Evidence map›Paper›PMID 37163532›Full record

ArticlePloS one2023

Using Artificial Intelligence (AI) to predict organizational agility.

Niusha Shafiabady, Nick Hadjinicolaou, Fareed Ud Din, Binayak Bhandari, Robert M X Wu, James Vakilian

Abstract read
In one paragraph

Article in PloS one, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 1 pooled it
–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

7 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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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

6 authors.

Niusha ShafiabadyFaculty of Science and Technology, Charles Darwin University, Haymarket, NSW, Australia.ORCID 0000-0001-7668-8524
Nick HadjinicolaouGlobal Project Management, Torrens University Australia, Adelaide, SA, Australia.
Fareed Ud DinFaculty of Science, Agriculture, Business and Law, School of Science & Technology, The University of New England, Armidale, NSW, Australia.ORCID 0000-0001-6122-2043
Binayak BhandariARC Training Centre for Automated Manufacture of Advanced Composites, The University of New South Wales, Sydney, NSW, Australia.
Robert M X WuSchool of Engineering and Technology, Central Queensland University, Rockhampton, Queensland, Australia.
James VakilianDesign and Creative Technology, Torrens University Australia, Sydney, NSW, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Since the pandemic organizations have been required to build agility to manage risks, stakeholder engagement, improve capabilities and maturity levels to deliver on strategy. Not only is there a requirement to improve performance, a focus on employee engagement and increased use of technology have surfaced as important factors to remain competitive in the new world. Consideration of the strategic horizon, strategic foresight and support structures is required to manage critical factors for the formulation, execution and transformation of strategy. Strategic foresight and Artificial Intelligence modelling are ways to predict an organizations future agility and potential through modelling of attributes, characteristics, practices, support structures, maturity levels and other aspects of future change. The application of this can support the development of required new competencies, skills and capabilities, use of tools and develop a culture of adaptation to improve engagement and performance to successfully deliver on strategy. In this paper we apply an Artificial Intelligence model to predict an organizations level of future agility that can be used to proactively make changes to support improving the level of agility. We also explore the barriers and benefits of improved organizational agility. The research data was collected from 44 respondents in public and private Australian industry sectors. These research findings together with findings from previous studies identify practices and characteristics that contribute to organizational agility for success. This paper contributes to the ongoing discourse of these principles, practices, attributes and characteristics that will help overcome some of the barriers for organizations with limited resources to build a framework and culture of agility to deliver on strategy in a changing world.

Indexed as

Artificial IntelligenceTechnologyAustraliaWork Engagement

Identifiers

PMID37163532
PMCPMC10171664

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.