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 00:49 UTC — 22 Oct 2026 03:34 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 |
|---|---|---|---|---|---|
| 2020 | All selected publications | 4 | 4 | 4/4 | 4/4 |
| Publication year | Journal / scope | Crossref citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2020 | All selected publications | 16 | 4 | 4/4 | 4/4 |
| Publication year | Journal / scope | OpenAlex citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2020 | All selected publications | 33 | 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): 2026-10-22T00:49:24.531355+00:00 — 2026-10-22T03:34:09.177734+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 | 1 | 4 | 4/4 |
| 2021 | All selected publications | 4 | 4 | 4/4 |
| 2022 | All selected publications | 9 | 4 | 4/4 |
| 2023 | All selected publications | 8 | 4 | 4/4 |
| 2024 | All selected publications | 6 | 4 | 4/4 |
| 2025 | All selected publications | 4 | 4 | 4/4 |
| 2026 | All selected publications | 1 | 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 ↗
Publications by publication year. 2026 is an incomplete year.
| Period | Publications |
|---|---|
| 2020 | 4 |
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 | 2 | 5 | 10 | 2/2 | 2.5 | 2.5 | 50.0 | 2/2 · 100.0% |
| International Journal of Research in Business and Social Science SSBFNET | 2 | 11 | 23 | 2/2 | 5.5 | 5.5 | 100.0 | 2/2 · 100.0% |
* Percentage among publications with a known citation count.
The financial system and capital market in developed countries are more developed as compare to emerging countries. Firms like small and medium enterprise (SMEs) needs finance to operate their business and make a competitive position in the market. In an emerging country like Pakistan, SMEs face a lot of financial and non-financial obstacles that may relate to the poor performance of SMEs. This study investigates the relationship between commercial loans, retain earnings, trade credit, managerial activities, and SME's performance. This study also investigates the interaction effect of managerial activities between independent variables and dependent variables. A survey was conducted in a small and medium enterprise of KPK Pakistan. Data were collected from 362 employees. SPSS (Statistical Package for the Social Sciences) software was employed for data analysis for descriptive and regression analysis. The finding confirmed that commercial loans, trade credit, retained earning have a positive and significant impact upon SME's performance. It is also found that managerial activities have played a mediating role and increased the performance of SMEs. Among variables under study, the more trade credit activities, the higher the performance of the SMEs is observed. Based on this study's results, Leaders, supervisors, and managers are those employees having a substantial role in the performance, development, failure, and success of an organization. Managerial activities are vital for a manager for the purpose to know what should be done in different circumstances and improve overall performance and accomplish organizational goals.
Short-term debt is regarded as an important source of financing for Small and Medium-sized enterprises (SMEs). This is because it can be easily accessed and useful during times of emergent working capital shortage. However, short-term debt is the least researched among the components of capital structure, which explains why its contribution to the financial performance of small and medium-sized businesses still lacks empirical validation especially in the Ugandan context. This paper sought to determine the effect of short-term debt on financial performance of Small and Medium Enterprises in Uganda. The study adopted a descriptive cross-sectional research design to collect and analyse the data. Stratified random sampling technique was used to select SMEs while purposive sampling technique was used to select one key respondent from each of the sampled 453 SMEs in Uganda. Primary data was collected using survey questionnaire. Data was analysed using descriptive statistics and simple linear regression analysis. The findings indicted that short-term debt had a negative and significant effect on financial performance of SMEs as measured by return on assets. The study provides empirical evidence to support the propositions in the extant literature that short-term debt significantly hampers financial performance of SMEs. The study recommends that SMEs should adopt low cost operation procedures to improve profitability. This would lead to accumulated profits that can be used for investment purposes as a means of driving growth among the SMEs without resorting to borrowing. This paper suggests that further research should be conducted to establish the justification for the negative and significant effect of short-term debt on financial performance using qualitative approaches.
This research aims to analyze the impact of efficient working capital management on the profitability of the manufacturing firm in Bangladesh. Fifty-two manufacturing companies listed with Dhaka Stock Exchange (DSE) have been selected randomly from 2012 to 2017. Return on Assets (ROA) and Return on Equity (ROE) are used as indicators of profitability, while the inventory conversion period (ICP), the average collection period (ACP), the average payment period (APP), and the Cash Conversion Cycle (CCC) are used as the independent variables which are used as a measurement of working capital management of the firm. Ordinary Least Squares regression models and Pearson's Correlation are used to establish the relationship between working capital management and profitability. The results revealed a significant negative relation between ROA and CCC, ACP; a significant negative relationship exists between ROE and CCC, APP. Manufacturing companies can increase profitability by decreasing the cash conversion cycle, average payment period, and average collection period. It also revealed that ICP is also positively related to ROA and ROE. Therefore, this research concludes that efficiently and effectively managing working capital is very important for increasing manufacturing companies' profitability.
