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The purpose of this paper is to investigate the optimal average drag coefficient of the Ahmed body for mixed platoon driving under crosswind and no crosswind conditions using the response surface optimization method. This study has extraordinary implications for the planning of future intelligent transportation.

First, the single vehicle and vehicle platoon models are validated. Second, the configuration with the lowest average drag coefficient under the two conditions is obtained by response surface optimization. At the same time, the aerodynamic characteristics of the mixed platoon driving under different conditions are also analyzed.

The configuration with the lowest average drag coefficient under no crosswind conditions is 0.3 L for longitudinal spacing and 0.8 W for lateral spacing, with an average drag coefficient of 0.1931. The configuration with the lowest average drag coefficient under crosswind conditions is 10° for yaw angle, 0.25 L for longitudinal spacing, and 0.8 W for lateral spacing, with an average drag coefficient of 0.2251. Compared to the single vehicle, the average drag coefficients for the two conditions are reduced by 25.1% and 41.3%, respectively.

This paper investigates the lowest average drag coefficient for mixed platoon driving under no crosswind and crosswind conditions using a response surface optimization method. The computational fluid dynamics (CFD) results of single vehicle and vehicle platoon are compared and verified with the experimental results to ensure the reliability of this study. The research results provide theoretical reference and guidance for the planning of intelligent transportation.

The purpose of this paper is to study the aerodynamic characteristics of Ahmed body in longitudinal and lateral platoons under crosswind by computational fluid dynamics simulation. It helps to improve the aerodynamic characteristics of vehicles by providing theoretical basis and engineering direction for the development and progress of intelligent transportation.

A two-car platoon model is used to compare with the experiment to prove the accuracy of the simulation method. The simplified Ahmed body model and the Reynolds Averaged N-S equation method are used to study the aerodynamic characteristics of vehicles at different distances under cross-winds.

When the longitudinal distance x/L = 0.25, the drag coefficients of the middle and trailing cars at β = 30° are improved by about 272% and 160% compared with β = 10°. The side force coefficients of the middle and trailing cars are increased by 50% and 62%. When the lateral distance y/W = 0.25, the side force coefficients of left and middle cars at β = 30° are reduced by 38% and 37.5% compared with β = 10°. However, the side force coefficient of the right car are increased by about 84.3%.

Most of the researches focus on the overtaking process, and there are few researches on the neat lateral platoon. The innovation of this paper is that in addition to studying the aerodynamic characteristics of longitudinal driving, the aerodynamic characteristics of neat lateral driving are also studied, and crosswind conditions are added. The authors hope to contribute to the development of intelligent transportation.

The purpose of this paper is to document earnings management of Chinese firms.

The paper takes advantage of the introduction of stringent delisting requirements around 2000 that non-cross-listed firms with consecutive earnings losses for more than two years would be delisted from the mainland Chinese exchanges. The paper examines whether listed firms in Chinese market manage earnings to avoid listings. The paper also examines whether mainland Chinese firms cross-listed in Hong Kong exchanges manage earnings the same way. The measure for earnings management is derived from a kernel density estimate for the return on equity distribution, following Bollen and Pool (2009).

The paper finds that the new delisting threats induce rampant earnings management on mainland markets, and cross-listing in Hong Kong has a curbing effect on earnings management. The paper also finds that prices became less value relevant after the implementation of delisting regulations, and investors rationally discounted the reliability of earnings announcements in China. Such market responses were absent for cross-listed firms in Hong Kong.

There is little conclusive evidence about whether cross-listing in a non-US market has a curbing effect on earnings management. The paper contributes to this literature by using this unique exogenous policy change in China and following a difference-in-difference approach in identifying the potential curbing effect. The particular measure adapted from Bollen and Pool (2009) utilizes information of the whole distribution of return on equity, thus extends earlier crude comparison of nearest two bars around zero and partially deals with the potential endogeneity problem.

This paper aims to investigate the reliability, availability, maintenance and safety analysis method for railway network operation.

