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: 5 / 5 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: 21 Oct 2026 00:49 UTC — 22 Oct 2026 01:37 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.
5 / 5 with data · 0 missing or unmatched. Percentages use all 5 selected publications.
5 / 5 with data · 0 missing or unmatched. Percentages use all 5 selected publications.
5 / 5 with data · 0 missing or unmatched. Percentages use all 5 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 |
|---|---|---|---|---|---|
| 2018 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 2019 | All selected publications | 0 | 0 | 0/0 | 0/0 |
| 2020 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 2021 | All selected publications | 0 | 0 | 0/0 | 0/0 |
| 2022 | All selected publications | 0 | 0 | 0/0 | 0/0 |
| 2023 | All selected publications | 3 | 3 | 3/3 | 3/3 |
| Publication year | Journal / scope | Crossref citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2018 | All selected publications | 3 | 1 | 1/1 | 1/1 |
| 2019 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2020 | All selected publications | 0 | 1 | 1/1 | 1/1 |
| 2021 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2022 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2023 | All selected publications | 2 | 3 | 3/3 | 3/3 |
| Publication year | Journal / scope | OpenAlex citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2018 | All selected publications | 11 | 1 | 1/1 | 1/1 |
| 2019 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2020 | All selected publications | 0 | 1 | 1/1 | 1/1 |
| 2021 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2022 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2023 | All selected publications | 5 | 3 | 3/3 | 3/3 |
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 5 / 5 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): 2026-10-21T00:49:30.128650+00:00 — 2026-10-22T01:37:17.794980+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 | 5 | 5/5 |
| 2018 | All selected publications | 0 | 5 | 5/5 |
| 2019 | All selected publications | 1 | 5 | 5/5 |
| 2020 | All selected publications | 0 | 5 | 5/5 |
| 2021 | All selected publications | 1 | 5 | 5/5 |
| 2022 | All selected publications | 2 | 5 | 5/5 |
| 2023 | All selected publications | 4 | 5 | 5/5 |
| 2024 | All selected publications | 5 | 5 | 5/5 |
| 2025 | All selected publications | 3 | 5 | 5/5 |
| 2026 | All selected publications | 0 | 5 | 5/5 |
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 |
|---|---|
| 2018-11 | 1 |
| 2020-07 | 1 |
| 2023-09 | 2 |
| 2023-12 | 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 | 5 | 5 | 16 | 5/5 | 1.0 | 0 | 40.0 | 5/5 · 100.0% |
* Percentage among publications with a known citation count.
A growing number of unimaginable cross-border start-up businesses have emerged in the ASEAN and global trade map, along with the development of communication and information technology that negates national borders. The new sector-referred to as creative economy - requires and utilizes high specific knowledge, skills and creativity. With literature review and descriptive analysis method, this study aims to: firstly, analyze the prospects for Indonesian creative economic sector in the ASEAN market; secondly, analyze the competitiveness of Indonesia's creative economic sector in ASEAN and the world levels. By making comparison of the data in two periods (2002-2006 and 2014-2015 periods), it can be concluded that the average contribution of creative economy to Indonesian economy continues to increase. The increase goes to the added value, the sectoral contribution to GDP, the provision of employment, and the sectoral absorption of national labor. The prospect of Indonesian creative economy in the ASEAN market lies in the growth of potential customers from the middle class. The number of Indonesian middle class will continue to increase. By adopting and analyzing the output of the Global Creativity Index model, it can be concluded that the competitiveness of Indonesian creative economy in ASEAN and the world is still weak. The weak competitiveness is due to low technology index and talent index. However, based on the findings from previous studies in several regions in Indonesia, it appears that Indonesian people have great potential creativity to develop
The creative economy is one of the world's most dynamic economic development drivers. Countries that can effectively develop and utilize the creative economy will reap substantial economic benefits. The creative economy potential in Indonesia continues to grow, including in Lebak Regency, Banten Province. Lebak Regency possesses excellent natural, cultural, and human resources. Palm sugar is one of the most well-known Lebak Regency SME products. This study aims to identify the framework for the contribution of added value to the creative economy in the regional economy as a tool for monitoring and evaluating government policies. This is a qualitative study employing an exploratory, descriptive approach. Primary data was collected through in-depth interviews with informants chosen using purposive sampling. The findings of this study indicate that the production of nira, which is processed into creative products, has the potential to increase the added value contribution of the creative economy by IDR 126 billion in 2022. Therefore, the author recommends that the government of Lebak Regency develop a program that focuses on increasing the added value of processed nira products into other creative products.
