Analysis of the promotion of cigarettes at the point of sale and its attractiveness to children

Smoking habit seriously affects public health in a number of direct and indirect ways. The study reported here took place in Brazil and examined the promotional activities of the tobacco industry at the point of sale, with particular reference to their impact on children. Tobacco control policies are generally in place in developed countries, and smokers typically develop the habit while still young. Trained researchers visited a stratified sample of 429 retail outlets in the city of São Paulo, comprising the local equivalents of bars, snack bars, luncheonettes and pubs. Data for analysis were collected by direct observation at the point of sale and interviews with the person deemed to be in charge of the outlet visited. The results indicate that the tobacco industry is displaying its products within full view of children and making use of the sales' incentives offered to the retailer. The findings contribute significantly to the study of the effect of promotion at the point of sale on young smokers and can inform the policy debate on the increasing regulation of tobacco marketing promotional methods.     

The role of subsidiaries from emerging economies—A survey involving the largest Brazilian multinationals

Several research projects have been devoted to the study of the internationalization of Brazilian firms; however there is a lack of research related to the strategy and management of subsidiaries of Brazilian multinational corporations in other countries. This article seeks to contribute to filling this gap. An academic research study was conducted involving 30 Brazilian multinational corporations. Of the 93 subsidiaries involved, 66 foreign subsidiaries answered the questionnaires. The main results concern the identification of three factors and the proposition of a typology of Brazilian subsidiaries of multinational corporations: implementing subsidiaries; market‐exploiting subsidiaries, and aspirants to strategically relevant subsidiaries. © 2012 Wiley Periodicals, Inc.     

Improving time series forecasting: An approach combining bootstrap aggregation,clusters and exponential smoothing

Some recent papers have demonstrated that combining bagging (bootstrap aggregating) with exponential smoothing methods can produce highly accurate forecasts and improve the forecast accuracy relative to traditional methods. We therefore propose a new approach that combines the bagging, exponential smoothing and clustering methods. The existing methods use bagging to generate and aggregate groups of forecasts in order to reduce the variance. However, none of them consider the effect of covariance among the group of forecasts, even though it could have a dramatic impact on the variance of the group, and therefore on the forecast accuracy. The proposed approach, referred to here as Bagged.Cluster.ETS, aims to reduce the covariance effect by using partitioning around medoids (PAM) to produce clusters of similar forecasts, then selecting several forecasts from each cluster to create a group with a reduced variance. This approach was tested on various different time series sets from the M3 and CIF 2016 competitions. The empirical results have shown a substantial reduction in the forecast error, considering sMAPE and MASE.     

Critical success factors associated with the implementation of enterprise risk management

The present research aimed to identify which critical success factors have the most influence on the implementation of Enterprise Risk Management – ERM, taking into consideration the important mission to ensure the survival, growth, and perpetuity of businesses in an environment with strong technology integration, global competition, and political, cultural, and economic contexts. To achieve this objective, a systematic and structured literature review was conducted, making it possible to identify 10 critical success factors for ERM initiatives that were analyzed and detailed, based on the literature findings and consultation with experts.     

Treating and Pruning: New approaches to forecasting model selection and combination using prediction intervals

We propose a new way of selecting among model forms in automated exponential smoothing routines, consequently enhancing their predictive power. The procedure, here addressed as treating, operates by selectively subsetting the ensemble of competing models based on information from their prediction intervals. By the same token, we set forth a pruning strategy to improve the accuracy of both point forecasts and prediction intervals in forecast combination methods. The proposed approaches are respectively applied to automated exponential smoothing routines and Bagging algorithms, to demonstrate their potential. An empirical experiment is conducted on a wide range of series from the M-Competitions. The results attest that the proposed approaches are simple, without requiring much additional computational cost, but capable of substantially improving forecasting accuracy for both point forecasts and prediction intervals, outperforming important benchmarks and recently developed forecast combination methods.     

Can sustainable investments outperform traditional benchmarks? Evidence from global stock markets

To contribute to overcoming global sustainability challenges, investors have been increasingly interested in making sustainable investments and incorporating environmental, social and governance (ESG) criteria into their portfolio selection decisions and managerial activities. However, these investors and other agents interested in sustainable investment need updated and robust information to support their decision making. We analyzed the performance of several Dow Jones Sustainability Indices (DJSIs) and compared them with their respective market benchmarks from 2013 to 2018. The indices comprise the following regions and countries: the world, the Asia‐Pacific, Europe, emerging markets and the US. The analysis was conducted based on both classic and modern portfolio metrics. The results suggest that sustainable investment performance is still heterogeneous worldwide, but there is a promising opportunity for investors to obtain superior risk‐adjusted returns in certain regions while incorporating sustainable investment practices. The findings are of utmost importance to financial market practitioners, business managers, academics and other stakeholders interested in promoting investments, corporate practices and scientific knowledge to achieve the Sustainable Development Goals (SDGs).     

Modelling demand and supply influences on utilization: A flow demand model to predict hospital utilization at the small area level

This study outlines a model to predict hospital utilization at the small area level within a National Health Service (NHS) institutional context. The proposed approach departs from alternative analyses based on utilization flows of hospital care between a local population and a hospital. A flow demand model is outlined that relates flow demand to utilization flows; models the interaction between hospital supply and utilization of alternative hospitals; captures the process of demand for hospital care, with special attention given to the role of other health care sectors, to the organizational and institutional context of the hospital system and to geographic variations. The flow approach partly overcomes the problem of dealing with simultaneity of determination between supply and demand. A two-part econometric model suitable to estimate the flow demand model for prediction purposes is tested and applied to the Portuguese health care system. The results show the model to be robust and to provide key information for defining future hospital policies at the central level.     

Employing the business model concept to support the adoption of product–service systems (PSS)

Although the existing literature indicates that the business model concept can be useful to implement product–service systems (PSS), there is still a paucity of guidelines to assist companies in this respect. Therefore, this paper proposes a framework to support the adoption of PSS employing the business model concept. This framework was developed based on literature review and intends to guide the company on the analysis of their business context, on the choice of the appropriate type of PSS and on the definition of their PSS characteristics. A single case study was then performed to illustrate an application of the framework in a machine tool manufacturer and provide research insights. Overall, results indicate that the framework can provide companies with a useful reference to PSS implementation, helping on the investigation of different PSS scenarios as well as the main barriers and challenges to be overcome.