Adriatic Sea Hub Ports Feeder Service Optimization Using Multi-Criteria Decision-Making Methods

From a scientific viewpoint, as well as from the perspective of navigation practice, it is clear that the Adriatic Sea feeder service is relatively underdeveloped. Hence, the objective of this study is to suggest a model for selecting the hub port and to optimize the network of seaports engaged in the feeder service. Accordingly, an appropriate hub port has been identified through the methods of multi-criteria decision making and expert assessment, and the optimum shipping route has been calculated by applying the travelling salesman algorithm (TSA). In order to analyze whether there is a possibility of obtaining better optimization results, an integration of a sub-hub port system is suggested. Optimization has been achieved by applying a minimum spanning tree algorithm (MST) and a combination of these algorithms. The proposed methodology for selecting the hub port, sub-hub port and optimizing the feeder network can be implemented globally. The practical application of the achieved model would result in cost minimization, owing to shorter shipping routes or a combination of different transportation means (feeders).

Effects of Digital Platform Openness on Recognition of Entrepreneurial Opportunities and Integration of Entrepreneurial Resources

Drawing on the theories of open innovation and entrepreneurship, this paper discusses the action mechanism of digital platform openness (DPO) on the recognition of entrepreneurial opportunities (EOR) and the integration of entrepreneurial resources (ERI) and explores the boundary conditions of this mechanism. Several hypotheses were put forward and verified by analysing 302 valid questionnaires. The results show that the breadth and depth of DPO positively affect EOR and ERI; these positive effects are positively moderated by the service level of the digital platform. The research findings provide a reference to digital platform enterprises to decide on platform opening strategy and platform service optimization.

B2C online ride-hailing pricing and service optimization under competitions

<p style='text-indent:20px;'>B2C online ride-hailing is to provide customers with anytime, anywhere and on-call ride services by professional vehicles and professional drivers. How to maintain good service quality and reasonable pricing under competition is of importance to a platform. In this paper, we will integrate pricing and service together to maximize the profit of a platform through Nash game theory. Specifically, we will establish the models for there scenarios: the demand market competition under decline of ride demand, the supply market competition under surge of ride demand, and the coexistence of demand and supply market competition for stable ride demand. Then, the Nash equilibriums are derived for the three models which are corresponding to minimize ride price, optimize quality of efforts and maximize profit. Our results uncover that the driver's incentive amount is conducive to the profit of both platform and the drivers for the case of demand market competition. The platforms and drivers achieve the highest profit under supply market competition, and the strategy through minimizing price and maximizing service can effectively adjust the balance between market supply and demand.</p>