4.7 Article

Public and private value creation using artificial intelligence: An empirical study of AI voice robot users in Chinese public sector

Journal

Publisher

ELSEVIER SCI LTD
DOI: 10.1016/j.ijinfomgt.2021.102401

Keywords

Value creation; Public value; Private value; Artificial intelligence; Voice robot

Funding

  1. National Natural Science Foun-dation of China (NSFC) [NSFC-71403080]
  2. Department of Science & Technology of Henan Province [172400410135, 182400410140]

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The study found that the effective use of AI voice robots is significantly associated with private value and procedural justice, but not with trust in government. Surprisingly, private value was found to have a greater impact on overall value creation than public value, contradicting common perceptions.
Despite significant theoretical and empirical attention on public value creation in the public sector, the relationship between artificial intelligence (AI) use and value creation from the citizen perspective remains poorly understood. We ground our study in Moore's public value management to examine the relationship between AI use and value creation. We conceptually categorize public service value into public value and private value. We use procedural justice and trust in government as indicators of public value and, based on motivation theory, we use perceived usefulness and perceived enjoyment as indicators of private value. A field survey of 492 AI voice robot users in China was conducted to test our model. The results indicated that the effective use of AI voice robots was significantly associated with private value and procedural justice. However, the relationship between the effective use of AI and trust in government was not found to be significant. Surprisingly, the respondents indicated that private value had a greater effect on overall value creation than public value. This contrasts with the common idea that value creation from the government perspective suggests that social objectives requiring public value are more important to citizens. The results also show that gender and citizens with different experiences show different AI usage behaviors.

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