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Hybridized Computational Predictive Framework (HCPF) for Organizational Management in E-business Transformation
Lanlan Xie, Vicente García Díaz and Carlos Enrique Montenegro-Marin

Recently, companies have taken e-business measures to handle their internal market and environmental processes more effectively. While the online markets have recently received a tremendous amount of attention, the E-business challenge concerns a much broader constituency. Hence, in this paper, Hybridized Computational Predictive Framework (HCPF) has been proposed to analyze the E-business transformation for organizational management and its impact on the online market. A new job definition and revised policies are necessary to introduce e-business application re-design, organizational transformation, and alignment. In addition, taxation, legal, and security considerations will be addressed by organizations. All the rules and models change the E-business. Adopting new technologies and business models in an enterprise is essential to increasing the organization’s productivity. The Internet economy needs an essential change in the participating organizations. By digitizing the whole supply chain, e-business and the online market’s real benefits can be achieved. The experimental results show that the proposed HCPF method achieves high accuracy of 93.6%, F-measure of 93.2%, less error rate of 1.2%, duration of 7.6%, perception of 94.2%, low cost of 24%, compared to other existing methods.

Keywords: E-business transformation, organizational management, online market, hybridized computation predictive framework

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