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您的检索式：作者名="Eric T.K.Lim"
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| 1 | Traversing knowledge networks:an algorithmic historiography of extant literature on the Internet of Things(IoT)显示文摘Research on the Internet of Things(IoT)has been booming for the past 6 years due to technological advances and potential for application.Nonetheless,the rapid growth of IoT articles and the heterogeneous nature of IoT pose challenges to conducting a systematic review of IoT literature.This study seeks to address the abovementioned challenges by reviewing 1065 IoT articles retrieved from the International Statistical Institute Web of Science via a blend of quantitative citation analysis and qualitative content analysis.For the former,we generated a historiography of IoT research,a citation network,in which we tried to identify main paths of codification and diffusion,as well as path-dependent transitions.For the latter,we explicated the progression of knowledge through 30 central IoT articles in chronological order regarding infrastructures,enabling technologies,potential technologies,and research challenges.Findings from this study contribute to both IoT research and management. | Fei Liu Chee-Wee Tan Eric T.K.Lim Ben Choi | 2017 | Journal of Management Analytics2017，4，1： | 1 |
| 2 | Image Analytics:A consolidation of visual feature extraction methods显示文摘Revolutionary advances in machine and deep learning techniques within the field of computer field have dramatically expanded our opportunities to decipher the merits of digital imagery in the business world.Although extant literature on computer vision has yielded a myriad of approaches for extracting core attributes from images,the esotericism of the advocated techniques hinders scholars from delving into the role of visual rhetoric in driving business performance.Consequently,this tutorial aims to consolidate resources for extracting visual features via conventional machine and/or deep learning techniques.We describe resources and techniques based on three visual feature extraction methods,namely calculation-,recognition-,and simulation-based.Additionally,we offer practical examples to illustrate how image features can be accessed via open-sourced python packages such as OpenCV and TensorFlow. | Xiaohui Liu Fei Liu Yijing Li Huizhang Shen Eric T.K.Lim Chee-Wee Tan | 2021 | Journal of Management Analytics2021，8，4： | 1 |
| 3 | Effects of age on live streaming viewer engagement:a dual coding perspective显示文摘Though the emerging live streaming industry has attracted growing attention,the dominant yanzhi category where streamers mostly interact with the audience through amateur talent shows and casual chats has not been widely investigated.To decode the mechanism behind the popularity of yanzhi streamers,this study draws on Dual Coding Theory(DCT)to posit that age estimated from a streamer’s face and voice can influence the level of viewer engagement.To validate our hypothesized relationships,274 one-minute video records ahead of a viewer commenting or/and gifting were collected and analyzed via deep learning algorithms.Analytical results attest to the negative effects of both facial and vocal age on viewer engagement,while their interaction has a positive impact on viewer engagement. | Fei Liu Yijing Li Xiaofei Song Zhao Cai Eric T.K.Lim Chee-Wee Tan | 2022 | Journal of Management Analytics2022，9，4： | 0 |
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