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: 21 Oct 2026 07:22 UTC — 22 Oct 2026 01:28 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 |
|---|---|---|---|---|---|
| 2023 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 2024 | All selected publications | 3 | 3 | 3/3 | 3/3 |
| Publication year | Journal / scope | Crossref citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2023 | All selected publications | 0 | 1 | 1/1 | 1/1 |
| 2024 | All selected publications | 5 | 3 | 3/3 | 3/3 |
| Publication year | Journal / scope | OpenAlex citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2023 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 2024 | All selected publications | 5 | 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 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): 2026-10-21T07:22:49.809674+00:00 — 2026-10-22T01:28:38.189600+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 | 0 | 4 | 4/4 |
| 2022 | All selected publications | 0 | 4 | 4/4 |
| 2023 | All selected publications | 0 | 4 | 4/4 |
| 2024 | All selected publications | 4 | 4 | 4/4 |
| 2025 | All selected publications | 1 | 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 |
|---|---|
| 2023 | 1 |
| 2024 | 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 | 1 | 2 | 2 | 1/1 | 2.0 | 2 | 100.0 | 1/1 · 100.0% |
| International Journal of Research in Business and Social Science SSBFNET | 3 | 3 | 4 | 3/3 | 1.0 | 0 | 33.3 | 3/3 · 100.0% |
* Percentage among publications with a known citation count.
The adoption of e-procurement systems in developing countries is progressing slowly due to several challenges and barriers. Likewise, the adoption of e-procurement systems has been extensively studied, with research focusing on direct effects of factors like transparency and compatibility. This research aimed to evaluate the direct and indirect effects of relative advantage and performance expectancy on the adoption of e-procurement systems by combining components from the Technology, Organization, and Environment model with a modified Unified Theory of Acceptance and Use of Technology. This was accomplished by analyzing the function of attitude as a mediator and the legal framework as a moderator in the suggested study model. This study used a cross-sectional survey research design, together with a stratified sampling technique, to acquire a sample size of 367 respondents. The data were acquired via the distribution of questionnaires and the examination of relevant documents. The collected data underwent descriptive analysis using IBM SPSS statistics version 26, and inferential analysis was performed using PLS-SEM with the assistance of SmartPLS 4 software. The study's results validate a significant statistical moderating impact of the legal framework on the relationship between performance expectancy and attitude towards adoption of e-procurement system. On the other hand, adoption of e-procurement system is impacted by performance expectancy and relative advantage, which have both direct and indirect significances. Attitudes have a direct impact on the adoption of e-procurement system. This study proposes that future research should include respondents from several countries to improve the applicability of the suggested model.
The existing body of literature on e-procurement adoption has not adequately predicted the direct and indirect impact of performance expectancy and effort expectancy on the usage behavior of e-procurement system through the attitude of users. This paper focuses on analyzing the direct and indirect effects of various factors that influence the usage behavior of e-procurement systems in Tanzania. The paper was guided by the Social Information Processing (SIP) theory, the Affect Infusion Model (AIM), and the modified Unified Theory of Acceptance and Use of Technology (UTAUT). The paper also used a deductive perspective and an explanatory cross-sectional survey research approach. A stratified sampling technique was used to identify 383 respondents (buyers and suppliers) that use the e-procurement system. Data gathering was conducted via the use of a documentary review and questionnaire. Inferential statistical analysis was conducted using the Partial Least Squares Structural Equation Modeling, with the assistance of SmartPLS 4 software. The results indicate that performance expectancy, effort expectancy, and attitude significantly influence positively the usage behavior of the e-procurement system (p value<0.05). The paper finds that the behavior of buyers and suppliers, after the adoption of an e-procurement system, is indirectly impacted by the system's performance expectancy and effort expectancy, via their positive attitudes. The results of this study confirm the usefulness of the proposed research model in directing management decision-making, particularly in determining the importance of investment considerations when implementing or improving an e-procurement system.
This article aims to assess the direct and indirect influence of suppliers' and buyers' behavioral intention on the performance of public procurement in Tanzania. This is accomplished by analyzing their utilization of the e-procurement system, using an adapted rendition of the Unified Theory of Acceptance and Use of Technology. The study used an explanatory cross-sectional survey research design and implemented a stratified sampling method to choose a sample of 312 participants, comprising of both customers and providers. The data collecting process included administering a questionnaire consisting of closed-ended questions and conducting a thorough examination of pertinent documents. The gathered data was then examined using Partial Least Squares Structural Equation Modeling, with the aid of SmartPLS 4 software. The findings indicate that behavioral intention has a favorable, direct, and indirect impact on the performance of public procurement. The research suggests that the effectiveness of public procurement is indirectly impacted by the behavioral inclination of both buyers and suppliers to use the e-procurement system. Moreover, the efficiency of the e-procurement system is significantly impacted by the use patterns of both purchasers and vendors. Therefore, it is recommended that developing countries, such as Tanzania, should take into account the behavioral intention and usage behavior of both buyers and suppliers before, during, and after the adoption of an e-procurement system.
