Bing Pan

13.8k total citations · 7 hit papers
114 papers, 9.4k citations indexed

About

Bing Pan is a scholar working on Sociology and Political Science, Marketing and Transportation. According to data from OpenAlex, Bing Pan has authored 114 papers receiving a total of 9.4k indexed citations (citations by other indexed papers that have themselves been cited), including 77 papers in Sociology and Political Science, 28 papers in Marketing and 16 papers in Transportation. Recurrent topics in Bing Pan's work include Diverse Aspects of Tourism Research (50 papers), Digital Marketing and Social Media (45 papers) and Technology Adoption and User Behaviour (13 papers). Bing Pan is often cited by papers focused on Diverse Aspects of Tourism Research (50 papers), Digital Marketing and Social Media (45 papers) and Technology Adoption and User Behaviour (13 papers). Bing Pan collaborates with scholars based in United States, China and Hong Kong. Bing Pan's co-authors include Stephen W. Litvin, Ronald E. Goldsmith, Geri Gay, Laura Granka, Helene Hembrooke, Thorsten Joachims, John C. Crotts, Daniel R. Fesenmaier, Tanya MacLaurin and Rob Law and has published in prestigious journals such as SHILAP Revista de lepidopterología, Scientific Reports and MIS Quarterly.

In The Last Decade

Bing Pan

106 papers receiving 8.7k citations

Hit Papers

Electronic word-of-mouth in hospitality and tourism manag... 2005 2026 2012 2019 2007 2005 2007 2007 2007 500 1000 1.5k 2.0k

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Bing Pan United States 36 6.3k 2.9k 1.5k 1.2k 1.1k 114 9.4k
Ulrike Gretzel United States 56 10.3k 1.6× 4.9k 1.7× 617 0.4× 2.3k 1.8× 1.6k 1.4× 201 13.0k
Μαριάννα Σιγάλα Greece 47 5.5k 0.9× 2.7k 0.9× 351 0.2× 1.3k 1.0× 1.7k 1.5× 181 9.0k
Anindya Ghose United States 47 4.8k 0.8× 5.2k 1.8× 1.1k 0.7× 1.5k 1.2× 645 0.6× 172 9.7k
Chulmo Koo South Korea 42 4.8k 0.8× 2.6k 0.9× 344 0.2× 1.6k 1.3× 772 0.7× 209 6.8k
Alessandro Acquisti United States 49 10.5k 1.7× 2.0k 0.7× 3.9k 2.6× 2.2k 1.8× 576 0.5× 184 16.3k
Luis V. Casaló Spain 48 5.9k 0.9× 3.4k 1.2× 470 0.3× 3.1k 2.5× 1.7k 1.5× 95 9.3k
Paulo Rita Portugal 37 3.1k 0.5× 2.3k 0.8× 449 0.3× 1.3k 1.0× 1.2k 1.0× 157 5.7k
Garry Wei‐Han Tan Malaysia 48 4.2k 0.7× 2.7k 0.9× 1.4k 0.9× 4.4k 3.5× 934 0.8× 140 8.9k
Sinan Aral United States 33 7.7k 1.2× 869 0.3× 1.6k 1.1× 871 0.7× 455 0.4× 84 13.9k
Raffaele Filieri France 47 6.6k 1.0× 4.1k 1.4× 381 0.2× 2.6k 2.1× 1.6k 1.4× 111 9.2k

Countries citing papers authored by Bing Pan

Since Specialization
Citations

This map shows the geographic impact of Bing Pan'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 Bing Pan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Bing Pan more than expected).

Fields of papers citing papers by Bing Pan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Bing Pan. 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 Bing Pan. The network helps show where Bing Pan may publish in the future.

