Evidence map›Paper›PMID 42343541›Full record

ArticleJournal of advanced research2026

Impact of technological heterogeneity on economic efficiency and total factor productivity change in developed and developing G20 economies.

Wasi Ul Hassan Shah, Gang Hao, Rizwana Yasmeen, Hong Yan, Heshan Sameera Kankanam Pathiranage, Qian Yang

Abstract read
In one paragraph

Article in Journal of advanced research, 2026. 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. From copper imbalance to immunometabolic remodeling: cuproptosis-related vulnerability and therapeutic hypotheses in autoimmune diseases.Inflammation research : official journal of the European Histamine Research Society ... [et al.] · 2026
    Review
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

6 authors.

Wasi Ul Hassan ShahSchool of Economics and Management, Zhejiang Shuren University, Hangzhou 310015, China. Electronic address: wasiulhassanshah@zjsru.edu.cn.
Gang HaoDepartment of Management Sciences, City University of Hong Kong, China. Electronic address: msghao@city.edu.hk.
Rizwana YasmeenSchool of Economics and Management, Panzhihua University, Panzhihua 617000 Sichuan, China. Electronic address: rizwana_239@yahoo.com.
Hong YanSchool of Economics and Management, Zhejiang Shuren University, Hangzhou 310015, China. Electronic address: yanhong@zjsru.edu.cn.
Heshan Sameera Kankanam PathiranageDepartment of Business Management, Sri Lanka Institute of Information Technology, Malabe, Sri Lanka. Electronic address: heshan.s@sliit.lk.
Qian YangSchool of Humanities and Foreign Languages, Zhejiang Shuren University, Hangzhou 310015, China. Electronic address: yang_qian_a@163.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionThe G20 economies, comprising both developed and developing nations, exhibit significant economic efficiency and technological advancement disparities. Understanding these differences is critical for fostering sustainable growth, particularly optimizing resource utilization and narrowing technological gaps.

objectivesThis study evaluates economic efficiency, technological heterogeneity, and total factor productivity change (TFPC) among G20 economies from 1997 to 2022. It distinguishes between developed and developing nations to identify key challenges and opportunities for productivity enhancement.

methodsWe assess economic efficiency using Data Envelopment Analysis (DEA) with the Super-SBM model. Meta-Frontier Analysis measures technological disparities, while the Malmquist-Luenberger Productivity Index (MLI) decomposes TFPC into efficiency change (EC) and technological change (TC).

resultsThe mean Meta-frontier efficiency score for G20 countries is 0.9556, indicating a 4.44% improvement potential. Developed economies (e.g., the U.S., Australia) exhibit optimal efficiency, whereas developing nations (e.g., Russia, China, India) lag due to slower technological integration. The Meta-Technology Ratio (MTR) reveals pronounced disparities, with developed economies scoring near 1, while emerging economies range between 0.8 and 0.9. Efficiency change (EC) drives productivity growth more substantially than technological change (TC).

conclusionNarrowing technological gaps, improving resource efficiency, and fostering innovation are vital for sustained economic development, particularly in emerging G20 economies. Policy recommendations include prioritizing R&D investments, technological advancement, and international collaboration to promote equitable and sustainable growth.

Indexed as

DEAEconomic efficiencyG20 economiesTechnology heterogeneityTotal factor productivity

Identifiers

PMID42343541
PMCPMC13316493

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.