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: 75 / 78 publications (96.2%). Latest observation: 21 Oct 2026, 00:21 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 00:30 UTC — 28 Oct 2026 16:21 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.
78 / 78 with data · 0 missing or unmatched. Percentages use all 78 selected publications.
78 / 78 with data · 0 missing or unmatched. Percentages use all 78 selected publications.
78 / 78 with data · 0 missing or unmatched. Percentages use all 78 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 |
|---|---|---|---|---|---|
| 2014 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 2015 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 2016 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 2017 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 2018 | All selected publications | 3 | 3 | 3/3 | 3/3 |
| 2019 | All selected publications | 0 | 0 | 0/0 | 0/0 |
| 2020 | All selected publications | 11 | 11 | 11/11 | 11/11 |
| 2021 | All selected publications | 8 | 8 | 8/8 | 8/8 |
| 2022 | All selected publications | 19 | 19 | 19/19 | 19/19 |
| 2023 | All selected publications | 14 | 14 | 14/14 | 14/14 |
| 2024 | All selected publications | 8 | 8 | 8/8 | 8/8 |
| 2025 | All selected publications | 8 | 8 | 8/8 | 8/8 |
| 2026 | All selected publications | 3 | 3 | 0/3 | 3/3 |
| Publication year | Journal / scope | Crossref citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2014 | All selected publications | 0 | 1 | 1/1 | 1/1 |
| 2015 | All selected publications | 5 | 1 | 1/1 | 1/1 |
| 2016 | All selected publications | 0 | 1 | 1/1 | 1/1 |
| 2017 | All selected publications | 0 | 1 | 1/1 | 1/1 |
| 2018 | All selected publications | 0 | 3 | 3/3 | 3/3 |
| 2019 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2020 | All selected publications | 81 | 11 | 11/11 | 11/11 |
| 2021 | All selected publications | 8 | 8 | 8/8 | 8/8 |
| 2022 | All selected publications | 28 | 19 | 19/19 | 19/19 |
| 2023 | All selected publications | 16 | 14 | 14/14 | 14/14 |
| 2024 | All selected publications | 11 | 8 | 8/8 | 8/8 |
| 2025 | All selected publications | 5 | 8 | 8/8 | 8/8 |
| 2026 | All selected publications | — | 3 | 0/3 | 3/3 |
| Publication year | Journal / scope | OpenAlex citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2014 | All selected publications | 0 | 1 | 1/1 | 1/1 |
| 2015 | All selected publications | 16 | 1 | 1/1 | 1/1 |
| 2016 | All selected publications | 0 | 1 | 1/1 | 1/1 |
| 2017 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 2018 | All selected publications | 11 | 3 | 3/3 | 3/3 |
| 2019 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2020 | All selected publications | 189 | 11 | 11/11 | 11/11 |
| 2021 | All selected publications | 27 | 8 | 8/8 | 8/8 |
| 2022 | All selected publications | 66 | 19 | 19/19 | 19/19 |
| 2023 | All selected publications | 24 | 14 | 14/14 | 14/14 |
| 2024 | All selected publications | 12 | 8 | 8/8 | 8/8 |
| 2025 | All selected publications | 5 | 8 | 8/8 | 8/8 |
| 2026 | All selected publications | 0 | 3 | 0/3 | 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 78 / 78 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): 2026-10-22T00:30:26.250851+00:00 — 2026-10-28T16:21:30.404356+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 | 2 | 78 | 78/78 |
| 2018 | All selected publications | 1 | 78 | 78/78 |
| 2019 | All selected publications | 1 | 78 | 78/78 |
| 2020 | All selected publications | 10 | 78 | 78/78 |
| 2021 | All selected publications | 27 | 78 | 78/78 |
| 2022 | All selected publications | 46 | 78 | 78/78 |
| 2023 | All selected publications | 84 | 78 | 78/78 |
| 2024 | All selected publications | 88 | 78 | 78/78 |
| 2025 | All selected publications | 60 | 78 | 78/78 |
| 2026 | All selected publications | 31 | 78 | 78/78 |
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 |
|---|---|
| 2014 | 1 |
| 2015 | 1 |
| 2016 | 1 |
| 2017 | 1 |
| 2018 | 3 |
| 2020 | 11 |
| 2021 | 8 |
| 2022 | 19 |
| 2023 | 14 |
| 2024 | 8 |
| 2025 | 8 |
| 2026 | 3 |
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 Finance & Banking Studies SSBFNET | 78 | 154 | 351 | 78/78 | 2.05 | 0 | 48.0 | 75/78 · 96.2% |
* Percentage among publications with a known citation count.
