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Reduction of Market and Technology Uncertainty during the Front End of New Product Development

Research output: Book/ReportDoctoral thesisMonograph

Details

Original languageEnglish
PublisherTampere University
Number of pages200
Volume243
ISBN (Electronic)978-952-03-1537-5
ISBN (Print)978-952-03-1536-8
Publication statusPublished - 8 May 2020
Publication typeG4 Doctoral dissertation (monograph)

Publication series

NameTampere University Dissertations
Volume243
ISSN (Print)2489-9860
ISSN (Electronic)2490-0028

Abstract

The management of the fuzzy front-end (FFE) phase of innovation is pivotal to the underlying success of new product development (NPD) initiatives. A crucial challenge that research and development (R&D) teams face at this early, and often chaotic, FFE phase is dealing with market and technology uncertainty related to product and technology innovation under development. A remarkable cause of new product defects and serious delays is a failure to adequately define the product concept, target market, positioning, and requirements before beginning product development. Successful NPD teams are capable of performing uncertainty reduction during the FFE phase, and the more the innovation team reduces uncertainty with regard to user needs and technology, the higher the possibilities of producing a commercially successful product. This study employs the technology acceptance model 3 (TAM3) as the voice of the customer (VoC) to a robotics FFE project, with the aim of understanding the extent to which TAM3 can be applied beyond its typical information technology (IT) product development (PD) phase setting to reduce market- and technology-based uncertainty during the FFE phase. The market is divided into early and late adopters of technology based on the diffusion of innovations theory. Further, the applicability of TAM3 is evaluated for both market segments. The multimethod research setup is implemented in two phases. In Phase 1, a quantitative study is conducted in which 121 test users evaluated a technology prototype and participated in a survey based on TAM3 theoretical constructs. Survey data is analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) technique. In Phase 2, the technology acceptance data collected from the early and late market segments was tested by a robotics R&D team to evaluate the capability of TAM3 to reduce market and technology uncertainty in the FFE phase. The findings suggest that there are significant differences in how the TAM3 performs in the robotics FFE phase compared to earlier findings mostly done in an IT PD setting. A few of the inner and outer constructs of TAM3 perform fundamentally differently in FFE. This research also reveals differences between the early and late market segments based on the TAM3 model. In addition, the results offer insight into how the TAM3-based VoC can reduce market and technology uncertainty during the important and challenging FFE phase.

Field of science, Statistics Finland