Evaluating the First-Mover's Advantage in Announcing Real-Time Delay Information
40 Pages Posted: 7 Dec 2017 Last revised: 12 Dec 2019
Date Written: December 2, 2017
(1) Problem definition: Internet-based technology advancements have enabled service providers to disseminate real-time delay estimates to customers who are strategic and delay-sensitive. In a market with two service providers who compete for market share, we investigate whether one of the service providers (the technology leader L) should make the first move to announce her real-time delay information, when her competitor (the follower F) can opt to respond.
(2) Academic/Practical Relevance: From L's viewpoint, it is crucial to evaluate the impact of delay announcements on her market share and whether the technology investment required for such an initiative is justified---an important question that has not been addressed in the delay announcement literature in such a setting.
(3) Methodology: We model and analyze the leader-follower setting as a sequential game and employ continuous-time Markov chains to address the queueing aspects of our research questions.
(4) Results: We find that L's optimal action depends on the relative service capacities of the service providers: When L has significantly lower service capacity (roughly more than 20% lower), it is optimal for her to initiate delay announcements. On the other hand, when she has significantly higher capacity (roughly more than 20% higher), it is optimal for her not to initiate delay announcements. When service capacities are not significantly different, her optimal action depends on system load.
(5) Managerial Implications: Managers of service providers with significantly higher service capacities should expect market share erosion to result from real-time delay broadcast. For a significantly lower-capacity service provider, delay announcements can be considered a strategic remedy for capacity shortage.
Keywords: service operations, delay announcements, admission control, sequential games, continuous time Markov chains
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