In mobile environments, a personal communication service (PCS) network must keep track of the location of each mobile user in order to correctly deliver calls. A basic scheme used in the standard IS-41 and GSM protocols is to always update the location of a mobile user whenever the mobile user moves to a new location. The problem with this approach is that the cost of location update operations is very high especially when the mobile user moves frequently. In recent years, various location management strategies for reducing the location update cost have been proposed. However, the performance issue of these proposed algorithms remains to be investigated. In this paper, we develop two Markov chains to analyze and compare the performance of two promising location update strategies, i.e., the two location algorithm (TLA) and the forwarding and resetting algorithm (FRA). By utilizing the Markov chain, we are able to quickly answer what-if questions regarding the performance of PCS networks under various workload conditions and also identify conditions under which one strategy can perform better than the others. Using the cost due to location update and search operations between two successive calls to a mobile user as a performance measure, we show that when the mobile user exhibits a high degree of locality and the mobile user‘s call-to-mobility ratio (CMR) is low, TLA can significantly outperform both FRA and IS-41. On the other hand, when CMR is high, FRA is the winner. Furthermore, unlike TLA which may perform worse than IS-41 at high CMR values, FRA at identified optimal conditions can always perform at least as good as IS-41, suggesting that FRA over TLA should be used as a generic scheme in reducing the location cost in the PCS network to cover all possible per-user CMR values.