University of Twente Student Theses
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Optimizing E-commerce Feature Selection via Categorization and Resource-Constrained Modeling
Costea, M.-P. (2025) Optimizing E-commerce Feature Selection via Categorization and Resource-Constrained Modeling.
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| Abstract: | In the competitive field of e-commerce, aligning webshop design features with business performance goals is essential. This research proposes a general, reusable methodology for webshop development that supports strategic, resource-constrained decision-making. Specifically, it introduces a structured, data-driven approach- developed in collaboration with Epart ment- to guide webshop feature selection based on expected business value. By categorizing webshops based on structural and functional characteristics, identifying category-specific KPIs, and mapping them to technical features, the research shows the approach of identifying performance-enhancing fea tures tailored to webshop types. Additionally, the suitability of a knapsack based optimization model is evaluated to prioritize these features based on their business impact and implementation cost. The outcome is a practical categorization framework for e-commerce webshops that supports the ap plication of this optimization model. Furthermore, this research provides a literature-based list of KPIs for each categorization layer and associated features hypothesized to positively influence them. Having a data-driven methodology for feature selection allows Epartment to proactively align development efforts with strategic performance goals, rather than reactively responding to client requests. |
| Item Type: | Essay (Bachelor) |
| Faculty: | EEMCS: Electrical Engineering, Mathematics and Computer Science |
| Subject: | 54 computer science, 85 business administration, organizational science |
| Programme: | Business & IT BSc (56066) |
| Link to this item: | https://purl.utwente.nl/essays/108055 |
| Export this item as: | BibTeX EndNote HTML Citation Reference Manager |
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