The study investigated the whether the default measures of liquidity and solvency are associated and whether default measures are related to firm profitability. A total of 41 firms were selected to be in the study sample out of 46 non-financial listed firms in the Nairobi Securities Exchange during years 2013 to 2017 and panel data regression analysis was employed. The findings revealed that liquidity and solvency are significantly and negatively associated while the default measures lacked a significant relationship with profitability in Kenyan listed companies. The findings implied that there is no need for firms to focus too much on the relationship between default and profitability including invest heavily in liquidity in order to meet short term obligations as nowadays it is possible for firms to either convert non-cash assets quickly or borrow on short notice from financial institutions in case of an urgent need to meet liquidity shortages. These findings are consistent with the shitability theory.
Short-term debt is regarded as an important source of financing for Small and Medium-sized enterprises (SMEs). This is because it can be easily accessed and useful during times of emergent working capital shortage. However, short-term debt is the least researched among the components of capital structure, which explains why its contribution to the financial performance of small and medium-sized businesses still lacks empirical validation especially in the Ugandan context. This paper sought to determine the effect of short-term debt on financial performance of Small and Medium Enterprises in Uganda. The study adopted a descriptive cross-sectional research design to collect and analyse the data. Stratified random sampling technique was used to select SMEs while purposive sampling technique was used to select one key respondent from each of the sampled 453 SMEs in Uganda. Primary data was collected using survey questionnaire. Data was analysed using descriptive statistics and simple linear regression analysis. The findings indicted that short-term debt had a negative and significant effect on financial performance of SMEs as measured by return on assets. The study provides empirical evidence to support the propositions in the extant literature that short-term debt significantly hampers financial performance of SMEs. The study recommends that SMEs should adopt low cost operation procedures to improve profitability. This would lead to accumulated profits that can be used for investment purposes as a means of driving growth among the SMEs without resorting to borrowing. This paper suggests that further research should be conducted to establish the justification for the negative and significant effect of short-term debt on financial performance using qualitative approaches.
This research aims to analyze the impact of efficient working capital management on the profitability of the manufacturing firm in Bangladesh. Fifty-two manufacturing companies listed with Dhaka Stock Exchange (DSE) have been selected randomly from 2012 to 2017. Return on Assets (ROA) and Return on Equity (ROE) are used as indicators of profitability, while the inventory conversion period (ICP), the average collection period (ACP), the average payment period (APP), and the Cash Conversion Cycle (CCC) are used as the independent variables which are used as a measurement of working capital management of the firm. Ordinary Least Squares regression models and Pearson's Correlation are used to establish the relationship between working capital management and profitability. The results revealed a significant negative relation between ROA and CCC, ACP; a significant negative relationship exists between ROE and CCC, APP. Manufacturing companies can increase profitability by decreasing the cash conversion cycle, average payment period, and average collection period. It also revealed that ICP is also positively related to ROA and ROE. Therefore, this research concludes that efficiently and effectively managing working capital is very important for increasing manufacturing companies' profitability.
The study investigated the whether the default measures of liquidity and solvency are associated and whether default measures are related to firm profitability. A total of 41 firms were selected to be in the study sample out of 46 non-financial listed firms in the Nairobi Securities Exchange during years 2013 to 2017 and panel data regression analysis was employed. The findings revealed that liquidity and solvency are significantly and negatively associated while the default measures lacked a significant relationship with profitability in Kenyan listed companies. The findings implied that there is no need for firms to focus too much on the relationship between default and profitability including invest heavily in liquidity in order to meet short term obligations as nowadays it is possible for firms to either convert non-cash assets quickly or borrow on short notice from financial institutions in case of an urgent need to meet liquidity shortages. These findings are consistent with the shitability theory.
The financial system and capital market in developed countries are more developed as compare to emerging countries. Firms like small and medium enterprise (SMEs) needs finance to operate their business and make a competitive position in the market. In an emerging country like Pakistan, SMEs face a lot of financial and non-financial obstacles that may relate to the poor performance of SMEs. This study investigates the relationship between commercial loans, retain earnings, trade credit, managerial activities, and SME's performance. This study also investigates the interaction effect of managerial activities between independent variables and dependent variables. A survey was conducted in a small and medium enterprise of KPK Pakistan. Data were collected from 362 employees. SPSS (Statistical Package for the Social Sciences) software was employed for data analysis for descriptive and regression analysis. The finding confirmed that commercial loans, trade credit, retained earning have a positive and significant impact upon SME's performance. It is also found that managerial activities have played a mediating role and increased the performance of SMEs. Among variables under study, the more trade credit activities, the higher the performance of the SMEs is observed. Based on this study's results, Leaders, supervisors, and managers are those employees having a substantial role in the performance, development, failure, and success of an organization. Managerial activities are vital for a manager for the purpose to know what should be done in different circumstances and improve overall performance and accomplish organizational goals.
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 19:56 UTC · ijfbs | complete · ijfbs · 20 Oct 2026 19:55 UTC |
| openalex-enrichment | 21 Oct 2026 07:23 UTC · ijrbs | complete · ijrbs · 21 Oct 2026 07:22 UTC |