This study examined the influence of customer experience on the preference for online bus booking services in Dar es Salaam, Tanzania. Specifically, the study aims to: i) Determine the influence of familiarity with online booking services on the customer preference for online bus booking services, ii) Examine the influence of perception on the customer preference for online booking services, iii) Examine the influence of customer satisfaction on the customer preference for online bus booking services. The study employed a convergent parallel research design whereas both qualitative and quantitative data were collected. A sample of 384 users of buses for their transport was involved using a questionnaire that was administered through Google form as one of the web-based tools. Qualitative data were analyzed using content analysis whereas quantitative data were analyzed using descriptive statistics whereas mean scores, standard deviations, frequency, and percent were computed. Further, a binary logistic regression model was performed to analyze quantitative data. The findings show that customer perception and satisfaction were statistically significant in influencing customers’ preference for online bus booking. The study recommends to all key players in the bus transport sector make use of the findings to enrich policies and strategies in the adoption of online bus booking.
This article aims to assess the direct and indirect influence of suppliers' and buyers' behavioral intention on the performance of public procurement in Tanzania. This is accomplished by analyzing their utilization of the e-procurement system, using an adapted rendition of the Unified Theory of Acceptance and Use of Technology. The study used an explanatory cross-sectional survey research design and implemented a stratified sampling method to choose a sample of 312 participants, comprising of both customers and providers. The data collecting process included administering a questionnaire consisting of closed-ended questions and conducting a thorough examination of pertinent documents. The gathered data was then examined using Partial Least Squares Structural Equation Modeling, with the aid of SmartPLS 4 software. The findings indicate that behavioral intention has a favorable, direct, and indirect impact on the performance of public procurement. The research suggests that the effectiveness of public procurement is indirectly impacted by the behavioral inclination of both buyers and suppliers to use the e-procurement system. Moreover, the efficiency of the e-procurement system is significantly impacted by the use patterns of both purchasers and vendors. Therefore, it is recommended that developing countries, such as Tanzania, should take into account the behavioral intention and usage behavior of both buyers and suppliers before, during, and after the adoption of an e-procurement system.
The existing body of literature on e-procurement adoption has not adequately predicted the direct and indirect impact of performance expectancy and effort expectancy on the usage behavior of e-procurement system through the attitude of users. This paper focuses on analyzing the direct and indirect effects of various factors that influence the usage behavior of e-procurement systems in Tanzania. The paper was guided by the Social Information Processing (SIP) theory, the Affect Infusion Model (AIM), and the modified Unified Theory of Acceptance and Use of Technology (UTAUT). The paper also used a deductive perspective and an explanatory cross-sectional survey research approach. A stratified sampling technique was used to identify 383 respondents (buyers and suppliers) that use the e-procurement system. Data gathering was conducted via the use of a documentary review and questionnaire. Inferential statistical analysis was conducted using the Partial Least Squares Structural Equation Modeling, with the assistance of SmartPLS 4 software. The results indicate that performance expectancy, effort expectancy, and attitude significantly influence positively the usage behavior of the e-procurement system (p value<0.05). The paper finds that the behavior of buyers and suppliers, after the adoption of an e-procurement system, is indirectly impacted by the system's performance expectancy and effort expectancy, via their positive attitudes. The results of this study confirm the usefulness of the proposed research model in directing management decision-making, particularly in determining the importance of investment considerations when implementing or improving an e-procurement system.
The adoption of e-procurement systems in developing countries is progressing slowly due to several challenges and barriers. Likewise, the adoption of e-procurement systems has been extensively studied, with research focusing on direct effects of factors like transparency and compatibility. This research aimed to evaluate the direct and indirect effects of relative advantage and performance expectancy on the adoption of e-procurement systems by combining components from the Technology, Organization, and Environment model with a modified Unified Theory of Acceptance and Use of Technology. This was accomplished by analyzing the function of attitude as a mediator and the legal framework as a moderator in the suggested study model. This study used a cross-sectional survey research design, together with a stratified sampling technique, to acquire a sample size of 367 respondents. The data were acquired via the distribution of questionnaires and the examination of relevant documents. The collected data underwent descriptive analysis using IBM SPSS statistics version 26, and inferential analysis was performed using PLS-SEM with the assistance of SmartPLS 4 software. The study's results validate a significant statistical moderating impact of the legal framework on the relationship between performance expectancy and attitude towards adoption of e-procurement system. On the other hand, adoption of e-procurement system is impacted by performance expectancy and relative advantage, which have both direct and indirect significances. Attitudes have a direct impact on the adoption of e-procurement system. This study proposes that future research should include respondents from several countries to improve the applicability of the suggested model.
This study examined the influence of customer experience on the preference for online bus booking services in Dar es Salaam, Tanzania. Specifically, the study aims to: i) Determine the influence of familiarity with online booking services on the customer preference for online bus booking services, ii) Examine the influence of perception on the customer preference for online booking services, iii) Examine the influence of customer satisfaction on the customer preference for online bus booking services. The study employed a convergent parallel research design whereas both qualitative and quantitative data were collected. A sample of 384 users of buses for their transport was involved using a questionnaire that was administered through Google form as one of the web-based tools. Qualitative data were analyzed using content analysis whereas quantitative data were analyzed using descriptive statistics whereas mean scores, standard deviations, frequency, and percent were computed. Further, a binary logistic regression model was performed to analyze quantitative data. The findings show that customer perception and satisfaction were statistically significant in influencing customers’ preference for online bus booking. The study recommends to all key players in the bus transport sector make use of the findings to enrich policies and strategies in the adoption of online bus booking.
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 |