Hakseung Shin

36 papers receiving 1.5k citations

Hit Papers

Reducing perceived health risk to attract hotel customers...2020202620222024202020212024100200300

Peers

Hakseung Shin
Comparison fields: 5 of 92
  • Sociology and Political Science 959
  • Marketing 600
  • Organizational Behavior and Human Resource Management 353
  • Artificial Intelligence 253
  • Economics and Econometrics 248
Replace Anestis Fotiadis with:
Anestis Fotiadis United Arab Emirates
Yangyang Jiang China
Juhyun Kang South Korea
Adiyukh Berbekova United States
Jacques Bulchand‐Gidumal Spain
Viraiyan Teeroovengadum Mauritius
Amr Al‐Ansi South Korea
Sunny Sun Hong Kong
María Fuentes Blasco Spain
Tony Garry New Zealand
Hakseung Shin relative to Anestis Fotiadis United Arab Emirates Anestis Fotiadis's profile →
Citations per field
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Anestis Fotiadis · 1×
Citations per year

Countries citing papers authored by Hakseung Shin

Since Specialization
Citations

This map shows the geographic impact of Hakseung Shin's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Hakseung Shin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hakseung Shin more than expected).

Fields of papers citing papers by Hakseung Shin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Hakseung Shin. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Hakseung Shin. The network helps show where Hakseung Shin may publish in the future.

Co-authorship network of co-authors of Hakseung Shin

This figure shows the co-authorship network connecting the top 25 collaborators of Hakseung Shin. A scholar is included among the top collaborators of Hakseung Shin based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Hakseung Shin. Hakseung Shin is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 3
2 8
3 2
4 2
5 7
6 1
7 1
8
How does the metaverse travel experience influence virtual and actual travel behaviors? Focusing on the role of telepresence and avatar identificationbreakdown →
42
9 12
10 9
11 21
12 36
13 16
14 8
15 13
16 114
17 119
18 33
19
Reducing perceived health risk to attract hotel customers in the COVID-19 pandemic era: Focused on technology innovation for social distancing and cleanlinessbreakdown →
384
20 83

About Hakseung Shin

Hakseung Shin is a scholar working on Marketing, Business and International Management and General Energy, having authored 37 papers that have together received 1.6k indexed citations. Recurring topics across this work include Digital Marketing and Social Media (15 papers), Diverse Aspects of Tourism Research (9 papers) and Customer Service Quality and Loyalty (9 papers). The work is most often cited by research in Marketing (600 citations), Organizational Behavior and Human Resource Management (353 citations) and Information Systems and Management (182 citations). Hakseung Shin has collaborated with scholars based in South Korea, United States and United Kingdom. Frequent co-authors include Juhyun Kang, Richard R. Perdue, Juan Luis Nicolau, Abhinav Sharma, Hoon Lee, María Jesús Santa-María, Mario Pandelaere, Jinhee Lee, Seunghee Baek and Hak‐Sung Kim. Their work appears in journals such as Tourism Management, Annals of Tourism Research and Journal of Travel Research.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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