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Scientific Data Sharing Platform Using Behavior Study Based on Extended TAM Model

  • Jianping Liu
  • Jian WangEmail author
  • Guomin Zhou
  • Guilan Zhang
  • Yao Pan
  • Xu Sa
  • Tingting Liu
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 576)

Abstract

Scientific data retrieval behavior is a typical human–computer interaction behavior, and users are in the dominant position in the interaction. It is of great significance to improve the scientific data sharing system to study the factors that affect scientific data user data search and retrieval. Based on the extended TAM model, this study used questionnaires to collect data from the competitors of the 6th “sharing cup” university students’ science and technology resources sharing service innovation contest and used structural equation method to analyze the data. The results show that the extended TAM model can explain and predict the using behavior of users’ scientific data sharing platform. Perceived ease of use, perceived usefulness, perceived playfulness, and behavior attitude have positive effects on actual behavior through behavior intention, of which perceived usefulness has the most significant effect. The research has an important guiding role for the construction of scientific data sharing platform.

Keywords

Scientific data sharing platform Scientific data retrieval TAM 

Notes

Acknowledgements

This work was supported by a grant from Social science fund—Scientific Data User Relevance Criteria and Use Model Empirical Study (14BTQ056), and National High-tech R&D Program of China (863 Program No.2013AA102405) and Agricultural Science, Technology Innovation Project of Chinese Academy of Agricultural Sciences (Project No.CAAS-ASTIP-2016-AII).

Compliance with Ethical Standards

The study was approved by the Logistics Department for Civilian Ethics Committee of Agricultural Information Institute, Chinese Academy of Agricultural Sciences.

All subjects who participated in the experiment were provided with and signed an informed consent form.

All relevant ethical safeguards have been met with regard to subject protection.

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Copyright information

© Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  • Jianping Liu
    • 1
    • 2
  • Jian Wang
    • 1
    • 2
    Email author
  • Guomin Zhou
    • 1
    • 2
  • Guilan Zhang
    • 1
    • 2
  • Yao Pan
    • 1
    • 2
  • Xu Sa
    • 1
    • 2
  • Tingting Liu
    • 1
    • 2
  1. 1.Agricultural Information Institute, Chinese Academy of Agricultural SciencesBeijingChina
  2. 2.Key Laboratory of Agricultural Big Data, Ministry of Agriculture and Rural AffairsBeijingChina

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