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Despite the fact that user participation (UP) has been highlighted as an important aspect in innovation, previous findings on its relationship with service innovation performance (SIP) are inconsistent. This study aims to investigate the relationships among UP, knowledge management capability (KMC) and SIP, especially in the digital age, inspired by the theories of knowledge-based and absorptive capacity.

Based on a sample of 252 Chinese e-commerce enterprises, this study adopts a hierarchical regression analysis and bootstrap method to test the theoretical framework and research hypotheses.

UP and KMC have positive effects on SIP, respectively. KMC plays a mediating role in the effect of UP on SIP. Furthermore, the intermediary role of KMC varies in different sub-paths between UP and SIP.

First, this study provides some explanations for inconsistent arguments on the relationship between UP and service innovation. Second, with the consideration of specific dimensions of UP and SIP, the mediation role of KMC varies in different sub-paths has been recognized, which provides a deeper understanding of the relationship between UP and SIP. Third, this study opens the discussion about how to realize SIP more effectively in the digital age, advancing theoretical and practical developments on service innovation.

Business model innovation (BMI) is an important channel of enterprise innovation, and BMI's antecedents have attracted extensive attention. The purpose of this paper is to address a substantial gap in the extant literature by developing a moderate model to explain the effects of boundary-spanning search on BMI as well as whether and how innovative cognitive imprinting (ICI) and environmental dynamics (ED) affect the above relationship.

A total of 239 usable questionnaires from different enterprises in China were collected to obtain firm-level data. Then multiple regression analyses were used by SPSS software to test hypotheses.

Boundary-spanning search extensity (BSE) and focus have inverted U-shaped impacts on BMI; ICI moderates the relationship between boundary-spanning search and BMI and steepens the curves; ED weakens the moderating role of ICI.

By identifying two antecedents of BMI, this paper contributes to the literature on the antecedents of BMI. Meanwhile, the joint moderating effect of ICI and ED is introduced into the emergent analysis framework of the relationship between boundary-spanning search and BMI and examined through empirical analysis for the first time.

The purpose of this paper is to demonstrate visually the knowledge structure and evolution of disruptive innovation. The paper used CiteSpace III to analyze 1,570 disruptive innovation records from the Web of Science database between 1997 and 2016.

Initially, this paper offers a comprehensive overview of papers, countries, journals, scholars and application areas. Subsequently, a time zone view of high-frequency keywords is presented, emphasizing the course of evolution of the study hotspots. Finally, a visualization map of cited references and co-citation analysis are provided to detect the knowledge base at the forefront of disruptive innovation.

The findings are as follows: the number of papers shows exponential growth. The USA has the largest contribution and the strongest center. The Netherlands shows the largest burst, followed by Japan. Journal of Production Innovation Management and Research Policy is the most important journals. Hang CC has the largest number of articles. Walsh ST is identified as a high-yielding scholar. Christensen CM is the most authoritative scholar. Engineering electrical electronic is the most widely used research category, followed by management and business. The evolutionary course of the study hotspots is divided into five stages, namely, start, burst, aggregation, dispersion and not yet formed. Eight key streams in the literature are extracted to summarize the knowledge base at the forefront of disruptive innovation.

This paper explores the whole picture of disruptive innovation research and demonstrates a visual knowledge structure and the evolution of disruptive innovation. It provides an important reference for scholars to capture the current situation and influential trends in this field.

Recent years have witnessed the rapid development of massive open online courses (MOOCs). With more and more courses being produced by instructors and being participated by learners all over the world, unprecedented massive educational resources are aggregated. The educational resources include videos, subtitles, lecture notes, quizzes, etc., on the teaching side, and forum contents, Wiki, log of learning behavior, log of homework, etc., on the learning side. However, the data are both unstructured and diverse. To facilitate knowledge management and mining on MOOCs, extracting keywords from the resources is important. This paper aims to adapt the state-of-the-art techniques to MOOC settings and evaluate the effectiveness on real data. In terms of practice, this paper also tries to answer the questions for the first time that to what extend can the MOOC resources support keyword extraction models, and how many human efforts are required to make the models work well.

