Evidence map›Paper›PMID 40478954›Full record

ArticleJournal of the knowledge economy2023

Linking Knowledge Heterogeneity with Project Performance in Digital Project Teams: The Role of Digital Capability and Knowledge Conversion.

Haijian Liu, Jichen Li, Longjun Liu

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. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

3 authors.

Haijian LiuDepartment of Business Administration, School of Business, Nanjing University, No.22 Hankou Road, Gulou District, Nanjing City, Jiangsu Province, 210093 China.
Jichen LiDepartment of Business Administration, School of Business, Nanjing University, No.22 Hankou Road, Gulou District, Nanjing City, Jiangsu Province, 210093 China.
Longjun LiuDepartment of Business Administration, School of Business, Nanjing University, No.22 Hankou Road, Gulou District, Nanjing City, Jiangsu Province, 210093 China.ORCID 0000-0002-6495-1695

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Digital project teams are constantly faced with undeniable challenges of how to improve team performance in the interactive era of knowledge economy and digital economy. This study aims to explore the mediating role of digital capability between knowledge heterogeneity and team performance and the moderating role of knowledge conversion. This study is quantitative and horizontal, focusing on digital project teams in China. The findings indicate that team knowledge heterogeneity can predict team performance, in which team digital capability plays a mediating role. Internal knowledge conversion enhances the positive relationship between team knowledge heterogeneity and capability, and further, external knowledge conversion enhances the moderating role of internal knowledge conversion. The originality of this study is that, concerning the relationship between knowledge heterogeneity and team performance, it is the first time to develop a model that regards digital capability as a mediator and knowledge conversion as a moderator. We constitute a significant contribution to the literature. Additionally, this study contains a series of practical implications which may contribute teams to a competitive advantage in emerging markets.

Indexed as

Digital capabilityDigital project teamsKnowledge conversionKnowledge heterogeneityTeam performance

Identifiers

PMID40478954
PMCPMC10009849

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.