Search results

The COVID-19 has become a global pandemic, which has caused large number of deaths and huge economic losses. These losses are not only caused by the virus but also by the related rumors. Nowadays, online social media are quite popular, where billions of people express their opinions and propagate information. Rumors about COVID-19 posted on online social media usually spread rapidly; it is hard to analyze and detect rumors only by artificial processing. The purpose of this paper is to propose a novel model called the Topic-Comment-based Rumor Detection model (TopCom) to detect rumors as soon as possible.

The authors conducted COVID-19 rumor detection from Sina Weibo, one of the most widely used Chinese online social media. The authors constructed a dataset about COVID-19 from January 1 to June 30, 2020 with a web crawler, including both rumor and non-rumors. The rumor detection task is regarded as a binary classification problem. The proposed TopCom model exploits the topical memory networks to fuse latent topic information with original microblogs, which solves the sparsity problems brought by short-text microblogs. In addition, TopCom fuses comments with corresponding microblogs to further improve the performance.

Experimental results on a publicly available dataset and the proposed COVID dataset have shown superiority and efficiency compared with baselines. The authors further randomly selected microblogs posted from July 1–31, 2020 for the case study, which also shows the effectiveness and application prospects for detecting rumors about COVID-19 automatically.

The originality of TopCom lies in the fusion of latent topic information of original microblogs and corresponding comments with DNNs-based models for the COVID-19 rumor detection task, whose value is to help detect rumors automatically in a short time.

Notwithstanding its significance as a form of strategic human capital investment, employee training has not yielded consistent conclusions among scholars regarding its impact on organizational performance. Some studies deem it effective, while others regard it as ineffective. We contend that distinct types of training impact various facets of firm performance.

In this study, we categorize employee training as either exploitative or explorative. Specifically, we examine their impact on two aspects of organizational performance: short-term performance and long-term competence, using a quasi-experimental setting and a difference-in-differences (DID) method.

We find that exploitative training is more effective in improving firms’ short-term performance (e.g. firms’ sales revenue), while explorative training is more effective in enhancing firms’ long-term competence (e.g. firms’ innovation output).

The findings of this study illuminate concrete benefits of training for practitioners, suggesting that firms can strategically select employee training category to maximize returns on their investment in strategic human capital based on their strategic orientations.

The purpose of this paper is to examine the financing and provision of basic public services in China. The main issue addressed is how to reform the public finance system to achieve quality and fairness in the provision of basic public services.

Based on an historical analysis of the functional transformation of the public finance system in China and on an empirical analysis of the current public finance system and the public service provision system, a comprehensive understanding was gained about the relationship between the financing and provision of basic public services.

The paper argues that there is a close relationship between the provision of basic public services and the functional changes made to the public finance system. Based on a systematic retrospective study of the Chinese Government’s efforts to improve basic public services over the last three decades, this paper offers policy suggestions on further public finance restructuring that would support better service provision.

By analyzing issues in the public service provision system, this paper contributes to the debate about the efficiency improvement made to governmental functions in China.

Driven by the growing pressure to justify the contributions of marketing activities, marketers have shown considerable interest in improving their marketing performance measurement systems (MPMSs). The purpose of this study is to examine the neglected mediating effect of marketing capabilities on the MPMS–firm performance relationship and to focus on specific aspects of MPMSs that have been largely omitted in the prior research, namely, the comprehensiveness and uses of MPMSs.

A survey was conducted with marketing and senior managers from 210 Irish-based companies. The proposed research model was tested by using the SPSS Process macro and structural equation modeling in AMOS 24.

The three characteristics of MPMSs influence firm performance in different manners: while the diagnostic use of MPMSs hinders the development of market-linking capability and thus negatively influences firm performance; the comprehensiveness of MPMSs positively influences firm performance through its impact on architectural marketing capability; and the interactive use of MPMSs via externally focused learning and market-linking capabilities.

