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: 14 / 15 publications (93.3%). 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 00:22 UTC — 21 Oct 2026 07:23 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.
15 / 15 with data · 0 missing or unmatched. Percentages use all 15 selected publications.
15 / 15 with data · 0 missing or unmatched. Percentages use all 15 selected publications.
15 / 15 with data · 0 missing or unmatched. Percentages use all 15 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 |
|---|---|---|---|---|---|
| 2017 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 2018 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 2019 | All selected publications | 0 | 0 | 0/0 | 0/0 |
| 2020 | All selected publications | 4 | 4 | 4/4 | 4/4 |
| 2021 | All selected publications | 4 | 4 | 4/4 | 4/4 |
| 2022 | All selected publications | 0 | 0 | 0/0 | 0/0 |
| 2023 | All selected publications | 0 | 0 | 0/0 | 0/0 |
| 2024 | All selected publications | 2 | 2 | 2/2 | 2/2 |
| 2025 | All selected publications | 0 | 0 | 0/0 | 0/0 |
| 2026 | All selected publications | 3 | 3 | 2/3 | 3/3 |
| Publication year | Journal / scope | Crossref citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2017 | All selected publications | 0 | 1 | 1/1 | 1/1 |
| 2018 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 2019 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2020 | All selected publications | 16 | 4 | 4/4 | 4/4 |
| 2021 | All selected publications | 13 | 4 | 4/4 | 4/4 |
| 2022 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2023 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2024 | All selected publications | 1 | 2 | 2/2 | 2/2 |
| 2025 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2026 | All selected publications | 0 | 3 | 2/3 | 3/3 |
| Publication year | Journal / scope | OpenAlex citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2017 | All selected publications | 2 | 1 | 1/1 | 1/1 |
| 2018 | All selected publications | 3 | 1 | 1/1 | 1/1 |
| 2019 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2020 | All selected publications | 33 | 4 | 4/4 | 4/4 |
| 2021 | All selected publications | 36 | 4 | 4/4 | 4/4 |
| 2022 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2023 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2024 | All selected publications | 2 | 2 | 2/2 | 2/2 |
| 2025 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2026 | All selected publications | 0 | 3 | 2/3 | 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 15 / 15 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): 2026-10-21T00:22:01.049844+00:00 — 2026-10-21T07:23:08.989439+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 | 15 | 15/15 |
| 2018 | All selected publications | 0 | 15 | 15/15 |
| 2019 | All selected publications | 0 | 15 | 15/15 |
| 2020 | All selected publications | 1 | 15 | 15/15 |
| 2021 | All selected publications | 7 | 15 | 15/15 |
| 2022 | All selected publications | 20 | 15 | 15/15 |
| 2023 | All selected publications | 26 | 15 | 15/15 |
| 2024 | All selected publications | 12 | 15 | 15/15 |
| 2025 | All selected publications | 8 | 15 | 15/15 |
| 2026 | All selected publications | 2 | 15 | 15/15 |
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 |
|---|---|
| 2017 | 1 |
| 2018 | 1 |
| 2020 | 4 |
| 2021 | 4 |
| 2024 | 2 |
| 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 | 6 | 6 | 16 | 6/6 | 1.2 | 0 | 40.0 | 5/6 · 83.3% |
| International Journal of Research in Business and Social Science SSBFNET | 9 | 25 | 60 | 9/9 | 2.78 | 1 | 66.7 | 9/9 · 100.0% |
* Percentage among publications with a known citation count.
This study examines the effect of working capital management on the financial performance of Non-financial companies quoted on the Nigerian Stock Exchange over the period 2014 – 2018 while using a panel research design. This work is unique because it considers a sample of 71 companies drawn from all the 10 non-financial sectors of the NSE. Unlike most extant studies, financial performance was captured by earnings per share as a proxy, while the right-hand side variable being working capital management was denominated by Accounts receivable period, Inventory turnover period, and Accounts payable period. This study also considered the effect of some control variables namely annual capital expenditure, age of firm, GDP, firm size, growth of the company, and firm leverage on EPS. Data were retrieved from the Nigerian Stock Exchange 2019 Factbook. The model estimation technique adopted was the Pooled Ordinary Least Squares, fixed effect, and random-effect methods. Results from this study are consistent with the theoretical position that all aspects of working capital management have a significant effect on financial performance. While ITP and ACP were negatively related to EPS, APP was found to have a positive relationship with EPS. The research results also reveal that although all the control variables were found to be significant, only the age of the firm was deemed to be positively related to EPS. Based on the findings, the research recommends that firms should focus their managerial attention on lowering their ITP and ACP while increasing their APP, as results indicate that management of these elements of working capital can translate into liquidity and higher profitability.
This study examines the relationship between the working capital management practices and sustainability of Barangay Micro Business Enterprises (BMBEs) in Ilocos Norte, Philippines. This study employed a correlational-descriptive research design. Data were gathered using a self-constructed questionnaire, which has been pre-tested to 30 other microenterprises and validated using Cronbach alpha. The participants were the owners of the 301 registered BMBEs in Ilocos Norte. This study was conducted from July to December 2020. The findings demonstrated that most of the BMBEs belong to the wholesale and retail trade sector, are registered as single proprietorships, and have no employees. The results also showed that the BMBEs have low economic, social, and environmental sustainability. Moreover, the study revealed that cash management was significantly related to economic and social sustainability, while accounts receivable and inventory management were significantly related to economic, social, and environmental sustainability.
