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: 8 / 8 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 — 23 Oct 2026 12:04 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.
8 / 8 with data · 0 missing or unmatched. Percentages use all 8 selected publications.
8 / 8 with data · 0 missing or unmatched. Percentages use all 8 selected publications.
8 / 8 with data · 0 missing or unmatched. Percentages use all 8 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 |
|---|---|---|---|---|---|
| 2022 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 2023 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 2024 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 2025 | All selected publications | 2 | 2 | 2/2 | 2/2 |
| 2026 | All selected publications | 3 | 3 | 3/3 | 3/3 |
| Publication year | Journal / scope | Crossref citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2022 | All selected publications | 0 | 1 | 1/1 | 1/1 |
| 2023 | All selected publications | 0 | 1 | 1/1 | 1/1 |
| 2024 | All selected publications | 0 | 1 | 1/1 | 1/1 |
| 2025 | All selected publications | 0 | 2 | 2/2 | 2/2 |
| 2026 | All selected publications | 0 | 3 | 3/3 | 3/3 |
| Publication year | Journal / scope | OpenAlex citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2022 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 2023 | All selected publications | 0 | 1 | 1/1 | 1/1 |
| 2024 | All selected publications | 0 | 1 | 1/1 | 1/1 |
| 2025 | All selected publications | 0 | 2 | 2/2 | 2/2 |
| 2026 | All selected publications | 0 | 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 8 / 8 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): 2026-10-21T07:22:51.962933+00:00 — 2026-10-23T12:04:33.657164+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 | 8 | 8/8 |
| 2018 | All selected publications | 0 | 8 | 8/8 |
| 2019 | All selected publications | 0 | 8 | 8/8 |
| 2020 | All selected publications | 0 | 8 | 8/8 |
| 2021 | All selected publications | 0 | 8 | 8/8 |
| 2022 | All selected publications | 0 | 8 | 8/8 |
| 2023 | All selected publications | 0 | 8 | 8/8 |
| 2024 | All selected publications | 0 | 8 | 8/8 |
| 2025 | All selected publications | 1 | 8 | 8/8 |
| 2026 | All selected publications | 0 | 8 | 8/8 |
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 |
|---|---|
| 2022 | 1 |
| 2023 | 1 |
| 2024 | 1 |
| 2025 | 2 |
| 2026 | 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 | 0 | 0 | 1/1 | 0.0 | 0 | 0.0 | 1/1 · 100.0% |
| International Journal of Research in Business and Social Science SSBFNET | 7 | 0 | 1 | 7/7 | 0.0 | 0 | 0.0 | 7/7 · 100.0% |
* Percentage among publications with a known citation count.
This paper examines the Resource-Based View (RBV) and the Theory of Firm Heterogeneity to clarify their theoretical boundaries and enhance their explanatory power. It addresses key limitations of RBV, including endogeneity, tautological reasoning, and limited attention to contextual influences, and examines how digital technologies and artificial intelligence (AI) reshape strategic resources and firm heterogeneity. The study employs a systematic review of the strategic management literature. It synthesises the core assumptions of RBV with insights from firm heterogeneity, evolutionary theory, and capability-based perspectives to assess how internal resources, contextual factors, and technological capabilities shape competitive advantage. The review indicates that RBV and the Theory of Firm Heterogeneity provide complementary explanations of persistent performance differences among firms. Competitive advantage depends not only on heterogeneous resources but also on firms' ability to adapt, integrate, and deploy these resources in response to changing environmental and institutional conditions. Digital transformation and AI further amplify firm heterogeneity by creating differences in technological capabilities and innovation capacity. The paper advances the strategic management literature by integrating RBV with the Theory of Firm Heterogeneity, offering a more comprehensive explanation of sustained competitive advantage. It demonstrates how digital technologies and AI reshape strategic resources and identifies future research opportunities in contextual influences, capability development, and technology-driven competitive advantage.
