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We consider the situation where multiple transportation service providers cooperate to offer an integrated multi-modal platform to enhance the convenience to the passengers through ease in multi-modal journey planning, payment, and first and last mile connectivity. This market structure allows the multi-modal platform to coordinate profits across modes and also provide incentives to the passengers. Accordingly, in this paper, we use cooperative game theory coupled with the hyperpath-based stochastic user equilibrium framework to study such a market. We assume that the platform sets incentives (price discount or excess charge on passengers) along every edge in the transportation network. We derive the continuity and monotonicity properties of the equilibrium flow with respect to the incentives along every edge. The optimal incentives that maximize the profit of the platform are obtained through a two time-scale stochastic approximation algorithm. We use the asymmetric Nash bargaining solution to design a fair profit sharing scheme among the service providers. We show that the profit for each service provider increases after cooperation on such a platform. Finally, we complement the theoretical results through two numerical simulations. [ABSTRACT FROM AUTHOR]

• A game theory approach in the reverse supply chain of ELVs collection is defined. • An ELV take-back center, an inspection center, and a repair center are considered. • The equilibrium values in the centralized and decentralized scenarios are obtained. • The impact of subsidy of the government on the supply chain centers is analyzed. • The best contract to increase the level of repair is the revenue-sharing contract. The presence of end-of-life vehicles (ELV) in the cities creates irreparable damage in environmental and economic terms. Thus, governments have been searching for ways to collect ELVs. An effective way to address ELVs is subsidies' policy. In this study, a supply chain including an ELV take-back center, an inspection center, and a repair center are considered. The decision variables are the purchase price of the ELVs, the sale price of the repaired vehicle, and the level of vehicle repair. In this supply chain, the government pays a subsidy to take-back centers that deliver their used vehicles. A Stackelberg game structure is considered with the government as the leader, the inspection center as the primary follower, and the collection and repair centers as the second followers. Using the game theory approach, the effects of government subsidies on equilibrium values of the decision-making variables of the centers in the ELV supply chain have been investigated in three scenarios. The scenarios comprise profit sharing, revenue sharing, and a centralized (cooperative) scenario. The results indicate that the centralized scenario has the most significant advantage compared to the two contracts of profit sharing and cost sharing. For example, the repair level of the ELVs, the amount of repaired vehicles demand, consumer surplus, and the whole supply chain's profit are at their maximum. The most significant impact of subsidy payment is related to the take-back center's profit and the ELV supply. On the other hand, the subsidy does not affect the profit of the repair center. [ABSTRACT FROM AUTHOR]

In virtual communities of practice, many participants use their knowledge to achieve a common goal based on cooperation, and the key to such cooperation is knowledge collaboration. Knowledge collaboration is the primary method of increasing the virtual community of practice's knowledge ability and achieving the core competency advantage of sustainable growth. Knowledge collaboration inevitably involves the psychological elements of the collaborators. This study focuses on the elements of the psychological contract of the members of the virtual community of practice when participating in knowledge collaboration; the psychological contract summarizes the members’ collaboration via seven psychological factors spread across two dimensions. Based on these factors, this study uses the game theory to create a cost game model and profit-sharing game model in the virtual community of practice knowledge collaboration. The cost game model is built upon Stackelberg equilibrium, the model is solved using backward induction, and its effectiveness is established. The profit-sharing model is based upon a modified Nash bargaining solution; the model is applied to the Python software development team in the Github community of practice and yields positive results. Finally, the research outcomes are summarized, and directions for future research are provided. [ABSTRACT FROM AUTHOR]

- The primary purpose of this paper is to perform optimal energy management in a distribution network (DN) consisting of several microgrids (MG). A cooperative game method has been used to achieve the best coalitions to diminish the total system costs. A fair profit-sharing procedure is defined as the individual contribution value (ICV) to share profits between players. In addition to ICV, as an economic indicator, the DN's maximum voltage deviation (MVD) in each game has been used to allocate rewards to each game's players (MGs). Studies have been executed on a modified 33-bus DN consisting of three distinct MGs. In the system under study, there is no direct connection among MGs. The case study also deliberates the uncertainties of RESs and technical real power losses in the DN considering demand response program. The paper results concede that despite the reduction in the costs of MMGs due to the application of DRP, it is still possible to reduce the total costs of an MMG system by forming coalitions and adopting proper procedures to profit allocation. In addition, the proposed profit-sharing method based on ICVs and MVDs is simple, consistent, and clear, thus facilitating calculations. Examining the games one by one also identifies the inappropriate games/players to form a coalition and helps reduce problem size in the upcoming scheduling. Solutions obtained through the combined use of ICV and MVD indicators are more profitable, have better technical characteristics, and lead to larger alliances with more MGs participation, increasing network flexibility. [Display omitted] • Proposing a novel criterion for profit-sharing in multi-microgrid energy management based on cooperative game theory. • Considering renewable energy sources uncertainties via scenario generation-reduction process. • Including price-based demand response programs in microgrids integrated into the distribution network. • Solving optimal energy management problem where cost-technical performance are considered. [ABSTRACT FROM AUTHOR]

We develop a (noncooperative) game theoretic model for a decentralized setting wherein fringe farmers compete with a two-tier cooperative network involving network farmers and a coordinator. We examine the roles of the coordinator and profit sharing in allocating costs/benefits of externalities in enhancing network efficiency and stability. Our main finding is that using profit sharing based mechanism the coordinator can overcome inherent inefficiency and instability of decentralization and noncooperative behavior of the network farmers. The roles of the coordinator and profit sharing are particularly important when it is economical for both network and fringe farmers to supply the product. [ABSTRACT FROM AUTHOR]

The highly distributed and frequently changing resources, as well as the rising costs and uncertainties of developing and launching new products necessitate that firms continuously collaborate in R&D projects. However, management of new product development, especially the leadership assignment of the sustainable collaboration between firms, presents a new set of challenges in sharing the benefits of innovation. This paper conceptualizes and formulates a sustainable collaborative R&D project involving two firms with diverse R&D and leadership technologies. Based on game theory, it examines the optimal mechanism of profit allocation and leadership distribution from a sustainability perspective that outweighs investigating them alone. The analysis shows that when leadership is technically impossible, the optimal profit allocation to each firm should be positively related to its comparative importance in the collaborative innovation project. However, when the two firms are much dependent on each other to complete the project, the focal firm, which is usually more important in the project, needs to give up more its profit shares to the partner firm to lighten the bottleneck R&D effects and induce a sustainable collaboration with partner firm. In contrast, when leadership is technically possible, the optimal leadership distribution for sustainable and effective collaboration depends on the interplay relationships between each firm's comparative importance in the collaborative R&D project, leadership ability, and the R&D and leadership efforts and costs. Furthermore, it is also found that distributing leadership to a firm with absolute dominances is always preferred to distributing to a firm with absolute weaknesses in both R&D and leadership technologies. • A higher degree of teamwork tends to result in a more equal profit allocation scheme. • One firm with lower R&D costs will not only increase the value of its own efforts but also its partner firm's efforts at a slightly lower rate. • The optimal sustainable profit allocation held by each firm should be positively related to its relative importance in the collaborative R&D project. • The less important firm should be allocated more profits than proportional to its relative importance in the project. • It is optimal to let the firm with both advantages in R&D and leading technologies to be the leader of the sustainable collaborative R&D project. [ABSTRACT FROM AUTHOR]