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Background: How many higher education researchers are there in the world? How many academic articles are published by researchers each year? This paper aims to answer these two questions by tracking the number of higher education teachers and the number of publications over the past four decades.

Methods: We collected data on the number of higher education institutions and researchers from the United Nations, the World Bank, and the US, China, and UK governments (three countries with the largest number of academic publications in recent years). We used Scopus to obtain the number of publications per year. The growth of higher education researchers and academic publications were characterized using 4-parameter logistic models.

Results: The number of higher education teachers-cum-researchers increased from 4 million in 1980 to 13.1 million in 2018 worldwide. Concurrently, the number of academic publications increased from 0.65 million in 1980 to 3.16 million in 2018 based on data from Scopus. At the country level, the number of academic publications from the USA increased from 0.15 million in 1980 to 0.70 million in 2018, while that from China increased by almost 1,000 times from 629 in 1980 to 0.60 million in 2018.

Conclusions: The number of higher education researchers would reach 13.6 million and they would publish 3.21 million academic articles in 2020, imposing enormous pressure to publishers, peer-reviewers, and people who want to understand emerging scientific development. Additionally, not all academic publications are easily assessable because most articles are behind pay-walls. In addition, unethical research practices including falsification, fabrication, plagiarism, slicing publication, publication in a predatory journal or conference, etc. may hinder scientific and human development.

Although scholars have been studying human resource management (HRM) and open innovation (OI), yet there is less attention to this relationship in the context of small-and medium-sized enterprises (SMEs). This paper aims to bring some insights about the human side of inbound open innovation (INOI) in SMEs. The goal is to better understand the role of organizational trust (OT) and developmental culture (DC) in the interactions between commitment-based HRM (C-HRM) and INOI.

The present study employs partial least squares-structural equation modeling to investigate the interrelationships among constructs, utilizing data gathered from a sample of 206 SMEs.

The study's empirical results indicate that the presence of OT serves as a complementary factor in mediating the relation between C-HRM and INOI. Furthermore, the analysis shows that there exists a moderating influence of DC in the relationship between C-HRM and INOI.

The role of HRM practices is important in developing OT and consequently foster INOI in SMEs. To achieve INOI, SMEs need a DC that induces C-HRM toward an OI approach.

This study adds to the understanding of the interactions between C-HRM practices and INOI in SMEs. The comprehension of the mediating function of OT and the moderating effect of DC serve to enhance the scholarly understanding of the human dimension of OI research.

This research establishes an evaluation index system and calculation method for the China's maritime power construction index (CMPCI). It has conducted practical tests on the progress of China's maritime power construction since the 12th–13th Five-Year Plans. This paper conducts a phased study on the construction of China's maritime power based on the CMPCI evaluation results; it expands the relevant achievements in the research field of quantitative research in China's maritime power construction. The verification results are consistent with the actual situation.

Fully reflect the guiding role of national marine policies in the new development stage, guide the transformation of China's marine management model. The CMPCI is a quantitative evaluation of the overall development level of China's maritime power construction over a certain period of time. The CMPCI in this article aims to comprehensively reflect the changes in the construction of China's maritime power, strives to cover various fields it encompasses. This study focuses on objective statistical data analysis, supplemented by multisource data, to objectively and fairly measure the level of CMPCI.

It fully reflects the highlights of marine science and technology, social democracy and strategic emerging industries. This research dynamically quantifies the trajectory of China's maritime power construction, synthetic reflecting the country's macroeconomic policy guiding function. Guiding the transformation of the marine resources utilization, marine economy development, marine scientific research and marine rights and interests maintenance and effectively serving the decision-making needs of the government.

The smoothness of the high-speed railway (HSR) on the bridge may exceed the allowable standard when an earthquake causes vibrations for HSR bridges, which may threaten the safety of running trains. Indeed, few studies have evaluated the exceeding probability of rail displacement exceeding the allowable standard. The purposes of this article are to provide a method for investigating the exceeding probability of the rail displacement of HSRs under seismic excitation and to calculate the exceeding probability.

In order to investigate the exceeding probability of the rail displacement under different seismic excitations, the workflow of analyzing the smoothness of the rail based on incremental dynamic analysis (IDA) is proposed, and the intensity measure and limit state for the exceeding probability analysis of HSRs are defined. Then a finite element model (FEM) of an assumed HSR track-bridge system is constructed, which comprises a five-span simply-supported girder bridge supporting a finite length CRTS II ballastless track. Under different seismic excitations, the seismic displacement response of the rail is calculated; the character of the rail displacement is analyzed; and the exceeding probability of the rail vertical displacement exceeding the allowable standard (2mm) is investigated.

