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Define Measure Visualize: Using Network Analysis in Place Branding

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Define Measure Visualize: Using Network Analysis in Place Branding

  1. 1. Define-Measure-Visualize Using Network Analysis in Place Branding H. Efe SEVIN American University, School of International Service International Place Branding Conference – Special Edition January 20 th , 2012 Utrecht, NL
  2. 2. The “Curse” <ul><li>If all I have is a hammer…. </li></ul><ul><li>‘ Disciplined’ scholars </li></ul><ul><li>Talking about roots of place branding </li></ul>
  3. 3. DMV in a nutshell
  4. 4. Anholt-GfK Nation Brands Index <ul><li>NBI Hexagon </li></ul><ul><li>Sum of “people’s perceptions of a country and its people across six areas of national assets, characteristics and competence” </li></ul><ul><ul><li>Partial definition </li></ul></ul><ul><ul><li>Communicative aspects </li></ul></ul><ul><li>Promoting distinct characteristics </li></ul><ul><li>Online survey </li></ul><ul><li>Ranking </li></ul>
  5. 5. FutureBrand Country Brand Index <ul><li>A country’s narrative and assets for internal and external audiences </li></ul><ul><li>Five areas: </li></ul><ul><ul><li>Value system </li></ul></ul><ul><ul><li>Quality of life </li></ul></ul><ul><ul><li>Good for business </li></ul></ul><ul><ul><li>Heritage </li></ul></ul><ul><ul><li>Culture and tourism </li></ul></ul><ul><li>Survey, focus group, crowdsourcing </li></ul><ul><li>Market-driven reporting </li></ul>
  6. 6. East-West Communications Nation Brands Perception Index <ul><li>Media-coverage </li></ul><ul><li>Volume / sentiment </li></ul><ul><li>Mass media – public opinion link </li></ul><ul><li>Categorization </li></ul>
  7. 7. 2011 ‘Top’ 10 NBI CBI NBPI 1 USA Canada Malaysia 2 Germany Switzerland South Korea 3 UK New Zealand France 4 France Japan Canada 5 Japan Australia Australia 6 Canada United States Thailand 7 Italy Sweden New Zealand 8 Australia Finland Brazil 9 Switzerland France UK 10 Sweden Italy Ireland
  8. 8. Literature <ul><li>Import (Kaplan et al, 2010) </li></ul><ul><ul><li>Brand personality </li></ul></ul><ul><li>Adapt (Insch and Florek, 2008) </li></ul><ul><ul><li>Customer satisfaction </li></ul></ul><ul><li>Devise (Hankinson, 2004b; Zenker et al, 2010) </li></ul><ul><ul><li>Relational network model </li></ul></ul><ul><ul><li>Complexity and diversity </li></ul></ul>
  9. 9. Story of measurement <ul><li>Issues with ‘ranking’ </li></ul><ul><li>‘ Incompatible’ requirements </li></ul><ul><li>Ambiguous terms </li></ul><ul><li>So, what do we need? </li></ul>
  10. 10. A Place Brand
  11. 11. DMV <ul><li>Define: Subjective network of associations </li></ul><ul><li>Measure: Who is talking to whom? What are they saying? </li></ul><ul><li>Visualize: What are the main concepts? Who are the main nodes? </li></ul>
  12. 12. Two examples <ul><li>Boston and New York </li></ul><ul><li>Tweets collected between December 3rd and December 24th, 2011 </li></ul><ul><ul><li>Content </li></ul></ul><ul><ul><li>Retweet networks </li></ul></ul><ul><li>Node attributes and network structure </li></ul>
  13. 13. Boston
  14. 14. NYC – High Level
  15. 15. NYC – Low Level
  16. 16. Boston - SNA
  17. 17. Findings <ul><li>No comparison between Boston and NYC (High Level) </li></ul><ul><ul><li>JB vs. Sports </li></ul></ul><ul><li>Ranking and comparison </li></ul><ul><ul><li>Boston>Vacation>Sports>Tickets </li></ul></ul><ul><ul><li>NYC>Video>JB </li></ul></ul><ul><li>Short term impacts of events </li></ul><ul><li>Low density </li></ul><ul><li>Significant ‘celebrity’ nodes </li></ul>
  18. 18. An Ideal Case <ul><li>Data triangulation </li></ul><ul><li>Data cleaning </li></ul><ul><li>Sub-networks </li></ul><ul><li>Measurement vs. Evaluation </li></ul><ul><li>MTML </li></ul>
  19. 19. Thank you! H. Efe SEVIN American University, School of International Service http://www.efesevin.com/ http://efesevin.wordpress.com/ [email_address]
  20. 20. Boston - SNA

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