Cooperative driving around intersections has aroused increasing interest in the last five years.Meanwhile,driving safety in non-signalized intersections has become an issue that has attracted attention globally.In vie...Cooperative driving around intersections has aroused increasing interest in the last five years.Meanwhile,driving safety in non-signalized intersections has become an issue that has attracted attention globally.In view of the potential collision risk when more than three vehicles approach a non-signalized intersection from different directions,we propose a driving model using cooperative game theory.First,the characteristic functions of this model are primarily established on each vehicle’s profit function and include safety,rapidity and comfort indicators.Second,the Shapley theorem is adopted,and its group rationality,individual rationality,and uniqueness are proved to be suitable for the characteristic functions of the model.Following this,different drivers’characteristics are considered.In order to simplify the calculation process,a zero-mean normalization method is introduced.In addition,a genetic algorithm method is adopted to search an optimal strategy set in the constrained multi-objective optimization problem.Finally,the model is confirmed as valid after simulation with a series of initial conditions.展开更多
A nested Stackelberg game among a provider of a product,a sender(existing customer),and a receiver(new customer)is developed to explore the optimal referral reward programs(RRPs)for innovative offerings.The results in...A nested Stackelberg game among a provider of a product,a sender(existing customer),and a receiver(new customer)is developed to explore the optimal referral reward programs(RRPs)for innovative offerings.The results indicate that the provider should forsake RRPs and purely rely on customers'organic word-of-mouth communication under certain conditions.In particular,when the innovativeness of the referred product is extremely high,the provider should forsake RRPs completely,even though few customers will make organic referrals for the product.When the innovativeness is on other levels,the provider should make optimal RRPs decision depending on both the sender's persuasion effectiveness and the tie-strength between the two customers.Moreover,the optimal rewards increase with the innovativeness of the referred product when the provider opts to use RRPs.These results seem contrary to the existing empirical finding to some extent,and it is due to the high referral cost for making a successful referral for the high innovative offerings.展开更多
基金Project(61673233)supported by the National Natural Science Foundation of ChinaProject(D171100006417003)supported by Beijing Municipal Science and Technology Program,China
文摘Cooperative driving around intersections has aroused increasing interest in the last five years.Meanwhile,driving safety in non-signalized intersections has become an issue that has attracted attention globally.In view of the potential collision risk when more than three vehicles approach a non-signalized intersection from different directions,we propose a driving model using cooperative game theory.First,the characteristic functions of this model are primarily established on each vehicle’s profit function and include safety,rapidity and comfort indicators.Second,the Shapley theorem is adopted,and its group rationality,individual rationality,and uniqueness are proved to be suitable for the characteristic functions of the model.Following this,different drivers’characteristics are considered.In order to simplify the calculation process,a zero-mean normalization method is introduced.In addition,a genetic algorithm method is adopted to search an optimal strategy set in the constrained multi-objective optimization problem.Finally,the model is confirmed as valid after simulation with a series of initial conditions.
基金The National Social Science Foundation of China(No.17BGL196)。
文摘A nested Stackelberg game among a provider of a product,a sender(existing customer),and a receiver(new customer)is developed to explore the optimal referral reward programs(RRPs)for innovative offerings.The results indicate that the provider should forsake RRPs and purely rely on customers'organic word-of-mouth communication under certain conditions.In particular,when the innovativeness of the referred product is extremely high,the provider should forsake RRPs completely,even though few customers will make organic referrals for the product.When the innovativeness is on other levels,the provider should make optimal RRPs decision depending on both the sender's persuasion effectiveness and the tie-strength between the two customers.Moreover,the optimal rewards increase with the innovativeness of the referred product when the provider opts to use RRPs.These results seem contrary to the existing empirical finding to some extent,and it is due to the high referral cost for making a successful referral for the high innovative offerings.
