This study examines the technical efficiency(TE) differences among typical cropping systems of smallholder farmers in the purple-soiled hilly region of southwestern China.Household-,plot-,and crop-level data and commu...This study examines the technical efficiency(TE) differences among typical cropping systems of smallholder farmers in the purple-soiled hilly region of southwestern China.Household-,plot-,and crop-level data and community surveys were conducted to explore TE levels and determinants of typical cropping systems by using a translog stochastic frontier production function.Results indicate significant difference in TE and its determinants among cropping systems.The mean TEs of the rice cropping system(R),the rice-rape cropping system(RR),the rice-rape-potato cropping system(RRP),and the oil cropping system(O) are0.86,0.90,0.84,and 0.85,respectively,which are over 1.17 times higher than those of the maize-sweet potato-other crop cropping system(MSO) and the maize-sweet potato-wheat cropping system(MSW) at0.78 and 0.69,respectively.Moreover,Technical inefficiency(TIE) of different cropping systems is significantly affected by characteristics of the household as well as plot.However,the impact of land quality,mechanical cultivation conditions,crop structure,farming system,farm radius,household type,cultivated land area per capita,and annual household income per capitalon TIE vary by cropping system.Additionally,output elasticity of land,labor,and capital,as a group,is greater than the one of agricultural machinery and irrigation.Finally,when household-owned effective agricultural labor is at full farming capacity,optimal plot sizes for the R,RR,RRP,MSO,MSW,and 0 cropping systems are 1.12hm^2,0.35 hm^2,0.25 hm^2,2.82 hm^2,1.87 hm^2,and 1.17hm^2,respectively.展开更多
Evaluating the success of changes to an existing Business Intelligence(BI)environment means that there is a need to compare the level of user satisfaction with the original and amended versions of the application.The ...Evaluating the success of changes to an existing Business Intelligence(BI)environment means that there is a need to compare the level of user satisfaction with the original and amended versions of the application.The focus of this paper is on producing an evaluation tool,which can be used to measure the success of changes to existing BI solutions to support improved BI reporting.The paper identifies the users involved in the BI process and investigates what is meant by satisfaction in this context from both a user and a technical perspective.The factors to be used to measure satisfaction and appropriate clusters of measurements are identified and an evaluation tool to be used by relevant stakeholders to measure success is developed.The approach used to validate the evaluation tool is discussed and the conclusion gives suggestions for further development and extension of the tool.展开更多
基金the support of the National Natural Science Foundation of China (Grant No.41501104)the National Key Technology R&D Program of China (Grant Nos.2013BAJ11B02,2013BAJ11B02-03)+1 种基金the Basic and Frontier Research Project of Chongqing Science &Technology Commission (Grant No.cstc2015jcyj A80025)the Science and technology research project of Chongqing Education Committee (Grant No.KJ1500336)
文摘This study examines the technical efficiency(TE) differences among typical cropping systems of smallholder farmers in the purple-soiled hilly region of southwestern China.Household-,plot-,and crop-level data and community surveys were conducted to explore TE levels and determinants of typical cropping systems by using a translog stochastic frontier production function.Results indicate significant difference in TE and its determinants among cropping systems.The mean TEs of the rice cropping system(R),the rice-rape cropping system(RR),the rice-rape-potato cropping system(RRP),and the oil cropping system(O) are0.86,0.90,0.84,and 0.85,respectively,which are over 1.17 times higher than those of the maize-sweet potato-other crop cropping system(MSO) and the maize-sweet potato-wheat cropping system(MSW) at0.78 and 0.69,respectively.Moreover,Technical inefficiency(TIE) of different cropping systems is significantly affected by characteristics of the household as well as plot.However,the impact of land quality,mechanical cultivation conditions,crop structure,farming system,farm radius,household type,cultivated land area per capita,and annual household income per capitalon TIE vary by cropping system.Additionally,output elasticity of land,labor,and capital,as a group,is greater than the one of agricultural machinery and irrigation.Finally,when household-owned effective agricultural labor is at full farming capacity,optimal plot sizes for the R,RR,RRP,MSO,MSW,and 0 cropping systems are 1.12hm^2,0.35 hm^2,0.25 hm^2,2.82 hm^2,1.87 hm^2,and 1.17hm^2,respectively.
基金This paper is extension of previous work“Measuring the Success of Changes to Existing Business Intelligence Solutions to Improve Business Intelligence Reporting”presented at International Conference on Research and Practical Issues of Enterprise Information Systems 2016(CONFENIS 2016)held on 13th and 14th December 2016 in ViennaAustria,and published in Lecture Notes in Business Information Processing,Volume 268,pages 225–236.DOI:10.1007/978-3-319-49944-4_17.
文摘Evaluating the success of changes to an existing Business Intelligence(BI)environment means that there is a need to compare the level of user satisfaction with the original and amended versions of the application.The focus of this paper is on producing an evaluation tool,which can be used to measure the success of changes to existing BI solutions to support improved BI reporting.The paper identifies the users involved in the BI process and investigates what is meant by satisfaction in this context from both a user and a technical perspective.The factors to be used to measure satisfaction and appropriate clusters of measurements are identified and an evaluation tool to be used by relevant stakeholders to measure success is developed.The approach used to validate the evaluation tool is discussed and the conclusion gives suggestions for further development and extension of the tool.
