La supervivencia en las empresas turísticas españolas: un estudio económico-contable

  1. Rubén Lado-Sestayo 1
  2. Milagros Vivel-Búa 1
  3. María Amparo Centeno-Carballido 2
  4. Andrea Martínez-Salgueiro 3
  1. 1 Universidade de Santiago de Compostela
    info

    Universidade de Santiago de Compostela

    Santiago de Compostela, España

    ROR https://ror.org/030eybx10

  2. 2 Universidade da Coruña
    info

    Universidade da Coruña

    La Coruña, España

    ROR https://ror.org/01qckj285

  3. 3 Universidade de Vigo
    info

    Universidade de Vigo

    Vigo, España

    ROR https://ror.org/05rdf8595

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Revista:
Revista de Contabilidad y Tributación. CEF

ISSN: 2695-6896,  2792-8306

Año de publicación: 2024

Número: 492

Páginas: 233-258

Tipo: Artículo

DOI: 10.51302/RCYT.2024.19297 DIALNET GOOGLE SCHOLAR

Otras publicaciones en: Revista de Contabilidad y Tributación. CEF

Resumen

Este artículo analiza la supervivencia empresarial y sus determinantes en el sector turístico espa-ñol durante el periodo 2018-2021. En particular, se analiza una muestra de empresas del ámbito hotelero y de restauración localizadas en España y durante un periodo de pandemia generado por el virus SARS-CoV-2. Al mismo tiempo, esta investigación considera como factores determinantes tanto variables a nivel de empresa como variables a nivel del destino turístico donde se ubican. Los resultados muestran que ambos tipos de variables son relevantes en el estudio de la supervivencia empresarial, si bien su significatividad e importancia es diferente en algunos casos en función de la naturaleza del negocio, esto es, entre hoteles y restaurantes.

