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I. INTRODUCTION A typical shortcoming of most current credit portfolio models is the lack of a stochastic modeling of risk factors, such as interest rates or credit spreads, during the revaluation process at the risk horizon. For example, fixed income instruments, such as bonds or loans, are revalued at the risk horizon using the current forward rates and (rating class specific) forward credit spreads for discounting future cash flows. Hence, the stochastic nature of the instrument's value in the future which results from changes in factors other than credit quality is ignored, and the riskiness of the credit portfolio at the risk horizon is underestimated. A further consequence is that correlations between changes of the debtor's default probability and changes of market risk factors and, hence, the exposure at default cannot be integrated into the credit portfolio model. This drawback is especially relevant for portfolios of defaultable market‐driven derivatives. One reason why risk factors not directly related to credit risk are neglected in most current credit portfolio models is that there is still no commonly accepted approach for modeling the credit quality of a debtor and the dependencies between the credit quality changes of different debtors. Hence, it might be over‐ambitious to incorporate correlations between market risk factors and credit quality changes. Even empirical evidence on the sign of the correlation remains inconclusive. Additionally, introducing stochastic market risk factors and modeling the correlation between these risk factors and credit quality changes would significantly increase the computational burden for calculating robust risk measures of credit portfolios.

Although the Boolean combination of keywords and/or subject codes is the predominant access method for the retrieval of passages from full‐text databases, menu access is an attractive alternative. The selection of an access method and the ensuing satisfaction with the results is based on the type of query and on the experience and knowledge of the user. This paper describes a prototype system which has integrated Boolean, menu, and direct access methods for the retrieval of passages from full‐text databases. The integration is based on the hierarchical structure inherent in such databases as legal statutes and regulations and engineering standards. The user may switch freely among access methods in order to develop the most appropriate search strategy. The retrieved passages are presented to the user within the context of the hierarchical structure.

Full‐text documents are usually searched by means of a Boolean retrieval algorithm that requires the user to specify the logical relationships between the terms of a query. In this paper, we summarise the results to date of a continuing programme of research at the University of Sheffield to investigate the use of nearest‐neighbour retrieval algorithms for full‐text searching. Given a natural‐language query statement, our methods result in a ranking of the paragraphs comprising a full‐text document in order of decreasing similarity with the query, where the similarity for each paragraph is determined by the number of keyword stems that it has in common with the query. A full‐text document test collection has been created to allow systematic tests of retrieval effectiveness to be carried out. Experiments with this collection demonstrate that nearest‐neighbour searching provides a means for paragraph‐based access to full‐text documents that is of comparable effectiveness to both Boolean and hypertext searching and that index term weighting schemes which have been developed for the searching of bibliographical databases can also be used to improve the effectiveness of retrieval from full‐text databases. A current project is investigating the extent to which a paragraph‐based full‐text retrieval system can be used to augment the explication facilities of an expert system on welding.

This study aims to define, classify and interconnect the wide range of known entrepreneurial abilities with terms such as skills, capabilities and competencies, which have been used inconsistently within the entrepreneurial field.

This investigation is based on a systematic literature review and strengthened by a meta-analysis equipped with a bibliometric study to assist the generation of outcomes with a quantitative investigation.

This study proposes an evolving entrepreneurial ability model which interconnects genetic and acquired skill types, capabilities and competencies and is equipped with an Entrepreneurial Skills Map essential to operate in the 21st century.

The proposed model is specific to the entrepreneurial field.

This study supports universities and government agencies for the development of educational programs to prepare current and future entrepreneurs to match the changes in the new environment that has emerged with the COVID-19 pandemic.

This research contributes to the entrepreneurship research domain by shedding light on the inconsistent use of non-standardised terminologies and providing an entrepreneurial model and updated skills map to guide scholars to frame research in the post-COVID era with more clarity.