The results show that: (1) The bridge-abutment joint position may form a step-like under seismic excitation, threatening the running safety of high-speed trains under seismic excitations, and the rail displacements at mid-span positions are bigger than that at other positions on the bridge. (2) The exceeding probability of rail displacement is up to about 44% when PGA = 0.01g, which is the level-five risk probability and can be described as 'very likely to happen'. (3) The exceeding probability of the rail at the mid-span positions is bigger than that above other positions of the bridge, and the mid-span positions of the track-bridge system above the bridge may be the most hazardous area for the running safety of trains under seismic excitation when high-speed trains run on bridges.

The work extends the seismic hazardous analysis of HSRs and would lead to a better understanding of the exceeding probability for the rail of HSRs under seismic excitations and better references for the alert of the HSR operation.

A real-time production scheduling method for semiconductor back-end manufacturing process becomes increasingly important in industry 4.0. Semiconductor back-end manufacturing process is always accompanied by order splitting and merging; besides, in each stage of the process, there are always multiple machine groups that have different production capabilities and capacities. This paper studies a multi-agent based scheduling architecture for the radio frequency identification (RFID)-enabled semiconductor back-end shopfloor, which integrates not only manufacturing resources but also human factors.

The architecture includes a task management (TM) agent, a staff instruction (SI) agent, a task scheduling (TS) agent, an information management center (IMC), machine group (MG) agent and a production monitoring (PM) agent. Then, based on the architecture, the authors developed a scheduling method consisting of capability & capacity planning and machine configuration modules in the TS agent.

The authors used greedy policy to assign each order to the appropriate machine groups based on the real-time utilization ration of each MG in the capability & capacity (C&C) planning module, and used a partial swarm optimization (PSO) algorithm to schedule each splitting job to the identified machine based on the C&C planning results. At last, we conducted a case study to demonstrate the proposed multi-agent based real-time production scheduling models and methods.

This paper proposes a multi-agent based real-time scheduling framework for semiconductor back-end industry. A C&C planning and a machine configuration algorithm are developed, respectively. The paper provides a feasible solution for semiconductor back-end manufacturing process to realize real-time scheduling.

The purpose of this review is to comprehensively consider the material properties and processing of additive titanium alloy and provide a new perspective for the robotic grinding and polishing of additive titanium alloy blades to ensure the surface integrity and machining accuracy of the blades.

At present, robot grinding and polishing are mainstream processing methods in blade automatic processing. This review systematically summarizes the processing characteristics and processing methods of additive manufacturing (AM) titanium alloy blades. On the one hand, the unique manufacturing process and thermal effect of AM have created the unique processing characteristics of additive titanium alloy blades. On the other hand, the robot grinding and polishing process needs to incorporate the material removal model into the traditional processing flow according to the processing characteristics of the additive titanium alloy.

Robot belt grinding can solve the processing problem of additive titanium alloy blades. The complex surface of the blade generates a robot grinding trajectory through trajectory planning. The trajectory planning of the robot profoundly affects the machining accuracy and surface quality of the blade. Subsequent research is needed to solve the problems of high machining accuracy of blade profiles, complex surface material removal models and uneven distribution of blade machining allowance. In the process parameters of the robot, the grinding parameters, trajectory planning and error compensation affect the surface quality of the blade through the material removal method, grinding force and grinding temperature. The machining accuracy of the blade surface is affected by robot vibration and stiffness.

This review systematically summarizes the processing characteristics and processing methods of aviation titanium alloy blades manufactured by AM. Combined with the material properties of additive titanium alloy, it provides a new idea for robot grinding and polishing of aviation titanium alloy blades manufactured by AM.

The purpose of this research is to develop a framework of an ontology-based Asset Information Model (AIM) for a Digital Twin (DT) platform and enhance predictive maintenance practices in building facilities that could enable proactive and data-driven decision-making during the Operation and Maintenance (O&M) process.

A scoping literature review was accomplished to establish the theoretical foundation for the current investigation. A study on developing an ontology-based AIM for predictive maintenance in building facilities was conducted. Semi-structured interviews were conducted with industry professionals to gather qualitative data for ontology-based AIM framework validation and insights.

