Guolong Li, Mangmang Gao, Jingjing Yang, Yunlu Wang and Xueming Cao
This study aims to propose a vertical coupling dynamic analysis method of vehicle–track–substructure based on forced vibration and use this method to analyze the influence on the…
Abstract
Purpose
This study aims to propose a vertical coupling dynamic analysis method of vehicle–track–substructure based on forced vibration and use this method to analyze the influence on the dynamic response of track and vehicle caused by local fastener failure.
Design/methodology/approach
The track and substructure are decomposed into the rail subsystem and substructure subsystem, in which the rail subsystem is composed of two layers of nodes corresponding to the upper rail and the lower fastener. The rail is treated as a continuous beam with elastic discrete point supports, and spring-damping elements are used to simulate the constraints between rail and fastener. Forced displacement and forced velocity are used to deal with the effect of the substructure on the rail system, while the external load is used to deal with the reverse effect. The fastener failure is simulated with the methods that cancel the forced vibration transmission, namely take no account of the substructure–rail interaction at that position.
Findings
The dynamic characteristics of the infrastructure with local diseases can be accurately calculated by using the proposed method. Local fastener failure will slightly affect the vibration of substructure and carbody, but it will significantly intensify the vibration response between wheel and rail. The maximum vertical displacement and the maximum vertical vibration acceleration of rail is 2.94 times and 2.97 times the normal value, respectively, under the train speed of 350 km·h−1. At the same time, the maximum wheel–rail force and wheel load reduction rate increase by 22.0 and 50.2%, respectively, from the normal value.
Originality/value
This method can better reveal the local vibration conditions of the rail and easily simulate the influence of various defects on the dynamic response of the coupling system.
Details
Keywords
Ida Musialkowska, Agata Kliber, Katarzyna Świerczyńska and Paweł Marszałek
This paper aims to find, which of the assets: gold, oil or bitcoin can be considered a safe-haven for investors in a crisis-driven Venezuela. The authors look also at the…
Abstract
Purpose
This paper aims to find, which of the assets: gold, oil or bitcoin can be considered a safe-haven for investors in a crisis-driven Venezuela. The authors look also at the governmental change of approach towards the use and mining of cryptocurrencies being one of the assets and potential applications of bitcoin as (quasi) money.
Design/methodology/approach
The authors collected the daily data (a period from 01 May 2014 to 31 July 2018) on the development of the following magnitudes: Caracas Stock Exchange main index: Índice Bursátil de Capitalisación (IBC) index; gold price in US dollars, the oil price in US dollars and Bitcoin price in bolivar fuerte (VEF) (LocalBitcoins). The authors estimated a threshold VAR model between IBC and each of the possible safe-haven assets, where the trigger variable was the IBC; then the authors modelled the residuals from the TVAR model using MGARCH model with dynamic conditional correlation.
Findings
The results show that that gold is a better safe-haven than oil for Venezuelan investors, while bitcoin can be considered a weak safe haven. Still, bitcoin can perform (to a certain extent) money functions in a crisis-driven country.
Research limitations/implications
Further research after the change of local currency from VEF into bolivar soberano might be looked at on the later stage.
Practical implications
The authors provide evidence on which of analysed asset is the best safe-haven for the investors acting in the time of the crisis. The evidence goes in line with other authors’ findings, thus, the results might bring implications for investors of more universal character. Additionally, the result might be helpful for governments and/or monetary authorities while projecting institutional frameworks and conducting monetary policy.
Social implications
The unprecedented economic crisis in Venezuela was one of the factors that fuelled the mining and use of cryptocurrencies in the daily life of its citizens. Nowadays, the country is a leader in terms of the use of bitcoin and other cryptocurrencies in Latin America. The results show a potential application of bitcoin as a store of value or even means of payments in Venezuelan (or in other countries affected by the crisis).
Originality/value
The paper builds on the original data set collected by the authors and brings evidence from the models the authors constructed to verify, which asset is the best option for investors in hard times of the crisis. The authors add to the existing literature on financial assets, cryptocurrencies and behaviour of investors under different economic conditions.
