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: 9 / 9 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 00:14 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.
9 / 9 with data · 0 missing or unmatched. Percentages use all 9 selected publications.
9 / 9 with data · 0 missing or unmatched. Percentages use all 9 selected publications.
9 / 9 with data · 0 missing or unmatched. Percentages use all 9 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 |
|---|---|---|---|---|---|
| 2012 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 2013 | All selected publications | 0 | 0 | 0/0 | 0/0 |
| 2014 | All selected publications | 0 | 0 | 0/0 | 0/0 |
| 2015 | All selected publications | 0 | 0 | 0/0 | 0/0 |
| 2016 | All selected publications | 0 | 0 | 0/0 | 0/0 |
| 2017 | All selected publications | 0 | 0 | 0/0 | 0/0 |
| 2018 | All selected publications | 0 | 0 | 0/0 | 0/0 |
| 2019 | All selected publications | 0 | 0 | 0/0 | 0/0 |
| 2020 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 2021 | All selected publications | 0 | 0 | 0/0 | 0/0 |
| 2022 | All selected publications | 0 | 0 | 0/0 | 0/0 |
| 2023 | All selected publications | 0 | 0 | 0/0 | 0/0 |
| 2024 | All selected publications | 0 | 0 | 0/0 | 0/0 |
| 2025 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 2026 | All selected publications | 6 | 6 | 6/6 | 6/6 |
| Publication year | Journal / scope | Crossref citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2012 | All selected publications | 12 | 1 | 1/1 | 1/1 |
| 2013 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2014 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2015 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2016 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2017 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2018 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2019 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2020 | All selected publications | 4 | 1 | 1/1 | 1/1 |
| 2021 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2022 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2023 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2024 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2025 | All selected publications | 0 | 1 | 1/1 | 1/1 |
| 2026 | All selected publications | 0 | 6 | 6/6 | 6/6 |
| Publication year | Journal / scope | OpenAlex citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2012 | All selected publications | 28 | 1 | 1/1 | 1/1 |
| 2013 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2014 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2015 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2016 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2017 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2018 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2019 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2020 | All selected publications | 7 | 1 | 1/1 | 1/1 |
| 2021 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2022 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2023 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2024 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2025 | All selected publications | 0 | 1 | 1/1 | 1/1 |
| 2026 | All selected publications | 0 | 6 | 6/6 | 6/6 |
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 9 / 9 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): 2026-10-21T00:14:35.730060+00:00 — 2026-10-21T07:23:09.614039+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 | 9 | 9/9 |
| 2018 | All selected publications | 2 | 9 | 9/9 |
| 2019 | All selected publications | 3 | 9 | 9/9 |
| 2020 | All selected publications | 2 | 9 | 9/9 |
| 2021 | All selected publications | 4 | 9 | 9/9 |
| 2022 | All selected publications | 5 | 9 | 9/9 |
| 2023 | All selected publications | 2 | 9 | 9/9 |
| 2024 | All selected publications | 6 | 9 | 9/9 |
| 2025 | All selected publications | 2 | 9 | 9/9 |
| 2026 | All selected publications | 0 | 9 | 9/9 |
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 |
|---|---|
| 2012 | 1 |
| 2020 | 1 |
| 2025 | 1 |
| 2026 | 6 |
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 Business Ecosystem & Strategy Bussecon International Academy | 5 | 0 | 0 | 5/5 | 0.0 | 0 | 0.0 | 5/5 · 100.0% |
| International Journal of Finance & Banking Studies SSBFNET | 2 | 16 | 35 | 2/2 | 8.0 | 8.0 | 100.0 | 2/2 · 100.0% |
| International Journal of Research in Business and Social Science SSBFNET | 2 | 0 | 0 | 2/2 | 0.0 | 0.0 | 0.0 | 2/2 · 100.0% |
* Percentage among publications with a known citation count.
