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: 16 / 16 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 01:09 UTC — 28 Oct 2026 23:22 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.
16 / 16 with data · 0 missing or unmatched. Percentages use all 16 selected publications.
16 / 16 with data · 0 missing or unmatched. Percentages use all 16 selected publications.
16 / 16 with data · 0 missing or unmatched. Percentages use all 16 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 |
|---|---|---|---|---|---|
| 2019 | All selected publications | 16 | 16 | 16/16 | 16/16 |
| Publication year | Journal / scope | Crossref citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2019 | All selected publications | 50 | 16 | 16/16 | 16/16 |
| Publication year | Journal / scope | OpenAlex citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2019 | All selected publications | 101 | 16 | 16/16 | 16/16 |
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 16 / 16 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): 2026-10-22T01:09:49.857716+00:00 — 2026-10-28T23:22:07.895300+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 | 16 | 16/16 |
| 2018 | All selected publications | 0 | 16 | 16/16 |
| 2019 | All selected publications | 0 | 16 | 16/16 |
| 2020 | All selected publications | 9 | 16 | 16/16 |
| 2021 | All selected publications | 14 | 16 | 16/16 |
| 2022 | All selected publications | 21 | 16 | 16/16 |
| 2023 | All selected publications | 18 | 16 | 16/16 |
| 2024 | All selected publications | 19 | 16 | 16/16 |
| 2025 | All selected publications | 14 | 16 | 16/16 |
| 2026 | All selected publications | 6 | 16 | 16/16 |
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 ↗
Records with full publication dates only. 2026 is an incomplete year.
| Period | Publications |
|---|---|
| 2019-03 | 1 |
| 2019-05 | 1 |
| 2019-07 | 3 |
| 2019-08 | 1 |
| 2019-10 | 7 |
| 2019-11 | 1 |
| 2019-12 | 2 |
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 | 3 | 6 | 2/2 | 1.5 | 1.5 | 50.0 | 2/2 · 100.0% |
| International Journal of Research in Business and Social Science SSBFNET | 14 | 47 | 95 | 14/14 | 3.36 | 2.0 | 78.6 | 14/14 · 100.0% |
* Percentage among publications with a known citation count.
Numerous studies have addressed the different context of mHealth services among diverse user groups. But due to a lack of understanding the insight of factors affecting the mHealth adoption, it’s crucial need to conduct a systematic review on this issue. The objective of this study was to synthesize the present understanding of the influential factors of mHealth adoption. We performed a systematic literature search on eight electronically reputed scientific databases from 2010 to March 2019, such as Science Direct, Springer, IEEE Xplore, JMIR, Taylor & Francis, Emerald, Mary Ann Liebert and Google Scholar. This was accomplished by gathering data including authors, countries, years, target population, sample size, models/theories, and key influential factors. Primarily, a total of 2969 potentially relatable papers were found, of which 50 met the inclusion criteria. It was found that cross-sectional approach, survey methods and structural equation modeling (SEM) were the most explored research methodologies whereas PLS-SEM was found to be the largest used analysis tools. From the analysis, a total of ninety-four influential factors were clearly recognized and the findings represent that the following 15 factors appeared most recurrently and significantly; perceived usefulness, perceived ease of use, social-influence, subjective norms, self-efficacy, trust, facilitating conditions, technology anxiety, performance expectancy, effort expectancy, cost, attitude, resistance to change, perceived privacy and security, and perceived behavioral control. The research results have significant theoretical and practical implications for mHealth services providers, researchers and policy makers with regards to the Sustainable Development Goals (SDGs) allied to healthcare.
Knowledge management is one of the most important strategic resources of the firm which has been ascertained to many organizations to acquire and apply it before their competitor for achieving competitive advantages. Similarly, due to rising environmental awareness among customers, governments, NGOs, and researchers, firms are facing increasing pressure to implement environmental management practices in their operations. The purpose of this paper is to identify the influence of knowledge management capability (KMC) on green supply chain management (GSCM) practices adoption of the manufacturing firm and subsequently the impact on firm performance. The data were collected from 262 Bangladeshi textile manufacturing firms and analyzed using structural equation modeling, typifying that exploratory and quantitative research. Drawing upon the resource-based view the study revealed that KMC has a significant positive effect on internal and external-GSCM practices adoption. Further, the study revealed that internal-GSCM practices have significantly positive effects on both economic and environmental performance while the external-GSCM practice has positive environmental performance but negatively affects economic performance. Finally, this study indicates that KMC is an intuitive resource of a firm that can bring sustainable performance through GSCM practices.
