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% · 4/4 recordsLast OpenAlex observation 22 Oct 2026, 01:07 UTC
PUBLICATIONS4In the selected collection
CROSSREF CITATIONS44/4 with known counts
OPENALEX CITATIONS54/4 with known counts
OPENALEX MEAN1.25Per article with a known count
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topic: Hydropower, Displacement, Environmental Impact 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

University of Minnesota44/4 records with data

Countries

United States44/4 records with data

Primary topics

Hydropower, Displacement, Environmental Impact44/4 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: 4/4 articles. Latest history observation: 2026-10-22T01:07:46.470040+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
4 MATCHING PUBLICATIONSExplore results →Export CSV ↓
INDEXED PUBLICATIONS4
CROSSREF CITATIONS4
CROSSREF · CITED PUBLICATIONS50.0%
CROSSREF · MEAN CITATIONS1.0

Crossref citation coverage: 4 / 4 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 CITATIONS5
DOI MATCH COVERAGE100.0%4 / 4 publications
MEAN · KNOWN COUNTS ONLY1.254 known · 0 unknown
MEDIAN · KNOWN COUNTS ONLY1.0

Observation range: 21 Oct 2026 00:49 UTC — 22 Oct 2026 01:07 UTC. Missing matches are not zero citations. Previous observations may remain if a refresh fails or a DOI no longer matches.

OpenAlex citation distributionNo citations21–526–20021+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

4 / 4 with data · 0 missing or unmatched. Percentages use all 4 selected publications.

Countries

4 / 4 with data · 0 missing or unmatched. Percentages use all 4 selected publications.

Primary topics

4 / 4 with data · 0 missing or unmatched. Percentages use all 4 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 4 / 4 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): 2026-10-21T00:49:34.953774+00:00 — 2026-10-22T01:07:46.470040+00:00. Older observations may be retained after failed or incomplete refreshes.

OpenAlex · Citations received by year

42.00 2017 · All selected publications · OpenAlex · Citations received by year: 0 · Annual history coverage 4/42018 · All selected publications · OpenAlex · Citations received by year: 0 · Annual history coverage 4/42019 · All selected publications · OpenAlex · Citations received by year: 0 · Annual history coverage 4/42020 · All selected publications · OpenAlex · Citations received by year: 0 · Annual history coverage 4/42021 · All selected publications · OpenAlex · Citations received by year: 4 · Annual history coverage 4/42022 · All selected publications · OpenAlex · Citations received by year: 0 · Annual history coverage 4/42023 · All selected publications · OpenAlex · Citations received by year: 0 · Annual history coverage 4/42024 · All selected publications · OpenAlex · Citations received by year: 1 · Annual history coverage 4/42025 · All selected publications · OpenAlex · Citations received by year: 0 · Annual history coverage 4/42026 · All selected publications · OpenAlex · Citations received by year: 0 · Annual history coverage 4/4 2017201820192020202120222023202420252026
View openalex · citations received by year data & coverage
Citation yearJournal / scopeOpenAlex · Citations received by yearPublicationsAnnual history known
2017All selected publications044/4
2018All selected publications044/4
2019All selected publications044/4
2020All selected publications044/4
2021All selected publications444/4
2022All selected publications044/4
2023All selected publications044/4
2024All selected publications144/4
2025All selected publications044/4
2026All selected publications044/4

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.

Mean1.0
Median0.5
No citations21–526–20021+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 Research in Business and Social Science
SSBFNET
4454/41.00.550.04/4 · 100.0%

* Percentage among publications with a known citation count.

Explore publications

View all 4 →

Most cited · Crossref

JOURNAL ARTICLE

Multidimensional well-being of residents affected by the Pak Mun Dam, Thailand

Pattaraphongpan Chaiyamart · William Gartner · Robert DelMas

International Journal of Research in Business and Social Science · 2021

Read abstract

Understanding the effects on the overall well-being of the communities affected by the Pak Mun Dam construction would fill in the gaps in existing knowledge and facilitate a deeper discussion of the factors that impact overall wellbeing. The Pak Mun Dam was finished in 1994 and from that point on there have been changes affecting local residents. This study attempts to understand the impact of those changes from a well-being perspective using primary data collected from residents in villages close to the dam site. Structural Equation Model (SEM) was a method for this research analysis.  Results from a structural model show that social and economic well-being are important factors that impact the overall well-being of the affected residents from the Pak Mun Dam area. Furthermore, we discuss how information from 20 items within seven dimensions of the well-being measurement model can be used to develop more efficient strategies and policies to increase well-being capital.

DOI 10.20525/ijrbs.v10i2.10573 Crossref citations3 OpenAlex citations
JOURNAL ARTICLE

Pak Mun Dam’s long term impact on local residents’ livelihood

Pattaraphongpan Chaiyamart · William Gartner · Stephan Carlson

International Journal of Research in Business and Social Science · 2021

Read abstract

Multidimensional well-being is an important method for understanding the social functioning of communities affected by the Pak Mun Dam, 26 years after its construction. This is the first quantitative research on the well-being of these communities. In six of eight well-being dimensions, the more distant communities are faring better than those in close proximity to the dam. Furthermore, 24 of 40 items that represent each dimension have statistically significant lower means in the affected community. This result shows the long-lasting nature of negative effects on communities and without appropriate policy action, negative impacts will linger preventing developmental progress from occurring.

