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: 3 / 3 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 07:23 UTC — 22 Oct 2026 01:57 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.
3 / 3 with data · 0 missing or unmatched. Percentages use all 3 selected publications.
3 / 3 with data · 0 missing or unmatched. Percentages use all 3 selected publications.
3 / 3 with data · 0 missing or unmatched. Percentages use all 3 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 |
|---|---|---|---|---|---|
| 2025 | All selected publications | 3 | 3 | 3/3 | 3/3 |
| Publication year | Journal / scope | Crossref citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2025 | All selected publications | 2 | 3 | 3/3 | 3/3 |
| Publication year | Journal / scope | OpenAlex citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2025 | All selected publications | 2 | 3 | 3/3 | 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 3 / 3 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): 2026-10-21T07:23:04.600996+00:00 — 2026-10-22T01:57:03.154658+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 | 3 | 3/3 |
| 2018 | All selected publications | 0 | 3 | 3/3 |
| 2019 | All selected publications | 0 | 3 | 3/3 |
| 2020 | All selected publications | 0 | 3 | 3/3 |
| 2021 | All selected publications | 0 | 3 | 3/3 |
| 2022 | All selected publications | 0 | 3 | 3/3 |
| 2023 | All selected publications | 0 | 3 | 3/3 |
| 2024 | All selected publications | 0 | 3 | 3/3 |
| 2025 | All selected publications | 1 | 3 | 3/3 |
| 2026 | All selected publications | 1 | 3 | 3/3 |
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 |
|---|---|
| 2025 | 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 Business Ecosystem & Strategy Bussecon International Academy | 2 | 2 | 2 | 2/2 | 1.0 | 1.0 | 100.0 | 2/2 · 100.0% |
| International Journal of Research in Business and Social Science SSBFNET | 1 | 0 | 0 | 1/1 | 0.0 | 0 | 0.0 | 1/1 · 100.0% |
* Percentage among publications with a known citation count.
The incorporation of generative artificial intelligence in governance, political knowledge, electoral, and democratic processes is essential as the world transitions to a digital paradigm. Numerous nations have adopted Generative AI (GenAI), a disruptive technology that compels electoral bodies to advocate for the integration of such tools into governance, electoral, and democratic processes. Nevertheless, these technologies do not ensure effortless integration or efficient usage owing to intricate socio-cultural and human dynamics. Certain African jurisdictions are ill-prepared for the adoption of these technologies due to factors including underdevelopment, insufficient electrical supply, lack of technology literacy, reluctance to change, and the goals of governing parties. This study examines generative artificial intelligence as a disruptive technology for enhancing governance, political knowledge, electoral processes, and democracy. A mixed-method approach was employed, incorporating surveys and in-person interviews. The analysis of data, debates, and interpretation of findings were grounded in postdigital theory and theme analysis employing an abductive reasoning technique, in alignment with the tenets of critical realism. The study demonstrated that GENAI can influence political knowledge, election processes, and enhance efficiency in government and democracy. Moreover, GENAI, including ChatGPT, can either exacerbate or mitigate societal tendencies that contribute to human division, facilitate the dissemination of misinformation, perpetuate echo chambers, and undermine social and political trust, as well as polarise disparate groups or sets of viewpoints or beliefs. AI offers substantial opportunities but also poses many obstacles, including technical constraints, ethical dilemmas, and social ramifications. The swift progression of AI may disrupt labour markets by automating tasks conventionally executed by people, resulting in job displacement. Implementing AI necessitates significant upskilling and proficiency with digital tools; therefore, governments and organisations must adequately train their personnel to reconcile the disparity between AI's capabilities and users' comprehension. Additionally, there is a requisite for governmental oversight, regulation, and monitoring of AI adoption and utilisation across all facets of its implementation.
Governments are diligently striving to attain sustainable development objectives. The Constitution of the Republic of South Africa 1996, in Chapter Two, section 27, states that “everyone has the right to health services, water, adequate food, and social security.” These constitutional obligations have established the archetypal local government, described as a governmental entity that upholds the principles of democracy, accountability, transparency, and inclusivity while effectively and efficiently addressing the needs and interests of its community. Nevertheless, the government encounters numerous obstacles in realising an optimal local governance structure. The Fourth Industrial Revolution (4IR) is prompting the government to reevaluate its operations. This study aimed to examine how optimal local governance may be attained through the fourth industrial revolution, emphasising the role of citizens. The research employed technological determinism theory as its theoretical foundation. The study's findings indicate that the Fourth Industrial Revolution enhanced citizen transparency, involvement, and participation in municipal government institutions. The Fourth Industrial Revolution facilitates the implementation of e-government systems to tackle existing developmental challenges. The primary challenge confronting South Africa is the lack of sufficient sustainable resources, encompassing digital illiteracy and inadequate infrastructure support. The report advocates for the critical necessity of investing in skill development and a telecommunications infrastructure that promotes openness and transparency within the socio-institutional aspect of the Fourth Industrial Revolution. The study provides a structured framework that enhances efficiency, transparency, and service delivery by addressing the challenges of digital transition. It retains contextual relevance to South African towns while drawing from worldwide best practices and delineates essential implementation processes, funding sources, and capacity-building activities for government workers. The findings contribute to the discourse on the modernisation of the public sector and digital governance.