Co-authorship network of co-authors of Bing Pan

This figure shows the co-authorship network connecting the top 25 collaborators of Bing Pan. A scholar is included among the top collaborators of Bing Pan 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 Bing Pan. Bing Pan 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
1.
Pan, Bing, et al.. (2025). A Comparison of Tourists’ Spatial–Temporal Behaviors Between Location-Based Service Data and Onsite GPS Tracks. Sustainability. 17(2). 391–391. 2 indexed citations
2.
Pan, Bing, et al.. (2024). Decolonizing knowledge production in tourism research. Tourism Management. 103. 104914–104914. 1 indexed citations
3.
Pratt, Stephen, Bing Pan, Elizabeth Agyeiwaah, et al.. (2024). Tourism myths and the Dunning Kruger effect. Annals of Tourism Research. 104. 103620–103620. 5 indexed citations
4.
Rice, William L., et al.. (2024). Explorations of preferred and maximum booking windows among U.S. national park campers: Implications for improved fairness. Tourism and Hospitality Research. 25(3). 526–534. 2 indexed citations
5.
Pan, Bing, Deborah Kerstetter, Xiaoli Yi, et al.. (2024). A Top Model of Urban Residents’ Subjective Well-Being in China. SAGE Open. 14(4).
6.
Yin, Junjun, et al.. (2023). Using social media user profiles to identify visitor demographics and origins in Yellowstone national park. Journal of Outdoor Recreation and Tourism. 44. 100620–100620. 6 indexed citations
7.
Schroeder, Ashley, et al.. (2023). Does algorithmic filtering lead to filter bubbles in online tourist information searches?. Information Technology & Tourism. 26(1). 183–217. 3 indexed citations
8.
Lin, Michael S., Amit Sharma, Bing Pan, & Donna Quadri-Felitti. (2023). Information asymmetry in the innovation adoption decision of tourism and hospitality SMEs in emerging markets: A mixed-method analysis. Tourism Management. 99. 104793–104793. 33 indexed citations
9.
Pan, Bing, et al.. (2023). Gauging indirect stakeholder sentiment towards orphanage tourism on Twitter. Tourism Recreation Research. 49(6). 1259–1272.
10.
Yin, Junjun, et al.. (2022). Assessing the validity of mobile device data for estimating visitor demographics and visitation patterns in Yellowstone National Park. Journal of Environmental Management. 317. 115410–115410. 22 indexed citations
11.
Pan, Bing, et al.. (2022). COVID-19’s impact on visitation behavior to US national parks from communities of color: evidence from mobile phone data. Scientific Reports. 12(1). 13398–13398. 17 indexed citations
12.
Rice, William L. & Bing Pan. (2021). Understanding changes in park visitation during the COVID-19 pandemic: A spatial application of big data. Wellbeing Space and Society. 2. 100037–100037. 91 indexed citations
13.
Pan, Bing, Wayne W. Smith, Stephen W. Litvin, Y. Yuan, & Arch G. Woodside. (2021). Ethnic bias and design factors impact response rates of online travel surveys. Journal of Global Scholars of Marketing Science. 32(2). 129–144. 1 indexed citations
14.
Miller, Zachary D., et al.. (2021). An exploratory study on Chinese tourists’ visitation to a U.S. National Park. Tourism Recreation Research. 48(1). 79–93. 1 indexed citations
15.
Rice, William L., et al.. (2019). Forecasting campground demand in US national parks. Annals of Tourism Research. 75. 424–438. 60 indexed citations
16.
Wang, Xingang, et al.. (2019). Agent-based simulations of China inbound tourism network. Scientific Reports. 9(1). 12325–12325. 11 indexed citations
17.
Pan, Bing & Dan Wang. (2016). Mobile Internet Access Patterns for Travel: Comparison of Desktops, Tablets, and Phones. Scholarworks (University of Massachusetts Amherst). 1 indexed citations
18.
Hung, Kam, Xiang Li, Bing Pan, & James F. Petrick. (2010). Knowledge Dissemination in Tourism Education: A Case of Tourism Marketing. Journal of Travel & Tourism Marketing. 27(5). 519–532. 9 indexed citations
19.
Pan, Bing, et al.. (2006). Bridging the gap: A conceptual model of the access of digital libraries. Texas Digital Library (University of Texas). 7(2). 1–24. 3 indexed citations
20.
Wang, Ming, et al.. (2004). [Analysis on the risk factors of severe acute respiratory syndromes coronavirus infection in workers from animal markets].. PubMed. 25(6). 503–5. 3 indexed citations

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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