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Titlebook: Digital Economy. Emerging Technologies and Business Innovation; Third International Mohamed Anis Bach Tobji,Rim Jallouli,Anton Nijholt Con

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樓主: 召喚
21#
發(fā)表于 2025-3-25 04:14:22 | 只看該作者
Exploring Readers’ Perception of?Professional Blogsow blog readers perceive and anticipate both blogs in general and professional blogs. In particular, the main interest of the research is to investigate the influence of monetising activities in blogs on authenticity of the blog authors and credibility of their blogs. The insights into the motivatio
22#
發(fā)表于 2025-3-25 11:18:35 | 只看該作者
Co-design and Chronic Regulatory Focus: A Cross-cultural Study and Suggestions for Future ,-Marketin and e-marketing revolutions greatly explain the spread of those collaborative practices. Special interest of this study is on consumer perceptual and behavioral responses toward co-designed packaging in order to assess the worthiness of conducting an online co-design experience. For this reason, ba
23#
發(fā)表于 2025-3-25 12:12:52 | 只看該作者
The Practices of Nonprofit Organizations in the New Age of Social Media: A Qualitative Study of Donold a fruitful relationship. Yet, emerging challenges have hindered them from taking advantages of all features offered by the new media namely with reference to potential donors’ receptivity to online charitable presence. Therefore, a critical examination of opportunities and challenges associated w
24#
發(fā)表于 2025-3-25 16:53:58 | 只看該作者
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發(fā)表于 2025-3-25 21:14:08 | 只看該作者
26#
發(fā)表于 2025-3-26 01:04:13 | 只看該作者
Competitive Intelligence in the Start-Up Companies Belonging to the ICT Sector in Tunisiang to the ICT sector in Tunisia, and on the other hand, it aims at counting their real needs in information. Based on questionnaires and interviews, our results show that in spite of the awareness of the importance of competitive intelligence, the latter suffers from several cultural weaknesses (wea
27#
發(fā)表于 2025-3-26 05:29:33 | 只看該作者
28#
發(fā)表于 2025-3-26 11:02:49 | 只看該作者
An Improved CNN Steganalysis Architecture Based on “Catalyst Kernels” and Transfer Learningarding the success of deep learning in the field of imaging analysis. Previous approaches have focused on proposing complex architectures with large sizes of images rather than simple models. In this work, we propose a more adjustable flexible architecture with the use of small size images. The robu
29#
發(fā)表于 2025-3-26 16:24:11 | 只看該作者
30#
發(fā)表于 2025-3-26 20:42:24 | 只看該作者
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