Data on human decision, feedback, and confidence during an artificial intelligence-assisted decision-making task

Chong, Leah; Zhang, Guanglu; Goucher-Lambert, Kosa; Kotovsky, Kenneth; Cagan, Jonathan

doi:10.1016/j.dib.2023.108884

Cited by 1 publication

(2 citation statements)

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“…This requires the establishment of a culture that promotes coordination, mutual understanding and cooperation among intraand inter-divisions of government organizations. This concept aligns with the current demand for research on human capital and procedures that are frequently overlooked (Chong et al, 2023;Chowdhury et al, 2023;Mukhuty et al, 2022). In essence, the establishment of an AI framework within governmental institutions is imperative for the progress of sustainability objectives and the facilitation of the circular economy (Danish and Senjyu, 2023;Son et al, 2023).…”

Section: Managerial Implicationsmentioning

confidence: 78%

“…The effective and efficient use of human capital has been instrumental in driving OP. According to Chong et al (2023), it has been observed that the use of AI has the potential to enhance the understanding and proficiency of decision-making and problem-solving techniques. Consequently, this can lead to an improvement in the generation of valuable insights for key decision-makers within organizational settings.…”

Section: Literature Reviewmentioning

confidence: 99%

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Artificial intelligence capabilities, dynamic capabilities and organizational creativity: contributing factors to the United Arab Emirates Government’s organizational performance

Almheiri,

Ahmad,

Abu Bakar

et al. 2024

JM2

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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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