Technical Note-Waterfall and Agile Product Development Approaches: Disjunctive Stochastic Programming Formulations
成果类型:
Article
署名作者:
Kettunen, Janne; Lejeune, Miguel A.
署名单位:
George Washington University
刊物名称:
OPERATIONS RESEARCH
ISSN/ISSBN:
0030-364X
DOI:
10.1287/opre.2019.1977
发表日期:
2020
页码:
1356-1363
关键词:
PRODUCT DEVELOPMENT
waterfall
Agile
disjunctive chance constraint
Stochastic Programming
摘要:
The periodic selection of new product development (NPD) projects is a crucial operational decision. The main goals of start-up companies in NPD are to attain a reliable return level and deliver this return level fast. Achieving these goals is complicated because of uncertainties in projects' returns and durations. We develop new disjunctive stochastic programming models that capture the above-mentioned NPD goals. The first stochastic model is static, representing the traditional waterfall product development process, whereas the second one is dynamic, representing the agile product development process. We design a reformulation method and a decomposition algorithm to solve a problem encountered by a U.S.-based software start-up company. Our results indicate counter-intuitively that high reliability in attaining a targeted return may be achieved by investing in projects with a longer development time and higher risk. Furthermore, we show that if the capability to make dynamic decisions is overlooked while available, the time to attain the targeted return is overestimated.
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