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The purpose of this study is to explore the means by which exporters foster innovation via the learning-by-exporting effect and to appraise the moderating role of employee human capital in the export–innovation relationship.

Leveraging the linked-survey-secondary data from the Human Capital Corporate Panel (HCCP) spanning 2011–2017, with 890 observations from 228 Korean exporters, this study utilizes Generalized Least Squares (GLS) regression to empirically test the proposed hypotheses.

The results indicate that exporting significantly boosts a firm’s innovation performance by encouraging the generation of new concepts in products, services, technologies and/or production lines. Moreover, the presence of international talent and highly educated staff positively moderates the relationship between export intensity and innovation performance.

By integrating organizational learning and human capital theories, this study yields theoretical and managerial insights by elucidating the roles of exporting and human capital in advancing innovation performance, thereby guiding corporate export strategies and human resource policies.

The purpose of this study is to investigate the impact of rapid internationalization by emerging-market multinational enterprises (EMNEs) on their innovation performance. It also seeks to identify any potential moderating factors that could influence this relationship.

By analyzing data from listed Chinese MNEs from 2012 to 2022, this study applies a negative binomial regression model to test the research hypotheses.

This study uncovers an inverted U-shaped relationship between the internationalization speed of EMNEs and their innovation performance. It also suggests that strong absorptive, learning and managerial capacities could play positive moderating roles in the effect of internationalization speed on EMNEs’ innovation performance.

This study highlights rapid global expansion, promoting new knowledge acquisition for EMNEs. However, due to time-compression dilemmas with limited EMNE firm-specific advantages, overly accelerated internationalization hinders learning effectiveness. Additionally, this study reveals the critical importance of three firm-specific capacities in EMNEs – absorptive, learning and managerial capacities – in efficiently assimilating newly acquired knowledge from foreign markets and enhancing their innovation performance through rapid internationalization.

This study aims to unravel the tensions and convergences between market-oriented neoliberal education and state-serving transnational higher education (TNHE) practices through an infrastructural lens within the broad context of post-pandemic geopolitics.

The study utilizes a case study approach, with a diverse array of data collection methods, including observations, interviews and review of material/online documents issued by the TNHE-related institutions and the Chinese Ministry of Education.

The study identifies three findings: (1) Re-articulation of transnational infrastructures, valuing ‘glocal' education and casting immobility as advantageous yet quasi-mobile; (2) Infrastructural tensions arising from stakeholder contests over program control and (3) Infrastructural dialectics, illustrating how promised (im)mobility becomes a tightly regulated academic journey due to institutional constraints and conflicts.

The findings elucidate the dynamic interplay between international education and TNHE amidst neoliberal pedagogical trends and pandemic-driven geopolitical shifts in China. While the interplay showcased a notable effect on Chinese students' (im)mobility during the pandemic, more empirical research is needed to understand international student (im)mobility issues in the post-pandemic era.

This study explores the infrastructural intersections between international and transnational education during the unprecedented Covid-19. Findings may provide a reference for policymakers and practitioners to strategize the “glocal” approach to international/transnational education in China after the pandemic.

This paper aims to review the latest management developments across the globe and pinpoint practical implications from cutting-edge research and case studies.

This briefing is prepared by an independent writer who adds their own impartial comments and places the articles in context.

Exporting firms can significantly improve their innovation capabilities through a focus on key aspects of their human capital. Increasing international experience and appointing and developing highly educated employees helps equip them with greater knowledge and understanding of diverse foreign markets to subsequently increase the positive impact of exporting intensity on innovation performance.

The briefing saves busy executives and researchers hours of reading time by selecting only the very best, most pertinent information and presenting it in a condensed and easy-to-digest format.

The aging and deterioration of engineering building structures present significant risks to both life and property. Fiber Bragg grating (FBG) sensors, acclaimed for their outstanding reusability, compact form factor, lightweight construction, heightened sensitivity, immunity to electromagnetic interference and exceptional precision, are increasingly being adopted for structural health monitoring in engineering buildings. This research paper aims to evaluate the current challenges faced by FBG sensors in the engineering building industry. It also anticipates future advancements and trends in their development within this field.

This study centers on five pivotal sectors within the field of structural engineering: bridges, tunnels, pipelines, highways and housing construction. The research delves into the challenges encountered and synthesizes the prospective advancements in each of these areas.

The exceptional performance of FBG sensors provides an ideal solution for comprehensive monitoring of potential structural damages, deformations and settlements in engineering buildings. However, FBG sensors are challenged by issues such as limited monitoring accuracy, underdeveloped packaging techniques, intricate and time-intensive embedding processes, low survival rates and an indeterminate lifespan.

This introduces an entirely novel perspective. Addressing the current limitations of FBG sensors, this paper envisions their future evolution. FBG sensors are anticipated to advance into sophisticated multi-layer fiber optic sensing networks, each layer encompassing numerous channels. Data integration technologies will consolidate the acquired information, while big data analytics will identify intricate correlations within the datasets. Concurrently, the combination of finite element modeling and neural networks will enable a comprehensive simulation of the adaptability and longevity of FBG sensors in their operational environments.

This empirical study aims to test the impact of four types of entrepreneurial context on the growth and success rates of new ventures in China and related the findings to the theory and practice of entrepreneurship dating back 2,500 years to ancient China.

