Can Location-Based Social Media and Online Reservation Services Tell More about Local Accommodation Industries than Open Governmental Data?

Sidor Sidor,Khouri Khouri,Kršák Kršák,Štrba Štrba,Cehlár Cehlár,Stričík Stričík,Bolechová Bolechová,Dugas Dugas,Gajdoš Gajdoš

doi:10.3390/su11215926

Abstract

The paper follows-up ongoing research focusing on the potential of machine-readable data as additional knowledge in the governance of local tourism and destination management organizations (DMOs) in Slovakia. The current focus is on one classic social media (Facebook), one location-based social media (Foursquare), two hybrid travel-related platforms with partial attributes of reservation services (Google Places, TripAdvisor), and two online reservation services (Booking, Airbnb). The global aim is the usage of extracted data for the identification of additional entities with the obligation of local occupancy taxation, which is the financial backbone of Slovak (DMOs). A set of simple and globally reusable scripts constructed in Python and PostgreSQL were used to extract data on lodging providers from the Google Places application programming interface (API), the Facebook Place Search API and the Foursquare Venue API over grid overlays of districts’ spatial representation. For pure scientific purposes in the case of Tripadvisor, Booking, and Airbnb, with no suitable access to open APIs, web scraping methods were used for data extraction. The pilot case was applied in the boundaries of Kosice city (Slovakia), and the aggregations of processed data were compared with official open statistics. Results indicate that the automated continuous monitoring of online platforms could help local public administrations in decreasing occupancy tax evasions and even widen knowledge about online audiences and visitors’ satisfaction.

Highlights

Aggregates of local municipalities’ hospitality related data at the regional and state levels are widely used for establishing long term local, regional, and national policies, development and marketing strategies and even funding rules
The purpose of the paper is to demonstrate on the case of Kosice city (Slovakia) the potential value of machine-readable data extracted from one classic social media (Facebook), one location-based social media (Foursquare), two hybrid travel-related platforms with partial attributes of reservation services (Google Places, TripAdvisor), and two online reservation services (Booking, Airbnb) within the processes of identification of entities with the potential obligation of local occupancy taxation and the capability to generate additional knowledge about local destinations’ markets
Larger double occurrences were observed in the Airbnb–Booking (18 ASPs), Booking– TripAdvisor (17 ASPs), Google–TripAdvisor (10 ASPs) and Booking–Google

Summary

Introduction

Aggregates of local municipalities’ hospitality related data at the regional and state levels are widely used for establishing long term local, regional, and national policies, development and marketing strategies and even funding rules. Lodging providers generate the most basic tourism metrics—the number of tourists and their number of overnight stays in a destination. In terms of public funding opportunities for Slovak destination management organizations (DMOs), the higher number of officially recorded overnight stays means a larger volume of levied occupancy tax [1]. The larger the volume of levied occupancy tax is, the higher is the limit for potential maximum public funding [1]. For this reason and others, official statistics should be open at the local level, and they should be precise and trustworthy

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Results

Conclusion