The Extent, Dynamics, and Potential Predictors of Technical Efficiency and Capacity Utilisation in Small-Scale Fisheries in Oman

This paper investigates the extent, dynamics, and factors influencing technical efficiency (TE) and capacity utilisation (CU) in small-scale fisheries (SSF) using a two-stage data envelopment analysis (DEA) approach covering the period 2010–2012. A considerable extent of boat-level technical ineffic...

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Main Authors: MOHAMMED AL-SIYABI, SHEKAR BOSE, HUSSEIN AL-MASROORI
Format: Article
Language:English
Published: Asian Fisheries Society 2021-03-01
Series:Asian Fisheries Science
Online Access:https://www.asianfisheriessociety.org/publication/downloadfile.php?id=1351&file=Y0dSbUx6QXpPRGczTURNd01ERTJNVGN4TkRZek5UVXVjR1Jt
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author MOHAMMED AL-SIYABI
SHEKAR BOSE
HUSSEIN AL-MASROORI
author_facet MOHAMMED AL-SIYABI
SHEKAR BOSE
HUSSEIN AL-MASROORI
author_sort MOHAMMED AL-SIYABI
collection DOAJ
description This paper investigates the extent, dynamics, and factors influencing technical efficiency (TE) and capacity utilisation (CU) in small-scale fisheries (SSF) using a two-stage data envelopment analysis (DEA) approach covering the period 2010–2012. A considerable extent of boat-level technical inefficiency, capacity underutilisation and scale inefficiency were evident. On average, TE and CU levels under the constant returns to scale (CRS) and variable returns to scale (VRS) models declined over time. The TE and CU scores of 2010 remained unaltered with the addition of ‘fishing time’ as an input to the model. The proportion of boats with unitary scale efficiency (SE) decreased from 26 % in 2010 to 12 % in 2012. The underutilisation rates of the inputs ‘crew’ and ‘fishing time’ ranged from 15.5 % to 31.6 % and 15.8 % to 28.6 %, respectively. Among the species category, the extent of excess capacity was 70 % to 156 % and 47 % to 119 % under the CRS and VRS models, respectively. The second-stage DEA results indicated that the explanatory variables ‘fishing location’, ‘catch per unit of effort’ (CPUE), ‘fuel costs’ and ‘crew share’ significantly influenced CU under the CRS model. In contrast, the significant influence of subsidies and other operating costs were noted under the VRS model. For the TE case, ‘age’, ‘education’, ‘subsidy’ and ‘CPUE’ were found to be significant under the CRS and VRS models. Other significant variables were found in the study under CRS and VRS models. Finally, the results from the descriptive and empirical analysis under the two-stage DEA model are discussed together with policy implications.
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spelling doaj.art-7165b55849194bea9b3f5b9acd7584912022-12-21T21:05:20ZengAsian Fisheries SocietyAsian Fisheries Science0116-65142073-37202021-03-0134110.33997/j.afs.2021.34.1.007The Extent, Dynamics, and Potential Predictors of Technical Efficiency and Capacity Utilisation in Small-Scale Fisheries in OmanMOHAMMED AL-SIYABISHEKAR BOSEHUSSEIN AL-MASROORIThis paper investigates the extent, dynamics, and factors influencing technical efficiency (TE) and capacity utilisation (CU) in small-scale fisheries (SSF) using a two-stage data envelopment analysis (DEA) approach covering the period 2010–2012. A considerable extent of boat-level technical inefficiency, capacity underutilisation and scale inefficiency were evident. On average, TE and CU levels under the constant returns to scale (CRS) and variable returns to scale (VRS) models declined over time. The TE and CU scores of 2010 remained unaltered with the addition of ‘fishing time’ as an input to the model. The proportion of boats with unitary scale efficiency (SE) decreased from 26 % in 2010 to 12 % in 2012. The underutilisation rates of the inputs ‘crew’ and ‘fishing time’ ranged from 15.5 % to 31.6 % and 15.8 % to 28.6 %, respectively. Among the species category, the extent of excess capacity was 70 % to 156 % and 47 % to 119 % under the CRS and VRS models, respectively. The second-stage DEA results indicated that the explanatory variables ‘fishing location’, ‘catch per unit of effort’ (CPUE), ‘fuel costs’ and ‘crew share’ significantly influenced CU under the CRS model. In contrast, the significant influence of subsidies and other operating costs were noted under the VRS model. For the TE case, ‘age’, ‘education’, ‘subsidy’ and ‘CPUE’ were found to be significant under the CRS and VRS models. Other significant variables were found in the study under CRS and VRS models. Finally, the results from the descriptive and empirical analysis under the two-stage DEA model are discussed together with policy implications.https://www.asianfisheriessociety.org/publication/downloadfile.php?id=1351&file=Y0dSbUx6QXpPRGczTURNd01ERTJNVGN4TkRZek5UVXVjR1Jt
spellingShingle MOHAMMED AL-SIYABI
SHEKAR BOSE
HUSSEIN AL-MASROORI
The Extent, Dynamics, and Potential Predictors of Technical Efficiency and Capacity Utilisation in Small-Scale Fisheries in Oman
Asian Fisheries Science
title The Extent, Dynamics, and Potential Predictors of Technical Efficiency and Capacity Utilisation in Small-Scale Fisheries in Oman
title_full The Extent, Dynamics, and Potential Predictors of Technical Efficiency and Capacity Utilisation in Small-Scale Fisheries in Oman
title_fullStr The Extent, Dynamics, and Potential Predictors of Technical Efficiency and Capacity Utilisation in Small-Scale Fisheries in Oman
title_full_unstemmed The Extent, Dynamics, and Potential Predictors of Technical Efficiency and Capacity Utilisation in Small-Scale Fisheries in Oman
title_short The Extent, Dynamics, and Potential Predictors of Technical Efficiency and Capacity Utilisation in Small-Scale Fisheries in Oman
title_sort extent dynamics and potential predictors of technical efficiency and capacity utilisation in small scale fisheries in oman
url https://www.asianfisheriessociety.org/publication/downloadfile.php?id=1351&file=Y0dSbUx6QXpPRGczTURNd01ERTJNVGN4TkRZek5UVXVjR1Jt
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