After describing the business guidelines given by Fan Li, an entrepreneurial merchant selling Chinese medicines in ancient times, a conceptual framework was extracted as the basis for a discussion of the relationship between entrepreneurial context and entrepreneurial activity. Entrepreneurial context was conceptualized as being composed of family, social, business and institutional components. Five hypotheses about the influence of these different context variables on entrepreneurial activities were developed. From data compiled from the sampling of 239 business entrepreneurs in Beijing, a hierarchical regression was formed and the hypotheses tested.

The impact of entrepreneurial context on entrepreneurial activity can be divided into two layers, internal factors (e.g. family context) which are similar to “yin” (?) in the traditional Chinese philosophy while external factors (e.g. business, social and institutional contexts) were like “yang” (?). The two factors play different roles in entrepreneurial activities, while different contexts mediate and moderate each other in complex ways.

Research limitations pertain to the size and locale of the sample. A larger sample that involved subjects from different regions would facilitate a wider understanding of the effects of entrepreneurial context upon the entrepreneurial process.

The theory of entrepreneurial context is in its beginning stages, and the paper completed a systematic study of entrepreneurial context through theoretical model building using large-sample empirical research. In addition, the paper is the first ever to relate the theory and practice of entrepreneurship back 2,500 years. Through a multi-research methodology, the study clearly shows the critical importance of integrating Chinese history into the development of management theory.

This chapter provides a multilevel perspective on the impact of leaders’ emotional display and control on subordinates’ job satisfaction.

This multilevel study investigates how the association of employees’ perceived immediate leaders’ servant leadership and their job satisfaction is influenced by leaders’ emotional labor. Participants in this study included 180 employees and 40 immediate leaders from 40 groups across 16 firms. To avoid of common methods of variances, multiple ratings were employed. Servant leadership of immediate team leaders and subordinates’ job satisfaction were rated by subordinates.

The results showed the positive relationship between perceived team leaders’ creating value for community (one dimension of servant leadership) and team members’ job satisfaction is strengthened by an increase in leaders’ deep-acting of emotions, but is decreased with an increase in leaders’ surface-acting and expression of naturally felt emotions.

This study confirms that a team leader’s emotional labor is likely to affect team members’ job satisfaction, which is also related to employees’ perceived servant leadership. Although how leaders display their emotions in organizations has a significant influence on the association between leaders’ creating value for community and subordinates’ job satisfaction, this study did not identify the explicit mechanisms to explain why this happens.

These findings will enrich the practice of leaders’ emotional management in organizations.

This chapter is the first to provide a perspective to understand leaders’ emotional labor from cross-level analysis. This study also extends our understandings of the effects of servant leadership and its relationships with subordinates’ job satisfaction through an exploration of each dimension of servant leadership on job satisfaction rather than relying on an overall measure servant leadership.

Small and medium-sized enterprises (SMEs) are currently showing an increasingly open innovation (OI) approach. Public policies supporting the adoption of OI by SMEs are becoming a priority for policymakers. Therefore, the aim of this article is to contribute to the literature by mapping scholars' policy recommendations for implementing OI among SMEs.

The authors conducted a systematic review of the literature (SRL) on the topic to achieve this purpose. A total of 99 academic articles were selected from the Web of Science and Scopus databases to suggest the main scholars' policy recommendations to implement OI among SMEs.

Results indicated that scholars' policy recommendations for OI adoption in SMEs can be organized into: research and development (R&D), networking, collaboration, knowledge and intellectual property rights (IPR), ecosystem, managerial capabilities, funding and incentives and sustainability policies.

Only relevant articles about this topic have been included due to the reliance on the interpretations of the authors. The analysis of the literature revealed that the authors did not always distinguish policies dedicated to SMEs and those dedicated to large companies. Moreover, policies are not matched according to each OI dimensions (e.g. inbound, outbound and coupled OI).

The article uses a systematic literature review method that combines qualitative and quantitative analyses. This method contributes to theoretical development of OI policies dedicated, in particular to SMEs. This paper also provides policymakers and researchers with insights on the scope of OI policies that could support economic growth.

Despite the widespread use of univariate empirical mode decomposition (EMD) in financial market forecasting, the application of multivariate empirical mode decomposition (MEMD) has not been fully investigated. The purpose of this study is to forecast the stock price index more accurately, relying on the capability of MEMD in modeling the dependency between relevant variables.

Quantitative and comprehensive assessments were carried out to compare the performance of some selected models. Data for the assessments were collected from three major stock exchanges, namely, the standard and poor 500 index from the USA, the Hang Seng index from Hong Kong and the Shanghai Stock Exchange composite index from China. MEMD-based support vector regression (SVR) was used as the modeling framework, where MEMD was first introduced to simultaneously decompose the relevant covariates, including the opening price, the highest price, the lowest price, the closing price and the trading volume of a stock price index. Then, SVR was used to set up forecasting models for each component decomposed and another SVR model was used to generate the final forecast based on the forecasts of each component. This paper named this the MEMD-SVR-SVR model.

The results show that the MEMD-based modeling framework outperforms other selected competing models. As per the models using MEMD, the MEMD-SVR-SVR model excels in terms of prediction accuracy across the various data sets.

This research extends the literature of EMD-based univariate models by considering the scenario of multiple variables for improving forecasting accuracy and simplifying computability, which contributes to the analytics pool for the financial analysis community.