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The purpose of this paper is to conduct performance evaluation of eight main scientific data sharing platforms in China and find existing problems, thus providing reference for maximizing the value of scientific data and enhancing scientific research efficiency.

First, the authors built an evaluation indicator system for the performance of scientific data sharing platforms. Next, the analytic hierarchy process was employed to set indicator weights. Then, the authors use experts grading method to give scored for each indicator and calculated the scoring results of the scientific data sharing platform performance evaluation. Finally, an analysis of the results was conducted.

The performance evaluation of eight platforms is arranged by descending order by the value of F: the Data Sharing Infrastructure of Earth System Science (76.962), the Basic Science Data Sharing Center (76.595), the National Scientific Data Sharing Platform for Population and Health (71.577), the China Earthquake Data Center (66.296), the China Meteorological Data Sharing Service System (65.159), the National Agricultural Scientific Data Sharing Center (55.068), the Chinese Forestry Science Data Center (56.894) and the National Scientific Data Sharing & Service Network on Material Environmental Corrosion (Aging) (52.528). And some existing shortcomings such as the relevant policies and regulation, standards of data description and organization, data availability and the services should be improved.

This paper is mainly discussing about the performance evaluation system covering operation management, data resource, platform function, service efficiency and influence of eight scientific data sharing centers and made comparative analysis. It reflected the reality development of scientific data sharing in China.

Under the new technological environment, academic libraries meet an extremely intense competition in offering information services, and marketing becomes an important means to attain the goal of their sustainable development. The purpose of this paper is to get an overview of library marketing in Chinese “985” Project Universities, the authors undertook a survey on each library of “985” Project Universities released on the web site of Ministry of Education of the People’s Republic of China. And then the authors identified some successful practices based on the survey.

First, the content of each web site, along with the individual hyperlinks and categories that every library web site has, were browsed to check the availability of the categories. Second, the search function of each library was explored using terms like “blog,” “video” and “tutorial” to retrieve information about services. Third, the Google search engine was used to retrieve information from Renren, microblog and YouTube accounts combining with the name of each library. And then the authors consult reference librarians about marketing methods and tools applied in their libraries with real-time online reference services.

This paper suggests that 29 libraries are exploiting video marketing, which is the most widely used marketing methods, accounting for 74.36 percent. Mobile library marketing and microblog marketing are another two major application among the 39 “985” Project Universities libraries in China, respectively, accounting for 69.23 and 58.97 percent.

The paper reveals that there are some deficiencies lying in the marketing of these libraries: characteristic resources in really simple syndication (RSS) are insufficient, video themes turn to be traditional and plain, network media marketing is relatively uncommon, and mobile library marketing is limited to mobile messaging services. It may fill in the gap of better understanding the relationship between the traditional information services and modern services from users’ perspective. It is instructive for libraries to systematically summarize success or failure experience of other library marketing, and keep an innovative concept and global vision.

This paper aims to find the current situation of research data services by academic libraries and summarize some strategies for university libraries to reference. Recent years have seen an increasing number of university libraries extended their traditional roles and provided research data services.

This paper selected 87 libraries of the top 100 universities listed in the World’s Best Universities released by the USA News in October 2012 as samples and conducted a Web site investigation to check if there were any research data services provided. In addition, it made an interview with the Wuhan University Library’s Research Data Service Workgroup to understand the procedure, difficulties and experiences of their research data service. Based on the survey and interview, it analyzed the current status and difficulties of research data services in university libraries and proposed some strategies for others to reference.

Of the 87 university libraries investigated, 50 libraries have offered research data services. Most of the services can be divided into six aspects: research data introduction, data management guideline, data curation and storage service, data management training, data management reference and resource recommendation. Among these services, research data introduction is the most frequently provided (47.13 per cent), followed by data curation and storage services (43.68 per cent), data management guideline (42.53 per cent), data management reference (41.38 per cent), resource recommendation (41.38 per cent) and data management training (24.14 per cent). The difficulties met by research data service of Chinese academic libraries are also concluded.

Through Web site investigation and interview with the Wuhan University Library’s Research Data Service, this paper presented an overall picture of research data services in university libraries and identified the difficulties and experiences of research data services of the Wuhan University Library. Based on some successful examples, it put forward some strategies for university libraries to reference. This study is very useful for academic libraries to promote their research data services.

Since the outbreak of COVID-19, tremendous changes have taken place in the US economy – the economic growth in the whole year of 2020 was negative, and though it enjoyed a significant rebound for the first half of 2021, the growth rate began to decline rapidly by the third quarter, and inflation suddenly rises rapidly, which after came the all-time highs of the “misery index” consisted of the inflation rate and unemployment rate. All signs indicate that the US economy will likely enter a “stagflation” crisis.

This paper analyzes the institutional and social contradictions in the United States during the neoliberal era from the perspectives of domestic social structure of accumulation (SSA) and international SSA based on the SSA theory.

The current risk of stagflation in the US economy is a concentrated outbreak of the long-term accumulated contradictions in neoliberal SSA under the impact of the epidemic, which is the product of the irreconcilable contradictions inherent in the capitalist mode of production.

Based on this analysis, the paper points out that with the deepening of the crisis, the neoliberal SSA is likely to end and a new SSA will be established gradually.

3D printing has been warmly welcomed by clothing enterprises for its customization capacity in recent years. However, such clothing enterprises have to face the digital transformation challenges brought by 3D printing. Since the business model is a competitive weapon for modern enterprises, there is a research gap between business model innovation and digital transformation challenges for 3D-printing garment enterprises. The aim of the paper is to innovate a new business model for 3D-printing garment enterprises in digital transformation.

A business model innovation canvas (BMIC), a new method for business model innovation, is used to innovate a new 3D-printing clothing enterprises business model in the context of digital transformation. The business model canvas (BMC) method is adopted to illustrate the new business model. The business model ecosystem is used to design the operating architecture and mechanism of the new business model.

First, 3D-printing clothing enterprises are facing digital transformation, and they urgently need to innovate new business models. Second, mass customization and distributed manufacturing are important ways of solving the business model problems faced by 3D-printing clothing enterprises in the process of digital transformation. Third, BMIC has proven to be an effective tool for business model innovation.

The new mass deep customization-distributed manufacturing (MDC-DM) business model is universal. As such, it can provide an important theoretical reference for other scholars to study similar problems. The digital transformation background is taken into account in the process of business model innovation. Therefore, this is the first hybrid research that has been focused on 3D printing, garment enterprises, digital transformation and business model innovation. On the other hand, business model innovation is a type of exploratory research, which means that the MDC-DM business model’s application effect cannot be immediately observed and requires further verification in the future.

The new business model MDC-DM is not only applicable to 3D-printing garment enterprises but also to some other enterprises that are either using or will use 3D printing to enhance their core competitiveness.

A new business model, MDC-DM, is created through BMIC, which allows 3D-printing garment enterprises to meet the challenges of digital transformation. In addition, the original canvas of the MDC-DM business model is designed using BMC. Moreover, the ecosystem of the MDC-DM business model is constructed, and its operation mechanisms are comprehensively designed.