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: 6 / 6 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 — 21 Oct 2026 00:49 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.
5 / 6 with data · 1 missing or unmatched. Percentages use all 6 selected publications.
5 / 6 with data · 1 missing or unmatched. Percentages use all 6 selected publications.
6 / 6 with data · 0 missing or unmatched. Percentages use all 6 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 | 3 | 3 | 3/3 | 3/3 |
| 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 | 1 | 1 | 1/1 | 1/1 |
| 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 | 1 | 1 | 1/1 | 1/1 |
| Publication year | Journal / scope | Crossref citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2013 | All selected publications | 2 | 3 | 3/3 | 3/3 |
| 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 | 1 | 1/1 | 1/1 |
| 2020 | All selected publications | 0 | 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 | 1 | 1 | 1/1 | 1/1 |
| Publication year | Journal / scope | OpenAlex citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2013 | All selected publications | 3 | 3 | 3/3 | 3/3 |
| 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 | 1 | 1/1 | 1/1 |
| 2020 | All selected publications | 2 | 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 | 1 | 1 | 1/1 | 1/1 |
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 6 / 6 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): 2026-10-21T00:22:00.229433+00:00 — 2026-10-21T00:49:33.089965+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 | 6 | 6/6 |
| 2018 | All selected publications | 1 | 6 | 6/6 |
| 2019 | All selected publications | 0 | 6 | 6/6 |
| 2020 | All selected publications | 0 | 6 | 6/6 |
| 2021 | All selected publications | 1 | 6 | 6/6 |
| 2022 | All selected publications | 2 | 6 | 6/6 |
| 2023 | All selected publications | 0 | 6 | 6/6 |
| 2024 | All selected publications | 0 | 6 | 6/6 |
| 2025 | All selected publications | 2 | 6 | 6/6 |
| 2026 | All selected publications | 0 | 6 | 6/6 |
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 | 3 |
| 2019 | 1 |
| 2020 | 1 |
| 2024 | 1 |
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 | 4 | 2 | 2 | 4/4 | 0.5 | 0.5 | 50.0 | 4/4 · 100.0% |
| International Journal of Research in Business and Social Science SSBFNET | 2 | 1 | 4 | 2/2 | 0.5 | 0.5 | 50.0 | 2/2 · 100.0% |
* Percentage among publications with a known citation count.
The article seeks to provide innovative measures aimed at addressing the delivery of affordable housing market in South Africa in view of diminishing fiscus and rising interest rates. It defines the mortgage finance trends in South Africa through analysis of primary data from financial institutions to establish the level of activity and contrarians. Upon understanding the market challenges, the author recommends sound proposition with respect to engineering responsive interventions diversify with respect to demand and supply side blockages in the Affordable Housing Market in South Africa. Based on the findings, the author has found that interest rate increases have hurt the property market activity greatly and lenders in turn also apply very stringent underwriting standards at the height of high interest rate cycles. Furthermore, it has been established the mortgage credit impairments have increased resulting in significant credit loss as the majority of low- and middle-income households are overindebted and mortgage debtors are on the verge of being foreclosed on due to the risk of default. The article concludes by providing recommendations as interventions and measures aimed at upscaling the delivery of affordable housing in South Africa.
In investigating the non-payment phenomenon in South Africa’s low income households, a case study of Protea Glenx the researcher employed quantitative tools and qualitative methods. The rationale was prompted by high level of evictions and repossessions for non-payment of mortgages in the Protea Glen area in Johannesburg South Africa. The research approach was to measure and draw sample size from the units of population, conduct interviews and captureand analyse data through the use of SPSS as a suitable statistical instrument. Furthermore, the aim was to employ a suitable model for measuring the relationship between dependent and independent variables and also to highlight the limitations of the study. The findings of the study revealed several interesting empirical results that underpinning the importance of borrower education for mortgage account holders and the need by the banking sector to properly empower borrowers about credit behaviour, responsibilities and obligations of owning a property plus the ongoing costs of ownership.

 
 
 This article was a result of an investigation measuring the ‘Correlation between Borrower Education and Non-payment Behaviour in Low Income Homeowners in South Africa as the premise of the study and poor relationship between lenders and borrowers as the secondary proposition. The study was motivated by the high level of foreclosures for non-payment of mortgages in the Protea Glen area in Johannesburg, Gauteng, as reported by the Human Rights Commission Inquiry in 2008. In investigating this non- payment behaviour the researcher employed largely quantitative instruments supplemented by qualitative methods. The study revealed interesting empirical findings that largely invalidated the founding hypotheses, despite existing theoretical frameworks - underpinned by various scholars - that sought to corroborate the hypotheses. The findings have however supported the premise that households reporting poor relationships with lenders were susceptible to non-payment behaviour. The rest of the secondary hypotheses were rejected by the empirical findings, viz. that there was no correlation between the level of formal education and non-payment behaviour; the link between propensity to default and the age of homeowners were also invalidated. From these findings, it can be demonstrated that there is a critical need for mitigating measures to remedy the identified shortcomings in this sector.
 
