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Objectives The Montreal Cognitive Assessment (MoCA) is an increasingly used screening tool for cognitive impairment. The aim of this study was to examine how MoCA performed in identifying cognitive impairment (CI) domains in SLE patients compared with formal standardized neuropsychological testing (NPT). Factors related to SLE disease, immunologic and psychological state associated with CI were also explored. Methods This cross-sectional study recruited 50 SLE patients without overt neuropsychiatric manifestations from April 2017 to May 2018. The patients were evaluated with MoCA, formal NPT and the Depression, Anxiety, and Stress Scales (DASS) 42-item self-report questionnaire. Values of sensitivity and specificity were computed for different cut-offs of MoCA within each cognitive domain of NPT and descriptive analysis was used to identify the factors affecting cognitive function. Results The median score for MoCA was 27.5 (range 22–30). Using a MoCA cutoff of Conclusion MoCA may be a useful screening tool to identify the most frequently affected cognitive domain which is executive functioning using a lower cutoff of

PurposeThis study adopts self-determination theory and stimulus-organism-response framework to develop a model that explores the motivations of such donors by considering their self-determination needs and extrinsic and intrinsic motivations.Design/methodology/approachBased on online survey data collected from 436 crowdfunding donors in China, this study follows a structural equation modeling analysis to test hypotheses.FindingsThe results indicate that perceived ease of use, perceived self-efficacy and social connection have positive effects on the donation intentions of backers through a combination of extrinsic and intrinsic motivations.Originality/valueThe findings shed light on various extrinsic and intrinsic motivations advancing knowledge of individual fund motivation in donation-based crowdfunding and provide guidelines for the development of donation-based crowdfunding theory and practice.

Product characteristics of wearable devices have large impacts on users’ initial trust as users intend to adopt wearable devices, which further impacts wearable devices' use intention. This paper a...

Purpose As retailers have increasingly embraced an omnichannel retailing strategy, explaining and predicting the helpfulness of online review should consider both online-based and offline-based reviews. The paper aims to discuss this issue. Design/methodology/approach Based on the signaling theory, this study intends to examine the impacts of review-related and reviewer-related signals on review helpfulness in the context of omnichannel retailing. The proposed research model and corresponding hypotheses were tested by using negative binomial regression. Findings The results shown that both review-related (review rating and review sentiment strength) and reviewer-related (reviewer real name and reviewer expertise) signals positively affect review helpfulness. Contrary to the authors’ expectations, review length negatively affects review helpfulness. Specifically, when the review submitted from an omnichannel retailer’s offline channel, the positive impacts of reviewer real name on review helpfulness will be stronger, and the positive impacts of reviewer expertise on review helpfulness will be weaker. Originality/value Unlike many previous studies tend to explore the antecedents of review helpfulness in a single-channel setting, the study examined the factors that affect review helpfulness in an omnichannel retailing context.

Citizens' visits and contributions are critical to the success of mobile government microblogging services (GMSs). Drawing on stimulus-organism-response (SOR) framework and the uses and gratifications (U&G) theory, a research model was developed to investigate the impacts of perceived integration and atmosphere on citizens' gratifications and subsequent impacts on mobile GMS participation behaviors. A two-staged structural equation modeling (SEM)-neural network approach was employed to test the proposed model by using data collected from 702 mobile GMS citizens in China. The empirical results showed that atmosphere and perceived integration positively influence the citizens' perceptions of social value, information value, and hedonic value, which further positively influence the citizens' intention to acquire and share information. Moreover, the neural network analysis showed that the impact of the atmosphere on information value and hedonic value is stronger than that of perceived integration. The information value is found to be the strongest antecedents of the intention to acquire intention, while the social value is the most influential factor in predicting intention to share intention. The theoretical and managerial implications for mobile GMS research are also discussed.

Despite mobile government microblogging service (GMS) initially attracted a huge number of followers, its discontinuance rate remains high. How to lead citizens to continue use mobile GMS is a question that many government agencies are asking. The present study attempts to understand the factors that affect mobile GMS continuance by focusing on the influences of perceived integration and perceived interactivity on citizens’ value evaluations. The research model was empirically tested against data collected from 619 mobile GMS users in China. The results of structural equation modeling analysis shown that perceived (online-offline) integration and perceived (citizen-government) interactivity positively affect both two extrinsic values (information value and social value), and two intrinsic values (hedonic value and emotional value) of using mobile GMS. Information value, social value, and hedonic value in turn further positively affect mobile GMS continuance. However, the influence of emotional value on mobile GMS continuance was not significant. Theoretical and practical implications of the findings are also presented.

