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Identifying competitors through comparative relation mining of online reviews in the restaurant industry
Linköping University, Department of Management and Engineering. Linköping University, Faculty of Science & Engineering. Tongji Univ, Peoples R China.
Linköping University, Department of Management and Engineering, Production Economics. Linköping University, Faculty of Science & Engineering.ORCID iD: 0000-0003-3058-7431
Tongji Univ, Peoples R China.
Univ Shanghai Sci and Technol, Peoples R China.
2018 (English)In: International Journal of Hospitality Management, ISSN 0278-4319, E-ISSN 1873-4693, Vol. 71, p. 19-32Article in journal (Refereed) Published
Abstract [en]

It is of importance for restaurants to identify their competitors to gain competitiveness. Meanwhile, opinion-rich resources like online reviews sites can be used to understand others opinion toward restaurant services. We thus propose a novel model to extract comparative relations from online reviews, and then construct three types of comparison relation networks, enabling competitiveness analysis for three tasks. The first network help restaurants analyze market structure for their positioning. The second network enables to identify top competitors using competitive index and dissimilarity index. The third network help restaurants identify strengths and weaknesses through aspects-comparison relation mining. Finally, the market environment is illustrated in a visual way according to the three types of networks. Experimental results reveal the effectiveness of the proposed competitiveness analysis using text analytics, which can identify top competitors and evaluate the market environment, as well as help the focal restaurant effectively develop a service improvement strategy.

Place, publisher, year, edition, pages
ELSEVIER SCI LTD , 2018. Vol. 71, p. 19-32
Keywords [en]
Competitor identification; Service improvement strategy; Competitive analysis; Aspects-comparison relation mining; Online review; Restaurant industry
National Category
Business Administration
Identifiers
URN: urn:nbn:se:liu:diva-147949DOI: 10.1016/j.ijhm.2017.09.004ISI: 000430779300004OAI: oai:DiVA.org:liu-147949DiVA, id: diva2:1209480
Note

Funding Agencies|Natural Science Foundation of China [71371144, 71601119, 71601082, 71771177]; program of China Scholarships Council

Available from: 2018-05-23 Created: 2018-05-23 Last updated: 2019-06-27

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CiteExportLink to record
Permanent link

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Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf