Seller Organization and Percentage Fee Design in the Daily Deal Market

The prosperity of the daily deal business has attracted more sellers to participate in daily deal campaigns with offering discounted deals via online platforms like Groupon and Juhuasuan. This gives rise to a new challenge for online platforms on how to efficiently organize a limited number of sellers to conduct daily deal campaigns. Our paper makes the first attempt to understand how different seller organization formats can influence the firms’ equilibrium strategies and profits in the daily deal market. We focus on two prevalent seller organization formats. (1) The seller agglomeration strategy: the platform (e.g., Groupon) does not distinguish the sellers’ type in each round of the campaign. (2) The seller segmentation strategy: the platform (e.g., Juhuasuan) organizes sellers of the same type in each round. Comparing to the agglomeration strategy, we show that the segmentation strategy can eliminate internal information asymmetry among competing sellers and thus can improve the sellers’ pricing efficiency and facilitate the platform to charge a higher percentage fee. This uncovers the value of seller segmentation and theoretically explains why platforms should carefully segmentate sellers in daily deal campaigns, although considerable efforts are required to enroll sellers.

Inter-Port Competition and Cooperation Under Different Market Environments

Aiming at the competition and cooperation decision-making problem between two ports in the same regional port group, this paper studies four kinds of dynamic game scenarios of two adjacent ports—namely, independent strategy–independent strategy (i.e., DD combinations), independent strategy–integrated strategy (i.e., DT combinations), integrated strategy–independent strategy (i.e., TD combinations), and integrated strategy–integrated strategy (i.e., TT combinations). By introducing port demand models and using the dynamic game method, the paper performs a comparative study of port service pricing, port demand, and port profit in different combinations of competition and cooperation. The results show that taking port profit as payment function, the equilibrium strategy of the leader port is the independent strategy, which is also the dominant strategy, while the independent strategy or integrated strategy of the follower port depends on the degree of service substitution provided by the two competing ports. When the degree of service substitution is low (0 < γ < 0.53), the equilibrium strategies of two competing ports are the DD combinations, but the equilibrium strategies can be improved by Pareto, and further analysis shows that TT combinations are the Pareto equilibrium strategies at this time. By contrast, when the degree of service substitution provided by the two competing ports is high (0.53 ≤γ < 1), the DT combinations are the equilibrium strategies of the two competing ports, which are also the Pareto equilibrium strategies at this time. The research shows that when the degree of service substitution of the two ports is low, to encourage the two ports to carry out differentiated development of service functions, it is conducive to promote the two ports to adopt the integrated cooperation strategies.

Dynamic Bargaining and Time-Consistency in Linear-State and Homogeneous Linear-Quadratic Cooperative Differential Games

Three different solution concepts are reviewed and computed for linear-state and homogeneous linear-quadratic cooperative differential games with asymmetric players. Discount rates can be nonconstant and/or different. Special attention is paid to the issues of time-consistency, agreeability and subgame-perfectness, both from the viewpoint of sustainability of cooperation and from the credibility of the announced equilibrium strategies.

Biodiversity of marine microbes is safeguarded by phenotypic heterogeneity in ecological traits

Why, contrary to theoretical predictions, do marine microbe communities harbor tremendous phenotypic heterogeneity? How can so many marine microbe species competing in the same niche coexist? We discovered a unifying explanation for both phenomena by investigating a non-cooperative game that interpolates between individual-level competitions and species-level outcomes. We identified all equilibrium strategies of the game. These strategies represent the probability distribution of competitive abilities (e.g. traits) and are characterized by maximal phenotypic heterogeneity. They are also neutral towards each other in the sense that an unlimited number of species can co-exist while competing according to the equilibrium strategies. Whereas prior theory predicts that natural selection would minimize trait variation around an optimum value, here we obtained a mathematical proof that species with maximally variable traits are those that endure. This discrepancy may reflect a disparity between predictions from models developed for larger organisms in contrast to our microbe-centric model. Rigorous mathematics proves that phenotypic heterogeneity is itself a mechanistic underpinning of microbial diversity. This discovery has fundamental ramifications for microbial ecology and may represent an adaptive reservoir sheltering biodiversity in changing environmental conditions.

Algorithm for Computing Approximate Nash Equilibrium in Continuous Games with Application to Continuous Blotto

Successful algorithms have been developed for computing Nash equilibrium in a variety of finite game classes. However, solving continuous games—in which the pure strategy space is (potentially uncountably) infinite—is far more challenging. Nonetheless, many real-world domains have continuous action spaces, e.g., where actions refer to an amount of time, money, or other resource that is naturally modeled as being real-valued as opposed to integral. We present a new algorithm for approximating Nash equilibrium strategies in continuous games. In addition to two-player zero-sum games, our algorithm also applies to multiplayer games and games with imperfect information. We experiment with our algorithm on a continuous imperfect-information Blotto game, in which two players distribute resources over multiple battlefields. Blotto games have frequently been used to model national security scenarios and have also been applied to electoral competition and auction theory. Experiments show that our algorithm is able to quickly compute close approximations of Nash equilibrium strategies for this game.

D2D Mobile Relaying Meets NOMA—Part II: A Reinforcement Learning Perspective

Structureless communications such as Device-to-Device (D2D) relaying are undeniably of paramount importance to improving the performance of today’s mobile networks. Such a communication paradigm requires a certain level of intelligence at the device level, thereby allowing it to interact with the environment and make proper decisions. However, decentralizing decision-making may induce paradoxical outcomes, resulting in a drop in performance, which sustains the design of self-organizing yet efficient systems. We propose that each device decides either to directly connect to the eNodeB or get access via another device through a D2D link. In the first part of this article, we describe a biform game framework to analyze the proposed self-organized system’s performance, under pure and mixed strategies. We use two reinforcement learning (RL) algorithms, enabling devices to self-organize and learn their pure/mixed equilibrium strategies in a fully distributed fashion. Decentralized RL algorithms are shown to play an important role in allowing devices to be self-organized and reach satisfactory performance with incomplete information or even under uncertainties. We point out through a simulation the importance of D2D relaying and assess how our learning schemes perform under slow/fast channel fading.