Thesis Open Access
Benyam Ayehu
{
"DOI": "10.20372/nadre:19786",
"author": [
{
"family": "Benyam Ayehu"
}
],
"issued": {
"date-parts": [
[
2025,
10,
14
]
]
},
"abstract": "<p>The purpose of the study was to investigate the determinants of supply chain management effectiveness in medium and large manufacturing enterprises in Dire Dawa Administration. A descriptive survey research design was adopted using both quantitative and qualitative methods. The study targeted 372 respondents at a 96% response but 282 were returned fully completed, giving a response rate of 76 %. Stratified sampling technique used to select the manufacturing enterprises, Simple random sampling technique was used to select the study company while purposive sampling was used to select the Management Staff, and stratified sampling was used to select the Employees. Data analysis involved frequencies, percentages, and inferential statistics such as Binary logistic regression analysis. The Nagelkereke R2 indicates the model estimate for 44.3% of the variance in the determinants of supply chain management effectiveness in the medium and large manufacturing enterprise. The findings suggested that there was significantly associated with SCM effectiveness of medium and large manufacturing enterprises but Transportation and Logistics Management there was not significantly associated with SCM effectiveness of medium and large manufacturing enterprises. It is advisable to consider all aspects of SCM dimensions in the manufacturing enterprises, as this study investigated; each SCM construct improves different aspects of SCM practices. In general, the managers in the medium and large manufacturing enterprises should consider implementing the SCM dimensions by implementing SCOR model on their operational activities as this study has indicated there is a strong positive relationship between most of SCM dimensions & SCM effectiveness.</p>",
"title": "Determinants Of Supply Chain Management Effectiveness In Medium And Large Manufacturing Enterprises In Dire Dawa Administration",
"type": "thesis",
"id": "19786"
}
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