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 27 Oct 2026, 18:55 UTC
PUBLICATIONS3In the selected collection
CROSSREF CITATIONS103/3 with known counts
OPENALEX CITATIONS113/3 with known counts
OPENALEX MEAN3.67Per article with a known count
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institution: Huazhong University of Science and Technology Remove ×country: Bangladesh 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.

View data & coverage

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

Huazhong University of Science and Technology3University of Barishal2Nanchang University13/3 records with data

Countries

Bangladesh3China33/3 records with data

Primary topics

Technology Adoption and User Behaviour1Efficiency Analysis Using DEA1Corruption and Economic Development13/3 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: 2026-10-27T18:55:35.970335+00:00. Source totals are never added together.
Research side by side

Compare journals

Select journals to compare the same collection filters. Source totals stay separate. These measures describe research activity, not journal quality.

Leave all unchecked to include every matching journal. Selection affects only comparison charts.
Display range
International Journal of Research in Business and Social Science

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 CITATIONS10
CROSSREF · CITED PUBLICATIONS100.0%
CROSSREF · MEAN CITATIONS3.33

Crossref citation coverage: 3 / 3 publications (100.0%). Latest observation: 21 Oct 2026, 07:22 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 CITATIONS11
DOI MATCH COVERAGE100.0%3 / 3 publications
MEAN · KNOWN COUNTS ONLY3.673 known · 0 unknown
MEDIAN · KNOWN COUNTS ONLY2

Observation range: 22 Oct 2026 00:59 UTC — 27 Oct 2026 18:55 UTC. Missing matches are not zero citations. Previous observations may remain if a refresh fails or a DOI no longer matches.

OpenAlex citation distributionNo citations01–526–20121+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): 2026-10-22T00:59:51.856686+00:00 — 2026-10-27T18:55:35.970335+00:00. Older observations may be retained after failed or incomplete refreshes.

OpenAlex · Citations received by year

31.50 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: 2 · Annual history coverage 3/32022 · All selected publications · OpenAlex · Citations received by year: 2 · Annual history coverage 3/32023 · All selected publications · OpenAlex · Citations received by year: 1 · Annual history coverage 3/32024 · All selected publications · OpenAlex · Citations received by year: 3 · Annual history coverage 3/32025 · All selected publications · OpenAlex · Citations received by year: 2 · Annual history coverage 3/32026 · All selected publications · OpenAlex · Citations received by year: 1 · 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 publications233/3
2022All selected publications233/3
2023All selected publications133/3
2024All selected publications333/3
2025All selected publications233/3
2026All selected publications133/3

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.

Mean3.33
Median2
No citations01–526–20121+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 Research in Business and Social Science
SSBFNET
310113/33.332100.03/3 · 100.0%

* Percentage among publications with a known citation count.

Explore publications

View all 3 →

Most cited · Crossref

JOURNAL ARTICLE

Why do citizens use e-tax system?

Md Faridur Rahman · Md. Shamim Talukder · Yang Lanrong · Abul Khayer

International Journal of Research in Business and Social Science · 2020

Read abstract

Among the various online services provided by the government, e-tax system is one of the commonly used e-government platforms, which offers significant benefits to government and citizens by reducing costs, eliminate human errors, and reduce the turnaround time for processing income tax returns. Despite these plausible benefits, some reservations have been articulated regarding the continuance usage intention of e-tax system. Thus, we investigate the most critical factors of e-tax continuance usage in this paper. We developed an integrated theoretical model based on the technology continuance theory (TCT) extended with social influence and perceived risk. The proposed conceptual model was empirically validated with data collected from a sample of 345 e-tax service users in Bangladesh. Partial least squares structural equation modeling (PLS-SEM) was employed to analyze the collected data. The study findings suggest that user satisfaction, perceived usefulness, and attitude have a direct impact on continuance usage intention where confirmation, ease of use and social influence have indirect influence on continuance usage intention of e-tax system. This paper discusses some contributions to theory and practice based on our findings

DOI 10.20525/ijrbs.v9i7.9467 Crossref citations8 OpenAlex citations
JOURNAL ARTICLE

The macroeconomic determinants of cross-country efficiency in wealth maximization

Md Harun Or Rosid · Zhao Xuefeng · Sujan Chandra Paul · Md Reza Sultanuzzaman

International Journal of Research in Business and Social Science · 2020

Read abstract

In the arena of economic analysis, the wealth of a nation is getting more and more attention to be a better indicator to evaluate the status of an economy. This paper had studied the aggregate household wealth of different nations of the world, 106 countries, for the year 2009-2018. During these years, only two countries of the world, China and the USA have managed to increase their wealth tremendously over the last decade while others experienced a slow pace in the growth of wealth. To satisfy the query of how efficient these countries were in maximizing their wealth, a stochastic frontier approach (SFA) has been used to predict the technical efficiency dependent variable and then generalized methods of moments (GMM) and other models have been used to find out the determinants of this efficiency. The study had come up with the result that land, labor, and capital mainly contributed to the output of wealth maximization while past year level of efficiency, export, and import played the main roles in determining the wealth maximizing efficiency status of a nation. It is found that there is a negative relationship between past-year efficiency with current years and the more a country imports, the less efficient the country is while the more it exports, the more efficient the country is in maximizing wealth. 

