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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

  1. Ahrholdt, D.C., Gudergan, S.P. and Ringle, C.M. (2017). Enhancing service loyalty: the roles of delight, satisfaction, and service quality. Journal of Travel Research, 56, pp. 436–450.
  2. Beccarini, C., and Ferrand, A. (2006). Factors affecting soccer club season ticket holders’ satisfaction: the Influence of club image and fans’ motives. European Sport Management Quarterly, 6(1), pp. 1–22.
  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.
  5. Lebart, L., Morineau, A, Feenelon, J.P.(1979). Traitement des donnees statistiques. Dunod, Paris.
  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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  • Anno di pubblicazione: 2021
  • Pagine: 137-140

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  • Anno di pubblicazione: 2021

Informazioni sul capitolo

Titolo del capitolo

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

Autori

Cristina Davino, Giuseppe Lamberti

Lingua

English

DOI

10.36253/978-88-5518-461-8.26

Opera sottoposta a peer review

Anno di pubblicazione

2021

Copyright

© 2021 Author(s)

Licenza d'uso

CC BY 4.0

Licenza dei metadati

CC0 1.0

Informazioni bibliografiche

Titolo del libro

ASA 2021 Statistics and Information Systems for Policy Evaluation

Sottotitolo del libro

BOOK OF SHORT PAPERS of the on-site conference

Curatori

Bruno Bertaccini, Luigi Fabbris, Alessandra Petrucci

Opera sottoposta a peer review

Anno di pubblicazione

2021

Copyright

© 2021 Author(s)

Licenza d'uso

CC BY 4.0

Licenza dei metadati

CC0 1.0

Editore

Firenze University Press

DOI

10.36253/978-88-5518-461-8

eISBN (pdf)

978-88-5518-461-8

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978-88-5518-462-5

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Proceedings e report

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2704-601X

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2704-5846

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