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 01:20 UTC — 22 Oct 2026 03:21 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 | 4 | 4 | 4/4 | 4/4 |
| Publication year | Journal / scope | Crossref citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2020 | All selected publications | 4 | 4 | 4/4 | 4/4 |
| Publication year | Journal / scope | OpenAlex citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2020 | All selected publications | 11 | 4 | 4/4 | 4/4 |
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): 2026-10-22T01:20:04.448283+00:00 — 2026-10-22T03:21:39.422742+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 | 2 | 4 | 4/4 |
| 2022 | All selected publications | 2 | 4 | 4/4 |
| 2023 | All selected publications | 2 | 4 | 4/4 |
| 2024 | All selected publications | 4 | 4 | 4/4 |
| 2025 | All selected publications | 0 | 4 | 4/4 |
| 2026 | All selected publications | 1 | 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 | 4 |
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 Research in Business and Social Science SSBFNET | 4 | 4 | 11 | 4/4 | 1.0 | 0.5 | 50.0 | 4/4 · 100.0% |
* Percentage among publications with a known citation count.
This study evaluated the influence of service tangibility on repeat visits in two-five star rated Hotels in Nairobi County. The significance of service quality cannot be overemphasized it is generally accepted that the interplay of service quality, customer satisfaction, and repeat visitation represents an attractive, cost-effective approach to gain a competitive advantage for most companies though the hotel industry is a very important sector in Kenya as it has many contributions to the economy. The tourism industry in Kenya is currently facing slow progress and the hotels are losing a lot of revenue due to poor services. The main objective of the study was to determine the influence of service tangibility on repeat visits in two-five star-rated hotels in Nairobi County. The specific objectives were to examine Quality and Cleanliness, the influence of Good Menu, and the impact of Comfortable Beds on repeat visits in two-five star-rated hotels in Nairobi. Mixed methods research design was applied based on a cross-sectional survey. The target population comprised of customers in 2-5 star rated hotels in Nairobi County. A questionnaire was used to collect primary data and the researcher conducted a pre-test of the research instruments to establish their validity. The study showed that there is a positive effect of quality attributes on customer satisfaction and customers’ repeat visits to hotels. The study concluded that majorly, the individual service quality attributes and the level of customer satisfaction influence repeat visits in star-rated hotels in Nairobi County
This study aims to test the role of relationship marketing on customer loyalty. The research used a quantitative approach with the survey method. The population of the research is all customers of BRI Bank in Kendari City Indonesia, where the respondent in this research is 77 customer. The cross-sectional data were collected to measure each variable research. Analysis research used Partial Least Squared (PLS) to test the role of each relationship marketing variable in building customer loyalty. The results explained that;(a) communication has a significant role on trust; (b) handling problem has a non-significant role on trust; (c) communication has a significant role on commitment; (d) handling problem has a non-significant role to commitment; (e)trust has a significant role on commitment; (f) communication has a non-significant role on loyalty; (g) handling problem has a non-significant role on loyalty; (h)trust has a significant role to customer loyalty; and (i) commitment has a significant role on loyalty. This study also found that the problem handling variable has no role in building customer loyalty. This study concludes that the BRI Bank is still not good at handling problems with its customers and the variables of trust and commitment play a significant role in mediating the role of communication in building customer loyalty.
This study aims to determine the implementation of the Customer Relationship Marketing (CRM) strategy in increasing Bank Bahteramas Customer Loyalty (CL) in Southeast Sulawesi. This research was conducted at 10 Bahteramas Bank Branch Offices in Southeast Sulawesi, namely; Kendari, Unaaha, Kolaka, Lasusua, Baubau, Raha, Wanci, Kasipute, Andoolo, Wanggudu. The sample in this study was 200 respondents who were distributed in all existing branch offices, where each branch office was taken, 20 respondents. The technique of determining the sample refers to the technique of accident sampling. This study uses multivariate regression. The results found that simultaneously CRM variables consisting of Bonding, Empathy, Reciprocity, Trust, and Commitment simultaneously had a significant effect on CL at Bahteramas Bank in Southeast Sulawesi. Then the partial test results (t-test) showed that: (1) Bonding as CRM strategy significantly influences on CL; (2) Empathy as CRM strategy has an insignificant effect on CL; (3) Reciprocal as CRM strategy has no significant effect on CL; (4) Trust as CRM strategy has a significant effect on CL; (5) Commitment as CRM strategy has a significant effect on CL.