Details
Keywords
Kuncheng Zhang, Shi-Zheng Tian, Benshuo Yang, Xin-Chang Guo and Yi-Fang Zhang
The island areas, in particular, are characterized by a more fragile ecological carrying capacity and higher value of resources and environment, which requires us to take Xi…
Abstract
Purpose
The island areas, in particular, are characterized by a more fragile ecological carrying capacity and higher value of resources and environment, which requires us to take Xi Jinping's green ecological development view as the theoretical basis and adhere to the high-quality development path of gradual development and ecological environment priority. Taking Shengsi and Daishan counties as examples, on the basis of their high-quality development evaluation and identification of the main influencing factors, this study explores the specific path of Xi Jinping's ecological development view in the high-quality development of typical island counties in China.
Design/methodology/approach
This paper applies the interpretative structural model to construct an evaluation index system for the high-quality development of the island. In determining the factor weights of the index layer, the AHP hierarchical analysis method was combined with the Delphi method to increase the objectivity of the assignment process as much as possible. This study used the technique for order of preference by similarity to ideal solution to calculate island high quality development index. To measure the main obstacle factors, the index factor contribution rate, the index factor deviation, and the index factor obstacle degree were applied in this research.
Findings
As China intensifies its maritime strategy, the sustainability of coastal and island regions is critical, particularly given their fragile ecosystems and high resource value. Our study reveals a declining trend in the high-quality development index for Shengsi, peaking at 0.4262 in 2010 and dropping to 0.3261 in 2012. To reverse this, it's essential to align with President Xi Jinping's green ecological development framework and commit to a high-quality development pathway.
Originality/value
The connotation and extension of Xi Jinping's view of ecological development should be continuously studied in depth and enriched, with green development as the core idea to guide the correct direction of the high-quality development of the island. In this paper, it is suggested that researchers are supposed to focus on these problems, such as the changes of sea water quality, the reduction of urban greening, the continuous negative growth of population in island areas, the decline of forestry added value and air quality protection, so as to ensure the sustainable high-quality development of example islands.
Details
Keywords
Xiaojie Xu and Yun Zhang
Forecasts of commodity prices are vital issues to market participants and policy makers. Those of corn are of no exception, considering its strategic importance. In the present…
Abstract
Purpose
Forecasts of commodity prices are vital issues to market participants and policy makers. Those of corn are of no exception, considering its strategic importance. In the present study, the authors assess the forecast problem for the weekly wholesale price index of yellow corn in China during January 1, 2010–January 10, 2020 period.
Design/methodology/approach
The authors employ the nonlinear auto-regressive neural network as the forecast tool and evaluate forecast performance of different model settings over algorithms, delays, hidden neurons and data splitting ratios in arriving at the final model.
Findings
The final model is relatively simple and leads to accurate and stable results. Particularly, it generates relative root mean square errors of 1.05%, 1.08% and 1.03% for training, validation and testing, respectively.
Originality/value
Through the analysis, the study shows usefulness of the neural network technique for commodity price forecasts. The results might serve as technical forecasts on a standalone basis or be combined with other fundamental forecasts for perspectives of price trends and corresponding policy analysis.
Details
Keywords
Andrea Mantelli, Marinella Levi, Stefano Turri and Raffaella Suriano
The purpose of this study is to demonstrate the potential of three-dimensional printing technology for the remanufacturing of end-of-life (EoL) composites. This technology will…
Abstract
Purpose
The purpose of this study is to demonstrate the potential of three-dimensional printing technology for the remanufacturing of end-of-life (EoL) composites. This technology will enable the rapid fabrication of environmentally sustainable structures with complex shapes and good mechanical properties. These three-dimensional printed objects will have several application fields, such as street furniture and urban renewal, thus promoting a circular economy model.
Design/methodology/approach
For this purpose, a low-cost liquid deposition modeling technology was used to extrude photo-curable and thermally curable composite inks, composed of an acrylate-based resin loaded with different amounts of mechanically recycled glass fiber reinforced composites (GFRCs). Rheological properties of the extruded inks and their printability window and the conversion of cured composites after an ultraviolet light (UV) assisted extrusion were investigated. In addition, tensile properties of composites remanufactured by this UV-assisted technology were studied.
Findings
A printability window was found for the three-dimensional printable GFRCs inks. The formulation of the composite printable inks was optimized to obtain high quality printed objects with a high content of recycled GFRCs. Tensile tests also showed promising mechanical properties for printed GFRCs obtained with this approach.
