The largest project managers and adjudicators of a country, both by number of projects and by cost, are public procurement agencies. Therefore, knowing and characterising public procurement announcements (tenders) is fundamental for managing public resources well. This article presents the case of public procurement in Spain, analysing a dataset from 2012 to 2018: 58,337 tenders with a cost of 31,426 million euros. Many studies of public procurement have been conducted globally or theoretically, but there is a dearth of data analysis, especially regarding Spain. A quantitative, graphical, and statistical description of the dataset is presented. Mainly, the analysis is of the relation between the award price and the bidding price. An award price estimator is proposed that uses the random forest regression method. A good estimator would be very useful and valuable for companies and public procurement agencies. It would be a key tool in their project management decision making. Finally, a similar analysis, employing a dataset from European countries, is presented to compare and generalise the results and conclusions. Hence, this is a novel study which fills a gap in the literature.

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Recommending the identity of bidders in public procurement auctions (tenders) has a significant impact in many areas of public procurement, but it has not yet been studied in depth. A bidders recommender would be a very beneficial tool because a supplier (company) can search appropriate tenders and, vice versa, a public procurement agency can discover automatically unknown companies which are suitable for its tender. This paper develops a pioneering algorithm to recommend potential bidders using a machine learning method, particularly a random forest classifier. The bidders recommender is described theoretically, so it can be implemented or adapted to any particular situation. It has been successfully validated with a case study: an actual Spanish tender dataset (free public information) which has 102,087 tenders from 2014 to 2020 and a company dataset (nonfree public information) which has 1,353,213 Spanish companies. Quantitative, graphical, and statistical descriptions of both datasets are presented. The results of the case study were satisfactory: the winning bidding company is within the recommended companies group, from 24% to 38% of the tenders, according to different test conditions and scenarios.

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The public procurement process plays an important role in the efficient use of public resources. In this context, the evaluation of machine learning techniques that are able to predict the award price is a relevant research topic. In this paper, the suitability of a representative set of machine learning algorithms is evaluated for this problem. The traditional regression methods, such as linear regression and random forest, are compared with the less investigated paradigms, such as isotonic regression and popular artificial neural network models. Extensive experiments are conducted based on the Spanish public procurement announcements (tenders) dataset and employ diverse error metrics and implementations in WEKA and Tensorflow 2.

En el presente estudio se examinarán las principales ventajas que conlleva la nueva regulación de la prueba preconstituida como medio de facilitar la declaración de las víctimas menores de edad y con discapacidad necesitadas de especial protección en el marco del proceso penal, con la finalidad de prevenir su victimización secundaria, y proteger la calidad de su testimonio. Y con este propósito, analizaremos el nuevo articulado de la Ley de Enjuiciamiento Criminal tras la reforma llevada a cabo por la Ley Orgánica 8/2021, de 4 de junio, de protección integral a la infancia y adolescencia frente a la violencia. Evaluándose a partir de la más reciente jurisprudencia, en qué medida los presupuestos y requisitos legalmente exigidos permiten garantizar en estos supuestos, que la práctica de la declaración se desarrolla conciliando el interés superior del menor con el derecho del acusado a un proceso justo con todas las garantías.

En este número del boletín se presentan los resultados de un estudio sobre la violencia en la pareja en un ámbito no abordado hasta el momento en España: las parejas universitarias. Este estudio ha surgido en el seno del proyecto de investigación que bajo el título «Estudio penal y criminológico de la violencia doméstica» se desarrolla de forma conjunta por el Departamento de Derecho Penal y el I.A.I.C. de la Universidad de Sevilla, subvencionado por el Ministerio de Educación y Ciencia.

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