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: 269 / 269 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 00:22 UTC — 22 Oct 2026 07:20 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.
257 / 269 with data · 12 missing or unmatched. Percentages use all 269 selected publications.
256 / 269 with data · 13 missing or unmatched. Percentages use all 269 selected publications.
269 / 269 with data · 0 missing or unmatched. Percentages use all 269 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 | 269 | 269 | 269/269 | 269/269 |
| Publication year | Journal / scope | Crossref citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2020 | All selected publications | 849 | 269 | 269/269 | 269/269 |
| Publication year | Journal / scope | OpenAlex citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2020 | All selected publications | 1640 | 269 | 269/269 | 269/269 |
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 269 / 269 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): 2026-10-21T00:22:02.333469+00:00 — 2026-10-22T07:20:32.875737+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 | 269 | 269/269 |
| 2018 | All selected publications | 0 | 269 | 269/269 |
| 2019 | All selected publications | 2 | 269 | 269/269 |
| 2020 | All selected publications | 52 | 269 | 269/269 |
| 2021 | All selected publications | 189 | 269 | 269/269 |
| 2022 | All selected publications | 295 | 269 | 269/269 |
| 2023 | All selected publications | 401 | 269 | 269/269 |
| 2024 | All selected publications | 345 | 269 | 269/269 |
| 2025 | All selected publications | 245 | 269 | 269/269 |
| 2026 | All selected publications | 111 | 269 | 269/269 |
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 | 269 |
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 | 16 | 67 | 94 | 16/16 | 4.19 | 2.0 | 68.8 | 16/16 · 100.0% |
| International Journal of Business Ecosystem & Strategy Bussecon International Academy | 16 | 54 | 77 | 16/16 | 3.38 | 3.0 | 87.5 | 16/16 · 100.0% |
| International Journal of Finance & Banking Studies SSBFNET | 41 | 169 | 348 | 41/41 | 4.12 | 2 | 80.5 | 41/41 · 100.0% |
| International Journal of Research in Business and Social Science SSBFNET | 196 | 559 | 1121 | 196/196 | 2.85 | 1.0 | 70.4 | 196/196 · 100.0% |
* 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.
Experiencing a pandemic and being quarantined have been proven to have debilitating effects in mental health. Some of the existing studies mentioned in this research have been conducted to assess the presence of possible mental health concerns brought about by the pandemic but most of these studies focused on the earlier phase of the pandemic. The present study focuses on the reported distress of the respondents who have been through a strict quarantine since March 2020 and are now experiencing a more relaxed lockdown. The objective of this research is to determine if COVID stress predicts common mental health concerns such as stress, depression and anxiety. A survey was conducted with 421 Filipino respondents ages 15 – 65 utilizing the COVID Stress Scales (CSS) by Taylor et al. (2020) and DASS-21. Correlational analysis was utilized showing the COVID Stress is a predictor of depression, anxiety, and stress symptoms. Then, comparative analyses were conducted to determine if differences of COVID stress across age groups, gender, occupation, and exposure. The results show that students and unemployed respondents are highly vulnerable to COVID stress and its mental health implications. Men and women did not significantly differ in distress. Surprisingly, those who have a COVID positive family member had the lowest COVID stress and DASS scores. There were 40.7% percent who experienced moderate to severe stress, 60.3% had moderate to severe anxiety and 53.1% of the respondents had moderate to severe depression. These findings show that the pandemic stress has debilitating effects on mental health. Common mental health concerns (e.g. depression and anxiety) may be highly prevalent due to the COVID-19 pandemic
Online banking has become a vital instrument for delivering quality and easily reached banking services at the lowest possible time with ensuring affordability both for customers and service providers. Although this banking has huge potentials and benefits, the successful adoption of online banking remains a significant challenge in the context of an emerging economy like Bangladesh. The purpose of this empirical study is to investigate the factors influencing the online banking services adoption in Bangladesh by using the extended Technology Acceptance Model (TAM) with government support and risk factors. A questionnaire survey method was used to collect data from 380 banking customers. To analyse the collected survey data and test the set of hypothesis, a structural equation modelling (SEM) method was used with the help of SmartPLS3 package. The results illustrate that perceived ease of use, perceived usefulness, attitude towards use, government support positively influence the intention to use as well as the intention to use positively impact on intention to continue to the adoption of online banking services. However, the relationship between risk and intention to use was statistically insignificant. Finally, the findings may assist banking professionals and programmers to develop and design successful policies regarding online banking services to boost this service industry in the future.
Increase in losses borne by banks as a result of inadequate operational risk management practices and the adverse impact on banks’ financial performance has been a major concern to bank management and regulators. This study analysed the impact of operational risk management practices on the financial performance of commercial banks in Nigeria. 10-years (2008 - 2017) secondary data extracted from audited financial statements of selected commercial banks in Nigeria was used for the study. The data was analysed using the Linear Multiple Regression Model. The results showed that there is a positive relationship between operational risk management and the financial performance of banks. The findings revealed that sound operational risk management practices impact positively on the financial performance of banks. We, therefore, recommend that banks’ management should deploy adequate resources towards understanding operational risk to ensure sound operational risk management and improved financial performance of banks.
