Harmonization of product information for child-care products

Abstract

This paper gives an overview of the prenormative research that has been conducted to achieve harmonization of product information for child-care products. This research supports the work of a project group of the European Committee for Standardization (CEN/TC 252/WG 6/PG 5). The project group is preparing a chapter on product information requirements for a CEN report on the safety of children's products. In the first study, the product information currently provided with child-care products was studied. In the second study, the following was drawn up: two lists of requirements, one for the legibility and one for the understandability of product information, a warning grammar, and a basic set of explicit warnings against the most frequent and severe hazards. In the third study, the effectiveness of explicit warnings for child-care products was investigated. The results of this study indicate that people perceive products with explicit warnings as more hazardous and the possible injuries in case of an accident as more severe. In a fourth study, warning symbols were designed for a number of warnings of the basic set. Future research will focus on testing the combination of warnings and symbols for child-care products for com-prehensibility in a number of European countries.     

Time-varying combinations of predictive densities using nonlinear filtering

We propose a Bayesian combination approach for multivariate predictive densities which relies upon a distributional state space representation of the combination weights. Several specifications of multivariate time-varying weights are introduced with a particular focus on weight dynamics driven by the past performance of the predictive densities and the use of learning mechanisms. In the proposed approach the model set can be incomplete, meaning that all models can be individually misspecified. A Sequential Monte Carlo method is proposed to approximate the filtering and predictive densities. The combination approach is assessed using statistical and utility-based performance measures for evaluating density forecasts of simulated data, US macroeconomic time series and surveys of stock market prices. Simulation results indicate that, for a set of linear autoregressive models, the combination strategy is successful in selecting, with probability close to one, the true model when the model set is complete and it is able to detect parameter instability when the model set includes the true model that has generated subsamples of data. Also, substantial uncertainty appears in the weights when predictors are similar; residual uncertainty reduces when the model set is complete; and learning reduces this uncertainty. For the macro series we find that incompleteness of the models is relatively large in the 1970’s, the beginning of the 1980’s and during the recent financial crisis, and lower during the Great Moderation; the predicted probabilities of recession accurately compare with the NBER business cycle dating; model weights have substantial uncertainty attached. With respect to returns of the S&P 500 series, we find that an investment strategy using a combination of predictions from professional forecasters and from a white noise model puts more weight on the white noise model in the beginning of the 1990’s and switches to giving more weight to the professional forecasts over time. Information on the complete predictive distribution and not just on some moments turns out to be very important, above all during turbulent times such as the recent financial crisis. More generally, the proposed distributional state space representation offers great flexibility in combining densities.     

Is social protection a necessity or a luxury good? New multivariate cointegration panel data results

The aim of this paper is to test the claim that social protection is a luxury good. Therefore, GDP elasticity of selected social protection expenditure is estimated using a new econometric approach developed first by Kao and Chiang (Advances in Econometrics, 15, 179–222, 2000). Time series properties of selected social expenditure in 18 OECD countries from 1981 to 1998 are examined. Using panel data cointegration tests and OLS, FMOLS and DOLS estimators, results were found which differ from previous analyses reporting substantially higher income elasticities. With the FMOLS, selected social expenditure has income elasticities smaller than one but greater than one with the DOLS. It is noteworthy that whether selected social expenditure is stationary or nonstationary may have critical implications for researchers and policy makers desiring to model and explain the impact of this expenditure on a country economic system.     

