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This study aims to investigate the role of network in affecting private firms’ internationalization decision. Specifically, it investigates the way that business ties, political ties and status influence an internationalization decision.

On the basis of the survey data collected from Chinese private firms, this study distinguishes business ties from political ties and introduces network status. Binary logistic regression is used to test the hypotheses.

Results show that private firms that have business ties are more likely to internationalize, whereas private firms that have political ties are less likely to internationalize. High-status private firms are more likely to internationalize. Political ties negatively moderate the relationship between business ties and internationalization. High-status firms with political ties are more likely to internationalize.

This study provides theoretical and practical contributions. Results complement previous research on social networks in the context of Chinese private firms and have implications for managers who exert effort to internationalize their firms.

Rather than focussing on dyadic distributor–supplier relationships, this study aims to examine whether the difference in transaction-specific investments (TSIs) between rival suppliers in a supplier–distributor–supplier triad influences whether distributors expropriate or maintain their supplier’s TSIs.

Drawing on triadic data from 276 questionnaires that address both the supplier–distributor relationship and the rival supplier–distributor relationship, a moderated regression analysis is used to test the hypotheses.

Five out of six hypotheses are supported by the empirical test. The results show that the supplier’s TSIs increase the distributor’s opportunistic behaviour and reduce cooperation when the distributor perceives that the supplier’s TSIs are lower than those of a rival supplier. In contrast, when the distributor perceives that the supplier’s TSIs are higher than those of a competitor, the supplier’s TSIs do not improve cooperation and can shift the link between the supplier’s TSIs and the distributor’s opportunism from being positive to negative.

The findings have implications for the top managers of supplier firms embedded in distribution networks. This study suggests that the competitor’s TSIs can be regarded as an indicator of the supplier’s relationship with the distributor. By keeping an eye on their competitors’ TSIs, the top managers of suppliers can predict the likelihood of distributors’ opportunistic and cooperative behaviour and make efforts to improve their position by adjusting their own firm’s TSIs. Furthermore, this information can help suppliers decide on their investment strategies and maintain stable and healthy relationships.

This study 1) examines the effect of TSIs using a triadic framework and triadic data and demonstrates that how a distributor responds to a supplier’s TSIs, with either opportunism or cooperation, depends on the relative level of those TSIs in focal and competitive relationships; and 2) reveals the expropriation effects and restraint effects of TSIs by drawing on prospect theory. This finding indicates the dynamics of TSIs in a triadic relationship.

Individuals who spend a large percentage of their incomes on consumption are perceived to prefer risks. Since entrepreneurs are well recognized as risk-takers, this chapter investigates whether consumption propensity is associated with entrepreneurship. Using micro-level data from Chinese Household Income Project, we find that households with a higher income–consumption ratio on average have a higher preference for risk-seeking, while they have a lower probability to be entrepreneurs. However, households who have higher consumption–income ratio and are in the top 10% of the wealth distribution are more likely to embark on entrepreneurship. In addition, we find that in-system connection (relationship with government-related units) decreases the likelihood of starting new business, while out-system connection (relationship with market units) increases it. These findings suggest that in an imperfect financial market, start-up finance and connections play important roles for entrepreneurship.

E-commerce live streaming (ELS) has become a new and important shopping channel. Although previous studies have provided insightful findings on how to engage consumers in ELS, limited effort has been made to explore the role of factors of live streaming rooms. Based on the literature on space perception and the retail environment, this study aims to develop a theoretical model to examine how perceived distance and perceived depth affect consumers' affective and cognitive perceptions and then further impact product attitude in ELS.

This study collected 414 valid survey responses to test the proposed research model. Survey data were analyzed using partial least squares (PLS)-structural equation modeling. The PLS Multi-Group analysis (PLS-MGA) was used to test the consistency of the research model across different product types and watching durations.

The results suggest that environmental factors of a live streaming room (i.e. perceived distance and perceived depth) can impact consumers' attitudes toward the product in the live streaming via both cognitive and affective routes. These effects keep consistent across different product types and watching durations.

The paper focuses on the environmental perspective, which is unexplored in previous literature on ELS. It highlights the importance of the space design of live streaming rooms.

This research paper aims to investigate the critical factors influencing the live commerce industry and their implications for Key Opinion Leaders (KOLs) and brands.

The study comprehensively reviews previous research, develops relevant hypotheses and utilizes personal information from 66 anchors, along with data from 23,000 product links obtained from the backends of live commerce platforms.

The study emphasizes that KOLs with higher traffic significantly influence Gross Merchandise Volume (GMV). Intriguingly, KOLs with lower traffic levels exhibit a more pronounced effect on Return on Investment (ROI), highlighting their significance in driving profitability. Furthermore, the study explores the correlation between KOL hashtags and GMV/ROI and the intricate relationship between product types and KOL hashtags.

