Evidence map›Paper›PMID 40478985›Full record

ArticleJournal of the knowledge economy2023

Influence of Employees' Intention to Adopt AI Applications and Big Data Analytical Capability on Operational Performance in the High-Tech Firms.

Chi-Hsiang Chen

Abstract read
In one paragraph

Article in Journal of the knowledge economy, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

1 author.

Chi-Hsiang ChenDepartment of Business Administration, Tamkang University, No.151, Yingzhuan Rd., Tamsui Dist, New Taipei City, 251301 Taiwan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

As the application of artificial intelligence (AI) becomes more prevalent, it has attracted the attention of high-tech firms, which adopt AI applications in response to emerging societal, technological, and environmental challenges. In the AI application processes, big data analytical capacity has become increasingly important. Although AI may potentially revolutionise the markets, industries, and general business activities, the question remains how high-tech firms can implement AI in their operations effectively and efficiently, so as to enhance their operational performances. This study aims to explore whether high-tech firm employees' intention to adopt AI applications and the firms' big data analytical capability would affect the operational performance. Besides utilising the unified theory of acceptance and use of technology as a framework, this study also adopted the structural equation modelling (SEM) and related statistical analyses (using SPSS and LISREL). The results show that employees' intention to adopt AI applications is positively related to integration capability and team collaboration, and big data analytical capability is positively related to integration capability but not to team collaboration. Moreover, both integration capability and team collaboration are positively correlated with operational performance.

Indexed as

AI applicationCollaborationHigh-tech firmIntentionOperational performance

Identifiers

PMID40478985
PMCPMC10039443

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.