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Record W2077641906 · doi:10.12735/jbm.v3i2p01

Strategy Implementation Framework Used by SMEs in Zimbabwe

2014· article· en· W2077641906 on OpenAlexvenueno aff
Tonderai Nyamwanza

Bibliographic record

VenueJournal of Business & Management · 2014
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicEntrepreneurship Studies and Influences
Canadian institutionsnot available
Fundersnot available
KeywordsBusinessProcess managementIndustrial organizationKnowledge managementComputer science

Abstract

fetched live from OpenAlex

The field of strategic management has been expanding to embrace new concepts and models with a view to better understanding the field. One area of strategic management which is gaining currency is strategy implementation. Many a scholar and practitioner is exploring ways in which strategy implementation can be enhanced for organisations to function effectively. Several approaches have been proffered including the development of implementation models and frameworks. This study seeks to enhance strategy implementation knowledge among SMEs in Zimbabwe by developing a new framework that seeks to shed light on how the SMEs implement strategy. The development of the framework seeks to explain why, despite government policies to support economic growth, SMEs in Zimbabwe have failed to drive economic growth yet evidence from literature has indicated the significant role played by SMEs in growing economies in other countries. In depth interviews were used to gather the data from multiple case studies. The major finding of this study was that the framework used by SMEs in Zimbabwe emphasized both self and family survival. There appears to be a significant focus on inward behaviour that focuses on relationships and family anchored business survival. This could be the underlying reasons for the somewhat underperformance of SMEs in delivering strong economic growth in Zimbabwe despite a plethora of state driven assistance programmes. There is therefore need to test the applicability of this model in a longitudinal study and make adaptations to make the current framework have a more business focussed approach.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.470
Threshold uncertainty score0.674

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.017
GPT teacher head0.269
Teacher spread0.252 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations23
Published2014
Admission routes1
Has abstractyes

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