Yazar "57162718000 [Dursun Cengizci, Aslıhan]" için Gastronomi ve Mutfak Sanatları Bölümü / Department of Gastronomy & Culinary Arts listeleme
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Big data use in determining competitive position: the case of theme parks in Hong Kong
Albayrak, Tahir; Dursun Cengizci, Aslıhan; Caber, Meltem; Nang Fong, Lawrence Hoc (Journal of Destination Marketing & Management, 2021)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 ... -
Conflict management styles of professional tour guides: a cluster analysis
Caber, Meltem; Ünal, Caner; Dursun Cengizci, Aslıhan; Güven, Aylin (Tourism Management Perspectives, 2019)Professional tour guides play an important role in tourist satisfaction and the business success of tour agencies/operators, since they are directly in contact with tourists and are responsible for managing the tours. ... -
Customer loyalty towards travel agency websites: the role of trust and hedonic value
Albayrak, Tahir; Karasakal, Sezer; Kocabulut, Özge; Dursun Cengizci, Aslıhan (Journal of Quality Assurance in Hospitality & Tourism, 2020)Website quality of online travel agencies and the impact of perceived website quality on customer behavior are still the research areas to be investigated by the academics. The present study explores the relationships ... -
Do tourists have different motivations for online travel purchasing? A segmentation of the Russian market
Albayrak, Tahir; Dursun Cengizci, Aslıhan; Ünal, Caner (Journal of Vacation Marketing, 2018)This study investigates online travel purchasing (OTP) motivations of Russian tourists as a neglected research topic in the literature. Data were collected from 403 Russian tourists visiting Antalya, Turkey. Convenience, ... -
Using data mining techniques for profiling profitable hotel customers: an application of RFM analysis
Dursun Cengizci, Aslıhan; Caber, Meltem (Tourism Management Perspectives, 2016)This study focuses on profiling profitable hotel customers by RFM analysis, which is a data mining technique. In RFM analysis, Recency, Frequency and Monetary indicators are employed for discovering the nature of the ...