Publication activity
Articles grouped by publication year
Hover over a year or focus the chart and use arrow keys to inspect values.
2026 is year to date. 0 undated publications excluded.
Research across participating journals · All insights follow your collection filters.
Publication activity alongside incoming citations.
Articles grouped by publication year
Hover over a year or focus the chart and use arrow keys to inspect values.
2026 is year to date. 0 undated publications excluded.
OpenAlex · year of the citing work
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.
Leading affiliations and themes in this collection.
Full distributions & methodology ↓Independent sources. Clear time scales.
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.
OpenAlex · incoming citation links grouped by citing-work year
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.
Select journals to compare the same collection filters. Source totals stay separate. These measures describe research activity, not journal quality.
Articles by publication year
Latest lifetime totals · grouped by publication year
Latest lifetime totals · grouped by publication year
By year of the citing work · 2017–2026
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.
Crossref citation coverage: 4 / 4 publications (100.0%). Latest observation: 21 Oct 2026, 07:22 UTC. Means and percentages use records with known counts.
DOI-matched OpenAlex observations for the same selected publications. These counts are separate from Crossref and are never added together.
Observation range: 22 Oct 2026 01:07 UTC — 22 Oct 2026 02:42 UTC. Missing matches are not zero citations. Previous observations may remain if a refresh fails or a DOI no longer matches.
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.
4 / 4 with data · 0 missing or unmatched. Percentages use all 4 selected publications.
4 / 4 with data · 0 missing or unmatched. Percentages use all 4 selected publications.
4 / 4 with data · 0 missing or unmatched. Percentages use all 4 selected publications.
Citations are the latest recorded totals for articles published in each year, not citations received during that year. Crossref and OpenAlex remain separate and share the same citation scale. 2026 is incomplete; newer articles have had less time to receive citations.
0 undated publications excluded. Unknown citation counts are shown as —, never as zero. Partial coverage can understate totals; expand each table for known / total records.
| Publication year | Journal / scope | Publications | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2021 | All selected publications | 4 | 4 | 4/4 | 4/4 |
| Publication year | Journal / scope | Crossref citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2021 | All selected publications | 4 | 4 | 4/4 | 4/4 |
| Publication year | Journal / scope | OpenAlex citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2021 | All selected publications | 5 | 4 | 4/4 | 4/4 |
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): 2026-10-22T01:07:46.470040+00:00 — 2026-10-22T02:42:25.821688+00:00. Older observations may be retained after failed or incomplete refreshes.
| Citation year | Journal / scope | OpenAlex · Citations received by year | Publications | Annual history known |
|---|---|---|---|---|
| 2017 | All selected publications | 0 | 4 | 4/4 |
| 2018 | All selected publications | 0 | 4 | 4/4 |
| 2019 | All selected publications | 0 | 4 | 4/4 |
| 2020 | All selected publications | 0 | 4 | 4/4 |
| 2021 | All selected publications | 4 | 4 | 4/4 |
| 2022 | All selected publications | 0 | 4 | 4/4 |
| 2023 | All selected publications | 0 | 4 | 4/4 |
| 2024 | All selected publications | 1 | 4 | 4/4 |
| 2025 | All selected publications | 0 | 4 | 4/4 |
| 2026 | All selected publications | 0 | 4 | 4/4 |
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 ↗
Records with full publication dates only. 2026 is an incomplete year.
| Period | Publications |
|---|---|
| 2021-03 | 1 |
| 2021-05 | 2 |
| 2021-06 | 1 |
Latest Crossref totals for the selected publications; not citations received in the selected years.
Unknown counts are excluded from the mean, median and cited-publication rate.
Same filters, source and counting rules across journals. Descriptive statistics, not a quality ranking.
| Journal / publisher | Publications | Crossref citations | OpenAlex citations | OpenAlex coverage | Crossref mean | Crossref median | Crossref cited %* | Crossref coverage |
|---|---|---|---|---|---|---|---|---|
| International Journal of Research in Business and Social Science SSBFNET | 4 | 4 | 5 | 4/4 | 1.0 | 0.5 | 50.0 | 4/4 · 100.0% |
* Percentage among publications with a known citation count.
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.
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.
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.
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.
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.
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.
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.
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.
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
| Source | Most recent successful journal sync | Latest attempt |
|---|---|---|
| crossref | 21 Oct 2026 07:22 UTC · ijrbs | complete · ijrbs · 21 Oct 2026 07:22 UTC |
| ojs-rest | 21 Oct 2026 07:22 UTC · ijrbs | complete · ijrbs · 21 Oct 2026 06:46 UTC |
| oai-pmh | 20 Oct 2026 19:55 UTC · ijrbs | complete · ijrbs · 20 Oct 2026 19:50 UTC |
| openalex-enrichment | 21 Oct 2026 07:23 UTC · ijrbs | complete · ijrbs · 21 Oct 2026 07:22 UTC |