中國服務(wù)型制造業(yè)全要素生產(chǎn)率評價與影響因素研究
本文選題:服務(wù)型制造 + 全要素生產(chǎn)率; 參考:《山東科技大學》2017年碩士論文
【摘要】:伴隨著以顧客為核心、注重服務(wù)質(zhì)量的互聯(lián)網(wǎng)經(jīng)濟和技術(shù)經(jīng)濟時代的到來,個性化和定制化的客戶需求不斷涌現(xiàn),服務(wù)型制造作為一種全新的生產(chǎn)模式引起了理論研究者和政策制定者的廣泛關(guān)注。服務(wù)型制造通過客戶全程參與,制造價值鏈中的企業(yè)相互提供生產(chǎn)性服務(wù)和服務(wù)性生產(chǎn),打破了制造業(yè)與服務(wù)業(yè)的界限,實現(xiàn)了分散化制造資源的整合和產(chǎn)品與服務(wù)的有效融合。立足我國實際,關(guān)注服務(wù)型制造業(yè)全要素生產(chǎn)率的具體狀況,探討不同細分行業(yè)、時期和地區(qū)間的變動趨勢并給出影響因素,對制定有關(guān)制造業(yè)發(fā)展戰(zhàn)略規(guī)劃和實施方案具有重要的意義。本文基于服務(wù)型制造理論、全要素生產(chǎn)率理論,運用我國服務(wù)型制造業(yè)分行業(yè)和地區(qū)的面板數(shù)據(jù),測算了服務(wù)型制造業(yè)的全要素生產(chǎn)率,對其異質(zhì)性、收斂性和影響因素進行了實證研究,并據(jù)此給出了推進服務(wù)型制造業(yè)科學發(fā)展,實現(xiàn)“中國制造”向“中國創(chuàng)造”轉(zhuǎn)型升級的對策建議。首先,基于面板數(shù)據(jù)對服務(wù)型制造業(yè)全要素生產(chǎn)率的異質(zhì)性進行了實證研究。通過構(gòu)建非參數(shù)Malmquist指數(shù),從時期、產(chǎn)業(yè)和地區(qū)三個方面測度了全要素生產(chǎn)率的時空差異,并對其變動趨勢和變動原因進行分析。研究發(fā)現(xiàn):2006-2014年間,我國服務(wù)型制造業(yè)總體TFP年均提升0.9%,主要源于技術(shù)進步率的提升,且總體波動比較明顯。各細分產(chǎn)業(yè)TFP指數(shù)的總體變動趨勢類似,交通運輸設(shè)備制造業(yè)增長最快。除北京和河北因產(chǎn)業(yè)調(diào)整較大,服務(wù)型制造業(yè)全要素生產(chǎn)率為下降以外,其他各省市均呈正向增長,尤以遼寧省的增長最顯著;中、西部地區(qū)的TFP增長要強于東部地區(qū),并主要體現(xiàn)在技術(shù)進步率的變動上,中西部地區(qū)的技術(shù)追趕效果較為明顯,地區(qū)差異逐漸縮小。其次,運用σ趨同和β趨同檢驗,從時期、產(chǎn)業(yè)和地區(qū)三個角度對服務(wù)型制造業(yè)TFP的變化趨勢進行趨同性檢驗發(fā)現(xiàn),2006-2014年間我國服務(wù)型制造業(yè)的TFP指數(shù)、技術(shù)效率指數(shù)呈絕對β收斂趨勢,但技術(shù)進步指數(shù)具有絕對β發(fā)散性;細分產(chǎn)業(yè)間的絕對β收斂性明顯;服務(wù)型制造業(yè)在區(qū)域上具有明顯的俱樂部趨同性,東、中、西部地區(qū)內(nèi)部的絕對β收斂速度均明顯高于總體水平細分產(chǎn)業(yè)存在絕對β趨同,同時形成了東、中、西部三大趨同俱樂部。再次,利用SPSS軟件和Eviews軟件,建立動態(tài)面板數(shù)據(jù)回歸模型,分析了影響服務(wù)型制造業(yè)全要素生產(chǎn)率提高的因素,發(fā)現(xiàn)人力資本水平、研發(fā)投入、政府支持、市場化程度、對外開放度等是形成服務(wù)型制造業(yè)全要素生產(chǎn)率行業(yè)差異的主要原因,但各因素的影響力度并不相同。最后,基于本研究的結(jié)論,從政府政策、行業(yè)和企業(yè)發(fā)展三個方面進行了分析,提出了推動服務(wù)型制造業(yè)專業(yè)化、精細化、服務(wù)化發(fā)展的對策建議。
[Abstract]:With the arrival of the era of Internet economy and technological economy, which takes the customer as the core and pays attention to the service quality, the individualized and customized customer needs emerge constantly. As a new mode of production, service-oriented manufacturing has attracted the attention of theoretical researchers and policy makers. Service-oriented manufacturing breaks the boundary between manufacturing and service industries by participating in the whole process, and enterprises in the manufacturing value chain provide each other with productive services and service-oriented production. The integration of decentralized manufacturing resources and the effective integration of products and services are realized. Based on the reality of our country, this paper focuses on the specific situation of total factor productivity of service manufacturing industry, discusses the changing trend of different subdivision industries, periods and regions, and gives the influencing factors. It is of great significance to formulate the strategic planning and implementation plan of manufacturing industry. Based on the service manufacturing theory and the total factor productivity theory, this paper calculates the total factor productivity of the service manufacturing industry by using the panel data of the service manufacturing industry in different industries and regions, and analyzes the heterogeneity of the total factor productivity of the service manufacturing industry. Based on the empirical study of convergence and influencing factors, the countermeasures and suggestions to promote the scientific development of service-oriented manufacturing industry and to realize the transformation and upgrading from "made in China" to "created in China" are put forward. Firstly, based on panel data, the heterogeneity of total factor productivity (TFP) in service manufacturing industry is studied