Development and validation of the Remote Working Benefits & Disadvantages scale

The changes that are constantly occurring in the labour sector have led organisations and companies to move towards digital transformation. This process was accelerated by the COVID-19 pandemic and  conducted to a massive recourse to the practice of remote working, which in this study is understood as the term for the way of performing work outside the usual workplace and with the support of ICT. Currently, there are no flexible scales in the literature that allow measuring the benefits and disadvantages of remote working with a single instrument. Thus, the distinction between the positive and negative consequences of working remotely, substantiated by a solid literature, provides a framework for a systematical understanding of the issue. The aim of the present study is to develop and validate a scale on remote working benefits and disadvantages (RW-B&D scale). For this end, a preliminary Exploratory Factor Analysis (EFA) with 304 participants, a tailored EFA with a sample of 301 workers and a Confirmatory Factor Analysis (CFA) with 677 workers were conducted. Participants were all Italian employees who worked remotely during the period of the COVID-19 health emergency. Data were collected between October 2020 and April 2021. The psychometric robustness of the model was assessed through bootstrap validation (5000 resamples), fit indices testing and measurement of factorial invariance. The statistical analyses demonstrated the bifactorial nature of the scale, supporting the research hypothesis. The model showed good fit indices, bootstrap validation reported statistically significant saturations, good reliability indices, and convergent and discriminant validity. Measurement invariance was tested for gender and organisational sector. The results suggested that the novel scale facilitates the quantitative measurement of the benefits and disadvantages associated with remote working in empirical terms. For this reason, it could be a streamlined and psychometrically valid instrument to identify the potential difficulties arising from remote working and, at the same time, the positive aspects that can be implemented to improve organisational well-being.

     

Do rainfall conditions push or pull rural migrants: evidence from Malawi

This article uses nationally representative data from Malawi's 2004/05 Integrated Household Survey (IHS2) to examine whether rainfall conditions influence a rural worker's decision to make a long‐term move to an urban or another rural area. Results of a Full Information Maximum Likelihood regression model reveal that (1) rainfall shocks have a negative association with rural out‐migration, (2) migrants choose to move to communities where rainfall variability and drought probability are lower, and (3) rainfall shocks have larger negative effects on the consumption of recent migrants than on the consumption of long‐time residents.     

The use of corporate social disclosures in the management of reputation and legitimacy: a cross sectoral analysis of UK Top 100 Companies

Recent years have witnessed an escalation in corporate social reporting (CSR) by UK companies (Gray, Kouhy and Lavers 1995). Whilst some elements of CSR reporting are required by law, much of it represents voluntary reporting. By investigating the non‐mandatory reporting of two aspects of social responsibility, corporate community involvement (CCI) and environmental impact, this paper seeks to explore why companies choose to make such disclosures. It specifically asks whether companies are primarily motivated by the strategic need to manage their reputation and legitimacy rather than by the recognition of their ethical accountability, which is the stated purpose of reports produced by cutting edge companies (Clarke 1998).     

Managing conflicting goals in pig farming: farmers' strategies and perspectives on sustainable pig farming in Sweden

Industrial meat production has several negative environmental effects. Governments’ agricultural policies aim for cost efficiency combined with high environmental and animal welfare, which puts farmers in a difficult situation trying to navigate between sometimes contradictory requirements. This paper studies how Swedish pig farmers resolve or cope with conflicting goals in pig farming. We have analysed the regulations governing EU and Swedish pig farming. We have also interviewed five Swedish pig farmers about their views of the different goals of pig farming and strategies for resolving conflicts between the goals of low environmental impact, high animal welfare and enough profitability to continue farming. The greatest divide was between the conventional farmers, who emphasized natural resource efficiency, and the organic farmers who stressed animal welfare, multifunctionality and ecosystem service delivery. We suggest four strategies to contribute to resolving some of the conflicting goals: improve communication about different types of pig farming; use public procurement as a driver towards more sustainable pork production; work towards improving the Common Agricultural Policy, perhaps by implementing payments for ecosystem services or multifunctionality; and finally, decrease the total production of pork to lower the emissions per land unit.     

Marketing strategy in emerging markets: a conceptual framework

Citing difference between emerging and developed markets, scholars highlight need for different approaches to marketing in emerging markets. In this paper, we argue that while there are some unique characteristics of emerging markets, all countries within emerging markets do not have similar levels of product penetration and consumption. As a result, it is wrong to assume that emerging markets are untapped and under-served across the product categories. To a list of characteristics identified as unique to emerging markets, we add large population as an important characteristic and discuss its strategic implications. We develop a conceptual framework that factors in combined effect of varying degrees of product penetration & consumption levels with large population of emerging market countries. The conceptual framework identifies four strategic alternatives for marketing in emerging markets. Instead of recommending any generic marketing strategy, we propose that marketers need to choose an appropriate mix of strategies aimed at primary and selective demand creation in emerging markets.