Technical, allocative and economic efficiency measures are derived for a sample of swine producers in Hawaii using the parametric stochastic efficiency decomposition technique and non parametric data envelopment analysis (DEA). Efficiency measures obtained from the two frontier approaches are compared. Firm-specific factors affecting productive efficiencies are also analyzed. Finally, swine producers' potential for reducing cost through improved efficiency is also examined. Under the specification of variable returns to scale (VRS), the mean technical, allocative and economic efficiency indices are 75.9%, 75.8% and 57.1 %, respectively, for the parametric approach and 75.9%, 80.3% and 60.3% for DEA; while for the constant returns to scale (CRS) they are 74.5%, 73.9% and 54.7%, respectively, for the parametric approach and 64.3%, 71.4% and 45.7% for DEA. Thus the results from both approaches reveal considerable inefficiencies in swine production in Hawaii. The removal of potential outliers increases the technical efficiencies in the parametric approach and allocative efficiencies in DEA, but, overall. contrary to popular belief, the results obtained from DEA are found to be more robust than those from the parametric approach. The estimated mean technical and economic efficiencies obtained from the parametric technique are higher than those from DEA for CRS models but quite similar for VRS models, while allocative efficiencies are generally higher in DEA. However, the efficiency rankings of the sample producers based on the two approaches are highly correlated, with the highest correlation being achieved for the technical efficiency rankings under CRS. Based on mean comparison and rank correlation analyses, the return to scale assumption is found to be crucial in assessing the similarities or differences in efficiency measures obtained from the two approaches. Analysis of the role of various firm-specific factors on productive efficiency shows that farm size has strong positive effects on efficiency levels. Similarly, farms producing market hogs are more efficient than those producing feeder pigs. Based on these results, by operating at the efficient frontier the sample swine producers would be able to reduce their production costs by 38--46% depending upon the method and returns to scale considered.
Social networks can profoundly affect human behavior, which is the primary force driving environmental change. However, empirical evidence linking microlevel social interactions to large-scale environmental outcomes has remained scarce. Here, we leverage comprehensive data on information-sharing networks among large-scale commercial tuna fishers to examine how social networks relate to shark bycatch, a global environmental issue. We demonstrate that the tendency for fishers to primarily share information within their ethnic group creates segregated networks that are strongly correlated with shark bycatch. However, some fishers share information across ethnic lines, and examinations of their bycatch rates show that network contacts are more strongly related to fishing behaviors than ethnicity. Our findings indicate that social networks are tied to actions that can directly impact marine ecosystems, and that biases toward within-group ties may impede the diffusion of sustainable behaviors. Importantly, our analysis suggests that enhanced communication channels across segregated fisher groups could have prevented the incidental catch of over 46,000 sharks between 2008 and 2012 in a single commercial fishery.social networks | environmental outcomes | homophily | shark bycatch | sustainability
Aquaponics, the symbiotic integration of aquaculture and hydroponics, has been touted as a sustainable food production technology. While there is anecdotal evidence, there are only a few studies on the economics of commercial aquaponics. In this study, we collect economic and production information from three aquaponic farms to investigate the economic feasibility of an aquaponics industry in Hawaii. Based on the information supplied by the farms, we develop a model case to analyze (i) profitability, (ii) return on investment, and (iii) input requirements for small-scale commercial aquaponics operation in Hawaii. We find that small-scale commercial aquaponics is economically feasible, but our findings are not as optimistic as those previously published. The modified internal rate of return of the model farm is 7.36%. We conduct sensitivity and decision reversal analysis to investigate how output prices and operational cost parameters affect the overall economic outcome. We find that economic outcome is very sensitive to output price. Investment in commercial aquaponics cannot be supported if annual sales revenue falls by 11%. We conclude by discussing challenges and risks faced by commercial aquaponic farms and the potential economic gain from organic certification and renewable energy implementation.
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