Less attention has been given to well-being and other household characteristics that influence clients’ access to micro-credit among women households especially. The paper investigates the determinants of access to credit by 320 women entrepreneurs in the Mfantsiman Municipality in the Central Region of Ghana. Data for the study was collected in June-July 2010 from six communities including Mankessim, Saltpond, Anomabu, Biriwa and Yamoransa. Sturctured questionnaires were used to collect the data from women entrepreneurs. The results of the study indicate that clients’ well-being influences access to credit amount. Clients who have been in business for long time are likely to access larger loan amounts. Marital status and education do not influence access to credit. Among the recommendations are that microfinance should not only target clients with high well-being scores but those with low well-being scores since the original aim of microfinance is to lift the poor out of poverty. It is important to give credit to aged business owners instead of young ones. Giving credit to married women because their husbands could serve as guarantors does not matter much but rather women who do not have husbands also need to benefit from micro-credit.
This study focused on sales-orientation and customer-orientation of Direct Sales Executives (DSEs) on sales performance at Fidelity Bank, Ghana; which was a cross-sectional study. Data were analysed using descriptive statistics, Kendall’s coefficient of concordance, cross tabulation and chi-squared test of independence. The result showed a strong association between prior sales experience and employment status. DSEs customer orientation was influenced by customer information while the sales orientation was on convincing customers to buy. The customer-oriented culture was based on reliable market and customer information. DSEs sales performance were influenced by complete knowledge of the bank’s products and services, listening skills and empathy. The study suggests that Fidelity Bank must sensitize its DSEs on the bank philosophy on its customer orientation culture. This study appears to be the first of its kind to explore the connection between sales orientation and customer orientation on performance in the Banking Industry in Ghana, thus providing empirical evidence for academics and practitioners.
Decentralized approaches to solid waste management (SWM) have gained global attention because of their provision for the effective participation of local communities. This study investigates community participation in decentralized solid waste management policy-making processes, drawing insights from Ghana. Using mixed methods, the study reveals that community participation only takes place at the policy implementation stage and takes the form of planning and managing community-led solid waste management initiatives such as occasional community clean-up exercise during festivals and public holidays, which are usually organized on a frequent basis. Regarding the factors that promote the solid waste management policy-making process, it was realized that “including the community in the solid waste management policy-making process” was the most important factor for the community to participate in the solid waste management policy-making process. Based on these findings, the top-down approach in solid waste management policy should be reversed to bottom-up approaches.
The dearth of studies in sub-Saharan Africa on how eXtensible Business Reporting Language (XBRL) enhances disclosure quality necessitated this study. Thus, this study aims to provide an overview of XBRL in the financial reporting space of sub-Saharan Africa-listed firms. This study discusses the evolution of corporate financial reporting and relates it to how business reporting software enhances the quality of information disclosure and transparency. Based on previous studies, we assessed XBRL in its format for reporting and cost implications from a global perspective. The findings indicated that by reporting using XBRL, we make the case for opening up sub-Saharan African investment markets and improving corporate governance quality in the global investors’ view. In other words, listed firms in the sub-region currently have a periodic and manual reporting approach to financial reporting, which makes it quite difficult for investors to have an up-to-the-minute view of the listed firms for investment purposes. Researchers and business firms need to understand the availability of XBRL technology and its application to enable voluntary corporate disclosures. In addition to the information disclosed, it is important for their search to determine how the software employs information in financial reporting. To the best of our knowledge, this study is one of the few in Africa, especially in the context of sub-Saharan Africa exchanges, to use the review to understand how prior studies involved XBRL reporting to enhance the transparency of listed firms.
This paper aims to examine the quantile-based frequency connectedness between cryptocurrencies and platinum returns across different market conditions and investment horizons. In this paper, it is also aimed to evaluate the asymmetric and time-varying spillover effects between cryptocurrency markets and platinum returns within short-, medium-, and long-term horizons. The study discussed the Heterogeneous Market Hypothesis together with the concepts of cryptocurrencies and platinum as part of the theoretical and conceptual foundations underpinning the analysis. The study adopted the positivist research paradigm, quantitative research approach, and explanatory research design. We employed a hybrid analytical framework combining Quantile Regression (QR), Quantile-on-Quantile Regression (QQR), and Ensemble Empirical Mode Decomposition (EEMD) to capture the non-linear and frequency-dependent dynamics between the selected variables. A dataset comprising daily prices of Cardano (ADA), Binance Coin (BNB), Bitcoin (BTC), Ethereum (ETH), TRON (TRX), Tether (USDT), Dogecoin (DOGE), Ripple (XRP), and platinum returns sourced from CoinMarketCap and the Bloomberg L.P. Terminal was analysed. The main findings of the study demonstrate that (i) the connectedness between cryptocurrencies and platinum returns is generally weak and predominantly inverse in the short term, indicating minimal immediate spillover effects between the two asset classes, (ii) medium-term relationships become significantly stronger with positive dependencies dominating across most quantiles, suggesting increasing integration driven by speculative investment flows and evolving investor sentiment, and finally (iii) long-run connectedness is highly asymmetric and predominantly positive, particularly from cryptocurrencies to platinum returns, although occasional negative dependencies at lower quantiles indicate limited hedging and safe-haven properties during extreme market downturns.
