Predicting Partner’s Digital Transformation Based on Artificial Intelligence
Source abstract
Abstract
Partner’s digital transformation is one of the most important metrics for businesses, particularly for businesses in the subscription world. Hence, how to predict partner transformation is a consistent focus in the industry. In this paper, we use an AI (Artificial Intelligence) relevant algorithm to analyze partner’s digital transformation issues and propose a novel method, named the hybrid VKR (VAE, K-means, and random forest) algorithm, to predict partner transformation. We apply our algorithm to partner transformation issues. First, we show the prediction of about 5980 partners from 25,689 partners, who are transformed and sorted according to important indicators. Secondly, we recap the tremendous effort that was required by the company to obtain high-quality results for economic change when a partner is transforming along with one or many of the transformation dimensions. Finally, we identify unethical behavior by looking through deal transaction data. Overall, our work sheds light on several potential problems in partner transformation and calls for improved scientific practices in this area.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Outsourcing and Supply Chain Management · Technology Adoption and User Behaviour · Digital Platforms and Economics
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Key Lab of IC&SP of MOE, School of Computer Science and Technology, Anhui University, Hefei 230039, China
Department of Computer Science and Engineering, University of Texas at Arlington, Arlington, TX 76019, USA
Funding
National Natural Science Foundation of China · NSFC Key Project of International (Regional) Cooperation and Exchanges
References (34)
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