As an industry that has an important role for other industrial sectors, the plastic and packaging industry is the supply chain for consumer products. Behind the high industrial growth and the potential is still large, there are problems with plastic waste, consumption power, and changes in people's lifestyles that can affect the growth of the plastic and packaging industry. This study aims to determine how much impact the NPM (Net Profit Margin), GPM (Gross Profit Margin), TAT (Total Assets Turnover) on Profit Growth in the plastic and packaging industry sub-sector companies listed in IDX (Indonesia Stock Exchange) for the period 2014 to 2018. The method used in this study is a quantitative descriptive. The sampling technique used was purposive sampling in order to obtain a sample of 11 companies from a population of 12 companies. In the study the method of data analysis used the multiple linear regression analysis techniques by processing data using Eviews 8, because the data is not normally distributed, it uses the log transformation method. The results showed that simultaneously NPM (Net Profit Margin), GPM (Gross Profit Margin), TAT (Total Assets Turnover) had a significant effect on profit growth. And partially NPM (Net Profit Margin) has a significant effect on profit growth, while GPM (Gross Profit Margin) and TAT (Total Assets Turnover) have no significant effect on profit growth.
An increase in MSMEs in large numbers is very instrumental in increasing economic growth in developing countries, including Indonesia. The research objective is based on identifying the effect of investment credit, interest rates, and labor on economic growth through the role of MSMEs. The design of this research is descriptive-verification to present a structured, factual and accurate picture and test hypotheses empirically through the MRA model. Empirical analysis proves that investment credit and interest rates through the role of MSMEs can influence positively and significantly on Indonesia's economic growth. In other results, it appears that the role of MSMEs is less able to mediate the effect of labor on Indonesia's economic growth. This fact is based on a negative and insignificant relationship. In a sentence or two, enter the implications and limitations of your research. In Indonesia, increasing bank lending to MSMEs in practice is undermined by lending policies by banks and by macroeconomic factors (economic growth, interest rates, investment credit, and labor).
The purpose of this study is to determine which indicators are more capable of showing more accurate sell and buy signals on the LQ45 index by using the oscillator indicator Moving Average Divergent Convergent (MACD), Bollinger Band, and Relative Strength Index (RSI). The results in this study indicate that the sell signal can be captured well by the Bollinger band and MACD indicators, but it cannot be captured properly by the RSI, the volume can be small or heading and are in the side ways, while the MACD plays a too slow role in capturing the signal buy compared to Bollinger bands and RSI. The use of a single indicator will never show a buy and sell signal that is really accurate, this is based on the results of research that shows the difference in timeliness in Bollinger, RSI and also MACD so that the combination of several types of indicators will be better compared to using single indicators. Although in statistics there are no significant differences, there are only differences in increment and improvement in the placement of existing values, but in this case, the order of this value is crucial for traders because it requires very high accuracy to determine the right decision in daily transactions.
This study aims to analyze the effects of human capital and organizational learning on employee performance with innovation behavior as a mediator. This study is conducted at a privately owned bank in Gorontalo City with a sample of 92 respondents. Researchers use purposive sampling with data collection technique that is questionnaires in Google Form. Data analysis is performed using SEM-PLS (Structural Equation Modeling Partial Least Square) with SmartPLS software version 3.0. The results of this study indicate that (1) human capital has positive effect on employee performance and innovation behavior, (2) organizational learning has positive effect on innovation behavior, (3) innovation behavior has positive effect on employee performance, and (4) innovation behavior mediates the effect of organizational learning on employee performance but cannot mediate human capital on employee performance.
