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This study investigates the impact of customer stability on the cost of debt and the moderating effect of environmental uncertainty on the above relationship.

An empirical analysis based on the ordinary least squares (OLS) regression model is conducted using China’s A-share listed companies on the Shanghai and Shenzhen Stock Exchanges from 2007 to 2021.

The results indicate that customer stability significantly inhibits the cost of debt, and the higher the environmental uncertainty, the more significant the inhibitory effect of customer stability on the cost of debt. The results of heterogeneity analyses indicate that the more intense the industry competition, the higher the customer concentration or the older the average customer age, the more significant the inhibiting effect of customer stability on the cost of debt.

This study highlights the importance of customer relationship management and supply chain risk management, which have both theoretical and managerial implications. Despite its contributions, this study has limitations, such as China’s institutional context limits, which the generalisability of our results, and the sample size for this study is small because of limitations in measuring customer stability.

Existing literature has not yet reached a consistent conclusion on how customer relationships affect the cost of debt, and such studies are mainly centered around perspectives such as customer concentration and the contagion effect of supply chains. This study constructs an indicator of customer stability using detailed information on the top five customers of China’s A-share listed companies and dynamically examines the impact of customer stability on the cost of debt, which expands the research on the influencing factors of the cost of debt, the economic consequences of customer stability and the theory of customer relationship management.

This study aims to investigate the effect of top management team (TMT) stability on outward foreign direct investment (OFDI) of Chinese firms and the moderating effects of state ownership and managerial ownership on this relationship.

An empirical analysis based on the ordinary least square regression model is conducted using Chinese A-share listed firms that engaged in OFDI from 2008 to 2021.

TMT stability has a positive effect on firms’ OFDI. Moreover, state ownership significantly strengthens the positive relationship between TMT stability and OFDI, while managerial ownership weakens this positive relationship.

The findings help firms to effectively retain TMT talents and promote the smooth internationalization of firms, thereby enhancing their long-term development capabilities and competitive advantages.

This study expands the investigation of the factors influencing OFDI at the micro level of the TMT, providing valuable decision-making insights for firms.

According to the resource-based theory, a firm’s unique resources and capabilities are the key to its competitive advantage. This paper aims to investigate the effect of top management team (TMT) stability, an important intangible resource of the firm, on the maturity mismatch between investment and financing of companies. Additionally, we explore the moderating effects of state ownership and institutional ownership in this context.

This study conducts an empirical analysis based on the ordinary least squares (OLS) model with a sample of Chinese companies listed on the Shanghai and Shenzhen stock exchanges from 2010 to 2022.

The results show that TMT stability significantly mitigates the degree of maturity mismatch. Both state ownership and institutional ownership weaken the negative effect of TMT stability on maturity mismatch. Besides, alleviating financing constraints is a crucial pathway through which TMT stability influences maturity mismatch.

The findings help firms to effectively retain TMT talents and reduce the occurrence of maturity mismatch.

This paper not only helps to expand the research on the economic effects of TMT stability but also provides new ideas on how to alleviate the maturity mismatch of companies.

This study investigates the effect of ownership structure – ownership concentration and firm ownership – on outward foreign direct investment (OFDI) by emerging market multinational enterprises (EMNEs), and further explores the moderating effects of international experience and migrant networks on this relationship.

Data of Chinese MNEs listed on Shenzhen and Shanghai stock exchanges between 2005 and 2016 are used. The empirical analysis is based on the negative binomial regression model.

The empirical results reveal a significant inverted-U relationship between ownership concentration and OFDI by EMNEs. State ownership is found to have a positive effect on OFDI by EMNEs. Both international experience and migrant networks strengthen the inverted-U relationship between ownership concentration and OFDI as well as the positive effect of state ownership on OFDI by EMNEs.

EMNEs need to maintain a moderate ownership concentration when conducting OFDI, and they are supposed to make full use of their own international experience and focus on migrant networks of the host country. Policy-makers in emerging economies need to better create a fair business environment for enterprises.

Combining agency theory and the resource-based view, this study integrates ownership structure, firm-level heterogeneous resources – international experience and country-level heterogeneous resources – migration networks into a framework to study OFDI by EMNEs, which expands the scope of research in international business.

This paper investigates the effect of business environment distance on innovation performance of emerging market multinational enterprises (EMNEs) and explores the mediating effect of absorptive capacity between the two, and it further analyzes the moderating effect of skilled migrants in the relationship between business environment distance and absorptive capacity.

An empirical analysis based on a fixed effect model is conducted using data of Chinese MNEs listed on the Shanghai and Shenzhen Stock that expand into developed markets from 2011 to 2018.

The results suggest business environment distance positively affects the innovation performance of EMNEs, and can enhance innovation performance by affecting absorptive capacity of EMNEs. In addition, skilled migrants strengthen the relationship between business environment distance and absorptive capacity of EMNEs.

Chinese MNEs should fully exploit business environment distance to acquire the technology needed for innovation activities, and strengthen absorptive capacity to maximize the benefits from innovation. Chinese government needs to strengthen the construction of skilled migrants to facilitate knowledge and technology transfer.

Combining springboard theory and institutional theory, this paper integrates macro and micro perspectives to explore whether and how business environment distance affects innovation performance of Chinese MNEs. The paper provides a good theoretical basis and important practical reference value for enhancing the technological innovation capability of Chinese MNEs and the overall technological innovation level of China.

This study investigates the effect of psychic distance (PD) on outward foreign direct investment (OFDI) by multinational firms originating in emerging economies and the moderating effect of firm heterogeneity on this relationship.

An empirical analysis based on a negative binomial regression model is conducted using OFDI data from 2008 to 2017 on companies listed on the Shanghai and Shenzhen Stock Exchanges in China, an emerging economy.

