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Using Startup Communication For Opportunity Recognition — An Approach To Identify Future Product Trends

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  • HAUKE SIMON

    (Institute of Business Administration at the Department of Chemistry and Pharmacy of the University of Münster, Germany)

  • JENS LEKER

    (Institute of Business Administration at the Department of Chemistry and Pharmacy of the University of Münster, Germany)

Abstract

A company’s ability to recognise early-stage opportunities and to understand the dynamics of emerging markets determines the success or failure of new products. Particularly the emergence of new information technology and social media networks provide ample opportunities to leverage a massive amount of data for managerial purposes. However, managers still meet using social media with skepticism and it is not fully understood how to make use of this information for new product development. We introduce a new method on how to use large-scale internet data as a complement to traditional approaches (patent or publication analysis and surveys) to overcome their shortcomings in terms of speed, dynamic and expense to conduct. More specifically, we propose that social media communication of startups can give valuable indications about future product trends especially in rapidly developing fields. Our approach measures the awareness of startups — and their products — as the increase of the communication about the startup on Twitter. Startup communication is a particularly well-suited indicator because startups develop new-to-the-world products or are in the development process. We illustrate our approach by analysing the communication of 545 startups. On a holistic level we determine industry trends. Fintech is among the topics that increase significantly in relevance. We determine more specific categories within the industries by applying cosine-similarity metrics and hierarchical cluster analysis. Subsequently we determine NPD relevant trends by the increase of retweets within these categories. The growing customer awareness of these clusters shows newly evolving customer needs. Incumbents may use this information to adjust to their current portfolio or to find collaboration partners to best meet upcoming challenges and opportunities. We think that the approach can be transferred to a multitude of fields, helping with the analysis of emerging fields and with early stage opportunity recognition.

Suggested Citation

  • Hauke Simon & Jens Leker, 2016. "Using Startup Communication For Opportunity Recognition — An Approach To Identify Future Product Trends," International Journal of Innovation Management (ijim), World Scientific Publishing Co. Pte. Ltd., vol. 20(08), pages 1-22, December.
    • Handle: RePEc:wsi:ijimxx:v:20:y:2016:i:08:n:s1363919616400168
    DOI: 10.1142/S1363919616400168
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    2. Geissinger, Andrea & Laurell, Christofer & Öberg, Christina & Sandström, Christian, 2023. "Social media analytics for innovation management research: A systematic literature review and future research agenda," Technovation, Elsevier, vol. 123(C).
    3. Leonid Gokhberg & Ilya Kuzminov & Pavel Bakhtin & Elena Tochilina & Alexander Chulok & Anton Timofeev & Alina Lavrinenko, 2017. "Big-Data-Augmented Approach to Emerging Technologies Identification: Case of Agriculture and Food Sector," HSE Working papers WP BRP 76/STI/2017, National Research University Higher School of Economics.
    4. Martin P. Allmendinger & Elisabeth S. C. Berger, 2019. "Selecting Corporate Firms For Collaborative Innovation: Entrepreneurial Decision Making In Asymmetric Partnerships," International Journal of Innovation Management (ijim), World Scientific Publishing Co. Pte. Ltd., vol. 24(01), pages 1-34, January.

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