The reliability of the railway network is proposed based on the accident frequency and the topology of the railway network. Network efficiency and capacity are proposed to evaluate the availability of the railway network. The maintenance of the railway network is analyzed from the perspective of accident recovery time. The safety index of the railway network is proposed to measure the safety of railway stations and sections and the K-means method is proposed to find the safety critical stations and sections. Finally, the effectiveness of the proposed method is illustrated through a real-world case study.

The case study shows that the proposed model can produce a big-picture averaged view of the network-wide safety level and help us identify the safety critical stations and sections by considering both the expected reduction of network efficiency and capacity.

The potential application of the proposed model is to help the safety managers determine the investments in safety management of each section and station and then increase the safety and robustness of railway network operation.

The safety analysis of the railway network should consider the reliability, availability and maintenance of the railway network. In this paper, the reliability of the railway network is proposed based on the accident frequency and the topology of the railway network. Network efficiency and capacity are proposed to evaluate the availability of the railway network. The maintenance of the railway network is analyzed from the perspective of recovery time. Finally, the safety index of the railway network is proposed to analyze the safety critical stations and sections.

Construction planning for microtunneling projects is a complex process due to the high level of uncertainties inherent in underground construction and the interdependent nature of decision variables. Simulation is a suitable decision-making tool to account for uncertainties and to model complex dependencies among decision variables. This paper aims to improve microtunneling construction planning by using simulation.

This study proposes a hybrid simulation approach that combines discrete event simulation (DES) with continuous simulation (CS) for microtunneling construction planning. In this approach, DES is used to model construction processes at the activity level and CS is used to model the continuous flow of soil material in the system.

To demonstrate the capability of the proposed approach in construction planning of microtunneling projects, different construction plan scenarios are compared in a microtunneling case study. The results of the case study show suitability of the hybrid DES-CS approach in simulating microtunneling construction processes and the practicality of the approach for identifying the most efficient construction plan.

This study proposes a new modeling approach for microtunneling construction processes using hybrid simulation and provides decision support at the construction planning stage of projects.

The purpose of this paper is the exploration of students’ preferred social media (SM) tools for receiving information about their academic library. The authors administered a questionnaire at their prospective institutions: the College of Staten Island (CSI), City University of New York, USA and the University of Western Ontario (UWO) in London, Ontario, Canada. The authors examine students’ preferences for various SM tools, and analyzed the types of information students expect from the library’s SM accounts. The authors argue that the library’s SM postings should be curated based on market research that provides a better understanding of the target audience.

The authors explore the SM preferences of students at their prospective institutions. The authors examine the SM channels students visit and the types of SM content they wish to seek out. The authors ran the authors’ study from September 1 through December 31, 2016. The authors used convenience sampling and a printed questionnaire to collect data from students in information literacy instruction sessions (n=633 at CSI, n=602 at UWO).

The authors found that more students (at both institutions) used Facebook and YouTube, as compared with other SM platforms. If they viewed their library’s SM accounts, students from both institutions preferred to read about news and current events, followed by announcements about new library services.

The authors illustrate that conducting market research helps SM managers understand their target audience. Market research is the key to successful SM management. It also helps in the development of a marketing plan and provides insights on students’ preferences regarding SM content.

This study compares students’ SM preferences across two academic institutions from two countries, the USA and Canada. The authors wished to investigate the similarities and differences among these students’ preferences.

Casting is one of the well-known manufacturing processes to make durable parts of goods and machinery. However, the quality of the casting parts depends on the proper choice of process variables related to properties of the materials used in making a mold and the product itself; hence, variables related to product/process designs are taken into consideration. Understanding casting techniques considering significant process variables is critical to achieving better quality castings and helps to improve the productivity of the casting processes. This study aims to understand the computational models developed for achieving better quality castings using various casting techniques.

A systematic literature review is conducted in the field of casting considering the period 2000–2020. The keyword co-occurrence network and word cloud from the bibliometric analysis and text mining of the articles reveal that optimization and simulation models are extensively developed for various casting techniques, including sand casting, investment casting, die casting and squeeze casting, to improve quality aspects of the casting's product. This study further investigates the optimization and simulation models and has identified various process variables involved in each casting technique that are significantly affecting the outcomes of the processes in terms of defects, mechanical properties, yield, dimensional accuracy and emissions.