The research findings indicate that while the development of ontology faced challenges in defining missing entities and relations in the context of predictive maintenance, insights gained from the interviews enabled the establishment of a comprehensive framework for ontology-based AIM adoption in the Facility Management (FM) sector.

The proposed ontology-based AIM has the potential to enable proactive and data-driven decision-making during the process, optimizing predictive maintenance practices and ultimately enhancing energy efficiency and sustainability in the building industry.

The research contributes to a practical guide for ontology development processes and presents a framework of an Ontology-based AIM for a Digital Twin platform.

The promotion of autonomous vehicles introduces privacy and security risks, underscoring the pressing need for responsible innovation implementation. To more effectively address the societal risks posed by autonomous vehicles, considering collaborative engagement of key stakeholders is essential. This study aims to provide insights into the governance of potential privacy and security issues in the innovation of autonomous driving technology by analyzing the micro-level decision-making processes of various stakeholders.

For this study, the authors use a nuanced approach, integrating key stakeholder theory, perceived value theory and prospect theory. The study constructs a model based on evolutionary game for the privacy and security governance mechanism of autonomous vehicles, involving enterprises, governments and consumers.

The governance of privacy and security in autonomous driving technology is influenced by key stakeholders’ decision-making behaviors and pivotal factors such as perceived value factors. The study finds that the governmental is influenced to a lesser extent by the decisions of other stakeholders, and factors such as risk preference coefficient, which contribute to perceived value, have a more significant influence than appearance factors like participation costs.

This study lacks an investigation into the risk sensitivity of various stakeholders in different scenarios.

The study delineates the roles and behaviors of key stakeholders and contributes valuable insights toward addressing pertinent risk concerns within the governance of autonomous vehicles. Through the study, the practical application of Responsible Innovation theory has been enriched, addressing the shortcomings in the analysis of micro-level processes within the framework of evolutionary game.

This review aims to give a critical view of the wheel/rail high frequency vibration-induced vibration fatigue in railway bogie.

Vibration fatigue of railway bogie arising from the wheel/rail high frequency vibration has become the main concern of railway operators. Previous reviews usually focused on the formation mechanism of wheel/rail high frequency vibration. This paper thus gives a critical review of the vibration fatigue of railway bogie owing to the short-pitch irregularities-induced high frequency vibration, including a brief introduction of short-pitch irregularities, associated high frequency vibration in railway bogie, typical vibration fatigue failure cases of railway bogie and methodologies used for the assessment of vibration fatigue and research gaps.

The results showed that the resulting excitation frequencies of short-pitch irregularity vary substantially due to different track types and formation mechanisms. The axle box-mounted components are much more vulnerable to vibration fatigue compared with other components. The wheel polygonal wear and rail corrugation-induced high frequency vibration is the main driving force of fatigue failure, and the fatigue crack usually initiates from the defect of the weld seam. Vibration spectrum for attachments of railway bogie defined in the standard underestimates the vibration level arising from the short-pitch irregularities. The current investigations on vibration fatigue mainly focus on the methods to improve the accuracy of fatigue damage assessment, and a systematical design method for vibration fatigue remains a huge gap to improve the survival probability when the rail vehicle is subjected to vibration fatigue.

The research can facilitate the development of a new methodology to improve the fatigue life of railway vehicles when subjected to wheel/rail high frequency vibration.

Building on the theory of brand psychological ownership, this paper aims to explore the mediating role of brand psychological ownership in the relationship between brand personality (innocence/coolness) and consumers’ preferences, as well as identify the boundary conditions of this relationship.

To test the hypotheses, a series of four experiments were conducted in Wuhan, a city in southern China, using questionnaires administered at two universities and two supermarkets. Hypotheses were tested using PLS-SEM in SmartPLS 4.

The results indicate that brand personality, specifically the dimensions of innocence and coolness, has a significant impact on consumers’ brand preferences. Brands with a cool personality are preferred over those with an innocent personality. Moreover, the relationship between brand personality and consumers’ brand preferences is moderated by power motivation and identity centrality.

This study contributes to the literature by differentiating between brand personality of innocence and coolness as two separate constructs and proposing brand psychological ownership as a mechanism through which brand personality affects brand preferences. The study’s samples were drawn from universities and supermarkets in southern China, providing evidence for the significant moderating effects of power motivation and identity centrality on consumers’ brand preferences.