动态能力
创造力
业务
组织学习
知识管理
政府(语言学)
组织绩效
组织承诺
组织行为学
计算机科学
产业组织
管理
公共关系
政治学
心理学
经济
社会心理学
语言学
哲学
作者
Hamad Mohamed Almheiri,Syed Zamberi Ahmad,Abdul Rahim Abu Bakar,Khalizani Khalid
标识
DOI:10.1108/jm2-11-2022-0272
摘要
Purpose This study aims to assess the effectiveness of a scale measuring artificial intelligence capabilities by using the resource-based theory. It seeks to examine the impact of these capabilities on the organizational-level resources of dynamic capabilities and organizational creativity, ultimately influencing the overall performance of government organizations. Design/methodology/approach The calibration of artificial intelligence capabilities scale was conducted using a combination of qualitative and quantitative analysis tools. A set of 26 initial items was formed in the qualitative study. In the quantitative study, self-reported data obtained from 344 public managers was used for the purposes of refining and validating the scale. Hypothesis testing is carried out to examine the relationship between theoretical constructs for the purpose of nomological testing. Findings Results provide empirical evidence that the presence of artificial intelligence capabilities positively and significantly impacts dynamic capabilities, organizational creativity and performance. Dynamic capabilities also found to partially mediate artificial intelligence capabilities relationship with organizational creativity and performance, and organizational creativity partially mediates dynamic capabilities – organizational creativity link. Practical implications The application of artificial intelligence holds promise for improving decision-making and problem-solving processes, thereby increasing the perceived value of public service. This can be achieved through the implementation of regulatory frameworks that serve as a blueprint for enhancing value and performance. Originality/value There are a limited number of studies on artificial intelligence capabilities conducted in the government sector, and these studies often present conflicting and inconclusive findings. Moreover, these studies indicate literature has not adequately explored the significance of organizational-level complementarity resources in facilitating the development of unique capabilities within government organizations. This paper presents a framework that can be used by government organizations to assess their artificial intelligence capabilities-organizational performance relation, drawing on the resource-based theory.
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