This paper presents a model for measuring intellectual capital (IC) within small and medium-sized enterprises (SMEs) in correlation with the key factors for the successful implementation of knowledge management (KM). Most of the existing IC measurement models are intended to cover general aspects. The kernel of these models could be customized/extended to handle more specific aspects, like KM. The focus of this study is the integration between an IC measurement model and the key factors for successful implementing of KM. The paper identifies, analyses and compares IC elements that are relevant for SMEs and how they can be linked with the IC measurement methods for determining if a company is ready for KM. For this purpose, a general IC measurement model is taken as reference for the study.

Around the world, there are thousands of metal structures completely or partially buried in the soil. The main concern in their design is corrosion. Corrosion is a mechanism that degrades materials and causes structural failures in infrastructures, which can lead to severe effects on the environment and have direct impact on the population health. In addition, corrosion is extremely complex in the underground environment due to the variability of the local conditions. The problem is that there are many methods to its evaluation but none have been clearly established. In order to ensure the useful life of such structures, engineers usually consider an excess thickness that increases the economic cost of manufacturing and does not satisfy the principles of efficiency in the use of resources. In this paper, an extended revision of the existing methods to evaluate corrosion is carried out to optimize the design of buried steel structures according to their service life. Thus, they are classified into two categories depending on the information they provide: qualitative and quantitative methods. As a result, it is concluded that the most exhaustive methodologies for estimating soil corrosion are quantitative methods fed by non-electrochemical data based on experimental studies that measure the mass loss of structures.

Abstract:A balanced scorecard (BSC) framework for a factory that develops software for banking was proposed by us at the end of 2015 to ensure its sustainability, and was focused on improving its productivity and cost. Based on this framework, the aim of this study is to construct an approach using the analytic hierarchy process (AHP) and BSC for evaluating a factory's performance in order for it to become a sustainable business. In this study, AHP is proposed to prioritise and determine weights for the perspectives and indicators included in the BSC for a financial software factory (FSF). The combination of these weights with different indicator measures produces a model that provides an effective assessment tool for FSF managers. The results of the study, which are shown both globally and disaggregated according to the different roles of FSF stakeholders, show that user satisfaction is the main pillar for making decisions. In addition, the result considering roles shows differences according to the relationship of each stakeholder with the software factory. The current study has been validated in a Spanish factory that develops software for several financial entities.

Knowledge of the free draft of ports is essential for the adequate management of ports. To maintain these drafts, it is necessary to carry out dredging periodically, and to conduct bathymetries using traditional techniques, such as echo sounding. However, an echo sounder is very expensive and its accuracy is subject to weather conditions. Thus, the use of recent advancements in remote sensing techniques provide a better solution for mapping and estimating the evolution of the seabed in these areas. This paper presents a cost-effective and practical method for estimating satellite-derived bathymetry for highly polluted and turbid waters at two different ports in the cities of Luarca and Candás in the Principality of Asturias (Spain). The method involves the use of the support vector machine (SVM) technique and open Sentinel-2 satellite imagery, which the European Space Agency has supplied. Models were compared to the bathymetries that were obtained from the in situ data collected by a single beam echo sounder that the Port Service of the Principality of Asturias provided. The most accurate values of the training and testing dataset in Candás, were R2 = 0.911 and RMSE = 0.3694 m, and R2 = 0.8553 and RMSE = 0.4370 m, respectively. The accuracies of the training and testing dataset values in Luarca were R2 = 0.976 and RMSE = 0.4409 m, and R2 = 0.9731 and RMSE = 0.4640 m, respectively. The regression analysis results of the training and testing dataset were consistent. The approaches that have been developed in this work may be included in the monitoring of future dredging activities in ports, especially where the water is polluted, muddy and highly turbid.

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.