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Methodology of stakeholders' behaviour modelling based on time.

Michal Munk1, Anna Pilkova2, Lubomir Benko1

  • 1Constantine the Philosopher University in Nitra, Slovakia.

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This study models bank web portal user behavior using multinomial logit models. Analysis of user activity before and after the financial crisis reveals distinct behavioral patterns.

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Area of Science:

  • Web Analytics
  • Behavioral Economics
  • Statistical Modeling

Background:

  • Understanding web user behavior is crucial for financial institutions.
  • The period 2009-2012 encompasses the financial crisis and its aftermath, offering a unique context for analysis.
  • Existing models may not fully capture the nuances of user behavior in response to economic events.

Purpose of the Study:

  • To develop and present methods for modeling bank web portal user behavior.
  • To analyze changes in user behavior from the financial crisis period (2009-2010) to the post-crisis period (2011-2012).
  • To provide a transferable methodology for web user behavior analysis in other domains.

Main Methods:

  • Data preprocessing including data cleaning, user/session identification, path completion, and variable determination.
  • Application of the multinomial logit model for user behavior modeling.
  • Parameter estimation, logits estimation, and probabilities estimation.

Main Results:

  • The study details a sequence of steps for raw log file preprocessing and user behavior modeling.
  • Empirical and theoretical values were compared for counts, probabilities, and logits to evaluate the model's performance.
  • The methodology allows for the examination of user behavior shifts across different economic periods.

Conclusions:

  • The presented methods offer a robust framework for analyzing web user behavior in the banking sector.
  • The multinomial logit model effectively captures user navigation patterns on a bank's web portal.
  • The findings provide insights into how economic conditions can influence online user engagement.