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Employees’ bootlegging innovation behavior is common and plays an important role in enterprise management. Based on the resource conservation theory and self-regulation theory, the purpose of this study is to explore the influence mechanism of leaders’ abusive supervision on employees’ bootlegging innovation behavior, with psychological safety as a mediator and mindfulness at workplace as a moderator.

Survey data were gathered from 591 employees’ self-assessment questionnaires in China. Hierarchical regression analysis was used to test the research model through SPSS and AMOS.

This study found that the leaders’ abusive supervision negatively affects employees’ bootlegging innovation behavior; employees’ psychological safety completely mediates the negative effect of leaders’ abusive supervision on employees’ bootlegging innovation behavior; and mindfulness at work moderates the influence of leaders’ abusive supervision on employee’ bootlegging innovation behavior, as well as the influence of leaders’ abusive supervision on employees’ psychological safety.

This study has significant implications in passive leadership that affect employees’ innovation. Authors found that leaders’ abusive supervise, mindfulness at workplace play a crucial role in employees’ bootleg innovation through psychological safety.

Theoretically, this study has enriched the antecedent research on employees’ bootlegging innovation behavior from the perspective of negative leadership behavior and employee psychology. And this study considered mindfulness at workplace as a boundary condition.

This study explores the impact of owner chief executive officers' (CEO) narcissism on the exporting small to medium-sized enterprises' (SMEs) decision-making on the international market expansion speed after their initial entry. Specifically, the authors use the mechanism of firms' international entrepreneurial orientation (IEO) to examine how owner CEO narcissism may influence SMEs' post-entry speed of internationalization (PSI), both directly and indirectly.

To test the hypotheses, the authors draw on data from a two-wave questionnaire and on archival export data from 291 Chinese exporting SMEs in three municipalities and 17 provinces from 2019 to 2020.

The results support the theoretical predictions that owner CEO narcissism shapes exporting SMEs' decisions on PSI, both directly and indirectly, through the mediation of firm-level IEO.

The study extends emerging research on the role of CEO narcissism in the upper echelons literature into the international marketing (IM) context. It also offers new insights into what drives exporting SMEs' IM decision-making from a psychological microfoundations perspective. Furthermore, the authors theoretically establish and empirically demonstrate the key role of a firm's IEO as a mediator to complement the existing literature's focus on the direct influence of CEO narcissism on firms' internationalization decisions.

The visible time window (VTW) calculation of satellites to ground targets is significant for Earth observation satellites' operation management and control. With the improvement of satellite maneuvering capability and the complexity of on-orbit observation tasks, the traditional VTW calculation methods can no longer meet the demands of satellite operation management and control due to a large amount of calculation and low efficiency. The purpose of this study is to propose a fast VTW calculation method based on map segmentation named map segmentation method (MSM), to improve the calculation efficiency, and further solve this problem.

The main feature of the MSM method is to segment the map and subsatellite trajectories and traverse the subsatellite points within a specific range around the target, significantly reducing the search space and the amount of computation and improving computational efficiency.

Numerical simulations for two satellite orbits are implemented to verify the feasibility of the proposed VTW calculation method, and the traditional traversal method (TM) is also performed for comparative analysis. The results show that the proposed method can obtain the same VTW, using less calculation time than the TM. The computational efficiency is significantly improved, especially for many tasks. The calculation time of observing 500 targets is saved by more than 70%, indicating a broad application prospect.

This paper proposes an original VTW calculation method based on map segmentation to improve the calculation efficiency. The simulation scenarios are designed to verify the accuracy and effectiveness of the proposed method, and the observation targets are randomly distributed on the map. For comparative analysis, the TM is also performed under the same simulation conditions.

This paper aims to study and modify the notch equivalent stress method, as well as to establish the notch equivalent stress range S–N curve and apply it to the fatigue assessment of engineering examples.

This paper studies the notch equivalent stress method and puts forward the concept of “singular equivalent crack”. Combined with the fatigue test results, by proposing to consider the singular coefficient of the transition angle of the welded structure and the introduction of material correction factors, this paper derives the notch equivalent stress equation for commonly used welded joints applicable to steel, and finally establishes the notch equivalent stress range of the S–N curve.

The obtained results show that the dispersion of fatigue data is 65.6 and 75.4% for T-joints and transverse cross-joints, respectively, under S–N curves using notched equivalent stress compared to the nominal stress range. The fatigue evaluation error of the modified notch equivalent stress equation for transverse cross welded joints improved by 50.65%, 53.1 and 39.6% on average, respectively, compared to the original other methods. The fatigue evaluation error for T-joints improved by 13.4 and 13.9%, respectively, compared to the original other methods.

