Author:
Afful-Dadzie Eric,Afful-Dadzie Anthony
Abstract
Purpose
The paper proposes an intuitionistic fuzzy TOPSIS multi-criteria decision making (MCDM) method for the selection of start-up businesses in a government venture capital (GVC) scheme. Most GVC funded start-ups fail or underperform compared to those funded by private venture capitals due to a number of reasons including lack of transparency and unfairness in the selection process. By its design, the proposed method is able to increase transparency and reduce the influence of bias in GVC start-up selection processes. The proposed method also models uncertainty in the selection criteria using fuzzy set theory that mirrors the natural human decision making process.
Design/methodology/approach
The proposed method first presents a set of criteria relevant to the selection of early stage but high potential start-ups in a Government Venture Capital (GVC) financing scheme. These criteria are then analyzed using the TOPSIS method in an intuitionistic fuzzy environment. The intuitionistic Fuzzy Weighted Averaging (IFWA) Operator is used to aggregate ratings of decision makers. A numerical example of how the proposed method could be used in GVC start-up candidates’ selection in a highly competitive government venture capital scheme is provided.
Findings
The methodology adopted increases fairness and transparency in the selection of start-up businesses for fund support in a government-run venture capital scheme. The criteria set proposed is ideal for selecting start-up businesses in a government controlled venture capital scheme. The decision making framework demonstrates how uncertainty in the selection criteria are efficiently modelled with the TOPSIS method.
Practical implications
As government venture capital schemes increase around the world, and concerns about failure and underperformance of GVC funded start-ups increase, the proposed method could help bring formalism and ensure the selection of start-ups with high success potential.
Originality/value
The framework designs relevant sets of criteria for a selection problem, demonstrates the use of extended TOPSIS method in intuitionistic fuzzy sets and apply the proposed method in an area that has not been considered before. Additionally, it demonstrates how intuitionistic fuzzy TOPSIS could be carried out in a real decision making application setting.
Subject
Management Science and Operations Research,General Business, Management and Accounting
Cited by
30 articles.
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