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: 19 / 19 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 07:22 UTC — 23 Oct 2026 10:27 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.
19 / 19 with data · 0 missing or unmatched. Percentages use all 19 selected publications.
19 / 19 with data · 0 missing or unmatched. Percentages use all 19 selected publications.
19 / 19 with data · 0 missing or unmatched. Percentages use all 19 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 |
|---|---|---|---|---|---|
| 2020 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 2021 | All selected publications | 0 | 0 | 0/0 | 0/0 |
| 2022 | All selected publications | 4 | 4 | 4/4 | 4/4 |
| 2023 | All selected publications | 8 | 8 | 8/8 | 8/8 |
| 2024 | All selected publications | 4 | 4 | 4/4 | 4/4 |
| 2025 | All selected publications | 2 | 2 | 2/2 | 2/2 |
| Publication year | Journal / scope | Crossref citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2020 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 2021 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2022 | All selected publications | 37 | 4 | 4/4 | 4/4 |
| 2023 | All selected publications | 24 | 8 | 8/8 | 8/8 |
| 2024 | All selected publications | 4 | 4 | 4/4 | 4/4 |
| 2025 | All selected publications | 2 | 2 | 2/2 | 2/2 |
| Publication year | Journal / scope | OpenAlex citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2020 | All selected publications | 4 | 1 | 1/1 | 1/1 |
| 2021 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2022 | All selected publications | 55 | 4 | 4/4 | 4/4 |
| 2023 | All selected publications | 42 | 8 | 8/8 | 8/8 |
| 2024 | All selected publications | 5 | 4 | 4/4 | 4/4 |
| 2025 | All selected publications | 1 | 2 | 2/2 | 2/2 |
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 19 / 19 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): 2026-10-21T07:22:45.257766+00:00 — 2026-10-23T10:27:39.857611+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 | 19 | 19/19 |
| 2018 | All selected publications | 0 | 19 | 19/19 |
| 2019 | All selected publications | 0 | 19 | 19/19 |
| 2020 | All selected publications | 0 | 19 | 19/19 |
| 2021 | All selected publications | 0 | 19 | 19/19 |
| 2022 | All selected publications | 1 | 19 | 19/19 |
| 2023 | All selected publications | 20 | 19 | 19/19 |
| 2024 | All selected publications | 33 | 19 | 19/19 |
| 2025 | All selected publications | 29 | 19 | 19/19 |
| 2026 | All selected publications | 24 | 19 | 19/19 |
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 ↗
Publications by publication year. 2026 is an incomplete year.
| Period | Publications |
|---|---|
| 2020 | 1 |
| 2022 | 4 |
| 2023 | 8 |
| 2024 | 4 |
| 2025 | 2 |
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 | 19 | 68 | 107 | 19/19 | 3.58 | 1 | 78.9 | 19/19 · 100.0% |
* Percentage among publications with a known citation count.
Financial management for young entrepreneurs needs to be done because disciplined financial arrangements will be able to minimize the risk of uncertainty. Young entrepreneurs have problems with financial management behavior, that is knowledge and skills in managing finances which have an impact on financial decision-making. This study aims to see the effect of financial knowledge, financial attitudes, and personality on financial management behavior in young entrepreneurs in Malang. The approach used in this research is quantitative with an explanatory approach. This study's population is young entrepreneurs in the Brawijaya University environment. The sampling technique used purposive sampling with a sample size of 150 samples. The results of this study prove that partially financial knowledge has no significant effect on Financial Management Behavior. Financial attitudes have a significant effect on Financial Management Behavior, and personality has a significant effect on Financial Management Behavior in Young Entrepreneurs in Malang City.