This paper aims to examine the quantile-based frequency connectedness between cryptocurrencies and platinum returns across different market conditions and investment horizons. In this paper, it is also aimed to evaluate the asymmetric and time-varying spillover effects between cryptocurrency markets and platinum returns within short-, medium-, and long-term horizons. The study discussed the Heterogeneous Market Hypothesis together with the concepts of cryptocurrencies and platinum as part of the theoretical and conceptual foundations underpinning the analysis. The study adopted the positivist research paradigm, quantitative research approach, and explanatory research design. We employed a hybrid analytical framework combining Quantile Regression (QR), Quantile-on-Quantile Regression (QQR), and Ensemble Empirical Mode Decomposition (EEMD) to capture the non-linear and frequency-dependent dynamics between the selected variables. A dataset comprising daily prices of Cardano (ADA), Binance Coin (BNB), Bitcoin (BTC), Ethereum (ETH), TRON (TRX), Tether (USDT), Dogecoin (DOGE), Ripple (XRP), and platinum returns sourced from CoinMarketCap and the Bloomberg L.P. Terminal was analysed. The main findings of the study demonstrate that (i) the connectedness between cryptocurrencies and platinum returns is generally weak and predominantly inverse in the short term, indicating minimal immediate spillover effects between the two asset classes, (ii) medium-term relationships become significantly stronger with positive dependencies dominating across most quantiles, suggesting increasing integration driven by speculative investment flows and evolving investor sentiment, and finally (iii) long-run connectedness is highly asymmetric and predominantly positive, particularly from cryptocurrencies to platinum returns, although occasional negative dependencies at lower quantiles indicate limited hedging and safe-haven properties during extreme market downturns.
This paper aims to examine the quantile-based frequency connectedness between cryptocurrencies and palladium returns across different market conditions and investment horizons. In this paper, it is also aimed to evaluate the asymmetric and time-varying spillover dynamics between cryptocurrency markets and palladium returns in order to determine their diversification, hedging, and safe-haven characteristics. The study discussed the Heterogeneous Market Hypothesis together with the concepts of cryptocurrencies and palladium as part of the theoretical and conceptual foundation of the analysis. We employed a hybrid analytical framework combining Quantile Regression (QR), Quantile-on-Quantile Regression (QQR), and Ensemble Empirical Mode Decomposition (EEMD) to capture the non-linear and frequency-dependent relationships between the selected variables. Daily time-series data on palladium prices and major cryptocurrencies, namely Cardano (ADA), Binance Coin (BNB), Bitcoin (BTC), Ethereum (ETH), TRON (TRX), Tether (USDT), Dogecoin (DOGE), and Ripple (XRP), sourced from CoinMarketCap and Bloomberg Terminal, were analysed over the study period. Main findings of the study demonstrate that (i) the connectedness between cryptocurrencies and palladium returns is generally weak in the short term, indicating limited immediate spillover effects between the two markets, (ii) medium- and long-term horizons exhibit stronger and predominantly positive connectedness across most quantiles, particularly from cryptocurrencies to palladium returns, suggesting increasing financial integration over time, and finally (iii) the cryptocurrency–palladium return nexus is asymmetric and state-dependent, with palladium occasionally displaying limited hedging and safe-haven properties during periods of market distress. The study concludes that cryptocurrencies primarily function as diversification instruments rather than consistent hedging assets against palladium market risks. Based on the findings, investors and portfolio managers are encouraged to adopt medium- to long-term investment strategies when integrating cryptocurrencies and palladium within diversified portfolios, while closely monitoring persistent cryptocurrency market trends that may influence palladium price dynamics over time.
