About

Dr. Bing Pan is an associate professor in the Department of Recreation, Park, and Tourism Management at Penn State University, within the College of Health and Human Development. He holds a Bachelor's and Master's degree from Nanjing University and completed his Ph.D. at the University of Illinois at Urbana-Champaign. He also spent two years as a post-doctoral fellow at Cornell University and served as a visiting associate professor at Hong Kong Polytechnic University for one year. Dr. Pan has over 12 years of consulting experience with local tourism organizations and businesses, focusing on economic impact analysis, intercept surveys, market research, and ROI analysis. His academic research interests include tourism big data, information technology, e-commerce, destination marketing, well-being and tourism, consumer behavior, and psychology. Recently, his research has concentrated on online behavior and online destination image. Dr. Pan is actively involved in scholarly service, serving on editorial review boards for several prominent journals such as Tourism Management, Journal of Travel Research, and Journal of Business Research, among others.

Research topics

• Sociology
• Geography
• Socioeconomics

Selected publications

• Investigating Different Usage Patterns of Residents and Tourists of an Urban Park with Triangulation Methods

  SSRN Electronic Journal · 2026-01-01

  preprintOpen access1st authorCorresponding
  PublisherDOI

• Tourist monitoring compass: linking measurement with constructs for nature-based tourism monitoring

  Journal of Hospitality and Tourism Horizons · 2025-10-31

  articleSenior author

  Purpose Data sources for monitoring tourists are prolific and growing. This phenomenon presents increasing opportunities for researchers and practitioners to diversify and enhance monitoring approaches; however, it also creates a complex landscape for developing rigorous methodology. The tourist monitoring compass is a conceptual framework that visualizes the suitability of traditional quantitative data and big data collection approaches for measuring salient social science constructs in nature-based tourism destinations. Design/methodology/approach Prominent quantitative data collection sources were placed on a matrix. The x-axis ranged from tourist attributes to tourist behavior. The y-axis rated sources based on their ability to measure phenomena ranging from psychological to observable. Findings Most data collection methods were well-suited for measuring observable phenomena – both behaviors and attributes. Relatively fewer sources measure psychological phenomena. The gaps among existing tools highlight the value of well-conceptualized theoretical models and the integration of multiple data sources using mixed methods for measuring complex phenomena. Practical implications Inspection of the framework can facilitate understanding of nature-based tourism monitoring measurement tools and constructs. The framework visualizes constructs to identify the current versatility, limitations and gaps of existing measurement approaches, revealing potential areas for innovation in how to use existing tools and prioritizing innovation in new approaches. Originality/value The present framework associates construct validity with measurement approaches to serve as a simple tool for practitioners and researchers to identify appropriate data collection sources based on their common uses. The framework may facilitate the initial step of designing tourist monitoring methodology – data selection – in an increasingly complex methodological landscape.

  PublisherDOI

• Virtual or physical: how different types of urban streets affect tourists’ restoration

  Current Issues in Tourism · 2025-04-18 · 3 citations

  articleSenior author
  PublisherDOI

• A Comparison of Tourists’ Spatial–Temporal Behaviors Between Location-Based Service Data and Onsite GPS Tracks

  Sustainability · 2025-01-07 · 9 citations

  articleOpen accessCorresponding

  Tourism and recreation managers rely on spatial-temporal data to measure visitors’ behavior for gauging carrying capacity and sustainable management. Location-based service (LBS) data, which passively record location data based on mobile devices, may enable managers to measure behaviors while overcoming constraints in labor, logistics, and cost associated with in-person data collection. However, further validation of LBS data at more refined spatial and temporal scales within tourism attractions is needed. We compared observations of salient spatial–temporal measures from a stratified sample of onsite visitors’ GPS traces in a popular U.S. National Park during peak season over two years with a sample of visitors’ traces collected during the same period by a third-party LBS data provider. We described trip characteristics and behaviors within 34 points of interest (POIs) and then pre-processed both datasets into weighted, directed networks that treated POIs as nodes and flow between POIs as edges. Both datasets reported similar proportions of day-use visitors (~79%) and had moderate-to-strong correlations across networks depicting visitor flow (r = 0.72–0.85, p < 0.001). However, relative to the onsite data, LBS data underestimated the number of POIs the visitors stopped by and differed in its rank of popular POIs, underestimating the length of time visitors spent in POIs (z = 1, p ≤ 0.001) and overestimating visitation to the most popular POIs (z = 180, p = 0.044). Our findings suggest that LBS data may be helpful for identifying trends or tracking tourist movement in aggregate and at crude spatial and temporal scales, but they are too sparse and noisy to reliably measure exact movement patterns, visitation rates, and stay time within attractions.

