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The purpose of this paper is to explore different tagging behaviours between Chinese and Americans by analysing the movie tags, and explore the feasibility of applying cultural differences to tag recommendations.

This paper introduced hypotheses based on several well-established psychological theories and tested them with social tags for the same movies generated by Chinese and Americans. And to prove the utility of the cultural factor consideration, this paper conducted a cross-cultural tag recommendation experiment.

The results show that compared with Americans, Chinese users tend to add more tags about movies’ background information (e.g. release year) and global contextual characteristics (e.g. genre); they also prefer to add tags about production countries and factual tags, and cultural factors can be applied for recommending more accurate tags.

Other reasons for tagging differences beyond cultural factors have not be explored. Tags for some sample movies in MovieLens might be unstable, as they had been tagged by a small scale of users; as a result, the tags’ type distribution might be influenced.

The results and conclusion of this study will be beneficial for the cross-cultural applications of social tags and mining users’ interests based on tags.

This paper provided a deeper investigation of the cross-cultural effect in people’s social tagging behaviours from cognitive perspective, and an empirical analysis has been performed to explore proper approaches of incorporating cultural differences for tag recommendation.

The purpose of this paper is to investigate the mechanical behavior of textile-reinforced concrete (TRC)-strengthened concrete columns with small eccentricity under chloride-wet-dry cycles.

A total of ten reinforced concrete (RC) columns were constructed and subjected to eccentric compression, and the effects of the slenderness ratio, a variable number of wet-dry cycles and the coupled effect of loading and a chloride environment were analyzed. One of the columns tested was unreinforced, whereas the remaining columns were strengthened laterally with TRC.

The results showed that a reduction in the slenderness ratio was conducive to the improvement of the bearing capacity of the reinforced column; however, the reinforcement effect of TRC tended to decrease with an increasing number of wet-dry cycles, and the coupled effect of loading and a chloride environment significantly degraded the compression performance of TRC-strengthened columns, with the damage becoming more serious with increase in the sustained load ratio.

In the next test, the duration of chloride-wet-dry cycles will be extended. In the same time, to obtain a clearer trend, the authors will also increase the number of specimens to obtain more data for drawing general conclusions.

The originality is to explore the feasibility of using cement-based materials (TRC) as a confinement technique in chloride environment. The investigations demonstrate that TRC has a good reinforcement effect on the concrete columns under chloride-wet-dry cycles. Finally, influence of each parameter is analyzed, which can be used as reference and foundation in actual application.

The authors develop a novel forecast combination approach based on the order statistics of individual predictability from panel data forecasts. To this end, the authors define the notion of forecast depth, which provides a ranking among different forecasts based on their normalized forecast errors during the training period. The forecast combination is in the form of a depth-weighted trimmed mean. The authors derive the limiting distribution of the depth-weighted forecast combination, based on which the authors can readily construct prediction intervals. Using this novel forecast combination, the authors predict the national level of new COVID-19 cases in the United States and compare it with other approaches including the ensemble forecast from the Centers for Disease Control and Prevention (CDC). The authors find that the depth-weighted forecast combination yields more accurate and robust predictions compared with other popular forecast combinations and reports much narrower prediction intervals.

Social networking sites (SNSs) have established an important presence in our daily lives and at work. This study explores how public service professionals use SNSs and how they perceive the potential of SNSs. This study further examines the relationship between the use of SNSs and social trust and civic participation. Last, this study identifies the challenges and opportunities facing public administration practitioners who use SNSs to build collaboration and promote public interests. Based on the nationwide survey results, this study provides a broader understanding of SNS use among public service professionals. Furthermore, it also provides management recommendations on how public service professionals can make full use of SNSs to facilitate their interactions with other public service professionals and citizens, and foster collaboration to pursue public interests.

The purpose of this study is to explore the economic impact of financial restatements by major customers on the audit opinion of their suppliers, showing that non-financial information disclosure potentially helps auditors make better assessments.

Using a sample of China’s listed firms from 2007 to 2021, the authors aim to find the relationship between customers’ financial restatements and their suppliers’ audit opinions. Heckman selection model, placebo tests and other robustness checks are used as well.

The findings reveal that customers’ financial restatements have a significant effect on the likelihood of suppliers receiving modified audit opinions. This relationship is pronounced when suppliers face a higher level of financial constraints, exhibit poorer accounting conservatism or receive more negative media coverage. Additionally, this effect occurs through increased business risk and information risk, which heightens auditors’ perceived audit risk. Moreover, the study highlights the influence of switching costs, auditor expertise and restatement severity on this relationship.

Risks originating from customers can spread along the supply chain, emphasizing the necessity for auditors to give heightened attention to both the audited firms and their customer information. Moreover, regulators should carefully consider the important impact of customer information disclosures to maximize the protection of the interests of external information users.

This study not only confirms the crucial role of customer information disclosures in annual reports for stakeholders and auditors but also contributes to the existing literature on customer–supplier relationships.

Interdependency among industries is vital for understanding economic structures and managing industrial portfolios. However, it is hard to precisely model the interconnecting structure among industries. One of the reasons is that the interdependencies show a different pattern in tail events. This paper aims to investigate industry interdependency with the tail events.

General predictive model of Rapach et al. (2016) is extended to an interdependency model via least absolute shrinkage and selection operator quantile regression and network analysis. A dynamic network approach was applied on the Fama–French industry portfolios to study the time-varying interdependencies.