Although this study used objective firm performance data to validate subjective data, the use of single-informant and self-reported measures may still be a concern, as the strong relationships between variables may be because of single-informant bias.

This study provides insights into how companies can use a comprehensive MPMS to cultivate specific crucial marketing capabilities and thereby enhance firm performance.

This study contributes to the marketing performance measurement literature by proposing and empirically validating the mediating effect of marketing capabilities on the MPMS–firm performance relationship.

The purpose of this paper is to analyze the influencing factors of patients’ financial burden through a case study of hospital on public‒private partnerships (PPP) model (Chaonan Minsheng Hospital of Guangdong Province) and provide some useful information to policymakers for better development of hospitals on PPP model.

There are total six indicators that are defined as patients’ financial burden, basing on the policy of “indicators of medical quality management and control on the third level large general hospital (2011 edition),” issued by Chinese Government. In total, 23 potentially influencing factors of patients’ financial burden for hospital on PPP model were chosen from the above policy. The five-year (2007‒2011) data for the above 29 indicators come from statistic department of hospital on PPP model. Grey relational analysis (GRA) was applied to analyze the influencing factors of patients’ financial burden for hospital on PPP model.

A clear rank of influencing factors of patients’ financial burden is obtained and suggestions are provided from results of GRA, which provide reference for policymakers of hospital on PPP model. The five main influencing factors of patients’ financial burden for hospital on PPP model, in sequence, are rescuing critical ill patients on emergency, rescuing critical ill inpatients, inpatient bed occupancy rate, working days per bed and medical building area.

The study on the influencing factors of patients’ financial burden for hospital on PPP model not only provides decision-making for policymaker of hospital and controlling of medical expenditure but also contributes to release patients’ financial burden for hospitals on PPP model.

Team leaders play a vital role in achieving superior team performance. However, their role in implementing the organizational customer orientation strategy is not well understood. Drawing on social exchange theory, this study investigates how team leader customer orientation affects team customer orientation climate and team performance (i.e. customer satisfaction) as well as the moderating role of transformational leadership in such effect.

This study builds on survey data collected from matched team leaders, employees and customers nested in 81 service teams and employs hierarchical multiple regression analysis to test the hypotheses.

The findings indicate that team leader customer orientation increases team customer orientation climate, which leads to a higher level of customer satisfaction. Leaders' transformational leadership moderates the link between a leader customer orientation and team customer orientation climate in an unexpected way. When a team leader is transformational, the team customer orientation climate is enhanced, regardless of the level of team leader customer orientation. When a team leader's transformational leadership is low, the higher leader customer orientation is and the higher team customer orientation climate is.

This study contributes to the customer orientation, transformational leadership and service literature by unraveling team leaders' roles in boosting team customer orientation climate and team effectiveness.

The purpose of this paper is to evaluate resource configuration and service ability in hospital on public private partnership (PPP) model (Chaonan Minsheng Hospital of Guangdong Province), supplying decision-making reference for participants of hospital on PPP model.

Four model of grey relational analysis (GRA) (Deng's correlation degree, grey absolute correlation degree, grey relative correlation degree and grey comprehensive correlation degree) are applied to evaluate resource configuration and service ability, a total of 11 indicators of hospital on PPP model public hospital and private hospital from 2007 to 2011.

The paper finds that different GRA models have different results when the paper applied them to evaluate resource configuration and service ability in hospital on PPP model. More than 60 per cent indicators of resource configuration (total six indicators) and service ability (total six indicators) are assessed as “hospital on PPP model ≻ public hospital” or “hospital on PPP model≻ private hospital” from three models of Deng's correlation degree, grey absolute correlation degree and grey comprehensive correlation degree.

Evaluation of resource configuration and service ability for hospital on PPP model with GRA makes results quantified objective and provides reference for decision making and management. GRA makes the comparison of resource configuration and service ability between hospital on PPP model and other model hospitals becoming possible.

The shortcoming for data analysis method of “large sample” is overcome and data analysis method of “small sample” is realized by using GRA, which broaden the method of evaluating hospital on PPP model.