Facing the service transformation of China’s manufacturing industry and the in-depth application of mobile information technology in the manufacturing industry, based on the relevant literature and theoretical analysis, this paper establishes a theoretical model of the impact of T on enterprise innovation service performance. The model structure reveals the mediating role of enterprise innovation service capability, and puts forward the corresponding research hypotheses. Then, taking some Chinese manufacturing enterprises as the research object, through the statistical analysis of the questionnaire data, it is concluded that the variable setting is reasonable and effective. On this basis, this paper studies the influence of manufacturing enterprises’ MIT capability on service innovation performance, and tests its influence path and influencing factors. This paper argues that it is an effective way to improve the service capability of enterprises through MIT, and then indirectly affect the service innovation performance of enterprises.

Due to the Terminal demand fluctuation in the open market environment, the structure stability of digital supply chain will be affected, resulting in the instability of service quality. Based on the T-JIT theory, a conceptual model should be constructed from the change of market demand, the flow of service information on the nodes of digital supply chain, the quality of service information of nodes in the chain and the digital capability of enterprises. Then, the model hypothesizes are to be verified by the survey data of digital supply chain for Chinese manufacturing. The results show that: under certain market demand disturbance, the stronger the enterprise's digital technology capability, the higher the service information flow and service information quality of digital supply chain, and the stronger the enterprise's digital technology capability, the more significant the positive regulation effect.

The water-cooled chiller is one of the indispensable equipment in each building. Due to long-term use or improper operation, it is easy to cause components of the equipment to be wore out, generating additional energy consumption, and even causing malfunction. In this study, we used technology of IoT (Internet of Things) to upload the operating parameters and data in each period of every water-cooled chiller to the cloud, and presented the visualized result. Managers were able to understand the current status of each water-cooled chiller much easier with the visualized results, and at the same time we conducted predictive analysis on the collected water-cooled chiller data. If we can predict the COP value trend accurately, managers can effectively arrange personnel to carry out the maintenance work of each water-cooled chiller to reduce unnecessary energy and cost losses.

With the growing number of virtual community providers entering the e-commerce transactions market, the mechanism affecting the community users shift to e-commerce buyers has gradually aroused the concern of industry and academia. Based on trust mechanism, the value of information and risk cost theory, this paper constructs the transformation model of the virtual community of users. To select members of the community survey, we collected a total of 269 valid questionnaires. After data processing and analysis, the results indicate that perceived purposeful value of virtual community members significantly positively affects community trading platform trust. Perceived purposeful value of virtual community members has a significant positive impact on their purchase intention of virtual community trading platform, and thus significantly affect the purchase intention. Community trading platform trust significantly positively affects users’ purchase intention.

In view of the collaborative innovation and development of enterprises’ products. It is an effective measure to improve the innovation efficiency of the manufacturing industry of China and promote the steady development of enterprises. More and more enterprises attach importance to collaborative product innovation based on resource sharing among supply chain nodes. As a decentralized data collection and sharing technology, the block-chain can provide support for resource sharing and business collaboration among enterprises in supply chain. As a trust guarantee system, the block-chain can provide support for resource sharing and business collaboration among supply chain enterprises. However, as a new technology, the use of block-chain by enterprises is still in a wait-and-see state. In order to help enterprises effectively understand the impact of block-chain on the collaborative product innovation of manufacturing supply chain, this paper will study the influencing factors of collaborative product innovation of supply chain on the basis of characteristics and actual situation of collaborative product innovation of Chinese manufacturing enterprises. First of all, we will make an empirical analysis on the current situation and existing problems of supply chain collaborative product innovation in China’s manufacturing industry through questionnaire survey, so as to study the problems in detail. Secondly, through the literature analysis of supply chain collaborative product innovation, this paper puts forward some measurement indicators, some research hypotheses, and then constructs a conceptual model of the influence factors of supply chain collaborative product innovation. Finally, based on the empirical study of the proposed model, some suggestions are put forward to improve the efficiency of supply chain collaborative product innovation.