNBIP,volume 199))

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Abstract

Effective project portfolio management (PPM) can both help reverse the prevailing trend of software failure and act as a key driver of business value. Despite the importance of PPM and its success in other disciplines such as finance and new product development, it has not been studied widely in information systems with little research examining PPM in an agile context. This study proposes to address this gap by using complex adaptive systems theory as a lens to study the enactment and effectiveness of four known modes of control (behavior, outcome, clan and self) in agile software project portfolios. It proposes an interpretivist approach using exploratory case studies to investigate portfolio control in its natural context. This study will contribute to the advancement of control theory and provide new insights for theory and practice by integrating the study of PPM and control in an agile environment.

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Authors and Affiliations

  1. Discipline of Business Information Systems, National University of Ireland, Galway

    Roger Sweetman, Orla O’Dwyer & Kieran Conboy

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  1. Roger Sweetman
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  2. Orla O’Dwyer
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  3. Kieran Conboy
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Editors and Affiliations

  1. SINTEF, Trondheim, Norway

    Torgeir Dingsøyr  & Nils Brede Moe  & 

  2. University of Cagliari, Cagliari, Italy

    Roberto Tonelli

  3. Brunel University London, Uxbridge, UK

    Steve Counsell

  4. Free University of Bozen-Bolzano, Bolzano, Italy

    Cigdem Gencel

  5. Blekinge Institute of Technology, Karlskrona, Sweden

    Kai Petersen

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Sweetman, R., O’Dwyer, O., Conboy, K. (2014). Control in Software Project Portfolios: A Complex Adaptive Systems Approach. In: Dingsøyr, T., Moe, N.B., Tonelli, R., Counsell, S., Gencel, C., Petersen, K. (eds) Agile Methods. Large-Scale Development, Refactoring, Testing, and Estimation. XP 2014. Lecture Notes in Business Information Processing, vol 199. Springer, Cham. https://doi.org/10.1007/978-3-319-14358-3_9

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  • DOI: https://doi.org/10.1007/978-3-319-14358-3_9

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-14357-6

  • Online ISBN: 978-3-319-14358-3

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