Use of Derivatives and Analysts’ Forecasts: New Evidence from Non‐financial Brazilian Companies

This study investigates whether market analysts’ forecasts are influenced by the presence of derivative financial instruments in listed firms. From a sample of firms comprising 1173 derivative users and 7797 non‐users for the 2006–14 period, the results indicate the existence of less error behaviour (bias) on earnings per share forecasts for derivative user firms compared to non‐user firms. This finding suggests that these instruments may be used to protect businesses and provide greater stability in the results of companies that use them. The presence of derivative financial instruments is increasing among listed firms, and management can use them for hedging or speculation (thus mitigating or increasing risk). The literature contains few studies on this issue, and the general understanding relies on the assumption that derivative financial instruments provide relevant information for decision making.     

Antecedents and outcomes of digital influencer endorsement: An exploratory study

The advertising and marketing literature have established that celebrity endorsements constitute an effective way to enhance attitudes toward brands and increase purchase intents. However, there are no relevant studies on digital influencers. This study addresses the research gap by examining the effect of digital influencers' attractiveness and the effect of the congruence between a digital influencer and a brand on consumer attitudes and purchase intentions. By applying structural equation modeling to a sample of 307 followers of digital influencers, a model was tested and group analysis was performed for two categories (“entertainment & video games” and “fashion & beauty”). The results show that both brand attitudes and purchase intentions are influenced by the digital influencer's attractiveness (which includes both likeability and familiarity) and by the congruence between the digital influencer and the brand. This study makes several contributions to both theory and practice, which are highlighted in this paper.     

The Euro: An Italian perspective

The adoption of Euro as a common currency of twelve European countries has meant a considerable change in the Italian exchange rate policy. In the past, before Italy entered the EMS and again in 1992-96 when Italy temporarily left the EMS, the Italian monetary authorities enacted a policy of managed exchange rates, aiming at keeping the dollar rate stable, while letting the Italian lira depreciate vis-à-vis the German mark. By so doing, the danger of imported inflation was reduced (the dollar area was then a major import area) and at the same time the Italian exports to Europe were made easier. In the presence of a regime of fixed exchange rates in the European area, Italian industry is trying to make its exports more competitive by means of a reduction in costs. This means moving segments of production to small or middle-size firms, located in Italy as well as in developing countries. A further help is coming from the gradual but consistent depreciation of the Euro against the US dollar. The relevance of the dollar area in Italian exports has been correspondingly increasing.     

Analysis of Domestic Factors Affecting Outward Foreign Direct Investment in Brazil

Developing markets have increasingly gained prominence in the world economy, but the domestic factors behind this success are not well established. This uncertainty may interfere with multinational expansion plans. In this article, we examine several macroeconomic and institutional factors affecting Brazilian outward foreign direct investment in 17 destination countries. We applied a pooled ordinary least squares regression over the 2001–2014 period. The findings suggest that macroeconomic factors are still statistically significant to explain investment abroad, but several institutional factors such as corruption have emerged, having a negative effect and political violence having a positive effect on Brazilian outward foreign direct investment.     

A note on how to measure hubbing practices in airline networks

Benefits and costs associated to hubbing practices of airlines are still subject to much debate. In the previous literature, some standard spatial concentration indices have been proposed to measure it. However, we show that these indices are “ill-defined” because they do not take into account the salient characteristic of hubbing: connecting passengers. The purpose of this research is to present a new methodology which avoids the pitfalls of other methods. Our new methodology also analyzes the level of concentration of the connecting passengers studying two different dimensions: hub airports and routes. Finally, we apply our methodology to some US carriers.     

Design principles of hybrid approaches in new product development: a systematic literature review

Setting the right approach for new product development (NPD) in the presence of uncertainty remains an ongoing debate in innovation management. Stage-gate systems (SGS) and agile methodology (AM) are the dominant approaches. Recently, hybrid approaches (combining SGS and AM) have been proposed. Although these hybrid approaches represent a significant development in NPD, combining them without considering their design principles might lead to contradictory and competing conceptual formulations, thus increasing the difficulty of comparison among studies. Moreover, scholars and practitioners may struggle to understand when, why and how a certain configuration of the NPD process provides the right response to different manifestations of uncertainty. The current literature faces problems regarding the clarity of design principles (e.g. flexibility and adaptability), and this has led to research gaps concerning the uncertainty contingency and outcomes of hybrid approaches. This study combines bibliometric and content analyses to identify four design parameters and principles of NPD hybrid approaches: flexibility, adaptability, velocity and integration. Our findings might help advance the development and comparison of different hybrid approaches.     

Predicting Corporate Failure Using a Neural Network Approach

This paper investigates the performance of Artificial Neural Networks for the classification and subsequent prediction of business entities into failed and non-failed classes. Two techniques, back-propagation and Optimal Estimation Theory (OET), are used to train the neural networks to predict bankruptcy filings. The data are drawn from Compustat data tapes representing a cross-section of industries. The results obtained with the neural networks are compared with other well-known bankruptcy prediction techniques such as discriminant analysis, probit and logit, as well as against benchmarks provided by directly applying the bankruptcy prediction models developed by Altman (1968) and Ohlson (1980) to our data set. We control the degree of ‘disproportionate sampling’ by creating ‘training’ and ‘testing’ populations with proportions of bankrupt firms ranging from 1% to 50%. For each population, we apply each technique 50 times to determine stable accuracy rates in terms of Type I, Type II and Total Error. We show that the performance of various classification techniques, in terms of their classification errors, depends on the proportions of bankrupt firms in the training and testing data sets, the variables used in the models, and assumptions about the relative costs of Type I and Type II errors. The neural network solutions do not achieve the ‘magical’ results that literature in this field often promises, although there are notable 'pockets' of superior performance by the neural networks, depending on particular combinations of proportions of bankrupt firms in training and testing data sets and assumptions about the relative costs of Type I and Type II errors. However, since we tested only one architecture for the neural network, it will be necessary to investigate potential improvements in neural network performance through systematic changes in neural network architecture.     

A CRITICAL REVIEW OF CONTAGION RISK IN BANKING

The recent financial crisis has focused the attention of scholars and policymakers on how to improve financial stability through better macro‐prudential regulation and supervision. In this paper, we compare the existing theoretical and empirical literature on contagion through the banking system. It is argued that the structure of the interbank market, the size of banks, the linkages among them, the level of correlation of their investments and the transparency of the regulator are key factors in determining the possibility of contagion. We discuss the different findings and present avenues for future research.