Predicting e-commerce company success by mining the text of its publicly-accessible website |
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| Authors: | Dirk Thorleuchter Dirk Van den Poel |
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| Affiliation: | 1. University of the District of Columbia, Washington, DC;2. Institute for Research on Innovation and Science, University of Michigan, Ann Arbor;3. Clausthal University, Germany;4. Strathclyde University, United Kingdom;5. Loughborough University, United Kingdom;6. Durham University, United Kingdom;7. University of Stuttgart, Germany;8. University of Southern Denmark, Denmark |
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| Abstract: | We analyze the impact of textual information from e-commerce companies’ websites on their commercial success. The textual information is extracted from web content of e-commerce companies divided into the Top 100 worldwide most successful companies and into the Top 101 to 500 worldwide most successful companies. It is shown that latent semantic concepts extracted from the analysis of textual information can be adopted as success factors for a Top 100 e-commerce company classification. This contributes to the existing literature concerning e-commerce success factors. As evaluation, a regression model based on these concepts is built that is successful in predicting the commercial success of the Top 100 companies. These findings are valuable for e-commerce websites creation. |
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