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Study On Training Mechanism Of Agricultural Technology Talent In Agriculture Modernization Process

Posted on:2012-04-01Degree:DoctorType:Dissertation
Country:ChinaCandidate:X B LiuFull Text:PDF
GTID:1229330377453239Subject:Agricultural Economics and Management
Abstract/Summary:PDF Full Text Request
The21stcentury is a knowledge-based economy era. In this era, various new kinds ofagriculture have been developed, such as facility agriculture, ecological agriculture,physical agriculture, aerospace agriculture, modern agri-food engineering andmolecular agriculture, all of these new types of agriculture not only provide morefeasible paths for agriculture modernization, but also mean the challenge to the qualityand quantity of agricultural technology talent. The agricultural and rural talent workconference held in2010clearly stated that: to develop modern agriculture actively,adjust and optimize the industrial structure of agriculture, push forward theconstruction of new countryside, it should take the technology talent seriously. Inaddition, the “National long-term talent development program (2010-2020)” alsostated the focus of future talent construction which including educating innovativetalents, special talents and rural utility talents. All kinds of these talents are crucial forChina’s economy.Under the guidance of official technology talent policies, the author read lots ofliterature and summarized the previous research on technology talent. The paper useseconomics and management scientific theories to analyze related problems. Also, itapplies quantitative analysis,qualitative analysis, logical analysis with historicalanalysis, comparative analysis as the method. The focus of this paper is the trainingmechanism of agricultural technology talent. This paper discusses the trainingmechanism in different phases in agriculture modernization in China. On the basis ofthe above discussion, it uses Regressive Model and the array model of time to predictthe demand and supply of agricultural technology talent, after that it uses SWOTmethod to analyze the strengths, weaknesses, opportunities and threats what thetechnology talent training mechanism now faces. In the last four chapters the papersums up the training experience in America, Japan, Israel and India, and gives thesuggestion in promoting the agricultural technology talent training mechanism in theprocess of agriculture modernization.The innovation of this paper can be summed up as the following:Firstly, the research topic is innovative. Viewing from the domestic andinternational literature, there has little which has discussed the training mechanism inthe process of agriculture modernization. In addition, new suggestion is proposed inthis paper which will play an important part in promoting the agriculturemodernization.Secondly, the data prediction is innovative. Since lack of the statistical datarelated to the agriculture, the paper presents using relevant data to calculate theapproximate data and thus the demand and supply of agricultural technology talent ispredicted. Thirdly, the combination of subject is innovative. The paper takes the humancapital theories into the research of industrial economics, and reveals the realisticsuggestion to promote the training mechanism of technology talent. The optimizedtraining mechanism belongs to the area of productive relationship, while theagriculture modernization belongs to the area of productive force, under the guidanceof the principle that productive forces determines the productive relationship whereasthe productive relationship affects the productive force, it is essential to build theadvanced technology talent training mechanism to fit the agriculture modernization,only by this can agricultural economy be promoted further.Fourthly, it is significant to use SWOT method to analyze the environment whichthe training mechanism now faces, as it helps to determine the further direction andstrategy in training mechanism development.
Keywords/Search Tags:Agriculture Modernization, Agricultural Technology Talent, TrainingMechanism
PDF Full Text Request
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