Originality/value
The novelty of this paper consists in the remanufacturing of GFRCs by the three-dimensional printing technology to promote the implementation of a circular economy. This study shows the feasibility of this approach, using mechanically recycled EoL GFRCs, composed of a thermoset polymer matrix, which cannot be melted as in case of thermoplastic-based composites. Objects with complex shapes were three-dimensional printed and presented here as a proof-of-concept.
Details
Keywords
Shuxin Ding, Tao Zhang, Kai Sheng, Yuanyuan Chen and Zhiming Yuan
The intelligent Central Traffic Control (CTC) system plays a vital role in establishing an intelligent high-speed railway (HSR) system. As the core of HSR transportation command…
Abstract
Purpose
The intelligent Central Traffic Control (CTC) system plays a vital role in establishing an intelligent high-speed railway (HSR) system. As the core of HSR transportation command, the intelligent CTC system is a new HSR dispatching command system that integrates the widely used CTC in China with the practical service requirements of intelligent dispatching. This paper aims to propose key technologies and applications for intelligent dispatching command in HSR in China.
Design/methodology/approach
This paper first briefly introduces the functions and configuration of the intelligent CTC system. Some new servers, terminals and interfaces are introduced, which are plan adjustment server/terminal, interface for automatic train operation (ATO), interface for Dynamic Monitoring System of Train Control Equipment (DMS), interface for Power Supervisory Control and Data Acquisition (PSCADA), interface for Disaster Monitoring, etc.
Findings
The key technologies applied in the intelligent CTC system include automatic adjustment of train operation plans, safety control of train routes and commands, traffic information data platform, integrated simulation of traffic dispatching and ATO function. These technologies have been applied in the Beijing-Zhangjiakou HSR, which commenced operations at the end of 2019. Implementing these key intelligent functions has improved the train dispatching command capacity, ensured the safe operation of intelligent HSR, reduced the labor intensity of dispatching operators and enhanced the intelligence level of China's dispatching system.
Originality/value
This paper provides further challenges and research directions for the intelligent dispatching command of HSR. To achieve the objectives, new measures need to be conducted, including the development of advanced technologies for intelligent dispatching command, coping with new requirements with the development of China's railway signaling system, the integration of traffic dispatching and train control and the application of AI and data-driven modeling and methods.
Details
Keywords
Giovanni De Luca and Monica Rosciano
The tourist industry has to adopt a big data-driven foresight approach to enhance decision-making in a post-COVID international landscape still marked by significant uncertainty…
Abstract
Purpose
The tourist industry has to adopt a big data-driven foresight approach to enhance decision-making in a post-COVID international landscape still marked by significant uncertainty and in which some megatrends have the potential to reshape society in the next decades. This paper, considering the opportunity offered by the application of the quantitative analysis on internet new data sources, proposes a prediction method using Google Trends data based on an estimated transfer function model.
Design/methodology/approach
The paper uses the time-series methods to model and predict Google Trends data. A transfer function model is used to transform the prediction of Google Trends data into predictions of tourist arrivals. It predicts the United States tourism demand in Italy.
Findings
The results highlight the potential expressed by the use of big data-driven foresight approach. Applying a transfer function model on internet search data, timely forecasts of tourism flows are obtained. The two scenarios emerged can be used in tourism stakeholders’ decision-making process. In a future perspective, the methodological path could be applied to other tourism origin markets, to other internet search engine or other socioeconomic and environmental contexts.
Originality/value
The study raises awareness of foresight literacy in the tourism sector. Secondly, it complements the research on tourism demand forecasting by evaluating the performance of quantitative forecasting techniques on new data sources. Thirdly, it is the first paper that makes the United States arrival predictions in Italy. Finally, the findings provide immediate valuable information to tourism stakeholders that could be used to make decisions.
Details
Keywords
Aruna Jha, Madhavi Kapoor, Khushi Kaul and Khushi Srivastava
Importance of corporate social responsibility (CSR) in marketing domain is increasing immensely. The effect of CSR perception on the purchase intention differs on the basis of…
Abstract
Purpose
Importance of corporate social responsibility (CSR) in marketing domain is increasing immensely. The effect of CSR perception on the purchase intention differs on the basis of mediators and contexts. The objective of this study is to examine the consumer behaviour of young consumers. For this, impact of CSR perception on purchase intention, satisfaction and price fairness of Generation Z is studied.
