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Automated driving systems (ADSs) are being developed to avoid human error and improve driving safety. However, limited focus has been given to the fallback behavior of automated vehicles, which act as a fail-safe mechanism to deal with safety issues resulting from sensor failure. Therefore, this study aims to establish a fallback control approach aimed at driving an automated vehicle to a safe parking lane under perceptive sensor malfunction.

Owing to an undetected area resulting from a front sensor malfunction, the proposed ADS first creates virtual vehicles to replace existing vehicles in the undetected area. Afterward, the virtual vehicles are assumed to perform the most hazardous driving behavior toward the host vehicle; an adaptive model predictive control algorithm is then presented to optimize the control task during the fallback procedure, avoiding potential collisions with surrounding vehicles. This fallback approach was tested in typical cases related to car-following and lane changes.

It is confirmed that the host vehicle avoid collision with the surrounding vehicles during the fallback procedure, revealing that the proposed method is effective for the test scenarios.

This study presents a model for the path-planning problem regarding an automated vehicle under perceptive sensor failure, and it proposes an original path-planning approach based on virtual vehicle scheme to improve the safety of an automated vehicle during a fallback procedure. This proposal gives a different view on the fallback safety problem from the normal strategy, in which the mode is switched to manual if a driver is available or the vehicle is instantly stopped.

The purpose of this paper is to present the landscape of the cash-per-publication reward policy in China and reveal its trend since the late 1990s.

This study is based on the analysis of 168 university documents regarding the cash-per-publication reward policy at 100 Chinese universities.

Chinese universities offer cash rewards from USD30 to USD165,000 for papers published in journals indexed by Web of Science, and the average reward amount has been increasing for the past ten years.

The cash-per-publication reward policy in China has never been systematically studied and investigated before except for in some case studies. This is the first paper that reveals the landscape of the cash-per-publication reward policy in China.

Magnetic fluid has excellent function used as lubricants in bearings and mechanical seals, and the purpose of this study is to investigate the sealing performance in a spiral groove mechanical seal lubricated by magnetic fluid.

The sealing characteristic parameters of the lubricating film between the end faces of two sealing rings were calculated based on the Muijderman narrow groove theory for a spiral groove mechanical seal lubricated by magnetic fluid. The film thickness was determined according to the balanced forces on the rotating ring, and the effects of operating conditions, intensity of the magnetic field and diameter of nanoparticles on the sealing characteristics were investigated.

It has been found that the intensity of magnetic field has a great effect on the viscosity of magnetic fluid, film thickness and friction torque while has a little effect on the mass flux of magnetic fluid. The film thickness, mass flux of magnetic fluid and friction torque increase with the increasing volume fraction, rotating speed and diameter of magnetic nanoparticles in magnetic fluid. The mass flux of magnetic fluid decrease with the increasing closing force, and the friction torque decreases with the increase of media pressure.

The change of intensity of magnetic field can affect the viscosity of magnetic fluid and then changes the sealing performance in a mechanical seal lubricated by magnetic fluid. To reduce the mass flux of magnetic fluid and friction torque, the volume fraction, diameter of solid magnetic particles and film thickness should be 5%–7%, 8–10 nm and 2–9.3 µm, respectively.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-02-2023-0032/

This paper aims to study the effect of the establishment of bankruptcy courts on bond issuance market. This paper helps to predict that the introduction of bankruptcy courts in China can mitigate price distortions caused by the implicit government guarantees and promote the development of the high-risk bond market.

This paper exploits the staggered introduction of bankruptcy courts across cities to implement a differences-in-differences strategy on bond issuance data. Using bonds issued in China between 2018 and 2020, the impact of bankruptcy courts on the bond issuance market can be analyzed.

This paper reveals that bond issuance credit spreads increase and is more sensitive to firm size, profitability and downside risk of issuance entity after the introduction of bankruptcy courts. It also reveals a substantive increase in bond issuance quantity and a decrease in issuer credit ratings following the establishment of bankruptcy courts. In addition, the increase of credit spreads is more prominent for publicly traded bonds, those whose issuers located in provinces with lower judicial confidence, bonds issued by SOEs and bonds with stronger government guarantees. Finally, the role of bankruptcy courts is more pronounced in regions with higher marketization.

This paper relates to previous studies that investigate the impact of laws and institutions on external financing. It helps provide new evidence to this literature on how improvements of efficiency and quality in bankruptcy enforcements relate to the marketization of bond issuance. The results provide further evidence on legal institutions and bond financing.

The purpose of this paper is to improve the GM(1, 1) model based on concave sequences.

First, the restored sequence of the GM(1, 1) model is proved to be convex, and the residual characters of the GM(1, 1) model for concave sequences are analyzed. Second, two symmetry transformations are introduced to transform an original concave sequence into a convex sequence, and then the GM(1, 1) model is established based on the convex sequence.

Compared with the traditional modeling method, the new method has high accuracy and is applicable for all concave sequence modeling.

Two cases are used to illustrate the superiority of this modeling method. Case A is to predict China’s per capita natural gas consumption, and case B is to predict the annual output of an oilfield.

The application scope of GM (1, 1) model is greatly extended.

This research aims to provide a conceptual framework with the scope to assist in establishing sustainable supply chain clusters (SCCs) by providing an instrument for organisations to enhance the three sustainability dimensions in a dynamic environment.

