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Creative Distraction: Lack of Collective Learning in Adapting to Online Advertising in Oslo, Norway

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  • Markus Bugge

Abstract

The advertising industry is often seen as adaptable and flexible, and its work organization and diverse project ecologies are assumed to nurture creativity, learning and innovation. The advertising industry in Oslo is currently going through a restructuring process of adapting to the Internet as an emerging media channel for marketing, but struggles to benefit from collective learning. The established advertising agencies have been reluctant regarding the new opportunities in Internet-based advertising, which has allowed for a set of smaller and specialized web agencies to emerge, and who now possess the best skills within interactive advertising. The paper argues that there are two parallel epistemic communities in the localized advertising industry. It is shown that the advertising industry seems to have been caught in a path-dependent technological trajectory, and that in order for collective learning to unfold geographical proximity needs to be supplemented by cultural and epistemic proximity and compatibility.

Suggested Citation

  • Markus Bugge, 2011. "Creative Distraction: Lack of Collective Learning in Adapting to Online Advertising in Oslo, Norway," Industry and Innovation, Taylor & Francis Journals, vol. 18(2), pages 227-248.
    • Handle: RePEc:taf:indinn:v:18:y:2011:i:2:p:227-248
    DOI: 10.1080/13662716.2011.541106
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    Citations

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    Cited by:

    1. Brian J Hracs & Doreen Jakob & Atle Hauge, 2013. "Standing out in the Crowd: The Rise of Exclusivity-Based Strategies to Compete in the Contemporary Marketplace for Music and Fashion," Environment and Planning A, , vol. 45(5), pages 1144-1161, May.
    2. Wu, Yuanyuan & Wu, Shikui, 2016. "Managing ambidexterity in creative industries: A survey," Journal of Business Research, Elsevier, vol. 69(7), pages 2388-2396.
    3. Øiestad, Sara & Bugge, Markus M., 2014. "Digitisation of publishing: Exploration based on existing business models," Technological Forecasting and Social Change, Elsevier, vol. 83(C), pages 54-65.

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