High-speed railway (HSR) is recognized as a green transportation mode with lower energy consumption and less pollution emission than other transportation. At present, China has the largest HSR network globally, but the maximum revenue of railway transportation corporations has not been realized. In order to make HSR achieve a favorable position within the fierce competition in the market, increase corporate revenue, and achieve the sustainable development of HSR and railway corporations, we introduce the concept of revenue management in HSR operations and propose an innovative model to optimize the price and seat allocation for HSR simultaneously. In the study, we formulate the optimization problem as a mixed-integer nonlinear programming (MINLP) model, which appropriately captures passengers’ choice behavior. To reduce the computational complexity, we further transform the proposed MINLP model into an equivalent model. Finally, the effectiveness of both the proposed model and solution algorithm are tested and validated by numerical experiments. The research results show that the model can flexibly adjust the price and seat allocation of the corresponding ticketing period according to the passenger demand, and increase the total expected revenue by 5.92% without increasing the capacity.
In order to improve the high-speed trains' service levels and increase their market shares, the Chinese high-speed railway (HSR) enterprise is reforming its ticket pricing strategy. A collaborative model that incorporates seat allocation decision into HSR dynamic pricing problem based on the revenue management theory is proposed, in which the objective is to maximize the total ticket revenue of enterprise under the constrains of price ceilings. A two-stage algorithm is developed to solve practical problems. The first stage solves the optimal price problem, and the second is to obtain the optimal seat allocation decisions. Finally, a case study based on the actual ticket data of Beijing-Shanghai HSR in China is implemented to show the effectiveness of the proposed approach, for which the results show that compared with the fixed price case, the revenue improvement ranges from 4.47% to 4.95% by using dynamic pricing strategy. Also, the case analysis shows that dynamic pricing strategy will lead to an increase in short-haul demands whereas a decrease in long-haul demands.INDEX TERMS High-speed railway (HSR), dynamic pricing, seat allocation, collaborative optimization, revenue management (RM).
The railway container transportation is attracting more and more attention in China. In order to improve the service quality, a novel concept of passenger-like container train is proposed, which can reduce the accumulation time of containers at the origin station and increase the train frequency compared with the traditional container through train. With the aim of generating optimal operation strategies for passenger-like container trains, this paper establishes an optimization model for the train stop plan problem, in which the objective is to minimize the total number of stops. In addition, the specific container-to-train distribution and the utilization rate of each individual train are considered. The proposed model is a mixed-integer linear programming one, which can be solved by using the CPLEX solver. Finally, the numerical experiments are performed to test the effectiveness of our model by using a simple railway line and the China Railway Express corridor as examples. The results prove the advantages of our method.
Despite the growing body of literature on the influence of industrial agglomeration on urban innovation, no consensus has been reached on the mechanism of the spillover effect. This empirical study exploits heterogeneity in spillover effects between manufacturing and producer service agglomerations on urban innovation based on a sample of 262 prefecture-level cities in China. We find some intriguing and new findings: (1) The threshold effect can be identified for the spillover effect of manufacturing agglomeration but not for that of producer service agglomeration. (2) Manufacturing and producer service agglomerations have opposite decomposition indirect effect. (3) The spatial spillover effect of industrial agglomeration can be restrained by absorptive capacity of nearby cities. This study not only provides empirical evidence for the reconciliation of the debate on the effect of manufacturing and producer service agglomeration, but also has important policy implication for reconsidering the role of industrial agglomeration in urban innovation.
The accurate distinction between cities and villages plays a great role in the sustainable development of cities. The physical urban area is not artificially delimited, and reflects the objective distribution of the spatial scope of the urban area. Although there are many methods that have studied and explained the physical urban area to a certain extent, the influencing factors of identification threshold are not studied deeply. In this paper, 22 administrative districts in central and western Chongqing Municipality are taken as the research object. Based on vector building data, the urban expansion curve method is used to identify the optimal distance threshold to extract the physical urban area of Chongqing Municipality. And the geographical detector technique is used to detect respectively that how and to what extent the urban spatial structure factors, geographical environment factors and social economic factors affect the optimal distance threshold of 22 administrative districts. The results show that the optimal distance threshold for identifying physical urban area of Chongqing Municipality based on the vector building is 146m, and the physical urban area is 1598.43km2, with the error of 2.1% compared with the built-up area. Taking 22 administrative districts as the individual research objects, it is found that the road network density and building density in urban spatial structure factors, urbanization rate and urban population density in socio-economic factors, and their interaction with regional GDP play a critical role in the optimal distance threshold, and the index value of influence degree ≥ 0.79. Under the influence of different factors, the optimal distance thresholds of 22 administrative districts show adaptive characteristics. Looking forward to the future, quantitative analysis of the relationship between the structural scale, economic indicators, geographical environment and the optimal distance threshold of different levels of cities will help to understand the driving mechanism that affects physical urban area identification more deeply. The adaptive characteristics of the optimal distance threshold proposed in this paper also provide a theoretical basis for further study on the morphological characteristics and distribution laws of multi-scale cities.
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