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: 4 / 4 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: 22 Oct 2026 01:34 UTC — 24 Oct 2026 07:05 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.
4 / 4 with data · 0 missing or unmatched. Percentages use all 4 selected publications.
4 / 4 with data · 0 missing or unmatched. Percentages use all 4 selected publications.
4 / 4 with data · 0 missing or unmatched. Percentages use all 4 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 | 1 | 1 | 1/1 | 1/1 |
| 2021 | All selected publications | 2 | 2 | 2/2 | 2/2 |
| 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 |
|---|---|---|---|---|---|
| 2020 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 2021 | All selected publications | 5 | 2 | 2/2 | 2/2 |
| 2022 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2023 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2024 | All selected publications | 0 | 1 | 1/1 | 1/1 |
| Publication year | Journal / scope | OpenAlex citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2020 | All selected publications | 2 | 1 | 1/1 | 1/1 |
| 2021 | All selected publications | 7 | 2 | 2/2 | 2/2 |
| 2022 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2023 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2024 | All selected publications | 0 | 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 4 / 4 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): 2026-10-22T01:34:38.277387+00:00 — 2026-10-24T07:05:19.512122+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 | 4 | 4/4 |
| 2018 | All selected publications | 0 | 4 | 4/4 |
| 2019 | All selected publications | 0 | 4 | 4/4 |
| 2020 | All selected publications | 0 | 4 | 4/4 |
| 2021 | All selected publications | 1 | 4 | 4/4 |
| 2022 | All selected publications | 2 | 4 | 4/4 |
| 2023 | All selected publications | 3 | 4 | 4/4 |
| 2024 | All selected publications | 2 | 4 | 4/4 |
| 2025 | All selected publications | 1 | 4 | 4/4 |
| 2026 | All selected publications | 0 | 4 | 4/4 |
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 | 1 |
| 2021 | 2 |
| 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 Business Ecosystem & Strategy Bussecon International Academy | 1 | 0 | 0 | 1/1 | 0.0 | 0 | 0.0 | 1/1 · 100.0% |
| International Journal of Research in Business and Social Science SSBFNET | 3 | 6 | 9 | 3/3 | 2.0 | 2 | 100.0 | 3/3 · 100.0% |
* Percentage among publications with a known citation count.
This research aims to investigate the effect of the social customer relationship management (CRM) process on achieving superior levels of costumers and financial performance. The object of this research is the Iraqi firms at the Iraqi environment market, while the subject is more than 200 respondents. Six variables from the research data were gathered through an instrument model invalid form that structured to be measured through reliable questionnaires. Statistical Analysis of the research data used partial least squares structural equation modeling with the significance in accordance with the output of SPSS 22.0. The findings indicate that the social CRM technologies of the firms improve the innovation activities on Both (services and products). This has a positive effect on the ability to achieve high performance through building customer-linking capabilities by adopting innovations, resulting in higher levels of efficiency. In exchange, higher levels of consumer contribution lead to having positive levels of customer and financial performance.
Online reviews play a significant role in supporting consumers to make purchase decisions across provided platforms. Many studies examine the characteristics of online reviews and their impacts, nevertheless, only a few studies examine the perceived value from online reviews. This study provides the integration view by utilizing the systematic approach to synthesize 36 academic papers out of 661 searched papers between January 1st, 2011, and December 22nd, 2019. The contribution of researchers in studying the perceived value is increasing significantly and continuously since 2018. There are two main types of online reviews regardless of online platforms: Expert-written reviews and customer-written reviews. Perceived values can be derived from online review and be transmitted to online review simultaneously upon the content of studies. The framing of questions for a review focus on five key questions and to illustrate by providing the mind mapping of perceived value to reveal components and relationship among them. The finding emphasizes the research contents of existing research and research allocation, analysis of techniques used, theories, methodologies used, implications in different industrial sectors to enhance the understanding of this relevant information, ambiguous meanings, and development of areas that lack attention in the past decade. Besides, the indication of studies could identify the importance of perceived values that has a greater impact on consumers in the pre-stage of purchase decision.
The use of Facebook as a social media platform has been cited to revolutionize the performance of different brand and firms globally. The performance of the products and brands has been attributed to the creation of Facebook media brand communities, whose level of engagement influences consumer product outcomes. This study attempted to establish to what extend Facebook social media brand communities and brand engagement on brand trust. The study established that the three attributes of Facebook brand communities positively influenced consumer brand engagement (shared consciousness (?=1.52, p=0.001), shared rituals (?=1.44, p=0.001), obligations to society (?=2.11, p=0.001). The study further established that social media brand engagement positively influenced brand trust. The study recommends that firms should effectively increase their product and brand promotion and engagement through Facebook.
