Evidence map›Paper›PMID 36425841›Full record

ArticleFrontiers in psychology2022

Management or technology? Firms' embeddedness in dual talent flow networks and their innovation performance.

Bo Sun, Ao Ruan, Biyu Peng, Shanshi Liu

Abstract read
In one paragraph

Article in Frontiers in psychology, 2022. 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

4 authors.

Bo SunSchool of Economics and Management, South China Normal University, Guangzhou, China.
Ao RuanInternational Business School, South China Normal University, Guangzhou, China.
Biyu PengInternational Business School, South China Normal University, Guangzhou, China.
Shanshi LiuSchool of Business Administration, South China University of Technology, Guangzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This paper examines the complex relationship between different types of talent flow networks and firms' innovation. Based on the social network theory and human capital theory, we divide the talent flow networks into "management talent flow networks" and "technical talent flow networks". The paper then investigates the potential interacting effect and matching effect between the two types of networks when they influence the innovation of firms. The empirical results, which draw from LinkedIn (China) resume data show that: (1) in both management talent flow networks and technical talent flow networks, higher degree of centrality and larger structural hole indexes can enhance firms' innovation performance; (2) there is significant interacting effect between management talent flow networks and technical talent flow networks in their influence on firms' innovation. That is, the interaction between firms' centrality in management talent flow networks and technical talent flow networks, and the interaction between firms' structural hole indexes in the two networks can both enhance their innovation performance; (3) there is also noteworthy matching effect between the two network types. That is, firms with balanced degree centrality (high-high, or low-low) and balanced structural hole indexes (high-high, or low-low) in management talent flow networks and technical talent flow networks exhibit better innovation performance than those with imbalanced degree centrality (high-low, or low-high) and structural hole indexes (high-low, or low-high) in the two networks. This paper contributes to the classification research on talent flow networks, and deepens our understanding of the complex influencing mechanism between talent flow networks and firms' innovation. Moreover, it provides managerial implications for firms to improve innovation performance

Indexed as

dual networksfirms’ innovation performancemanagement talent flowresume datatechnical talent flow

Identifiers

PMID36425841
PMCPMC9679641

What OpenQuestion holds

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Registered trials

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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.