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: 5 / 5 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 07:23 UTC — 22 Oct 2026 06:43 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.
5 / 5 with data · 0 missing or unmatched. Percentages use all 5 selected publications.
5 / 5 with data · 0 missing or unmatched. Percentages use all 5 selected publications.
5 / 5 with data · 0 missing or unmatched. Percentages use all 5 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 |
|---|---|---|---|---|---|
| 2021 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 2022 | All selected publications | 2 | 2 | 2/2 | 2/2 |
| 2023 | All selected publications | 0 | 0 | 0/0 | 0/0 |
| 2024 | All selected publications | 0 | 0 | 0/0 | 0/0 |
| 2025 | All selected publications | 0 | 0 | 0/0 | 0/0 |
| 2026 | All selected publications | 2 | 2 | 2/2 | 2/2 |
| Publication year | Journal / scope | Crossref citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2021 | All selected publications | 8 | 1 | 1/1 | 1/1 |
| 2022 | All selected publications | 4 | 2 | 2/2 | 2/2 |
| 2023 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2024 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2025 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2026 | All selected publications | 0 | 2 | 2/2 | 2/2 |
| Publication year | Journal / scope | OpenAlex citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2021 | All selected publications | 11 | 1 | 1/1 | 1/1 |
| 2022 | All selected publications | 7 | 2 | 2/2 | 2/2 |
| 2023 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2024 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2025 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2026 | All selected publications | 0 | 2 | 2/2 | 2/2 |
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 5 / 5 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): 2026-10-21T07:23:07.414777+00:00 — 2026-10-22T06:43:00.647492+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 | 5 | 5/5 |
| 2018 | All selected publications | 0 | 5 | 5/5 |
| 2019 | All selected publications | 0 | 5 | 5/5 |
| 2020 | All selected publications | 0 | 5 | 5/5 |
| 2021 | All selected publications | 0 | 5 | 5/5 |
| 2022 | All selected publications | 3 | 5 | 5/5 |
| 2023 | All selected publications | 4 | 5 | 5/5 |
| 2024 | All selected publications | 4 | 5 | 5/5 |
| 2025 | All selected publications | 2 | 5 | 5/5 |
| 2026 | All selected publications | 5 | 5 | 5/5 |
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 |
|---|---|
| 2021 | 1 |
| 2022 | 2 |
| 2026 | 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 Research in Business and Social Science SSBFNET | 5 | 12 | 18 | 5/5 | 2.4 | 2 | 60.0 | 5/5 · 100.0% |
* Percentage among publications with a known citation count.
The objective of this paper was to present a dynamic resource orchestration framework as a source of organizational resilience through blended orchestration of the firm's dynamic and static resources to generate sustained value during disruptive shocks. We adopted an integrative literature review methodology and proposed a dynamic resource orchestration framework as a managerial option to create and sustain firm value. Conceptually, a dynamic resource orchestration framework was presented as the integration of firm resources and managerial capability. We proposed dynamic resource orchestration as a model input impacting organizational resilience through the combined effects of resource accumulation, resource orchestration, and managerial capabilities. Through a thorough examination of the literature production anchored on dynamic capabilities framework and organizational resilience, we advanced a perspective that the ultimate source of combined firm resilience and sustainable competitive advantage does not necessarily accrue from the resources at a firm's disposal but by how management dynamically blends and orchestrates the existing resources, thereby creating an optimal source of capability. Our proposed conceptualization was based on the assumption that dynamic capabilities are part of firm resources and, therefore, strategic orchestration of dynamic capabilities leads to superior firm resourcefulness and consequential sustained resilience. We identified gaps and proposed directions for future research.