This research proposes a conceptual framework to enhance sustainability and organisational performance through three theoretical lenses: the system theory, extended resource-based view and the dynamic capabilities (DCs) theory. This approach is carried out through a comprehensive review of the existing literature on SCCs.

Four main propositions are formulated and demonstrated using the developed framework, which expands the discussion about SCCs and their key characteristics in a dynamic environment. This is particularly relevant as it allows empirical testing of the theories in an SCC context.

It can be noted that more extensive research is needed to further understand the issues faced in establishing sustainable clusters. Drawing on the theoretical lenses to establish the framework helps to enhance the understanding and operational capabilities of sustainable SCCs during and after disruptions, such as the global disruption created by COVID-19.

This research paves the way to help organisations improve their adaptability to the dynamic business environment by emphasizing the importance of clustering and linking it to sustainability through DCs to establish a sustainable cluster.

This research aims to guide organisations' use of SCCs as tools to enhance sustainability in a dynamic environment, given that the relationship amongst supply chain cluster design characteristics (SCCDCs), DCs and sustainability remains unexplored. The combination of the three theoretical lenses in developing the proposed framework will assist in further understanding the applicability of these theories when they are considered together.

The purpose of this paper is to provide strong theoretical and technical support for the dynamic evolution of service system in “Cluster Supply Chain”(CSC), which can deal with two kinds of context changes: the internal service component changes and the external customer requirement changes.

A “feedback-based” evolution mechanism of service system for CSC is proposed in this study. By means of the feedback update of enterprise service’s Quality of Service (QoS) attribute and the adjustment of the assumed QoS evaluation model, the evolution of service system can be achieved to suit the dynamic market demands.

Results of the study suggest: by means of the “feed-back” evolution mechanism of service system, the enterprises in CSC can handle the context changes effectively to maintain the optimized operation status.

The implementation of evolution mechanism in service system can keep the effectiveness of enterprise service composition to face the frequent service component changes and the unpredictable market turbulence.

This paper proposes a method to realize the autonomous evolution of service system in CSC, which can support the flexibility and adaptability of enterprise service composition in the changing environment.

Although the Nash nonlinear grey Bernoulli model (NNGBM(1, 1)) is incomparable with respect to its flexibility over traditional grey models, errors are still inevitable in forecasting. The purpose of this paper is to propose a Fourier residual modified Nash nonlinear grey Bernoulli model (FNNGBM(1, 1)) and use it to forecast the nonlinear time series of the international trade of Chinese high-tech products.

A Fourier series is used to modify the forecasting residual of the NNGBM(1, 1) model, so as to improve its forecasting ability. The parameters optimization of FNNGBM(1, 1) is formulated as a combinatorial optimization problem and is solved collectively using the concept of Nash equilibrium.

The simulation and practical application to fluctuation data both prove that FNNGBM(1, 1) could offer a more precise forecast than NNGBM(1, 1) and the Fourier residual GM(1, 1) (FGM(1, 1)). The import/export data of Chinese high-tech products will maintain rapid growth, with corresponding trade balance enlargement; however, there will be a concomitant decrease in the trade specialization coefficient.

This study is deliberately general in its scope and outlook: its focus is mainly on the overall condition of Chinese high-tech products trade. Future research is recommended to analyze specific industrial trade sectors and extraneous influencing factors.

An effective method is proposed to enhance the accuracy of NNGBM(1, 1) model in forecasting a small sample, nonlinear time series.

Modern cutting fluids often are real aqueous solutions of chemical compounds. That form of cutting fluid is simpler in preparation, as compared to emulsions and microemulsions. The water base is a good cooling medium of high‐ecological value. The purpose of this paper is to discover water‐soluble additives that could improve the lubricity of water.

Three cationic surfactants were chosen to be analyzed. Their tribological properties were verified using two testers: T0‐2 (four‐ball machine) and T‐11 (ball‐on‐disk). The results of the tests performed using friction couples made of steel (T0‐2, T‐11) and steel‐ceramics (T‐11) were satisfactory.

The friction coefficients and wear scar diameters are even a few times smaller, as compared to the ones measured in a water environment.

The paper demonstrates that the crucial role in improvement of the tribological properties is played by the surface activity of the additives (confirmed by the measurements of the surface tension and wetting angle). As the cationic surfactants are bactericidal and anti‐corrosive, they can be classified as multi‐purpose additives modifying water lubricity.

The purpose of this study is to carry out the systematic literature review, bibliometric analysis and content analysis of extant literature of service supply chain (SSC).

Systematic literature review (SLR) technique was used for identifying the research papers. In the first step after reading titles, abstracts and keywords and, full-length articles wherever required, papers not related to SSC were removed. In second steps papers were read more critically and papers not related to SSC were removed. Finally on 502 papers bibliometric and content analysis was further carried out. Content analysis was based on the clusters formed by bibliographic coupling. Further, content analysis of the recent articles revealed the current research trends and research gaps.

This paper identified the six existing research diversifications in SSC as (1) logistics SSC, (2) model, framework and conceptual papers, (3) third-party logistics service providers, (4) articles from various perspective, (5) measurement of quality and performance on services and (6) impact of adoption of technology, cooperation and branding on logistics service providers. Further, six future research directions are also provided.

This research provides a clear view of the progression of publication, research diversification, research themes of six identified clusters, sub-themes of clusters and content analysis of each cluster. Content analysis of recent articles reveals the current research trend and future research directions.

This is a first of its kind of study which presents the diversification of research areas within SSC, bibliometric analysis, content analysis and provides actionable future research direction.