Secondary use of medical big data is increasingly popular in healthcare services and clinical research. Understanding the logic behind medical big data demonstrates tendencies in hospital information technology and shows great significance for hospital information systems that are designing and expanding services. Big data has four characteristics--Volume, Variety, Velocity and Value (the 4 Vs)--that make traditional systems incapable of processing these data using standalones. Apache Hadoop MapReduce is a promising software framework for developing applications that process vast amounts of data in parallel with large clusters of commodity hardware in a reliable, fault-tolerant manner. With the Hadoop framework and MapReduce application program interface (API), we can more easily develop our own MapReduce applications to run on a Hadoop framework that can scale up from a single node to thousands of machines. This paper investigates a practical case of a Hadoop-based medical big data processing system. We developed this system to intelligently process medical big data and uncover some features of hospital information system user behaviors. This paper studies user behaviors regarding various data produced by different hospital information systems for daily work. In this paper, we also built a five-node Hadoop cluster to execute distributed MapReduce algorithms. Our distributed algorithms show promise in facilitating efficient data processing with medical big data in healthcare services and clinical research compared with single nodes. Additionally, with medical big data analytics, we can design our hospital information systems to be much more intelligent and easier to use by making personalized recommendations.

Grassroots healthcare institutions (GHIs) are the smallest administrative levels of medical institutions, where most patients access health services. The latest report from the National Bureau of Statistics of China showed that 96.04 % of 950,297 medical institutions in China were at the grassroots level in 2012, including county-level hospitals, township central hospitals, community health service centers, and rural clinics. In developing countries, these institutions are facing challenges involving a shortage of funds and talent, inconsistent medical standards, inefficient information sharing, and difficulties in management during the adoption of health information technologies (HIT). Because of the necessity and gravity for GHIs, our aim is to provide hospital information services for GHIs using Cloud computing technologies and service modes. In this medical scenario, the computing resources are pooled by means of a Cloud-based Virtual Desktop Infrastructure (VDI) to serve multiple GHIs, with different hospital information systems dynamically assigned and reassigned according to demand. This paper is concerned with establishing a Cloud-based Hospital Information Service Center to provide hospital information software as a service (HI-SaaS) with the aim of providing GHIs with an attractive and high-performance medical information service. Compared with individually establishing all hospital information systems, this approach is more cost-effective and affordable for GHIs and does not compromise HIT performance.

TikTok has one of the most advanced algorithm systems and is the most addictive as compared to other social media platforms. While research on social media addiction is abundant, we know much less about how the TikTok information system environment affects users’ internal states of enjoyment, concentration, and time distortion (which scholars define as the flow experience), which in turn influences their addiction behavior. To fill this gap, this study collects responses from 659 adolescents in China aged between 10 and 19 years old, and the data is then analyzed using Partial Least Square (PLS). We find that the system quality has a stronger influence than information quality in determining adolescents’ experience with TikTok and that the flow experience has significant direct and indirect effects on TikTok addiction behavior. Notably, this study finds that TikTok addiction is determined by users’ mental concentration on the medium and its content. Several theoretical insights from the stimulus–organism–response (S–O–R) model and the flow theory are used to explain the findings.

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Copycats often choose brand names that mimic perceptual, conceptual, or both elements of leading brand names. Yet little is known about how perceptual and conceptual similarities of a copycat interact to affect consumers' evaluations, especially in logographic language systems (e.g., Chinese). Three laboratory experiments demonstrate that perceptual similarity alone leads to negative evaluations of copycat brand names; this negative effect, however, can be mitigated when conceptual similarity is added. The underlying mechanism for this effect can be traced to consumers' persuasion knowledge. Perceptual (vs. conceptual) similarity activates consumers' persuasion knowledge about the insincere motives of the copycat brand, which in turn shapes their brand evaluations. However, this effect can become less prominent when conceptual similarity is added because it alleviates use of persuasion knowledge, or when a consumer is in a happy mood because it neutralizes persuasion knowledge. These findings shed light on how different types of copycat strategies interact to affect copycat brand name evaluations and offer important implications for marketing practice.

This study explores the impacts of the World Golf Championships HSBC Champions tournament in Shanghai, China as perceived by host community residents over the past ten years, and how those perceptions affected their attitudes towards the future hosting of this event. An empirical study was carried out and data collected from 1047 Shanghai residents using structured questionnaires. Multiple factor analysis identified six factors underlying the perceived impacts of the event. It was found that after over a decade of continuous staging, the WGC-HSBC Champions did not affect the life of most local residents due to their low awareness of the event. Despite that, the study also found that residents' positive perceptions led to their support for the future hosting of the event, which confirms the usefulness of social exchange theory in explaining residents' perceptions. Finally, implications for destination managers are discussed to ensure the needs of both visitors and residents are addressed.

Counterfeits have been a longstanding concern to global brand manufactures. However, recently, a new product category that partly imitates and partly innovates under the term shanzhai has entered into market. Shanzhai products mimic original leading brands through visual or functional similarities and may also provide additional features. Given this new copycat phenomenon, our study for the first time conceptually distinguishes shanzhai products from counterfeits, theoretically compares the values of consumers choosing shanzhai products versus counterfeits, and empirically tests such differences in one integrative model. Specifically, shanzhai buyers value product functional benefits more than counterfeit buyers, while counterfeit buyers value status consumption, yet experience less self‐clarity than shanzhai buyers. Our findings offer important implications for imitative innovation literature as well as for practitioners.

Abstract:In 2013,