Dynamic performance evaluation of aerospace industry actors in Belgium

status: accepte

Efficiency measurement of R&D firms: a size perspective

status: accepte

Geographical proximity and economic performance of space industry actors in Belgium

status: accepte

Robust performance evaluation of Belgian R&D firms with missing data

status: publishe

Environmental performance assessment in the transport sector using nonparametric frontier analysis:A literature review

The increasing environmental issues relating to carbon dioxide emissions are a primary concern globally and have triggered excessive research to investigate possible ways to reduce such emissions, especially in the transport sector, as initiated by Sustainable Development Goal (SDG) 13. This study investigates the importance of the nonparametric frontier analysis methodology, particularly Data Envelopment Analysis, in measuring environmental performance in the transport sector, emphasising how EU countries are working on meeting the recommendations of SDG 13. Researchers and policymakers have indisputably identified the transport sector as the primary source of global emissions. This paper aims to underline the significant environmental trends in the transport sector, including research topics, key works, research methods, future research direction, and recommendations to explore possible global or regional research agendas. In this regard, we mainly focus on various techniques used to measure the environmental performance within the transport sector. This research considers 186 articles from 46 journals. The survey's main findings show the ever-increasing attention paid to studying the transport sector's emissions, emphasising road and passenger car CO2 emissions as the major source of emissions in the transport sector. In the existing literature, the top three frequently adopted methodologies for measuring environmental performance in transportation include Data Envelopment Analysis, emission analysis, and simulation. This study shows research gaps and future directions on environmental performance assessment within the transport sector, particularly maritime and aviation.<br/

A fuzzy decision support system for credit scoring

Credit score is a creditworthiness index, which enables the lender (bank and credit card companies) to evaluate its own risk exposure toward a particular potential customer. There are several credit scoring methods available in the literature, but one that is widely used is the FICO method. This method provides a score ranging from 300 to 850 as a fast filter for high-volume complex credit decisions. However, it falls short in the aspect of a decision support system where revised scoring can be achieved to reflect the borrower’s strength and weakness in each scoring dimension, as well as the possible trade-offs made to maintain one’s lending risk. Hence, this study discusses and develops a decision support tool for credit score model based on multi-criteria decision-making principles. In the proposed methodology, criteria weights are generated by fuzzy AHP. Fuzzy linguistic theory is applied in AHP to describe the uncertainties and vagueness arising from human subjectivity in decision making. Finally, drawing from the risk distance function, TOPSIS is used to rank the alternatives based on the least risk exposure. A sensitivity analysis is also demonstrated by the proposed fuzzy AHP-TOPSIS method