Estimating efficiency and productivity growth of the Grain Silos and Flour Mills Organisation in Saudi Arabia
The Grain Silos and Flour Mills Organisation (GSFMO) is the responsible authority monopolising the Kingdom's milling industry. However, the organisation has recently been facing financial problems. The aim of this study is to estimate the technical, cost and allocative efficiency (TE, CE and AE...
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| Format: | Thesis (University of Nottingham only) |
| Language: | English |
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2015
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| Online Access: | https://eprints.nottingham.ac.uk/29223/ |
| _version_ | 1848793741426425856 |
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| author | Alyami, Jaber |
| author_facet | Alyami, Jaber |
| author_sort | Alyami, Jaber |
| building | Nottingham Research Data Repository |
| collection | Online Access |
| description | The Grain Silos and Flour Mills Organisation (GSFMO) is the responsible authority monopolising the Kingdom's milling industry. However, the organisation has recently been facing financial problems. The aim of this study is to estimate the technical, cost and allocative efficiency (TE, CE and AE) of the flour mills of the GSFMO (1988-2011), using Data Envelopment Analysis (DEA) and Stochastic Frontier Analysis (SFA) approaches. In addition, it seeks to explain variation in efficiency levels between the mills and conduct further analysis through the second stage regression to estimate the effect of managerial variables. Productivity growth over time was also estimated in this study using DEA (2008-2011) and SFA (1988-2011) approaches. Both primary data and secondary data (1988-2011) to cover the nine milling branches were utilised.
Using DEA under constant return to scale (CRS), average TE ranged from 91.72% in Khamis branch to 97.63% in Almadinah. Average TE under input-orientated variable return to scale (VRS) was lower than TE estimated under output-orientated VRS. The older branches had the lowest TE compared to newer branches. Under VRS, TE was greater than TE for the same branches under CRS. TE results using SFA were quite analogous to the results using DEA. Regarding productivity growth, using DEA for the 2008-2011 data, no consistent patterns were found across the GSFMO branches in the mean total factor productivity growth (TFPG), technical change (TC), and efficiency change (EC). When using SFA to estimate productivity growth over the period 1988 to 2011, there was a decrease in productivity growth for most branches.
With regards to the results of the second stage regression, branch managers’ age, local temperature and 'bad' infrastructure have a significant negative relationship with TE, while manager's experience did not seem to have any significant relationship with TE. However, new and mix machine conditions and number of mills in each branch have a significant positive relationship with TE. In terms of CE and AE using the DEA approach, the results show that major losses incurred by the organisation were partly due to the significant decrease in CE and AE and that there is a significant scope to reduce inputs costs in the production process. |
| first_indexed | 2025-11-14T19:05:07Z |
| format | Thesis (University of Nottingham only) |
| id | nottingham-29223 |
| institution | University of Nottingham Malaysia Campus |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-14T19:05:07Z |
| publishDate | 2015 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | nottingham-292232025-02-28T11:35:44Z https://eprints.nottingham.ac.uk/29223/ Estimating efficiency and productivity growth of the Grain Silos and Flour Mills Organisation in Saudi Arabia Alyami, Jaber The Grain Silos and Flour Mills Organisation (GSFMO) is the responsible authority monopolising the Kingdom's milling industry. However, the organisation has recently been facing financial problems. The aim of this study is to estimate the technical, cost and allocative efficiency (TE, CE and AE) of the flour mills of the GSFMO (1988-2011), using Data Envelopment Analysis (DEA) and Stochastic Frontier Analysis (SFA) approaches. In addition, it seeks to explain variation in efficiency levels between the mills and conduct further analysis through the second stage regression to estimate the effect of managerial variables. Productivity growth over time was also estimated in this study using DEA (2008-2011) and SFA (1988-2011) approaches. Both primary data and secondary data (1988-2011) to cover the nine milling branches were utilised. Using DEA under constant return to scale (CRS), average TE ranged from 91.72% in Khamis branch to 97.63% in Almadinah. Average TE under input-orientated variable return to scale (VRS) was lower than TE estimated under output-orientated VRS. The older branches had the lowest TE compared to newer branches. Under VRS, TE was greater than TE for the same branches under CRS. TE results using SFA were quite analogous to the results using DEA. Regarding productivity growth, using DEA for the 2008-2011 data, no consistent patterns were found across the GSFMO branches in the mean total factor productivity growth (TFPG), technical change (TC), and efficiency change (EC). When using SFA to estimate productivity growth over the period 1988 to 2011, there was a decrease in productivity growth for most branches. With regards to the results of the second stage regression, branch managers’ age, local temperature and 'bad' infrastructure have a significant negative relationship with TE, while manager's experience did not seem to have any significant relationship with TE. However, new and mix machine conditions and number of mills in each branch have a significant positive relationship with TE. In terms of CE and AE using the DEA approach, the results show that major losses incurred by the organisation were partly due to the significant decrease in CE and AE and that there is a significant scope to reduce inputs costs in the production process. 2015-07-14 Thesis (University of Nottingham only) NonPeerReviewed application/pdf en arr https://eprints.nottingham.ac.uk/29223/1/Final%20thesis%2025-6-2015%20Jaber%20Alyami.pdf Alyami, Jaber (2015) Estimating efficiency and productivity growth of the Grain Silos and Flour Mills Organisation in Saudi Arabia. PhD thesis, University of Nottingham. The Grain Silos and Flour Mills Organisation; Data Envelopment Analysis; Stochostic Frontier Analysis; Total Faxtor Productivity Growth; Technical Efficiency. |
| spellingShingle | The Grain Silos and Flour Mills Organisation; Data Envelopment Analysis; Stochostic Frontier Analysis; Total Faxtor Productivity Growth; Technical Efficiency. Alyami, Jaber Estimating efficiency and productivity growth of the Grain Silos and Flour Mills Organisation in Saudi Arabia |
| title | Estimating efficiency and productivity growth of the Grain Silos and Flour Mills Organisation in Saudi Arabia |
| title_full | Estimating efficiency and productivity growth of the Grain Silos and Flour Mills Organisation in Saudi Arabia |
| title_fullStr | Estimating efficiency and productivity growth of the Grain Silos and Flour Mills Organisation in Saudi Arabia |
| title_full_unstemmed | Estimating efficiency and productivity growth of the Grain Silos and Flour Mills Organisation in Saudi Arabia |
| title_short | Estimating efficiency and productivity growth of the Grain Silos and Flour Mills Organisation in Saudi Arabia |
| title_sort | estimating efficiency and productivity growth of the grain silos and flour mills organisation in saudi arabia |
| topic | The Grain Silos and Flour Mills Organisation; Data Envelopment Analysis; Stochostic Frontier Analysis; Total Faxtor Productivity Growth; Technical Efficiency. |
| url | https://eprints.nottingham.ac.uk/29223/ |