Based on which side generates the data, i.e instructors or learners, the data are classified to teaching resources and learning resources, respectively. The approach used on teaching resources is based on machine learning models with labels, while the approach used on learning resources is based on graph model without labels.

From the teaching resources, the methods used by the authors can accurately extract keywords with only 10 per cent labeled data. The authors find a characteristic of the data that the resources of various forms, e.g. subtitles and PPTs, should be separately considered because they have the different model ability. From the learning resources, the keywords extracted from MOOC forums are not as domain-specific as those extracted from teaching resources, but they can reflect the topics which are lively discussed in forums. Then instructors can get feedback from the indication. The authors implement two applications with the extracted keywords: generating concept map and generating learning path. The visual demos show they have the potential to improve learning efficiency when they are integrated into a real MOOC platform.

Conducting keyword extraction on MOOC resources is quite difficult because teaching resources are hard to be obtained due to copyrights. Also, getting labeled data is tough because usually expertise of the corresponding domain is required.

The experiment results support that MOOC resources are good enough for building models of keyword extraction, and an acceptable balance between human efforts and model accuracy can be achieved.

This paper presents a pioneer study on keyword extraction on MOOC resources and obtains some new findings.

Since the multi-component of powder metallurgy was dispersed, and each component sheared flow and tiered under the action of friction force, it was difficult to disclose the evolution characteristics of each component. Meanwhile, third body mixing with particles of each component covered on the friction surface, which further increased the difficulty of understanding evolution of each component and the corresponding third body in the friction process. To solve this problem, this paper aims to propose a mechanical assembled method which compact several component sheets in order.

Pure copper, aluminum and artificial graphite sheets with thickness 0.5, 1 and 2 mm, respectively, were assembled into a jig by mechanical compact method. The relationship between arrangement patterns of the components and its friction coefficient was studied by using fixed speed friction test machine, the speed range from 200 to 2,000 r/min and the pressure range from 0.25 to 0.64 MPa.

The testing results showed that when the distribution of same components was congregated, friction coefficient dropped from 0.6 to 0.4. While the distribution of different components was dispersed, friction coefficient dropped from 0.6 to 0.25. The friction coefficient decline was caused by performances changes of third body fluidity. The sufficiently mixed third body made third body adhesion weaker and increased third body fluidity. That provoked friction coefficient decreasing obviously at high speed. On the contrary, with the high congregation of same components, strong third body adhesion led to a rougher surface which contributed to a higher friction coefficient.

By means of the mechanical-assembled multi-layer components to reveal the influence mechanism of every component on friction properties, will provide a new test approach for tribology.

Examines the fifteenth published year of the ITCRR. Runs the whole gamut of textile innovation, research and testing, some of which investigates hitherto untouched aspects. Subjects discussed include cotton fabric processing, asbestos substitutes, textile adjuncts to cardiovascular surgery, wet textile processes, hand evaluation, nanotechnology, thermoplastic composites, robotic ironing, protective clothing (agricultural and industrial), ecological aspects of fibre properties – to name but a few! There would appear to be no limit to the future potential for textile applications.

The purpose of this study is to present a highly stretchable and flexible strain sensor with simple and low cost of fabrication process and excellent dynamic characteristics, which make it suitable for human motion monitoring under large strain and high frequency.

The strain sensor was fabricated using the rubber/latex polymer as elastic carrier and single-walled carbon nanotubes (SWCNTs)/carbon black (CB) as a synergistic conductive network. The rubber/latex polymer was pre-treated in naphtha and then soaked in SWCNTs/CB/silicon rubber composite solution. The strain sensing and other performance of the sensor were measured and human motion tracking applications were tried.

