Employing of Extended Characteristic Surface Model for Forecasting of Demand in Tourism

Konferenzbeitrag

Extended Characteristic Surface Model (eCSM) is a theoretical tool of general application designed for computing coefficients in stochastic (Monte Carlo) simulations in particular in multi equation stochastic econometric models. Econometric models are most often used for economic analysis of large enterprises as well as national economies but rarely for analysis of the small entities. The reason are very high costs of building and testing of such a large-scale models. However, presented hereby eCSM delivers not so expensive, rather intuitive and flexible method eligible for consumer sentiment analysis and forecasting as well as for "what-if" inferring suitable for entities of all sizes. In particular, it allows for analysis of demand variation resulting from messages concerning competing merchandises. The article is focused on application of eCSM for evaluation of sentiment and forecast of demand in tourism. In the work extended characteristic surface method is explained in thorough details, furthermore influence of factors such as demographic structure, prices or market size on financial outcomes is analyzed on the example of small touristic entity.

Object Details

• Language: Englisch

References and Relationships

• Bibliographic citation: In: Proceedings of the ENTRENOVA - ENTerprise REsearch InNOVAtion Conference, Virtual Conference, 10-12 September 2020 ; Year: 2020 ; Pages: 60-73 ; Zagreb: IRENET - Society for Advancing Innovation and Research in Economy

Classification and Topics

• Classification: Wirtschaft ; Econometrics ; Forecasting Models; Simulation Methods ; Criteria for Decision-Making under Risk and Uncertainty ; Micro-Based Behavioral Economics: Role and Effects of Psychological, Emotional, Social, and Cognitive Factors on Decision Making‡ ; Tourism and Development
• Subject: Sentiment ; Forecasting ; Visualization ; Machine Learning ; Tourism

Contributors, Places and Time

• Event: Geistige Schöpfung
• (who): Opiła, Janusz
• Event: Veröffentlichung
• (who): IRENET - Society for Advancing Innovation and Research in Economy
• (where): Zagreb
• (when): 2020

Further information

• Handle: http://hdl.handle.net/10419/224676
• Last update: 10.03.2025, 11:43 AM CET