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Hierarchical Advance Soft Computing Techniques for Analyzing the Success Drivers of E-business and its Strategies
Weiwei Xu, B.Vinodhini and Parthasarathy Poovendran

The literature review of the market has recently been increasingly analyzed based on the relative impact of the empirical determination of strategic success factors in e-commerce across various smart city platforms. To quantify the cumulative impacts of a given policy or e-commerce model, this research perspective has been focused on the effect of marketing practices and selected business models, differentiating direct and indirect factors on sales and profitability in a smart city platform. In this research, Hierarchical Advance Soft Computing Techniques (HASCT) has been proposed to analyze the performance factor of e-commerce in various sectors of smart cities platform. Furthermore, HASCT evaluates the relative value of the different strategic components using unrelated regression models in e-commerce. Here, the indirect impact of sales on profitability determines the overall flexibility of the marketing plan. Furthermore, the Fuzzy Decision-making trial and evaluation laboratory model (DEMATEL) has been introduced for effective decision making and measure the success factors of e-commerce. The numerical results have been executed, and the proposed HASCT method enhances customer buying behavior prediction of 95.6%, profitability ratio of 98.7%, the performance ratio of 96.8%, accuracy ratio of 97.7%, and less error rate 9.8% in smart cities platforms.

Keywords: E-business, soft computing, smart cities, sales and profitability, regression models

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