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: 10 / 10 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 00:01 UTC — 21 Oct 2026 07:22 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.
8 / 10 with data · 2 missing or unmatched. Percentages use all 10 selected publications.
8 / 10 with data · 2 missing or unmatched. Percentages use all 10 selected publications.
10 / 10 with data · 0 missing or unmatched. Percentages use all 10 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 |
|---|---|---|---|---|---|
| 2013 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 2014 | All selected publications | 0 | 0 | 0/0 | 0/0 |
| 2015 | All selected publications | 0 | 0 | 0/0 | 0/0 |
| 2016 | All selected publications | 2 | 2 | 2/2 | 2/2 |
| 2017 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 2018 | All selected publications | 0 | 0 | 0/0 | 0/0 |
| 2019 | All selected publications | 0 | 0 | 0/0 | 0/0 |
| 2020 | All selected publications | 0 | 0 | 0/0 | 0/0 |
| 2021 | All selected publications | 2 | 2 | 2/2 | 2/2 |
| 2022 | All selected publications | 2 | 2 | 2/2 | 2/2 |
| 2023 | All selected publications | 2 | 2 | 2/2 | 2/2 |
| Publication year | Journal / scope | Crossref citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2013 | All selected publications | 0 | 1 | 1/1 | 1/1 |
| 2014 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2015 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2016 | All selected publications | 1 | 2 | 2/2 | 2/2 |
| 2017 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 2018 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2019 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2020 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2021 | All selected publications | 3 | 2 | 2/2 | 2/2 |
| 2022 | All selected publications | 2 | 2 | 2/2 | 2/2 |
| 2023 | All selected publications | 1 | 2 | 2/2 | 2/2 |
| Publication year | Journal / scope | OpenAlex citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2013 | All selected publications | 0 | 1 | 1/1 | 1/1 |
| 2014 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2015 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2016 | All selected publications | 8 | 2 | 2/2 | 2/2 |
| 2017 | All selected publications | 2 | 1 | 1/1 | 1/1 |
| 2018 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2019 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2020 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2021 | All selected publications | 7 | 2 | 2/2 | 2/2 |
| 2022 | All selected publications | 4 | 2 | 2/2 | 2/2 |
| 2023 | All selected publications | 5 | 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 10 / 10 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): 2026-10-21T00:01:59.957867+00:00 — 2026-10-21T07:22:43.905583+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 | 1 | 10 | 10/10 |
| 2018 | All selected publications | 1 | 10 | 10/10 |
| 2019 | All selected publications | 3 | 10 | 10/10 |
| 2020 | All selected publications | 0 | 10 | 10/10 |
| 2021 | All selected publications | 2 | 10 | 10/10 |
| 2022 | All selected publications | 3 | 10 | 10/10 |
| 2023 | All selected publications | 2 | 10 | 10/10 |
| 2024 | All selected publications | 7 | 10 | 10/10 |
| 2025 | All selected publications | 6 | 10 | 10/10 |
| 2026 | All selected publications | 0 | 10 | 10/10 |
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 |
|---|---|
| 2013 | 1 |
| 2016 | 2 |
| 2017 | 1 |
| 2021 | 2 |
| 2022 | 2 |
| 2023 | 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 |
|---|---|---|---|---|---|---|---|---|
| Bussecon Review of Social Sciences Bussecon International Academy | 2 | 3 | 3 | 2/2 | 1.5 | 1.5 | 100.0 | 2/2 · 100.0% |
| International Journal of Finance & Banking Studies SSBFNET | 4 | 1 | 12 | 4/4 | 0.25 | 0.0 | 25.0 | 4/4 · 100.0% |
| International Journal of Research in Business and Social Science SSBFNET | 4 | 4 | 11 | 4/4 | 1.0 | 1.0 | 75.0 | 4/4 · 100.0% |
* Percentage among publications with a known citation count.
The objective of this paper is to identify the challenges of implementing and adopting an effective ERM system and to suggest alternative strategies that could be pursued as countermeasures to those challenges. This study is based on survey data gathered from 379 respondents representing 129 companies listed on the Colombo Stock Exchange of Sri Lanka. This study found that the lack of availability of information to make risk-based decisions; the need to ensure that all decisions are made within the organization’s risk tolerance level, and the lack of top management support for ERM implementation; are the most influencing challenges for business organizations that obstruct ERM effectiveness. This study suggests that organizations should promote a good corporate culture that fosters ERM supportive internal environment. It is also suggested that the support of the top management and their commitment to being corporative with the firms’ ERM function without making ERM is the sole responsibility of the finance people. Further, it is suggested that organizations have a designated position dedicated to overseeing the ERM function and providing executive leadership for its effective implementation.
