Yazar "Polat, Eray" seçeneğine göre listele
Listeleniyor 1 - 2 / 2
Sayfa Başına Sonuç
Sıralama seçenekleri
Öğe Past, present, and future scene of influencer marketing in hospitality and tourism management(Routledge Journals, Taylor & Francis, 2024) Polat, Eray; Çelik, Fatih; Ibrahim, Blend; Gürsoy, DoğanThis paper reviews influencer marketing (IM)-research in the tourism and hospitality (H&T) field to provide a state-of-the-art of the past, present, and future of IM-research. It identifies research themes, theoretical underpinnings, and methodologies utilized in IM-research. Seventy-five studies are examined through co-citation, bibliographic coupling and content analysis based on the TCCM (theory/context/characteristics/methodology) framework. Co-citation analysis reveals that IM-research focused on travel blogs, vlogs, celebrity endorsement, influencer authenticity. An assessment of recent studies through bibliographic coupling indicates a partial shift toward the study of more contemporary issues. This field-discipline-focused hybrid-review contributes to literature and practice by presenting the past, present, and future of IM-research.Öğe Unpacking the power of user-generated videos in hospitality and tourism: a systematic literature review and future direction(Routledge, 2023) Polat, Eray; Çelik, Fatih; Ibrahim, Blend; Köseoglu, Mehmet AliWe review user-generated video (UGV)-research in hospitality and tourism (H&T), provide an overview of its current-state, and suggest ways forward. We adopted a systematic literature review methodology and reviewed 66 articles with TCM (theory/context/methodology) framework. UGV research focuses on (i) destination image perception, (ii) short-form videos and travel live-streaming, (iii) behavioral intentions, and (iv) crisis management. Theoretical development is diverse, given the descriptive nature of research questions, but it is still in its infancy. The context varies by H&T setting, type of social media platform, population, and country. Research methods and techniques range from traditional analysis to advanced machine learning or artificial intelligence-based quantitative approaches, predominantly qualitative methods.