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The economic value of sports increases in importance in today’s society. Sports clubs’ budgets break records every year. The costs of injuries increase together with these remarkable budgets of sports clubs. Several injury prevention programs already exist but no previous programs combine multiple factors through artificial intelligence to predict injury risks. This paper investigates how artificial intelligence can support sports clubs’ health and injury management. Since no previous research is conducted and no data is available to study this subject, a large literature study has been fulfilled. This literature defines the term artificial intelligence and how AI is evolving in the last decade. The current injury prevention practices are also examined through a literature review. Are current programs effective, what are the costs of those programs and how did they changed over time? Interviews with people of different interests in sports were taken to sketch a wide picture of the future of artificial intelligence in sports. Football clubs in Belgium and the Netherlands have started to collect data, but need much more monitored data to be able to use artificial intelligence techniques. Clubs need to invest in tools to measure data more accurate and more frequent. The three phases in artificial intelligence for injury prevention are explained and examples are provided to accelerate the implantation.

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The following pages present an attempt to describe whether there has been a significant change in the efficiency of spending on education in 34 OECD countries between 2006 and 2015 by applying a popular technique in the field - Data Envelopment Analysis. Because countries tend to have a discrepant level of development as they function under divergent conditions, we see it as inadequate to compare all the OECD countries as if they were equals. As a solution, we apply an order-m calculation to avoid the potential disturbance created by outliers and the relatively small sample size. Furthermore, the Malmquest index is calculated for all the analysed years. The following research creates as well a relation to existing literature which is presented in the Annex.

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The purpose of this contribution is twofold. First, a critical assessment of the Ibrahim Index of African Governance (IIAG) is carried out. Subsequently, a detailed methodology is provided to enable a Benefit-of-the-Doubt (BoD) analysis of the IIAG. These two major parts are preceded by background information about Africa, governance and composite indicators in general, and the IIAG in particular. As for the assessment of the IIAG, the results are ambiguous: while the IIAG is found to be fairly well conceived, it is also partially obscured due to the inherent normative nature of governance. There is still no consensus about what governance is, what it does, how it is defined and how it is measured and so on. However, ambiguity should not be perceived as a insurmountable constraint in se, as long as objectivity is pursued within a theoretical framework and confirmed by data. As a result of the aforementioned features, national-performance governance indexes invoked additional criticism on top of the common criticisms on composite indicators. The BoD-approach to the IIAG can be regarded as a reconciling method when there is no consensus on the “relative worth” of certain indicators, sub-categories and categories when combined into a single metric. The multiple-layer Data Envelopment Analysis (DEA) model employed here, allows to derive the weights endogenously (as opposed to paternalistic weighting), and can also be applied for aggregation purposes. A country is assigned its own optimal importance weights for the indicators, sub-categories or categories, to maximize its overall governance score, benchmarked against all 54 other African countries. One could interpret these optimal importance weights as a reflection of implicitly revealed policy priorities. This seems to be additionally substantiated in the current context, as some advocate for “good enough governance” (i.e. selecting a few imperatives from a long list etc.) and country-specific priorities vis à vis the unmanageable “good governance” agenda. In short, at least reflecting these country-specific characteristics and ambiguities when measuring governance using the BoD-approach, could be very instrumental in overcoming certain issues. Moreover, it allows to combat some methodological concerns, inherent to composite indicators. A variety of weight restrictions and aggregation methods were employed. The majority of our models correlated quite well to even excellently with the 2018 IIAG rankings and scores. This might indicate the robustness of the IIAG, and perhaps more importantly, the BoD-approach makes it harder for countries to dispute the weighting and aggregation schemes employed, as more data-driven flexibility is offered.

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This article investigates how the distance between China and the signatories of the One Belt - One Road initiative influences the Chinese outward foreign direct investment location decisions. We identify four dimensions of distance, namely: cultural, administrative, geographic and economic distance, in what constitutes the CAGE framework. Using panel data from 2003-2012 for 50 countries along the One Belt - One Road, an augmented version of the gravity model is built. Our empirical results indicate that administrative distance is negatively associated with China’s outward foreign direct investment. We also find that the Chinese motivations are market seeking and that countries sharing borders with China have been favoured with increased FDI from China. We conclude with suggestions for future research that call for more exhaustive models.

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This paper conduced a panel data regression in the geographical area EU, OECD and BRICS to verify if nuclear energy slows the growth rate of renewables. The timeframe of the regression of this research paper is from 1990-2015. It found confirmatory evidence for one of the two hypotheses. Nuclear electricity production was first found significantly reducing the implementation speed of renewable energy sources as a percentage of electricity production. After using the Driscoll and Kraay estimator comply with the assumptions, nuclear percentage became an insignificant variable in all models reducing the growth rate of renewable energy sources a percentage of electricity production. As a second hypothesis, this research paper found that the CO2 allowance prices do increase the growth rate of the renewable energy sources as a percentage of electricity production in EU compared to the non EU OECD countries and BRICS countries.