“Indicators to prevent university drop-out and delayed graduation. An Italian case”

International audiencePurposeResearch on the association between individual characteristics of undergraduate students, drop-out and delayed graduation is still evolving. Therefore, further evidence is required. The paper aims to discuss this issue.Design/methodology/approachThis paper reports on an empirical study examining the relationship between students' individual characteristics and delayed graduation. The analysis is based on a sample of 1,167 students who have registered on and have completed a full-time undergraduate programme in Italy. Using a Probit model, the findings document the individual, background and environmental indicators that play a role in explaining delayed graduation.FindingsThe study observes that students who commute to university perform better than those residing on campus. Other factors increasing the probability of completing the undergraduate programme on time include individual characteristics (e.g. gender and age), student background (family income, education), institutional environment (teaching and research quality) and student satisfaction. Finally, some policy implications are discussed.Social implications - A direct policy implication of these findings is that supporting academic staff in order to enhance their performance in both research and teaching has a positive effect on the performance of the students.Originality/valueThis paper contributes to the debate on the impact of institutional quality on students' performance, aiming to address the question of balance between teaching and research orientation

Deconstructing Speech: new tools for speech manipulation

My research at the London College of Communication is concerned with archives of recorded speech, what new tools need to be devised for its manipulation and how to go about this process of invention. Research into available forms of analysis of speech is discussed below with regard to two specific areas, feature vectors from linear predictive coding (LPC) analysis and hidden Markov-model-based automatic speech recognition (ASR) systems. These are discussed in order to demonstrate that whilst aspects of each may be useful in devising a system of speech-archive manipulation for artistic use. Their drawbacks and deficiencies for use in art – consequent of the reasons for their invention – necessitate the creation of tools with artistic, rather than engineering agendas in mind. It is through the initial process of devising conceptual tools for understanding speech as sound objects that I have been confronted with issues of semiotics and semantics of the voice and of the relationship between sound and meaning in speech, and of the role of analysis in mediating existing methods of communication. This is discussed with reference to Jean-Jacques Nattiez’s Music and Discourse: Towards a Semiology of Music (Nattiez 1987). The ‘trace’ – a neutral level of semiotic analysis proposed by Nattiez, far from being hypothetical as suggested by Hatten (1992: 88–98) and others, is present by analogy to many forms of mediation in modern spoken communication and the reproduction of music, and it is precisely this neutrality with regards to meaning that tools for manipulation of speech must possess, since the relationships between the sound of speech and its meaning are ‘intense’ (after Deleuze 1968

The determinants of length of stay in the Azores : a count model approach

This paper employs count data models to estimate the determinants of length of stay, as count data models naturally lend themselves to overcome the censoring and truncation data issues associated with the non-negative, integer nature of length of stay. This paper employs a rich micro data set gathered through questionnaires ministered to a representative sample of tourists departing from the Azores: the fastest growing touristic region in Portugal. It is found that sociodemographic profiles, such as nationality and Azorean ascendancy, and trip attributes, such as repeat visitation rates and type of flight, are important determinants of length of stay. In addition, it is found that destination image and attitudes regarding environmental initiatives, constructed from a factor analysis exercise, also influence length of stay. In particular, the results suggest that marketing strategies that promote the Azores for its nature, landscape, remoteness, weather and safety may increase length of stay, whereas cultural heritage has the opposite effect.N/

Endogenous equilibria in liquid markets with frictions and boundedly rational agents

In this paper we propose a simple binary mean field game, where N agents may decide whether to trade or not a share of a risky asset in a liquid market. The asset's returns are endogenously determined taking into account demand and transaction costs. Agents' utility depends on the aggregate demand, which is determined by all agents' observed and forecasted actions. Agents are boundedly rational in the sense that they can go wrong choosing their optimal strategy. The explicit dependence on past actions generates endogenous dynamics of the system. We, firstly, study under a rather general setting (risk attitudes, pricing rules and noises) the aggregate demand for the asset, the emerging returns and the structure of the equilibria of the asymptotic game. It is shown that multiple Nash equilibria may arise. Stability conditions are characterized, in particular boom and crash cycles are detected. Then we precisely analyze properties of equilibria under significant examples, performing comparative statics exercises and showing the stabilizing property of exogenous transaction costs.Endogenous dynamics; Nash equilibria; Bounded rationality; Transaction costs; Mean field games; Random utility

An ontology for software component matching

The Web is likely to be a central platform for software development in the future. We investigate how Semantic Web technologies, in particular ontologies, can be utilised to support software component development in a Web environment. We use description logics, which underlie Semantic Web ontology languages such as DAML+OIL, to develop an ontology for matching requested and provided components. A link between modal logic and description logics will prove invaluable for the provision of reasoning support for component and service behaviour

Does segmentation always improve model performance in credit scoring?

Credit scoring allows for the credit risk assessment of bank customers. A single scoring model (scorecard) can be developed for the entire customer population, e.g. using logistic regression. However, it is often expected that segmentation, i.e. dividing the population into several groups and building separate scorecards for them, will improve the model performance. The most common statistical methods for segmentation are the two-step approaches, where logistic regression follows Classification and Regression Trees (CART) or Chi-squared Automatic Interaction Detection (CHAID) trees etc. In this research, the two-step approaches are applied as well as a new, simultaneous method, in which both segmentation and scorecards are optimised at the same time: Logistic Trees with Unbiased Selection (LOTUS). For reference purposes, a single-scorecard model is used. The above-mentioned methods are applied to the data provided by two of the major UK banks and one of the European credit bureaus. The model performance measures are then compared to examine whether there is improvement due to the segmentation methods used. It is found that segmentation does not always improve model performance in credit scoring: for none of the analysed real-world datasets, the multi-scorecard models perform considerably better than the single-scorecard ones. Moreover, in this application, there is no difference in performance between the two-step and simultaneous approache

A question of value(s): Political connectedness and executive compensation in public sector organizations

While the de-politicization of public sector management was a core objective of past reform initiatives, more recent debates urge the state to act as a strong principal when it comes to public sector unity and policy coherence - and consequently make a case for reinvigorating links between the political and managerial sphere. Using data from Austrian public sector organizations, we test and confirm the causal relationship of political connectedness of board members and executive compensation. Differentiating between value-based and interest-based in-groups, we suggest that only value-based political connectedness has the potential to restore patronage as a control instrument and governance tool. Self-interested and reward-driven patronage, on the other hand, indicated by a strong association of political connectedness and executive pay, refers to the type of politicization that previous public sector reforms promised to abolish