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 11:27 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 |
|---|---|---|---|---|---|
| 2024 | All selected publications | 4 | 4 | 4/4 | 4/4 |
| Publication year | Journal / scope | Crossref citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2024 | All selected publications | 5 | 4 | 4/4 | 4/4 |
| Publication year | Journal / scope | OpenAlex citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2024 | All selected publications | 7 | 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): 2026-10-21T07:22:56.390046+00:00 — 2026-10-22T11:27:20.104376+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 | 1 | 4 | 4/4 |
| 2025 | All selected publications | 4 | 4 | 4/4 |
| 2026 | All selected publications | 2 | 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 |
|---|---|
| 2024 | 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 | 5 | 7 | 4/4 | 1.25 | 1.0 | 75.0 | 4/4 · 100.0% |
* Percentage among publications with a known citation count.
This study explores the critical role of dynamic capabilities in enhancing business performance among small and medium-sized enterprises (SMEs) in the café sector of Malang City, Indonesia. Specifically, it examines how dynamic capabilities influence both explorative and exploitative innovations and how these innovations, in turn, affect business performance. Using a quantitative approach, data were collected from 110 café owners through structured questionnaires. The results indicate that dynamic capabilities significantly impact both explorative and exploitative innovations. Explorative innovation, which involves the development of new products and the exploration of new markets, was found to have a substantial positive effect on business performance. Conversely, exploitative innovation, which focuses on refining and improving existing products and processes, showed a positive but less pronounced impact. The findings underscore the importance of dynamic capabilities in fostering innovation and improving business performance in a competitive environment. This study offers practical insights for café owners and entrepreneurs in the food and beverage sector, highlighting the need for continuous development of dynamic capabilities and a balanced approach to innovation. Future research is encouraged to expand on these findings by exploring additional factors and utilizing longitudinal data to capture the evolving nature of these relationships.
This present study was conducted to advance an understanding of market orientation concept, by exploring the relationship between market orientation, competitive strategy and business performance in a sample of small- and medium-sized companies in Indonesia. A quantitative research method was adopted to investigate the relationship between the variables. A total of 200 questionnaires were distributed, from which 182 usable questionnaire were obtained (91% response rate). Correlational and regression analyses were used to examine the relationships between market orientation and the other variables measured in the study. It was found that market orientation had both direct and indirect positive influence on business performance. All three dimensions of market orientation (i.e., customer orientation, competitor orientation and inter-functional coordination) showed a simple linear relationship to the business performance, and the inter-functional coordination had the strongest association with business performance.
Today, the company is becoming more and more aware of the immense power of knowledge, the stakes of which are becoming more and more crucial. However, acquiring, developing and maintaining competitive advantage from internal resources and skills remains the overarching goal for every organization. It is for this reason that it is necessary to put in place a strategic plan for the application of knowledge. This research focuses on the efforts made by companies in terms of knowledge management processes in order to implement innovative solutions. The objective of this research is part of this perspective and aims to examine the relationship between the application of knowledge and organizational innovation by highlighting the mediating effect of innovative capabilities. To determine this relationship, a quantitative method was adopted using a total of 252 Tunisian senior managers. The results of the structural equation analysis reveal the existence of a significant influence of knowledge management on both types of technical and administrative organizational innovation.