There are relatively few studies on the fatigue assessment of notch equivalent stress method. In this paper, the notch equivalent stress method is studied and modified to improve the accuracy of fatigue assessment of welded structures with singular stresses.

Nucleic acid testing is an effective method of accurate prevention and control and a key measure to block the spread of the epidemic. However, the fraud in nucleic acid testing occurred frequently during epidemics. This paper aims to provide a viable scheme for the government to strengthen the supervision of nucleic acid testing and to provide a new condition for the punishment for the negative act of the government and the upper limit of the reward for nucleic acid testing institution of no data fraud.

This paper formulates an evolutionary game model between the government and nucleic acid testing institution under four different mechanisms of reward and punishment to solve the issue of nucleic acid testing supervision. The authors discuss the stability of equilibrium points under the four distinct strategies and conduct simulation experiments.

The authors find that the strategy of dynamic reward and static penalty outperforms the strategies of static reward and static penalty, dynamic reward and static penalty, static reward and dynamic penalty, dynamic reward and dynamic penalty. The results reveal the appropriate punishment for the negative act of the government can enhance the positivity of the government's supervision in the strategy of dynamic reward and static penalty, while the upper limit of the reward for nucleic acid testing institution of no data fraud cannot be too high. Otherwise, it will backfire. Another interesting and counterintuitive result is that in the strategy of dynamic reward and dynamic penalty, the upper limit of the penalty for data fraud of nucleic acid testing institution cannot be augmented recklessly. Otherwise, it will diminish the government's positivity for supervision.

Most of the existing evolutionary game researches related to the reward and punishment mechanism and data fraud merely highlight that increasing the intensity of reward and punishment can help improve the government's supervision initiative and can minimize data fraud of nucleic acid institution, but they fall short of the boundary conditions for the punishment and reward mechanism. Previous literature only study the supervision of nucleic acid testing qualitatively and lacks quantitative research. Moreover, they do not depict the problem scenario of testing data fraud of nucleic acid institution regulated by the government via the evolutionary game model. Thus, this study effectively bridges these gaps. This research is universal and can be extended to other industries.

The rapid rise of large language models (LLMs) has propelled them to the forefront of applications in natural language processing (NLP). This paper aims to present a comprehensive examination of the research landscape in LLMs, providing an overview of the prevailing themes and topics within this dynamic domain.

Drawing from an extensive corpus of 198 records published between 1996 to 2023 from the relevant academic database encompassing journal articles, books, book chapters, conference papers and selected working papers, this study delves deep into the multifaceted world of LLM research. In this study, the authors employed the BERTopic algorithm, a recent advancement in topic modeling, to conduct a comprehensive analysis of the data after it had been meticulously cleaned and preprocessed. BERTopic leverages the power of transformer-based language models like bidirectional encoder representations from transformers (BERT) to generate more meaningful and coherent topics. This approach facilitates the identification of hidden patterns within the data, enabling authors to uncover valuable insights that might otherwise have remained obscure. The analysis revealed four distinct clusters of topics in LLM research: “language and NLP”, “education and teaching”, “clinical and medical applications” and “speech and recognition techniques”. Each cluster embodies a unique aspect of LLM application and showcases the breadth of possibilities that LLM technology has to offer. In addition to presenting the research findings, this paper identifies key challenges and opportunities in the realm of LLMs. It underscores the necessity for further investigation in specific areas, including the paramount importance of addressing potential biases, transparency and explainability, data privacy and security, and responsible deployment of LLM technology.

The analysis revealed four distinct clusters of topics in LLM research: “language and NLP”, “education and teaching”, “clinical and medical applications” and “speech and recognition techniques”. Each cluster embodies a unique aspect of LLM application and showcases the breadth of possibilities that LLM technology has to offer. In addition to presenting the research findings, this paper identifies key challenges and opportunities in the realm of LLMs. It underscores the necessity for further investigation in specific areas, including the paramount importance of addressing potential biases, transparency and explainability, data privacy and security, and responsible deployment of LLM technology.

This classification offers practical guidance for researchers, developers, educators, and policymakers to focus efforts and resources. The study underscores the importance of addressing challenges in LLMs, including potential biases, transparency, data privacy, and responsible deployment. Policymakers can utilize this information to shape regulations, while developers can tailor technology development based on the diverse applications identified. The findings also emphasize the need for interdisciplinary collaboration and highlight ethical considerations, providing a roadmap for navigating the complex landscape of LLM research and applications.