Referencias bibliográficas

  • Altman, E. I. (1968). Financial Ratios, Discriminant Analysis and the Prediction of Corporate Bankruptcy. The Journal of Finance, 23(4), 589-609.
  • Barros, C. P., Butler, R. y Correia, A. (2010). The Length of Stay of Golf Tourism: A Survival Analysis. Tourism Management, 31(1), 13-21.
  • Beaver, W. H. (1966). Financial Ratios as Predictors of Failure. Journal of Accounting Research, 4, 71-111.
  • Billor, N., Hadi, A. S. y Velleman, P. F. (2000). BACON: Blocked Adaptive Computation-ally Efficient Outlier Nominators. Computational Statistics & Data Analysis, 34(3), 279-298.
  • Brouder, P. y Eriksson, R. (2013). Staying Power: What Influences Micro-Firm Survival in Tourism? Tourism Geographies: An International Journal of Tourism Space, Place and Environment, 15(1), 125-144.
  • Chen, M.-H. (2013). Risk Determinants of China's Hotel Industry. Tourism Economics, 19(1), 77-99.
  • Diakomihalis, M. (2012). The Accuracy of Altman's Models in Predicting Hotel Bankruptcy. International Journal of Accounting and Financial Reporting, 2(2), 96-113.
  • El Kalak, I. y Hudson, R. (2016). The Effect of Size on the Failure Probabilities of Smes: An Empirical Study on the US Market Using Discrete Hazard Model. International Review of Financial Analysis, 43, 135-145.
  • Falk, M. (2013). A Survival Analysis of Ski Lift Companies. Tourism Management, 36(1), 377-390.
  • Fitzpatrick, P. (1932). A Comparison of the Ratios of Successful Industrial Enterprises with Those of Failed Companies. The Accountants Publishing Company, 6, 727-731.
  • Flagestad, A. y Hope, C. A. (2001). Strategic Success in Winter Sports Destinations: A Sustainable Value Creation Perspective. Tourism Management, 22(5), 445-461.
  • Gémar, G., Moniche, L. y Morales, A. J. (2016). Survival Analysis of the Spanish Hotel Industry. Tourism Management, 54(1), 428-438.
  • Getis, A. y Ord, J. K. (1992). The Analysis of Spatial Association by Use of Distance Statistics. Geographical Analysis, 24(3), 189-206.
  • Gu, Z. (2002). Analyzing Bankruptcy in the Restaurant Industry: A Multiple Discriminant Model. International Journal of Hospitality Management, 21(1), 25-42.
  • Gu, Z. y Gao, L. (2000), A Multivariate Model for Predicting Business Failures of Hos-pitality Firms. Tourism and Hospitality Research, 2(1), 37-49.
  • Gu, Z. y Kim, H. (2003). An Examination of the Determinants of Hotel REITs' Unsystem-atic Risk. Journal of Hospitality & Tourism Research, 27(2), 166-184.
  • Heracleous, L. y Werres, K. (2016). On the Road to Disaster: Strategic Misalignments and Corporate Failure. Long Range Planning, 49(4), 491-506.
  • Hostelería de España (2022). Anuario de la hostelería de España. https://www.cetex.es/wp-content/uploads/2022/12/ANU-ARIO-HOSTELERIA-2022.pdf
  • Hsu, L. T. J. y Jang, S. S. (2008). Advertising Expenditure, Intangible Value and Risk: A Study of Restaurant Companies. International Journal of Hospitality Management, 27(2), 259-267.
  • Kalnins, A. y Chung, W. (2006). Social Capital, Geography, and Survival: Gujarati Immigrant Entrepreneurs in the US Lodging Industry. Management Science, 52(2), 233-247.
  • Kaniovski, S. y Peneder, M. (2008). Deter-minants of Firm Survival in the Austrian Accommodation Sector. Tourism Economics, 14(3), 527-543.
  • Kim, H. (2011). Prediction of Hotel Bankruptcy Using Support Vector Machine, Artificial Neural Network, Logistic Regression, and Multivariate Discriminant Analysis. The Service Industries Journal, 31(3), 441-468.
  • Kim, H. y Gu, Z. (2006a). A Logistic Regression Analysis for Predicting Bankruptcy in the Hospitality Industry. The Journal of Hospitality Financial Management, 14(1), 17-34.
  • Kim, H. y Gu, Z. (2006b). Predicting Restaurant Bankruptcy: A Logit Model in Comparison with a Discriminant Model. Journal of Hospitality & Tourism Research, 14(1), 474-493.
  • Kim, H., Kim, J. y Gu, Z. (2012). An Examination of US Hotel Firms' Risk Features and their Determinants of Systematic Risk. International Journal of Tourism Research, 14(1), 28-39.
  • Kim, W. G., Ryan, B. y Ceschini, S. (2007). Factors Affecting Systematic Risk in the US Restaurant Industry. Tourism Economics, 13(2), 197-208.
  • Lado-Sestayo, R., Vivel-Búa, M. y Otero-González, L. (2016). Survival in the Lodging Sector: An Analysis at the Firm and Location Levels. International Journal of Hospitality Management, 59, 19-30.
  • Li, H. y Sun, J. (2012). Forecasting Busi-ness Failure: The Use of Nearest-Neigh-bour Support Vectors and Correcting Imbalanced Samples. Evidence from the Chinese Hotel Industry. Tourism Management, 33(1), 622-634.
  • Li, H., Li, J., Chang, P. y Sun, J. (2013). Parametric Prediction on Default Risk of Chi-nese Listed Tourism Companies by Using Random Oversampling, Isomap, and Locally Linear Embeddings on Imbalanced Samples. International Journal of Hospitality Management, 35(1), 141-151.
  • Martin, D. (1977). Early Warning of Bank Failure: A Logit Regression Approach. Journal of Banking & Finance, 1(3), 249-276.
  • Mellahi, K. y Wilkinson, A. (2004). Organizational Failure: A Critique of Recent Research and a Proposed Integrative Framework. International Journal of Management Reviews, 5(1), 21-41.
  • Moulton, W. N., Thomas, H. y Pruett, M. (1996). Business Failure Path Ways: Environmental Stress and Organizational Response. Journal of Management, 22(4), 571-595.
  • Ohlson, J. A. (1980). Financial Ratios and the Probabilistic Prediction of Bankruptcy. Journal of Accounting Research, 18, 109-131.
  • OIT (2017). Pautas de la OIT sobre trabajo decente y turismo socialmente responsable. Departamento de Políticas Sectoriales.
  • Olsen, M., Bellas, C. y Kish, L. V. (1983). Improving the Prediction of Restaurant Failure through Ratio Analysis. International Journal of Hospitality Management, 2(4), 187-193.
  • Park, S. S. y Murat, H. (2012). A Comparative Study of Logit and Artificial Neural Networks in Predicting Bankruptcy in the Hospitality Industry. Tourism Economics: The Business and Finance of Tourism and Recreation, 18(2), 311-338.
  • Serrano, C. y Martín, B. (1993). Predicción de la crisis bancaria mediante el empleo de redes neuronales artificiales. Revista Española de Financiación y Contabilidad, 22(74), 153-176.
  • Smith, R. y Winakor, A. (1935). Changes in Financial Structure of Unsuccessful Industrial Corporations. Bureau of Business Research, 51.
  • Tascón, M. T. y Gutiérrez, F. J. C. (2012). Variables y modelos para la identificación y predicción del fracaso empresarial: Revisión de la investigación empírica reciente/Variables and Models for the Identifi-cation and Prediction of Business Failure: Revision of Recent Empirical Research Advances. Revista de Contabilidad/SpanishAccounting Review, 15(1), 7-58.
  • Tavlin, E. M., Moncarz, E. y Dumont, D. (1989). Financial Failure in the Hospitality Industry. FIU Review, 7(1), 55-75.
  • UNWTO (2020). World Tourism Barometer/Barómetro OMT del Turismo Mundial. https://doi.org/10.18111/wtobarometeresp
  • Vivel-Búa, M. y Lado-Sestayo, R. (2021). Contagion Effect on Business Failure: A Spatial Analysis of the Hotel Sector. Journal of Hospitality & Tourism Research, 47(3), 482-502.
  • Vivel-Búa, M., Lado-Sestayo, R. y Otero-González, L. (2018). Risk Determinants in the Hotel Sector: Risk Credit in MSMEs. International Journal of Hospitality Management, 70, 110-119.
  • Vivel-Búa, M., Lado-Sestayo, R. y Otero-González, L. (2019). Influence of Firm Characteristics and the Environment on Hotel Survival across MSMEs Segments During the 2007-2015 Period. Tourism Management, 75, 477-490.
  • Youn, H. y Gu, Z. (2010a). Predict US Restaurant Firm Failures: The Artificial Neural Network Model versus Logistic Regression Model. Tourism and Hospitality Research, 10(3), 1-17.
  • Youn, H. y Gu, Z. (2010b). Predicting Korean Lodging Firm Failures: An Artificial Neural Network Model along with a Logistic Regression Model. International Journal of Hospitality Management, 29(1), 120-127.
  • Zmijewski, M. (1984). Methodological Issues Related to the Estimation of Financial Distress Prediction Models. Journal of Accounting Research, 22(1), 59-82.
Fuente de los datos: Dialnet