MAPPING CURRENT STATE IN THE FIELD OF PREDICTION METHODS OF BUSINESS AND ECONOMIC CHARACTERISTICS ACROSS INDUSTRIES

The results of the prediction of business and economic characteristics provide valuable information to stakeholders (business owners and managers, investors, and shareholders). The aim of the paper is to provide a comprehensive overview on methods applied in practice for predicting significant business and economic variables. The research is structured into selected key industries for most of the world's economies. An extensive literary review of the scientific papers published over the last decade revealed that the most used prediction methods include ANN, GARCH combined with ARIMA. These are the methods strong enough to capture the specifics of the industries for the economic and business prediction purposes. The LS-SVM and ARIMA methods are used separately to a lesser extent. The other methods were used mainly for the purpose of vali-dation of their predicting applicability.

Experimental Determination of the Manson-Coffin Curves for an Original Unconventional Vehicle Frame

This article is divided into two parts-in the first part, authors inform about their testing device that enables the acquisition of results from uniaxial and multiaxial fatigue tests (the bending-torsion combination). We present the approaches used during designing and building the testing device. The direct implementation of the research in the second part will concentrate on implementing the acquired results for the frame design of a vehicle worked out by the authors. The three-wheeled vehicle has the front steered wheel suspended in an unconventional way. This original design can cause an increased load on the vehicle's frame. This can be apparent mainly during driving through curves. Therefore, the fatigue curves of the tested material (EN AW 6063) will be implemented from the point of view of its usability in operation. A vehicle frame is most often loaded by bending and torsion. The authors assess the influence of welding on the fatigue life of this unique unconventional vehicle by determining the fatigue curves of the material for its production. The stresses achieved on the test specimens fully correspond to the load of the frame (in welds) during its operation.

Best–Worst Method for Modelling Mobility Choice after COVID-19: Evidence from Italy

All countries have suffered from the COVID-19 crisis; the pandemic has adversely impacted all sectors. In this study, we examine the transport sector with a specific focus on the problem of commuting mode choice and propose a new decision-making approach for the alternative modes after synthesizing expert opinions. As a methodology, a customized model of the recently developed best–worst method (BWM) is used to evaluate mobility choice alternatives. The survey reflects citizens’ opinions toward mobility choices in two Italian cities, Palermo and Catania, before and during the pandemic. BWM is a useful tool for examining mobility choice in big cities. The adopted model is easy to apply and capable of providing effective solutions for sustainable mode choice. The urban context is analyzed considering the importance of transport choices, evaluating the variation of resilience to the changing opinions of users.

Machine Learning Approach Using MLP and SVM Algorithms for the Fault Prediction of a Centrifugal Pump in the Oil and Gas Industry

The demand for cost-effective, reliable and safe machinery operation requires accurate fault detection and classification to achieve an efficient maintenance strategy and increase performance. Furthermore, in strategic sectors such as the oil and gas industry, fault prediction plays a key role to extend component lifetime and reduce unplanned equipment thus preventing costly breakdowns and plant shutdowns. This paper presents the preliminary development of a simple and easy to implement machine learning (ML) model for early fault prediction of a centrifugal pump in the oil and gas industry. The data analysis is based on real-life historical data from process and equipment sensors mounted on the selected machinery. The raw sensor data, mainly from temperature, pressure and vibrations probes, are denoised, pre-processed and successively coded to train the model. To validate the learning capabilities of the ML model, two different algorithms—the Support Vector Machine (SVM) and the Multilayer Perceptron (MLP)—are implemented in KNIME platform. Based on these algorithms, potential faults are successfully recognized and classified ensuring good prediction accuracy. Indeed, results from this preliminary work show that the model allows us to properly detect the trends of system deviations from normal operation behavior and generate fault prediction alerts as a maintenance decision support system for operatives, aiming at avoiding possible incoming failures.

Effects of the COVID-19 Lockdown on Urban Mobility: Empirical Evidence from the City of Santander (Spain)

This article analyses the impact that the confinement measures or quarantine imposed in Spain on 15 March 2020 had on urban mobility in the northern city of Santander. Data have been collected from traffic counters, public transport ITS, and recordings from traffic control cameras and environmental sensors to make comparisons between journey flows and times before and during the confinement. This data has been used to re-estimate Origin-Destination trip matrices to obtain an initial diagnostic of how daily mobility has been reduced and how the modal distribution and journey purposes have changed. The impact on externalities such as NO2 emissions and traffic accidents have also been quantified. The analysis revealed an overall mobility fall of 76%, being less important in the case of the private car. Public transport users dropped by up to 93%, NO2 emissions were reduced by up to 60%, and traffic accidents were reduced by up to 67% in relative terms.

