Emilio Mendez Suarez

Personal Details

First Name:	Emilio
Middle Name:	Mendez
Last Name:	Suarez
Suffix:
RePEc Short-ID:	psu625
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Citations

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Working papers

1. Alcaraz, J.M. & Susaeta, L. & Suárez, E. & Colon, C. & Gutierrez, I. & Cunha, R. & Leguizamón, F. & Idrovo, S. & Weisz, N. & Correia, M. & Pin , José Ramón, 2015. "The Human Resources Contribution to Social Responsibility and Environmental Sustainability: Explorations from Ibero-America," IESE Research Papers D/1114, IESE Business School.

   Cited by:

   1. Pedraja Rejas, Liliana & Rodríguez Ponce, Emilio & Muñoz Fritis, Camila, 2022. "Human resource management and performance in Ibero-America: Bibliometric analysis of scientific production," Cuadernos de Gestión, Universidad del País Vasco - Instituto de Economía Aplicada a la Empresa (IEAE).

2. Gutierrez, I. & Alcaraz, J.M. & Susaeta, L. & Suarez, E. & Pin , José Ramón, 2015. "Managing Sustainability for Competitive Advantage: Evidence From the Hospitality Industry," IESE Research Papers D/1115, IESE Business School.

   Cited by:

   1. Vincenzo Formisano & Bernardino Quattrociocchi & Maria Fedele & Mario Calabrese, 2018. "From Viability to Sustainability: The Contribution of the Viable Systems Approach (VSA)," Sustainability, MDPI, vol. 10(3), pages 1-17, March.
   2. Vitor Pereira & Graça Miranda Silva & Álvaro Dias, 2021. "Sustainability Practices in Hospitality: Case Study of a Luxury Hotel in Arrábida Natural Park," Sustainability, MDPI, vol. 13(6), pages 1-21, March.

Articles

1. Farzan Aminian & E. Suarez & Mehran Aminian & Daniel Walz, 2006. "Forecasting Economic Data with Neural Networks," Computational Economics, Springer;Society for Computational Economics, vol. 28(1), pages 71-88, August.

   Cited by:

   1. Panayotis G. Michaelides & Efthymios G. Tsionas & Angelos T. Vouldis & Konstantinos N. Konstantakis & Panagiotis Patrinos, 2018. "A Semi-Parametric Non-linear Neural Network Filter: Theory and Empirical Evidence," Computational Economics, Springer;Society for Computational Economics, vol. 51(3), pages 637-675, March.
   2. Oscar Claveria & Enric Monte & Salvador Torra, 2017. "“Regional tourism demand forecasting with machine learning models: Gaussian process regression vs. neural network models in a multiple-input multiple-output setting”," AQR Working Papers 201701, University of Barcelona, Regional Quantitative Analysis Group, revised Jan 2017.
      • Oscar Claveria & Enric Monte & Salvador Torra, 2017. "“Regional tourism demand forecasting with machine learning models: Gaussian process regression vs. neural network models in a multiple-input multiple-output setting"," IREA Working Papers 201701, University of Barcelona, Research Institute of Applied Economics, revised Jan 2017.
   3. Dan Farhat, 2012. "Artificial Neural Networks and Aggregate Consumption Patterns in New Zealand," Working Papers 1205, University of Otago, Department of Economics, revised Dec 2012.
   4. Mostafa, Mohamed M. & Nataraajan, Rajan, 2009. "A neuro-computational intelligence analysis of the ecological footprint of nations," Computational Statistics & Data Analysis, Elsevier, vol. 53(9), pages 3516-3531, July.
   5. Dan Farhat, 2014. "Artificial Neural Networks and Aggregate Consumption Patterns in New Zealand:," Working Papers 1404, University of Otago, Department of Economics, revised Mar 2014.
   6. Robert G. Biscontri, 2012. "A Radial Basis Function Approach To Earnings Forecast," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 19(1), pages 1-18, January.
   7. Peter Sarlin & Dorina Marghescu, 2011. "Neuro‐Genetic Predictions Of Currency Crises," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 18(4), pages 145-160, October.
   8. Roman Matkovskyy & Taoufik Bouraoui, 2019. "Application of Neural Networks to Short Time Series Composite Indexes: Evidence from the Nonlinear Autoregressive with Exogenous Inputs (NARX) Model," Post-Print hal-02155402, HAL.
      • Roman Matkovskyy & Taoufik Bouraoui, 2019. "Application of Neural Networks to Short Time Series Composite Indexes: Evidence from the Nonlinear Autoregressive with Exogenous Inputs (NARX) Model," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 17(2), pages 433-446, June.
   9. Mostafa, Mohamed M. & El-Masry, Ahmed A., 2016. "Oil price forecasting using gene expression programming and artificial neural networks," Economic Modelling, Elsevier, vol. 54(C), pages 40-53.
   10. Oscar Claveria & Enric Monte & Salvador Torra, 2016. "Modelling cross-dependencies between Spain’s regional tourism markets with an extension of the Gaussian process regression model," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 7(3), pages 341-357, August.
   11. Tiago E. Pratas & Filipe R. Ramos & Lihki Rubio, 2023. "Forecasting bitcoin volatility: exploring the potential of deep learning," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 13(2), pages 285-305, June.
   12. Sarat Chandra Nayak & Bijan Bihari Misra, 2019. "A chemical-reaction-optimization-based neuro-fuzzy hybrid network for stock closing price prediction," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 5(1), pages 1-34, December.
   13. Dan Farhat, 2014. "Information Processing, Pattern Transmission and Aggregate Consumption Patterns in New Zealand:," Working Papers 1405, University of Otago, Department of Economics, revised Mar 2014.

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