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Targeted Promotions on an E-Book Platform: Crowding Out, Heterogeneity ...

https://www.fox.temple.edu/sites/fox/files/targeting-crowdout-jmr19.pdf

Abstract Targeted promotions based on individual purchase history can increase sales. However, the opportunity costs of targeting to optimize promoted product sales are poorly understood. A series of randomized field experiments with a large e-book platform shows that although targeted promotions increase promoted product sales and purchases of similar products, they can crowd out purchases of ...

Contemporaneous and Delayed Sales Impact of Location-Based Mobile ...

https://www.fox.temple.edu/sites/fox/files/ISR-delayed-effects.pdf

Can location-based mobile promotion (LMP) trigger contemporaneous and delayed sales purchases? As mobile technologies can reach users anywhere and anytime, LMP becomes a promising new channel. We unravel the dynamic sales impact of LMP on the basis of a randomized field experiment with 22,000 mobile users sponsored by one of the largest mobile service providers in the world. Our identification ...

Lecture 6 – Chapter 3 TCP flow and congestion control

https://cis.temple.edu/~tug29203/19spring-5617/lectures/ch3-3.pdf

Lecture 6 – Chapter 3 TCP flow and congestion control CIS 5617, Fall 2019 Anduo Wang Based on Slides created by JFK/KWR

Oral Health Advocacy Toolkit Strategies and Resources for Dental ...

https://dentistry.temple.edu/sites/dentistry/files/Oral_Health_Advocacy_Toolkit.pdf

Dental and dental hygiene academia, therefore, should prepare future dental professionals to become strong advocates of oral health in their communities. In support of this objective, the Temple University’s Maurice H. Kornberg School of Dentistry developed this toolkit primarily for dental, dental hygiene, and dental residency programs that wish to initiate advocacy training or refine their ...

Distributed Deep Multi-Agent Reinforcement Learning for Cooperative ...

https://cis.temple.edu/~jiewu/research/publications/Publication_files/Distributed_Deep_Multi-Agent_Reinforcement_Learning_for_Cooperative_Edge_Caching_in_Internet-of-Vehicles.pdf

Abstract—Edge caching is a promising approach to reduce duplicate content transmission in Internet-of-Vehicles (IoVs). Sev-eral Reinforcement Learning (RL) based edge caching methods have been proposed to improve the resource utilization and reduce the backhaul trafic load. However, they only obtain the local sub-optimal solution, as they neglect the influence from environments by other ...