These strain sensors based on aforementioned materials display high stretchability (500 per cent), excellent flexibility, fast response (approximately 45 ms), low creep (3.1 per cent at 100 per cent strain), temperature and humidity independence, superior stability and reproducibility during approximately 5,000 stretch/release cycles. Furthermore, the authors used these composites as human motion sensors, effectively monitoring joint motion, indicating that the stretchable strain sensor based on the rubber/latex polymer and the synergetic effects of mixed SWCNTs and CB could have promising applications in flexible and wearable devices for human motion tracking.

This paper presents a low-cost and a new type of strain sensor with excellent performance that can open up new fields of applications in flexible, stretchable and wearable electronics, especially in human motion tracking applications where very large strain should be accommodated by the strain sensor.

A project manager’s (PM) emotional intelligence (EI) is essential for project performance (PP). However, the cause and effect and the potential moderators of the relationship between EI and PP remain disputed. Some scholars found a positive association between PMs’ EI and project outcomes, while some other studies showed non or negative relation. This paper aims to find the relationship between PMs’ EI and PP and the factors that influence this relationship based on diverse prior research.

This paper conducts a meta-analysis of 5,229 observations based on 24 independent studies from 1990 to 2021.

Results show that PMs’ EI has a significant positive influence on PP, and the project complexity and measurement of PP are two critical moderators explaining inconsistencies in existing research.

The current study proposes suggestions for construction companies on PMs’ selection and training. This study also offers suggestions for PMs in management practice.

To the best of the authors’ knowledge, this study is the first to explore the inconsistencies in prior research results on the relationship between PMs’ EI and PP at the meta-analytic level. This research extends the current literature by revealing the factors leading to existing consistencies that are not explored before. This study implies that the meta-analysis method could help reach a balanced conclusion based on inconsistent results.

With the rapid development of social media in the past few years, some dark aspects of usage have appeared, e.g., Weibo addiction. Therefore, the purpose of this paper is to address the question of how Weibo keeps users hooked.

The study utilizes the netnography method to explore the symptoms of Weibo addiction and how it is formed.

First, some Weibo users have typical symptoms of addictive behavior, such as withdrawal, loss of control and general living problems; second, narcissism plays an important role in the process of Weibo addiction and has a stronger effect on content generation than content consumption; third, some users use Weibo as a means to alleviate anxiety, but they can then become more anxious owing to addiction; and fourth, the effect of comments has two sides – on the one hand, comments are one kind of feedback to posts, satisfying posters’ social needs, while on the other hand, a storytelling system consists of one post and its comments, upon which some Weibo users become more dependent.

This research is only a preliminary, exploratory study. Therefore, care should be taken when interpreting these findings.

This study should help social media service providers and users to pay attention to the risk of social media addiction. Social media service providers should take social responsibility, design more user-oriented guidelines for marketing ethics and launch more responsible marketing activities. Users should enhance self-control and better balance social media use and offline real life.

Netnography has not been widely used as an addictive behavior research technique. This study is further bolstered because it has also noticed the difference of addiction mechanisms between addictive micro-bloggers and their followers.

This paper seeks to discuss the genealogical sources for Chinese immigrants as well as the settlement of Chinese in the USA and the historical evolution of Chinese names, their origins, arrangement and development. It aims to cover the origins of various classes of Chinese surnames, followed by the content description of a traditional genealogical book for jiapu.

The paper researches the various ways that a Chinese person can find out about their ancestry.

The paper reveals the roles of libraries, including serving the needs of patrons interested in genealogical research, preserving and interpreting information through oral and family history projects and collaborating with other libraries through interlibrary loan, document delivery, library consortia, collection management and international resource‐sharing.

The study provides information on where and how to locate the genealogical resources for researching the genealogy of a Chinese family.

The paper analyzes the value of genealogical research as a documentary source for population history, life expectancy in a clan, marriages and family connections, as well as lineage organizations and inter‐lineage relations.