Design/methodology/approach
Preliminary data analysis is run to check normality, skewness and common method bias. PLS-SEM is deployed to examine the relationships amongst the research variables. Sequential mediation through PLS bootstrapping helped in exploring new and exciting research results which are supported with literature.
Findings
The CSR perception of Generation Z does not have a direct effect on their purchase intention. Interestingly, satisfaction and price fairness fully mediate the relationship between CSR perception and purchase intentions separately, i.e. CSR perception of Generation Z influences purchase intention only through satisfaction and price fairness. Furthermore, satisfaction and price fairness are also found to sequentially mediate the relationship between CSR perception and purchase intentions.
Research limitations/implications
The research will aid not only the fast-food industry but the industries that are looking to focus on what Generation Z consumers expect in emerging markets including India. Understanding consumer expectations out of CSR initiatives will help them to incorporate social considerations into their marketing strategies and increase their profitability. Generation Z is regarded as the most challenging consumer demographic to market due to their proclivity for conducting extensive research and comparison shopping before making a purchase decision. As a result, the companies that want to use CSR as a strategy may find it advantageous to investigate how marketing of their CSR initiatives will lead to competitive edge and influence purchase decisions of this generational cohort.
Originality/value
This study adds to the academic literature by developing and evaluating a research model for consumer responses of a very important generation cohort to CSR in an emerging economy setting. CSR activities alone may not be enough to improve purchase intention of Generation Z adults. Sequential mediation for Generation Z adults' relationship between CSR and price fairness flows through satisfaction and finally to purchase intention is interesting because it clearly establishes a link amongst belief, attitude and actions of the target audience under study in a meaningful way within the framework given by cognitive consistency theory.
Details
Keywords
Bingzi Jin and Xiaojie Xu
Agriculture commodity price forecasts have long been important for a variety of market players. The study we conducted aims to address this difficulty by examining the weekly…
Abstract
Purpose
Agriculture commodity price forecasts have long been important for a variety of market players. The study we conducted aims to address this difficulty by examining the weekly wholesale price index of green grams in the Chinese market. The index covers a ten-year period, from January 1, 2010, to January 3, 2020, and has significant economic implications.
Design/methodology/approach
In order to address the nonlinear patterns present in the price time series, we investigate the nonlinear auto-regressive neural network as the forecast model. This modeling technique is able to combine a variety of basic nonlinear functions to approximate more complex nonlinear characteristics. Specifically, we examine prediction performance that corresponds to several configurations across data splitting ratios, hidden neuron and delay counts, and model estimation approaches.
Findings
Our model turns out to be rather simple and yields forecasts with good stability and accuracy. Relative root mean square errors throughout training, validation and testing are specifically 4.34, 4.71 and 3.98%, respectively. The results of benchmark research show that the neural network produces statistically considerably better performance when compared to other machine learning models and classic time-series econometric methods.
Originality/value
Utilizing our findings as independent technical price forecasts would be one use. Alternatively, policy research and fresh insights into price patterns might be achieved by combining them with other (basic) prediction outputs.
Details
Keywords
Utilizing the Marxist theory of unequal exchange to explain the terms of trade between nations, this paper elucidates one possible mechanism that…
Abstract
Purpose
Utilizing the Marxist theory of unequal exchange to explain the terms of trade between nations, this paper elucidates one possible mechanism that gives rise to ecologically unequal exchange between developed and developing economies.
Design/methodology/approach
We propose a two-sector linear production model and demonstrate that a decrease in the organic composition of capital and an increase in the rate of surplus value in a sector will lead to a relative price decrease and value transfer out of that particular sector, as well as increasing the environmental costs of trade. Furthermore, we measure the levels of unequal exchange (value transfer) and ecologically unequal exchange of 40 economies and empirically validate their relationship.
Findings
The findings suggest that an important cause of the ecologically unequal exchange is the value transfer between economies caused by the international division of labor and real wage disparities. The inequality in international trade is a significant factor contributing to the gap in the ecological environment level between developed and developing economies.
Originality/value
By introducing the theory of unequal exchange or value transfer into the analysis of ecological unequal exchange, we provide a mathematical framework for analyzing ecological unequal exchange and a method for calculating the scale of ecological unequal exchange and value transfer, thereby enhancing the theoretical depth and practical significance of the ecological unequal exchange theory.