Distribution network protection is a complicated problem and mal-operation of the protective relays due to false settings make the operation of the network unreliable. Besides, obtaining proper settings could be very complicated. This paper aims to discuss an innovative evolutionary Lightning Flash Algorithm (LFA) which is developed for solving the relay coordination problems in distribution networks. The proposed method is inspired from the movements of cloud to ground lightning strikes in a thunderstorm phenomenon. LFA is applied on three case study systems including ring, interconnected and radial distribution networks. The power flow analysis is performed in Digsilent Power Factory software; then the collected data are sent to MATLAB software for optimization process. The proposed algorithm provides optimum time multiplier setting and plug setting of all digital overcurrent relays in each system. The results are compared with other methods such as particle swarm optimization and genetic algorithm. The result comparisons demonstrate that the proposed LFA can successfully obtain proper relay settings in distribution networks with faster speed of convergence and lower total operation time of relays. Also, it shows the superiority and effectiveness of this method against other algorithms.

A novel LFA is designed based on the movements of cloud to ground lightning strikes in a thunderstorm. This method is used to optimally adjust the time multiplier setting and plug setting of the relays in distribution system to provide a proper coordination scheme.

The proposed algorithm was tested on three case study systems, and the results were compared with other methods. The results confirmed that the proposed method could optimally adjust the relay settings in the electric distribution system to provide a proper protection scheme.

The practical implications can be conducted on distribution networks. The studies provided in this paper approve the practical application of the proposed method in providing proper relay protection in real power system.

This paper proposes a new evolutionary method derived from the movements of cloud to ground lightning strikes in thunderstorm. The proposed method can be used as an optimization toolbox to solve complex optimization problems in practical engineering systems.

This paper proposes an intelligent fault diagnosis method, which aims to obtain the outstanding fault diagnosis results of the gearbox.

An intelligent fault diagnosis method based on energy entropy-weighted complementary ensemble empirical mode decomposition (EWCEEMD) and support vector machine (SVM) optimized by whale optimization algorithm (WOA) is proposed. The raw signal is first denoised by the wavelet noise reduction method. Then, complementary ensemble empirical mode decomposition (CEEMD) is used to generate several intrinsic mode functions (IMFs). Next, energy entropy is used as an indicator to measure the sensibility of the IMF and converted into a weight coefficient by function. After that, IMFs are linearly weighted to form the reconstruction signal, and several features are extracted from the new signal. Finally, the support vector machine optimized by the whale optimization algorithm (WOA-SVM) model is used for gearbox fault classification using feature vectors.

The fault features extracted by this method have a better clustering effect and clear boundaries under each fault mode than the unimproved method. At the same time, the accuracy of fault diagnosis is greatly improved.

In most studies of fault diagnosis, the sensitivity of IMF has not been appreciated. In this paper, energy entropy is chosen to quantify sensitivity. In addition, high classification accuracy can be achieved by applying WOA-SVM as the final classification model, improving the efficiency of fault diagnosis as well.

Family involvement is traditionally conceptualized as the role parents assume in formal early childhood education (ECE) settings, such as preschool. However, family involvement in early learning is not limited to formal, school-like experiences. For many children, much of their early learning occurs with parents, family members, and other informal caregivers within the home and during outings into their local communities. Therefore, finding innovative ways for communities to engage families in their young children’s early learning process is very important. Public libraries are well-established community resources that are recognized by families as reliable institutions with trustworthy information. This chapter suggests that public libraries hold great potential to provide early education experiences that naturally encourage family involvement in early learning. First, we review how public libraries are well positioned to support family involvement in children’s early learning. We also highlight recent library-based efforts to reach families with research-informed learning experiences that support children’s school readiness. A case study of one public library’s partnership with university researchers to deliver library-based interactive parent-child programming is presented. Finally, we address national efforts to include public libraries within statewide early childhood comprehensive systems and important considerations for building upon the potential of public libraries to support families with young children.