 
The purpose of the study was to establish the effect of exchange rate on the performance of the residential property market in Kenya. The study used secondary data that was accumulated using secondary data collection sheet from first quarter of 2005 to fourth quarter of 2018. The study conducted several test statistics and diagnostic tests in order to achieve the most optimal solution. Vector error correction model and auto-regressive distributed lag model were employed to test the hypothesis in the short run and long run respectively. The results found out that exchange rate had a negative effect on performance of residential properties in Kenya in both the short run and positive effect in long run. The study has narrowed down the research gap brought about by the conflicting emprical, theoretical and conceptual literature with regard to the effect of exchange rate on performance of residential property market in Kenya.
 Key Words: Exchange Rate, Performance, Residential Property
This article reflects on social welfare system and governance of housing markets from an end-user perspective. The article criticallyanalyses the way in which social welfare has correlated to unsustainable development and created self entitlement behaviours andattitudes in the South African low income housing market. The phenomenon was demonstrable by empirical research whosefindings confirmed an existence of an association between a fully subsidized social housing model (as underpinned by South Africa’s social welfare) and propensity to default on mortgages. The study found that the risk of default by homeowners in the low income housing market in South Africa is influenced by government’s housing grant model. In other words, the research established that the principle of servicing a mortgaged starter property (that is almost similar to a government free house by both structure and design) is not universally accepted by homeowners of these mortgaged houses. The unintended consequences are that the system has created indefinite expectations that potentially could; (i) erode the country’s balance sheet; (ii) add to non-payment behaviour; (iii) pressurize the economic and credit systems; (iv) propagate entitlement attitudes and mindsets; (v) create social instability and (v) widened the country’s balance of payment deficits.
The article seeks to provide innovative measures aimed at addressing the delivery of affordable housing market in South Africa in view of diminishing fiscus and rising interest rates. It defines the mortgage finance trends in South Africa through analysis of primary data from financial institutions to establish the level of activity and contrarians. Upon understanding the market challenges, the author recommends sound proposition with respect to engineering responsive interventions diversify with respect to demand and supply side blockages in the Affordable Housing Market in South Africa. Based on the findings, the author has found that interest rate increases have hurt the property market activity greatly and lenders in turn also apply very stringent underwriting standards at the height of high interest rate cycles. Furthermore, it has been established the mortgage credit impairments have increased resulting in significant credit loss as the majority of low- and middle-income households are overindebted and mortgage debtors are on the verge of being foreclosed on due to the risk of default. The article concludes by providing recommendations as interventions and measures aimed at upscaling the delivery of affordable housing in South Africa.
The researcher studied and investigated the level of importance of consumers’ choice mainly price, location, safety and security, facilities and amenities, and exclusivity in the Philippines. This research was limited to 400 potential residential property buyers from any of the top 10 real estate developers in the Philippines. This study focused on 5 consumers’ choice factors mainly price, location, safety and security, facilities and amenities, and exclusivity towards purchase intention of residential property in the Philippines. Among the 5 consumers’ choice factors for buying residential property, the number one consideration is the safety and security (Mean = 5.530), followed by price (Mean = 5.488), location (Mean = 5.424), facilities and amenities (Mean = 5.266), and exclusivity (Mean = 4.983). From this study, four out of five consumers’ choice factors are rated very high important namely: price, location, safety and security, and facilities and amenities. On the other hand, exclusivity is rated of high importance in terms of buying a residential property.
The purpose of the study was to establish the effect of exchange rate on the performance of the residential property market in Kenya. The study used secondary data that was accumulated using secondary data collection sheet from first quarter of 2005 to fourth quarter of 2018. The study conducted several test statistics and diagnostic tests in order to achieve the most optimal solution. Vector error correction model and auto-regressive distributed lag model were employed to test the hypothesis in the short run and long run respectively. The results found out that exchange rate had a negative effect on performance of residential properties in Kenya in both the short run and positive effect in long run. The study has narrowed down the research gap brought about by the conflicting emprical, theoretical and conceptual literature with regard to the effect of exchange rate on performance of residential property market in Kenya.
 Key Words: Exchange Rate, Performance, Residential Property
This article reflects on social welfare system and governance of housing markets from an end-user perspective. The article criticallyanalyses the way in which social welfare has correlated to unsustainable development and created self entitlement behaviours andattitudes in the South African low income housing market. The phenomenon was demonstrable by empirical research whosefindings confirmed an existence of an association between a fully subsidized social housing model (as underpinned by South Africa’s social welfare) and propensity to default on mortgages. The study found that the risk of default by homeowners in the low income housing market in South Africa is influenced by government’s housing grant model. In other words, the research established that the principle of servicing a mortgaged starter property (that is almost similar to a government free house by both structure and design) is not universally accepted by homeowners of these mortgaged houses. The unintended consequences are that the system has created indefinite expectations that potentially could; (i) erode the country’s balance sheet; (ii) add to non-payment behaviour; (iii) pressurize the economic and credit systems; (iv) propagate entitlement attitudes and mindsets; (v) create social instability and (v) widened the country’s balance of payment deficits.
In investigating the non-payment phenomenon in South Africa’s low income households, a case study of Protea Glenx the researcher employed quantitative tools and qualitative methods. The rationale was prompted by high level of evictions and repossessions for non-payment of mortgages in the Protea Glen area in Johannesburg South Africa. The research approach was to measure and draw sample size from the units of population, conduct interviews and captureand analyse data through the use of SPSS as a suitable statistical instrument. Furthermore, the aim was to employ a suitable model for measuring the relationship between dependent and independent variables and also to highlight the limitations of the study. The findings of the study revealed several interesting empirical results that underpinning the importance of borrower education for mortgage account holders and the need by the banking sector to properly empower borrowers about credit behaviour, responsibilities and obligations of owning a property plus the ongoing costs of ownership.
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 |