China Railway Express (CRE) is one of the most important constituent parts of the Belt and Road Initiative. Freight demand analysis is fundamental as a basis for the operational strategy of CRE and the investment policy along the CRE-routes. Most of the existing relevant literature has focused on the organization of the train operations of CRE, with little research related to demand analysis. This paper contributes to filling this gap by estimating customers' demand preferences for rail freight service attributes, by using a novel multi-criteria decision-analysis (MCDA) method namely Best-Worst Method (BWM). To this end, a BWM survey was conducted in China to capture customers' preferences for the main attributes that define the transport service offered by CRE. Two variants of BWM, the linear and the Bayesian, are employed for the analysis. Reliability is suggested as the most important attribute for CRE to focus on, to gain customers. We also conduct a cluster analysis based on the results, which helps the CRE operator to identify homogeneous customer segments, and to optimize the use of CRE's resources with a differentiated pricing strategy.
In recent years, although rail transport has contributed significantly to the productivity of the Chinese economy, it has also been faced with the fierce competition and challenge from other modes of transportation, and therefore, freight-pricing issue has received more attention by researchers. In this paper, the rail freight option (RFO) based on option theory is proposed to study the optimal pricing decision of the railway transportation enterprise and contract customers’ optimal purchase decisions. To obtain an effective RFO contract, the railway freight contract transaction process is first analyzed. Then, the theoretical framework for the RFO contract trading is put forward in the railway freight market. Next, a two-stage Stackelberg game theoretic approach is presented based on the principle of utility maximization to achieve the optimal decision of RFO contract. Subsequently, the reverse reasoning method in dynamic programming is used to solve the optimal combination decision of the contract customer. Finally, the optimal pricing decision of RFO is discussed using Kuhn–Tucker conditions and Lagrangian function. The result shows that the railway transportation enterprise should pay more attention to the option strike price w1 in terms of maximizing system utility and achieving Pareto optimal.
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