Role of digitalization of logistics outsourcing in sustainable development of automotive industry in China

Relevance. Digital technologies can bring regional logistics outsourcing in the automotive industry to a new level of performance. However, the digitalization of logistics outsourcing and its role in improving the sustainability of the automotive industry are poorly understood.Research objective. To develop the conceptual framework of the digital ecosystem of regional logistics outsourcing in the automotive industry. The object of the study is the automotive industry in China.Data and methods. Prospects for the digitalization of regional logistics outsourcing of the automotive industry and its impact on the sustainability of the industry are considered in terms of the economics of transaction costs and a resource-based approach. The data sources involved the national policy documents reflecting the strategic directions of digital development of China, statistical data provided by the National Bureau of Statistics of China, as well as research papers presented in the Scopus database.Results. The authors analyzed the trends of digital transformations in the geographic clusters of production of the automotive industry in China. The digitalization of regional logistics outsourcing was determined to influence the sustainability of the automotive industry development in the context of its economic, social, environmental and technological components. The logistics ecosystem model developed by Capgemini was supplemented by the conceptual framework of the digital logistics outsourcing ecosystem for the Chinese automotive industry. The key components of this framework were determined.Conclusions. It can be concluded that digitalization of regional logistics outsourcing will contribute to increasing the sustainability of the automotive industry. However, this requires the formation of a digital landscape of logistics outsourcing, which involves changes in the entire supply chain management system. The results of the study can be used to improve the efficiency of supply chain management in the automotive industry

Optimal Design of Demand-Responsive Feeder Transit Services

The general public considers Fixed-Route Transit (FRT) to be inconvenient while Demand-Responsive Transit (DRT) provides much of the desired flexibility with a door-to-door type of service. However, FRT is typically more cost efficient than DRT to deploy. Therefore, there is an increased interest in flexible transit services including all types of hybrid services that combine FRT and pure DRT. The demand-responsive feeder transit, also known as Demand-Responsive Connector (DRC), is a flexible transit service because it operates in a demand-responsive fashion within a service area and moves customers to/from a transfer point that connects to a FRT network. In this research we develop analytical models, validated by simulation, to design the DRC system. Feeder transit services are generally operated with a DRC policy which might be converted to a traditional FRT policy for higher demand. By using continuous approximations, we provide an analytical modeling framework to help planners and operators in their choice of the two policies. We compare utility functions of the two policies to derive rigorous analytical and approximate closed-form expressions of critical demand densities. They represent the switching conditions, that are functions of the parameters of each considered scenario, such as the geometry of the service area, the vehicle speed and also the weights assigned to each term contributing to the utility function: walking time, waiting time and riding time. We address the problem faced by planners in determining the optimal number of zones for dividing a service area. We develop analytical models representing the total cost functions balancing customer service quality and vehicle operating cost. We obtain close-form expressions for the FRT and approximation formulas for the DRC to determine the optimal number of zones. Finally we develop a real-case application with collected customer demand data and road network data of El Cenizo, Texas. With our analytical formulas, we obtain the optimal number of zones, and the times for switching FRT and DRC policies during a day. Simulation results considering the road network of El Cenizo demonstrate that our analytical formulas provide good estimates for practical use

Safety Assessment of Freeway Active Traffic Management by Exploring the Relationship Between Safety and Congestion

This study has shown how Oregon crash incident data and PSU Portal traffic data can be combined to determine what factors lead to increased crash risk. Data related to Oregon highway 217 was used to conduct the analysis. The first analysis used Portal traffic data to determine Level of Service (LOS) and then determine the relationship between that and crash rate (Fatal and Injury) which was derived from ODOT\u2019s crash database. Similar to studies conducted in other states, there was a clear relationship between LOS and crash rate, with worse LOS associated with increased crash rate. The second part of the study used Portal data again, but this time the mean and variation of the variables speed, occupancy and volume were calculated 5-10 and 10-15 minutes before a crash incident on Oregon 217 on both the upstream and downstream directions. The crash incidents this time were derived from the Traffic Management Operations Center (TMOC) incident data which gave incident times to the nearest minute as opposed to the nearest hour in the LOS study. Given the number of correlated predictors in the data, logistic regression modeling may have led to regression estimates with large variances. Instead, logistic lasso regression was used to select a subset of significant predictor variables to predict the probability of a crash occurring given the traffic conditions at the time. Increasing upstream speed variation and occupancy, and downstream occupancy variation, volume and volume variation were associated with increased crash risk. Slower or decreasing downstream speed was associated with an increased crash risk

Platinum-based metallomesogens bearing a Pt(4,6-dfppy)(acac) skeleton : Synthesis, photophysical properties and polarised phosphorescence application

