The impact of the Covid-19 on Europe economy has been similar to that produced in the 2008 crisis, even with worse long-term consequences. Most governments have implemented recovery plans similar to those that were then implemented. However, there are differences in the economic impact that require different methodologies which focus on the microenvironment. Entrepreneurs' sponsorship may help to recover the current socio-economic situation. Simultaneously, technological progress in Artificial Intelligence and Big Data allows the analysis of vast amounts of information and support decision making. This paper shows a brief introduction of entrepreneurship policy in twenty countries after the irruption of the Covid-19 to contextualize, and applies Artificial Intelligence to examine factors whose influence is strong in the survival rate of entrepreneurs within a public support program. Specifically, two types of artificial networks are used: self-organizing maps and multilayer perceptron (respectively, SOM and MLP). After the application of neural networks on a data set of 2,221 entrepreneurs from Andalusia (Spain) and with 769 variables taken during the recovery after the crisis from 2008 to 2012, the prediction in the probability of entrepreneurial survival and business success is shown to be realistic in more than 98% of individuals analysed.
RESUMEN: Este artículo aborda la problemática de la optimización de los servicios de apoyo a emprendedores como alternativa para afrontar la crisis en las economías desarrolladas, pretendiendo ser un primer paso para obtener una metodología de orientación útil para cualquier entidad de apoyo al emprendimiento. Para ello, se presenta una revisión de la literatura sobre los factores que inciden en la supervivencia de emprendedores y los correspondientes planteamientos metodológi-cos utilizados para modelizar este fenómeno con técnicas de análisis cuantitativo. Posteriormente, se toma una muestra de 1.618 emprendedores, con datos del 2013, en la región de Europa con peores tasas de desempleo en la presente década: Andalucía, en el sur de España; los resultados podrían ser extrapolables a regiones con problemáticas análogas. Este estudio comprueba cómo, a través del análisis multivariante, se pueden conocer mejor los factores que influyen en la supervivencia y reforzar así el servicio de apoyo. Se concluye que resultan particularmente relevantes ciertas variables vinculadas al tipo de servicio de apoyo, como número total de servicios de apoyo en los primeros meses, pasar un proceso previo de preincubación, estar presente en alguna solicitud de incentivos o plan de empleo, así como otras del tipo forma jurídica o ubicación geográfica.PALABRAS CLAVE: análisis multivariante, Andalucía, emprendimiento, supervivencia. IntroducciónAnte una situación socioeconómica adversa en Europa, el primero de los cinco objetivos que se ha planteado dentro de la estrategia política 'Horizonte 2020' es el empleo para el 75% de las personas de 20 a 64 años. Esto Contabilidad y Finanzas RELEVANT FACTORS IN PUBLIC SERVICES OPTIMIZATION TO SUPPORT ENTREPRENEURS AND THE SURVIVAL RATE OF COMPANIESABSTRACT: This article deals with issues related to the optimization of support services for entrepreneurs as an alternative to face crisis in developed economies. This work expects to represent an initial step to obtain a useful guidance methodology for any organization supporting entrepreneurship. For this purpose, a literature review on the factors that affect entrepreneurs' survival is presented, as well as the corresponding methodological approaches used to model this phenomenon by means of quantitative analysis techniques. Using data from 2013, we selected a sample of 1,618 entrepreneurs from the European region with the worst unemployment rates in the current decade: Andalusia, in the south of Spain. Our results could be extrapolated to regions with analogous problems. This study verifies how, through multivariate analysis, the factors that influence survival can be better known, allowing to strengthening support services. It is concluded that certain variables related to the type of support service are particularly relevant, such as the "total number of support services in the first months", "passing through a previous pre-incubation process", "being present in any incentive request or employment plan", and others classified as "legal form" o...
The aim of this paper is to assess the level of success achieved by entrepreneurs. The concept of success has many subjective facets, and it needs to be evaluated to reach other higher objectives, such as improving support systems for entrepreneurs. The usual pre-existing focuses for the evaluation of business performance are analysed and adapted. Based on a real case, the most relevant variables for detecting success are studied and an algorithmic process (based on decision trees) is established to ascertain whether an entrepreneur has achieved success. The data refers to entrepreneurs from Andalusia, the European region with the highest unemployment rates and where support for entrepreneurship is on the agenda of all political parties. The model specifies a minimal set of variables to evaluate success in each case. Subsequently, a simple set of 29 questions is also offered, serving to classify most entrepreneurs (over 98% of 2221 individuals in the case analysed) by their level of success. An objective procedure to measure the success of entrepreneurs is given. Such method is based on artificial intelligence and on three focuses: positioning, expectations and evolution. Both the variables used in this case and the 29 questions necessary to classify the entrepreneurs by their level of success are explicitly provided.
La pandemia de la COVID 19 ha afectado de forma notable a las Universidades, provocando y acelerando cambios que afectan a todos los ámbitos. Entre estas modificaciones, la docencia ha tenido que realizar importantes variaciones metodológicas, asumiendo una mayor presencia tecnológica. En este marco, el objetivo del estudio es analizar el impacto provocado por estos cambios en la asignatura de Estadística Empresarial II (EEII), impartida en las titulaciones del Grado en Administración y Dirección de Empresas (GADE) y el Doble Grado en Derecho y Administración y Dirección de Empresas (XAYD) en la Universidad Pablo de Olavide de Sevilla. Se comprueba que las modificaciones introducidas en la asignatura, provocan un efecto negativo sobre los resultados académicos, tanto en el número de presentados como en el de aprobados. Abstract The COVID-19 pandemic has noticeably affected Universities, provoking and accelerating changes in every field. Among these modifications, teaching has gone through significant methodological changes, assuming a larger technological presence. Regarding this, the main purpose of this paper is to analyze the impact of these alterations on the subject Statistics for Business II, taught in Degree in Business Administration and Management and Double Degree in Business Administration and Management and Law, at Pablo de Olavide University in Seville. The changes introduced in this subject have been proved to negatively affect its academic results, both in the number of students who took the final tests as well as the number of those who passed it.
<p>El propósito de este artículo es proponer un nuevo método para evaluar el nivel de éxito alcanzado por los emprendedores. Si bien el concepto de éxito tiene muchas facetas subjetivas, debe tratar de evaluarse para conseguir objetivos como el de mejorar los sistemas de apoyo al emprendimiento. En un primer paso, se analizan y adaptan los enfoques preexistentes habituales para la evaluación del desempeño de pequeñas empresas. Sobre la base del caso real de la región con las tasas de desempleo más altas de Europa, se estudian las variables más relevantes para detectar el éxito y se establece un proceso algorítmico para determinar si un emprendedor ha logrado o no el éxito. El modelo proporciona un conjunto mínimo de variables para evaluar el desempeño en cada caso particular. También se establece un conjunto simple de preguntas, que sirve para clasificar a la mayoría de los empresarios por su nivel de éxito (se clasifica a más del 98% en el caso analizado).</p>
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