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Verwendung von Word of Mouth-Daten zur Identifikation von Asymmetrie im Wettbewerb: Eine textbasierte Analyse am Beispiel deutscher Automobilmarken
[Identification of asymmetric competition by using word of mouth data: A text-based analysis among German automotive brands]

Author

Listed:
  • Tobias Reckmann

    (Universität Hamburg)

Abstract

Zusammenfassung Kundenkommentare im Web 2.0 stellen für Unternehmen aufgrund ihrer Menge sowie Zeitaktualität eine viel versprechende Informationsbasis dar. Entsprechend bestehen verstärkt Bestrebungen, online kommunizierte Kundenerfahrungen zu strukturieren und für die Marketingpraxis nutzbar zu machen. Dieser Beitrag stellt einen neuartigen textbasierten Ansatz vor, der es erlaubt, komplexe Wettbewerbsbeziehungen basierend auf Kundenrezensionen zu visualisieren. Am Beispiel fünf deutscher Automobilmarken lassen sich asymmetrische Wettbewerbsbeziehungen identifizieren, bei denen je nach Referenzmarke der jeweiligen Kundenerfahrung unterschiedliche Wahrnehmungen konkurrierender Marken vorliegen. Durch Offenlegung dieser heterogenen Wahrnehmungsräume von Kunden können in Frage kommende Marken für zukünftiges Wechselverhalten frühzeitig identifiziert und Ressourcen entsprechend allokiert werden.

Suggested Citation

  • Tobias Reckmann, 2017. "Verwendung von Word of Mouth-Daten zur Identifikation von Asymmetrie im Wettbewerb: Eine textbasierte Analyse am Beispiel deutscher Automobilmarken [Identification of asymmetric competition by usin," Schmalenbach Journal of Business Research, Springer, vol. 69(2), pages 173-201, June.
    • Handle: RePEc:spr:sjobre:v:69:y:2017:i:2:d:10.1007_s41471-016-0027-4
    DOI: 10.1007/s41471-016-0027-4
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    References listed on IDEAS

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    1. Nedungadi, Prakash, 1990. "Recall and Consumer Consideration Sets: Influencing Choice without Altering Brand Evaluations," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 17(3), pages 263-276, December.
    2. Gregory S. Carpenter & Lee G. Cooper & Dominique M. Hanssens & David F. Midgley, 1988. "Modeling Asymmetric Competition," Marketing Science, INFORMS, vol. 7(4), pages 393-412.
    3. Wayne S. Desarbo & Kamel Jedidi, 1995. "The Spatial Representation of Heterogeneous Consideration Sets," Marketing Science, INFORMS, vol. 14(3), pages 326-342.
    4. Terry Elrod, 1988. "Choice Map: Inferring a Product-Market Map from Panel Data," Marketing Science, INFORMS, vol. 7(1), pages 21-40.
    5. Kristine de Valck & Roberts V. Kozinets & Andrea C. Wojnicki & Sarah J.S. Wilner, 2010. "Networked Narratives: Understanding Word-of-Mouth Marketing in Online Communities," Post-Print hal-00458424, HAL.
    6. Decker, Reinhold & Trusov, Michael, 2010. "Estimating aggregate consumer preferences from online product reviews," International Journal of Research in Marketing, Elsevier, vol. 27(4), pages 293-307.
    7. Faure, Corinne & Natter, Martin, 2010. "New metrics for evaluating preference maps," International Journal of Research in Marketing, Elsevier, vol. 27(3), pages 261-270.
    8. David Godes & Dina Mayzlin, 2004. "Using Online Conversations to Study Word-of-Mouth Communication," Marketing Science, INFORMS, vol. 23(4), pages 545-560, June.
    9. Wendy W. Moe & David A. Schweidel, 2012. "Online Product Opinions: Incidence, Evaluation, and Evolution," Marketing Science, INFORMS, vol. 31(3), pages 372-386, May.
    10. Dellarocas, Chrysanthos, 2003. "The Digitization of Word-of-mouth: Promise and Challenges of Online Feedback Mechanisms," Working papers 4296-03, Massachusetts Institute of Technology (MIT), Sloan School of Management.
    11. Chrysanthos Dellarocas, 2003. "The Digitization of Word of Mouth: Promise and Challenges of Online Feedback Mechanisms," Management Science, INFORMS, vol. 49(10), pages 1407-1424, October.
    12. Kardes, Frank R, et al, 1993. "Brand Retrieval, Consideration Set Composition, Consumer Choice, and the Pioneering Advantage," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 20(1), pages 62-75, June.
    13. Yubo Chen & Jinhong Xie, 2008. "Online Consumer Review: Word-of-Mouth as a New Element of Marketing Communication Mix," Management Science, INFORMS, vol. 54(3), pages 477-491, March.
    14. Anindya Ghose & Panagiotis G. Ipeirotis & Beibei Li, 2012. "Designing Ranking Systems for Hotels on Travel Search Engines by Mining User-Generated and Crowdsourced Content," Marketing Science, INFORMS, vol. 31(3), pages 493-520, May.
    15. J. Kruskal, 1964. "Multidimensional scaling by optimizing goodness of fit to a nonmetric hypothesis," Psychometrika, Springer;The Psychometric Society, vol. 29(1), pages 1-27, March.
    16. Oded Netzer & Ronen Feldman & Jacob Goldenberg & Moshe Fresko, 2012. "Mine Your Own Business: Market-Structure Surveillance Through Text Mining," Marketing Science, INFORMS, vol. 31(3), pages 521-543, May.
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