The results suggest a U-shaped relationship between PD and OFDI by firms in emerging economies. Both executive foreign experience and state ownership negatively moderate the U-shaped relationship between PD and OFDI.

Emerging economies should encourage and guide multinational firms in engaging in OFDI and emphasize the advantages and disadvantages of PD for multinational firms. Additionally, non-sate-owned firms should recruit those who have a foreign education to provide support for OFDI by firms in emerging economies. Multinational firms should determine investment locations by consulting with executives with foreign experience to improve their ability to engage in OFDI.

This study combines macro and micro perspectives and integrates PD and firm heterogeneity into the same model with a sample of multinational firms originating in China. The findings support the existence of a PD paradox, which helps to enriching the theory on foreign direct investment.

The topic of employees’ unethical pro-organizational behavior (UPB) has attracted more and more interest in both practice and academic fields. However, previous studies have mainly investigated the antecedents of UPB and little research has discussed the outcome variables. This study aims to provide a comprehensive understanding of the effect mechanism of UPB on employee performance evaluation rated by a supervisor through a leader-member exchange (LMX) and the moderating role of supervisor bottom-line mentality (BLM).

This study used a sample consisting of 304 employees and 96 supervisors in several manufacturing firms in China. The authors used hierarchical linear modeling to test the hypotheses, as this was cross-level research. In addition, this paper also uses Mplus7.4 to test the moderating effects of supervisor BLM on the indirect effects between the UPB and performance evaluation by a moderated path analysis.

The results confirm that UPB is positively related to performance evaluation rated by supervisors. Additionally, the mediating effect of LMX in the relationship between UPB and performance evaluation is successfully demonstrated. Furthermore, supervisor BLM cross-levelly moderates the relationship between UPB and LMX, as well as moderates the mediation effect of LMX on the correlation between UPB and performance evaluation.

The primary contribution of this research is building a cross-level model for the effect of UPB on followers’ performance evaluation scored by the supervisor and thereby extending the nomological networks of both UPB and performance evaluation literature. Another contribution the study makes to the literature is that it provides a new perspective to understand how UPB relates to followers’ performance evaluation.

This is the first study about how and when UPB predicts followers’ performance evaluation rated by the supervisor.

Recent tourism research has adopted social media analytics (SMA) to examine tourism destination image (TDI) and gain timely insights for marketing purposes. Comparing the methodologies of SMA and intercept surveys would provide a more in-depth understanding of both methodologies and a more holistic understanding of TDI than each method on their own. This study aims to investigate the unique merits and biases of SMA and a traditional visitor intercept survey.

This study collected and compared data for the same tourism destination from two sources: responses from a visitor intercept survey (n = 1,336) and Flickr social media photos and metadata (n = 11,775). Content analysis, machine learning and text analysis techniques were used to analyze and compare the destination image represented from both methods.

The results indicated that the survey data and social media data shared major similarities in the identified key image phrases. Social media data revealed more diverse and more specific aspects of the destination, whereas survey data provided more insights in specific local landmarks. Survey data also included additional subjective judgment and attachment towards the destination. Together, the data suggested that social media data should serve as an additional and complementary source of information to traditional survey data.

This study fills a research gap by comparing two methodologies in obtaining TDI: SMA and a traditional visitor intercept survey. Furthermore, within SMA, photo and metadata are compared to offer additional awareness of social media data’s underlying complexity. The results showed the limitations of text-based image questions in surveys. The findings provide meaningful insights for tourism marketers by having a more holistic understanding of TDI through multiple data sources.

Bridge plans are a complicated grey system. It depends on various natural and social factors. The purpose of this paper is to provide a scientific method for optimization of bridge construction plan.

Grey relational analysis (GRA) is completely new analysis method has been proposed in the grey system theory. Grey relational order can be used to describe the relation between the related factors based on data series rather than linear relation and typical distribution. First, this paper describes the basic steps and formulae of GRA. Then provides an example to show how to select best bridge construction plan with the method. Specially discusses significant influence of weight selection on decision making for a bridge plan.

The optimization of bridge construction plan will be selected more reasonable and more objective with the method GRA.

This paper will be further studied on how to quantify indicators more objectively and how to decide weight factor more reasonably.

It has significant practical value to apply GRA to optimization of bridge plans and other engineering projects.

A scientific method‐GRA has been applied to the selection of bridge plans for seeking the best comprehensive result.

This study explored preservice and in-service early childhood teachers' online academic learning beliefs and strategies.

Two hundred preservice and in-service teachers respectively from Taiwan participated in this research. A focus group discussion was carried out concerning the development of the questionnaires. The exploratory and confirmatory factor analysis confirmed good construct validity and reliabilities of the survey.

The survey results showed that in-service teachers generally held more sophisticated learning beliefs than the preservice teachers in all scales. Also, in-service teachers responded with a higher level of online academic learning strategies than the preservice teachers did. Regarding their online experiences, preservice teachers who spent an appropriate amount of time online had more positive beliefs than those with excessive online experiences. However, preservice teachers did not reveal employment of their ICT literacy in their online academic learning strategies. It was found that those in-service teachers with more online learning experience also showed higher levels of online academic learning beliefs. They used more deep strategies in their online academic learning.

The findings of this study could provide insights for the development of online academic learning ability in preschool teacher training programs.

(1) In-service teachers generally held more sophisticated learning beliefs than the preservice teachers. (2) Preservice teachers who spent an appropriate amount of time online had more positive beliefs than those with excessive online experiences. (3) Preservice teachers did not reveal employment of their ICT literacy in their online academic learning strategies. (4) In-service teachers with more online learning experience also showed higher levels of online academic learning beliefs. They used more deep strategies in their online academic learning.