The research aims to explore the impact of digital platform integration and reconstruction capabilities on organizational agility (mediator) and ESG performance of small and medium size enterprises of Pakistan. The study also examines the moderating role of technology uncertainty between digital platform capabilities and organizational agility that further leads to ESG performance. Data is collected from 300 firms while industries include; IT, Manufacturing, Textiles, Electronics, and Automobile in eight big cities of Pakistan and the respondents are middle and senior managers. Data was analyzed using the software; SPSS (reliability analysis) and R Studio (version 4.5.2), Structural Equation modeling (SEM) and regression Analysis. The study used Resource-Based View and Dynamic Capability Theory to see the role of digital platform capabilities, organization agility and uncertain technology conditions’ on ESG. The findings of this research are that such organizations with agility perform better on the ESG dimensions. First, this study takes a capability perspective to explore the impact of digital platform integration and reconstruction capability on Organizational agility, which extends the related studies taking digital perspective. Second, the inner mechanism between organizational agility and firm ESG performance is revealed where organizational agility works as a bridge for ESG performance. Third, the relationship between digital platform capabilities and organizational agility is exposed by the moderation of technology uncertainty. Where technology uncertainty positively moderates the relationship between digital platform capabilities and organizational agility.
The study focused on assessing how the level of adoption of four Absorptive Capacity(AC) dimensions as a driver of strategic technological change has contributed to sustainable performance of firms operating in the insurance sector in Kenya. The conceptualization of the study was informed by the postulates of three theoretical frameworks; the Model of Absorptive capacity, Resource Based View( RBV) and Knowledge Based view (KBV) with four hypotheses testing the effect of each of the four dimensions of AC on sustainable performance of the insurance firms. A descriptive survey design was adopted to obtain data from a target sample of 224 respondents representing heads of units actively involved in roles associated with AC in 56 Insurance firms. The study registered a response rate of 83% with the respondents demonstrating demographic characteristics indicating adequate industry work experience and education levels. The dimensions of Absorptive Capacity aligning to strategy implementation and strategic choice were adopted to a higher extent compared to those aligning to strategic thinking aspects touching on strategy formulation. Though all the four dimensions had a significant positive effect on sustainable performance, those aligning towards strategic choice and implementation had a higher effect on sustainable performance than those aligning towards strategic thinking. The study concluded that the four dimensions of AC are suitable drivers of strategic technological change in the manner in which their attributes speak to the three strategic management processes of strategic planning(formulation), choice and implementation. The study calls on future research to extend the implications of the findings reported by providing more plausible explanations to the dilemmas revolving around the low adoption of the AC dimensions aligning towards strategic thinking and its subsequent effect on sustainable performance using objective data on the dimensions of AC.
This study investigates the impact of knowledge management on innovation in Tunisia's banking sector through a survey of salaried executives. The results indicate a strong positive relationship, emphasizing that key components—knowledge acquisition, application, and sharing—drive both administrative and technical innovation. Effective knowledge management allows organizations to adapt to market trends and enhance business processes. Knowledge sharing fosters an innovative environment for idea creation. Therefore, organizations, especially banks aiming to boost innovation, should prioritize sustainable knowledge management to gain a competitive edge and become more agile in a fluctuating economy.
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 paper examines the Resource-Based View (RBV) and the Theory of Firm Heterogeneity to clarify their theoretical boundaries and enhance their explanatory power. It addresses key limitations of RBV, including endogeneity, tautological reasoning, and limited attention to contextual influences, and examines how digital technologies and artificial intelligence (AI) reshape strategic resources and firm heterogeneity. The study employs a systematic review of the strategic management literature. It synthesises the core assumptions of RBV with insights from firm heterogeneity, evolutionary theory, and capability-based perspectives to assess how internal resources, contextual factors, and technological capabilities shape competitive advantage. The review indicates that RBV and the Theory of Firm Heterogeneity provide complementary explanations of persistent performance differences among firms. Competitive advantage depends not only on heterogeneous resources but also on firms' ability to adapt, integrate, and deploy these resources in response to changing environmental and institutional conditions. Digital transformation and AI further amplify firm heterogeneity by creating differences in technological capabilities and innovation capacity. The paper advances the strategic management literature by integrating RBV with the Theory of Firm Heterogeneity, offering a more comprehensive explanation of sustained competitive advantage. It demonstrates how digital technologies and AI reshape strategic resources and identifies future research opportunities in contextual influences, capability development, and technology-driven competitive advantage.
