Price and Non-Price Restraints When Retailers are Vertically Differentiated

This paper considers vertical restraints in the context of an intrabrand competition model in which a single manufacturer deals with two vertically differentiated retailers. We establish two main results. First, we show that if the market cannot be vertically segmented, the manufacturer will foreclose the low quality retailer either directly by dealing exclusively with the high quality retailer, or indirectly by setting a sufficiently high minimum RPM or a sufficiently high wholesale price. Although vertical restraints are not needed to foreclosure the low quality retailer, the manufacturer prefers to impose restraints because they lead to a higher retail price and hence a higher profit. This result means that exclusive dealings with the high quality retailer or an RPM may have anti competitive effects. Moreover, the use of vertical restraints to foreclose low quality retailers is often justified on the grounds that it alleviates a free rider problem in the provision of special services. However since we show that foreclosure occurs even without restraints, it is clear that the benefits associated with foreclosure cannot be used to justify the use of vertical restraints. Second, we show that if the market can be vertically segmented, the manufacturer will impose customer restrictions by requiring the low quality retailer to deal only with consumers whose willingness to pay for quality is below some threshold. We show that this restriction benefits the manufacturer as well as consumers with low willingness to pay for quality, including some that are served by the high quality retailer, but it harms consumers with high willingness to pay for quality.

A Wavelet-Based Approach To Monitoring Parkinson's Disease Symptoms

Parkinson's disease is a neuro-degenerative disorder affecting tens of millions of people worldwide. Lately, there has been considerable interest in systems for at-home monitoring of patients, using wearable devices which contain inertial measurement units. We present a new wavelet-based approach for analysis of data from single wrist-worn smart-watches, and show high detection performance for tremor, bradykinesia, and dyskinesia, which have been the major targets for monitoring in this context. We also discuss the implication of our controlled-experiment results for uncontrolled home monitoring of freely behaving patients.Comment: ICASSP 201