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Assessing the Association of Popular Attractions with Taiwan’s Inbound Tourist Numbers: The Case of Night-Market Keywords

Author

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  • Chien-Jung Ting
  • Hsing-Mei Juan

Abstract

This study examines the relationship between Taiwan’s most popular attractions and inbound tourist arrivals, using night-market–related keywords as a case in point. Leveraging high-frequency Google Trends data, we use search intensity for night-market keywords to forecast lower-frequency inbound arrivals, with the aim of improving prediction accuracy by exploiting timely information. We construct a composite night-market search index via principal component analysis (PCA) and assess its interrelationship with inbound arrivals to identify which keywords are most closely associated with tourism demand. The contributions are threefold: (1) the empirical results robustly show that inbound tourist arrivals are significantly affected by night-market keyword searches; (2) the statistically significant keyword “Shilin Night Market†aligns with actual search behavior, confirming its prominence among international visitors; and (3) to our knowledge, this is the first study to directly analyze the effect of night-market–related online search activity on inbound tourism to Taiwan, thereby filling a gap in the literature. Our findings also reflect the policy context in which night-market branding has been promoted by local governments and private initiatives over the past two decades, suggesting that place-based tourism marketing has effectively stimulated inbound demand and, in turn, intensified related search activity.  JEL classification numbers: C32, M31, R11.

Suggested Citation

  • Chien-Jung Ting & Hsing-Mei Juan, 2025. "Assessing the Association of Popular Attractions with Taiwan’s Inbound Tourist Numbers: The Case of Night-Market Keywords," Advances in Management and Applied Economics, SCIENPRESS Ltd, vol. 15(6), pages 1-4.
    • Handle: RePEc:spt:admaec:v:15:y:2025:i:6:f:15_6_4
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    Keywords

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    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • M31 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Marketing and Advertising - - - Marketing
    • R11 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Regional Economic Activity: Growth, Development, Environmental Issues, and Changes

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