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This paper aims to answer following three important but not well-answered or unanswered questions in the extant trust literatures: What is the true magnitude that trust impacts on performance? Is there any consistency among the effects of trust on performance at different levels? How does vertical distance affect the trust-performance relationship?

It captures the law between trust and performance at different levels by conducting a meta-analytic examination consisting of 238 independent empirical studies, 586 effect sizes and 110,576 independent samples.

It makes a periodic conclusion that trust significantly promotes performance. Specifically, trust not only has stronger positive correlation with team performance than individual and organizational performance inside organization, but also strongly facilitates organizational performance between organizations. Moreover, consistency exits in the effects of trust on performance at different levels. On one hand, trust has stronger positive correlation with performance of contextual type than performance of innovative type than performance of task type at different levels. On the other hand, promotion effect of trust on performance strengthens when the vertical distance between trustors and trustees diminishes. Additionally, three potential moderators including publication status, measurement tool and common method variance moderate the focused relation, but moderating effect is not thorough for regional culture. Moderating directions of the above four potential moderators are highly consistent.

This paper answers the three important but not well-answered or unanswered questions.

The purpose of this paper is to demonstrate the feasibility of using shape memory polymer (SMP) for developing vascular stent. In particular, the expansion performance is analyzed through extensive modeling and simulation.

Firstly, the authors construct the model geometry and propose a constitutive model to describe the deformation of the stent due to the expansion process. The authors then simulate the expansion process under varying conditions, including different heating rates and recovery temperatures. Finally, the authors analyze the radial strength of the SMP stent.

A less invasive and stable expansion performance of the SMP stent is confirmed by the simulation method. A fitting function of the expansion process is proposed based on the characteristics of the SMP.

The effects of dynamic blood flow on the SMP stent is ignored. A fluid-structure interaction analysis may need to be considered to give a more accurate description of the behaviour of the SMP stent.

The findings will provide guidance for the rational design and application of SMP stents.

The work will provide guidance for the new generation stent design.

This is the first time that the expansion performance of a SMP stent has been analyzed both qualitatively and quantitatively through modelling and simulation.

The existing research does not systematically explore customers' option about different payment methods, nor does it analyze how shopping channels and shopping scale affect customers' option about different payment methods. Furthermore, there is a lack of exploration on what the relationship is, and how they are adjusted by customer purchasing experience. The authors’ research questions are: (1) when using different shopping channels in online retailing, whether customers will choose different types of payment methods? (2) Does the purchase amounts affect customers' choice of different payment methods?

This study takes 60,484 customers from JD.com, one of the largest B2C platforms in China, as the research object and collects the purchase data of these customers from October 01, 2012 to December 31, 2013, and analyzes them through panel data models.

Based on their purchase data, the authors find the main results by using panel data model that (1) the use of mobile channel has a positive effect on cash on delivery (COD), implying that when consumers use mobile to purchase, they have a higher possibility to use COD, (2) the order size has a positive effects on COD, that is to say, when the purchase amount increases, the possibility of using COD also increases. (3) Furthermore, when consumers' purchase experience abound, mobile channel's positive effect on COD will be decreased, but it does not affect the positive effect between order size and COD.

From the aspects of shopping channels, product attributes and customer purchase experience, it fills the gaps in the research on the preselection of payment methods and makes research of payment methods a complete research system. Secondly, this study adds COD to the options of payment method selection. Finally, the moderating effect of customer shopping experience from a dynamic perspective elaborates that customers can learn from multiple purchases and overcome the shopping risks brought by shopping channels, thereby reducing the probability of choosing a COD method.

The purpose of this study is to explore what is synergistic innovation in the logistics service outsourcing context and how this strategy can potentially benefit an organization by improving performance outcomes.

A total of 21 in-depth interviews were conducted to conceptualize the construct of synergistic innovation. In addition, a theory-based model is tested using data collected from 282 Chinese manufacturing firms that are currently engaged in logistics service outsourcing.

The results from the in-depth interviews reveal that synergistic innovation goes beyond just interactions on innovation but requires both parties to achieve synergies that otherwise cannot be achieved by individual party alone. In addition, the empirical analysis suggests that synergistic innovation can help firms improve both logistics service performance and market performance. This process is dynamic as knowledge integration capability influences the outcomes of synergistic innovation.

This study is among the first to conceptualize synergistic innovation. It also offers a practical scale that helps future studies effectively measure this construct. Moreover, the results of this study provide compelling insights into how managers can use logistics service outsourcing as an important source for improving innovation outcomes.

