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: 11 / 11 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 00:49 UTC — 21 Oct 2026 07:23 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.
11 / 11 with data · 0 missing or unmatched. Percentages use all 11 selected publications.
11 / 11 with data · 0 missing or unmatched. Percentages use all 11 selected publications.
11 / 11 with data · 0 missing or unmatched. Percentages use all 11 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 |
|---|---|---|---|---|---|
| 2017 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 2018 | All selected publications | 0 | 0 | 0/0 | 0/0 |
| 2019 | All selected publications | 0 | 0 | 0/0 | 0/0 |
| 2020 | All selected publications | 0 | 0 | 0/0 | 0/0 |
| 2021 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 2022 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 2023 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 2024 | All selected publications | 4 | 4 | 4/4 | 4/4 |
| 2025 | All selected publications | 2 | 2 | 2/2 | 2/2 |
| 2026 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| Publication year | Journal / scope | Crossref citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2017 | All selected publications | 0 | 1 | 1/1 | 1/1 |
| 2018 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2019 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2020 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2021 | All selected publications | 3 | 1 | 1/1 | 1/1 |
| 2022 | All selected publications | 4 | 1 | 1/1 | 1/1 |
| 2023 | All selected publications | 0 | 1 | 1/1 | 1/1 |
| 2024 | All selected publications | 8 | 4 | 4/4 | 4/4 |
| 2025 | All selected publications | 0 | 2 | 2/2 | 2/2 |
| 2026 | All selected publications | 0 | 1 | 1/1 | 1/1 |
| Publication year | Journal / scope | OpenAlex citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2017 | All selected publications | 0 | 1 | 1/1 | 1/1 |
| 2018 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2019 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2020 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2021 | All selected publications | 5 | 1 | 1/1 | 1/1 |
| 2022 | All selected publications | 9 | 1 | 1/1 | 1/1 |
| 2023 | All selected publications | 2 | 1 | 1/1 | 1/1 |
| 2024 | All selected publications | 11 | 4 | 4/4 | 4/4 |
| 2025 | All selected publications | 0 | 2 | 2/2 | 2/2 |
| 2026 | 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 11 / 11 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): 2026-10-21T00:49:30.109996+00:00 — 2026-10-21T07:23:05.181578+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 | 11 | 11/11 |
| 2018 | All selected publications | 0 | 11 | 11/11 |
| 2019 | All selected publications | 0 | 11 | 11/11 |
| 2020 | All selected publications | 0 | 11 | 11/11 |
| 2021 | All selected publications | 0 | 11 | 11/11 |
| 2022 | All selected publications | 1 | 11 | 11/11 |
| 2023 | All selected publications | 3 | 11 | 11/11 |
| 2024 | All selected publications | 9 | 11 | 11/11 |
| 2025 | All selected publications | 7 | 11 | 11/11 |
| 2026 | All selected publications | 7 | 11 | 11/11 |
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 |
|---|---|
| 2017 | 1 |
| 2021 | 1 |
| 2022 | 1 |
| 2023 | 1 |
| 2024 | 4 |
| 2025 | 2 |
| 2026 | 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 Research in Business and Social Science SSBFNET | 11 | 15 | 27 | 11/11 | 1.36 | 1 | 54.5 | 11/11 · 100.0% |
* Percentage among publications with a known citation count.
The COVID-19 pandemic that disrupted national economic activities had an impact on the MSME sector. This study examines the mediating role of company performance in supporting competitive advantage during the pandemic, which is a difficult time for MSMEs. This research collaborates entrepreneurial orientation and market orientation so that it can be predicted the factors that support MSMEs in creating competitive advantage. The sample of this research is the owners or business actors of MSMEs in the Cilacap district as many as 100 respondents and PLS-SEM is used to analyze the data. The results show that business performance acts as a full mediation for entrepreneurial orientation and competitive advantage. Market orientation has a direct effect on competitive advantage, but business performance does not mediate market orientation and competitive advantage. The results of the study also show that there are market orientation findings that act as a full mediation of the relationship between entrepreneurial orientation and competitive advantage. From these results, it can be concluded that entrepreneurial orientation requires business performance and market orientation to influence competitive advantage.
The ever-evolving digital marketing landscape has continuously adapted to technological advancement, consumer behaviour and ecosystem trends. The 21st century marketplace needs traditional marketing practices, and digital platforms to ensure the actualisation of their growth and development in the ecosystem. The study examined how different digital marketing platforms can influence SMEs' operations and performance (Online marketing, and ICT initiatives). The study employed a quantitative design with primary data collection via a questionnaire designed based on 5-Likert’s Scale to answer the research questions; if there is a significant relationship between Online Marketing and SMEs' Business Competitiveness, and if ICT initiative has a positive relationship with SMEs' Business Growth. Two (2) hypotheses were formulated and tested using a statistical package for social sciences (SPSS). To ascertain the hypotheses formulated, both descriptive and regression analyses were carried out, and the output clearly showed a significant influence of digital marketing on the performance of SMEs. The result shows a positive impact of online marketing on SME business competitiveness. However, this study concluded that in the technology-driven environment, 21st-century SMEs will always see the usefulness and relevance of digital marketing because of its role in improving their performance. This study recommends that SMEs incorporate intensive digital platforms and engage in time-to-time updates of their online marketing channels.
