@article{44092,
  abstract     = {{We study how competition between physicians affects the provision of medical care. In
our theoretical model, physicians are faced with a heterogeneous patient population, in which patients
systematically vary with regard to both their responsiveness to the provided quality of care and their
state of health. We test the behavioral predictions derived from this model in a controlled laboratory
experiment. In line with the model, we observe that competition significantly improves patient benefits
as long as patients are able to respond to the quality provided. For those patients, who are not able
to choose a physician, competition even decreases the patient benefit compared to a situation without
competition. This decrease is in contrast to our theoretical prediction implying no change in benefits for
passive patients. Deviations from patient-optimal treatment are highest for passive patients in need of
a low quantity of medical services. With repetition, both, the positive effects of competition for active
patients as well as the negative effects of competition for passive patients become more pronounced. Our
results imply that competition can not only improve but also worsen patient outcome and that patients’
responsiveness to quality is decisive.}},
  author       = {{Brosig-Koch, Jeannette and Hehenkamp, Burkhard and Kokot, Johanna}},
  journal      = {{Health Economics}},
  keywords     = {{physician competition, patient characteristics, heterogeneity in quality responses, fee-for-service, laboratory experiment}},
  title        = {{{Who benefits from quality competition in health care? A theory and a laboratory experiment on the relevance of patient characteristics}}},
  doi          = {{10.1002/hec.4689}},
  year         = {{2023}},
}

@inproceedings{31847,
  abstract     = {{The famous $k$-Server Problem covers plenty of resource allocation scenarios, and several variations have been studied extensively for decades. However, to the best of our knowledge, no research has considered the problem if the servers are not identical and requests can express which specific servers should serve them. Therefore, we present a new model generalizing the $k$-Server Problem by *preferences* of the requests and proceed to study it in a uniform metric space for deterministic online algorithms (the special case of paging).

In our model, requests can either demand to be answered by any server (*general requests*) or by a specific one (*specific requests*). If only general requests appear, the instance is one of the original $k$-Server Problem, and a lower bound for the competitive ratio of $k$ applies. If only specific requests appear, a solution with a competitive ratio of $1$ becomes trivial since there is no freedom regarding the servers' movements. Perhaps counter-intuitively, we show that if both kinds of requests appear, the lower bound raises to $2k-1$.

We study deterministic online algorithms in uniform metrics and present two algorithms. The first one has an adaptive competitive ratio dependent on the frequency of specific requests. It achieves a worst-case competitive ratio of $3k-2$ while it is optimal when only general or only specific requests appear (competitive ratio of $k$ and $1$, respectively). The second has a fixed close-to-optimal worst-case competitive ratio of $2k+14$. For the first algorithm, we show a lower bound of $3k-2$, while the second algorithm has a lower bound of $2k-1$ when only general requests appear.
    
The two algorithms differ in only one behavioral rule for each server that significantly influences the competitive ratio. Each server acting according to the rule allows approaching the worst-case lower bound, while it implies an increased lower bound for $k$-Server instances. In other words, there is a trade-off between performing well against instances of the $k$-Server Problem and instances containing specific requests. We also show that no deterministic online algorithm can be optimal for both kinds of instances simultaneously.}},
  author       = {{Castenow, Jannik and Feldkord, Björn and Knollmann, Till and Malatyali, Manuel and Meyer auf der Heide, Friedhelm}},
  booktitle    = {{Proceedings of the 34th ACM Symposium on Parallelism in Algorithms and Architectures}},
  isbn         = {{9781450391467}},
  keywords     = {{K-Server Problem, Heterogeneity, Online Caching}},
  pages        = {{345--356}},
  publisher    = {{Association for Computing Machinery}},
  title        = {{{The k-Server with Preferences Problem}}},
  doi          = {{10.1145/3490148.3538595}},
  year         = {{2022}},
}