Margus Tiru

Everyday space–time geographies: using mobile phone-based sensor data to monitor urban activity in Harbin, Paris, and Tallinn

This paper proposes a methodology for using mobile telephone-based sensor data for detecting spatial and temporal differences in everyday activities in cities. Mobile telephone-based sensor data has great applicability in developing urban monitoring tools and smart city solutions. The paper outlines methods for delineating indicator points of temporal events referenced as ‘midnight’, ‘morning start’, ‘midday’, and ‘duration of day’, which represent the mobile telephone usage of residents (what we call social time) rather than solar or standard time. Density maps by time quartiles were also utilized to test the versatility of this methodology and to analyze the spatial differences in cities. The methodology was tested with data from cities of Harbin (China), Paris (France), and Tallinn (Estonia). Results show that the developed methods have potential for measuring the distribution of temporal activities in cities and monitoring urban changes with georeferenced mobile phone data.

Mobile Positioning Data in Tourism Studies and Monitoring: Case Study in Tartu, Estonia

We introduce mobile positioning based data sources in tourism studies using the case study of tourism in Tartu, Estonia. Mobile positioning data is a promising source for tourism geography as it is one easiest and most cost effective sources for investigating the flows of tourists with relatively good spatial and temporal coverage. Mobile positioning data allows one to link the digital track of visitors with visited events and locations retrospectively. The data also has potential for the development of real-time monitoring tools for tourism planning and management, as it has been tested in Estonia with “Positium Tourism Barometer”. The biggest problem with positioning data is privacy and surveillance, and those issues needs to be addressed and discussed very carefully.

LBS in marketing and tourism management: measuring destination loyalty with mobile positioning data

The aim of this article is to elaborate a mobile positioning-based methodology to measure the ‘destination loyalty’ of foreign tourists to a place. Loyal customers are highly appreciated in marketing, since they are of greater benefit than ‘on–off’ customers; they need different marketing strategies than those required to attract new visitors. Theoretical approaches to the destination loyalty of tourists suggest measuring behavioural loyalty, which we do here by detecting repeated visits. By using passive mobile positioning, we elaborated a methodology to determine repeat visits of tourists to a destination. This uses the number, duration, frequency and geography of visits in order to identify repeat visitors in a particular area. We tested the algorithm using a database containing information about foreign tourists who had visited Estonia in the past 5 years. It revealed that the algorithm permits detection of repeat visits. The results demonstrate that repeat visitors make up 29.9% of visitors to Estonia, 63.9% of the number of visits and 70.14% of the total number of visiting days. The algorithm can also be successfully applied in other location-based services solutions, in targeting location-specific advertising, m-ticketing or in personalising packages of mobile communication services.

Mobile Positioning Based Tourism Monitoring System: Positium Barometer

This paper introduces experiences with mobile positioning data in the web-based tourism management and monitoring system: “Positium Barometer”. The system has been developed for tourism enterprises, public authorities, scientists and planners to obtain statistical overviews and standardized analyses about the space-time movement of tourists. Positium Barometer uses passive mobile positioning data —location data that is stored automatically in the memory files (billing memory, hand-over logs etc) of mobile operators. Our database consists of records of the locations of roaming call activities in Estonia. Data is stored for every call activity of a foreign phone in Estonia. The data is anonymous, phone numbers and user data are not identified by mobile operators. LBS (Location Based Services) data is a new and promising source for studying the geography of tourism and space-time behaviour since the data is spatially more precise than questionnaires or accommodation statistics. The biggest problem of mobile positioning is fear of surveillance.

Mobile Positioning Data in Emergency Management: Measuring the Impact of Street Riots and Political Confrontation on Incoming Tourism

The aim of this chapter is to examine how mobile positioning data can be used for measuring the impacts of short term events and emergency situations on tourism. As case study, we measure the impact of street riots and political confrontation on incoming tourism with the case study of the Bronze Night riots in Estonia, in April 2007. This political unrest was real emergency situation for Estonia and tourism is one of the most important industries for Estonia. We draw out methodological lessons on using such Call Detail Record based datasets as source for tourism statistics and emergency management.

Segmentation of Repeat Visitors with the Help of Passive Mobile Positioning

Since the 1980s the emphasis of marketing strategies has shifted to long-term relationships (Gummesson, 1999). The increasing number of destination alternatives and thus competition for market share requires also destination managers to think about customer retention and how to encourage customers to keep returning. The study by Wang (2004) revealed that repeat visitors spend more money than first-time visitors. Oppermann (1999) has added that having knowledge of the amount and type of loyal tourists helps to forecast total demand, design infrastructure, and create positioning strategy. Several authors (Buttle, 2004; Oppermann, 2000; Petrick, 2004, etc.) have pointed out that repeat visitation indicates a customer’s positive attitude, which leads to positive word-of-mouth (WoM).