Organizational and accounting change within the context of the environmental agenda: evidence from Portugal

Purpose – The purpose of this paper is to explore the process of organizational change undergone by a large Portuguese business group within the context of the environmental agenda and the role of accounting as a mechanism for change. Design/methodology/approach – The paper reports the results of a case study conducted between 2006 and 2009. Information was obtained from semi-structured interviews and secondary sources. Organizational changes were analyzed using Laughlin’s model in order to identify which category reflected most of the changes introduced to address environmental matters. Findings – This paper offers evidence that change is not a homogeneous phenomenon. Additionally, it confirms previous studies’ findings which found that accounting did not play a significant role in the process of organizational change within the context of the environmental agenda. Originality/value – This paper seeks to complement the research in this area by integrating observations from a case study into an existing model of levels of organizational change according to how a Portuguese business group incorporated environmental issues into its processes, policies and corporate culture.

Measuring fund performance using multi-factor models: evidence for the Portuguese market

This paper examines the performance of Portuguese equity funds investing in the domestic and in the European Union market, using several unconditional and conditional multi-factor models. In terms of overall performance, we find that National funds are neutral performers, while European Union funds under-perform the market significantly. These results do not seem to be a consequence of management fees. Overall, our findings are supportive of the robustness of conditional multi-factor models. In fact, Portuguese equity funds seem to be relatively more exposed to smallcaps and more value-oriented. Also, they present strong evidence of time-varying betas and, in the case of the European Union funds, of time-varying alphas too. Finally, in terms of market timing, our tests suggest that mutual fund managers in our sample do not exhibit any market timing abilities. Nevertheless, we find some evidence of timevarying conditional market timing abilities but only at the individual fund level.

Models for the Reverse Engineering of Java/Swing Applications

Abstract. Interest in design and development of graphical user interface (GUIs) is growing in the last few years. However, correctness of GUI's code is essential to the correct execution of the overall software. Models can help in the evaluation of interactive applications by allowing designers to concentrate on its more important aspects. This paper describes our approach to reverse engineering abstract GUI models directly from the Java/Swing code.

Color Models and Illumination Changes

Color model representation allows characterizing in a quantitative manner, any defined color spectrum of visible light, i.e. with a wavelength between 400nm and 700nm. To accomplish that, each model, or color space, is associated with a function that allows mapping the spectral power distribution of the visible electromagnetic radiation, in a space defined by a set of discrete values that quantify the color components composing the model. Some color spaces are sensitive to changes in lighting conditions. Others assure the preservation of certain chromatic features, remaining immune to these changes. Therefore, it becomes necessary to identify the strengths and weaknesses of each model in order to justify the adoption of color spaces in image processing and analysis techniques. This chapter will address the topic of digital imaging, main standards and formats. Next we will set the mathematical model of the image acquisition sensor response, which enables assessment of the various color spaces, with the aim of determining their invariance to illumination changes.

Extracting and verifying coordination models from source code

Current software development relies increasingly on non-trivial coordination logic for com- bining autonomous services often running on di erent platforms. As a rule, however, in typical non-trivial software systems, such a coordination layer is strongly weaved within the application at source code level. Therefore, its precise identi cation becomes a major methodological (and technical) problem which cannot be overestimated along any program understanding or refactoring process. Open access to source code, as granted in OSS certi cation, provides an opportunity for the devel- opment of methods and technologies to extract, from source code, the relevant coordination information. This paper is a step in this direction, combining a number of program analysis techniques to automatically recover coordination information from legacy code. Such information is then expressed as a model in Orc, a general purpose orchestration language

Comparative analysis between statistical and artificial intelligence models in business failure prediction

A growing number of predicting corporate failure models has emerged since 60s. Economic and social consequences of business failure can be dramatic, thus it is not surprise that the issue has been of growing interest in academic research as well as in business context. The main purpose of this study is to compare the predictive ability of five developed models based on three statistical techniques (Discriminant Analysis, Logit and Probit) and two models based on Artificial Intelligence (Neural Networks and Rough Sets). The five models were employed to a dataset of 420 non-bankrupt firms and 125 bankrupt firms belonging to the textile and clothing industry, over the period 2003–09. Results show that all the models performed well, with an overall correct classification level higher than 90%, and a type II error always less than 2%. The type I error increases as we move away from the year prior to failure. Our models contribute to the discussion of corporate financial distress causes. Moreover it can be used to assist decisions of creditors, investors and auditors. Additionally, this research can be of great contribution to devisers of national economic policies that aim to reduce industrial unemployment.

Comparative Analysis between Statistical and Artificial Intelligence Models in Business Failure Prediction

A growing number of predicting corporate failure models has emerged since 60s. Economic and social consequences of business failure can be dramatic, thus it is not surprise that the issue has been of growing interest in academic research as well as in business context. The main purpose of this study is to compare the predictive ability of five developed models based on three statistical techniques (Discriminant Analysis, Logit and Probit) and two models based on Artificial Intelligence (Neural Networks and Rough Sets). The five models were employed to a dataset of 420 non-bankrupt firms and 125 bankrupt firms belonging to the textile and clothing industry, over the period 2003–09. Results show that all the models performed well, with an overall correct classification level higher than 90%, and a type II error always less than 2%. The type I error increases as we move away from the year prior to failure. Our models contribute to the discussion of corporate financial distress causes. Moreover it can be used to assist decisions of creditors, investors and auditors. Additionally, this research can be of great contribution to devisers of national economic policies that aim to reduce industrial unemployment.

Relationships between NPM, the use of PM practices and the organizational performance: empirical evidence from government agencies

Purpose – this paper has two main purposes: (1)explore if government agencies more oriented to NPM postulates are more willing to use PM practices and to improve their performance; and (2) investigate whether the fit between the use of PM practices and the organizationa performance is dependent upon from the capacity of agencies to adapt its structures to changes introduced by NPM reforms. Design/methodology/approach - this paper is based on the survey method and provides empirical evidence from Portuguese government agencies.Findings (mandatory) - Our findings suggest that government agencies that made structural arrangements under the NPM reforms are more willing to use PM practices and will perform better than other agencies. In addition, this paper show that therelationship between the use of PM practices and the organizational performance is dependent upon from the agencies capacity to adopt new structural arrangements under the NPM reforms.Practical implications – this paper has three main contributions: (1) contribute to knowledge about the relationship between the introduction of NPM changes in the use of PM practices; (2) contribute to clarify whether agencies more oriented to NPM postulates are improving performance; and (3) help to clarify the way the organizations should adapt their structures for to be more effective in the use of PM practices. Originality/value - The quantitative empirical research, based on the unique survey applied to Portuguese government agencies on this field, allow us to add to prior research mainly based on case studies and oriented to local governments (Budding, 2004).