Manned-unmanned teaming can be a very promising air-to-air combat tactic since it can maximize the advantage of combining human insight with the robustness of the machine. The rapid advances in artificial intelligence and autonomous control technology will speed up the development of manned-unmanned teaming air-to-air combat system. In this paper, we introduce a manned-unmanned teaming air-to-air combat tactic which is composed of a manned aircraft and an UAV. In this tactic, a manned aircraft equipped with radar is functioning both as a sensor to detect the hostile aircraft and as a controller to direct the UAV to engage the hostile aircraft. The UAV equipped with missiles is functioning as an actor to engage the hostile aircraft. We also developed a combat scenario of executing this tactic where the manned-unmanned teaming is engaging a hostile aircraft. The hostile aircraft is equipped with both missiles and radar. To demonstrate the efficiency of the tactic, we run the simulation of the scenario of the tactic. Using the simulation, we found the optimal formation and maneuver for the manned-unmanned teaming where the manned-unmanned teaming can survive while the hostile aircraft is shot-downed. The result of this study can provide an insight to how manned aircraft can collaborate with UAV to carry out air-to-air combat missions.

By increasing awareness of product offers and availability in the consumer’s proximity, Location Based Marketing (LBM) increases relevance of placed advertisements. However, depending on how it is executed, such advertising can also be perceived as intrusive, irritating, or even violating consumer’s privacy. Existing knowledge does not offer clear directions for retailers, who are keen to know of LBM’s effectiveness on sales. In this paper, authors investigate the effects of LBM on application (app) driven revenues of 116 major mobile retailers from around the globe. In particular, we examine the contingency effects of the roles of device as well as privacy needs of the brand audience. Findings reveal that effects of LBM on app-based revenues vary by tactic (inbound vs. outbound), type of device (Tablet vs. Phone), and user type based on brand of app (Android vs. Apple). Overall, this research identifies critical factors for retailers to consider, in order to best monetize their location based efforts. Contributions of the analysis and managerial implications are discussed.