-
Ding, Y.; Zhang, G.; Chambers, T.; Song, M.; Wang, X.; Zhai, C.: Content-based citation analysis : the next generation of citation analysis (2014)
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- Date
- 22. 8.2014 16:52:04
- Source
- Journal of the Association for Information Science and Technology. 65(2014) no.9, S.1820-1833
-
Teo, H.-H.; Wang, X.; Wei, K.-K.; Sia, C.-L.; Lee, M.K.O.: Organizational learning capacity and attitude toward complex technological innovations : an empirical study (2006)
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- Abstract
- Recent studies have found organizational learning capacity to be a key factor in influencing organizational assimilation and exploitation of knowledge-intensive innovations. Despite its increasing importance, the impact of organizational learning capacity an technology assimilation is not well understood. Distilling from extant works an organizational learning and technology assimilation, this study identifies four components of organizational learning capacity, namely, systems orientation, organizational climate for learning orientation, knowledge acquisition and utilization orientation, and information sharing and dissemination orientation. The authors subject these components to structural equation modeling analyses to better understand their structure and dimensionality. The analyses strongly support the proposed four major dimensions underlying organizational learning capacity. Organizational learning capacity, as a higher-order factor, has a significant impact an attitude towards organizational adoption of knowledge-intensive innovations. Implications for practice and research are discussed.
- Source
- Journal of the American Society for Information Science and Technology. 57(2006) no.2, S.264-279
-
Jiang, Y.; Zheng, H.-T.; Wang, X.; Lu, B.; Wu, K.: Affiliation disambiguation for constructing semantic digital libraries (2011)
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- Source
- Journal of the American Society for Information Science and Technology. 62(2011) no.6, S.1029-1041
-
Wang, X.; Hong, Z.; Xu, Y.(C.); Zhang, C.; Ling, H.: Relevance judgments of mobile commercial information (2014)
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- Source
- Journal of the Association for Information Science and Technology. 65(2014) no.7, S.1335-1348
-
Wang, X.; High, A.; Wang, X.; Zhao, K.: Predicting users' continued engagement in online health communities from the quantity and quality of received support (2021)
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- Source
- Journal of the Association for Information Science and Technology. 72(2021) no.6, S.710-722
-
Wang, X.; Zhang, M.; Fan, W.; Zhao, K.: Understanding the spread of COVID-19 misinformation on social media : the effects of topics and a political leader's nudge (2022)
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- Source
- Journal of the Association for Information Science and Technology. 73(2022) no.5, S.726-737
-
Wang, X.; Song, N.; Zhou, H.; Cheng, H.: Argument ontology for describing scientific articles : a statistical study based on articles from two research areas (2019)
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- Source
- Proceedings of the Association for Information Science and Technology 56(2019) no.1, S.855-857
-
Wang, X.; Erdelez, S.; Allen, C.; Anderson, B.; Cao, H.; Shyu, C.-R.: Role of domain knowledge in developing user-centered medical-image indexing (2012)
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- Source
- Journal of the American Society for Information Science and Technology. 63(2012) no.2, S.225-241
-
Reyes Ayala, B.; Knudson, R.; Chen, J.; Cao, G.; Wang, X.: Metadata records machine translation combining multi-engine outputs with limited parallel data (2018)
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- Source
- Journal of the Association for Information Science and Technology. 69(2018) no.1, S.47-59
-
Yang, B.; Rousseau, R.; Wang, X.; Huang, S.: How important is scientific software in bioinformatics research? : a comparative study between international and Chinese research communities (2018)
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- Source
- Journal of the Association for Information Science and Technology. 69(2018) no.9, S.1122-1133
-
Wang, F.; Wang, X.: Tracing theory diffusion : a text mining and citation-based analysis of TAM (2020)
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- Abstract
- Theory is a kind of condensed human knowledge. This paper is to examine the mechanism of interdisciplinary diffusion of theoretical knowledge by tracing the diffusion of a representative theory, the Technology Acceptance Model (TAM). Design/methodology/approach Based on the full-scale dataset of Web of Science (WoS), the citations of Davis's original work about TAM were analysed and the interdisciplinary diffusion paths of TAM were delineated, a supervised machine learning method was used to extract theory incidents, and a content analysis was used to categorize the patterns of theory evolution. Findings It is found that the diffusion of a theory is intertwined with its evolution. In the process, the role that a participating discipline play is related to its knowledge distance from the original disciplines of TAM. With the distance increases, the capacity to support theory development and innovation weakens, while that to assume analytical tools for practical problems increases. During the diffusion, a theory evolves into new extensions in four theoretical construction patterns, elaboration, proliferation, competition and integration. Research limitations/implications The study does not only deepen the understanding of the trajectory of a theory but also enriches the research of knowledge diffusion and innovation. Originality/value The study elaborates the relationship between theory diffusion and theory development, reveals the roles of the participating disciplines played in theory diffusion and vice versa, interprets four patterns of theory evolution and uses text mining technique to extract theory incidents, which makes up for the shortcomings of citation analysis and content analysis used in previous studies.
-
Fang, Z.; Costas, R.; Tian, W.; Wang, X.; Wouters, P.: How is science clicked on Twitter? : click metrics for Bitly short links to scientific publications (2021)
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- Source
- Journal of the Association for Information Science and Technology. 72(2021) no.7, S.918-932
-
Wang, X.; Duan, Q.; Liang, M.: Understanding the process of data reuse : an extensive review (2021)
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- Source
- Journal of the Association for Information Science and Technology. 72(2021) no.9, S.1161-1182
-
Walsh, J.A.; Cobb, P.J.; Fremery, W. de; Golub, K.; Keah, H.; Kim, J.; Kiplang'at, J.; Liu, Y.-H.; Mahony, S.; Oh, S.G.; Sula, C.A.; Underwood, T.; Wang, X.: Digital humanities in the iSchool (2022)
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- Source
- Journal of the Association for Information Science and Technology. 73(2022) no.2, S.188-203
-
Wang, X.; Song, N.; Zhou, H.; Cheng, H.: ¬The representation of argumentation in scientific papers : a comparative analysis of two research areas (2022)
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- Source
- Journal of the Association for Information Science and Technology. 73(2022) no.6, S.863-878
-
Cui, Y.; Wang, Y.; Liu, X.; Wang, X.; Zhang, X.: Multidimensional scholarly citations : characterizing and understanding scholars' citation behaviors (2023)
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- Source
- Journal of the Association for Information Science and Technology. 74(2023) no.1, S.115-127
-
Wang, X.; Lin, X.; Shao, B.: Artificial intelligence changes the way we work : a close look at innovating with chatbots (2023)
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- Journal of the Association for Information Science and Technology. 74(2023) no.3, S.339-353
-
Tian, W.; Cai, R.; Fang, Z.; Geng, Y.; Wang, X.; Hu, Z.: Understanding co-corresponding authorship : a bibliometric analysis and detailed overview (2024)
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- Source
- Journal of the Association for Information Science and Technology. 75(2023) no.1, S.3-23
