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Consequences of trading hours deregulation. A spatio-temporal object-oriented data model for Madrid region

Author

Listed:
  • Juan Luis Santos

    (Institute for Economic and Social Analysis - IAES)

  • Federico Pablo-Martí

    (University of Alcala)

Abstract

During the summer of 2012 the Commercial Revitalization Act (Ley de Dinamización Comercial) was passed in Madrid region. It allows businesses to open 24 hours a day 365 days a year and start the business activity without a license. In this paper we present the design of a object-oriented data model to study the impact of this measure on the trade according to size and location of the establishment. The database is not only spatial but time is included in the design as a main piece to determine the effects faithfully. The results show a limited extension of time for most establishments and areas as well as a small demand transfer small to larger ones that also occur in a lower degree without the application of this measure.

Suggested Citation

  • Juan Luis Santos & Federico Pablo-Martí, 2014. "Consequences of trading hours deregulation. A spatio-temporal object-oriented data model for Madrid region," Journal of Socioeconomic Engineering, Instituto Universitario de Análisis Económico y Social, issue 1, pages 4-11, June.
  • Handle: RePEc:uae:soceng:y:2014:i:1:p:4-11
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    References listed on IDEAS

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    1. Teller, Christoph & Reutterer, Thomas, 2008. "The evolving concept of retail attractiveness: What makes retail agglomerations attractive when customers shop at them?," Journal of Retailing and Consumer Services, Elsevier, vol. 15(3), pages 127-143.
    2. Mª De Los Llanos Matea Rosa & Juan S. Mora-Sanguinetti, 2012. "Comercio Minorista Y Regulación Autonómica: Efectos En La Densidad Comercial, El Empleo Y La Inflación," Revista de Economia Aplicada, Universidad de Zaragoza, Departamento de Estructura Economica y Economia Publica, vol. 20(2), pages 5-54, Autumn.
    3. Schenk, Tilman A. & Loffler, Gunter & Rauh, Jurgen, 2007. "Agent-based simulation of consumer behavior in grocery shopping on a regional level," Journal of Business Research, Elsevier, vol. 60(8), pages 894-903, August.
    4. Ronald N. Buliung & Pavlos S. Kanaroglou, 2004. "On design and implementation of an object-relational spatial database for activity/travel behaviour research," Journal of Geographical Systems, Springer, vol. 6(3), pages 237-262, October.
    5. Federico Pablo-Martí & Josep-Maria Arauzo-Carod, 2012. "Concentration Analysis Using Microgreographic Data," Advances in Spatial Science, in: Esteban Fernández Vázquez & Fernando Rubiera Morollón (ed.), Defining the Spatial Scale in Modern Regional Analysis, edition 127, chapter 0, pages 311-326, Springer.
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    Cited by:

    1. Ahmed Hamroush & Hassan Tawfik, 2014. "Synchronized Information in the Producer-Consumer Problem," Journal of Socioeconomic Engineering, Instituto Universitario de Análisis Económico y Social, issue 2, pages 25-30, December.

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    More about this item

    Keywords

    deregulation of trading hours; spatio-temporal database; spatial shopping behavior; policy impact;
    All these keywords.

    JEL classification:

    • D12 - Microeconomics - - Household Behavior - - - Consumer Economics: Empirical Analysis
    • D47 - Microeconomics - - Market Structure, Pricing, and Design - - - Market Design
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques

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