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Linear regression pathmox segmentation tree: the case of visitors’ satisfaction to attend a Spanish football match at the stadium

  • Cristina Davino
  • Giuseppe Lamberti

Analysis of a dependency model can be furthered by assessing whether a model and/or the impact of regressors on dependent variables differ if heterogeneity is observed. In other words, it may be interesting to assess differences between a global model estimated for a whole group and models estimated for sub-groups identified on the basis of known categorical variables external to the model, as those variables may identify partitions characterized by dependency structure heterogeneity. This is particularly important in decision-making as policies based on the generic model could yield inaccurate and biased results. In this paper, we propose a procedure, the Pathmox approach that exploits the potential of segmentation trees to identify partitions in an initial set of data characterized by different linear regression patterns. We will apply this new approach to measure the visitors’ satisfaction to attend a Spanish football match at the stadium. Thus, we will analyze the relationship between two significant aspects related to the visitors’ satisfaction: stadium service quality and image of the football team, taking into account five visitors’ background variables as potential sources of heterogeneity: age, gender, if they were tourist (yes or not), if it was the first time at the stadium (yes or not), and level of involvement with the football team. From a decision-making perspective, the paper contributes evidence exemplifying how an apparently representative global model can in fact mask different relationships between variables due to heterogeneous data, underlining the importance of accounting for heterogeneity when defining new policies.

  • Keywords:
  • pathmox,
  • linear regression,
  • segmentation tree,
  • decision making,
  • heterogeneity,
  • visitors satisfaction,
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Cristina Davino

University of Naples Federico II, Italy - ORCID: 0000-0003-1154-4209

Giuseppe Lamberti

Autonomous University of Barcelona, Spain - ORCID: 0000-0002-8666-796X

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  3. Chow, G.C. (1986). Test of equality between sets of coefficients in two linear regressions. Econometrica, 28, pp. 591–605.
  4. Lamberti, G., Aluja, T, Sanchez, G. (2016). The Pathmox approach for PLS path modeling. Applied Stochastic Models in Business and Industry, 32, pp. 453–468.
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  6. Oliver, R.L. (2010) Satisfaction: a behavioral perspective on the consumer. Armonk, NY: M.E. Sharpe.
  7. Zeileis, A., Hornik, K., (2007). Generalized M-fluctuation tests for parameter instability. Statistica Neerlandica, 61, pp. 488–508.
  8. Zeileis, A., Hothorn, T., Hornik, K., (2008). Model-Based Recursive Partitioning. Journal of Computational and Graphical Statistics, 17, pp. 492–514.
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  • Publication Year: 2021
  • Pages: 137-140
  • Content License: CC BY 4.0
  • © 2021 Author(s)

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  • Publication Year: 2021
  • Content License: CC BY 4.0
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Chapter Information

Chapter Title

Linear regression pathmox segmentation tree: the case of visitors’ satisfaction to attend a Spanish football match at the stadium

Authors

Cristina Davino, Giuseppe Lamberti

DOI

10.36253/978-88-5518-461-8.26

Peer Reviewed

Publication Year

2021

Copyright Information

© 2021 Author(s)

Content License

CC BY 4.0

Metadata License

CC0 1.0

Table of Contents

Book Title

ASA 2021 Statistics and Information Systems for Policy Evaluation

Book Subtitle

BOOK OF SHORT PAPERS of the on-site conference

Editors

Alessandra Petrucci, Bruno Bertaccini, Luigi Fabbris

Peer Reviewed

Publication Year

2021

Copyright Information

© 2021 Author(s)

Content License

CC BY 4.0

Metadata License

CC0 1.0

Publisher Name

Firenze University Press

DOI

10.36253/978-88-5518-461-8

eISBN (pdf)

978-88-5518-461-8

eISBN (xml)

978-88-5518-462-5

Series Title

Proceedings e report

Series Issn ISSN

2704-601X

Series E-Issn

2704-5846

20

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