The findings significantly enhance the understanding of live shopping behavior and provide valuable insights for business management strategies. Practitioners can leverage this empirical evidence to make informed decisions, utilizing extensive data samples of KOLs and brands.

This research contributes unique insights into the live-streaming commerce industry using backend data from Live Streaming E-commerce platforms. The findings are more accurate based on market data than previous studies that relied on platform reviews or questionnaires. Additionally, this paper investigates the impact of KOLs on the performance of live e-commerce from three perspectives: GMV, ROI and hot-selling products.

The purpose of this study is to investigate the influencing mechanism of consumers' continuous purchase intention toward the subscriber-based knowledge payment platforms (SBKPPs).

This study obtained 226 valid samples through questionnaire surveys and used partial least square structural equation modeling (PLS-SEM) and fuzzy-set qualitative comparative analysis (fsQCA) methods to elucidate the complex causal patterns of consumers' continuous purchase intention toward the SBKPPs.

The findings revealed that perceived utilitarian value, perceived hedonic value and perceived social value directly affected consumers' continuous purchase intention, while content quality and service quality indirectly affected consumers' continuous purchase intention. In addition, this study also demonstrated that all factors must be combined to play a role, and there exist four configurations resulting in consumers' continuous purchase intention toward the SBKPPs.

The results can help researchers and practitioners better understand the causal patterns of consumers' continuous purchase intention toward the SBKPPs.

This study contributes to the knowledge payment literature by investigating consumers' continuous purchase intention toward the SBKPPs. This study also provides practical enlightenment for the SBKPPs' marketing.

This study aims to investigate the effect of post-treatment on anti-corrosion performance of Al coating on the surface of Ti-6Al-4V (TC4) fastener.

The Al coatings with different layer structures were prepared on TC4 by middle-frequency and direct-current combined magnetron sputtering. The cross-sectional morphology and surface roughness of coatings were characterized by scanning electron microscope and atomic force microscope. The corrosion resistance was evaluated by electrochemical method. The monolayer coating was post-treated by Alodine chemical conversion, Ar⁺ bombardment and a combination of two methods above.

The results show that the interfaces in bilayer and trilayer coatings reduce the defects. Ar⁺ bombardment reduces the corrosion current density, and Alodine chemical conversion leads to a higher pitting corrosion potential. The combined post-treatment has the highest polarization resistance.

The corrosion resistance of the Al coating is enhanced as the layer quantity increases. The combination of two post-treatments, Ar⁺ bombardment and Alodine chemical conversion, could achieve an overall improvement in corrosion resistance of Al coating.

The type 120 emergency valve is an essential braking component of railway freight trains, but corresponding diaphragms consisting of natural rubber (NR) and chloroprene rubber (CR) exhibit insufficient aging resistance and low-temperature resistance, respectively. In order to develop type 120 emergency valve rubber diaphragms with long-life and high-performance, low-temperatureresistant CR and NR were processed.

The physical properties of the low-temperature-resistant CR and NR were tested by low-temperature stretching, dynamic mechanical analysis, differential scanning calorimetry and thermogravimetric analysis. Single-valve and single-vehicle tests of type 120 emergency valves were carried out for emergency diaphragms consisting of NR and CR.

The low-temperature-resistant CR and NR exhibited excellent physical properties. The elasticity and low-temperature resistance of NR were superior to those of CR, whereas the mechanical properties of the two rubbers were similar in the temperature range of 0 °C–150 °C. The NR and CR emergency diaphragms met the requirements of the single-valve test. In the low-temperature single-vehicle test, only the low-temperature sensitivity test of the NR emergency diaphragm met the requirements.

The innovation of this study is that it provides valuable data and experience for future development of type 120 valve rubber diaphragms.

Recognizing every worker's working status instead of only describing the existing construction activities in static images or videos as most computer vision-based approaches do; identifying workers and their activities simultaneously; establishing a connection between workers and their behaviors.

Taking a reinforcement processing area as a research case, a new method for recognizing each different worker's activity through the position relationship of objects detected by Faster R-CNN is proposed. Firstly, based on four workers and four kinds of high-frequency activities, a Faster R-CNN model is trained. Then, by inputting the video into the model, with the coordinate of the boxes at each moment, the status of each worker can be judged.

The Faster R-CNN detector shows a satisfying performance with an mAP of 0.9654; with the detected boxes, a connection between the workers and activities is established; Through this connection, the average accuracy of activity recognition reached 0.92; with the proposed method, the labor consumption of each worker can be viewed more intuitively on the visualization graphics.

With this proposed method, the visualization graphics generated will help managers to evaluate the labor consumption of each worker more intuitively. Furthermore, human resources can be allocated more efficiently according to the information obtained. It is especially suitable for some small construction scenarios, in which the recognition model can work for a long time after it is established. This is potentially beneficial for the healthy operation of the entire project, and can also have a positive indirect impact on structural health and safety.