Optimal Workfare in Unemployment Insurance

Most workers are only partially insured against unemployment. One reason is that high unemployment compensation creates a free rider problem when monitoring of job search behavior is limited; people who do not seek employment (non-workers) may nevertheless collect unemployment compensation. We show that unproductive workfare for unemployed workers may improve unemployment insurance if workers and non-workers value leisure differently. If they differ only with respect to productivity workfare has to be based on a productivity related task requirement (task workfare); a simple time requirement (time workfare) is not enough. Task workfare is simply a better screening device, also implying that task workfare Pareto dominates time workfare. Finally, we show that the scope for using workfare is larger the smaller are the transfers from workers to non-workers.workfare; unemployment insurance

RFID-based Recommender Systems in Stationary Trade

Recommender Systems have been successfully deployed in a variety of e-Commerce application scenarios. Customer selections of services or standard goods are supported as well as product configuration tasks. Little research has however been done on the application of Recommender Systems outside the virtual domain in real-world stationary trade. This surprises as on a business side, brick-and-mortar stores remain the primary distribution channel for products of daily usage. On a technical side, the growing popularity of RFID-transponders for product identification has laid the foundation for generating both context-aware and user-adaptive product recommendations. This contribution describes approaches and challenges of utilizing concepts from the realm of Recommender Systems in RFID-enabled stationary trade

CONSUMERS FACING SUPRA-COMPLEX CHOICES IN THE MODERN MARKETPLACE

In this paper, we suggest that many of the choice situations confronting consumers in the modern marketplace have become supra-complex. Supra-complex decision-making occurs when the perceived difficulty of transforming product information into knowledge exceeds the expected benefits of doing so, even if decision-making heuristics, or other kind of attribute-related decision rules, are applied. Under conditions of supra-complexity, we propose that consumers instead use mental markers in order to justify their decisions. Mental markers are any mental construct the consumer uses for the purpose of gaining mental justification of overall choices. We argue that the usage of mental markers leads to reductions in cognitive dissonance, reduced usage of mental resources and time. Drawing on the principle of mental justification as well as consumers’ propensity to use goals as blueprints for directing their behaviour, we propose a framework for understanding consumer decisions when faced with supra-complexity