Does telic/paratelic user mode matter on the effectiveness of interactive internet advertising? A reversal theory perspective

Drawing on reversal theory (Apter, 2007), the current research proposes that internet users' metamotivational state (telic vs. paratelic) determines advertising interactivity's effectiveness. An online field experiment involving 141 Facebook and Twitter users tests this proposition. Research findings support telic state consumers form more positive attitudes toward a low-level interactive ad, whereas paratelic state consumers form more positive attitudes toward a high-level interactive ad. Further, this research shows that an arousal seeking tendency mediates the metamotivational state's impact on ad attitude.     

西方消费文化理论研究的发展、演变与反思

西方消费文化理论运用了社会学、哲学、历史学、政治学等跨学科研究方法，经历了传统社会、现代社会到后现代社会的深刻变化，形成了炫耀性消费、符号消费等诸多理论，对其进行全面评述，并加以批判性运用，是当前西方消费文化研究的重要任务。     

A signalling model of school grades under different evaluation systems

We examine the role of school grades as a signal of worker productivity under different examination systems in relation to errors that may affect student performance. Firms use school grades as a signal of workers’ effective skills, taking into account that these evaluations are effected by stochastic shocks. We show that more precise evaluation systems, being associated with a higher reactivity of wages to school grades, induce students to provide more effort. Low ability students tend to react less than high ability students. Moreover, individuals with low abilities may prefer less accurate evaluation systems. Nevertheless, when productivity increases, these systems become less convenient and the number of individuals preferring them diminishes. Our analysis highlights an important trade-off between centralised and decentralised evaluation systems. On the one hand, frequent evaluations, typical of decentralised systems, weaken the impact on grades of those errors which influence student performance and, so, reduce signal noise, while, on the other hand, different teachers generally adopt different performance assessment standards, leading to noisier evaluations.     

Understanding repeat playing behavior in casual games using a Bayesian data augmentation approach

With an estimated market size of nearly $18 billion in 2016, casual games (games played over social networks or mobile devices) have become increasingly popular. Because most casual games are free to install, understanding repeat playing behavior is important for game developers as it directly drives advertising revenue. Game developers are keenly interested in benchmarking their game versus the market average, and understanding how genre and various game mechanics drive repeat playing behavior. Such cross-sectional analysis, however, is difficult to conduct because individual-level data on competitors’ games are not publicly available, and that the casual gaming industry is highly fragmented with each firm making only a handful of games.I develop a Bayesian approach, based on a parsimonious Hidden Markov Model at the individual level in conjunction with data augmentation, to study repeat playing behavior using only publicly available data. After applying the proposed approach to a sample of 379 casual games, I find that the average daily attrition rate across game is around 36.5%, with an average “play” rate of 47.9%, resulting in an average ARPU (average revenue per user) across games of around 20.5 cents. Certain genres are linked to higher attrition rates and play rates. In addition, giving out a “daily bonus” or limiting the amount of time that gamers can play each day are associated with a 17.7% and 16.4% higher ARPU, respectively.