This paper examined the connectedness between Copper returns and major cryptocurrency returns, with particular attention to their predictive ability and their roles in diversification and risk transmission across varying market conditions and investment horizons. In this study, it is also aimed to evaluate how these relationships evolve across different quantiles and frequency domains, thereby capturing both distributional asymmetries and time-dependent dynamics. We employed a hybrid analytical approach combining Ensemble Empirical Mode Decomposition and Quantile-on-Quantile Regression to decompose the return series and estimate dependence structures across multiple quantiles and time scales. A dataset comprising daily observations of copper and selected cryptocurrencies, Cardano (ADA), Binance Coin (BNB), Bitcoin (BTC), Ethereum (ETH), TRON (TRX), Tether (USDT), Dogecoin (DOGE), and Ripple (XRP), covering the period from 17 September 2014 to 17 April 2026 was analysed. The main findings of the study demonstrate that (i) short-term connectedness between copper and cryptocurrencies is generally weak, indicating limited immediate transmission of shocks; (ii) medium- and long-term results reveal stronger and more structured dependence, with certain cryptocurrencies, particularly Bitcoin and Binance Coin, exhibiting notable predictive influence on copper returns alongside time-varying co-movements; and finally (iii) the relationship is highly state-dependent, with stronger and asymmetric spillovers emerging during extreme market conditions, suggesting that cryptocurrencies primarily serve as diversifiers rather than consistent hedges. These results highlight the dynamic nature of the cryptocurrency–copper nexus and provide important implications for portfolio diversification, risk management, and financial market monitoring in increasingly interconnected global markets.
This paper examined the connectedness between silver returns and major cryptocurrencies, with particular attention to their predictive ability and their roles as hedging, safe-haven, and diversification instruments across varying market conditions and investment horizons. In this paper, it is also aimed to evaluate how these relationships evolve across different quantiles and frequency domains, thereby capturing both distributional asymmetries and time-dependent dynamics. We employed a hybrid analytical approach combining Ensemble Empirical Mode Decomposition and Quantile-in-Quantile Regression to decompose the return series and estimate dependence structures across multiple quantiles and time scales. A dataset comprising daily observations of silver and selected cryptocurrencies, Cardano (ADA), Binance Coin (BNB), Bitcoin (BTC), Ethereum (ETH), TRON (TRX), Tether (USDT), Dogecoin (DOGE), and Ripple (XRP), covering the period from 17 September 2014 to 17 April 2026 was analysed. The main findings of the study demonstrate that (i) the short-term connectedness between silver and cryptocurrencies is generally weak and statistically insignificant, suggesting limited immediate transmission of shocks between the two markets; (ii) the medium- and long-term results reveal stronger and more structured dependence, with cryptocurrencies, particularly Bitcoin and Binance Coin, exhibiting notable predictive influence on silver returns, alongside evidence of time-varying co-movements; and finally (iii) the nature of the relationship is markedly state-dependent, as certain cryptocurrencies display hedging or diversification benefits under specific market conditions, while others exhibit mixed or asymmetric effects, especially during periods of extreme market stress. The findings indicate that the cryptocurrency–silver nexus is dynamic and evolves across both time horizons and market states, offering delicate implications for portfolio diversification, risk management, and financial market monitoring in an increasingly interconnected global environment.
This paper examined the effect of TQM on environmental performance (EP) and the mediating role of innovation (INN) in this relationship. We employed a quantitative research method and collected cross-sectional data from 320 SMEs in the food and beverages manufacturing industry OF Ghana. We further utilised PLS-SEM to analyse the data collected. The main results revealed that TQM has a favourable and substantial impact on EP (β = 0.812, p-value = 0.000) and on INN (β = 0.771, p-value = 0.000). Additionally, INN has a favourable and substantial impact on EP (β = 0.163, p-value = 0.000), and, finally, INN partially mediates the direct link between TQM and EP (β = 0.126, p-value = 0.000). However, this mediating effect was strongly influenced by continuous improvement, employee involvement and product innovation. Therefore, SMEs in the food and beverages manufacturing sector should consider investing more in continuous improvement and employee involvement initiatives. Also, pay close attention to and adapt to changes in taste and market trends related to their products.
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 |