DOI 10.20525/ijrbs.v9i6.8942 Crossref citations2 OpenAlex citations
JOURNAL ARTICLE

Impact of democracy on literacy rate

Md Arif Hosen · Sujan Chandra Paul · Md Harun Or Rosid

International Journal of Research in Business and Social Science · 2020

Read abstract

This study investigates the impact of democracy indices on the literacy rate. Panel Data of 134 Countries from 2007-2018 were collected from the website the World Bank and Gapminder. This study uses Ordinary Least Square (OLS), Pooled Ordinary Least Square (POLS), Driscoll-Kraay (DK), Second Stage Least Square (2SLS), Generalized Methods of Moments (GMM) methods. This research has found that political participation index and political culture index has a significant positive relationship with literacy rate in all the method. The functioning of the government index has a significant positive relationship and electoral process and the pluralism index has a significant negative relationship with literacy rate in all the methods except the GMM method. The civil liberties index has a significant negative relationship with literacy rate in POLS and in the other models, there is no significant relationship between the civil liberties index and literacy rate.

DOI 10.20525/ijrbs.v9i7.9681 Crossref citations1 OpenAlex citations

Selected results

JOURNAL ARTICLE

Why do citizens use e-tax system?

Md Faridur Rahman · Md. Shamim Talukder · Yang Lanrong · Abul Khayer

International Journal of Research in Business and Social Science · 2020

Read abstract

Among the various online services provided by the government, e-tax system is one of the commonly used e-government platforms, which offers significant benefits to government and citizens by reducing costs, eliminate human errors, and reduce the turnaround time for processing income tax returns. Despite these plausible benefits, some reservations have been articulated regarding the continuance usage intention of e-tax system. Thus, we investigate the most critical factors of e-tax continuance usage in this paper. We developed an integrated theoretical model based on the technology continuance theory (TCT) extended with social influence and perceived risk. The proposed conceptual model was empirically validated with data collected from a sample of 345 e-tax service users in Bangladesh. Partial least squares structural equation modeling (PLS-SEM) was employed to analyze the collected data. The study findings suggest that user satisfaction, perceived usefulness, and attitude have a direct impact on continuance usage intention where confirmation, ease of use and social influence have indirect influence on continuance usage intention of e-tax system. This paper discusses some contributions to theory and practice based on our findings

DOI 10.20525/ijrbs.v9i7.9467 Crossref citations8 OpenAlex citations
JOURNAL ARTICLE

Impact of democracy on literacy rate

Md Arif Hosen · Sujan Chandra Paul · Md Harun Or Rosid

International Journal of Research in Business and Social Science · 2020

Read abstract

This study investigates the impact of democracy indices on the literacy rate. Panel Data of 134 Countries from 2007-2018 were collected from the website the World Bank and Gapminder. This study uses Ordinary Least Square (OLS), Pooled Ordinary Least Square (POLS), Driscoll-Kraay (DK), Second Stage Least Square (2SLS), Generalized Methods of Moments (GMM) methods. This research has found that political participation index and political culture index has a significant positive relationship with literacy rate in all the method. The functioning of the government index has a significant positive relationship and electoral process and the pluralism index has a significant negative relationship with literacy rate in all the methods except the GMM method. The civil liberties index has a significant negative relationship with literacy rate in POLS and in the other models, there is no significant relationship between the civil liberties index and literacy rate.

DOI 10.20525/ijrbs.v9i7.9681 Crossref citations1 OpenAlex citations
JOURNAL ARTICLE

The macroeconomic determinants of cross-country efficiency in wealth maximization

Md Harun Or Rosid · Zhao Xuefeng · Sujan Chandra Paul · Md Reza Sultanuzzaman

International Journal of Research in Business and Social Science · 2020

Read abstract

In the arena of economic analysis, the wealth of a nation is getting more and more attention to be a better indicator to evaluate the status of an economy. This paper had studied the aggregate household wealth of different nations of the world, 106 countries, for the year 2009-2018. During these years, only two countries of the world, China and the USA have managed to increase their wealth tremendously over the last decade while others experienced a slow pace in the growth of wealth. To satisfy the query of how efficient these countries were in maximizing their wealth, a stochastic frontier approach (SFA) has been used to predict the technical efficiency dependent variable and then generalized methods of moments (GMM) and other models have been used to find out the determinants of this efficiency. The study had come up with the result that land, labor, and capital mainly contributed to the output of wealth maximization while past year level of efficiency, export, and import played the main roles in determining the wealth maximizing efficiency status of a nation. It is found that there is a negative relationship between past-year efficiency with current years and the more a country imports, the less efficient the country is while the more it exports, the more efficient the country is in maximizing wealth. 

DOI 10.20525/ijrbs.v9i6.8942 Crossref citations2 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 07:22 UTC · ijrbscomplete · ijrbs · 21 Oct 2026 07:22 UTC
ojs-rest21 Oct 2026 07:22 UTC · ijrbscomplete · ijrbs · 21 Oct 2026 06:46 UTC
oai-pmh20 Oct 2026 19:55 UTC · ijrbscomplete · ijrbs · 20 Oct 2026 19:50 UTC
openalex-enrichment21 Oct 2026 07:23 UTC · ijrbscomplete · ijrbs · 21 Oct 2026 07:22 UTC
Full import history & methodology →