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This study contributes to the limited literature on crowdlending by providing a data-driven analysis of the sector. A synthetic DP2 indicator is proposed to identify the leaders of the crowdlending market, the key factors behind their success and the medium-term competitive implications.

The study examines 17 crowdlending platforms and eight performance indicators. The information provided by these indicators is aggregated using a synthetic indicator based on the P₂ Distance (DP2) method.

Mintos, Evoestate, Peerberry, Bondster and Fellow Finance are the leading platforms. This method reveals the key variables in the identification of market leaders, namely year-on-year variation in the number of investors and year-on-year variation in lending per investor. The leaders in terms of lending volumes should not take their current situation for granted. Small and medium-sized platforms are pushing hard and may overtake the incumbents as market leaders.

Financial intermediation through crowdlending is becoming an increasingly popular alternative to traditional models. Changes in the sector are expected in the coming years due to the rise of platforms with a moderate amount of lending and solid year-on-year improvement. To become leaders and to attract both lenders and borrowers, platforms are encouraged to improve the information that they provide.

This paper offers the first analysis of market leadership in the crowdlending sector. It analyses the competitive market of the crowdlending sector based on its actors and key factors. These factors explain the differences in the market position of different platforms. Based on this analysis, the trends in this sector can be identified. This study is exploratory, so it offers empirical data that can be useful in the development of theories that apply to the sector.

In the typical study comparing the evolution of economic inequality among different territorial units, an inequality indicator is chosen, and its value is calculated from sample data. Thus, the problem turns out to be the selection of the inequality indicator.

This paper shows that there is no need for a selection of a single inequality indicator. A whole set of inequality indicators are considered and calculated for the European Countries, using income data from European Community Household Panel (ECHP). The information they provide is then collapsed into a composite inequality indicator, through an adaptation of Principal Component Analysis (PCA). We analyze the conditions needed to make longitudinal comparisons possible. Results obtained with this composite indicator are used to compare and analyze the trends in economic inequality in the EU Countries.

This paper analyzes tourism competitiveness in Latin America, providing a country-level ranking of tourism competitiveness. The study also identifies which areas of management to focus on in order to increase competitiveness in each case.

The study is based on the variables used by the World Economic Forum (WEF) to measure tourism competitiveness. The DP2 distance method is used to create a synthetic indicator. This method helps identify which areas best explain differences in competitiveness between countries.

In tourism, the most competitive Latin American countries are Costa Rica, Chile, Panama, Mexico and Uruguay. The areas that best explain the differences between countries relate to cultural and natural resources, the implementation of information and communication technologies (ICTs), international openness and transport infrastructure. These are therefore priority areas for tourism managers.

This paper provides detailed analysis for each country. The situation in each country is presented in terms of the key areas highlighted by the analysis. This approach can aid the individual decisions of companies and public managers, thus enhancing tourism competitiveness. This greater competitiveness can strengthen the tourism sector, which is crucial in uncertain times.

Based on a synthetic indicator, this research offers the first country-level analysis of tourism competitiveness in Latin America. The study is also novel in its ability to detect the areas where action should be taken to improve tourism competitiveness. This analysis offers an alternative to the WEF Travel and Tourism Competitiveness Index (TTCI), which has certain weaknesses. The results can help enhance tourism competitiveness in Latin American countries through the specific recommendations presented in this paper.

Este documento analiza la competitividad del turismo en América Latina, proporcionando un ranking a nivel país. El estudio también identifica en qué áreas de gestión deben enfocarse los esfuerzos para aumentar la competitividad en cada caso.

La investigación se basa en las variables propuestas por el Foro Económico Mundial (WEF) para medir la competitividad del turismo. El método de distancia DP₂ se utiliza para crear un indicador sintético. Este método ayuda a identificar qué factores explican en mayor medida las diferencias de competitividad entre países.

Los países latinoamericanos más competitivos en cuanto a la actividad turística son Costa Rica, Chile, Panamá, México y Uruguay. Los factores que mejor explican las diferencias entre países se relacionan con los recursos culturales y naturales, la implementación de tecnologías de la información y la comunicación (TIC), la apertura internacional y las infraestructuras de transporte. Por tanto, estas serían las áreas prioritarias de trabajo para los gestores turísticos.

Este documento proporciona un análisis detallado de cada país. La situación individual se presenta mediante un análisis de las áreas clave destacadas como responsables en mayor medida de la competitividad. Este enfoque puede ayudar a las decisiones tomadas por los gestores de las empresas y los administradores públicos, mejorando así la competitividad del turismo. Esta mayor competitividad puede fortalecer el sector turístico, que es crucial en tiempos de incertidumbre.

