Crowdfunding is the practice of funding a project or venture by raising monetary contributions from a large number of people, typically via the Internet. Lendwithcare is amongst the first crowdfunding platforms specifically dedicated to support individual and group entrepreneurs in developing countries through partner microfinance institutions. A key objective of Lendwithcare is to identify the attributes (i.e., the characteristics of crowdfunding projects in their online descriptions) that affect investors/potential investors when taking their investment decision. This paper proposes a decision rule-based approach to address this issue. This approach relies on the Dominance-Based Rough Approach (DRSA), which is a well-known multicriteria sorting method. The outputs of DRSA are a collection of if-then decision rules and a collection of attribute reducts. In this paper, new measures are proposed for calculating the relative importance of condition attributes based on the characteristics of decision rules and of attribute reducts. Decision rule-based measures are parameterised in order to consider the characteristics of decision rules using both learning and testing datasets. The proposed measures can be aggregated into a comprehensive measure indicating the overall importance of each condition attribute. Furthermore, the proposed measures are extended in order to compute the relative importance of a collection of condition attributes taken together. In addition, decision rule-based measures are extended to evaluate the relative importance of specific values of condition attributes. The proposed approach has been applied and validated using real-world data from Lendwithcare.
|Number of pages||24|
|Journal||European Journal of Operational Research|
|Early online date||19 Mar 2020|
|Publication status||Published - 16 Oct 2020|
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- Rough sets
- Dominance-based Rough Set Approach
- Relative importance
- Decision rules
- Attribute reducts
- Dominance-based rough set approach
ASJC Scopus subject areas
- Information Systems and Management
- Computer Science(all)
- Modelling and Simulation
- Management Science and Operations Research
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