The recruitment process is more of an issue for many businesses. The process of determining the appropriate candidate to hire is often a costly, time-consuming process. Besides, due to incorrect decision-making or lack of objectivity in hiring processes, recruitment processes may not proceed effectively. Businesses are trying to use technology in their recruitment processes to avoid these problems. Currently, many businesses use internet and software technologies to receive applications and evaluate candidates. But despite these technologies, it takes time and additional personnel costs for people to coordinate all processes. Due to these and similar situations, there has been an increase in the use of artificial intelligence technologies in recruitment processes in the world recently. The use of artificial intelligence in recruitment processes has the effect of reducing costs and decision-making errors and appears to be beneficial in saving time. In this study, the use of artificial intelligence in the recruitment processes of businesses in Turkey was examined. In this context, interviews were conducted with the human resources managers of 22 businesses. According to research results, it was understood that artificial intelligence was benefited only as an auxiliary element in recruitment processes. It has been found that businesses do not rely much on artificial intelligence in their recruitment processes, so they do not use it or partially use it.
This study sought to establish the influence of fraud risk management practices in regard to preventive, detective and corrective controls on the level of fraud occurrence on listed firms in Kenya. This is because limited research had been conducted in the context of listed firms in Kenya and limited attention paid on how corrective controls influences fraud occurrence. A causal research design was applied. Data was obtained from a sample of 275 senior managers by using structured questionnaires. The findings revealed that only preventive and corrective controls had a profound negative effect on the degree of fraud occurrence on listed companies in Kenya. Conversely, detective controls did not considerably reduce fraud occurrence on listed companies in Kenya. The key implication of the findings noted by this study is that the proper implication of the most effectual anti-fraud measures can only be realized when the management are committed to do so. Additionally, corrective controls must be seriously looked into as an effective strategy of curbing fraud since they indeed are instrumental in curbing fraud. Future studies should be extended to the public sector in regard to the government ministries and the distinctive partitions of the private sector such as the insurance, real estate, manufacturing, automobile sectors among others respectively. Moreover, future studies can explore how firm size in terms of asset size or employee size moderates the relationship between fraud risk management practices and the level of fraud occurrence.
This paper focuses on the phenomenon of suicide ravaging Nigerian society. It specifically espouses the causes, manifestations, and feasible panacea to the scourge of suicide in the context of students in higher education in Nigeria. It adopted the content analysis methodology whereby existing secondary data on suicide were comprehensively reviewed and major strands and themes in the data analyzed were used as the basis for the discourse in this paper. The results of the reviewed data reveal that the major causal factors of the upsurge in suicide in Nigeria are attributed to a myriad of problems bedeviling Nigerian society such as; the comatose economy, abject poverty, anomie, globalization, get-rich-syndrome, peer influence, stress, and anxiety associated with socio-economic and political realities of the Nigerian society. These systemic and personal problems negatively impact the youths especially those in the higher institutions of learning because of the rigors associated with academic pursuits in Nigeria. A feasible panacea on how to stem the tide of suicide in Nigeria was discussed at the end of the paper.
Spiritual well-being is the affirmation of one’s life in a relation to external world, one’s ownself and a transcendental power like God. It reflects positive feelings, attitudes, and perceptions leading to a sense of identity, wholeness, peace, harmony, and purpose in life. In this study, it is predicted that individuals with high spiritual well-being will be more spiritually resistant during the COVID-19 pandemic, which is one of the most noteworthy periods when people need to be psychologically strong and resilient. In this study, resilience has been defined as the individual endurance against difficulties and the ability to bounce back and even get better. Hence we hypothesized that spiritual well-being of individuals will be effective on their resilience. We conducted our study in Turkey among adults older than 20 years old. We obtained 384 usable data and we analysed our date by using SPSS 20.0 program. Results confirmed the assumption of this study, regarding spiritual well-being/ resilience relationship.
The recruitment process is more of an issue for many businesses. The process of determining the appropriate candidate to hire is often a costly, time-consuming process. Besides, due to incorrect decision-making or lack of objectivity in hiring processes, recruitment processes may not proceed effectively. Businesses are trying to use technology in their recruitment processes to avoid these problems. Currently, many businesses use internet and software technologies to receive applications and evaluate candidates. But despite these technologies, it takes time and additional personnel costs for people to coordinate all processes. Due to these and similar situations, there has been an increase in the use of artificial intelligence technologies in recruitment processes in the world recently. The use of artificial intelligence in recruitment processes has the effect of reducing costs and decision-making errors and appears to be beneficial in saving time. In this study, the use of artificial intelligence in the recruitment processes of businesses in Turkey was examined. In this context, interviews were conducted with the human resources managers of 22 businesses. According to research results, it was understood that artificial intelligence was benefited only as an auxiliary element in recruitment processes. It has been found that businesses do not rely much on artificial intelligence in their recruitment processes, so they do not use it or partially use it.
With the negative effects of global financial crisis in 2008-2009 and recent Covid 19 pandemic, the need for stress management for individuals and business organizations is significantly increasing. However, the latest advances in digitalization and digital transformation of service companies are reshaping and redesigning the working conditions. This study aimed to explain how stress and burnout syndrome affects the individuals and business organizations. It is also aimed to maintain a theoretical perspective on burnout syndrome models. Main contribution of the paper to literature is its theoretical perspective with fundamental theories and models of burnout syndrome.
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 |