South Africa is one of the most popular tourist destinations on the African continent, with timeshares—vacation properties shared by multiple owners—being an important feature of the tourism industry as it contributes significant growth and sustainability of tourist destinations. After its introduction in the 1960s, timeshare gained popularity through its capability to provide luxury holiday affordability and security in South Africa. Since then, timeshare businesses have used traditional public relations, marketing, advertising strategies and tactics to increase brand awareness and reach sales targets. During the difficult COVID-19 period, global tourism declined drastically due to travel restrictions, extreme lockdowns and tight regulations, forcing businesses to adapt their marketing strategies to cope with unprecedented challenges and the loss of customers. Before the pandemic’s culmination, travel agencies and timeshares thus utilized digital marketing and social media to effectively strategise and publicly engage with their audiences online. Drawing upon McGuire’s (1969) theory of information processing, and Echtner and Ritchie’s (1993) destination image branding, a content and thematic analysis of two South African timeshare companies and their Facebook page content was studied to investigate the public relations tactics and marketing strategies implemented during the COVID-19 pandemic. Key findings reveal that timeshares engaged publicly with customers through posts which stimulated online participation, which included the sharing of images, information, updates, competitions and discounts, thus maximising the potential of social media to engage with stakeholders on a short to long term basis.
South Africa is one of the most popular tourist destinations on the African continent, with timeshares—vacation properties shared by multiple owners—being an important feature of the tourism industry as it contributes significant growth and sustainability of tourist destinations. After its introduction in the 1960s, timeshare gained popularity through its capability to provide luxury holiday affordability and security in South Africa. Since then, timeshare businesses have used traditional public relations, marketing, advertising strategies and tactics to increase brand awareness and reach sales targets. During the difficult COVID-19 period, global tourism declined drastically due to travel restrictions, extreme lockdowns and tight regulations, forcing businesses to adapt their marketing strategies to cope with unprecedented challenges and the loss of customers. Before the pandemic’s culmination, travel agencies and timeshares thus utilized digital marketing and social media to effectively strategise and publicly engage with their audiences online. Drawing upon McGuire’s (1969) theory of information processing, and Echtner and Ritchie’s (1993) destination image branding, a content and thematic analysis of two South African timeshare companies and their Facebook page content was studied to investigate the public relations tactics and marketing strategies implemented during the COVID-19 pandemic. Key findings reveal that timeshares engaged publicly with customers through posts which stimulated online participation, which included the sharing of images, information, updates, competitions and discounts, thus maximising the potential of social media to engage with stakeholders on a short to long term basis.
Online reviews play a significant role in supporting consumers to make purchase decisions across provided platforms. Many studies examine the characteristics of online reviews and their impacts, nevertheless, only a few studies examine the perceived value from online reviews. This study provides the integration view by utilizing the systematic approach to synthesize 36 academic papers out of 661 searched papers between January 1st, 2011, and December 22nd, 2019. The contribution of researchers in studying the perceived value is increasing significantly and continuously since 2018. There are two main types of online reviews regardless of online platforms: Expert-written reviews and customer-written reviews. Perceived values can be derived from online review and be transmitted to online review simultaneously upon the content of studies. The framing of questions for a review focus on five key questions and to illustrate by providing the mind mapping of perceived value to reveal components and relationship among them. The finding emphasizes the research contents of existing research and research allocation, analysis of techniques used, theories, methodologies used, implications in different industrial sectors to enhance the understanding of this relevant information, ambiguous meanings, and development of areas that lack attention in the past decade. Besides, the indication of studies could identify the importance of perceived values that has a greater impact on consumers in the pre-stage of purchase decision.
This research aims to investigate the effect of the social customer relationship management (CRM) process on achieving superior levels of costumers and financial performance. The object of this research is the Iraqi firms at the Iraqi environment market, while the subject is more than 200 respondents. Six variables from the research data were gathered through an instrument model invalid form that structured to be measured through reliable questionnaires. Statistical Analysis of the research data used partial least squares structural equation modeling with the significance in accordance with the output of SPSS 22.0. The findings indicate that the social CRM technologies of the firms improve the innovation activities on Both (services and products). This has a positive effect on the ability to achieve high performance through building customer-linking capabilities by adopting innovations, resulting in higher levels of efficiency. In exchange, higher levels of consumer contribution lead to having positive levels of customer and financial performance.
The use of Facebook as a social media platform has been cited to revolutionize the performance of different brand and firms globally. The performance of the products and brands has been attributed to the creation of Facebook media brand communities, whose level of engagement influences consumer product outcomes. This study attempted to establish to what extend Facebook social media brand communities and brand engagement on brand trust. The study established that the three attributes of Facebook brand communities positively influenced consumer brand engagement (shared consciousness (?=1.52, p=0.001), shared rituals (?=1.44, p=0.001), obligations to society (?=2.11, p=0.001). The study further established that social media brand engagement positively influenced brand trust. The study recommends that firms should effectively increase their product and brand promotion and engagement through Facebook.
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 |