Evidência empírica dos factores explicativos dos dividendos distribuídos pelas empresas cotadas na EURONEXT Lisboa

Companies’ decision to pay dividends to its shareholders is a topic that has received increasing attention in business finance. This paper provides an additional contribution to the development of this topic focusing on the analysis of the determinants of dividend policy by issuing companies in the Portuguese capital market. For this purpose, we use a set of financial and economic information specific to each firm to explain its dividend per share. The sample used in the empirical study contains 54 firms and it refers to the 2005-2009 period. Results suggest that net income, dividends per share paid in the previous financial year and return on assets all present a positive and statistically significant effect on dividends per share paid in a given financial year. Moreover, results show that Lintner’s (1956) model appears to be valid in explaining dividend policy by issuing companies in Euronext Lisbon.

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.

On the discovery of business processes orchestration patterns

COORDINSPECTOR is a Software Tool aiming at extracting the coordination layer of a software system. Such a reverse engineering process provides a clear view of the actually invoked services as well as the logic behind such invocations. The analysis process is based on program slicing techniques and the generation of, System Dependence Graphs and Coordination Dependence Graphs. The tool analyzes Common Intermediate Language (CIL), the native language of the Microsoft .Net Framework, thus making suitable for processing systems developed in any .Net Framework compilable language. COORDINSPECTOR generates graphical representations of the coordination layer together with business process orchestrations specified in WSBPEL 2.0

«Corruption» and social and economic criminal law: criminology, criminal policy, political science and law&economics - a new idea about criminal liability of legal entities

Abstract: If we think there is a significant number of legal offshore in the globalized world, then there is not even a global consensus about what «corruption» is. The «illegal corruption» in a country may be legal in another. Moreover, the great global corruption is above the law or above democratic States. And not all democratic States are «Rule of Law». Therefore, the solution is global earlier in time and space law, democratic, free and true law. While the human being does not reach a consensus of what «corruption» really is, the discussion will not go further than a caricature. One of the other problems about «corruption» is that it is very difficult to establish the imputation of crimes, including «corruption» (v.g. Portugal) on some «companies», corporations. We have a juridical problem in the composition of the art. 11. of the Portuguese Penal Code.

The host-tourist interaction in a world heritage site: the case of Guimarães

Guimarães, in the northwest of Portugal, is a city of strong symbolic and cultural significance and its nomination by UNESCO as world heritage, in 2001, enlarged its tourism potential. In this paper we present a few results of a survey that envisaged capturing the Guimarães residents’ perceptions of tourism impacts and their attitudes towards tourists. Specifically, one analyzes the type of relationship that exists between some socio-demographic groups and the perceived tourism impacts, as well as their socio-characteristics and the existing level of interaction between residents and tourists. The survey was implemented between January and March 2010 to a convenience sample of 540 inhabitants of the municipality of Guimarães resulting in 400 questionnaires with complete data. For this, we made use of various statistical techniques. Using a factorial analysis, we can conclude that the three factors used explain 52.3% of the variance contained in the original variables obtained from the survey. By another side, using a logit model in the analysis and taking as the dependent variable the frequent or very frequent contact with tourists, we found that only the variables referred to perceived positive impacts of tourism, education and the place of residence in urban areas have shown to be statistically significant. We are aware of the multiple ways the issue of residents’ perceptions and attitudes towards tourism can be approached and of the difficulties to get useful policy-oriented insights. This paper is a step in that trail.

The perceived potential of business social networking sites

Business social networking is a facilitator of several business activities, such as market studies, communication with clients, and identification of business partners. This paper traduces the results of a study undertaken with the purpose of getting to know how the potential of networking is perceived in the promotion of business by participants of the LinkedIn network, and presents two main contributions: (1) to disseminate within the business community which is the relevance given to social networking; and (2) which are the social networks best suitable to the promotion of business, to support the definition of strategies and approaches accordingly. The results confirm that LinkedIn is the most suitable network to answer the needs of those that look for professional contacts and for the promotion of business, while innovation is the most recognized factor in the promotion of business through social networking. This study contributes to a better understanding of the potential of different business social networking sites, to support organizations and professionals to align their strategies with the perceived potential of each network.

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.