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Journal of Theoretical and Applied Electronic Commerce Research, Volume 17, Issue 3

September 2022 - 18 articles

Cover Story: Three-dimensional models are indispensable in various industries today, ranging from architecture to manufacturing and the future creation of a metaverse. However, the adequate pricing of 3D models traded on online platforms, i.e., virtual 3D assets, remains vague. Therefore, this study identifies the relevant price determinants of virtual 3D assets through the analysis of a dataset containing the characteristics of 135.384 3D models based on a machine learning approach to derive a virtual 3D asset price prediction tool. The findings imply that the geometry and number of material files, as well as the quality of textures, are the most relevant price determinants, whereas animations and file formats play a minor role. Thereby, the results partly contradict the pricing recommendations of virtual 3D asset marketplace providers. View this paper
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Articles (18)

  • Article
  • Open Access
8 Citations
4,877 Views
16 Pages

The holiday atmosphere abounds in marketing campaigns. The present research examines how the holiday atmosphere of a brand logo influences consumers’ merchandise-related nostalgic preference. Across three studies, the authors find that when con...

  • Article
  • Open Access
16 Citations
6,695 Views
16 Pages

Customer response models have gained popularity due to their ability to significantly improve the likelihood of targeting the customers most likely to buy a product or a service. These models are built using databases of previous customers’ buy...

  • Article
  • Open Access
60 Citations
12,280 Views
19 Pages

Online grocery shopping in Germany has shown a strong growth in the past years and is expected to further develop in the future, especially through the influence of COVID-19. The main purpose of this study was to examine six theoretical customer-orie...

  • Article
  • Open Access
9 Citations
5,682 Views
35 Pages

Negative reviews on e-commerce platforms are posted to express complaints about unsatisfactory experiences. However, the exact knowledge of how online consumers post negative reviews still remains unknown. To obtain an in-depth understanding of how u...

  • Article
  • Open Access
17 Citations
4,761 Views
25 Pages

Towards Virtual 3D Asset Price Prediction Based on Machine Learning

  • Jakob J. Korbel,
  • Umar H. Siddiq and
  • Rüdiger Zarnekow

Although 3D models are today indispensable in various industries, the adequate pricing of 3D models traded on online platforms, i.e., virtual 3D assets, remains vague. This study identifies relevant price determinants of virtual 3D assets through the...

  • Article
  • Open Access
44 Citations
15,126 Views
15 Pages

Online shopping has intensified in the last decade. The COVID-19 pandemic has imposed circulation limitations and more restrictive behaviors on consumers due to fears of contracting the virus, boosting online grocery shopping. This study aims to asse...

  • Article
  • Open Access
14 Citations
4,725 Views
16 Pages

In practice, several e-commerce platforms offering online channels not only act as resellers but also serve as the marketplace. However, the existing literature rarely explores the impact of the offline service effort strategy with the showrooming ef...

  • Article
  • Open Access
7 Citations
4,518 Views
18 Pages

New Practice of E-Commerce Platform: Evidence from Two Trade-In Programs

  • Qiang Hu,
  • Tingyuan Lou,
  • Jicai Li,
  • Wenjin Zuo,
  • Xihui Chen and
  • Lindong Ma

In the context of developing the digital platform economy, trade-in programs have become an effective strategy for e-commerce platforms to stimulate consumption. Many head e-commerce platforms have launched their own trade-in programs. However, the e...

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J. Theor. Appl. Electron. Commer. Res. - ISSN 0718-1876