Entrepreneurial Orientation and Performance of Small and Medium- Sized Enterprises in Nairobi City County, Kenya
Notice bibliographique
Résumé
Kenya’s economic growth is estimated to have decelerated to 4.4 per cent in the third quarter of 2017 compared to 5.6 per cent in a similar period of 2016. During the quarter, the macroeconomic fundamentals remained largely stable and supportive of growth. However, uncertainty associated with political environment coupled with effects of adverse weather conditions slowed down the performance of the economy. As a result, most sectors of the economy posted poor performance during the quarter under review compared to the same quarter of 2016. (Kenya Economic Outlook, 2017).The Micro and Small Enterprises sector in Kenya is regarded as the driving force to spur economic growth, innovation and job creation. The general objective of the study is to investigate the effect of entrepreneurial orientation on performance of SMES in Nairobi County, Kenya. The specific objectives of the study are; to determine the effect of innovation, analyze the effect of risk taking and establish the effect of pro-activeness on performance of SMEs in Nairobi County. This study used descriptive research design. The study population is 2300 SMEs registered to operate in Nairobi County. Stratified sampling was used to obtain a sample size of 230 respondents. Data was collected using semi-structured questionnaires. Descriptive and inferential statistics was used in the analysis of data using SPSS and Ms Excel. Data was then be presented using tables, graphs and figures. Based on the findings, the study concluded that entrepreneurial orientation is useful as a Predictor of performance of SMEs. All the Entrepreneurial orientation dimensions: innovativeness, proactiveness and risk-taking had Positive significant effect on performance of SMEs. This implies that behaviors associated with innovativeness, proactiveness and risk-taking when taken as an overall strategic may indeed help SMEs in Kenya to grow. Further, the results suggests that EO-oriented activities within an organization not only results in better performance but also assist owners of SMEs to make better decision regarding the choice of strategic resources acquired. The findings of this study add to our understanding on the relationship between EO and performance of SMEs and represent an important contribution to the body of knowledge in the field of entrepreneurship. Based on the research findings and conclusion this study recommends that: SMEs need to embrace the entrepreneurial orientation dimensions, innovativeness, risk taking and proactiveness to increase business performance. Entrepreneurs need to consider risk-taking to effectively and successfully respond to the dynamic environments that require organizations to increase decision-making speed. Entrepreneurs should be innovative and develop new products ahead of their competitors. They should also be proactive by carrying out strategic environmental scans for new opportunities in the market. Finally, there is need for the Department of Micro and Small-Enterprise Development (DMSED) to consider in its blue print, facilitation of workshops and seminars for small and medium entrepreneurs to sensitize them on the significance of these dimensions in business performance. This study recommends that future researchers should carry out research on the Factors that play a mediating role in the influence of entrepreneurial orientation on performance like munificence, dynamism and hostility should be in future studies.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».