Abstract Resources and capabilities in SMEs are only advantageous when the SMEs have the potential to execute the right strategies and processes. SMEs must analyze their business environments and understand the resources available to operate efficiently and effectively and achieve a sustained performance. This study is the subject of the influence of valuable resources on performance of SMEs. This study used a cross-sectional survey design. The target population for this study comprised of 121, 680 SMEs. The research used stratified random sampling technique. The sample size of this study was 399 SMEs. A structured questionnaire was used to collect data. Findings showed that there was a positive significant correlation between valuable resource and SMEs performance (r=.270; p<.01). According to the linear regression analysis valuable resources account for 7.3% of SMEs performance. According to the regression coefficients, one-unit increase in valuable resources improved SMEs performance by 0.269 units (? = 0.269). The t-statistics results showed that t = 4.778, p<0.05. Therefore, there was enough evidence to reject the null hypothesis and conclude that valuable resources have a statistically significant influence on SMEs Performance. The study concluded that valuable resource has a significant relationship with SMEs Performance. Valuable resources have a statistically significant influence on SMEs Performance. Increasing valuable resources in an SMEs will help the enterprise register higher performance. Key Words: Organizational Resources, Valuable Resources, Performance
This present study was conducted to advance an understanding of market orientation concept, by exploring the relationship between market orientation, competitive strategy and business performance in a sample of small- and medium-sized companies in Indonesia. A quantitative research method was adopted to investigate the relationship between the variables. A total of 200 questionnaires were distributed, from which 182 usable questionnaire were obtained (91% response rate). Correlational and regression analyses were used to examine the relationships between market orientation and the other variables measured in the study. It was found that market orientation had both direct and indirect positive influence on business performance. All three dimensions of market orientation (i.e., customer orientation, competitor orientation and inter-functional coordination) showed a simple linear relationship to the business performance, and the inter-functional coordination had the strongest association with business performance.
Abstract Resources and capabilities in SMEs are only advantageous when the SMEs have the potential to execute the right strategies and processes. SMEs must analyze their business environments and understand the resources available to operate efficiently and effectively and achieve a sustained performance. This study is the subject of the influence of valuable resources on performance of SMEs. This study used a cross-sectional survey design. The target population for this study comprised of 121, 680 SMEs. The research used stratified random sampling technique. The sample size of this study was 399 SMEs. A structured questionnaire was used to collect data. Findings showed that there was a positive significant correlation between valuable resource and SMEs performance (r=.270; p<.01). According to the linear regression analysis valuable resources account for 7.3% of SMEs performance. According to the regression coefficients, one-unit increase in valuable resources improved SMEs performance by 0.269 units (? = 0.269). The t-statistics results showed that t = 4.778, p<0.05. Therefore, there was enough evidence to reject the null hypothesis and conclude that valuable resources have a statistically significant influence on SMEs Performance. The study concluded that valuable resource has a significant relationship with SMEs Performance. Valuable resources have a statistically significant influence on SMEs Performance. Increasing valuable resources in an SMEs will help the enterprise register higher performance. Key Words: Organizational Resources, Valuable Resources, Performance
This study explores the critical role of dynamic capabilities in enhancing business performance among small and medium-sized enterprises (SMEs) in the café sector of Malang City, Indonesia. Specifically, it examines how dynamic capabilities influence both explorative and exploitative innovations and how these innovations, in turn, affect business performance. Using a quantitative approach, data were collected from 110 café owners through structured questionnaires. The results indicate that dynamic capabilities significantly impact both explorative and exploitative innovations. Explorative innovation, which involves the development of new products and the exploration of new markets, was found to have a substantial positive effect on business performance. Conversely, exploitative innovation, which focuses on refining and improving existing products and processes, showed a positive but less pronounced impact. The findings underscore the importance of dynamic capabilities in fostering innovation and improving business performance in a competitive environment. This study offers practical insights for café owners and entrepreneurs in the food and beverage sector, highlighting the need for continuous development of dynamic capabilities and a balanced approach to innovation. Future research is encouraged to expand on these findings by exploring additional factors and utilizing longitudinal data to capture the evolving nature of these relationships.
Today, the company is becoming more and more aware of the immense power of knowledge, the stakes of which are becoming more and more crucial. However, acquiring, developing and maintaining competitive advantage from internal resources and skills remains the overarching goal for every organization. It is for this reason that it is necessary to put in place a strategic plan for the application of knowledge. This research focuses on the efforts made by companies in terms of knowledge management processes in order to implement innovative solutions. The objective of this research is part of this perspective and aims to examine the relationship between the application of knowledge and organizational innovation by highlighting the mediating effect of innovative capabilities. To determine this relationship, a quantitative method was adopted using a total of 252 Tunisian senior managers. The results of the structural equation analysis reveal the existence of a significant influence of knowledge management on both types of technical and administrative organizational innovation.
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 |