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How to evaluate innovative ideas and concepts at the front-end?

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  • Dziallas, Marisa

Abstract

Despite growing research on front-end indicators, the understanding of the evaluation of innovative ideas in the early stages of the innovation process within a company remains limited. A reason for this might be a lack of data on front-end evaluation. This paper investigates existing theoretical and new indicators in terms of their importance and practical applicability in the industry. This study follows a qualitative empirical research design, using a new dataset based on 32 interviews with experts conducted in six international automotive original equipment manufacturers (OEMs). To improve generalization, the perspectives of volume, premium, and entry-level manufacturers are included. The four most relevant indicators are high customer relevance, strategic fit, high communication potential, and vision potential. The data suggest the need for more flexible and faster front-end evaluation approaches. The findings enhance the quality of innovation decisions by presenting novel insights into innovation evaluation at the front end.

Suggested Citation

  • Dziallas, Marisa, 2020. "How to evaluate innovative ideas and concepts at the front-end?," Journal of Business Research, Elsevier, vol. 110(C), pages 502-518.
    • Handle: RePEc:eee:jbrese:v:110:y:2020:i:c:p:502-518
    DOI: 10.1016/j.jbusres.2018.05.008
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    4. Hong, Suckwon & Kim, Juram & Woo, Han-Gyun & Kim, Young-Choon & Lee, Changyong, 2022. "Screening ideas in the early stages of technology development: A word2vec and convolutional neural network approach," Technovation, Elsevier, vol. 112(C).
    5. Mai, Nhat Chi, 2021. "A Comprehensive Model for Idea Evaluation at Early-Stage Level (Pre-Seed)," OSF Preprints axngj, Center for Open Science.
    6. Svetlana Klessova & Sebastian Engell & Catherine Thomas, 2022. "Assessment of the advancement of market-upstream innovations and of the performance of research and innovation projects," Post-Print hal-03636260, HAL.
    7. Yuan-Wei Du & Yu-Kun Shan, 2021. "A Dynamic Intelligent Recommendation Method Based on the Analytical ER Rule for Evaluating Product Ideas in Large-Scale Group Decision-Making," Group Decision and Negotiation, Springer, vol. 30(6), pages 1373-1393, December.
    8. Jorge Isaías Martínez-Lobatón & Jean Pierre Seclen-Luna, 2023. "Assessing the New Product Development Process activities in Peruvian medium-sized manufacturing companies," Estudios Gerenciales, Universidad Icesi, vol. 39(166), pages 2-10, March.
    9. Gama, Fábio & Sjödin, David & Parida, Vinit & Frishammar, Johan & Wincent, Joakim, 2022. "Exploratory and exploitative capability paths for innovation: A contingency framework for harnessing fuzziness in the front end," Technovation, Elsevier, vol. 113(C).
    10. Cillo, Paola & Priem, Richard L. & Verona, Gianmario & Zanella, Paola, 2021. "Consumer-CEO interaction as catalyst for business model innovation in established firms," Journal of Business Research, Elsevier, vol. 131(C), pages 241-253.

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