PurposeBased on the stimulus-organism-response theory, this research constructs the influence of the stimulus factors of the live-streaming shopping environment on consumers' psychological situation. It then produces the research model of impulsive purchase intention.Design/methodology/approachIn this study, the online questionnaire survey method was used to survey users who participated in live-streaming shopping, and a total of 335 valid questionnaires were collected. Then SPSS and SmartPLS were used for data empirical evaluation and hypotheses test.FindingsResearch results show that demand, convenience, interactivity, and playfulness are positively stimulating consumers' perceived enjoyment. And their perceived enjoyment directly drives their intention of impulsive purchase.Practical implicationsThe choice of the live streaming platform, the design of the interactive interface, and the design of the shopping process are all factors that the streamer must carefully consider. The results of this study can be used as a reference for the development of live-streaming shopping and provide the industry with an understanding of the main factors that affect users' live streaming and impulsive purchases to plan an effective live streaming platform and content.Originality/value“E-commerce live streaming” is regarded as the latest trend of e-commerce, and impulse buying is regarded as a key factor in the success of transactions. This research has developed factors that influence impulsive purchases after watching live streaming based on the SOR theory.

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PurposeThis paper seeks to identify the variables that affect the innovation performance of R&D teams, and to investigate the interactions between these variables.Design/methodology/approachA research framework is first established through a literature review, and is then adjusted according to case studies of five high‐tech companies in Taiwan. The adjusted model is then tested through a survey of high‐tech companies in Taiwan.FindingsIt is concluded that the style of the upper management team and the leadership of the R&D manager are the main forces that determine R&D management practice, but that the educational background, work experience, and expertise of R&D managers do not distinguish the level of discipline or the sophistication of R&D management practice. Some aspects of R&D management practice, for example, the generation and utilization of technical reports and the cultivation of professional knowledge, can be reinforced by office support and alliance. With adequate resource support, more sophisticated R&D management practice does lead to better innovation performance as measured by the number of new products, patents, and technical reports.Research limitations/implicationsThe findings are derived only from the high‐tech industry in Taiwan. This regional limitation is inevitable in a single study. In the future, more regions can be investigated and compared.Practical implicationsR&D management practice links closely to innovation performance. Disciplined and sophisticated practice improves innovation performance in many ways under different contingencies.Originality/valueR&D management practice was never a focus of study. This paper approaches the topic of innovation performance from this perspective and confirms its importance in many ways.

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Identifying the impact of climatic factors on mosquito population dynamics is of great importance for dengue outbreak control. The purpose of this study is to develop an approach to predict spatial/temporal mosquito reproduction and disease outbreaks. The prediction of a dengue outbreak is only possible if the temporal relationship between mosquito replication and the weather is known. At present, this is unclear and needs to be examined. Moreover, because the development of mosquito density is a dynamic process in the course of time, it should be observed as closely as possible, in this study in a 1-day timeframe. This paper makes a thorough study of the situation in southern Taiwan and analyzes a large amount of data from 1999 to 2004 related to dengue cases and larval density. We first use the method, k-means, to conduct data clustering and derive representative larvae replication patterns. Then, we propose mathematical models to approximate the development of larval density, describe the expansion of mosquito activity areas, and construct a surveillance system to raise alerts based on real-time input of weather data and larval indices. Analysis of historic data reveals some new information on the spatial and temporal relationships between larval density and dengue outbreaks. In Taiwan, if the weather becomes or remains warm and humid for 6 days after a bout of rain, there can be a sharp increase in the larval mosquito population. About 7 days after the Breteau index begins to rise, larval density reaches its climax; and, about 12 days after the climax of larval density, cases of dengue may be reported. The system is tested using subsequent data from 2005 to 2009 and shows satisfactory accuracy. Numerous data support these findings, and this new knowledge is thus validated and can be used to assist public health professionals to take effective dengue control measures.