DOI 10.20525/ijrbs.v10i3.11381 Crossref citations2 OpenAlex citations
JOURNAL ARTICLE

Well-being capital and government’s intervention to dam’s affected residents: Pak Mun Dam, Thailand

Pattaraphongpan Chaiyamart · William Gartner · Kristen Nelson

International Journal of Research in Business and Social Science · 2021

Read abstract

Government plays an important role as a well-being capital provider through policies, strategies, or even direct provision to local residents to improve their livelihoods. Pak Mun Dam is one of the most controversial dams in Thailand, and government intervention is needed to solve the issues the dam has created. This study tests the premise that government intervention will impact overall well-being only through structural means by providing strategy and policies related to social and economic well-being. Government training programs and government services will impact over all well-being through social well-being. A satisfactory solution to the Pak Mun Dam situation will impact overall well-being through economic well-being. In this study a number of items, related to different well-being dimensions, were examined. The findings suggest that appropriate policy must address the four significant items which surfaced in the economic well-being measure and ten items in the social well-being dimension.

DOI 10.20525/ijrbs.v10i4.12170 Crossref citations0 OpenAlex citations
JOURNAL ARTICLE

Marginal rate of substitution of multidimensional well-being for affected residents of the dam, Pak Mun Dam.

Pattaraphongpan Chaiyamart · William Gartner

International Journal of Research in Business and Social Science · 2021

Read abstract

The marginal rate of substitution shows that negatively affected residents of Pak Mun Dam are willing to trade three units of economic well-being to gain one more unit of social well-being. Marginal rate of substitution (MRS) provides important information to the government regarding such trade-offs. Given the limited budget and resources, the optimal point of the combination of these dimensions of well-being should be determined in order to provide better strategy and policy to improve the conditions for residents affected by the dam’s construction. Structural Equation Model (SEM) was used to find a standardized estimate of each dimension and used it for MRS calculation.  

DOI 10.20525/ijrbs.v10i3.11340 Crossref citations0 OpenAlex citations

Selected results

JOURNAL ARTICLE

Well-being capital and government’s intervention to dam’s affected residents: Pak Mun Dam, Thailand

Pattaraphongpan Chaiyamart · William Gartner · Kristen Nelson

International Journal of Research in Business and Social Science · 2021

Read abstract

Government plays an important role as a well-being capital provider through policies, strategies, or even direct provision to local residents to improve their livelihoods. Pak Mun Dam is one of the most controversial dams in Thailand, and government intervention is needed to solve the issues the dam has created. This study tests the premise that government intervention will impact overall well-being only through structural means by providing strategy and policies related to social and economic well-being. Government training programs and government services will impact over all well-being through social well-being. A satisfactory solution to the Pak Mun Dam situation will impact overall well-being through economic well-being. In this study a number of items, related to different well-being dimensions, were examined. The findings suggest that appropriate policy must address the four significant items which surfaced in the economic well-being measure and ten items in the social well-being dimension.

DOI 10.20525/ijrbs.v10i4.12170 Crossref citations0 OpenAlex citations
JOURNAL ARTICLE

Marginal rate of substitution of multidimensional well-being for affected residents of the dam, Pak Mun Dam.

Pattaraphongpan Chaiyamart · William Gartner

International Journal of Research in Business and Social Science · 2021

Read abstract

The marginal rate of substitution shows that negatively affected residents of Pak Mun Dam are willing to trade three units of economic well-being to gain one more unit of social well-being. Marginal rate of substitution (MRS) provides important information to the government regarding such trade-offs. Given the limited budget and resources, the optimal point of the combination of these dimensions of well-being should be determined in order to provide better strategy and policy to improve the conditions for residents affected by the dam’s construction. Structural Equation Model (SEM) was used to find a standardized estimate of each dimension and used it for MRS calculation.  

DOI 10.20525/ijrbs.v10i3.11340 Crossref citations0 OpenAlex citations
JOURNAL ARTICLE

Pak Mun Dam’s long term impact on local residents’ livelihood

Pattaraphongpan Chaiyamart · William Gartner · Stephan Carlson

International Journal of Research in Business and Social Science · 2021

Read abstract

Multidimensional well-being is an important method for understanding the social functioning of communities affected by the Pak Mun Dam, 26 years after its construction. This is the first quantitative research on the well-being of these communities. In six of eight well-being dimensions, the more distant communities are faring better than those in close proximity to the dam. Furthermore, 24 of 40 items that represent each dimension have statistically significant lower means in the affected community. This result shows the long-lasting nature of negative effects on communities and without appropriate policy action, negative impacts will linger preventing developmental progress from occurring.

DOI 10.20525/ijrbs.v10i3.11381 Crossref citations2 OpenAlex citations
JOURNAL ARTICLE

Multidimensional well-being of residents affected by the Pak Mun Dam, Thailand

Pattaraphongpan Chaiyamart · William Gartner · Robert DelMas

International Journal of Research in Business and Social Science · 2021

Read abstract

Understanding the effects on the overall well-being of the communities affected by the Pak Mun Dam construction would fill in the gaps in existing knowledge and facilitate a deeper discussion of the factors that impact overall wellbeing. The Pak Mun Dam was finished in 1994 and from that point on there have been changes affecting local residents. This study attempts to understand the impact of those changes from a well-being perspective using primary data collected from residents in villages close to the dam site. Structural Equation Model (SEM) was a method for this research analysis.  Results from a structural model show that social and economic well-being are important factors that impact the overall well-being of the affected residents from the Pak Mun Dam area. Furthermore, we discuss how information from 20 items within seven dimensions of the well-being measurement model can be used to develop more efficient strategies and policies to increase well-being capital.

DOI 10.20525/ijrbs.v10i2.10573 Crossref citations3 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 →