Clashing institutional interests in skills between government and industry: An analysis of demand for technical and soft skills of graduates in the UK

Technological knowledge and skills provide a basis for developing national competitiveness. However, there is an emerging clash of interests in the UK labour market between employers and policy makers. The former requests highly skilled workers who often jealously train in house for their specific operations while the latter aims to reduce unemployment through the expansion of vocational training to lower skilled workers. Universities need to find their strategic position in the knowledge economy characterised by radical technological change and shifting occupational structure by meeting the future skills demand while balancing between the clashing institutional interests. This study analyses 510 job advertisements in the supply chain management area, using a combination of OMDS and HCA techniques. The advertisements are categorised by means of six dimensions according to the skills, duties and job type. This study analyses not only employers' needs in skill types according to job roles but also emerging institutional clashes in the job market and their implications for skills training policy and curriculum development

State recognition for ‘contested languages’: a comparative study of Sardinian and Asturian, 1992–2010

While the idea of a named language as a separate and discrete identity is a political and social construct, in the cases of Sardinian and Asturian doubts over their respective ‘languageness’ have real material consequences, particularly in relation to language policy decisions at the state level. The Asturian example highlights how its lack of official status means that it is either ignored or subjected to repeated challenges to its status as a language variety deserving of recognition and support, reflecting how ‘official language’ in the Spanish context is often understood in practice as synonymous with the theoretically broader category of ‘language’. In contrast, the recent state recognition of Sardinian speakers as a linguistic minority in Italy (Law 482/1999) illustrates how legal recognition served to overcome existing obstacles to the implementation of regional language policy measures. At the same time, the limited subsequent effects of this Law, particularly in the sphere of education, are a reminder of the shortcomings of top-down policies which fail to engage with the local language practices and attitudes of the communities of speakers recognized. The contrastive focus of this article thus acknowledges the continued material consequences of top-down language classification, while highlighting its inadequacies as a language policy mechanism which reinforces artificial distinctions between speech varieties and speakers deserving of recognition

Selecting DEA specifications and ranking units via PCA

DEA model selection is problematic. The estimated efficiency for any DMU depends on the inputs and outputs included in the model. It also depends on the number of outputs plus inputs. It is clearly important to select parsimonious specifications and to avoid as far as possible models that assign full high efficiency ratings to DMUs that operate in unusual ways (mavericks). A new method for model selection is proposed in this paper. Efficiencies are calculated for all possible DEA model specifications. The results are analysed using Principal Components Analysis. It is shown that model equivalence or dissimilarity can be easily assessed using this approach. The reasons why particular DMUs achieve a certain level of efficiency with a given model specification become clear. The methodology has the additional advantage of producing DMU rankings

An approach to the measurement of intangible assets in public sector using scaling techniques

This paper discusses the identification and measurement of intangible assets in the public sector. A discussion of Intellectual Capital theory identifies and classifies a number of intangible assets of relevance to the Public Sector. Multidimensional Scaling and related multivariate techniques are proposed for their detection and quantification. The methodology is illustrated with a case study: the provision of council services through the Internet by Spanish municipalities. The technique identifies three intangible assets related to external structural capital: service, image and transparency. Five strategic groups reveal the different objectives, strategic use of Internet, and actions taken by the various Spanish councils

An approach to the measurement of intangible assets in dot com based on web metrics and financial information

A sample of 76 firms that operate in the Internet is studied in order to explore forms of identifying and measuring intangible assets in this area of business. The firms meet three conditions: operate in the Internet, have available accounting information, and be quoted in the stock exchange. Data was obtained on two successive years for four web metrics indicators, 30 ratios that combine accounting and web traffic information, 31 accounting ratios, a measure of stock exchange performance, and a measure of efficiency based on Data Envelopment Analysis. Modelling relied on multivariate statistical approaches: Factor Analysis, Scaling techniques, multivariate regression, and hierarchical cluster analysis. Two intangible assets were identified: one was related to internal structure and was associated with managerial efficiency; and another one was associated with external image and customer loyalty. Comparison between the two years found many changes, confirming the view that this is a very dynamic sector, although the main conclusions remained unchanged

On model selection in data envelopment analysis: a multivariate statistical approach

This paper addresses an important issue in DEA: the selection of inputs and outputs to be included in a model. A two-stage methodology is suggested. The first stage applies a methodology based on comparing reduced models that do not include a particular input/output with extended models that include it. The second stage uses the tools of multivariate statistical analysis to visualize important aspects of the models considered. In this way model selection combines mathematical tools, statistical analysis, and the exercise of judgment. The methodology has the advantage of explaining why some Decision Making Units (DMUs) appear to be efficient under some models and inefficient under other models. It is also possible to produce rankings of DMUs that are a consensus over all the models. The methodology is illustrated with the help of a case study: the efficiency of Spanish banks. It is found that, in this case, there are various defensible definitions of efficiency, and it is suggested that a variety of models should be estimated

Country and size effects in financial ratios: a European perspective

Harmonised aggregate financial statements are published by the European Commission in the BACH database. This information is organised by country, size of firm, and year. Financial ratios obtained from this database are analysed using multivariate statistical techniques in order to explore country and size effects. The data relates to three size groups, eleven countries, fourteen years, and fifteen financial ratios. It is found that financial ratios reflect the size of the firm, but that the way in which this is reflected varies between the different countries. It is also found that there are no significant size related differences in financial profitability, but that such differences appear when countries are compared. Important regularities are found over time. Some time effects are also found in the way countries react to the business cycle

The path of efficiency in DEA: multidimensional scaling as a tool for post-optimality analysis

DEA measures efficiency by means of a mere score. This is clearly useful, but there is a need to look further away into the context in which efficiency is achieved. It is argued that Scaling techniques provide a framework for the interpretation of DEA efficiency scores. A methodology is proposed and illustrated by means of a case study: the dot com business. This methodology has the advantage of visualising the main characteristics of the situation under investigation, and revealing aspects that would otherwise have remained hidden. It is shown that DEA model selection can greatly benefit from its inclusion in a scaling framework. It is also shown how the methodology proposed can highlight various strategic behaviours that firms follow in the path to efficiency

Change and invariance in EU aggregate financial statement data

Aggregate accounting data from the BACH data base for European manufacturing companies is used to explore the nature of the differences in financial structure between eleven countries in the European Union over the period 1986-1999. The analysis relies on scaling methods, which visualise the most important features of the data and their dynamic evolution. It is found that there is a geographical divide in the EU, which appears to be related to company profitability and staff cost structure. The differences between countries are influenced by the economic cycle, being more accentuated in periods of low economic activity

Behind DEA efficiency in financial institutions

DEA has been extensively used to measure the efficiency of financial institutions. Its advantages are clearly understood. But there are many unresolved problems. There are various views based on different modelling philosophies of what constitutes inputs and outputs in a financial institution. The paper explores up to what point the various combinations of inputs and outputs are equivalent, and up to what point the efficiency score obtained by a given institution changes under the various combinations of inputs and outputs. The extent to which two institutions that achieve the same efficiency score arrive at it following different strategies is explored with the aim of finding out what is behind such a score.It is suggested that, not one but many different DEA specifications, containing different combinations of inputs and outputs, be modelled and that the results be analysed with the tools of multivariate statistics. Particular emphasis is placed on using tools that visualise the main characteristics of the data. By-products of the approach proposed here are the creation of league tables of financial institutions in terms of efficiencies and the possibility to assess strengths and weaknesses of individual institutions. This methodology is applied to the particular case of Spanish savings banks (Cajas de Ahorros) and proves to be particularly rewarding