empirically. By constructing the nonparametric Malmquist index, this paper measures the temporal and spatial differences of total factor productivity from three aspects: period, industry and region, and analyzes its changing trend and reasons. It is found that the average annual TFP increase of service manufacturing industry in China from 2006 to 2014 is 0.9%, which is mainly due to the improvement of technological progress rate, and the overall fluctuation is obvious. The overall change trend of the TFP index of each subdivision industry is similar, the transportation equipment manufacturing industry grows fastest. With the exception of Beijing and Hebei, where the total factor productivity of the service-oriented manufacturing industry is declining due to industrial adjustment, all other provinces and cities have a positive growth trend, especially in Liaoning Province. In the west, the growth of TFP is stronger than that in the eastern region. And mainly reflected in the change of technological progress rate, the technology catch-up effect in the central and western regions is obvious, and the regional differences are gradually narrowing. Secondly, by using 蟽 -convergence and 尾 -convergence test, this paper analyzes the trend of TFP change in service-oriented manufacturing industry from three angles of period, industry and region, and finds out the TFP index of service-oriented manufacturing industry in China from 2006 to 2014. The technical efficiency index has the trend of absolute 尾 convergence, but the technological progress index has absolute 尾 divergence; the absolute 尾 convergence among the subdivision industries is obvious; the service manufacturing industry has obvious club convergence in the region. The convergence rate of absolute 尾 in the western region is obviously higher than that in the overall horizontal subdivision industry, and at the same time, the three major convergence clubs of east, middle and west are formed. Thirdly, using SPSS software and Eviews software, establish dynamic panel data regression model, analyze the factors that affect the total factor productivity of service-oriented manufacturing industry, find out the level of human capital, R & D investment, government support, marketization degree. The degree of opening to the outside world is the main reason for the difference of the total factor productivity of the service manufacturing industry, but the influence of each factor is not the same. Finally, based on the conclusion of this study, this paper analyzes the three aspects of government policy, industry and enterprise development, and puts forward some countermeasures and suggestions to promote the specialization, refinement and service development of service-oriented manufacturing industry.
【學位授予單位】:山東科技大學
【學位級別】:碩士
【學位授予年份】:2017
【分類號】:F224;F424
【參考文獻】
相關(guān)期刊論文 前10條
1 肖挺;;我國省份間服務(wù)業(yè)全要素生產(chǎn)率的檢驗分析[J];云南財經(jīng)大學學報;2017年02期
2 李占風;劉曉歌;;中國生產(chǎn)性服務(wù)業(yè)TFP的時空差異與影響因素分析[J];統(tǒng)計與信息論壇;2016年12期
3 陳菁泉;劉偉;杜重華;;環(huán)境規(guī)制下全要素生產(chǎn)率逆轉(zhuǎn)拐點的空間效應(yīng)——基于省際工業(yè)面板數(shù)據(jù)的驗證[J];經(jīng)濟理論與經(jīng)濟管理;2016年05期
4 王恕立;汪思齊;滕澤偉;;環(huán)境約束下的中國服務(wù)業(yè)全要素生產(chǎn)率增長[J];財經(jīng)研究;2016年05期
5 杜江;王銳;王新華;;環(huán)境全要素生產(chǎn)率與農(nóng)業(yè)增長:基于DEA-GML指數(shù)與面板Tobit模型的兩階段分析[J];中國農(nóng)村經(jīng)濟;2016年03期
6 肖挺;;我國服務(wù)業(yè)分地區(qū)及分行業(yè)生產(chǎn)率動態(tài)變化及收斂性分析[J];軟科學;2016年03期
7 陳超凡;;中國工業(yè)綠色全要素生產(chǎn)率及其影響因素——基于ML生產(chǎn)率指數(shù)及動態(tài)面板模型的實證研究[J];統(tǒng)計研究;2016年03期
8 王恕立;滕澤偉;劉軍;;中國服務(wù)業(yè)生產(chǎn)率變動的差異分析——基于區(qū)域及行業(yè)視角[J];經(jīng)濟研究;2015年08期
9 李靖華;馬麗亞;黃秋波;;我國制造企業(yè)“服務(wù)化困境”的實證分析[J];科學學與科學技術(shù)管理;2015年06期
10 杜江;;中國農(nóng)業(yè)全要素生產(chǎn)率增長及其時空分異[J];科研管理;2015年05期
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