In the past decade, Southeast Asia has seen the development of financial inclusion, as evidenced by the growth of the penetration, availability, and usage dimensions of financial inclusion. This study analyses the impact financial inclusion has on economic growth, represented by GDP per capita growth, and unemployment using data from Indonesia, Malaysia, Thailand, the Philippines, and Cambodia. The authors employed panel data regression with fixed effect and random effect models to analyse the data. The results show that the number of commercial bank branches and outstanding loans statistically significantly affect GDP per capita growth, while the number of saving/deposit accounts does not. All three variables are shown to have a statistically significant impact on unemployment.
This article maps the knowledge structure and evolution of bankruptcy/default prediction research in financial institutions using a bibliometric co-citation approach, which identifies works that are often cited together due to the proximity of their theories, methods, or themes. Bibliographic data were collected from the Web of Science (WoS) for the period 1970-2025, then extracted in a complete bibliographic format and prepared for network analysis. The co-citation procedure is carried out by extracting the reference list, normalizing and unifying citation variations, and preparing a co-citation matrix, which is then visualized and classified using VOSviewer with minimum threshold parameters and normalized association strength. The results of the document ranking based on the number of citations and Total Link Strength (TLS) show the development trajectory of the field from the ratio and Z-Score approach to the logit probabilistic model, the market foundation based on the structural theory of credit risk, the governance perspective supported by agency theory, the dynamic panel methodology/GMM for longitudinal data, to computational waves (neural networks and machine learning) to capture nonlinear patterns of credit scoring. The co-citation map uncovers four main clusters: econometrics & banking risk, structural theory, ratios, and computational, with Merton and Altman acting as the cross-cluster binding nodes. These findings support the design of a more comprehensive early warning system (EWS) by integrating ratio signals, market indicators, governance/agency factors, and ML models to improve accuracy and adaptation.
This study examines the effect of Good Corporate Governance (GCG), financing quality, Islamic Corporate Social Responsibility (ICSR), and operational efficiency on the financial performance of Islamic Commercial Banks (Bank Umum Syariah/BUS) in Indonesia using a quantitative explanatory approach with panel data regression analysis. The research focuses on 14 Islamic Commercial Banks registered with the Financial Services Authority (Otoritas Jasa Keuangan/OJK) over the 2019–2024 period, resulting in 84 firm-year observations selected through purposive sampling based on the availability of complete annual reports. Financial performance is proxied by Return on Assets (ROA), while GCG is measured using governance indicators disclosed in annual reports, financing quality is represented by Non-Performing Financing (NPF), ICSR is measured using an ICSR disclosure index, and operational efficiency is proxied by the BOPO ratio. The analysis was conducted using EViews version 13. The empirical results show that Good Corporate Governance has a positive and statistically significant effect on financial performance, indicating that stronger governance practices contribute to higher profitability. Financing quality does not exhibit a significant effect on ROA. Conversely, Islamic Corporate Social Responsibility and operational efficiency have a negative and statistically significant effect on financial performance, suggesting that higher operational inefficiency and CSR-related costs may reduce short-term profitability. Overall, this study contributes to the Islamic banking literature by providing empirical evidence on key determinants of financial performance in Islamic Commercial Banks and highlights the importance of strengthening governance practices, improving operational efficiency, and managing ICSR programs more strategically to balance social objectives with long-term financial sustainability, while offering insights for regulators and stakeholders in reinforcing governance frameworks and optimizing Islamic value-based social responsibility.