This paper aims to study the characteristics and evolution rules of tagging knowledge network for users with different activity levels in question-and-answer (Q&A) community represented by Zhihu.

A random sample of issue tag data generated by topics in the Zhihu network environment is selected. By defining user quality and selecting the top 20% and bottom 20% of users to focus on, i.e. top users and bot users, the authors apply time slicing for both types of data to construct label knowledge networks, use Q-Q diagrams and ARIMA models to analyze network indicators and introduce the theory and methods of network motif.

This study shows that when the power index of degree distribution is less than or equal to 3.1, the ARIMA model with rank index of label network has a higher fitting degree. With the development of the community, the correlation between tags in the tagging knowledge network is very weak.

It is not comprehensive and sufficient to classify users only according to their activity levels. And traditional statistical analysis is not applicable to large data sets. In the follow-up work, the authors will further explore the characteristics of the network at a larger scale and longer timescale and consider adding more node features, including some edge features. Then, users are statistically classified according to the attributes of nodes and edges to construct complex networks, and algorithms such as machine learning and deep learning are used to calculate large-scale data sets to deeply study the evolution of knowledge networks.

This paper uses the real data of the Zhihu community to divide users according to user activity and combines the theoretical methods of statistical testing, time series and network motifs to carry out the time series evolution of the knowledge network of the Q&A community. And these research methods provide other network problems with some new ideas. Research has found that user activity has a certain impact on the evolution of the tagging network. The tagging network followed by users with high activity level tends to be stable, and the tagging network followed by users with low activity level gradually fluctuates.

Research has found that user activity has a certain impact on the evolution of the tagging network. The tagging network followed by users with high activity level tends to be stable, and the tagging network followed by users with low activity level gradually fluctuates. For the community, understanding the formation mechanism of its network structure and key nodes in the network is conducive to improving the knowledge system of the content, finding user behavior preferences and improving user experience. Future research work will focus on identifying outbreak points from a large number of topics, predicting topical trends and conducting timely public opinion guidance and control.

In terms of data selection, the user quality is defined; the Zhihu tags are divided into two categories for time slicing; and network indicators and network motifs are compared and analyzed. In addition, statistical tests, time series analysis and network modality theory are used to analyze the tags.

The literature review aims to facilitate a broader understanding of on-demand service platform operations management and proposes potential research directions for scholars.

This study searches four databases for relevant literature on on-demand service platform operations management and selects 72 papers for this review. According to the research context, the literature can be divided into research on “a single platform” and research on “multiple platforms”. According to the research methods, the literature can be classified into “Mathematical Models”, “Empirical Studies”, “Multiple Methods” and “Literature Review”. Through comparative analysis, we identify research gaps and propose five future research agendas.

This paper proposes five research agendas for future research on on-demand service platform operations management. First, research can be done to combine classic research problems in the field of operations management with platform characteristics. Second, both the dynamic and steady-state issues of on-demand service platforms can be further explored. Third, research employing mathematical models and empirical analysis simultaneously can be more fruitful. Fourth, more research efforts on the various interactions among two or more platforms can be pursued. Last but not least, it is worthwhile to examine new models and paths that have emerged during the latest development of the platform economy.

Through categorizing the literature into two research contexts as well as classifying it according to four research methods, this article clearly shows the research progresses made so far in on-demand service platform operations management and provides future research directions.

The purpose of this paper is to improve the corrosion resistance of the 6061-Al alloy as the battery pack material for electric vehicles, and the nano-SiC/MAO composite coating was prepared.

The corrosion resistance of coatings was evaluated by the global electrochemical test, and the local electrochemical impedance spectroscopy (LEIS) was used to study the local corrosion mechanism. The laser confocal microscope, scanning electron microscope and X-ray diffractometer (XRD) were used to characterise coatings.

Results showed that the impedance of nano-SiC/MAO coating was 1–2 times higher than MAO coating, and the main corrosion product was Al(OH)₃. LEIS results showed that the impedance of the nano-SiC/MAO coating was two times higher than the MAO coating. The defective SiC/Micro-arc oxidation coating still had high corrosion resistance compared to the MAO coating.

The physical model of the local corrosion mechanism for SiC/MAO composite coating in “cavity-fracture collapse” mode was proposed.

