The Effects of Animation and Format on the Perception and Memory of Online Advertising

Based on a general framework of consumer perception and processing of advertising, this study examines the impact of animation and ad format on the attention and memorization of online ads. Consumer attention to a variety of real-world ads was measured with eye tracking and ad memory was assessed with recognition and recall tests. The results suggest that on average, animation had little or no effect on attention. We did nevertheless observe a strong interaction effect between animation and ad format, which suggests that the effect of animation is conditioned by ad format. Animation has a positive effect on attention to skyscrapers, but a negative one on attention to banners. As to memorization, animation improved recognition effects, but mainly for banners. Surprisingly, consumers could recognize ads without having looked at them, which suggests that online consumers are especially parsimonious in allocating their focal attention and memory resources to irrelevant ads when they are involved in other tasks.     

Organizational factors enhancing customer knowledge utilization in the management of key account relationships

Customer knowledge has become an important topic for both academicians and practitioners in recent years. However, there has been little academic research on the utilization of customer-specific knowledge. This study adds to our understanding in focusing on the relationships between various intra-organizational factors and customer knowledge utilization in the context of key account management. The results of the study show, that the use of teams, top management involvement, KAM formalization and CRM technology enhance the utilization of customer knowledge in the management of large industrial key account customers.     

Product involvement in organic food consumption: Does ideology meet practice?

This study assesses the level of consumers' felt involvement in four distinct product categories of organic food (coffee, bread, fruit, and flour), and examines the role of felt involvement in the broader context of organic food shopping behavior. It is shown that the reason why consumers do not buy organic food regularly despite their positive attitudes is that such ideologically formed attitudes are not present in habitual, low‐involvement shopping activities with limited problem‐solving needs as in food shopping from grocery stores. The statistical analysis of an empirical sample of 200 consumers gives substantial support to the hypothesized new organic food buying behavior model. © 2009 Wiley Periodicals, Inc.     

Global times and emerging socio‐spatial shapes

Books reviewed in this article: Saskia Sassen (ed.) Global networks ‐ linked cities Sajal Lahiri (ed.) Regionalism and globalization. Theory and practice     

On optimal income taxation with heterogeneous work preferences

This paper considers the problem of optimal income taxation when individuals are assumed to differ with respect to their earnings potential and work preferences. A numerical method for solving this two-dimensional problem has been developed. We assume an additive utility function, and utilitarian social objectives. Rather than solve the first order conditions associated with the problem, we directly compute the best tax function, which can be written in terms of a second order B-spline function. Our findings show that marginal tax rates are higher than might be anticipated, and that very little bunching occurs at the optimum. Our simulation results show that the correlation between taste for work and productivity has a crucial role in determining the extent of redistribution in our model.     

Disruptions in Supply Networks: A Probabilistic Risk Assessment Approach

Supply disruptions are attracting growing attention. Even in geographically, politically and economically stable locations, companies are exposed to disruptions, because they depend on their suppliers and suppliers’ suppliers. The analysis of these disruptions helps mitigate risks: for example, instead of relying on local measures such as safety stock or insurance, a company can introduce new supply contracts or backup risky suppliers. In this article, we analyze risks caused by supplier disruptions by introducing concepts from probabilistic risk assessment (PRA), which is a widely employed methodology for the risk analysis of complex engineering systems. We apply PRA to examine simple networks such as triads analytically, and use simulation to analyze disruption risks in random networks of realistic size. We also illustrate how PRA can support strategic decisions such as whether or not to use single or multiple suppliers; which suppliers are more risky than others; and what impacts the complexity of the supply base has on the reliability of the supplier network.