Polarised phosphorescence has a bright future in backlighting for conventional liquid crystal displays due to its theoretical 100% internal quantum efficiency and low cost. However, there are scarce reports on polarised phosphorescence from metallomesogens. In this contribution, a platinum-based metallomesogen containing a mesogenic biphenyl (Pt1) was prepared and characterised. To further explore the effect of the substituent on mesophase and emission properties, a related complex Pt2 containing a tetraphenylethene (TPE) moiety was also synthesised. Both complexes melt at elevated temperatures but thereafter do not appear to crystallise on cooling. Complex Pt1 shows an enantiotropic nematic phase from which a broad emission can be seen when spread as a film; in solution, an intense, sky-blue emission is observed. For Pt2, which shows a monotropic SmA phase, the emission in the condensed phase is suppressed and there is only weak emission in solution. Polarisation-dependent photoluminescence with a polarised ratio of 5.4 was obtained for the aligned film of a Pt1:polyimide mixture. Using Pt1 as an emissive layer, non-doped, polarised organic light-emitting diodes presented a broad emission spectrum in the range of 450-900 nm with a polarised ratio of 1.33 and the highest external quantum efficiency of 1.1%. This research has an important significance for achieving broad-based polarised phosphorescence from platinum complex-based metallomesogens

Optimal Zone Design for Feeder Transit Services

Feeder transit services generally operate within residential service areas and move customers to and from a transfer point that connects to a major fixed-route transit network. Feeders can operate in a traditional fixed-route or in an emerging demand-responsive fashion. In designing such systems, planners may divide the entire service area into zones independently served by a single feeder line to provide better customer service, lower operating cost, and make management of the operations easier. An analytical model is developed to help decision makers determine the number of zones in a residential service area while balancing customer service quality and vehicle operating costs. For fixed-route and demand-responsive feeder transit, closed-form expressions and numerical procedures are used to derive the optimal number of zones as a function of the main parameters. Analytical expressions are validated by simulation runs

Feeder transit services: Choosing between fixed and demand responsive policy

The Demand Responsive Connector (DRC) connects a residential area to a major transit network through a transfer point and is one of the most often adopted types of flexible transit services. In this paper, analytical and simulation models are developed to assist planners in the decision making process when having to choose between a demand responsive and a fixed-route operating policy and whether and when to switch from one to the other during the day. The best policy is chosen to maximize the service quality, defined as a weighed sum of customer walking time, waiting time and ride time. Based on the results of one-vehicle operations for various scenarios, we have generated critical customer demands, which represent switching points between the competing service policies. Our findings show that the critical demands are in the range from 10 to 50 customers/mile2/h and that a demand responsive policy is more preferred during afternoon peak hours

2-Vehicle zone optimal design for feeder transit services

Feeder transit services perform the crucial first/last mile access to transit by connecting people within a residential area to a major transit network. In this paper, we address the optimal zone design problem faced by planners for feeder transit services with high demands and long length of service area, where a two-vehicle operation is assumed to be adopted in each zone. By balancing customer service quality and operating cost, we develop an analytical model of the system by assuming continuous approximations. Closed-form expressions and numerical procedures are employed to derive the optimal number of zones to aid decision makers in determining the best design as a function of the main parameters. Analytical expressions and results are then validated by simulation analysis

A methodology to derive the critical demand density for designing and operating feeder transit services

Feeder lines are one of the most often used types of flexible transit services connecting a service area to a major transit network through a transfer point. They often switch operations between a demand responsive and a fixed-route policy. In designing and running such systems, the identification of the condition justifying the operating switch is often hard to properly evaluate. In this paper, the authors propose an analytical model and solution of the problem to assist decision makers and operators in their choice. By employing continuous approximations, the authors derive handy but powerful closed-form expressions to estimate the critical demand densities, representing the switching point between the competing operating policies. Based on the results of one-vehicle and two-vehicle operations for various scenarios, in comparison to values generated from simulation, the authors verify the validity of their analytical modeling approach

A methodology to derive the critical demand density for designing and operating feeder transit services

Feeder lines are one of the most often used types of flexible transit services connecting a service area to a major transit network through a transfer point. They often switch operations between a demand responsive and a fixed-route policy. In designing and running such systems, the identification of the condition justifying the operating switch is often hard to properly evaluate. In this paper, we propose an analytical model and solution of the problem to assist decision makers and operators in their choice. By employing continuous approximations, we derive handy but powerful closed-form expressions to estimate the critical demand densities, representing the switching point between the competing operating policies. Based on the results of one-vehicle and two-vehicle operations for various scenarios, in comparison to values generated from simulation, we verify the validity of our analytical modeling approach.Feeder transit Flexible transit Demand responsive Continuous approximation Critical demand

A blockchain-based certifiable anonymous E-taxing protocol.

The security of the tax system is directly related to the development of a country. The conventional process of tax payment laborious steps, so this process becomes a cause of irregularities among taxpayers and tax authorities, increasing the rate of corruption in tax collection. Blockchain, as a distributed ledger technology, its unique advantages and promising applications in taxation offer an effective solution to the problems of electronic taxation. However, the transparency of blockchain exists the risk of privacy disclosure, the high degree of anonymity brings the problem of lack of user supervision. Therefore, for balancing the contradiction of taxpayer privacy and supervision, we propose a blockchain-based self-certified and anonymous e-taxing scheme, which uses blockchain as the underlying support, and utilizes cryptography technology such as self-certified public key, Diffie-Hellman, to reduce the taxpayer's reliance on the certificate authority, and protects the taxpayer's anonymity while realizing the tracking of the real identity of malicious taxpayers. The security analysis proves that the scheme has the properties such as anonymity, conditional privacy and unforgeability, etc. Finally, performance analysis shows that compared with similar schemes, the scheme significantly improves the registration efficiency, proving its practicability and implementability