Preceding researchers have tended to focus on the negative aspect of the perceived overqualification and its inadequacy in the organization. We offer an alternative perspective and postulate that perceived overqualification could influence employees’ behavior through an interactive mechanism. We propose that relational skill abilities, in the form of job autonomy of overqualified employees, determine their tendency to experience interpersonal influences, and, thus engage in helping behavior with devastating work deviance behavior. Data were collected from 20 multinational companies in China through a survey of 500 participants. Structural equation modeling was used for the analysis of data. The results indicate that perceived overqualification has a strong indirect impact via interpersonal influence on the helping behavior and workplace deviance behavior, and increase the helping behavior and decrease the workplace deviance behavior at the working environment. Further, outcomes concluded that job autonomy and prosocial motivation have a significant moderating role and increase the employers helping behavior and deteriorations their Workplace deviance behavior.
Though it is called corporate social responsibility (CSR), it is the people in the organization particularly, top managers who develop and get implemented corporate social policies. Organization behavior is the reflection of their top managers. However, exploration of the role of top managers in spreading CSR in the organization is scant in the literature. The purpose of this paper is to explore the impact of top managers’ CSR perceptions on firm-level CSR in Ethiopia. Structured questionnaires were used to collect data from 294 executive managers of four sectors, namely textile, food, bank, and floriculture industries. Multiple hierarchical regression and process macro 3.3 were employed to analyze the data with the aid of SPSS. The analysis reveals that top managers’ CSR perception is a significant predictor of firm-level CSR behaviors. The result also shows that corporate ethical culture fully mediates the relationship between top managers’ CSR perception and organization CSR. Moreover, transformational leadership has a moderating effect between the direct top managers’ CSR perception and firm-level CSR relationship.
Intense competition has in many markets decreased the prospects for differentiation in terms of technology and product/service quality. For this reason, CSR becomes an important attribute that can enhance a company's image. To win customers' loyalty in today's markets, companies have to focus on building and sustaining customer loyalty. Nowadays, organizations looking forward to achieving a sustainable competitive improvement based on focusing on a customer-oriented concept which will lead to customer satisfaction, trust and finally to customer loyalty. In this regard, CSR has become a valuable tool. This research, therefore, aims to investigate the direct effect of CSR on customer loyalty by observing the intervening influence of Perceived service quality and trust. In this research, it is proved CSR aspects namely business practice CSR which is related to primary stakeholders, such as customers and employees, and philanthropic CSR, which is related to secondary stakeholders, such as the community has a positive and significant effect on the customer loyalty. Moreover, perceived service quality and trust also serve as an intervener between CSR and Loyalty. Data collected from account holders of three main banks in Kenya. Structural equation modeling is examined by using PLS software. The findings of this study would help scholars in developing more CSR based loyalty models. These findings can also aid the service industry such as commercial banks in Kenya to better incorporate CSR initiatives in their strategic planning process
The purpose of this study was to assess the effect of indirect investment on the performance of real estate in Nairobi County Kenya. The independent variables for indirect investment were: investment trusts, exchange-traded funds, commingled funds, and infrastructure funds. The dependent variable was the performance of real estate in Nairobi County Kenya. Secondary data was collected from the real estate’s online sources and some from the company offices and analyzed using multiple regression analysis. Both descriptive statistics and inferential statistics were determined. The study was only able to collect secondary data from 45 real estate companies out of the target population of 69 registered by KPDA in 2015 as it was hard to get data of the rest either from online sources or from the company offices. With the aid of STATA 12.0 software and Excel software, quantitative results were tabulated and presented in the form of charts, bar graphs, and narratives. The study found an existing relationship between the performance of the real estate sector and the Investment Trust Fund, the Exchange Trust Fund, the Commingled Fund, Infrastructure Fund. The study concludes that most of the coefficients were significant. The study also concludes that there is a relationship between the performance of the real estate sector and the Investment Trust Fund, Exchange Trust Fund, Commingled Fund, Infrastructure Fund when these components are considered together, they affect Performance.
