A comparison of methods to separate treatment from self-selection effects in an online banking setting

S. Gensler*, P.S.H. Leeflang, B. Skiera

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

10 Citations (Scopus)

Abstract

The literature discusses several methods to control for self-selection effects but provides little guidance on which method to use in a setting with a limited number of variables. The authors theoretically compare and empirically assess the performance of different matching methods and instrumental variable and control function methods in this type of setting by investigating the effect of online banking on product usage. Hybrid matching in combination with the Gaussian kernel algorithm outperforms the other methods with respect to predictive validity. The empirical finding of large self-selection effects indicates the importance of controlling for these effects when assessing the effectiveness of marketing activities. (C) 2012 Elsevier Inc. All rights reserved.

Original languageEnglish
Pages (from-to)1272-1278
Number of pages7
JournalJournal of Business Research
Volume66
Issue number9
DOIs
Publication statusPublished - Sept-2013

Keywords

  • Self-selection effects
  • Matching methods
  • Instrumental variables method
  • Control function method
  • Online use
  • PROPENSITY SCORE
  • INSTRUMENTAL VARIABLES
  • CUSTOMER SATISFACTION
  • DISTRIBUTION CHANNELS
  • WEAK INSTRUMENTS
  • LOYALTY
  • MODELS
  • CRITIQUE
  • BEHAVIOR
  • IMPACT

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