CiteNScope — Scholarly Index & Analytics
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CiteNScope / Analytics

Explore the evidence.
Understand the reach.

Research across participating journals · All insights follow your collection filters.

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OpenAlex coverage 100.0% · 3/3 recordsLast OpenAlex observation 22 Oct 2026, 05:18 UTC
PUBLICATIONS3In the selected collection
CROSSREF CITATIONS03/3 with known counts
OPENALEX CITATIONS03/3 with known counts
OPENALEX MEAN0.0Per article with a known count
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topic: Global trade and economics Remove ×
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Output and reach

Publication activity alongside incoming citations.

Publication activity

Articles grouped by publication year

Publications

Hover over a year or focus the chart and use arrow keys to inspect values.

2026 is year to date. 0 undated publications excluded.

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Citations received

OpenAlex · year of the citing work

OpenAlex

Hover over a year or focus the chart and use arrow keys to inspect values.

2017–2026 annual-history window. 2026 is year to date. Unknown years have gaps.

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Research landscape

Leading affiliations and themes in this collection.

Full distributions & methodology ↓

Institutions

University of Port Harcourt1Budapest University of Economics and Business1Cihan University-Erbil13/3 records with data

Countries

Hungary1Iraq1Nigeria13/3 records with data

Primary topics

Global trade and economics33/3 records with data
Two perspectives on citations

Follow the research impact

Independent sources. Clear time scales.

Lifetime citations by publication year

Crossref and OpenAlex · separate totals for the same publication cohorts

Hover over a year or focus the chart and use arrow keys to inspect values.

Latest lifetime totals, grouped by the cited article’s year. These are not citations received in that year.

View data & coverage

Citations received each year

OpenAlex · incoming citation links grouped by citing-work year

OpenAlex

Hover over a year or focus the chart and use arrow keys to inspect values.

2017–2026 annual-history window. 2026 is year to date. Unknown years have gaps.

View data & coverage
Annual history: 3/3 articles. Latest history observation: 2026-10-22T05:18:13.825866+00:00. Source totals are never added together.
Research side by side

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Display range
International Journal of Finance & Banking Studies

Publications

Articles by publication year

View data & coverage

Crossref citations

Latest lifetime totals · grouped by publication year

View data & coverage

OpenAlex citations

Latest lifetime totals · grouped by publication year

View data & coverage

OpenAlex · Citations received

By year of the citing work · 2017–2026

View data & coverage

2026 is year to date. Crossref and OpenAlex lifetime charts share a citation scale. Unknown observations appear as gaps; known zero stays zero. Annual receipts use available OpenAlex histories and may not sum to lifetime totals. 0 undated publications excluded from publication-year charts.

Full analytics report All distributions, publications, comparisons & data provenance
3 MATCHING PUBLICATIONSExplore results →Export CSV ↓
INDEXED PUBLICATIONS3
CROSSREF CITATIONS0
CROSSREF · CITED PUBLICATIONS0.0%
CROSSREF · MEAN CITATIONS0.0

Crossref citation coverage: 3 / 3 publications (100.0%). Latest observation: 21 Oct 2026, 00:21 UTC. Means and percentages use records with known counts.

OpenAlex / Separate citation source

A broader view of this research

DOI-matched OpenAlex observations for the same selected publications. These counts are separate from Crossref and are never added together.

OPENALEX CITATIONS0
DOI MATCH COVERAGE100.0%3 / 3 publications
MEAN · KNOWN COUNTS ONLY0.03 known · 0 unknown
MEDIAN · KNOWN COUNTS ONLY0

Observation range: 22 Oct 2026 01:21 UTC — 22 Oct 2026 05:18 UTC. Missing matches are not zero citations. Previous observations may remain if a refresh fails or a DOI no longer matches.

OpenAlex citation distributionNo citations31–506–20021+0Unknown0

Institutions, countries & topics

OpenAlex affiliations and primary-topic classification. Each publication counts once per institution or country; multi-affiliated publications appear in multiple groups, so percentages can sum above 100%. Countries describe author affiliations, not nationality. Topics use one primary topic per publication.