Talent development in the modern age needs to translate into self-employability. The study aims to investigate the relationship between Talent Development and Self Employability amongst Actors in the creative industry of South Africa and how Talent Development impacts Employability amongst this group. This study is important for Actors to have a framework to assist them with developing their talent for employability purposes. Underpinned by the post-positivism philosophy and using a deductive reasoning approach, the study chose a quantitative research design and Cagne’s Expanded Model of Talent Development as the theoretical framework of the study. The population of the study was the film and television Actors (N=325) as the study’s participants and accounting for the entire population. Simple random probability sampling was chosen (n=150) as it seeks to generalize the findings of the study to the entire population. The data collection tool was a 5-point self-administered structured questionnaire. The data collection instrument was pre-tested using a small sample and the data gathered was analyzed using quantitative data analysis methods which will be used for the main analysis, aided by Statistical Package for Social Sciences (SPSS) version 27. The study found a clear association between Talent Development and Self-perceived Employability with both constructs having a positive medium correlation. The main elements making a significant contribution were the Actors' cognitive abilities as well as their motivation and they needed to work on their mentorship. The finding of the study seeks to improve the theoretical understanding of talent development and further recommendations for managers within the creative industry to create formal mentorship programmes to aid upcoming Actors.
The creative economy is a field enduring extremely rapid growth. One of the areas of concern is the subsector of application and game developers due to its contribution to increasing the gross regional domestic product and creating employment opportunities, particularly in the province of DKI Jakarta, Indonesia. This paper aims to identify development models for the information and communication sector, particularly for application and game developers in DKI Jakarta. We employed a mixed-methods approach, data and information were collected from key informants selected using a technique of purposive sampling. Main findings of the study demonstrate that the dynamic system method can be used as a development model for the application sector and game developers in DKI Jakarta, as it can potentially increase the benefits of program strategies that the DKI Tourism and Creative Economy Agency will implement.
The efficiency of economic cooperation is based on its cultural understanding as well as on a tradition that is expressed through business effects promoted by products from the creative industry domain. Since the creative industry relies on project activities in a large number of sectors, it is possible to predict that one creative product can be realized in a number of creative sectors (e.g., in publishing, architecture, music, audiovisual arts, etc.). The Croatian-Chinese cultural and economic tradition is built on multi-year cooperation globally remembered by the contribution of Marco Polo, and the creative industry is an opportunity to design creative products promoting the Silk Road and the role of Marco Polo, which aims to connect the People’s Republic of China and the Republic of Croatia. This paper analyzes the contributions of the Vilijun project and its products within the creative industry and its twelve sectors. Such approach has demonstrated and analyzed the strategies of connecting the People’s Republic of China and the Republic of Croatia as the preconditions for achieving mutual economic effects and is on the trail of the 2012 “China’s Twelve Measures for Promoting Friendly Cooperation with Central and Eastern European Countries”.
Talent development in the modern age needs to translate into self-employability. The study aims to investigate the relationship between Talent Development and Self Employability amongst Actors in the creative industry of South Africa and how Talent Development impacts Employability amongst this group. This study is important for Actors to have a framework to assist them with developing their talent for employability purposes. Underpinned by the post-positivism philosophy and using a deductive reasoning approach, the study chose a quantitative research design and Cagne’s Expanded Model of Talent Development as the theoretical framework of the study. The population of the study was the film and television Actors (N=325) as the study’s participants and accounting for the entire population. Simple random probability sampling was chosen (n=150) as it seeks to generalize the findings of the study to the entire population. The data collection tool was a 5-point self-administered structured questionnaire. The data collection instrument was pre-tested using a small sample and the data gathered was analyzed using quantitative data analysis methods which will be used for the main analysis, aided by Statistical Package for Social Sciences (SPSS) version 27. The study found a clear association between Talent Development and Self-perceived Employability with both constructs having a positive medium correlation. The main elements making a significant contribution were the Actors' cognitive abilities as well as their motivation and they needed to work on their mentorship. The finding of the study seeks to improve the theoretical understanding of talent development and further recommendations for managers within the creative industry to create formal mentorship programmes to aid upcoming Actors.