This study has drawn out the need for developing smart casting environments with data-driven modeling that will enable dynamic fine-tuning of the casting processes and help in achieving desired outcomes in today's competitive markets. This study highlights the possible technology interventions across the metal casting processes, which can further enhance the quality of the metal casting products and productivity of the casting processes, which show the future scope of this field.

This paper investigates the body of literature on the contributions of various researchers in producing high-quality casting parts and performs bibliometric analysis on the articles. However, research articles from high-quality journals are considered for the literature analysis in identifying the critical parameters influencing quality of metal castings.

The systematic literature review reveals the analytical models developed using simulation and optimization techniques and the important quality characteristics of the casting products. Further, the study also explores critical influencing parameters involved in every casting process that significantly affects the quality characteristics of the metal castings.

The rich primary and secondary data sources for studying historical Chinese marketing theory and practice are discussed. This paper aims to briefly address possible challenges (and their solutions) to using these sources.

A bibliographic review is used to analyze historical sources pertaining to Chinese marketing theory and practice.

Marketing scholars can draw from multiple but neglected and underused Chinese sources to glean important historical data reflecting pre-1949 Chinese marketing.

Underused Chinese multilateral historical marketing materials are inalienable to extending historical marketing study. Many studies about marketing theory and practice are amenable to such materials.

By scrutinizing these materials, contemporary marketers can formulate parallel strategies from the repertoire of historical marketing strategies.

This is the first comprehensive survey of an invaluable non-Western source for historical research in marketing.

Aiming at the shortcomings of EEG signals generated by brain's sensorimotor region activated tasks, such as poor performance, low efficiency and weak robustness, this paper proposes an EEG signals classification method based on multi-dimensional fusion features.

First, the improved Morlet wavelet is used to extract the spectrum feature maps from EEG signals. Then, the spatial-frequency features are extracted from the PSD maps by using the three-dimensional convolutional neural networks (3DCNNs) model. Finally, the spatial-frequency features are incorporated to the bidirectional gated recurrent units (Bi-GRUs) models to extract the spatial-frequency-sequential multi-dimensional fusion features for recognition of brain's sensorimotor region activated task.

In the comparative experiments, the data sets of motor imagery (MI)/action observation (AO)/action execution (AE) tasks are selected to test the classification performance and robustness of the proposed algorithm. In addition, the impact of extracted features on the sensorimotor region and the impact on the classification processing are also analyzed by visualization during experiments.

The experimental results show that the proposed algorithm extracts the corresponding brain activation features for different action related tasks, so as to achieve more stable classification performance in dealing with AO/MI/AE tasks, and has the best robustness on EEG signals of different subjects.

The purpose of the study is to identify and analyze critical mediating and moderating market intelligence challenges faced by the SMEs when implementing corporate social responsibility (CSR) based on an applied market-oriented business model (MOBM).

Focusing on developing CSR-integrated market intelligence, this study uses an action research method by analyzing four case studies. Data is collected through interviews, interactive and knowledge-sharing meetings and on-site observations. The study is part of a larger European Union project using the developed MOBM to follow the four companies' CSR implementation and learning process over a 14-month period. The action research includes seven meetings; between these, the researchers introduced the SMEs to different business focus areas, where CSR is a vital part of the MOBM.

This study shows that the SMEs are too technology-focused and have little initial idea of how to integrate CSR advantages for market intelligence into their internationalization. The MOBM model offers insights and knowledge on the strength and weakness of the internal organization to meet challenges in internationalization.

Via case study and action research, this study spotlights the challenges that SMEs face in the CSR implementation process and how they deal with those challenges to develop market intelligence competence internally. Instead of following a traditional research approach, the current study applies a CSR-based method where the SMEs go through a knowledge development process that originated from a theoretically designed MOBM.