Institutions

3 / 3 with data · 0 missing or unmatched. Percentages use all 3 selected publications.

Countries

3 / 3 with data · 0 missing or unmatched. Percentages use all 3 selected publications.

Primary topics

3 / 3 with data · 0 missing or unmatched. Percentages use all 3 selected publications.

Citation year / OpenAlex

Citations received over time

Incoming citations to the selected publications, grouped by the year of the citing work. This is separate from lifetime citation totals grouped by the cited article’s publication year.

The publication filters above define which articles receive the citations. The citation-year range below only controls this chart and the incoming-citation comparison. Removing publication-year filters includes older articles’ incoming citations too.

Annual history available for 3 / 3 selected publications. Supported display window: 2017–2026; 2026 is incomplete. Within a successfully fetched ten-year window, omitted years mean zero. Missing histories and years beyond a saved observation’s window remain unknown (—); partial coverage can understate totals.

Annual-history observations (UTC): 2026-10-22T01:21:43.213905+00:00 — 2026-10-22T05:18:13.825866+00:00. Older observations may be retained after failed or incomplete refreshes.

OpenAlex · Citations received by year

10.50 2017 · All selected publications · OpenAlex · Citations received by year: 0 · Annual history coverage 3/32018 · All selected publications · OpenAlex · Citations received by year: 0 · Annual history coverage 3/32019 · All selected publications · OpenAlex · Citations received by year: 0 · Annual history coverage 3/32020 · All selected publications · OpenAlex · Citations received by year: 0 · Annual history coverage 3/32021 · All selected publications · OpenAlex · Citations received by year: 0 · Annual history coverage 3/32022 · All selected publications · OpenAlex · Citations received by year: 0 · Annual history coverage 3/32023 · All selected publications · OpenAlex · Citations received by year: 0 · Annual history coverage 3/32024 · All selected publications · OpenAlex · Citations received by year: 0 · Annual history coverage 3/32025 · All selected publications · OpenAlex · Citations received by year: 0 · Annual history coverage 3/32026 · All selected publications · OpenAlex · Citations received by year: 0 · Annual history coverage 3/3 2017201820192020202120222023202420252026
View openalex · citations received by year data & coverage
Citation yearJournal / scopeOpenAlex · Citations received by yearPublicationsAnnual history known
2017All selected publications033/3
2018All selected publications033/3
2019All selected publications033/3
2020All selected publications033/3
2021All selected publications033/3
2022All selected publications033/3
2023All selected publications033/3
2024All selected publications033/3
2025All selected publications033/3
2026All selected publications033/3

Counts represent citation links, not unique citing papers across a journal: one paper citing two selected articles contributes two links. Older citations outside this window are excluded, so annual sums need not equal lifetime totals. OpenAlex methodology ↗

Crossref citation distribution

Latest Crossref totals for the selected publications; not citations received in the selected years.

Mean0.0
Median0
No citations31–506–20021+0Unknown0

Unknown counts are excluded from the mean, median and cited-publication rate.

Journal comparison

Same filters, source and counting rules across journals. Descriptive statistics, not a quality ranking.

Journal / publisherPublicationsCrossref citationsOpenAlex citationsOpenAlex coverageCrossref meanCrossref medianCrossref cited %*Crossref coverage
International Journal of Finance & Banking Studies
SSBFNET
3003/30.000.03/3 · 100.0%

* Percentage among publications with a known citation count.

Explore publications

View all 3 →

Most cited · Crossref

JOURNAL ARTICLE

Trade Liberalization and the Performance of the Manufacturing Subsector in Nigeria