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.
Research Originality: This study investigates the relationship between inventory management and profitability within the textiles industry in Bangladesh, emphasizing the key factors that significantly enhance the industry's profitability. Research Objectives: This analysis investigates how various factors, including total assets, total equity, total revenue, share capital, retained earnings, finished items, work in progress, and raw materials, impact profit after tax (PAT). Research Methods: The data spans from 2011 to 2023 and encompasses 46 textile companies listed on the Dhaka Stock Exchange (DSE). To conduct this study, different models like Pooled Ordinary Least Square (POLS), Second Stage Least Square (2SLS), Generalized Method of Moments (GMM) are utilized. Empirical Results: Through the application of techniques including Pooled Ordinary Least Squares (POLS), Two-Stage Least Squares (2SLS), and the Generalized Method of Moments (GMM), we have established that total assets exhibit a significant negative correlation with PAT in both the POLS and 2SLS models. On the other hand, there is a notable positive correlation between total revenue and retained earnings on PAT across all 2SLS, POLS, and GMM models. The share capital shows a negative correlation with PAT in all three models: 2SLS, POLS, and GMM. The main independent variable, which is our fundamental focus, shows that finished goods have a positive correlation with PAT; however, this correlation lacks significance. The raw materials exhibited a negative correlation with PAT, and this relationship is significant. The correlation between Packing Materials and PAT is notably positive. This study highlights the importance of strategies that could facilitate sustainable growth in the textile industry.
This paper searches the impact of trade credit on firms’ performance in 15 sub-Saharan African (SSA) countries. In particular, we also examine whether trade credit can advance in an environment of higher financial inclusion rate. We achieve this by using a fixed effect estimation model and solving endogeneity by GMM and IV-2SLS methods by utilizing firm level data from the Bloomberg terminal from 2010 to 2023. Baseline results summarize that firm performance grows with the level of trade credit finance. We find a firm’s industry and SSA blocs heterogeneity the trade credit-firm performance nexus. Additionally, financial inclusion alone is positive and when interacted with trade credit it becomes significant. The major implication among others is that trade credit facilitates more firm performance in a situation of higher financial inclusion level.
The coal industry in Indonesia is a capital-intensive sector characterized by long operating cycles and high dependence on global commodity price fluctuations. These conditions create substantial liquidity needs, making efficient working capital management crucial. This study aims to examine the effect of Supply Chain Finance (SCF) on firm performance in Indonesia’s coal production sub-industry. SCF in this study is measured using the Cash Conversion Cycle (CCC) and its components, Days Sales Outstanding (DSO), Days Inventory Outstanding (DIO), and Days Payable Outstanding (DPO). Firm performance is proxied by Return on Assets (ROA), while the control variables include firm size (SIZE), leverage (LEV), and sales growth (SALEG). The main hypothesis proposes that SCF has a positive effect on firm performance. This research employs secondary data from 19 coal production companies listed on the Indonesia Stock Exchange (IDX) during the 2020-2024 period. The analysis is conducted using panel data regression with the Random Effect Model (REM) approach, estimated through the Generalized Least Square (XTGLS) method.The results show that SCF has no significant effect on firm performance, while leverage (LEV) and sales growth (SALEG) have a negative and significant effect. The coefficient of determination (R²) of 27.06% indicates that the model explains 27.06% of the variation in firm performance. These findings suggest that SCF efficiency in the coal industry does not directly enhance profitability, likely due to the long cash conversion cycle and high capital requirements inherent in this sector.
Given the critical role of financial characteristics in determining Micro and Small Enterprises (MSEs’) access to debt finance, it is essential to understand how these characteristics influence lending decisions, particularly from a developing market context. This study aims to examine the key financial characteristics that significantly influence MSEs’ ability to access debt finance. Using systematic sampling technique, we collect data from 171 Ghanaian MSEs that are registered with Ghana Enterprise Agency. The data was analyzed using SPSS linear regression version 24. The result shows financial management experience and profitability as the significant financial characteristics that influence MSEs ability to access debt finance. The result further shows that equity structure and financial statement have negative significant influence on MSEs ability to access debt finance. Asset tangibility, liquidity, debt service coverage ratio, and working capital has no significant influence on MSEs’ access to debt financing.
This study examines the correlation between inventory and accounts payable management and the profitability of construction companies listed on the Johannesburg Stock Exchange (JSE). The annual financial statements of all 13 listed construction businesses from 2009 to 2019, including statements of financial position and financial performance, were obtained from an external database for statistical analysis. The study employed multiple linear regression to assess the impact of working capital management on the financial performance of construction companies listed on the JSE. Additionally, a correlation model was utilised to investigate any potential relationships among the variables being examined. The study's findings indicate that the management of working capital has a notable impact on the profitability of construction companies listed on the Johannesburg Stock Exchange (JSE) in South Africa. Despite contradicting findings from other studies that support the opposite conclusion, this study demonstrates that effective management of working capital does not necessarily lead to a positive relationship with financial performance for financial managers of construction companies. Therefore, it is crucial to consider other aspects of management in addition to working 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 19:56 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 |