This paper examines the role of social media in enhancing public participation within the Mossel Bay Municipality, focusing on both opportunities and challenges. While social media platforms have become important channels for communication, participation, and accountability between citizens and local government, their integration into governance processes in South Africa remains underexplored. Existing literature primarily focuses on national-level initiatives or metropolitan municipalities, leaving a gap in understanding the dynamics of social media use in smaller municipal contexts. This research addresses this gap by investigating how social media platforms can strengthen citizen engagement, participation, and accountability in a local municipality. Employing a qualitative approach, the study involved semi-structured interviews with 20 participants, including municipal officials, councillors, and ward committee members. The findings reveal that social media offers significant opportunities to engage diverse audiences, particularly youth, working adults, and urban populations often excluded from traditional participation channels. However, challenges such as digital inequality, limited interaction, and insufficient strategic planning constrain its effectiveness. The study underscores the need for Mossel Bay Municipality to move beyond one-way communication and develop a comprehensive social media strategy with clear goals, interactive mechanisms, and inclusive engagement practices. By focusing on a local municipal context, this research advances e-governance scholarship in South Africa, highlighting practical strategies for leveraging social media to enhance participatory governance and promote social inclusion.
This paper examines the role of social media in enhancing public participation within the Mossel Bay Municipality, focusing on both opportunities and challenges. While social media platforms have become important channels for communication, participation, and accountability between citizens and local government, their integration into governance processes in South Africa remains underexplored. Existing literature primarily focuses on national-level initiatives or metropolitan municipalities, leaving a gap in understanding the dynamics of social media use in smaller municipal contexts. This research addresses this gap by investigating how social media platforms can strengthen citizen engagement, participation, and accountability in a local municipality. Employing a qualitative approach, the study involved semi-structured interviews with 20 participants, including municipal officials, councillors, and ward committee members. The findings reveal that social media offers significant opportunities to engage diverse audiences, particularly youth, working adults, and urban populations often excluded from traditional participation channels. However, challenges such as digital inequality, limited interaction, and insufficient strategic planning constrain its effectiveness. The study underscores the need for Mossel Bay Municipality to move beyond one-way communication and develop a comprehensive social media strategy with clear goals, interactive mechanisms, and inclusive engagement practices. By focusing on a local municipal context, this research advances e-governance scholarship in South Africa, highlighting practical strategies for leveraging social media to enhance participatory governance and promote social inclusion.
The incorporation of generative artificial intelligence in governance, political knowledge, electoral, and democratic processes is essential as the world transitions to a digital paradigm. Numerous nations have adopted Generative AI (GenAI), a disruptive technology that compels electoral bodies to advocate for the integration of such tools into governance, electoral, and democratic processes. Nevertheless, these technologies do not ensure effortless integration or efficient usage owing to intricate socio-cultural and human dynamics. Certain African jurisdictions are ill-prepared for the adoption of these technologies due to factors including underdevelopment, insufficient electrical supply, lack of technology literacy, reluctance to change, and the goals of governing parties. This study examines generative artificial intelligence as a disruptive technology for enhancing governance, political knowledge, electoral processes, and democracy. A mixed-method approach was employed, incorporating surveys and in-person interviews. The analysis of data, debates, and interpretation of findings were grounded in postdigital theory and theme analysis employing an abductive reasoning technique, in alignment with the tenets of critical realism. The study demonstrated that GENAI can influence political knowledge, election processes, and enhance efficiency in government and democracy. Moreover, GENAI, including ChatGPT, can either exacerbate or mitigate societal tendencies that contribute to human division, facilitate the dissemination of misinformation, perpetuate echo chambers, and undermine social and political trust, as well as polarise disparate groups or sets of viewpoints or beliefs. AI offers substantial opportunities but also poses many obstacles, including technical constraints, ethical dilemmas, and social ramifications. The swift progression of AI may disrupt labour markets by automating tasks conventionally executed by people, resulting in job displacement. Implementing AI necessitates significant upskilling and proficiency with digital tools; therefore, governments and organisations must adequately train their personnel to reconcile the disparity between AI's capabilities and users' comprehension. Additionally, there is a requisite for governmental oversight, regulation, and monitoring of AI adoption and utilisation across all facets of its implementation.
Governments are diligently striving to attain sustainable development objectives. The Constitution of the Republic of South Africa 1996, in Chapter Two, section 27, states that “everyone has the right to health services, water, adequate food, and social security.” These constitutional obligations have established the archetypal local government, described as a governmental entity that upholds the principles of democracy, accountability, transparency, and inclusivity while effectively and efficiently addressing the needs and interests of its community. Nevertheless, the government encounters numerous obstacles in realising an optimal local governance structure. The Fourth Industrial Revolution (4IR) is prompting the government to reevaluate its operations. This study aimed to examine how optimal local governance may be attained through the fourth industrial revolution, emphasising the role of citizens. The research employed technological determinism theory as its theoretical foundation. The study's findings indicate that the Fourth Industrial Revolution enhanced citizen transparency, involvement, and participation in municipal government institutions. The Fourth Industrial Revolution facilitates the implementation of e-government systems to tackle existing developmental challenges. The primary challenge confronting South Africa is the lack of sufficient sustainable resources, encompassing digital illiteracy and inadequate infrastructure support. The report advocates for the critical necessity of investing in skill development and a telecommunications infrastructure that promotes openness and transparency within the socio-institutional aspect of the Fourth Industrial Revolution. The study provides a structured framework that enhances efficiency, transparency, and service delivery by addressing the challenges of digital transition. It retains contextual relevance to South African towns while drawing from worldwide best practices and delineates essential implementation processes, funding sources, and capacity-building activities for government workers. The findings contribute to the discourse on the modernisation of the public sector and digital governance.
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 19:55 UTC · ijrbs | complete · ijrbs · 20 Oct 2026 19:50 UTC |
| openalex-enrichment | 21 Oct 2026 07:23 UTC · ijrbs | complete · ijrbs · 21 Oct 2026 07:22 UTC |