SMEs’ strategic orientation through Miles and Snow typology: a synthesis of literature and future directions
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Purpose The purpose of this research is to present a systematic analysis of consequents and antecedents of strategy and performance. To acheive this, this systematic review article analyzes and synthesizes mainstream research on small and medium-sized enterprises (SMEs) where Miles and Snow typology was used for strategic orientation of the SMEs. The specific focus of the research is to develop a conceptual framework showing consequents and antecedents of the strategic orientation. Design/methodology/approach This study uses systematic literature review (SLR) method to identify, summarize and synthesize literature on Miles and Snow typology. Preferred reporting method for systematic reviews and meta-analyses to ensure adherence to systematic approach. The key words search consists of the words: “Miles and Snow”, “Miles and Snow” and “miles-snow” from Web of Science and Scopus databases for sample articles. Findings The trend of research on SMEs using Miles and Snow typology is on the rise with a shift from developed countries to the developing ones. Support for strategy-performance relationship hypotheses is overwhelming but the traditional view is in decline while new antecedent and consequent variables are being added. Mediator and moderating variables are also identified. Originality/value The SLR where a synthesis approach was applied for finding antecedents and consequent variables of strategy-performance relationship along with a presentation of conceptual framework makes this research unique. Additionally, the article presents the trends of research over the time based on timeframe, regions, methodological approaches and hypotheses support.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it