A denser network with heterogeneous central industries is found in tail cases. Significant interdependency varieties across time are shown under dynamic network analysis. Market volatility is identified as an influential factor of industry connectedness as well as clustering tendency under both normal and tail cases. Moreover, combining dynamic network with prediction direction information into out-of-sample industry return forecasting, a lower tail case is obtained, which gives the most accurate prediction of one-month forward returns. Finally, the Sharpe ratio criterion prefers high-centrality portfolios when tail risks are considered.

This study examines the industry portfolio interactions under the framework of network analysis and also takes into consideration tail risks. The combination of economic interpretation and statistical methodology helps in having a clear investigation of industry interdependency. Moreover, a new trading strategy based on network centrality seems profitable in our data sample.

The paper aims to propose a user-centred collaborative framework for providing integrated information services (IIS) to corporate users in China. The framework is conceptualized based on a literature review of IIS models and a case study. The authors provide suggestions with regard to the implementation of effective and efficient information services for corporate users based on the proposed framework.

This paper reviews the efforts of investigating appropriate models for integrated information services (IIS) and proposes a user-centred collaborative framework for providing IIS for corporate users. It is organized as follows: first is an overview through a review of the related literature of the current status of information resource services in China. Then, a case study of IIS in Hubei Province is analysed. Next, a user-centred collaborative IIS framework is presented that aims to address the needs of corporate users. The paper concludes with a summary and suggestions for future study to build effective and efficient IIS systems.

Through an exploratory survey conducted in 2009, it was discovered that, in general, corporate users need all kinds of information, not only scientific publications but also business and market information. Their channel to obtain needed information was mainly the Internet. Books and domain-specific databases were also used by most of the participants. The major challenges for corporate users to obtain needed information included the high cost of purchasing or leasing desired information resources, the low quality of information on the Internet, limited information workers or their skills and the quality of high-level information services.

The survey served as a tool to gather primitive information on user needs. It was an incomplete, unsystematic exploration. However, the authors could still gain some insights on the users’ information needs and directions for future IIS. The results showed that Hubei Science and Technology Information Sharing Service, which was an implementation of the agency collaboration-based IIS model, satisfied the needs of less than 30 per cent of the participants. It has much room for improvement.

This paper proposes a user-centred collaborative integrated information services (UCIIS) framework. The UCIIS framework takes the idea of the user-centred integrated information service (IIS) model that the construction of IIS should start from understanding the users of the services, but it also takes important characteristics from the agency collaboration-based IIS model.

The discussion in this paper is basically on the macro level, leaving a lot of interesting future work to design, develop and evaluate IIS systems based on the proposed framework. Specifically, interest is in developing user models through systematic and comprehensive investigation of corporate information users’ needs, and examining current library and information science curricula to produce qualified information professionals who can carry out user experience studies, and high-level knowledge discovery tasks using various advanced computational technologies.

This study examines the relationship between internal control and corporate environmental responsibility.

Unlike US studies that concentrate solely on internal control over financial reporting, this study uses a comprehensive index that encompasses internal control over financial reporting, operations, and compliance. Corporate environmental responsibility is measured by environmental investments. Our research sample comprises Chinese listed firms from 2010 to 2018.

The results demonstrate a positive correlation between internal control and corporate environmental investments. Furthermore, we find that firms with high-quality internal control can improve their financial and environmental performance through environmental investments. After decomposing internal control into its five components, we show that the control environment, control activities, and information and communication components exhibit stronger effects on environmental investments than the risk assessment and monitoring components. Finally, the cross-sectional analyses reveal that the positive effect of internal control is more pronounced in private firms and in firms that are subject to weaker environmental regulation.

By focusing on the effect of a comprehensive internal mechanism on corporate environmental responsibility in China, this study contributes to the literature in developed-country settings that overwhelmingly focuses on the impact of external stakeholders and regulations.

This paper explores education group school principal’s influence on professional learning community (PLC) development in China.

Qualitative comparative case studies were conducted.

The findings show that principals indicated principal-level factors were their major concerns regarding PLC cultural condition design, school needs were the major concerns in PLCs’ relational and structural design, and educational-group factors impacted principals’ extension of PLCs’ structural conditions.

This article concludes by presenting a “three-context” framework for understanding education group principal’s influence on PLCs in China.

The purpose of this study is to construct a gray relational model based on information diffusion to avoid rank reversal when the available decision information is insufficient, or the decision objects vary.

Considering that the sample dependence of the ideal sequence selection in gray relational decision-making is based on case sampling, which causes the phenomenon of rank reversal, this study designs an ideal point diffusion method based on the development trend and distribution skewness of the sample information. In this method, a gray relational model for sample classification is constructed using a virtual-ideal sequence. Subsequently, an optimization model is established to obtain the criteria weights and classification radius values that minimize the deviation between the comprehensive relational degree of the classification object and the critical value.

The rank-reversal problem in gray relational models could drive decision-makers away from using this method. The results of this study demonstrate that the proposed gray relational model based on information diffusion and virtual-ideal sequencing can effectively avoid rank reversal. The method is applied to classify 31 brownfield redevelopment projects based on available interval gray information. The case analysis verifies the rationality and feasibility of the model.

This study proposes a robust method for ideal point choice when the decision information is limited or dynamic. This method can reduce the influence of ideal sequence changes in gray relational models on decision-making results considerably better than other approaches.