Identifying explanatory factors of bitcoin price with artificial neural networks

This study aims to develop a new model that allows determining with high precision the factors that explain the price of bitcoin. To do this, an extensive database of variables related to bitcoin and artificial neural network techniques has been used. The results obtained have made it possible to identify that aspects related to the number of forum posts, the volume of transactions on the blockchain, and the hash rate provide an excellent strategy for predicting the price of bitcoi

Improving customer engagement through the determinants of employee engagement

In the field of marketing, an engagement orientation urges companies to co-create a broader range of activities with their customers and requires all employees to commit to the company and understand the value of customers engagement (Harmeling et al., 2017). Several previous studies have focused on how companies can develop customer engagement through marketing and employee engagement (Venkatesan, 2017). However, little research has examined the factors that determine the level of employee engagement in this relationship with the customers. The objective of this research is to identify which variables of the organization, associated with employee engagement, show a relationship or incidence in the customer engagement. To achieve this goal present study uses Radial Basis Function Neural Networks in order to model the behavior of the employee engagement of the selected sample. The results obtained provide significant information on how relationships with stakeholders, and especially customer engagement, can be improved.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Identifying influencing factors on cryptocurrency price: Evidence for bitcoin and ethereum

El presente estudio tiene como objetivo el desarrollo de nuevos modelos para determinar con alta precisión los factores que explican el precio de las principales criptomonedas. Para ello, se ha utilizado una amplia base de datos de variables relacionadas con el bitcoin y el ethereum, y se han aplicado técnicas de redes neuronales artificiales. Los resultados obtenidos han permitido identificar que los aspectos relacionados con el número de publicaciones en foros, el volumen de transacciones en blockchain y la tasa de hash proporcionan una excelente estrategia para predecir el precio del bitcoin. También, que el volumen de transacciones, el tamaño de los bloques, las comisiones de mineros y los precios del petróleo son los mejores predictores del valor de mercado del ethereu

Public Aids Evaluation: Empirical Evidence for Spanish Industrial Companies

The implementation of different forms of public aids for industrial companies is standard practice in all countries to promote economic development and job creation. This study presents a comparative analysis of the effectiveness of different instruments for public aid to industrial companies. Using a wide sample of Spanish companies that have received four types of public aid, it has been possible to verify the effect of each of the public aid on the evolution of the companies´ efficiency. The results obtained suggest that the participative loan is the instrument that improves the efficiency of companies significantly

Public Aids Evaluation: Empirical Evidence for Spanish Industrial Companies

931-934The implementation of different forms of public aids for industrial companies is standard practice in all countries to promote economic development and job creation. This study presents a comparative analysis of the effectiveness of different instruments for public aid to industrial companies. Using a wide sample of Spanish companies that have received four types of public aid, it has been possible to verify the effect of each of the public aid on the evolution of the companies´ efficiency. The results obtained suggest that the participative loan is the instrument that improves the efficiency of companies significantly

The Impact of Social Media on Restaurant Corporations’ Financial Performance

Social media, in the form of online reviews (ORs), has become an essential element for consumers in the restaurant industry, providing reliable and unbiased information based on the dining experiences of other consumers. Social media is not only a crucial phenomenon for the strategy of restaurants, but also for their corporations. However, previous literature has focused on the analysis at the establishment level, rather than at the corporate level, especially when referring to financial performance. The present study tries to verify if social media also affects corporate financial performance. For this, the impact of ORs on advanced measures of financial performance was examined at the corporate level on a sample of 800 restaurants selected from the total population of active restaurants in Europe in 2018. The investigation applied both regression analysis and nonparametric techniques. They demonstrate a positive effect of ORs on financial performance, and a heterogeneous relationship between both variables across the European countries. Restaurants are becoming aware of the implications of this phenomenon since it could provide strategies for sustainable economic development

A Multi-Class Model to Predict the Result of the Legal Insolvency Proceedings

742-745A small number of studies have been carried out to build models with which to predict the results of the insolvency proceedings. In addition, there are no models that have demonstrated a high predictive capacity for all situations in which such legal processes can end. The proposal of this study is the construction of a multi-class model that predicts with high precision the possible future situations of companies that are in legal insolvency proceedings. The results of this study reveal that using the Naive Bayes classifier the model achieves an accuracy of more than 91% and that the best predictors are variables related to the profitability, efficiency and volume of resources generated by the companies