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Graphical diagnostics in proportional odds models—Empirical study on determinants of FinTech payment service diffusion by SMEs in Italy

Author

Listed:
  • Anna Crisci

    (University of Naples Federico II)

  • Luana Serino

    (Università Telematica Pegaso)

  • Francesco Campanella

    (University of Campania “Luigi Vanvitelli”)

Abstract

FinTech, the merging of finance and modern Internet-based technology, has rapidly presented itself as a disruptor to traditional business sector. In this paper, we examine the determinants of the use of FinTech payment services by Italian SMEs, using a conceptual framework based on the technology diffusion theories. In this study we consider the proportional odds model for ordinal logistic regression and we consider different approaches to assessing the goodness of fit of the model. Model diagnostic is an essential element in statistical modeling of business data, since, it helps researcher to re-evaluate their working models in order to inform business strategies. To test the fit of the model and check the assumptions in the ordinal regression model (i.e., misspecification mean structure, proportional, heteroscedasticity, etc.) diagnostic plots based on surrogate residuals are shown. The findings states that the innovation-firm level, firm’size, and a gendered governance positively impact on the Fintech payment services diffusion. The reported findings per the study are strong, robust, and reliable since the various proposed models employed in the study are significantly fit and valid.

Suggested Citation

  • Anna Crisci & Luana Serino & Francesco Campanella, 2024. "Graphical diagnostics in proportional odds models—Empirical study on determinants of FinTech payment service diffusion by SMEs in Italy," Quality & Quantity: International Journal of Methodology, Springer, vol. 58(6), pages 5755-5776, December.
    • Handle: RePEc:spr:qualqt:v:58:y:2024:i:6:d:10.1007_s11135-024-01905-x
    DOI: 10.1007/s11135-024-01905-x
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    References listed on IDEAS

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    1. Dungang Liu & Heping Zhang, 2018. "Residuals and Diagnostics for Ordinal Regression Models: A Surrogate Approach," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 113(522), pages 845-854, April.
    2. Christian Haddad & Lars Hornuf, 2016. "The Emergence of the Global Fintech Market: Economic and Technological Determinants," Research Papers in Economics 2016-10, University of Trier, Department of Economics.
    3. Luana Serino & Armando Papa & Francesco Campanella & Jens Mueller, 2019. "Credit access and performance of Italian firms: how relevant is gender?," International Journal of Managerial and Financial Accounting, Inderscience Enterprises Ltd, vol. 11(3/4), pages 269-289.
    4. Christian Haddad & Lars Hornuf, 2016. "The Emergence of the Global Fintech Market: Economic and Technological Determinants," CESifo Working Paper Series 6131, CESifo.
    5. Cephas Paa Kwasi Coffie & Hongjiang Zhao & Isaac Adjei Mensah, 2020. "Panel Econometric Analysis on Mobile Payment Transactions and Traditional Banks Effort toward Financial Accessibility in Sub-Sahara Africa," Sustainability, MDPI, vol. 12(3), pages 1-20, January.
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