Evidence map›Paper›PMID 39182030›Full record

ArticleBMC geriatrics2024

The paradox of aging population and firm digital transformation in China.

Hao Wang, Tao Zhang, Xi Wang, Jiansong Zheng

Abstract read
In one paragraph

Article in BMC geriatrics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

4 authors.

Hao WangFaculty of Humanities and Social Sciences, Macao Polytechnic University, Rua de Luís Gonzaga Gomes, Macao, China.
Tao ZhangFaculty of Humanities and Social Sciences, Macao Polytechnic University, Rua de Luís Gonzaga Gomes, Macao, China. taozhang@mpu.edu.mo.
Xi WangFaculty of Humanities and Social Sciences, Macao Polytechnic University, Rua de Luís Gonzaga Gomes, Macao, China.
Jiansong ZhengFaculty of Humanities and Social Sciences, Macao Polytechnic University, Rua de Luís Gonzaga Gomes, Macao, China.

Funding

Research Project of Macao Polytechnic University RP/ESCHS-03/2020
6 · The paper itself

Abstract

Although a number researchers have acknowledged that the aging population inhibits firm digital transformation, others find it promoting digital transformation in some firms. As the relevant literature to clarify such paradox is still scare, this paper wants to fill the gap regarding the labor cost theory, the capital-skill complementarity hypothesis, and the human capital externality theory. Based on the empirical tests of Chinese A-share listed companies from 2001 to 2022, this study detected a U-shaped relationship between the aging population and digital transformation. In terms of the institutional environment, higher marketization strengthens the U-shaped relationship by making the slopes on either side of it steeper. However, higher minimum wage levels weaken the U-shaped relationship. In terms of firm strategy, firms with stronger marketing capabilities strengthened the U-shaped relationship. However, firms with higher customer concentration weakened the U-shaped relationship. Overall, we enriched scholarly understanding of the impact of the aging population on digital transformation and demonstrated the dual potential impact of aging populations. Instead of assuming they are detrimental to the economy and society, positive contributions in the form of innovation and progress for companies can be detected.

Indexed as

AgingAgedChinaCommerceHumansPopulation DynamicsAging populationDigital transformationMarketing capabilityMarketizationMinimum wage

Identifiers

PMID39182030
PMCPMC11344399

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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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.