Investment intention in millennials and Gen Z in Indonesia grows yearly. However, the cause of the growing enthusiasm for investment among millennials and Gen Z is recently fear of being vulnerable to Fear of Missing Out (FOMO) behaviour alone, not based on financial factors such as financial knowledge, financial well-being and financial attitude. This study aims to determine the role of financial knowledge and financial well-being on investment intention mediated by financial attitude. This research belongs to the type of explanatory research. Respondents in this study are Millennials and Gen Z generations who invest and live in Malang City. Determination of the number of samples in this study using the purposive sampling technique with a total sample of 400 respondents. Methods of collecting data using a questionnaire, then analyzed using PLS-SEM. The study results confirm that financial knowledge positively affects investment intention. Financial well-being does not affect investment intention. Financial attitude has a positive influence on investment intention. Financial knowledge and financial well-being have a positive influence on financial attitude. Financial attitude can partially mediate the relationship between financial knowledge and investment intention. In addition, financial attitude can also mediate the relationship between financial well-being and investment intentions fully. Millennials and Gen Z are expected to improve financial knowledge and attitudes to increase interest in more targeted investments. This advice will also positively impact the Financial Well-being of millennials and Gen Z in the future.
Behavioral finance elucidates how investors rationally commit errors in the process of making investment decisions as a result of cognitive and emotional biases, ultimately resulting in unfavorable investment choices. People are unable to avoid a variety of behavioral biases that have an impact on investors' investment decision-making processes. The human mind employs shortcuts and emotional filters to interpret information, leading to errors in the decision-making process. The objective of this study is to investigate and assess the impact of behavioral biases such as disposition effects, herding, and overconfidence on investment decision-making. Additionally, we will examine how financial literacy moderates these biases. The research employed a purposive sample strategy to select generation Z investors in Kediri City. The sample size of 400 respondents was determined using the Krejcie & Morgan table. This research employs the Partial Least Squares (PLS) Structural Equation Model (SEM) analysis method using the SmartPLS version 3 data processing application. The research findings indicate that the disposition effect and overconfidence exert a substantial impact on investment decision-making; however, herding does not exhibit a significant influence on investment choice-making. Financial knowledge enhances the impact of the disposition effect on investment decision-making in a positive way. Financial literacy has a negative moderating effect on the influence of herding and overconfidence on investment decision-making among Generation Z investors in Kediri City.
This research aims to know the effect of financial knowledge on firm performance; the role of financial behavior and access to finance as mediation and the role of financial risk attitude as moderation. The object of this research is the owner of small-medium enterprises, sector food and beverage in Malang. Data collection was carried out using a questionnaire of 150 respondents. Data analysis of this research uses partial least square (PLS). The finding indicates that financial knowledge has a positive and significant effect on firm performance; financial behavior mediates the relationship of financial knowledge dan firm performance; while access to finance doesn’t mediate the relationship of financial knowledge with firm performance. This research also found that financial risk attitude weakens the relationship of financial knowledge with financial behavior.
MSMEs play a vital role in global economic development, as well as being the key to most businesses and important contributors to job creation and economic development. However, amidst the uncertain business and economic situation, most MSMEs have to struggle to maintain their business performance. So efforts are needed from various parties to improve business performance in MSMEs. This research aims to test and analyze the influence of financial literacy levels on business performance, with financial access and financial risk attitudes as mediating variables. Sampling in this research used a purposive sampling technique among tofu processing industry players in Kediri City. The sample was determined using the Slovin method and a sample of 400 respondents was obtained. The method used in this research uses Structural Equation Model (SEM) Partial Least Square (PLS) analysis through the SmartPLS data processing program version 3. The results of this research show that all hypotheses are accepted. Financial literacy, access to finance and financial risk attitudes have a positive and significant effect on business performance. Financial access is able to mediate the relationship between financial literacy and financial risk attitudes, and financial risk attitudes are also able to mediate the relationship between financial literacy and business performance in the Kediri City tofu processing industry.