The creative economy is a field enduring extremely rapid growth. One of the areas of concern is the subsector of application and game developers due to its contribution to increasing the gross regional domestic product and creating employment opportunities, particularly in the province of DKI Jakarta, Indonesia. This paper aims to identify development models for the information and communication sector, particularly for application and game developers in DKI Jakarta. We employed a mixed-methods approach, data and information were collected from key informants selected using a technique of purposive sampling. Main findings of the study demonstrate that the dynamic system method can be used as a development model for the application sector and game developers in DKI Jakarta, as it can potentially increase the benefits of program strategies that the DKI Tourism and Creative Economy Agency will implement.
The creative economy is one of the world's most dynamic economic development drivers. Countries that can effectively develop and utilize the creative economy will reap substantial economic benefits. The creative economy potential in Indonesia continues to grow, including in Lebak Regency, Banten Province. Lebak Regency possesses excellent natural, cultural, and human resources. Palm sugar is one of the most well-known Lebak Regency SME products. This study aims to identify the framework for the contribution of added value to the creative economy in the regional economy as a tool for monitoring and evaluating government policies. This is a qualitative study employing an exploratory, descriptive approach. Primary data was collected through in-depth interviews with informants chosen using purposive sampling. The findings of this study indicate that the production of nira, which is processed into creative products, has the potential to increase the added value contribution of the creative economy by IDR 126 billion in 2022. Therefore, the author recommends that the government of Lebak Regency develop a program that focuses on increasing the added value of processed nira products into other creative products.
The efficiency of economic cooperation is based on its cultural understanding as well as on a tradition that is expressed through business effects promoted by products from the creative industry domain. Since the creative industry relies on project activities in a large number of sectors, it is possible to predict that one creative product can be realized in a number of creative sectors (e.g., in publishing, architecture, music, audiovisual arts, etc.). The Croatian-Chinese cultural and economic tradition is built on multi-year cooperation globally remembered by the contribution of Marco Polo, and the creative industry is an opportunity to design creative products promoting the Silk Road and the role of Marco Polo, which aims to connect the People’s Republic of China and the Republic of Croatia. This paper analyzes the contributions of the Vilijun project and its products within the creative industry and its twelve sectors. Such approach has demonstrated and analyzed the strategies of connecting the People’s Republic of China and the Republic of Croatia as the preconditions for achieving mutual economic effects and is on the trail of the 2012 “China’s Twelve Measures for Promoting Friendly Cooperation with Central and Eastern European Countries”.
A growing number of unimaginable cross-border start-up businesses have emerged in the ASEAN and global trade map, along with the development of communication and information technology that negates national borders. The new sector-referred to as creative economy - requires and utilizes high specific knowledge, skills and creativity. With literature review and descriptive analysis method, this study aims to: firstly, analyze the prospects for Indonesian creative economic sector in the ASEAN market; secondly, analyze the competitiveness of Indonesia's creative economic sector in ASEAN and the world levels. By making comparison of the data in two periods (2002-2006 and 2014-2015 periods), it can be concluded that the average contribution of creative economy to Indonesian economy continues to increase. The increase goes to the added value, the sectoral contribution to GDP, the provision of employment, and the sectoral absorption of national labor. The prospect of Indonesian creative economy in the ASEAN market lies in the growth of potential customers from the middle class. The number of Indonesian middle class will continue to increase. By adopting and analyzing the output of the Global Creativity Index model, it can be concluded that the competitiveness of Indonesian creative economy in ASEAN and the world is still weak. The weak competitiveness is due to low technology index and talent index. However, based on the findings from previous studies in several regions in Indonesia, it appears that Indonesian people have great potential creativity to develop
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 |