Basado en un indicador sintético, esta investigación ofrece el primer análisis a nivel país de la competitividad turística en América Latina. El estudio también es novedoso por su capacidad para detectar los ámbitos en los que se debe actuar para mejorar la competitividad turística. Este análisis ofrece una alternativa al Índice de Competitividad de Viajes y Turismo (TTCI) del Foro Económico Mundial (WEF), que tiene ciertas debilidades. Los resultados pueden ayudar a mejorar la competitividad del turismo en los países de América Latina a través de las recomendaciones específicas presentadas en este documento.

The purpose of this paper is to compare the security of oil supply of the 27 European Union (EU27) member countries throughout the measurement of the vulnerability that their economies have exhibited to oil during the period from 1995 to 2007. Additionally, the EU27 future oil vulnerability is to be estimated for two indicative scenarios: a low oil price projection and a high price one. The two projections are going up to 2030.

Six indicators that quantify the core concepts that affect the security of supply of a country have been integrated in a synthetic index that measures the vulnerability of the case study countries for the time period under consideration. For the development of the synthetic index the principal component analysis (PCA) has been applied.

The results of this paper are illustrative of the existing vulnerabilities in the oil supply that may signal for a common EU policy addressing the energy availability risk issue.

The main limitation of the analysis is the usage of six indicators in order to capture the core essence of vulnerability and security of supply. The integration of additional indicators in the synthetic index may strive towards a more precise analysis.

The contribution of the paper lies in the usage of a statistical technique, PCA, for the development of a synthetic index that specifies the vulnerability in oil for EU27.

The aim of this study is to provide a detailed picture of the digitalization propensity and human IT agility of Italian SMEs, verifying whether companies are pursuing coherent and reliable choices for these dimensions and whether digitalization choices affect human IT agility.

Using a POSET approach, this study constructs two nonaggregative multidimensional indicators of human information technology (IT) agility and firms' digitalization. The analysis is based on the microdata provided by ISTAT relating to 4,682 Italian manufacturing companies.

The results show the existence of a strong relationship between digitalization propensity and human IT agility. However, the analysis shows that companies are characterized by a low level of digitalization propensity and human IT agility. At the same time, the findings highlighted that the managerial choices adopted by companies appear to be inconsistent with respect to the two multidimensional indicators.

This study has important implications for managers and policymakers by suggesting acting specific policies to promote a better implementation of digitalization that considers the key role of human IT agility.

This study contributes to the existing literature on organizational agility and digitalization by providing a detailed picture of the Italian manufactured SMEs. At the same time, the POSET approach allows to aggregate a lot of information in one or more indicators without neglecting the value of each dimension faced with the extreme heterogeneity of companies' profiles.

The purpose of this paper is to focus on measuring the contribution generated by social media when used for business purposes, distinguishing between metrics and methods for data collection and data analysis. Organizations worldwide have widely endorsed social media, but available studies on the contribution generated by these technologies for organizations are fragmented. A performance measurement system (PMS) framework to monitor social media is theoretically derived, highlighting the methods for data collection and data analysis and metrics to quantify social media impacts in terms of financials, network structure, interactions, conversations and users’ opinion.

This is a qualitative research based on a literature review of papers in management, information technology, marketing and public relations.

A PMS framework to quantify the contribution of social media is theoretically derived, distinguishing between metrics and methods. PMS metrics support the measurement of the financial and relational impact of social media, as well as the impact of social media conversations and users’ opinions. PMS methods comprise different approaches for data collection and data analysis that range from manual to automated data collection and from content to sentiment analysis techniques.

The PMS framework contributes to the academic literature by integrating a unique model of the available approaches for social media measurement that can serve as a basis for future research directions. The framework also supports practitioners that face necessity to quantify financial and relational contributions of social media as well as the contribution of social media conversation and users’ opinion.

The purpose of this paper is to analyze the informational behavior of a group of future professionals in the field of social sciences (SS), in terms of their competence in the communication–dissemination of information.

The IL-HUMASS, EVALCI/KN and EVALCI/SK tests regarding the affective (attitudes, motivations) and cognitive (knowledge, skills) dimensions are distributed to a stratified sample of five universities and eight degree courses in Spain. Infographics and non-parametric methods allow to compare the disciplinary profiles with regard to gender, academic course and academic degrees. An Information Literacy Communication synthetic indicator based on structural equation modeling includes the subjective and effective dimensions to measure the holistic learning outcomes in communication–dissemination of information.

