Residential College | false |
Status | 已發表Published |
Big data use in determining competitive position: The case of theme parks in Hong Kong | |
Albayrak, Tahir1; Cengizci, Aslıhan Dursun2; Caber, Meltem3; Nang Fong, Lawrence Hoc4 | |
2021-12-01 | |
Source Publication | Journal of Destination Marketing and Management |
ABS Journal Level | 1 |
ISSN | 2212-571X |
Volume | 22Pages:100668 |
Abstract | Theme park operators need to understand their competitiveness in a destination to increase their market share. This study adopted the big data approach by analysing online reviews to assess the competitiveness of a theme park called Ocean Park (HKOP) against its competitor Disneyland (HKDL) in Hong Kong. Firstly, the strengths and weaknesses of HKOP were identified through importance performance analysis (IPA) and asymmetric impact performance analysis (AIPA). Results revealed that urgent action is required for the ‘Staff’, ‘Fast pass’, and ‘F&B and prices’ attributes, since they are the basic attributes that perform poorly. Secondly, to determine HKOP's competitive position against its rival HKDL, importance performance competitor analysis (IPCA) and asymmetric impact competitor analysis (AICA) were performed. On the one hand, the IPCA results indicated that the ‘Shows’, ‘Spend time’, and ‘Time & weather’ attributes are the strengths of HKOP when compared with HKDL. On the other hand, the AICA findings suggested urgent action for the ‘Child friendly’, ‘Waiting time’, ‘F&B and prices’, ‘Staff’, and ‘Accessibility’ attributes of HKOP. This research is one of the scarce studies that follow a holistic approach to understand competitiveness by examining each attribute's company-based and competitor-comparative performance. |
Keyword | Business-to-business Competitiveness Hong Kong Ocean Park Latent Dirichlet Allocation Online Reviews Theme Parks |
DOI | 10.1016/j.jdmm.2021.100668 |
URL | View the original |
Indexed By | SSCI |
Language | 英語English |
WOS Research Area | Social Sciences - Other Topics ; Business & Economics |
WOS Subject | Hospitality, Leisure, Sport & Tourism ; Management |
WOS ID | WOS:000719274100002 |
Publisher | ELSEVIERRADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS |
Scopus ID | 2-s2.0-85118535681 |
Fulltext Access | |
Citation statistics | |
Document Type | Journal article |
Collection | Faculty of Business Administration DEPARTMENT OF INTEGRATED RESORT AND TOURISM MANAGEMENT |
Corresponding Author | Albayrak, Tahir |
Affiliation | 1.Akdeniz University, Tourism Faculty, Tourism Management Department, Antalya, Campus, Turkey 2.Antalya Bilim University, Tourism Faculty, Antalya, Turkey 3.Akdeniz University, Tourism Faculty, Tourism Guidance Department, Antalya, Campus, Turkey 4.Faculty of Business Administration, Centre for Cognitive and Brain Sciences, University of Macau, Taipa, Avenida da Universidade, Macau SAR, E22-3037, China |
Recommended Citation GB/T 7714 | Albayrak, Tahir,Cengizci, Aslıhan Dursun,Caber, Meltem,et al. Big data use in determining competitive position: The case of theme parks in Hong Kong[J]. Journal of Destination Marketing and Management, 2021, 22, 100668. |
APA | Albayrak, Tahir., Cengizci, Aslıhan Dursun., Caber, Meltem., & Nang Fong, Lawrence Hoc (2021). Big data use in determining competitive position: The case of theme parks in Hong Kong. Journal of Destination Marketing and Management, 22, 100668. |
MLA | Albayrak, Tahir,et al."Big data use in determining competitive position: The case of theme parks in Hong Kong".Journal of Destination Marketing and Management 22(2021):100668. |
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