Mediation by Organizational Design in the Influence of Organizational Ambidexterity on the Performance of Large Manufacturing Firms in Kenya
Bibliographic record
Abstract
The aim of this study was to establish the role of organizational design in the organizational ambidexterity - performance relationship among large manufacturing firms (LMFs) in Kenya. The studies linking ambidexterity to organizational performance are few and with mixed findings. The few studies indicate that there is no clear ambidexterity - organizational performance relationship. The research was founded on dynamic capabilities and configurations theories. Based on the reviewed literature, a conceptual model and hypotheses were formulated. The study was guided by positivist philosophy. The population of the research was the entire 107 Kenyan large manufacturing firms (LMFs). Cross-sectional research design was used. Primary data in respect of predictor variables was used and was collected using a structured questionnaire. The respondents were the senior managers of the large manufacturing firms (LMFs) in Kenya; namely Chief Executive Officers/Managing Directors (CEOs/MDs) or General Managers (GMs), or Heads of departments (HODs). Descriptive statistics, correlations, linear, multiple and hierarchical regressions were applied in the data scrutiny and interpretation. The study results showed partial organizational design mediating role in the organizational ambidexterity - performance association of LMFs in Kenya. The study findings are useful to practitioners and managers of LMFs, policymakers in government as well as scholars and researchers. The study recommends further studies on the mediating role of organizational design, different variable operationalization, diversify respondents and context as well as longitudinal study.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".