Evaluating Cyclists’ Route Preferences with Respect to Infrastructure

Providing a sufficiently appropriate route environment is crucial to ensuring fair and safe biking, thus encouraging cycling as a sustainable mode of transport. At the same time, better understanding of cyclists’ preferences regarding the features of their routes and their infrastructure requirements is fundamental to evaluating improvement of the current infrastructure or the development of new infrastructure. The present study has two objectives. The first is to investigate cyclists’ route preferences by means of a choice experiment based on a stated preference survey. Subsequently, the second objective is to compare cyclist preferences in two countries with different cycling characteristics (both in infrastructure as well as cyclists’ behavior). For this purpose, a graphical online stated preferences survey was conducted in Greece and Germany. Within the framework of statistical analyses, multinomial mixed logit discrete choice models were developed that allow us to quantify the trade-offs of interest, while distinguishing between the preferences of different user groups. In addition, user requirements in Greece, as a country with a low cycling share and very little dedicated bike infrastructure, were compared to the requirements in Germany, where cycling is popular and the infrastructure is well developed. The results over the whole sample indicate that subgroups value infrastructure differently according to their specific needs. When looking at country specifics, users from Greece are significantly more willing to accept longer travel times in return for higher-quality facilities. The utility of low speed limits in mixed traffic is also different. In Germany, low speed limits offset the disturbance caused by motorized traffic, but in Greece they do not. Consequently, the results help to asses which types of infrastructure are most sustainable from a user perspective and help to set priorities when the aim is to adapt the road infrastructure efficiently in a stable strategy.

A Dynamic Adjustment Model of Cruising Taxicab Fleet Size Combined the Operating and Flied Survey Data

Due to the lack of adjustment index systems for taxi fleet sizes in China, this paper used the taxi operating datasets from Ningbo City and established a regression tree model to consider the endogenous indicators that affect taxi fleet sizes. Then, a dynamic adjustment mechanism of taxi fleet sizes was proposed by combining the exogenous and endogenous indicators. The importance of the exogenous and endogenous indicators was sorted using the Delphi method. The threshold value of each indicator was also given. The results indicated that (1) in the three-layer structure of the regression tree model, the mileage utilization had the strongest effect on the fleet size of taxis, and the F statistic was 63.73; followed by the average daily revenue of a single taxi, the average waiting time to catch a single taxi, the average operating time of a single taxi, and the revenue per 100 km. The overall accuracy of the model was found to be valid. (2) When the mileage utilization was less than 0.6179 and the average daily revenue of a single taxi was less than 798.38 Yuan, the fleet size of cruising taxis was surplus and should be reduced by 362 vehicles. (3) When the mileage utilization was more than 0.6774 and the average waiting time to catch a single taxi was more than 259.09 s, the fleet size of cruising taxis was insufficient, and we suggest an increase of 463 taxis.

Green Supply Chain Decisions Considering Consumers’ Low-Carbon Awareness under Different Government Subsidies

This study examined how to arrange the generation and pricing of supply chain members in the case of consumer green preference with different government subsidies. The green supply chain comprises a manufacturer and a retailer; the government subsidizes manufacturers who produce green products and consumers who buy green products. The study built a green supply chain pricing decision model with different forms of subsidy under various power structures. By backward induction and sensitivity analysis, this study analyzed optimal strategies of green supply chain under various modes, and we discuss how the government subsidy coefficient affects the optimal decision of a green supply chain. The results show that, firstly, whether the government subsidizes the manufacturers or the consumers, the wholesale price offered by the manufacturer is directly proportional to the subsidy coefficient under the two power structures. Secondly, when the government subsidizes the manufacturer, the carbon-emission level and the retail price are inversely proportional to the subsidy coefficient under the manufacturer leader; the carbon-emission level and the retail price are all directly proportional to the subsidy coefficient under the retailer leader. Finally, when the government subsidizes the consumers, the carbon-emission level and the retail price are directly proportional to the subsidy coefficient under the two power structures.

Design for Six Sigma (DFSS) Applied to a New E-Segment Sedan

“Innovation activities” means all the scientific, technological, organizational, financial and commercial steps aimed at implementing innovation. Some innovation activities are themselves innovative, others are not new, but they are necessary for the implementation of innovation, such as Research and Development not linked to a specific innovation. Innovation has a close reference to the economic market, that is to say with the users of the innovated product: if these are not sufficiently developed they are not able to understand it and appreciate it. Innovation, making the process better, generates greater competitiveness: it is the dream of something better that translates into general well-being. This work presents an innovative hybrid car’s design, belonging to the E-segment. The choice of this segment is already innovative in its nature, as despite being currently in strong development, hybrid and electric engines are still little used for large sedans. The method we present in this paper for the car design is also innovative and is called Design for Six Sigma. It is a method used to develop new products, through the determination of customer and market needs and the transformation of these requests into the product generated.

