DECISION SUPPORT SYSTEM METHODS FOR E-COMMERCE PLATFORM SELECTION : A SYSTEMATIC LITERATURE REVIEW
Keywords:
Decision Support System, E-commerce Selection, Systematic Literature ReviewAbstract
The rapid expansion of the digital economy has intensified competition among e-commerce platforms, creating a complex decision-making environment for consumers. To address this challenge, this study conducts a Systematic Literature Review (SLR) to evaluate the application of Decision Support System (DSS) methods. Analyzing 20 selected peer-reviewed articles, the review identifies Simple Additive Weighting (SAW) and Analytical Hierarchy Process (AHP) as the dominant Multi-Criteria Decision-Making (MCDM) approaches, favored for their computational efficiency and structural capability. The findings confirm that these methods effectively mitigate user subjectivity by transforming qualitative preferences into rational, quantitative rankings. Furthermore, the analysis establishes that platform selection is driven by a holistic balance of economic factors (pricing, fees), service quality (delivery speed), and technical usability (security, interface). These insights provide a robust framework for optimizing consumer decision-making and highlight a growing trend toward hybrid models and AI integration.
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