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Flights are often delayed owing to emergencies. This paper proposes a cooperative slot secondary assignment (CSSA) model based on a collaborative decision-making (CDM) mechanism, and the operation mode of flight waves designs an improved intelligent algorithm to solve the optimal flight plan and minimize the total delay of passenger time.

Taking passenger delays, transfer delays and flight cancellation delays into account comprehensively, the total delay time is minimized as the objective function. The model is verified by a linear solver and compared with the first come first service (FCFS) method to prove the effectiveness of the method. An improved adaptive partheno-genetic algorithm (IAPGA) using hierarchical serial number coding was designed, combining elite and roulette strategies to find pareto solutions.

Comparing and analyzing the experimental results of various scale examples, the optimization model in this paper is greatly optimized compared to the FCFS method in terms of total delay time, and the IAPGA algorithm is better than the algorithm before in terms of solution performance and solution set quality.

Based on the actual situation, this paper considers the operation mode of flight waves. In addition, the flight plan solved by the model can be guaranteed in terms of feasibility and effectiveness, which can provide airlines with reasonable decision-making opinions when reassigning slot resources.

Supplier–supplier coopetition is vital to buyer innovation in reality. However, it has not received enough attention in prior research. Integrating the ability-motivation-opportunity framework of organizational learning perspective and the awareness-motivation-capability framework of competitive dynamics theory, this paper investigates the effect of supplier–supplier coopetition within supplier network on buyer innovation, as well as the contingent role of the relational attributes -- duration and tie strength dispersion of buyer–suppliers relationship at the supplier network level.

Testing this model on the secondary data of supply networks formed by 204 US listed buyer firms in SIC code 28, 35, 36 during 2008–2019, the authors utilize a fixed-effect regression model to investigate the relationship between supplier–supplier coopetition and the focal buyer's innovation.

The authors provide support for the positive influence of supplier–supplier cooperation on buyer innovation and an inverted U-shaped relationship between supplier–supplier competition and the focal buyer's innovation. The buyer–suppliers tie strength dispersion amplified the above two effects, and supplier–supplier cooperation mitigates the effect of supplier–supplier competition on the focal buyer's innovation.

Extending the traditional dyadic view to a network-level view via linking the supplier–supplier dyad and the buyer–suppliers dyad, this paper contributes to a better understanding of supplier–supplier coopetition and its impact on buyer innovation with learning and competitive tension as the underlying explanations, and validates the contingent role of buyer–suppliers relational attributes.