The research aims to explore the impact of digital platform integration and reconstruction capabilities on organizational agility (mediator) and ESG performance of small and medium size enterprises of Pakistan. The study also examines the moderating role of technology uncertainty between digital platform capabilities and organizational agility that further leads to ESG performance. Data is collected from 300 firms while industries include; IT, Manufacturing, Textiles, Electronics, and Automobile in eight big cities of Pakistan and the respondents are middle and senior managers. Data was analyzed using the software; SPSS (reliability analysis) and R Studio (version 4.5.2), Structural Equation modeling (SEM) and regression Analysis. The study used Resource-Based View and Dynamic Capability Theory to see the role of digital platform capabilities, organization agility and uncertain technology conditions’ on ESG. The findings of this research are that such organizations with agility perform better on the ESG dimensions. First, this study takes a capability perspective to explore the impact of digital platform integration and reconstruction capability on Organizational agility, which extends the related studies taking digital perspective. Second, the inner mechanism between organizational agility and firm ESG performance is revealed where organizational agility works as a bridge for ESG performance. Third, the relationship between digital platform capabilities and organizational agility is exposed by the moderation of technology uncertainty. Where technology uncertainty positively moderates the relationship between digital platform capabilities and organizational agility.
The study focused on assessing how the level of adoption of four Absorptive Capacity(AC) dimensions as a driver of strategic technological change has contributed to sustainable performance of firms operating in the insurance sector in Kenya. The conceptualization of the study was informed by the postulates of three theoretical frameworks; the Model of Absorptive capacity, Resource Based View( RBV) and Knowledge Based view (KBV) with four hypotheses testing the effect of each of the four dimensions of AC on sustainable performance of the insurance firms. A descriptive survey design was adopted to obtain data from a target sample of 224 respondents representing heads of units actively involved in roles associated with AC in 56 Insurance firms. The study registered a response rate of 83% with the respondents demonstrating demographic characteristics indicating adequate industry work experience and education levels. The dimensions of Absorptive Capacity aligning to strategy implementation and strategic choice were adopted to a higher extent compared to those aligning to strategic thinking aspects touching on strategy formulation. Though all the four dimensions had a significant positive effect on sustainable performance, those aligning towards strategic choice and implementation had a higher effect on sustainable performance than those aligning towards strategic thinking. The study concluded that the four dimensions of AC are suitable drivers of strategic technological change in the manner in which their attributes speak to the three strategic management processes of strategic planning(formulation), choice and implementation. The study calls on future research to extend the implications of the findings reported by providing more plausible explanations to the dilemmas revolving around the low adoption of the AC dimensions aligning towards strategic thinking and its subsequent effect on sustainable performance using objective data on the dimensions of AC.
This study investigates the impact of knowledge management on innovation in Tunisia's banking sector through a survey of salaried executives. The results indicate a strong positive relationship, emphasizing that key components—knowledge acquisition, application, and sharing—drive both administrative and technical innovation. Effective knowledge management allows organizations to adapt to market trends and enhance business processes. Knowledge sharing fosters an innovative environment for idea creation. Therefore, organizations, especially banks aiming to boost innovation, should prioritize sustainable knowledge management to gain a competitive edge and become more agile in a fluctuating economy.
This research analyses how a service firm develops an ecosystem and serves as the orchestrator. A unique coffee shop in a mountainous area was used as the subject because it has abundant resources to become an orchestrator and various distinctive traits. A single case study design was selected to enable researchers to analyse depth and rich data, covering all participants within the ecosystem. Using a holistic case study design enables investigators to explore complex interplays of ecosystem participants. This study demonstrates that a firm uses elements of dynamic capabilities to manage the evolving process of ecosystem dynamics, starting from the initial formation of the ecosystem to the maturity stage. Our analysis identifies what derivative capabilities can be created from each element of dynamic capabilities and how these derivative capabilities are employed for developing and managing partners involved in the ecosystem. This study establishes a contribution by examining a coffee shop, representing a small service firm, and its evolution into an ecosystem orchestrator role - an under-explored setting in prevailing orchestration literature concentrated on large platform corporations. Single case studies are often criticized because their generalizability is thin and their findings are narrow. However, this weakness has led to the advantage of presenting insights in detail and depth.
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 |