Collins Onuosa · Uyu Eta · Nenubari John Ikue · Ibimna Ikemenjima

International Journal of Finance & Banking Studies · 2024

Read abstract

Trade liberalization is a widely accepted policy for fostering economic growth, particularly in developing countries. Advocates argue that open economies, through increased competition, specialization, and access to global markets, outperform closed economies. However, the short-term effects on developing economies like Nigeria remain debated, especially within the manufacturing sector. Nigeria's trade policy has fluctuated between protectionism and openness, significantly influencing its manufacturing performance. Critics, drawing from dependency theory, argue that liberalization exposes weaker economies to exploitation by stronger nations, leading to trade imbalances and inhibiting industrial growth. This study investigates the nonlinear effects of trade liberalization on Nigeria’s manufacturing sector, addressing a gap in the literature by employing a quadratic approach to determine threshold effects. By incorporating a quadratic form of the trade variable, the study tests the hypothesis that trade liberalization initially boosts the manufacturing sector but results in diminishing returns as openness intensifies. The research is framed within the Laffer Curve of Trade, suggesting that beyond a certain threshold, excessive openness may harm the manufacturing sector. The AutoRegressive Distributed Lag (ARDL) model is used to assess both short-run and long-run effects, with findings indicating a convex relationship between trade liberalization and manufacturing output, highlighting the critical importance of identifying optimal policy thresholds to maximize industrial growth. 

DOI 10.20525/ijfbs.v13i3.36450 Crossref citations0 OpenAlex citations
JOURNAL ARTICLE

Shift in the Importance of Consumption of Professional Services and Investments (GFCF) for Manufacturing Industries by R&D Intensity in Advanced Economies

Anastasiia Alekhnovich · Leonid Anuchin

International Journal of Finance & Banking Studies · 2024

Read abstract

The research revealed and analysed a trend, between 1995-2020, of a declining gross fixed capital formation (GFCF) to domestic value added in gross exports (DVA in Gross exports) ratio in manufacturing industries for most Advanced Economies, which occurred on the backdrop of increasing of intermediate consumption of professional services. Our model proves the partial substitution of GFCF with intermediate consumption of professional services in Advanced Economies due to the change of production operating model (value chain management in manufacturing industries), which is evidenced by high influence of the combined factor on the DVA in Gross exports. This substitution facilitates the upgrading of value chain by creation of backward and forward linkages for manufacturing industries, depending on their R&D intensity. Systemic and long-term nature of changes may reflect potential paradigm shift in Advanced Economies' production operating models. 

DOI 10.20525/ijfbs.v13i3.36700 Crossref citations0 OpenAlex citations
JOURNAL ARTICLE

The Impact of NTMs on Trade

Masoud Ali Khalid · Narmen Ghafor

International Journal of Finance & Banking Studies · 2019

Read abstract

Non-tariff measures such as food safety and technical standards are used to achieve the non-trade objective of protecting consumers’ health and safety. On the other hand, they can also be deployed as a trade secure tool to drive a price wedge between foreign and domestic producers. This study investigates the protectionist tools of 34 developing countries food safety standards using a sample of developing countries food imported from developed and other developing countries with a specific focus on vegetables, Trunks, machinery, and tobacco. We employ theoretical framework of gravity equation by applying SGMM estimation. Our results indicate that vegetable and machinery variables are negative and statistically significant. Meaning that both variables have a negative impact on GDP, in other words, both variables are not support GDP and economic growth in the developing countries. Finally, Trunk variable is positive and statistically significant. It shows that, this variable leads to promote economic growth in the developing countries. While Tobacco is positive and statistically insignificant, meaning that this product is not play an important role in the trade sector in our sample countries.

DOI 10.20525/ijfbs.v8i1.2800 Crossref citations0 OpenAlex citations

Selected results

JOURNAL ARTICLE

Trade Liberalization and the Performance of the Manufacturing Subsector in Nigeria

