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In this paper, the authors aim to introduce international dynamic marketing capabilities (IDMCs) theoretically derived from marketing capabilities (MCs), dynamic marketing capabilities (DMCs) and international marketing capabilities (IMCs) and provide a novel conceptualization of the concept by applying a holistic view of the international enterprise.

This is a literature review that maps the current research on MCs, DMCs and IMCs and serves as a basis for the theoretical conceptualization of a novel IDMCs concept as well as for the identification of research gaps and the development of future research directions on this phenomenon.

Existing typologies of MCs, DMCs and IMCs are classified into four categories: strategic, operational, analytical and value creation capabilities. A new typology of IDMCs is proposed, consisting of digital MC and dynamic internationalization capability as strategic capabilities, agile IMC, IM excellence and absorptive capability in IM as operational capabilities, IM resilience capability, IM knowledge management capability, AI-enabled IDMC and Industry 4.0-enabled IDMC as analytical capabilities, and ambidextrous IM innovation capability as value creation capability. Finally, the authors identify research gaps and develop research questions that open future research avenues for the coming years.

This paper offers a novel view of MCs, DMCs and IMCs and argues that, in contrast to the majority of previous research, a comprehensive understanding of these is only possible if all levels are considered simultaneously: the strategic, the operational, the analytical and the value creation level. A new conceptualization and typology of IDMCs follows this logic.

It is significant for station passenger flow organization, platform equipment layout and train running optimization to master platform passenger distribution characteristics of urban rail transit stations. The purpose of this paper is to master the characteristics of platform passenger flow distribution in urban rail transit stations and optimize the station passenger flow organization, platform equipment layout and train operation adjustment.

The model considers two types of passengers, with and without luggage, as well as their door selection and microscopic movement behavior. In addition, it improves the traditional social force model by incorporating passenger state transitions under same-platform-transfer scenarios, considering the influence of static obstacles and dynamic queues on passenger movement direction.

Based on this model, a dynamic simulation of platform passenger flow distribution was conducted using Beijingxi Railway Station as an example under same-platform-transfer scenarios, verifying the model’s effectiveness.

Complex scenarios, such as carrying luggage and same-platform-transfers, bring difficulties to the analysis of passenger distribution on platforms. Therefore, this paper proposes a simulation model for the dynamic distribution of subway platform passengers, taking into account the scenarios of carrying luggage and same-platform-transfers.

Efficient traffic incident management is needed to alleviate the negative impact of traffic incidents. Accurate and reliable estimation of traffic incident duration is of great importance for traffic incident management. Previous studies have proposed models for traffic incident duration prediction; however, most of these studies focus on the total duration and could not update prediction results in real-time. From a traveler’s perspective, the relevant factor is the residual duration of the impact of the traffic incident. Besides, few (if any) studies have used dynamic traffic flow parameters in the prediction models. This paper aims to propose a framework to fill these gaps.

This paper proposes a framework based on the multi-layer perception (MLP) and long short-term memory (LSTM) model. The proposed methodology integrates traffic incident-related factors and real-time traffic flow parameters to predict the residual traffic incident duration. To validate the effectiveness of the framework, traffic incident data and traffic flow data from Shanghai Zhonghuan Expressway are used for modeling training and testing.

Results show that the model with 30-min time window and taking both traffic volume and speed as inputs performed best. The area under the curve values exceed 0.85 and the prediction accuracies exceed 0.75. These indicators demonstrated that the model is appropriate for this study context. The model provides new insights into traffic incident duration prediction.

The incident samples applied by this study might not be enough and the variables are not abundant. The number of injuries and casualties, more detailed description of the incident location and other variables are expected to be used to characterize the traffic incident comprehensively. The framework needs to be further validated through a sufficiently large number of variables and locations.

The framework can help reduce the impacts of incidents on the safety of efficiency of road traffic once implemented in intelligent transport system and traffic management systems in future practical applications.

This study uses two artificial neural network methods, MLP and LSTM, to establish a framework aiming at providing accurate and time-efficient information on traffic incident duration in the future for transportation operators and travelers. This study will contribute to the deployment of emergency management and urban traffic navigation planning.

Salt rock from salt lakes can serve as a cost-effective material for subgrade filling, as demonstrated in projects like the Qarhan Salt Lake section of the Qinghai-Tibet Railway and the Qarhan Salt Lake section of the G215 Highway. This state-of-the-art paper aims to summarize the engineering properties of salt rock filling and present the advances of its utilization.

This paper collects and analyzes laboratory and field data of salt rock filling from previous studies to present a comprehensive analysis of the engineering properties and utilization of salt rock fillings.

Salt rock primarily contains minerals such as halite and glauberite, which contribute to its unique phase-changing behavior under varying environmental conditions, impacting its mechanical properties. Salt rock filling shrinks when in contact with vapor or unsaturated brine and expands under cooling or evaporation. Its use is particularly recommended for arid regions, with specific restrictions depending on the structure type. This paper discusses suggested countermeasures to mitigate these issues, as well as key quality acceptance indices for salt rock filling compaction. Moisture content after air-drying is recommended as a crucial parameter for construction quality control.

This review aims to support future research and engineering practices in salt rock subgrade applications.