Despite the institutionalization of operational risk management in banks and the strict supervision of bank regulators, operational risk events are still on the increase. It is becoming evident to banks that there is a need to identify the drivers of this risk and nib it at the root to reduce the probability of recurrence. Hence, this study examined the drivers of operational risks in Nigerian commercial banks and the extent to which each driver contributes to operational risk. To achieve the study’s objectives, primary data were collected from the Operational Risk Management Desks of six (6) sampled commercial banks and analyzed using SPSS and Microsoft Excel. The result showed that Internal processes, IT systems and Quality of Risk Officers are determinants of operational losses in banks. The internal process was however indicated as having the most impact. The study concluded that Internal Process is the major driver of operational risk in Nigerian Commercial banks. The researcher, therefore, recommends that bank management must have defined procedures for core activities and prioritize regular review of their critical processes to reduce operational risk events and the associated costs.
The aim of this paper is to compare the views of internal controllers/auditors and branch/call center personnel of the banks with respect to the operational risk. Within this scope, we made two different surveys to the personnel in Turkish banks in order to achieve this objective. The first survey was conducted by 310 branch and call center personnel whereas 151 personnel in internal control and audit departments of the banks carried out the second survey. The major finding in this study is that there is a difference in the views of these two groups regarding the evaluation of operational risk. In general, internal controllers/auditors look at the operational risk more negatively than branch/call center personnel. The personnel who control and audit operations in the bank think that operational risk knowledge level of branch/call center personnel is less sufficient, operational risk levels are higher, the controls to avoid this risk are less efficient than branch/call center personnel consider.
The main aim of the investigation was to analyze the effect of operational and market risk exposures on the financial performance of DT-SACCOs in Kenya. The specific objectives of the study were to; assess the effect of operating expense risk exposure on the financial performance of DT-SACCOs in Kenya; To establish the effect of operation efficiency risk exposure on the financial performance of DT-SACCOs in Kenya; Effect of interest rate risk exposure on the financial performance of DT-SACCOs in Kenya; Effect of foreign exchange rate risk exposure on the financial performance of DT-SACCOs in Kenya. Effect of operational and market risk exposure on the financial performance of DT-SACCOs in Kenya. The study used panel data between the years 2010-2019 which was 10 years period. The results revealed that at both bivariate and multivariate regression operating expense risk, operating efficiency and foreign exchange risk exposure had a significant effect on the financial performance of DT-SACCOs in Kenya. Only interest rate risk exposure did not have a significant effect on the financial performance of DT-SACCOs in Kenya.
Enterprise risk management (ERM) has gained an increased attention during the recent past as an integrated approach to manage risk for creating and preserving firm value. The objective of this study is to explore and empirically verify as to whether the adoption of the ERM has an impact on the firm performance. This study uses both primary and secondary data pertaining to 129 companies listed on the Colombo Stock Exchange under the banking & finance, insurance, diversified, manufacturing, food and beverage and chemical and pharmaceutical sectors. Primary and secondary data are collected by distributing a survey questionnaire and analyzing the published financial statements of the observing companies. Researcher adopts ERM integrated framework suggested by the committee of sponsoring organization (COSO) of the Treadway Commission of the USA to assess the value relevance of ERM and uses return on equity (ROE) as a proxy to measure the firm performance. This study finds, except for control activities, none of the key ERM functions, suggested by the COSO’s ERM integrated framework, has a significant impact on the performance of listed companies. Internal environment, objective setting, and information & communication indicated a weak positive impact on the firm performance. Nevertheless, none of those impacts were statistically significant. Empirical evidence reveals that firms’ risk responding strategies have no impact on the performance. Surprisingly, monitoring of ERM functions has weak negative, but not significant, impact on the firm performance. These findings are contradictory with the theoretical expectation that the adoption of ERM practices has a positive impact on firm performance as confirmed by the prior researchers.
Hedging as a derivatives instrument is one of the practices in risk management. The hedging decision, among other things, comprises forwards, futures, options, and swaps. This study analyzes managerial ownership, financial distress, leverage, liquidity, profitability, and company size on hedging decisions. This study was conducted in a mining sector company listed on the IDX in 2016-2020. The samples were 27 listed companies that were selected based on the purposive sampling method. The logistic regression model was implemented to test the hypothesis. The results of this study are as follows: managerial ownership, financial distress, and company size significantly affected hedging decisions; liquidity variables have a significant adverse impact on hedging decisions; other variables, namely leverage, and profitability, do not affect hedging decisions because they are insignificant. This study suggests that the management prefers implementing hedging to reduce future risks.