Collins Onuosa · Uyu Eta · Nenubari John Ikue · Ibimna Ikemenjima

International Journal of Finance & Banking Studies · 2024

Read abstract

Trade liberalization is a widely accepted policy for fostering economic growth, particularly in developing countries. Advocates argue that open economies, through increased competition, specialization, and access to global markets, outperform closed economies. However, the short-term effects on developing economies like Nigeria remain debated, especially within the manufacturing sector. Nigeria's trade policy has fluctuated between protectionism and openness, significantly influencing its manufacturing performance. Critics, drawing from dependency theory, argue that liberalization exposes weaker economies to exploitation by stronger nations, leading to trade imbalances and inhibiting industrial growth. This study investigates the nonlinear effects of trade liberalization on Nigeria’s manufacturing sector, addressing a gap in the literature by employing a quadratic approach to determine threshold effects. By incorporating a quadratic form of the trade variable, the study tests the hypothesis that trade liberalization initially boosts the manufacturing sector but results in diminishing returns as openness intensifies. The research is framed within the Laffer Curve of Trade, suggesting that beyond a certain threshold, excessive openness may harm the manufacturing sector. The AutoRegressive Distributed Lag (ARDL) model is used to assess both short-run and long-run effects, with findings indicating a convex relationship between trade liberalization and manufacturing output, highlighting the critical importance of identifying optimal policy thresholds to maximize industrial growth. 

DOI 10.20525/ijfbs.v13i3.36450 Crossref citations0 OpenAlex citations
JOURNAL ARTICLE

Shift in the Importance of Consumption of Professional Services and Investments (GFCF) for Manufacturing Industries by R&D Intensity in Advanced Economies

Anastasiia Alekhnovich · Leonid Anuchin

International Journal of Finance & Banking Studies · 2024

Read abstract

The research revealed and analysed a trend, between 1995-2020, of a declining gross fixed capital formation (GFCF) to domestic value added in gross exports (DVA in Gross exports) ratio in manufacturing industries for most Advanced Economies, which occurred on the backdrop of increasing of intermediate consumption of professional services. Our model proves the partial substitution of GFCF with intermediate consumption of professional services in Advanced Economies due to the change of production operating model (value chain management in manufacturing industries), which is evidenced by high influence of the combined factor on the DVA in Gross exports. This substitution facilitates the upgrading of value chain by creation of backward and forward linkages for manufacturing industries, depending on their R&D intensity. Systemic and long-term nature of changes may reflect potential paradigm shift in Advanced Economies' production operating models. 

DOI 10.20525/ijfbs.v13i3.36700 Crossref citations0 OpenAlex citations
JOURNAL ARTICLE

The Impact of NTMs on Trade

Masoud Ali Khalid · Narmen Ghafor

International Journal of Finance & Banking Studies · 2019

Read abstract

Non-tariff measures such as food safety and technical standards are used to achieve the non-trade objective of protecting consumers’ health and safety. On the other hand, they can also be deployed as a trade secure tool to drive a price wedge between foreign and domestic producers. This study investigates the protectionist tools of 34 developing countries food safety standards using a sample of developing countries food imported from developed and other developing countries with a specific focus on vegetables, Trunks, machinery, and tobacco. We employ theoretical framework of gravity equation by applying SGMM estimation. Our results indicate that vegetable and machinery variables are negative and statistically significant. Meaning that both variables have a negative impact on GDP, in other words, both variables are not support GDP and economic growth in the developing countries. Finally, Trunk variable is positive and statistically significant. It shows that, this variable leads to promote economic growth in the developing countries. While Tobacco is positive and statistically insignificant, meaning that this product is not play an important role in the trade sector in our sample countries.

DOI 10.20525/ijfbs.v8i1.2800 Crossref citations0 OpenAlex citations

Data coverage & freshness

Source coverage refers to this result set; a publication may occur in several sources. Sync times refer to contributing journals.

Missing abstracts: 0 · Missing authors: 0 · Missing publication dates: 0 · Dates without day precision: 0

SourceMost recent successful journal syncLatest attempt
crossref21 Oct 2026 00:21 UTC · ijfbscomplete · ijfbs · 21 Oct 2026 00:21 UTC
ojs-rest21 Oct 2026 00:21 UTC · ijfbscomplete · ijfbs · 21 Oct 2026 00:14 UTC
oai-pmh20 Oct 2026 19:56 UTC · ijfbscomplete · ijfbs · 20 Oct 2026 19:55 UTC
openalex-enrichment21 Oct 2026 00:22 UTC · ijfbscomplete · ijfbs · 21 Oct 2026 00:21 UTC
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