  PublisherOA PDFDOI

• Forecasting fine-grained tourism demand with peripheral surroundings: implications for destination networking

  Journal of Travel & Tourism Marketing · 2025-06-13 · 2 citations

  article
  PublisherDOI

• Examining the Dual Function of In-Flight Safety Videos in Safety Management and Destination Marketing

  Journal of Travel Research · 2025-06-17

  articleSenior author

  This study investigates the dual function of in-flight safety videos as both a safety management tool and destination marketing material. Based on the information processing model and affect transfer model, a mixed-methods design was adopted. The content of safety videos from 55 major national flag carriers was analyzed. A between-subjects experiment was conducted to measure the effects of key media components on safety management and destination marketing outcomes. The results reveal varying effects. While it does not influence perceived safety or compliance intentions, the inclusion of destination content, particularly when presented through live-shot imagery, positively impacts destination image and increases visit intentions. However, this comes at the cost of reduced memory recall among viewers. These findings confirm the dual function of modern in-flight safety videos and reveal a trade-off between aesthetic appeal and functional effectiveness. We conclude with implications for balancing different objectives when destinations are used as an appeal for safety videos.

  PublisherDOI

• A virtual reality-based experiment on tourists’ choice of evacuation route

  Tourism Management · 2025-10-30

  articleSenior author
  PublisherDOI

• A Top Model of Urban Residents’ Subjective Well-Being in China

  SAGE Open · 2024-10-01 · 2 citations

  articleOpen access1st authorCorresponding

  Past research on subjective well-being (SWB) in Western society and China has revealed various contributing factors. This study conducted a series of interviews with Chinese urban residents to systematically analyze those factors based on Bronfenbrenner’s Ecological System Theory. The results revealed that 5 layers, 23 factors, and 55 elements, many of which had distinct Chinese characteristics, contributed to Chinese urban residents’ SWB. The Top Model of SWB, visualized as a spinning top or gyroscope, showcased the interdependent layers of factors impacting Chinese urban residents’ SWB. At its vertical axis is a time dimension as residents often reflect on factors by comparing their present situation with the past and the future. Discussion regarding each layer, the primary factors that comprise each layer, links between the layers, and the impact of a time dimension was included to substantiate the proposed model. The discussions focus on the study’s contribution to SWB literature, public policy-making, and future research on urban Chinese residents’ SWB.

  PublisherDOI

• Explorations of preferred and maximum booking windows among U.S. national park campers: Implications for improved fairness

  Tourism and Hospitality Research · 2024-03-03 · 3 citations

  article

  The purpose of this research note is to inform national park management regarding the strategies in rationing campsites in popular U.S. national park campgrounds and provide data-driven guidance for the design of more fair and equitable methods for distributing limited, highly demanded campsites. To explore preferences in campsite rationing techniques and preferred and maximum campsite booking windows, we collected survey data among randomly sampled onsite visitors in Grand Canyon National Park at scenic viewpoints and Mather Campground in 2023. The rationing technique with the highest level of positive support was advance reservation, followed by a combination of time frames for booking window (e.g., 6-month, 2- month, and 2-week) and a combination of rationing techniques (e.g., advance reservation and first-come, first-serve). Concerning fairness and equity, we found that respondents in higher annual household income groups had a longer maximum booking window, on average, than those in lower income groups. Thus, we discuss the merits of offering a diversity of booking windows to meet the needs of multiple groups, each with constrained booking horizons.

  PublisherDOI

• Tourism myths and the Dunning Kruger effect

  Annals of Tourism Research · 2024-01-01 · 8 citations

  articleOpen access
  PublisherOA PDFDOI

Frequent coauthors

• So Young Park

  Florida Atlantic University

  14 shared

• Daniel R. Fesenmaier

  MODUL University Vienna

  14 shared

• William L. Rice

  University of Montana

  12 shared

• Helene Hembrooke

  12 shared

• Zachary D. Miller

  Bureau of Land Management

  11 shared

• Laura Granka

  Google (United States)

  10 shared

• Wayne W. Smith

  10 shared

• Geri Gay

  10 shared

Labs

• Social Data AnalyticsPI

Education

• PhD, Leisure Studies

  University of Illinois

  2003

• MS, Urban and Resources Sciences

  Nanjing University

  1998

• BS, Urban and Resources Sciences

  Nanjing University

  1995