PurposeThe purpose of this paper is to identify the measures employed in the provision of patron services in Chinese academic libraries responding to the COVID-19 pandemic, noting the challenges and issues inherent in providing substantial services while undergoing a public health emergency.Design/methodology/approachThis paper uses an analytical survey study of 137 Chinese academic libraries using data collected through a combination of website investigation, social media access and direct correspondences.FindingsOver 94% of Chinese academic libraries released COVID-19-related information through their websites; the majority switched their service focus to partly or solely remotely online, including remote access, free electronic resources, virtual references reachable 24/7 and research support services deliverable online; services of print materials were altered to e-books for conveniences.Research limitations/implicationsIt should be noted that the survey was conducted from February 12 to April 5, 2020; because of the rapid updates to the library's website and social media channels, the status of their patron services are in the process of dynamic changes and that there should be many libraries that have adopted some patron service methods, but this study is difficult to cover comprehensively. In addition, patron services carried out offline by the surveyed libraries but not disclosed on the online platform could not be analyzed in a way that would be consistent with the data provided by the survey.Originality/valueBy providing evidence of the current status of patron services in Chinese academic libraries during the COVID-19 pandemic, this study helps fulfill the scant empirical attention given to the impact of nationwide public health crises on academic libraries and offers new data of the best practices that help library administrators enhance the impact, efficiency and value of library services to their target community users.

Purpose -This paper aims to explore the status and construction pattern of Web 2.0 technologies employed in top Chinese university libraries, their functionalities and features. Design/methodology/approach -A combination of online survey and content analysis methodology is applied to a sample of 38 top Chinese university libraries' web sites. The Web 2.0 tools are categorized by generally accepted standards with some adjustment for library practices. Data were collected by accessing these university library web sites on two separate occasions during the period of February 10-20, 2009 by utilizing a checklist of 52 questions. Findings -More than two-thirds of the 38 top Chinese university libraries apply one or more kinds of Web 2.0 tools through the basic functions of their web sites. Among six types of tools, Catalog 2.0 and RSS are the most common, while IM, Blog, SNS and Wiki are less frequent. Research limitations/implications -Internal applications that are not publicly accessible contain hidden information that may not be gathered through content analysis since these links usually cannot be found on library web sites. It is difficult to get exact information as to the applications of Web 2.0 in these libraries without an interview method in combination to observation. Originality/value -This study provides an overall picture of Web 2.0 tools developed in top Chinese university libraries, allowing for future evaluation and planning. The implementation of Web 2.0 applications and their constructing pattern is not only indicative of the development of the Chinese digital libraries, but also to their development of digital libraries in the world at large.

Purpose – This paper aims to explore Web 2.0 technologies usage and trends in the top 100 US academic libraries as exemplified through the academic library websites. Design/methodology/approach – The top 100 universities were selected from the US News & World Report's (USNWR) 2013 ranked list's top 100 of the best colleges in the USA. Content analysis was used in terms of quantitative approach. A checklist was developed as the main research instrument based on other checklists and questionnaires. Each of the selected university library websites was visited within a period of two weeks to explore implementation and usage of web tools, including SNS, blog, RSS, wikis, podcast/vodcast, and social bookmarking/tagging. Findings – All 100 academic libraries had a social media presence on Facebook and Twitter, making SNS the most widely applied Web 2.0 tool. The wiki was the least applied Web 2.0 technology, with a 34 percent participation rate. Blog was the second most popular tool with a 99 percent participation rate, followed by RSS and IM/Chat with 97 percent and 91 percent respectively. The vodcast and podcast had 47 percent and 46 percent participation rates respectively, while social bookmarking/tagging were also used by 39 percent of the academic libraries. Research limitations/implications – This study is completely based on publicly available data regarding usage of Web 2.0 applications. Web 2.0 tools used on library intranets were not analyzed for this study. Outcomes suggest that academic libraries are increasingly using Web 2.0 applications to promote themselves, enhance library services, and highlight resources to patrons. Originality/value – This is the first research that draws an overall picture of the usage and trends of Web 2.0 applications in the top 100 US academic libraries. This study demonstrates some noticeable patterns regarding usage, trends, and adoption which are relevant to how Web 2.0 applications are perceived and used within academic libraries. The study provides academic libraries with helpful information to better meet their user needs by effectively applying Web 2.0. Additionally, library managers, librarians and other libraries may also find this research beneficial as they plan to deploy Web 2.0.

Abstract:The forecasting of energy consumption in China is a key requirement for achieving national energy security and energy planning. In this study, multi-variable linear regression (MLR) and support vector regression (SVR) were utilized with a gated recurrent unit (GRU) artificial neural network of Chinese energy to establish a forecasting model. The derived model was validated through four economic variables; the gross domestic product (GDP), population, imports, and exports. The performance of various forecasting models was assessed via MAPE and RMSE, and three scenarios were configured based on different sources of variable data. In predicting Chinese energy consumption from 2015 to 2021, results from the established GRU model of the highest predictive accuracy showed that Chinese energy consumption would be likely to fluctuate from 2954.04 Mtoe to 5618.67 Mtoe in 2021.