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406 428 24 2 ; S ; [EN] The World Wide Web (WWW) has become the largest repository of information in the world, providing a data stream that grows at the same time as the scope of the Internet does in society. As with most Information and Communication Technologies (ICTs), its digital nature makes it easy for computer programs to analyze it and discover information. This is why it is being increas­ingly explored as a source of new indicators of technology, economics and development. Web-based indicators can be made available on a real-time basis, unlike delayed official data releases. In this paper, we examine the viability of monitoring firm export orientation from automatically retrieved web variables. Our focus on exports is consistent with the role of internationalization in economic development. To evaluate our approach, we first checked to what extent web variables are capable of predicting firm export orientation. Once these new variables are validated, their automated re­trieval is assessed by comparing the predictive performance of two nowcast models: one considering the manually retrieved web variables, the other considering the automatically retrieved ones. Our results evidence that i) web-based variables are good predictors for firm export orientation, and ii) the process of extracting and analyzing such variables can be entirely automated with no significant loss of performance. This way, it is possible to nowcast not only the export orientation of a firm, but also of an economic sector or of a region. This work has been partially supported by the Spanish Ministry of Economy and Competitiveness under grant TIN2013-43913-R, and the Spanish Ministry of Education under grant FPU14/02386. Blazquez, D.; Domenech, J. (2018). Web Data Mining for Monitoring Business Export Orientation. Technological and Economic Development of Economy. 24(2):406-428. https://doi.org/10.3846/20294913.2016.1213193

[EN] The Small Business Act of the European Commission in 2008 acknowledge s the key role of Small and Medium Enterprises (SMEs) in the EU economy. Th is is particularly relevant for Italy, which has the largest share of SMEs in Europe, as well as for other countries such as Portugal, Spain and Greece. On the other hand, SMEs experience more difficulties in their early stages mainly due to high market competition and credit constraints, as highlighted by Fritsch and Weyh (2006). For these reasons, the study of SMEs default risk is always relevant. There are several papers studying firm default factors in a single country (see Ciampi, 2015, Fantazzini and Figini, 2009, Flix and dos Santos, 2018). The literature concentrates mainly on financial indicators built on businesses' balance sheets, which are available about two years late wi th respect to their reference period. This diminishes the significance of the results, both for credit risk and policy aims, and particularly in a forecasting perspective. The purpose of this paper is to provide a preliminary study on a sample of spanish firms selected from the SABI, Sistema de Análisis de Balances Ibéricos, which is listed among Bureau van Dijk databases. The analysis will be carried out according to both parametric and non-parametric discrimination techniques, with the standard construction of a training set on which to build a model and a validation set to test the validity and robustness of the results, and, in the end, the reliability of the model in predicting default. Finally we present a new proposal: a scheme to understand to what ext ent firms' default can be predicted by substituting the traditional data sour ces (offline information) with data collected from their corporate websites (onli ne information) in order to exploit more up-to-date information. ; Crosato, L.; Domenech, J.; Liberati, C. (2020). Predicting SME's default: some old facts and a new idea. Editorial Universitat Politècnica de València. http://hdl.handle.net/10251/149606 ; OCS

AbstractLarge companies increasingly look externally for opportunities to enhance innovation, which has resulted in closer study of innovation systems. We examined the role of service intermediaries (universities, technology centers, and consultants) within these systems using a sample of predominately small‐ and medium‐sized enterprises located in Valencia, Spain. As with studies of large companies, absorptive capacity (e.g., research and development expenditures) was positively related to the likelihood that a firm would engage in service collaborations. However, the rate of collaboration was higher relative to studies dominated by larger companies. Also, there were differences in the pattern of firm characteristics associated with the use of specific services. For example, the level of SME export activity related positively to the use of technology centers, but negatively to university collaborations. Copyright © 2011 ASAC. Published by John Wiley & Sons, Ltd.