This study aims to assess the impact of exposure to Carbon Emission Disclosure (CED) and the level of Greenhouse Gas (GHG) emissions on the valuation of companies operating in the Indonesian banking sector. This in-depth study also evaluates the influence of capital structure and intellectual property assets. In addition, this study explicitly examines how financial performance moderates the relationship between these variables and the company's value. Using a quantitative research method, this analysis observed a sample consisting of banking entities listed on the Indonesia Stock Exchange (IDX) from 2020 to 2024. The theoretical framework underpinning this research comprises Legitimacy Theory, Stakeholder Theory, Signal Theory, Preference Order Theory, and the resource-based view (RBV). The results reveal that transparent disclosure of carbon emissions and the accumulation of intellectual capital positively influence the company's value, while GHG emissions and leverage have adverse effects. Crucially, financial performance (ROA) moderates these relationships by weakening the positive impact of carbon disclosure and buffering the negative impact of GHG emissions but does not significantly moderate the effects of capital structure or intellectual capital. These findings offer practical guidelines for banking management to align environmental sustainability practices with financial strategies to enhance corporate value.
Capital financing plays a crucial role in sustaining the growth potential of pharmaceutical companies, enabling them to expand operations and compete effectively in the market. In the face of a slowing global economy, maintaining solid financial performance across existing business lines becomes increasingly important. This study aims to examine the relationship between capital structure and the financial performance of pharmaceutical companies in Indonesia. The research sample consists of nine publicly listed pharmaceutical firms over the period 2013–2023. The empirical analysis employs three panel data estimation approaches—Pooled Ordinary Least Squares (Pooled OLS), Fixed Effects Model (FEM), and Random Effects Model (REM)—to account for different assumptions about unobserved firm-specific characteristics. Based on the Hausman test, FEM is determined as the most suitable model for the dataset. The estimation results reveal that the Long-term Debt to Total Assets (LDTA) ratio exerts a statistically significant negative effect on Return on Assets (ROA), indicating that a higher proportion of long-term debt tends to reduce profitability. Conversely, the Short-term Debt to Total Assets (SDTA) and Total Debt to Total Equity (TDTE) ratios have positive but statistically insignificant impacts on ROA, suggesting that neither short-term liabilities nor overall leverage significantly influence profitability in the observed period. These results imply that excessive reliance on long-term borrowing can impose interest burdens and financial constraints, thereby weakening performance. Consequently, financial managers in the pharmaceutical sector are encouraged to optimize their financing structure, prioritizing internal funds or short-term financing sources that align with operational needs and market conditions to sustain profitability and ensure long-term competitiveness.
This study looks at the effect of accounting flexibility on earnings quality in public companies listed on the Indonesia Stock Exchange during the period 2016 to 2019. This study uses two models to measure earnings quality, namely ERC and earnings persistence. The results showed that accounting flexibility, namely the limitations of companies to carry out accrual earnings management, can reduce earnings quality, as shown by the abnormal accrual model which shows a significant positive coefficient direction, and for the ERC model and earnings persistence which shows a negative and significant coefficient direction. The higher the level of accrual earnings management up to a certain limit point, the more incentive company managers will have to increase accounting flexibility and switch to real earnings management (Xu and Yang, 2013; Masri, 2018). Theoretical contributions show that the higher the level of accrual earnings management up to a certain limit point, the more incentive company managers will have to increase accounting flexibility and switch to real earnings management (Xu and Yang, 2013; Masri, 2018; Purba, Surya, Joshi & Tiagy, 2023). The Implications of this research show that accounting flexibility is carried out when abnormal accruals reach the highest limit point reflected in accounting choices in net operating assets in the balance sheet, so in this case it results in a low level of earnings informativeness and earnings persistence.
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 00:21 UTC · ijfbs | complete · ijfbs · 21 Oct 2026 00:21 UTC |
| ojs-rest | 21 Oct 2026 00:21 UTC · ijfbs | complete · ijfbs · 21 Oct 2026 00:14 UTC |
| oai-pmh | 20 Oct 2026 19:56 UTC · ijfbs | complete · ijfbs · 20 Oct 2026 19:55 UTC |
| openalex-enrichment | 21 Oct 2026 00:22 UTC · ijfbs | complete · ijfbs · 21 Oct 2026 00:21 UTC |