Marketing and strategy research has given a lot of importance to the study of product and service quality improvement. This has been widely studied in the literature as an appropriate competitive strategy to ensure customer satisfaction in the marketplace and gain a sustainable competitive advantage. In this paper, first, we have opted for an extensive review of marketing literature, quality of service and consumer satisfaction. Next, we propose to determine the factors that may affect customer satisfaction in the telecommunications industry in Tunisia. Indeed, each organization chooses to succeed in its strategy of satisfying its customers and to prevent the risk of losing them. Our empirical results indicate that most customers are satisfied with the quality of service provided to them, and most customers believe that Tunisie Telecom's service quality is above their expectations. Quality of reception at the counters of Tunisie Telecom's agencies is the key element for the success of the quality improvement project and is the major factor that can strongly influence client satisfaction and behavior.
This study evaluated the influence of service tangibility on repeat visits in two-five star rated Hotels in Nairobi County. The significance of service quality cannot be overemphasized it is generally accepted that the interplay of service quality, customer satisfaction, and repeat visitation represents an attractive, cost-effective approach to gain a competitive advantage for most companies though the hotel industry is a very important sector in Kenya as it has many contributions to the economy. The tourism industry in Kenya is currently facing slow progress and the hotels are losing a lot of revenue due to poor services. The main objective of the study was to determine the influence of service tangibility on repeat visits in two-five star-rated hotels in Nairobi County. The specific objectives were to examine Quality and Cleanliness, the influence of Good Menu, and the impact of Comfortable Beds on repeat visits in two-five star-rated hotels in Nairobi. Mixed methods research design was applied based on a cross-sectional survey. The target population comprised of customers in 2-5 star rated hotels in Nairobi County. A questionnaire was used to collect primary data and the researcher conducted a pre-test of the research instruments to establish their validity. The study showed that there is a positive effect of quality attributes on customer satisfaction and customers’ repeat visits to hotels. The study concluded that majorly, the individual service quality attributes and the level of customer satisfaction influence repeat visits in star-rated hotels in Nairobi County
This study aims to determine the implementation of the Customer Relationship Marketing (CRM) strategy in increasing Bank Bahteramas Customer Loyalty (CL) in Southeast Sulawesi. This research was conducted at 10 Bahteramas Bank Branch Offices in Southeast Sulawesi, namely; Kendari, Unaaha, Kolaka, Lasusua, Baubau, Raha, Wanci, Kasipute, Andoolo, Wanggudu. The sample in this study was 200 respondents who were distributed in all existing branch offices, where each branch office was taken, 20 respondents. The technique of determining the sample refers to the technique of accident sampling. This study uses multivariate regression. The results found that simultaneously CRM variables consisting of Bonding, Empathy, Reciprocity, Trust, and Commitment simultaneously had a significant effect on CL at Bahteramas Bank in Southeast Sulawesi. Then the partial test results (t-test) showed that: (1) Bonding as CRM strategy significantly influences on CL; (2) Empathy as CRM strategy has an insignificant effect on CL; (3) Reciprocal as CRM strategy has no significant effect on CL; (4) Trust as CRM strategy has a significant effect on CL; (5) Commitment as CRM strategy has a significant effect on CL.
This study aims to test the role of relationship marketing on customer loyalty. The research used a quantitative approach with the survey method. The population of the research is all customers of BRI Bank in Kendari City Indonesia, where the respondent in this research is 77 customer. The cross-sectional data were collected to measure each variable research. Analysis research used Partial Least Squared (PLS) to test the role of each relationship marketing variable in building customer loyalty. The results explained that;(a) communication has a significant role on trust; (b) handling problem has a non-significant role on trust; (c) communication has a significant role on commitment; (d) handling problem has a non-significant role to commitment; (e)trust has a significant role on commitment; (f) communication has a non-significant role on loyalty; (g) handling problem has a non-significant role on loyalty; (h)trust has a significant role to customer loyalty; and (i) commitment has a significant role on loyalty. This study also found that the problem handling variable has no role in building customer loyalty. This study concludes that the BRI Bank is still not good at handling problems with its customers and the variables of trust and commitment play a significant role in mediating the role of communication in building customer loyalty.
Marketing and strategy research has given a lot of importance to the study of product and service quality improvement. This has been widely studied in the literature as an appropriate competitive strategy to ensure customer satisfaction in the marketplace and gain a sustainable competitive advantage. In this paper, first, we have opted for an extensive review of marketing literature, quality of service and consumer satisfaction. Next, we propose to determine the factors that may affect customer satisfaction in the telecommunications industry in Tunisia. Indeed, each organization chooses to succeed in its strategy of satisfying its customers and to prevent the risk of losing them. Our empirical results indicate that most customers are satisfied with the quality of service provided to them, and most customers believe that Tunisie Telecom's service quality is above their expectations. Quality of reception at the counters of Tunisie Telecom's agencies is the key element for the success of the quality improvement project and is the major factor that can strongly influence client satisfaction and behavior.
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 |