Digital transformation has created an information revolution, eliminated boundaries, created a knowledge-based global market, and in MSMEs finding new business models, conducting business transactions and collaborating in all fields to form economic strength. Activities that are completely digital, even transaction activities are carried out digitally because they are faster, more effective and efficient. Therefore, MSMEs can apply a business model strategy that can combine online and offline activities. To increase their capability, MSMEs start with developing strategies to become hybrid businesses and combined online and offline business models. In this case, the authors conducted research on MSMEs that use strategies to combine online and offline business, this study offers guidance for MSMEs on what strategies should be used in achieving a business hybrid so that online and offline business models can be combined. In the formation of a business hybrid, there are five capabilities, namely, assimilative capability, ambidextrous capability, environmental capability, autonomous capability and digital and non-digital competitiveness capability. The ability of assimilative can improve managerial ability in the company, absorb knowledge or resources not only from the external environment, but can come from different business units within a company.
Various studies have been carried out to establish the key drivers impacting small enterprise sustainable performance in developing countries. Despite many policy-oriented studies to uncover the factors influencing SME resilience in emerging markets, these firms continue to register high failure rate, which has been further exacerbated by the Covid-19 pandemic. Guided by a history of linear- and log-linear econometric model estimation that ignores potential network effects, our study extends the literature by implicating SMME resilience as a production network. Utilising data from both incubated and non-incubated SMMEs, marking a departure from traditional linear econometric models, radial basis function artificial neural network algorithm was invoked to establish the drivers of SMME resilience during Covid-19 regime. The study extends the literature by implicating eXplainable Artificial Intelligence (XAI) methods. Specifically, optimal SHapley Additive Explanations values (SHAP values) were computed to enhance the prediction output from the machine learning algorithm. The XAI analytics provide insightful findings on the key drivers which influenced the resilience of SMMEs during the Covid-19 pandemic. The importance of innovation through introduction of new products, company age and higher number of marketing mediums is confirmed however total assets, analytics, educational level and number of workers surfaced as a threat to these enterprises’ sustainable performance. The study recommends that both the government and SMEs should leverage XAI to identify their heterogeneous attributes and inform intelligent decision-making which necessities their resilient performance.
This study aims to analyze the influence of innovation, competitiveness, and business ecosystem variables on strengthening the local economy. The development of small businesses as the basis of the people's economy is one of the strategic steps that need to be followed up with concrete steps to increase family productivity, improve the economy, and overcome the problems of poverty, and unemployment. Community business is one of the strengthening of the local economy. This research is field research with qualitative and quantitative approaches to provide a comprehensive explanation. The research sample was MSME business actors in Sukajadi Village, Muaraenim Regency using the purposive sampling method. Data collection techniques are used through surveys, documentation, and questionnaires using Likert scales to assess instruments. Multiple linear regression equations were utilized for the analysis of the data. The results showed that the variables of innovation, competitiveness, and business ecosystem partially or simultaneously affect the strengthening of the local economy. The independent variable affected the dependent variable by 51.2% while the remaining 48.8% was influenced by other variables not described in this study. Innovation, competitiveness, and business ecosystems play a crucial role in strengthening the local economy. These factors are interconnected and have a positive impact simultaneously and reinforce each other. By working together, innovation, competitiveness, and business ecosystems can create a strong sustainable, and inclusive local economic environment at the local level. This not only benefits local businesses but also for communities to become more resilient and able to access more opportunities. This condition supports the improvement of the welfare and quality of life of the community as a whole.
This study examines the integration of digitalization, mobile applications, and vernacular languages in Small, Medium and Micro Enterprise (SMME) management within KwaZulu-Natal Province, South Africa. A quantitative descriptive analysis was conducted using systematic probability sampling of 147 SMMEs across five sectors (agriculture, hospitality, construction, healthcare, and transportation) in the KwaZulu-Natal Midlands region. Findings reveal significant gaps between policy support and the actual implementation of digital-vernacular language integration, with 45% of respondents indicating inadequate policy support and 58.9% expressing dissatisfaction with the current progress of digitalization. Results suggest the need for targeted policy interventions to support the digital transformation of SMMEs that incorporate indigenous language capabilities. The study contributes to understanding the intersection of digital transformation and linguistic diversity in emerging economy entrepreneurship management, and the dynamic capabilities theory was undertaken as the benchmark to support the literature. The findings revealed a disconnect between the provision of support from policymakers and authorities regarding the program of action and deliverables that could help SMMEs integrate their entrepreneurial management with the demands of digitalisation, including resources and capabilities. The findings further exposed the gap between the expectations of SMMEs and the current level of digital and vernacular language integration in terms of systematic support and deliverables. Additionally, the findings characterized the slow pace of transformation supported by policymakers in digitalization, mobile applications, and the adoption of vernacular languages, which is already at an advanced stage in similar emerging economies in the global South.
