Consumers' perceived risk: Sources versus consequences

In this study, we examine an important factor that affects consumers' acceptance of business-to-commerce (B2C) electronic commerce - perceived risk. The objective of this paper is to examine the definition of perceived risk in the context of B2C electronic commerce. The paper highlights the importance of perceived risk and the interwoven relation between perceived risk and trust. It discusses the problem of defining perceived risk in prior B2C research. This study proposes a new classification of consumers' perceived risk based on sources. It highlights the importance of identifying the sources of consumer's risk perceptions in addition to the consequences dimensions. Two focus group discussion sessions were conducted to verify the proposed classification. Results indicate that Internet consumers perceive three sources of risk in B2C electronic commerce: technology, vendor, and product. © 2003 Elsevier B.V. All rights reserved.

Rates of electronic energy transfer in conformationally flexible bichromophoric macrocyclic complexes: a combined experimental and molecular modeling study

Electronic energy transfer (EET) rate constants between a naphthalene donor and anthracene acceptor in [ZnL4a](ClO4)(2) and [ZnL4b](ClO4)(2) were determined by time-resolved fluorescence where L-4a and L-4b are the trans and cis isomers of 6-((anthracen-9-yl-methyl)amino)-6,13-dimethyl-13-((naphthalen-1-yl-methyl)amino)-1,4,8,11-tetraazacyclotetradecane, respectively. These isomers differ in the relative disposition of the appended chromophores with respect to the macrocyclic plane. The trans isomer has an energy transfer rate constant (k(EET)) of 8.7 x 10(8) s(-1), whereas that of the cis isomer is significantly faster (2.3 x 10(9) s(-1)). Molecular modeling was used to determine the likely distribution of conformations in CH3CN solution for these complexes in an attempt to identify any distance or orientation dependency that may account for the differing rate constants observed. The calculated conformational distributions together with analysis by H-1 NMR for the [ZnL4a](2+) trans complex in the common trans-III N-based isomer gave a calculated Forster rate constant close to that observed experimentally. For the [ZnL4b](2+) cis complex, the experimentally determined rate constant may be attributed to a combination of trans-Ill and trans-I N-based isomeric forms of the complex in solution.

O papel do governo eletr??nico no fortalecimento da governan??a do setor p??blico

As novas Tecnologias da Informa????o e Comunica????o (TIC), entre as quais se destacam a internet, as redes de computadores, a transmiss??o via sat??lite e a telefonia m??vel, criaram condi????es para o surgimento de Sociedades do Conhecimento. Nesse contexto, o Estado, por interm??dio do governo eletr??nico, ?? o principal instrumento de que os cidad??os disp??em atualmente para enfrentar os desafios impostos pela globaliza????o, por meio de intera????es in??ditas da sociedade, empresas e governos. O objetivo deste trabalho foi estabelecer rela????es entre a governan??a do setor p??blico e o governo eletr??nico, partindo-se de um marco referencial te??rico das duas ??reas de estudo. Para tanto, foram delineados seus escopos e limites de atua????o, instituindo-se v??nculos, de acordo com a????es do Governo Eletr??nico brasileiro: certifica????o digital; Portal da Transpar??ncia; vota????o eletr??nica; preg??es eletr??nicos e Portal da Previd??ncia Social. Conclui-se que, apesar dos avan??os recentes observados pela an??lise de v??rias dimens??es da governan??a, baseados em iniciativas de governo eletr??nico aqui inventariadas, ainda h?? muito que fazer em dire????o ?? inclus??o social no Brasil, assim como em outros pa??ses. As TIC podem vir a ser um poderoso agente de inclus??o digital, apoiando a governan??a com a cria????o de espa??os virtuais para participa????o democr??tica e di??logo c??vico e expans??o da participa????o em tomada de decis??o coletiva, promovendo a igualdade e a cidadania.

The Brazilian Business World: the difficult adaptation to globalization

The article deals with the internationalization of Brazilian businesses in the current decade. In the 1990s, Brazil embraced economic neoliberalism and promoted a huge opening up of its economy. At that time, Brazilian companies had to adapt rapidly. Twenty years later, the country has reinforced its presence in Latin America and has ensured a better position in the global markets, especially by through agricultural exports.

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

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.