This study aims to examine and analyze the effect of income on financial well-being, with financial literacy serving as a mediating variable. A quantitative research approach was employed, with the object of study being the community of Poncokusumo Tourism Village. The sample size was determined using a saturated sampling technique, involving 154 respondents from the village community. Data were collected through questionnaires and analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The findings reveal that: (i) income has a significant effect on financial well-being, (ii) financial literacy significantly influences financial well-being, (iii) income positively affects financial literacy, and (iv) financial literacy mediates the relationship between income and financial well-being. Income plays a crucial role as it significantly enhances individuals' quality of life by enabling them to meet daily needs, improve living standards, and plan for future financial security. Furthermore, stable income contributes to greater economic resilience among families and fosters community development. Respondents reported a general satisfaction with their monthly income, which in turn facilitates better financial management and supports the achievement of both short-term and long-term financial goals. This study contributes to the literature by suggesting that village government institutions, non-governmental organizations, and other stakeholders should take initiatives to provide financial literacy training. Future research is encouraged to incorporate additional variables to deepen the understanding of factors influencing financial well-being.
The study aims to examine and analyze the role of financial socialization, financial attitude, and locus of control on financial behavior with financial literacy as a mediating variable. This study uses quantitative data. The object of this research is generation z in Malang city. The sample size in this study was determined using a purposive sampling technique with a total sample of 240 generation z in Malang city. The data collection method uses a questionnaire, data is analyzed using PLS-SEM. The research results show (i) financial socialization not influences financial behavior, (ii) financial attitude influences financial behavior, (iii) locus of control influences financial behavior, (iv) financial socialization, financial attitude and locus of control influences financial literacy, and finally (v) financial literacy mediates between financial socialization, financial attitude, locus of control and financial behavior. The importance of financial behavior cannot be ignored, as it plays a crucial role in achieving individual well-being and overall economic stability. Good financial behavior helps individuals manage their spending, savings, and investments wisely, so that they can achieve their short-term and long-term financial goals. This research makes a theoretical contribution by supporting the theory of Planned Behavior and for educational institutions, non-governmental organizations and other related parties can take the initiative to provide training related to financial literacy. It is hoped that future research can add new variables to influence financial behavior.
That are many factors that can influence country's economic growth. Given its important contribution to Gross Domestic Product (GDP) and job creation, it is necessary to further study what factors can affect the existence and the performance of SMEs. This study aims to analyze the effect of financial literacy and the use of financial technology on the performance of SMEs mediated by financial inclusion. The data was collected using purposive sampling technique by distributing questionnaire. The sample of this study consists of 150 culinary SME actors in Malang City that have used QRIS (Quick Response Code Indonesia Standards) application as one of the payment methods. Collected data was analyzed using PLS software. The results showed that there is a significant influence between financial literacy and the use of financial technology on business performance. Financial inclusion can significantly mediate the effect of financial literacy and the use of financial technology on business performance.
This study aims to analyze the impact of financial socialization on financial well-being through financial literacy as a mediating variable. Using a quantitative approach, the study involved employees of PT. Solusi Bangun Indonesia Tbk and collected data through questionnaires. The results indicate that financial socialization has a significant effect on financial literacy but does not have a direct impact on financial well-being. Financial literacy was found to have a positive and significant effect on financial well-being and plays a mediating role between financial socialization and financial well-being. These findings emphasize the importance of improving financial literacy to support better financial management and enhance individual well-being. This research provides insights for the development of more effective financial education programs to improve financial literacy and well-being among employees.
This paper aims to examine the effect of financial stress on financial well-being with the mediation of financial health. This article also aims to see the influence of each variable, especially the importance of financial health. We use the Structural Equation Modeling (SEM) data analysis (SEM-PLS) method. The data sample is 230 young adults aged 25-30 years who live in Blitar City and Regency. The main findings of this research show that (i) there is a significant negative effect of financial stress on financial well-being, (ii) financial health has a positive effect on financial well-being, and finally, (iii) financial health mediates between financial stress and financial well-being. Financial health not only has a direct effect on financial well-being but also partially mediates financial stress. Young adults are expected to be able to manage their financial stress in everyday life. This aims to improve the individual's financial health, which will automatically improve the individual's financial well-being. It is hoped that future research can add new variables to influence financial well-being.
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 |