Exploring Public–Private Partnership Scheme in Operation and Maintenance Stage of Railway Project

Public–private partnership (PPP) has been extensively used in many sectors worldwide to provide alternative funding for public infrastructure. However, limited evidence found that this scheme was successfully adopted in railway transport particularly in the later stage of the project life cycle. Private participation during operation and maintenance stages are worthy of comprehensive research to cope with recovery of public investment and institutionalization problems. This research aims to analyze the potential of unbundling scenarios based on railway components by taking into account the Light Rail Transit (LRT) project in developing countries as the case study. A life cycle cost evaluation and sensitivity analysis were used to formulate a practical and regulatory framework for the macro-level of decision-making modeling. The findings indicate a possible scenario by considering the passenger demand, ticket price, and government support to generate the best option based on net present value (NPV) and internal rate of return (IRR). The proposed alternative recommends an attractive investment return for private interest, encourages lower support for government subsidy, and offers a reasonable tariff for the users. The study also suggests future implications from the adoption of research findings which may affect policy formulation and railway industry as a whole.

Evaluating the Performance of Public Transit System: A Case Study of Eleven Cities in China

This paper presents a super efficiency network Data Envelopment Analysis (SE-NDEA) model for eleven cities in China. The model focuses on measuring the performance of public transit system by integrating multiple stakeholders involved in public transit system with the exogenous environment in where they operated. Thus, local authority, bus operators, passengers, uncontrollable environmental factors, and the externality of public transit are all taken into account in the measurement framework. They are interrelated inputs and outputs. The measurement framework can simultaneously capture each public transit system’s production efficiency, service effectiveness, and operational effectiveness. Meanwhile, undesirable outputs, uncontrollable factors, and boundary-valued variables are considered. The paper evaluates the performance of public transit system of 11 Chinese cities from 2009 to 2016. The results reveal that the exogenous environment has a marked impact on the performance measurement of public transit system. Super cities tend to perform better than mega cities, and mega cities tend to perform better than large cities. Furthermore, service effectiveness has a significantly positive correlation with production efficiency, and transit rail tends to perform better than the conventional bus. These findings have an important implication for China’s bus priority implement and more general managerial insights for public transit development.

Analysis of Operations upon Entry into Intermodal Freight Terminals

The design of intermodal freight terminals requires extensive research and a thorough analysis of the technical, financial and organizational aspects. In the paper, the operation of the reposition of large cargo containers (one of the types of intermodal transport units, ITUs) on the dedicated places is subjected to a discussion. The analysis is carried out with the use of a vehicle equipped with a telescopic arm, such as a reach stacker. The considered storage facility is reduced to a block characterized by spatial accumulation given in the paper. The description of the procedure for the execution of the handling operation from the arrival of a tractor-trailer with a container into a terminal, followed by the ITUs being set aside in a dedicated place and, in the end, the departure of the truck without load, is given in the paper. The activities are described in detail in order to present a descriptive model of particular operations upon entry to the intermodal freight terminal. Moreover, the paper contains relevant figures illustrating the various steps of realization and the analysis of duration of activities supported by actual realizations. The durations of the individual activities described in the paper are experimental, and the results have been validated on real-world intermodal freight terminals. Therefore, the authors believe that the obtained values may be used in analytical, simulation and numerical models of intermodal freight terminals.

A Sustainable Transport Competitiveness Analysis of the China Railway Express in the Context of the Belt and Road Initiative

The implementation of China’s Belt and Road Initiative macro strategy has promoted exchanges and cooperation between China and Europe and countries along the route. The operation of the China Railway Express provides a new transportation platform for China–Europe trade. The sustainable development of the China Railway Express has a great significance in terms of promoting the growth of China–Europe trade and meeting the demand for freight in Asia and Europe. Its time-saving advantage over shipping and its economic advantage over air transport cannot be ignored. This paper is based on the discrete selection model of stochastic utility theory. The paper constructs a multi-logit model based on generalized cost functions, including economics, timeliness, reliability, convenience, safety, and environmental protection. To calculate the market share of the China Railway Express and China–Europe Shipping, the paper conducts a quantitative analysis of the market competitiveness of the China Railway Express. Then, the sensitivity analysis and elastic analysis are carried out on the China Railway Express freight rate, the Chinese road freight rate, the China Railway Express service fee, the China Railway Express travelling speed, the China Railway Express sending operation time at the departure station, the China Railway Express transportation time error, the China Railway Express transportation frequency, and the China Railway Express carbon emissions per unit. Finally, based on the analysis results, suggestions for promoting the sustainable development of the China Railway Express are given.