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Events and Festivals Contribution for Local Sustainability

Author

Listed:
  • Leandro Pereira

    (ISCTE Business School, Business Research Unit, 1649-026 Lisbon, Portugal
    Winning Lab., 1750-149 Lisbon, Portugal)

  • Carlos Jerónimo

    (ISCTE Business School, Business Research Unit, 1649-026 Lisbon, Portugal
    Winning Lab., 1750-149 Lisbon, Portugal)

  • Mariana Sempiterno

    (Winning Lab., 1750-149 Lisbon, Portugal)

  • Renato Lopes da Costa

    (ISCTE Business School, Business Research Unit, 1649-026 Lisbon, Portugal)

  • Álvaro Dias

    (ISCTE Business School, Business Research Unit, 1649-026 Lisbon, Portugal
    Department of Center of Politics Research, Economy and Society, Faculty of Social Sciences, Universidade Lusófona de Humanidades e Tecnologias, 1749-024 Lisbon, Portugal)

  • Nélson António

    (ISCTE Business School, Business Research Unit, 1649-026 Lisbon, Portugal)

Abstract

Festivals can improve the image of host communities, making them an appealing destination and boosting local economy. However, it is hard to measure their actual impact, which is a key factor to justify governments’ initiatives. This study aims to verify how accurate direct expenditure analysis can be. First, the impact of new visitors’ expenditure is calculated based on a survey. Then, consumption indicators are used to forecast the actual economic impact of the festival. Finally, both results are compared. Even though the values gathered with consumption indicators are only a lower bound of the festival’s impact, this study found that assessing expenditure intentions during the festival leads to impact estimates that can be three times higher. The theoretical contribution of this study is to identify direct expenditure analysis weaknesses and how to reduce their effects.

Suggested Citation

  • Leandro Pereira & Carlos Jerónimo & Mariana Sempiterno & Renato Lopes da Costa & Álvaro Dias & Nélson António, 2021. "Events and Festivals Contribution for Local Sustainability," Sustainability, MDPI, vol. 13(3), pages 1-8, February.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:3:p:1520-:d:491191
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    References listed on IDEAS

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    1. Della Lucia, Maria, 2013. "Economic performance measurement systems for event planning and investment decision making," Tourism Management, Elsevier, vol. 34(C), pages 91-100.
    2. Attanasi, Giuseppe & Casoria, Fortuna & Centorrino, Samuele & Urso, Giulia, 2013. "Cultural investment, local development and instantaneous social capital: A case study of a gathering festival in the South of Italy," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 47(C), pages 228-247.
    3. Getz, Donald & Page, Stephen J., 2016. "Progress and prospects for event tourism research," Tourism Management, Elsevier, vol. 52(C), pages 593-631.
    4. Barry Burgan & Trevor Mules, 2001. "Reconciling Cost—Benefit and Economic Impact Assessment for Event Tourism," Tourism Economics, , vol. 7(4), pages 321-330, December.
    5. Holt, Charles C., 2004. "Forecasting seasonals and trends by exponentially weighted moving averages," International Journal of Forecasting, Elsevier, vol. 20(1), pages 5-10.
    6. L. Damonte & John Marcis & Thomas Rella, 2013. "Methodology to Reduce Bias in Tourism-Driven Economic Impact Studies," Atlantic Economic Journal, Springer;International Atlantic Economic Society, vol. 41(4), pages 451-452, December.
    7. Holt, Charles C., 2004. "Author's retrospective on 'Forecasting seasonals and trends by exponentially weighted moving averages'," International Journal of Forecasting, Elsevier, vol. 20(1), pages 11-13.
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    Cited by:

    1. Margarida Anjo, Ana & Sousa, Bruno & Santos, Vasco & Lopes Dias, Álvaro & Valeri, Marco, 2021. "Lisbon as a literary tourism site: Εssays of a digital map of Pessoa as a new trigger," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 7, pages 58-67.
    2. Luyi Qiu & Aro I & Timothy J. Lee & Jinok Susanna Kim, 2021. "How Sustainable Social Media Advertising Affect Visitors’ Decision to Attend a Festival Event?," Sustainability, MDPI, vol. 13(17), pages 1-16, August.
    3. Miguel Duarte & Álvaro Dias & Bruno Sousa & Leandro Pereira, 2023. "Lifestyle Entrepreneurship as a Vehicle for Leisure and Sustainable Tourism," IJERPH, MDPI, vol. 20(4), pages 1-13, February.

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