Evidence map›Paper›PMID 35712135›Full record

ArticleFrontiers in psychology2022

The Influence of Knowledge Base on the Dual-Innovation Performance of Firms.

Liping Zhang, Hailin Li, Chunpei Lin, Xiaoji Wan

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. 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

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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

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
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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

4 authors.

Liping ZhangCollege of Business Administration, Huaqiao University, Quanzhou, China.
Hailin LiCollege of Business Administration, Huaqiao University, Quanzhou, China.
Chunpei LinCollege of Business Administration, Huaqiao University, Quanzhou, China.
Xiaoji WanCollege of Business Administration, Huaqiao University, Quanzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Dual innovation, which includes exploratory innovation and exploitative innovation, is crucial for firms to obtain a sustainable competitive advantage. The knowledge base of firms greatly influences or even determines the scope, direction, and path of their dual-innovation activities, which drive their innovation process and produce different innovation performances. This study uses data source patents obtained by 285 focal firms in the Chinese new-energy vehicle industry in the period 2015-2020. Five knowledge-base features are selected by analyzing the correlation and multicollinearity, and four different firm clusters are found by using the k-means clustering algorithm. Based on the classification and regression tree (CART) algorithm, we mine the potential decision rules governing the dual-innovation performance of firms. The results show that the exploratory innovation performance of firms in different clusters is mainly affected by two different knowledge-base features. Knowledge-base scale is a key factor affecting the exploitative innovation performance of firms. Firms in different clusters can improve their dual-innovation performance by rationally tuning the combination of knowledge-base features.

Indexed as

CART algorithmdecision rulesdual-innovation performancek-means clusteringknowledge base

Identifiers

PMID35712135
PMCPMC9195518

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.