[EN] Public policies have encouraged the proliferation of technology platforms that support the transition towards sustainable agriculture and the development of innovations in the food system. Provided the difficulty associated with assessing the outputs and outcomes of technology platforms, this work proposes a practical assessment method based on the retrieval and analysis of online documents related to the technology platforms. Concretely, the method consists of applying web scraping techniques to retrieve documents related to a technology platform from the Internet and then applying web data-mining techniques to automatically classify these documents into the functions that the platform should fulfill, which are described from the viewpoint of co-evolution of innovation. Data are automatically processed to obtain a variety of metrics, which are applied to measure the impact of European Technology Platforms (ETPs) on promoting an organic food paradigm. This method provides time-series data that helps to follow the evolution of the different functions of the platform and to describe its lifecycle. It has been applied to one platform taken as a case study, TP Organics, which represents a key platform for stakeholders that promote organic farming and agroecology as core components of an ambitious program for sustainable agriculture. The obtained online-based measures have been proven to assess the global evolution of the platform, its dissemination through the European Union (EU) Member States, and the evolution of the different functions expected to be fulfilled by it regarding the diffusion and promotion of innovations in organic agriculture. ; This research was partially supported by the Spanish Ministry of Science, Innovation and Universities with grant AGL2015-65897-C3-3-R; and by the Spanish Ministry of Education with grant FPU14/02386. ; Blazquez, D.; Domenech, J.; García Alvarez-Coque, JM. (2018). Assessing Technology Platforms for Sustainability with Web Data Mining Techniques. Sustainability. ...

[EN] The purpose of this paper is to propose an intelligent system to automatically monitor the firms¿ engagement in e-commerce by analyzing online data retrieved from their corporate websites. The design of the proposed system combines web content mining and scraping techniques with learning methods for Big Data. Corporate websites are scraped to extract more than 150 features related to the e-commerce adoption, such as the presence of some keywords or a private area. Then, these features are taken as input by a classification model that includes dimensionality reduction techniques. The system is evaluated with a data set consisting of 426 corporate websites of firms based in France and Spain. The system successfully classified most of the firms into those that adopted e-commerce and those that did not, reaching a classification accuracy of 90.6%. This demonstrates the feasibility of monitoring e-commerce adoption from online data. Moreover, the proposed system represents a cost-effective alternative to surveys as method for collecting e-commerce information from companies, and is capable of providing more frequent information than surveys and avoids the non-response errors. This is the first research work to design and evaluate an intelligent system to automatically detect e-commerce engagement from online data. This proposal opens up the opportunity to monitor e-commerce adoption at a large scale, with highly granular information that otherwise would require every firm to complete a survey. In addition, it makes it possible to track the evolution of this activity in real time, so that governments and institutions could make informed decisions earlier. ; This work has been partially supported by the Spanish Ministry of Economy and Competitiveness with Grant TIN2013-43913-R, and by the Spanish Ministry of Education with Grant FPU14/02386. ; Blazquez, D.; Domenech, J.; Gil, JA.; Pont Sanjuan, A. (2018). Monitoring E-commerce Adoption from Online Data. Knowledge and Information Systems. 1-19. ...

[ES] El sistema universitario en España en su proceso de adaptación al marco de homologación Europeo requiere del esfuerzo de los docentes universitarios quienes en el desarrollo de su labor, se sirven de nuevos instrumentos para la evaluar las competencias de los alumnos universitarios. En este trabajo se presenta una aplicación de la co-evaluación como sistema de evaluación del trabajo colaborativo a una asignatura de Grado de primer curso impartida en la Universitat Politècnica de València ; De La Poza, E.; Domenech, J.; Guadalajara Olmeda, MN.; Mas Verdú, F.; Martinez Gomez, VD.; Barrachina Martínez, I.; Martí Selva, ML. (2014). La co-evaluación como sistema de evaluación del trabajo colaborativo. Editorial Universitat Politècnica de València. 856-865. http://hdl.handle.net/10251/144721 ; S ; 856 ; 865