The digitalization of archival management has rapidly developed with the maturation of digital technology. With data's exponential growth, archival resources have transitioned from single modalities, such as text, images, audio and video, to integrated multimodal forms. This paper identifies key trends, gaps and areas of focus in the field. Furthermore, it proposes a theoretical organizational framework based on deep learning to address the challenges of managing archives in the era of big data.

Via a comprehensive systematic literature review, the authors investigate the field of multimodal archive resource organization and the application of deep learning techniques in archive organization. A systematic search and filtering process is conducted to identify relevant articles, which are then summarized, discussed and analyzed to provide a comprehensive understanding of existing literature.

The authors' findings reveal that most research on multimodal archive resources predominantly focuses on aspects related to storage, management and retrieval. Furthermore, the utilization of deep learning techniques in image archive retrieval is increasing, highlighting their potential for enhancing image archive organization practices; however, practical research and implementation remain scarce. The review also underscores gaps in the literature, emphasizing the need for more practical case studies and the application of theoretical concepts in real-world scenarios. In response to these insights, the authors' study proposes an innovative deep learning-based organizational framework. This proposed framework is designed to navigate the complexities inherent in managing multimodal archive resources, representing a significant stride toward more efficient and effective archival practices.

This study comprehensively reviews the existing literature on multimodal archive resources organization. Additionally, a theoretical organizational framework based on deep learning is proposed, offering a novel perspective and solution for further advancements in the field. These insights contribute theoretically and practically, providing valuable knowledge for researchers, practitioners and archivists involved in organizing multimodal archive resources.

Consumers worldwide are increasingly ordering groceries from grocery delivery platforms (GDPs). This study aimed to explore the role of brick-and-mortar (B&M) retailers and GDPs in online grocery shopping (OGS) experience, attitude and continuous purchase intention under the platform model of online grocery retailing.

This study used a mixed method approach. A qualitative analysis was conducted based on 30 in-depth interviews and relevant literature to identify key attributes of the OGS experience. Then, data from 352 online grocery shoppers was used to examine the associations between service attributes, attitude and continuous purchase intention using a structural equation model.

The authors identified six key attributes of the OGS experience related to B&M retailers and GDPs. The quantitative study results showed that customer service, price value and instant delivery significantly impact attitude towards GDPs, while product quality, product assortment, customer service, price value and attitude toward GDPs positively impact online attitude toward B&M retailers. Online attitude toward B&M retailers significantly influences continuous purchase intention.

B&M retailers and GDPs should strengthen cooperation and joint oversight.

This study identified key attributes of the OGS experience associated with B&M retailers and GDPs under the platform model, giving a comprehensive understanding of the relationship between the OGS experience and behavioural intention when B&M retailers collaborate with GDPs.

This study is conducted to determine the factors that affect profitability in Chinese listed companies (by using financial ratios). Four independent variables liquidity, intangible assets, working capital and company leverage were empirically tested for their relationships with profitability besides two control variables which are firm size and company efficiency.

This study used secondary data extracted manually from the annual reports of non-financial Chinese listed companies on the Shanghai stock exchange (http://www.szse.cn/); the data set covers 100 companies during the period of 2017–2019, and a random selection method was used in order to achieve credibility and fairness as much as possible.

The findings show firm size, working capital and intangible assets have positive and significant relationships with profitability [return on assets (ROA) and earnings per share (EPS)]. Positive working capital is important to lower the cost of capital and improve companies' profitability. Intangible assets are also an essential source to improve profitability due to their low costs. In addition, the findings display a negative and strong relationship between liquidity and profitability, meaning that companies suffer low profit due to inefficient use of liquid items. Interestingly, leverage, which is measured by debt ratio and leverage ratio, shows mixed results; debt ratio shows a positive and strong association with ROA but not with EPS; while leverage ratio displays a strong but negative association with ROA but not with EPS. These results confirm the inverted U-shape relationship between leverage and profitability, which depends on the balance between benefit and cost of debt.

Profitability is also important for employees and society where business organization provides sustainability and stability for both of them. Employees can then significantly contribute to achieve higher firm's profitability by efficiently using firm's resources.

This study differs than previous studies in number of aspects: First, this study focuses on financial ratios to explain profitability in Chinese companies. This study provides empirical results about the factors connected to profitability and help stakeholders to make their right decisions. Second, it examines the impact of four independent factors and two control variables that some of them are new in Chinese context such as intangible assets. Third previous studies focus on financial industry such as banks; however, this study focuses on non-financial industry.