Dynamic Capabilities View (DCV) has an illustrious history of shaping strategic management thinking. However, with the increased frequency of systemic disruption episodes, alternative postulations emerge that promise a more robust explanation for organisational sustainability. The Dynamic Resource Orchestration View (DROV) is the latest evolution in theory development, extending the Dynamic Resource-Based View (DRBV). As a framework, it elevates leadership strategy as a superordinate resource, with dynamic resource orchestration, rather than resource base, as the differentiating factor that sets resilient organisations apart in systemic disruptions. The present study utilised the lenses of DROV to mine the perspectives of 13 Kenyan ex-bankers on dynamic resource orchestration at the intersection of strategy-induced organisational resilience. The results provided empirical validation of the robustness of DROV in explaining strategy-induced organisational resilience, with dynamic resource orchestration as a source of differentiation for sustainable competitive advantage (SCA). The study has effectively contributed to strategic management scholarship by underscoring the critical role of leadership strategy, decisions and actions in the organisational resilience– SCA equation. It has also highlighted the attributes that characterise high-resilience organisations (prospering or capitalising organisations), moderate-resilience organisations (surviving organisations) and low-resilience organisations (struggling organisations). A conceptual illustration for deepening research on the novelty, dimensionality and utility of DROV is provided
Small and medium enterprises are major players in the competition and growth of economies. They have been accelerating changes towards achieving Burundi’s vision 2025. Even so, they have experienced numerous challenges which hinder their performance. Those obstacles can be improved by adopting entrepreneurial innovation as a strategy. The focus of this paper was to examine how entrepreneurial innovation affects the performance of small and medium enterprises in Bujumbura, Burundi. The resource-based view and dynamic capability theory were the main theories. This study used positivism as a research philosophy. An explanatory research design was employed on a sample size of 164 small and medium enterprises selected from the target population of 279 small and medium enterprises in Bujumbura, Burundi. The study found that process, organizational, and market innovation all had a significant effect on the performance of small and medium enterprises, while product innovation had no effect. The study recommends that small and medium business owners and managers should focus their efforts on establishing entrepreneurial innovation such as process, organizational, and market innovation to improve their performance and acquire a long-term competitive edge.
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 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 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 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.
Dynamic Capabilities View (DCV) has an illustrious history of shaping strategic management thinking. However, with the increased frequency of systemic disruption episodes, alternative postulations emerge that promise a more robust explanation for organisational sustainability. The Dynamic Resource Orchestration View (DROV) is the latest evolution in theory development, extending the Dynamic Resource-Based View (DRBV). As a framework, it elevates leadership strategy as a superordinate resource, with dynamic resource orchestration, rather than resource base, as the differentiating factor that sets resilient organisations apart in systemic disruptions. The present study utilised the lenses of DROV to mine the perspectives of 13 Kenyan ex-bankers on dynamic resource orchestration at the intersection of strategy-induced organisational resilience. The results provided empirical validation of the robustness of DROV in explaining strategy-induced organisational resilience, with dynamic resource orchestration as a source of differentiation for sustainable competitive advantage (SCA). The study has effectively contributed to strategic management scholarship by underscoring the critical role of leadership strategy, decisions and actions in the organisational resilience– SCA equation. It has also highlighted the attributes that characterise high-resilience organisations (prospering or capitalising organisations), moderate-resilience organisations (surviving organisations) and low-resilience organisations (struggling organisations). A conceptual illustration for deepening research on the novelty, dimensionality and utility of DROV is provided
Small and medium enterprises are major players in the competition and growth of economies. They have been accelerating changes towards achieving Burundi’s vision 2025. Even so, they have experienced numerous challenges which hinder their performance. Those obstacles can be improved by adopting entrepreneurial innovation as a strategy. The focus of this paper was to examine how entrepreneurial innovation affects the performance of small and medium enterprises in Bujumbura, Burundi. The resource-based view and dynamic capability theory were the main theories. This study used positivism as a research philosophy. An explanatory research design was employed on a sample size of 164 small and medium enterprises selected from the target population of 279 small and medium enterprises in Bujumbura, Burundi. The study found that process, organizational, and market innovation all had a significant effect on the performance of small and medium enterprises, while product innovation had no effect. The study recommends that small and medium business owners and managers should focus their efforts on establishing entrepreneurial innovation such as process, organizational, and market innovation to improve their performance and acquire a long-term competitive edge.
The objective of this paper was to present a dynamic resource orchestration framework as a source of organizational resilience through blended orchestration of the firm's dynamic and static resources to generate sustained value during disruptive shocks. We adopted an integrative literature review methodology and proposed a dynamic resource orchestration framework as a managerial option to create and sustain firm value. Conceptually, a dynamic resource orchestration framework was presented as the integration of firm resources and managerial capability. We proposed dynamic resource orchestration as a model input impacting organizational resilience through the combined effects of resource accumulation, resource orchestration, and managerial capabilities. Through a thorough examination of the literature production anchored on dynamic capabilities framework and organizational resilience, we advanced a perspective that the ultimate source of combined firm resilience and sustainable competitive advantage does not necessarily accrue from the resources at a firm's disposal but by how management dynamically blends and orchestrates the existing resources, thereby creating an optimal source of capability. Our proposed conceptualization was based on the assumption that dynamic capabilities are part of firm resources and, therefore, strategic orchestration of dynamic capabilities leads to superior firm resourcefulness and consequential sustained resilience. We identified gaps and proposed directions for future research.
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 |