Agile approach as an answer to internal uncertainty: a case study in large-scale manufacturing

Abdulkadir Özgen and Mehmet Gençer

International Journal of Manufacturing Technology and Management, 2023, vol. 37, issue 5/6, 563-579

Abstract: The success of agile product development in the software industry has attracted the attention of new product development (NPD) community. Agile approach has the potential to overcome the uncertainty that dominates today's business conditions. However, there is little research regarding the performance of agile practices, most of which were developed in the software industry, in other contexts. Through a case study methodology, we explore how agile practices address organisational uncertainty in a large-scale manufacturing firm. The study, based on semi-structured interviews, covers two NPD projects with a total of 12 sub-teams. Our results indicate that in a large organisation, internal sources of NPD uncertainty dominate external sources. The three factors in organisational uncertainties are interdependency, team volatility and distributed teams. Furthermore, we develop a model to explain how various agile practices can provide the NPD teams with capabilities to mitigate these organisational uncertainties.

Keywords: agile practices; new product development; uncertainty; large-scale organisation; organisational change. (search for similar items in EconPapers)
Date: 2023
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.inderscience.com/link.php?id=133680 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ids:ijmtma:v:37:y:2023:i:5/6:p:563-579

Access Statistics for this article

More articles in International Journal of Manufacturing Technology and Management from Inderscience Enterprises Ltd
Bibliographic data for series maintained by Sarah Parker ().