Evidence map›Paper›PMID 35571380›Full record

ArticleAnnals of operations research2022

Sustainable competitive advantage in maternal and child health institutions: a dynamic capability approach.

Haibin Yuan, Fernando A F Ferreira

Open access · bronzeAbstract read
In one paragraph

Article in Annals of operations research, 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
5.5field-weighted citation impact, top 4% of its field
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

2 citing papers in PubMed, 15 citations in OpenAlex.

  1. Trial
  2. 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

2 authors at 1 institution in 3 countries.

Haibin YuanISCTE Business School, BRU-IUL, University Institute of Lisbon, Avenida das Forças Armadas, 1649-026 Lisbon, Portugal.
Fernando A F FerreiraISCTE Business School, BRU-IUL, University Institute of Lisbon, Avenida das Forças Armadas, 1649-026 Lisbon, Portugal.ORCID 0000-0001-5208-9084
Iscte – Instituto Universitário de Lisboa · PT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

China's government has always attached great importance to protecting women and children's rights and has made a consistent effort to promote their all-round health. The on-going medical reforms in the country have resulted in a falling birth rate and rising demand for increasingly diversified, multi-level healthcare services. Maternal and child health (MCH) institutions have had to implement more extensive changes and deal with greater challenges in order to survive and develop. MCH organizations thus need to find ways to improve their competitiveness. This study integrates qualitative and quantitative business analytics methods by conducting empirical research using varied techniques, namely the Delphi method and analytic hierarchy process (AHP). A panel of experts were consulted in three rounds of surveys, and the results were processed with AHP in order to develop an evaluation indicator model of MCH institutions' competitive advantages. Ten hospitals were selected to verify the model's applicability. Sensitivity analysis confirmed that the model has good stability. The proposed model highlights that human resources have the greatest weight as a determinant of competitive advantage. The findings, therefore, concentrate on people as the core resource, suggesting that MCH institutions can acquire and maintain competitive advantages based on three dimensions: department leader development, improved scientific research capacity, and a more flexible hospital culture.

Indexed as

Business analytics methodsCompetitive advantageDynamic capabilityMaternal and child health institutionsOperational researchResource

Identifiers

PMID35571380
PMCPMC9088137
OpenAlexW4229452522

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.