Though it is called corporate social responsibility (CSR), it is the people in the organization particularly, top managers who develop and get implemented corporate social policies. Organization behavior is the reflection of their top managers. However, exploration of the role of top managers in spreading CSR in the organization is scant in the literature. The purpose of this paper is to explore the impact of top managers’ CSR perceptions on firm-level CSR in Ethiopia. Structured questionnaires were used to collect data from 294 executive managers of four sectors, namely textile, food, bank, and floriculture industries. Multiple hierarchical regression and process macro 3.3 were employed to analyze the data with the aid of SPSS. The analysis reveals that top managers’ CSR perception is a significant predictor of firm-level CSR behaviors. The result also shows that corporate ethical culture fully mediates the relationship between top managers’ CSR perception and organization CSR. Moreover, transformational leadership has a moderating effect between the direct top managers’ CSR perception and firm-level CSR relationship.
This study attempts to clarify and evaluate the factors that impact on cotton sector production in Cameroon and differentiate producers `behavior. A description of producers ‘behaviour is made in order to identify their main characteristics, which should shed light on the relationships between cotton textile production , the main producers` characteristics price and non-price variables. An inventory of ongoing sectoral agricultural policies is presented and suggestions are made for formulating alternative policies. The next section presents both a review of agricultural policies and the cotton sector in Cameroon. The third and fourth sections are literature review and cotton belt while the fifth presents the methodology. Discussion and interpretation of the empirical findings is followed by the conclusion and policy recommendations.
Practitioners and academics have been perplexed over the years by low efficiency and bad performance in construction projects. Several critical factors have been uncovered by previous studies which are governance mechanism, task conflict and opportunism. But an obvious question arises how the mechanism of governance in the presence of conflict can mitigate opportunism. The overarching objective of this study is therefore to create a model to study the effectiveness of these mechanisms of governance in the presence of task conflict. This paper is based on a positivist study philosophy in which a quantitative deductive method was used to collect data from 139 participants. Hypotheses were tested using structural equation modeling (SEM) through SmartPLS3.The research findings show that relational governance affects project efficiency considerably and is helpful in decreasing opportunism and conflict. In addition, there is proof that opportunistic behavior will increase the task conflict among parties but both task conflict and opportunism doesn’t have direct impact on the performance of project
Numerous studies have addressed the different context of mHealth services among diverse user groups. But due to a lack of understanding the insight of factors affecting the mHealth adoption, it’s crucial need to conduct a systematic review on this issue. The objective of this study was to synthesize the present understanding of the influential factors of mHealth adoption. We performed a systematic literature search on eight electronically reputed scientific databases from 2010 to March 2019, such as Science Direct, Springer, IEEE Xplore, JMIR, Taylor & Francis, Emerald, Mary Ann Liebert and Google Scholar. This was accomplished by gathering data including authors, countries, years, target population, sample size, models/theories, and key influential factors. Primarily, a total of 2969 potentially relatable papers were found, of which 50 met the inclusion criteria. It was found that cross-sectional approach, survey methods and structural equation modeling (SEM) were the most explored research methodologies whereas PLS-SEM was found to be the largest used analysis tools. From the analysis, a total of ninety-four influential factors were clearly recognized and the findings represent that the following 15 factors appeared most recurrently and significantly; perceived usefulness, perceived ease of use, social-influence, subjective norms, self-efficacy, trust, facilitating conditions, technology anxiety, performance expectancy, effort expectancy, cost, attitude, resistance to change, perceived privacy and security, and perceived behavioral control. The research results have significant theoretical and practical implications for mHealth services providers, researchers and policy makers with regards to the Sustainable Development Goals (SDGs) allied to healthcare.
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 |