This study evaluates resources allocated for risk management by business organisations (financial and non-financial firms) in developing countries, using Zambia as a case study. Primary data collected from 158 organisations were analysed using MegaStat. The findings revealed that the majority (54.5%) of organisations, especially non-financial institutions, only commit resources to risk mitigation on an Adhoc or post-event basis, while 45.5% showed a budgeted approach. A significant part of the budgeted 45.5% was used for risk management activities, and 54.5% was used for regular daily operations. Despite this variation, all organisations engaged reported a significant expenditure on risk management, at least on Adhoc. At 4 degrees of freedom (df), which was one less than the total number of possible outcomes, a non-parametric test for significance yielded a scientific P-value of 1.57e-0.7, (a numerical magnitude of 0.0014, P< 0.05). This suggests that the correlation and pattern of the findings were not random or by chance, but they carried a statistical significance. The study's main findings demonstrate that some business organisations in Zambia and other developing countries incur significant expenditure with a higher portion of their budgets to respond to risk management needs. Business organisations which do not have formal risk structures do so informally due to pressure from emerging business risks. The findings also indicated that financial institutions in developing countries allocate more resources towards risk management than non-financial institutions. The Phi coefficient (degree of association) was 0.486, showing a moderately significant relationship between the variables (risk management and resource allocation). Business organisations in Zambia and other developing nations must develop sound risk mitigation plans and allocate resources for risk management.
The objective of this paper is to identify the challenges of implementing and adopting an effective ERM system and to suggest alternative strategies that could be pursued as countermeasures to those challenges. This study is based on survey data gathered from 379 respondents representing 129 companies listed on the Colombo Stock Exchange of Sri Lanka. This study found that the lack of availability of information to make risk-based decisions; the need to ensure that all decisions are made within the organization’s risk tolerance level, and the lack of top management support for ERM implementation; are the most influencing challenges for business organizations that obstruct ERM effectiveness. This study suggests that organizations should promote a good corporate culture that fosters ERM supportive internal environment. It is also suggested that the support of the top management and their commitment to being corporative with the firms’ ERM function without making ERM is the sole responsibility of the finance people. Further, it is suggested that organizations have a designated position dedicated to overseeing the ERM function and providing executive leadership for its effective implementation.
The study examined the drivers of Enterprise Risk Management culture in insurance firms in Kenya. The research was conducted using a desktop methodology. This involves the use of qualitative data that is obtained from government publications, public records, historical and statistical documents, and technical and trade journals. This kind of data is commonly preferred since it is easily accessible hence it saves time and cost of field research. Therefore, this study relied on already published studies, public records, and online journals to obtain secondary data that was used to draw the results, conclusion, and recommendations of the study. The results from the empirical review were found to have conceptual and geographical gaps that the current study aimed to fill. Most of the findings from the reviewed studies revealed that the competence of risk assessment strategies, risk treatment strategies, corporate governance frameworks, and risk monitoring frameworks are some of the drivers of ERM culture in Insurance firms. The results also revealed that the implementation of effective ERM culture has a significant impact on the performance of insurance firms. This study will benefit most of the stakeholders in the insurance sector in Kenya. The findings of the study will also enable the risk committee to identify the factors that can help develop and maintain technical models that support the ERM function.
Despite the institutionalization of operational risk management in banks and the strict supervision of bank regulators, operational risk events are still on the increase. It is becoming evident to banks that there is a need to identify the drivers of this risk and nib it at the root to reduce the probability of recurrence. Hence, this study examined the drivers of operational risks in Nigerian commercial banks and the extent to which each driver contributes to operational risk. To achieve the study’s objectives, primary data were collected from the Operational Risk Management Desks of six (6) sampled commercial banks and analyzed using SPSS and Microsoft Excel. The result showed that Internal processes, IT systems and Quality of Risk Officers are determinants of operational losses in banks. The internal process was however indicated as having the most impact. The study concluded that Internal Process is the major driver of operational risk in Nigerian Commercial banks. The researcher, therefore, recommends that bank management must have defined procedures for core activities and prioritize regular review of their critical processes to reduce operational risk events and the associated costs.
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 |