Prof. Dr. Katerina Volchek, M.Sc, BA

Professorin

Member of the Board and Director for Marketing at the International Federation for IT and Travel & Tourism

EC 2.07

0991/3615-8880


Vortrag
  • Katerina Volchek
Exploring ways to improve personalisation: the influence of tourist context on service perception

In: 27th annual ENTER International Conference on Information and Communication Technologies in Tourism

  • 2020
  • Europan Campus Rottal-Inn
  • MOBIL
Zeitschriftenartikel
  • D. Buhalis
  • Katerina Volchek
Bridging marketing theory and big data analytics: The taxonomy of marketing attribution, vol. 55

In: International Journal of Information Management

  • 2020

DOI: 10.1016/j.ijinfomgt.2020.102253

The integration of technology in business strategy increases the complexity of marketing communications and urges the need for advanced marketing performance analytics. Rapid advancements in marketing attribution methods created gaps in the systematic description of the methods and explanation of their capabilities. This paper contrasts theoretically elaborated facilitators and the capabilities of data-driven analytics against the empirically identified classes of marketing attribution. It proposes a novel taxonomy, which serves as a tool for systematic naming and describing marketing attribution methods. The findings allow to reflect on the contemporary attribution methods’ capabilities to account for the specifics of the customer journey, thereby, creating currently lacking theoretical backbone for advancing the accuracy of value attribution.
  • Europan Campus Rottal-Inn
  • MOBIL
Zeitschriftenartikel
  • Katerina Volchek
  • R. Law
  • D. Buhalis
  • H. Song
Exploring Ways to Improve Personalisation: The Influence of Tourist Context on Service Perception, vol. 17, pg. 1-16.

In: e-Review of Tourism Research

  • 2020
The heterogeneity and dynamic nature of tourist needs requires an advanced understanding of their context. This study aims to investigate the effects of observable factors of internal and external contexts on tourist perceptions towards personalised information services performance. An exploratory approach is used to test measurement invariance and the moderating effects of personal, travel, technical and social parameters of the tourist context, when applicable. The findings demonstrate that contextual factors motivate tourists to attribute different meanings to the parameters of the service, that have already been personalised for them. Individually developed personalisation design solutions are required for each travel context.
  • Europan Campus Rottal-Inn
  • MOBIL
Vortrag
  • Katerina Volchek
The more - the better? The effect of Information of Tourist Perceptions of Personalisation

In: Travel and Tourism Research Association International Conference (TTRA 2020 EUROPE)

  • 2020
  • Europan Campus Rottal-Inn
  • MOBIL
Zeitschriftenartikel
  • Katerina Volchek
  • R. Law
  • D. Buhalis
  • H. Song
The Good, the bad, and the ugly: Tourist perceptions on interactions with personalised content, vol. 16, pg. 62-67.

In: e-Review of Tourism Research

  • 2019
Personalisation is a critical factor in superior customer experience and retention. It is also observed to be acause ofuserfrustration. This paper challenges the assumption that accurate content personalisation always positively affects tourist perceptions on the usefulness and ease of use of the information systems. The study integrates the logic of technology acceptance and the process of human motivation to explain personalised recommender system acceptance. In-depthsemi-structuredinterviews with tourists, industry practitioners, and academic experts were used in research. The findings illustrate that the characteristics of personalised content have double and, sometimes, ambivalent influence on tourist perceptions on system performance. A comprehensive strategy is required to optimise the potential of personalisation. This study expands the understanding of tourist interactions with personalised content and calls for further exploration of the effects of information system components on user experience.
  • Europan Campus Rottal-Inn
  • MOBIL
Zeitschriftenartikel
  • Katerina Volchek
  • A. Liu
  • H. Song
  • D. Buhalis
Forecasting tourist arrivals at attractions: Search engine empowered methodologies, vol. 25, pg. 425-447.

In: Tourism Economics

  • 2019

DOI: 10.1177/1354816618811558

Tourist decision to visit attractions is a complex process influenced by multiple factors of individual context. This study investigates how the accuracy of tourism demand forecasting can be improved at the micro level. The number of visits to five London museums is forecast and the predictive powers of Naïve I, seasonal Naïve, seasonal autoregressive moving average, seasonal autoregressive moving average with explanatory variables, SARMAX-mixed frequency data sampling and artificial neural network models are compared. The empirical findings extend understanding of different types of data and forecasting algorithms to the level of specific attractions. Introducing the Google Trends index on pure time-series models enhances the forecasts of the volume of arrivals to attractions. However, none of the applied models outperforms the others in all situations. Different models’ forecasting accuracy varies for short- and long-term demand predictions. The application of higher frequency search query data allows for the generation of weekly predictions, which are essential for attraction- and destination-level planning.
  • Europan Campus Rottal-Inn
  • MOBIL
Beitrag (Sammelband oder Tagungsband)
  • Katerina Volchek
  • H. Song
  • R. Law
  • D. Buhalis
Forecasting London Museum Visitors Using Google Trends Data
  • 2018
Information search is an indicator of tourist interest in a specificservice and potential purchase decision. User online search patterns are a well-known toolfor forecasting pre-trip consumerbehaviour, such as hotel demand and international tourist arrivals. However, the potential of search engine data for estimating thedemand for tourist attractions, which is created both before and during a trip, remains underexplored. This research note investigates the relationships between Google search queries for the most popular London museums and actual visits to theseattractions. Preliminary findings indicatehigh correlation between monthly series data. Search query data isexpected togenerate reliable forecasts ofvisits toLondon museums.
  • Europan Campus Rottal-Inn
  • MOBIL

Labore

Manager of DigiHealth/ eTourism Lab


Kernkompetenzen

  • Digital Transformation
  • Smart Tourism
  • Marketing and Personalised Experience Design
  • Business Strategy and Innovation Management