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In a fast evolving labour market, higher education graduates need to develop employability competences. Key in becoming employable is the ability to reflect on learning experiences, both within a curriculum as well as extra-curricular and work placements. This paper wants to conceptualise how an online learning platform might entail a reflective practice that systematically supports students in reflecting on their learning experiences.

When studying online learning platforms for developing students' employability competences, it became clear that the effectiveness of the platform depends on how the platform guides students' reflective practice. In turn, the authors studied which features (tools, services and resources) of the online learning platform are guiding the reflective practice.

This resulted in the introduction of an online learning platform, containing a comprehensive set of online learning tools and services, which supports students' reflective practice and, in turn, their employability competences. The online platform facilitates both feedback from curricular and work-related learning experiences and can be used as a start by students for showcasing their employability competences. The reflective practice consists of a recurrent, systematic process of reflection, containing various phases: become aware, analyse current state, draft and plan a solution, take action and, finally, reflect in and on action.

Future research revolves around studying the features of online learning platforms and their role in fostering students' reflection and employability competences.

The conceptual model provides concrete indicators on how to implement online learning platforms for supporting students' reflection and employability competences.

This is the first article that analyses an online learning platform that guides students' reflective practice and fosters their employability competences. The authors provide concrete suggestions on how to model the online platform, building further on reflective practice theory.

The purpose of this study is to examine the relationship between corporate reputation and earnings quality. This study uses a sample of 1,092 firm year observations from 273 firm listed companies on the Indonesia Stock Exchange from 2013 to 2016, except for the financial industry. We uses a public measure, “100 Top Emiten” by Investor magazine, as a proxy for corporate reputation, while earnings quality is measured by calculating the absolute value of discretionary accrual. Growth of assets, firm size, leverage and profitability are used as control variables in this study. Multiple linear regression analysis is used to test the research hypothesis. The results of the regression in this study indicate that corporate reputation has a positive and significant relationship with earnings quality. This indicates that a reputable company will be encouraged to produce an earnings quality in an effort for the company to maintain investor confidence in the company, so that the company's image and reputation can be maintained. Earnings management in this study was calculated using cross-sectional method instead of time series method. Cross-sectional method is a method by comparing the financial data of a company with a company or other similar industries, whereas the time series method uses the comparison of financial data in a period with the previous period by analyzing what happens behind the trend figures on a company.

The paper aims to disentangle the physiological credit risk from the credit risk coming from the inefficient screening and monitoring management process. The analysis is conducted on a sample of 338 Italian banks–56 joint-stock banks (SpA), 23 cooperative banks (Popolari) and 259 mutual banks (BCCs)–over the time period 2006–2017.

The authors use the maximum likelihood method to estimate the efficient frontier, as a set of best management credit practices, which minimises the credit risk defined on the basis of the level of loans granted, the technical structure of the loan portfolio (such as credit lines, mortgages, consumer loans and other technical loan categories) and the interest rate charges.

The empirical results show that the increase in non-performing loans (NPLs) is related both to the severe and protracted recession in Italy, which significantly reduced borrowers' capacity to service their debt, and to other factors, such as banks' lending monitoring policies with limited capacity to work-out defaulted loans.

The authors propose a new approach to the study of the performance of the credit process. With the stochastic frontier, the physiological credit risk, assumed by the bank according to its lending activity and management choices, is separated from the credit risk resulting from an inefficient management of the screening and monitoring process. In addition, the authors analyse the determinants of the excess of NPLs. This aspect is considered particularly original because the scientific contributions which consider the causes of NPLs have largely focused on the level of NPLs not considering the physiological part, linked to the structure of the bank's loan portfolio and its operational strategy and therefore not compressible and in any case not attributable to mismanagement or moral hazard.