This research investigates the connection between governmental assistance and business outcomes, incorporating the intermediary functions of business networking and digital marketing. Data were gathered through a questionnaire, which was distributed to 152 participants who represent MSMEs in the culinary industry in Surabaya City. The examination of this data was performed utilizing the SEM-PLS method, facilitated by SmartPLS 3.0 software. Findings from the study reveal that governmental support significantly enhances both business networking and digital marketing. Additionally, business networking and digital marketing significantly improve business performance. The research additionally illustrates that both business networking and digital marketing play a significant role in mediating the connection between government support and the success of culinary MSMEs in Surabaya City.
The COVID-19 pandemic significantly impacted Small, Medium, and Micro Enterprises (SMMEs) in South Africa, revealing their inadequate financial reserves and insufficient strategic assistance. In response, the government implemented financial and non-financial measures to promote innovation and enhance corporate resilience. This study assessed the efficacy of these approaches in aiding SMMEs during and post-pandemic, emphasising innovation uptake and sustainability results. A positivist paradigm and quantitative design were utilised, surveying 201 small, medium, and micro enterprise (SMME) owners and managers in eThekwini Municipality via structured questionnaires. Data analysis utilising SPSS (version 28.0) identified significant deficiencies in governmental assistance frameworks, especially with accessibility and communication. Participants indicated inadequate communication regarding funding initiatives, challenges in accessing newly implemented programs, and minimal influence on business recovery and innovation. The findings reveal a continual disparity between policy objectives and actual support, emphasising the necessity for enhanced communication tactics and more accessible tools to bolster SMME resilience during crises
The ever-evolving digital marketing landscape has continuously adapted to technological advancement, consumer behaviour and ecosystem trends. The 21st century marketplace needs traditional marketing practices, and digital platforms to ensure the actualisation of their growth and development in the ecosystem. The study examined how different digital marketing platforms can influence SMEs' operations and performance (Online marketing, and ICT initiatives). The study employed a quantitative design with primary data collection via a questionnaire designed based on 5-Likert’s Scale to answer the research questions; if there is a significant relationship between Online Marketing and SMEs' Business Competitiveness, and if ICT initiative has a positive relationship with SMEs' Business Growth. Two (2) hypotheses were formulated and tested using a statistical package for social sciences (SPSS). To ascertain the hypotheses formulated, both descriptive and regression analyses were carried out, and the output clearly showed a significant influence of digital marketing on the performance of SMEs. The result shows a positive impact of online marketing on SME business competitiveness. However, this study concluded that in the technology-driven environment, 21st-century SMEs will always see the usefulness and relevance of digital marketing because of its role in improving their performance. This study recommends that SMEs incorporate intensive digital platforms and engage in time-to-time updates of their online marketing channels.
The creative economy industry has created millions of jobs in Indonesia. One of the creative economy fields in Indonesia is makeup artist. But the makeup artist field also has many challenges in the increasingly fierce business competition. This research aims to investigate the influence of social media usage, innovation and competitive advantage on makeup artist business performance by considering the role competitive advantage as mediators. This research was conducted in Malang Raya with a focus on the makeup artist services business. The research method used was a survey with a questionnaire as a data collection instrument. The research sample consisted of 112 respondents who were owners of makeup artist business in Indonesia. The quantitative approach is used to describe, strengthen, and explain the hypotheses proposed in the study of observed phenomena. The statistical method used for data processing is Partial Least Squares Structural Equation Modeling (PLS-SEM). This study demonstrates a significant and positive correlation between social media usage, innovation and competitive advantage on the makeup artist business performance. The results of the mediation analysis also show that competitive advantage mediate the relationship between social media usage and innovation on makeup artist business performance. Therefore, makeup artists should optimize the use of social media to improve their business performance goals. This includes the use of the latest wardrobe, makeup trend, photo and video taking techniques, keep up to date with viral makeup content. The better the use of social media, the better the innovation, and the ability to maintain a competitive advantage by fulfills client expectations will make clients buy and recommend makeup services so as to improve the performance of makeup artists both financially and nonfinancially.
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 |