A Hybrid ANP Method for Evaluation of Government Data Sustainability

Jicang Xu, Linlin Li and Ming Ren
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Jicang Xu: School of Information Resource Management, Renmin University of China, Beijing 100872, China
Linlin Li: School of Information Resource Management, Renmin University of China, Beijing 100872, China
Ming Ren: School of Information Resource Management, Renmin University of China, Beijing 100872, China

Sustainability, 2022, vol. 14, issue 2, 1-32

Abstract: The evaluation of government data sustainability is a multicriteria decision making problem. The analytic network process (ANP) is among the most popular methods in determining the weights of criteria, and its limitation is the un-convergence problem. This paper proposes a hybrid ANP (H-ANP) method, which aims to improve the ANP by combining the weights obtained from the analytic hierarchy process (AHP). The proposed method is proved to be convergent since the network of the H-ANP is strongly connected. According to the simulation experiments, H-ANP is more robust than ANP under different settings of parameters. It also shows a higher Kendall cor-relationship and lower MSE with respect to AHP, compared with the existing method (e.g., the averagely connected ANP method). An empirical example is also provided, which uses H-ANP to evaluate the government data sustainability of a city.

Keywords: multicriteria decision making; ANP; H-ANP; convergence; data sustainability evaluation (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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