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Segmenting with big data analytics and Python: A quantitative exploratory analysis of household savings

Author

Listed:
  • Cuomo, Maria Teresa
  • Tortora, Debora
  • Colosimo, Ivan
  • Ricciardi Celsi, Lorenzo
  • Genovino, Cinzia
  • Festa, Giuseppe
  • La Rocca, Michele

Abstract

According to the national balance sheets of the most advanced economies, despite a recent sharp decline in per capita net wealth, Italian private households present a higher rate among the wealthiest and least indebted in Europe. Recently, the COVID-19 outbreak caused a new leap in households' savings worldwide, particularly in advanced economies and Italy. This study underlines that using advanced analytics tools, household saving behaviour information, and big data analytics may support data-driven decision approaches addressing the management of complex relationships in the financial arena. More specifically, using exploratory and predictive analyses based on big data analytics and machine learning, this study aims to provide extensive customer profiling in the household saving sector in Italy, supporting a data-driven decision-making approach. A profiling of household savings has been defined using the information provided by big data analysis. To proceed in this direction, the hardware and software requirements necessary to perform data processing were considered in the first phase of the study. Data collection was performed according to the so-called extract, transform, load (ETL) process. The contribution of this study lies in the results obtained in terms of data analytics over a dataset that accounts for the purchasing behaviour of almost 20 million postal savers. The clustering algorithm is highly efficient and scales well for large datasets. K-means clustering can be implemented within the MapReduce computational framework. Therefore, the overall procedure proposed here can be easily extended to big data using parallel computing and software implementing MapReduce, such as Hadoop and Spark.

Suggested Citation

  • Cuomo, Maria Teresa & Tortora, Debora & Colosimo, Ivan & Ricciardi Celsi, Lorenzo & Genovino, Cinzia & Festa, Giuseppe & La Rocca, Michele, 2023. "Segmenting with big data analytics and Python: A quantitative exploratory analysis of household savings," Technological Forecasting and Social Change, Elsevier, vol. 191(C).
    • Handle: RePEc:eee:tefoso:v:191:y:2023:i:c:s0040162523001166
    DOI: 10.1016/j.techfore.2023.122431
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    References listed on IDEAS

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    1. Venieris, Yiannis P & Gupta, Dipak K, 1986. "Income Distribution and Sociopolitical Instability as Determinants of Savings: A Cross-sectional Model," Journal of Political Economy, University of Chicago Press, vol. 94(4), pages 873-883, August.
    2. Paolo Acciari & Salvatore Morelli, 2020. "Wealth Transfers and Net Wealth at Death: Evidence from the Italian Inheritance Tax Records 1995–2016," NBER Chapters, in: Measuring Distribution and Mobility of Income and Wealth, pages 175-203, National Bureau of Economic Research, Inc.
    3. Annamaria Lusardi, 2008. "Household Saving Behavior: The Role of Financial Literacy, Information, and Financial Education Programs," NBER Working Papers 13824, National Bureau of Economic Research, Inc.
    4. Thaler, Richard H & Shefrin, H M, 1981. "An Economic Theory of Self-Control," Journal of Political Economy, University of Chicago Press, vol. 89(2), pages 392-406, April.
    5. Nicola Fuchs‐Schündeln & Paolo Masella & Hannah Paule‐Paludkiewicz, 2020. "Cultural Determinants of Household Saving Behavior," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 52(5), pages 1035-1070, August.
    6. Elisa Guglielminetti & Concetta Rondinelli, 2021. "Consumption and saving patterns in Italy during Covid-19," Questioni di Economia e Finanza (Occasional Papers) 620, Bank of Italy, Economic Research and International Relations Area.
    7. Miles S. Kimball, 1990. "Precautionary Saving and the Marginal Propensity to Consume," NBER Working Papers 3403, National Bureau of Economic Research, Inc.
    8. OR Attanasio & J Banks, 2001. "The assessment: household saving - issues in theory and policy," Oxford Review of Economic Policy, Oxford University Press and Oxford Review of Economic Policy Limited, vol. 17(1), pages 1-19, Spring.
    9. Milton Friedman, 1957. "A Theory of the Consumption Function," NBER Books, National Bureau of Economic Research, Inc, number frie57-1, March.
    10. Luis Hernández & Carlos Baladrón & Javier M. Aguiar & Belén Carro & Antonio Sánchez-Esguevillas, 2012. "Classification and Clustering of Electricity Demand Patterns in Industrial Parks," Energies, MDPI, vol. 5(12), pages 1-14, December.
    11. Ricardo Bebczuk & Leonardo Gasparini & Noelia Garbero & Julian Amendolaggine, 2015. "Understanding the Determinants of Household Saving: Micro Evidence for Latin America," CEDLAS, Working Papers 0189, CEDLAS, Universidad Nacional de La Plata.
    12. Milton Friedman, 1957. "Introduction to "A Theory of the Consumption Function"," NBER Chapters, in: A Theory of the Consumption Function, pages 1-6, National Bureau of Economic Research, Inc.
    13. Oleg V. Buklemishev, 2020. "Coronavirus crisis and its effects on the economy," Population and Economics, ARPHA Platform, vol. 4(2), pages 13-17, April.
    14. Campbell, John Y & Mankiw, N Gregory, 1990. "Permanent Income, Current Income, and Consumption," Journal of Business & Economic Statistics, American Statistical Association, vol. 8(3), pages 265-279, July.
    15. David Roubaud & Rameshwar Dubey & Cyril Foropon & Angappa Gunasekaran & Stephen J. Childe & Zongwei Luo & Fosso Wamba Samuel, 2018. "Examining the role of big data and predictive analytics on collaborative performance in context to sustainable consumption and production behaviour," Post-Print hal-02051276, HAL.
    16. Chunhui Yuan & Haitao Yang, 2019. "Research on K-Value Selection Method of K-Means Clustering Algorithm," J, MDPI, vol. 2(2), pages 1-10, June.
    17. Gulnur MURADOGLU & Fatma TASKIN, 1996. "Differences In Household Savings Behavior: Evidence From Industrial And Developing Countries," The Developing Economies, Institute of Developing Economies, vol. 34(2), pages 138-153, June.
    18. Lusardi, Annamaria, 1998. "On the Importance of the Precautionary Saving Motive," American Economic Review, American Economic Association, vol. 88(2), pages 449-453, May.
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