Significant differences regarding the informational behavior of future professionals in SS are discovered. The synthetic indicator allows academic degrees to be ranked in order to identify those in need of initiatives aimed at improving communication–dissemination competence.

Findings must be taken into account to design effective learning programs. This methodological approach can be expanded to scientific and academic environments.

The paper puts forward the first evidence-based study on communication–dissemination competence among future SS professionals, as no similar research has been found in the scientific literature. It is also the first time that the definition of a predictive performance indicator, based on a powerful statistical methodology, has been proposed.

The purpose of this paper is to establish a synthetic evaluation index system of new socialist countryside (NSC) development at county level in China, and by which to evaluate the level of NSC construction among different regions in China. Then, some problems of rural development can be found and corresponding measures can be proposed, which could provide references for policymaking.

First, from agricultural, rural and farmers' perspective, a preliminary index system which containing 44 indicators was put forward. Then, combining with a series of subjective and objective indicator screening methods, such as fuzzy synthetic evaluation, clustering analysis, correlation and variation coefficient analysis, the final index system containing 22 indicators was established. Third, combining with factor analysis, the final index system was used to evaluate the level of NSC construction in 28 counties of China in 2007. Finally, we calculated district factor scores by a model and gave an aggregate index ranking of different regions.

NSC construction at county level is not well developed in China and there are significant geographical differences among different districts. First, NSC construction in Shanghai, Beijing, Nanjing, Guangzhou and Hangzhou is relatively better. Second, NSC construction of East China is better than that of North China and Central China. Northeast of China is better than Southwest and Northwest. Third, NSC construction in municipalities is higher than non‐municipalities. Rural development in Western regions of China needs to be paid special attention.

A final evaluation index system including 22 indicators was designed. These indicators are complete, independent, weakly correlative and stable. The index system can be further applied to evaluate other regions' NSC development. The evaluation results can provide useful references for NSC reform in the whole nation.

To improve power system peak dispatching ability, connecting energy-storage device such as electric vehicle (EV) and regenerative electric heater (REH) to power grid is a good choice.

This paper establishes a multi-energy combined peak dispatching system MCPDS which includes EV, REH and wind power. The matter-element extension model based on improved variable weight theory is applied to evaluate MCPDS synthetic benefit.

The research shows that the MCPDS established in this paper performs excellently in security benefit, economic benefit, social benefit and environmental benefit.

With the assistance of energy storage devices such as EV and REH, the electrical system peak dispatching ability and power system operation efficiency has improved. More devices with energy-storage ability should be introduced into electrical power system to improve its synthetic benefit.

The objective of this paper is to analyze the relationship between innovation and the development of artificial intelligence (AI) and digital technologies in Europe. The use of digital technologies among European companies is studied through a composite index, while the relationship between innovation and AI is studied through a log-linear regression model. The results of the model have made possible to develop interesting indications for economic and industrial policy.

The use of digital technologies among European companies is studied through a composite index of AI and information technology (ICT) (using the Fair and Sustainable Welfare methodology) with the aim of measuring territorial gaps and to know which European countries are more or less inclined to its use, while the relationship between innovation and AI is studied through a log-linear regression model.

In the paper, two different methodologies were used to analyze the relationship between innovation and the development of digital technologies in Europe. The synthetic indicator made possible to develop a taxonomy between the different countries, the log-linear model made possible to identify and explain the determinants of innovation.

The description of the biunivocal relationship between innovation and AI is a topical and relevant issue that is treated in the paper in an original way using a synthetic indicator and a log-linear model.

本文旨在探討在歐洲、創新與人工智能和數字技術的發展之間的關係。研究人員透過一個綜合指數、去探討歐洲公司之間數字技術的使用狀況。至於創新與人工智能之間的關係, 則以對數線性回歸模型來進行研究。從模型所得的結果, 為我們提供了建議、去訂定適切的經濟和產業政策。

研究人員透過一個人工智能和資訊科技的綜合指數, 去探討歐洲企業之間數字技術的使用狀況 (研究人員使用了公平和可持續福利方法論), 其目標為測量領土差距, 以及確定哪些歐洲國家、大體上傾向於使用數字技術;至於創新與人工智能之間的關係, 則以對數性回歸模型來進行研究。

本文使用了兩個不同的方法、去探討在歐洲、創新與數字技術發展之間的關係。有關的合成指標, 使研究人員可製定一個不同國家間的分類法;而有關的對數線性模型, 則讓研究人員可確立並說明創新的決定因素。

本文使用了合成指標和對數線性模型、去探討創新與人工智能之間的一對一的關係, 這是時下受到關注和適宜的課題;就研究法而言, 本研究確是新穎獨創的。