This study stands out as the first to examine the evolution of LLMs across such a long time frame and across such diversified disciplines. It provides a unique perspective on the key areas of LLM research, highlighting the breadth and depth of LLM’s evolution.

While there is research that has explored how institutions have responded to various crises, these are usually locally or regionally situated. However, no event has impacted higher education globally like COVID-19 and it will certainly alter the way top administrators lead and how institutions move forward. Thus, this chapter will explore how to better understand how presidents and top administrators navigate the (inter)national geopolitics as they move the institution forward. In addition, clear and up-to-date communication has proven to be important in battling this crisis. Thus, how presidents at national universities have communicated with students, faculty, staff, and various off-campus communities members regarding COVID-19 and how they have achieved is important to explore. Our findings suggest that presidents and top administrators need to build support to help them navigate the political roadblocks they may encounter. Findings also suggest that communication is the main role they play as leaders on their campus. On/off-campus community members see the presidents as the face of the university and key communicator as relates to communicating what the institutions is doing and how they are addressing the crisis. This chapter helps in better understanding the roles presidents and top administrators play during a global crisis.

This paper aims to present the vertical integration state-of-the-art and propose an expansion of the operations and supply chain management (OSCM) field by identifying gaps and bottlenecks.

This paper uses a systematic literature review based on a sample of 173 OSCM field articles, collected from Scopus and Web of Science databases.

There are no single factors, such as future costs, structures or skills development, in the decision to vertically integrate operations. It is necessary to combine the vision of production costs with the perspective of governance and transaction costs. In addition, it is essential to consider the competency perspective and its impact on capability building.

Few studies have attempted to understand how vertical integration is used in terms of OSCM research themes and theories. Vertical integration can help companies face challenges and serve as a potential solution for achieving better prices, demand control and quality management.

The significant role of vertical integration mechanisms in supply chains is crucial for managers evaluating a firm's reconfiguration with more vertical operations. Policymakers interested in supporting the smoothness of vertical integration decisions in regulatory agencies play a key role as contingencies.

In times of global challenges, vertical integration is a strategy known to be more effective for firms to obtain a competitive advantage, making them more resilient.

This paper addresses gaps in the vertical integration theme and provides insights for future research development.

The 21st century has brought the business model earth-shaking changes, especially since the Corona Virus Disease 2019 (COVID-19) epidemic at the end of 2019. Now, the epidemic normalization is slowing down China's rapid development. However, technological development, like artificial intelligence (AI), is unstoppable and is transforming China's economic growth modes from factor-driven to innovation-driven systems. Therefore, it is necessary to study further the new changes in labor entrepreneurship and innovation business models and their mechanism of action on economic growth.

This work studies how innovative human capital (IHC) uses AI and other scientific and technological (S&T) innovation technologies to promote China's innovation-driven economic growth model transformation from the labor entrepreneurship and innovation perspective.

The research shows that the entrepreneurial innovation ability of IHC can increase marginal return and output multiplier effect. It changes the traditional business model and promotes China's economic growth and innovation development. At the same time, this work analyzes China's inter-provincial panel data through the panel smooth transition regression (PSTR) model. It concludes that there is a nonlinear relationship between IHC and the output of innovative achievements. The main body presents three stages of nonlinear changes: first rising, then slightly declining, and rising so far.

The finding provides a direction for solving the problem of slow economic growth and accelerating the transformation of economic growth mode under epidemic normalization.

Drawing on the self-cognitive theory, this study aims to propose a conceptual model that links customer mistreatment with different types of helping behaviors through the self-efficacy mechanism.

The empirical analysis made use of the original data of three hotels located in southern China. The authors tested the hypotheses with a three-wave survey of a sample of 430 frontline workers in 95 groups.

Customer mistreatment may reduce employees’ self-efficacy, which has both positive and negative effects depending on the type of helping. Moreover, the coworkers’ supporting climate buffered the influence of self-efficacy on autonomous and dependent helping.

The authors resolve the ambiguity surrounding customer mistreatment-helping and self-efficacy-helping relations. Thus, the authors extend the knowledge on the influence of customer mistreatment and self-efficacy on helping behaviors by establishing that both positive and negative effects may exist depending on the type of helping. Moreover, this study identifies the predictive role of self-efficacy in autonomous and dependent helping.