Should Higher Education Subsidies Depend on Parental Income?

In many countries, student grants, tuition fees, and subsidizedloans depend on parental income. This paper examines the efficiencyand distributional effects of such conditioning, and assesseswhether it is optimal practice when the government wants toreduce after-tax income inequality in the most efficient manner.Increasing the mean level of education among the work-forcecompresses wage differentials by level of education and therebythe pre-tax income distribution. Hence, subsidizing educationmay be part of an optimal redistribution policy. However, educationsubsidies mainly benefit high-ability students, limiting theirredistributive virtues. Conditioning education subsidies onparental income may enable the government to reduce inframarginalsubsidies, mainly benefiting high-ability students, while preservingthe marginal subsidy, and thus the favourable effect on themean education level which leads to wage compression.     

Getting the word out on Twitter: the role of influentials,information brokers and strong ties in building word-of-mouth for brands

Using a sample of over 5300 tweets from top global brands, this study investigated how different types of users can influence brand content diffusion via retweets. Twitter users who influenced followers to retweet brand content were categorized as (1) influentials, because of their above average ability to influence others to retweet their tweets (in general), (2) information brokers, because of their position connecting groups of users or (3) having strong ties, because of their high percentage of friends in common and a mutual friend–follower relationship with the influenced follower. The results indicate that influentials and information brokers are associated with larger number of retweets for brand content. In addition, although information brokers have a larger overall influence on retweeting, they are more prone to do so when influentials are mentioned in the brand tweet, providing support for the strategy that aims to associate the brand with influential users.     

The element of surprise: the diverse impact of slightly alternative specifications of context on opinion formation in multi-level modeling

The rise of multi-level modeling in social sciences brings new challenges. Multi-level modeling, although used in a great variety of ways, aims at simultaneously assessing the impact of individual-level and context-level characteristics on a dependent variable that is measured at the individual level. However, comprehending how public opinion is affected by context and how people experience contextual changes is a challenge. Little scholarly attention has been paid to the way context is incorporated in these models. The current study compares the use of the same independent variable (GNI) measured in three different ways to predict attitudes regarding EU enlargement, trust in the EU, and European Unification in 25 EU countries, using data from the European Social Survey. We introduce an alternative way to measure change, taking a larger time span into consideration, and find that this is a good way to measure contextual surprise. Our findings show that the way a variable is measured greatly influences the size and even direction of the effect. Hence, it is crucial to assess both conceptually and methodologically the best way to measure context before one simply implements a variable and interprets empty results.     

Changing consumer behaviour through eco-efficient services: an empirical study of car sharing in the Netherlands

In this paper ‘innovation’ is discussed as a strategy to change consumer behaviour to reduce the environmental impact of consumption. Innovation aims to improve the ‘production process’ of certain end results or ‘units of service’ for the consumer, which is defined as the ‘consumption technology’. This concept includes the entire organization of how these units of service are produced. ‘Eco-efficient services’ are introduced as an innovation strategy, based on theoretical considerations through which more eco-efficient consumption technologies and less environmentally damaging consumption behaviour could be realized. This strategy is explored through an empirical consumer behaviour study on commercial car sharing services in the Netherlands. Based on an inventory of the environmental effects of this approach, as exemplified by the car sharing schemes, it can tentatively be concluded that the eco-efficient services concept offers an interesting framework for reconsidering the current consumption practice and for generating innovative activities in industry. © 1998 John Wiley & Sons, Ltd and ERP Environment.     

How advertising in offline media drives reach of and engagement with brands on Facebook

ABSTRACT

Research investigating the drivers of consumers’ engagement with brands on social media is proliferating. However, little is known about how advertising outside social media drives engagement with brands on social media. This study aims to explore the relation between advertising spend in different offline media (TV, radio, newspapers, magazines, out of home), and reach of and engagement with brand pages on Facebook. The study uses a unique real-life data-set containing information about the Facebook pages of 45 brands for approximately three years combined with Nielsen Advertising Spend data. Results showed that while advertising in offline media influenced organic and viral reach, the number of page likes was directly influenced by advertising on Facebook only. It can be concluded that offline advertising is relevant in driving consumers’ online brand engagement; however, there is a unique set of drivers for organic reach, viral reach and likes.     

Moving up. Applying aggregate level time series analysis in the study of media coverage

In this article the advantages of aggregate level time series analysis for the study of media coverage are discussed. This type of analysis offers the opportunity to answer questions relating to causes and effects of media attention for issues and all kind of other content characteristics. Data that ask for a time series approach have become widely available during the past years, due to the rise of digital archives and social media such as Twitter and Facebook. This type of analysis allows for answering a set of interesting research questions and strong inferences about causal processes. Common challenges in time series analysis, relating to stationarity, accounting for a series’ past and autoregressive conditional heteroscedasticity are discussed. Two useful approaches, ARIMA and VAR, are introduced stepwise. An empirical example, dealing with intermedia agenda-setting between different newspapers in the Netherlands, demonstrates how both techniques can be applied and how they provide insightful answers to interesting research problems.     

Wage rigidity and job creation

Recent research in macroeconomics emphasizes the role of wage rigidity in accounting for the volatility of unemployment fluctuations. We use worker-level data from the CPS to measure the sensitivity of wages of newly hired workers to changes in aggregate labor market conditions. The wage of new hires, unlike the aggregate wage, is volatile and responds almost one-to-one to changes in labor productivity. We conclude that there is little evidence for wage rigidity in the data.     

People management: developing and testing a measurement scale

Abstract

The central concept in this study is people management, referring to line managers’ implementation of HR practices and their leadership behaviour oriented at supporting the employees they supervise at work. In this study we conceptualize people management and develop a multidimensional scale to measure it from the perspectives of both employees and line managers. Using a Study 1/Study 2 design, including two-wave multilevel data from employees and line managers of a financial service provider, and cross-sectional data from teachers, educational support staff, and supervisors, we demonstrate the scale’s reliability and multidimensionality across samples and over time. We provide evidence of the convergent validity by showing that employees’ and line managers’ perceptions of people management are significantly related, and that people management is significantly related to transformational and transactional leadership. Also, we demonstrate that people management adds explained variance above and beyond transformational and transactional leadership in predicting team performance. We demonstrate criterion-related validity through people management’s relationship with job satisfaction, commitment, and work engagement. We discuss the implications of our measure for theory and research on people management, its antecedents, and its effects.