创新柔性对制造企业智能化转型影响机制研究
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摘要
智能制造是全球制造业的发展趋势,也是中国制造业转型升级的主攻方向。基于创新柔性理论,系统分析了创新柔性、技术创新和制造企业智能化转型之间的内在关系,构建了创新柔性对制造企业智能化转型的影响模型,深入研究创新柔性对制造企业智能化转型的影响机制。通过新能源装备制造企业的问卷调查数据对模型及假设进行实证分析。研究表明,创新柔性对制造企业智能化转型有显著正向影响,技术创新在创新柔性与制造企业智能化转型之间起部分中介作用,信息化水平在创新柔性与技术创新之间、技术创新与制造企业智能化转型之间均有正向调节作用,政策环境在创新柔性与制造企业智能化转型之间、技术创新与制造企业智能化转型之间均有正向调节作用。研究结果对制造企业智能化转型具有理论意义和实践启示。
At present,China is at the intersection of energy revolution and equipment manufacturing towards intelligent manufacturing.The energy revolution requires increasing the proportion of new energy in the energy structure to promote low-carbon energy structure.But the intelligent manufacturing transition of equipment manufacturing requires the manufacturer of equipment to adapt to the Development and Change of Environment and to improve enterprise ability and management level. New energy equipment,in front of equipment manufacturing development in China,its intelligent manufacturing level in future will directly affect the development and utilization prospects of new energy in China,and then affect the low-carbon process of China's energy structure.The existing literature shows that the factors affecting the development of intelligent manufacturing include both external environment and internal capability. However,most of the previous research results are based on individual factors and lack of systematic and quantitative research. The mechanism of influencing factors on the development of intelligent manufacturing needs further study.This paper puts forward hypotheses of relevance among the external environment,enterprise capability,management level and intelligent manufacturing,as well as relevance between the external environment and enterprise capability. External environment has a direct positive impact on intelligent manufacturing. Enterprise capability variables which are measured by innovation,integration,interconnection and other secondary variables,has a direct positive impact on intelligent manufacturing of new energy equipment. External environment promotes intelligent manufacturing of new energy equipment through the direct positive impact on enterprise innovation capability,integration capability and interconnection capability,and then on enterprise capability. Management level and enterprise capability promote each other and have a positive impact on enterprise capability in the process of promoting the development of new energy equipment intelligent manufacturing. Management level has a direct and positive impact on enterprise capability,and then affects intelligent manufacturing.A small range of questionnaires were issued for predictive testing before the formal issuance of large sample questionnaires.The reliability and validity of variables were preliminarily tested. The subjects of the questionnaire were asked by 5 point likert scale. In the pre-test stage,questionnaires are sent out by mail and e-mail. In the empirical stage,questionnaires are sent out to leaders of new energy equipment manufacturing enterprises and scholars in the field of new energy equipment intelligent manufacturing. The validity rate of the questionnaire reached the general standard. The items in the scale of measurement cited the scale with good reliability and validity and high recognition from the relevant literature. In this paper,the cronbachs alpha coefficient method is used to test the reliability of the measurement scale. Confirmatory factor analysis is used to test the validity of the survey data,and to judge the fitness of the model.The detection result show that the internal consistency and reliability of all relevant variables such as external environment,enterprise capability,management level and intelligent manufacturing are high enough,and the structural model of variables are satisfactorily. On the basis of confirmatory factor analysis,the maximum likelihood method (ML) is used to validate the model and related hypothesis of the influencing factors of new energy equipment intelligent manufacturing. In the process of empirical research,some correlations of items in the model are added in pursuit of making the model pass the test.The empirical results based on structural equation model show that the factors affecting the development of new energy equipment intelligent manufacturing mainly include external environment,enterprise capacity and management level1. The external environment and management level indirectly drive the development of intelligent manufacturing with enterprise capability as the intermediate variable. Meanwhile,the external environment has a direct impact on the development of intelligent manufacturing. Policy orientation puts forward the overall requirements for the development of enterprise capability. The upstream and downstream industrial partnership promotes the communication between upstream and downstream enterprises in the process of intelligent manufacturing of new energy equipment,and it has a direct impact on the enterprise capability. Industry competition forces enterprises to seek comparative advantages and makes the differences comparing with other enterprises.2. The external environment has a negative effect on the development of new energy equipment intelligent manufacturing.Unfair competition has come into being because some enterprises occupy a monopoly position by non-market-oriented means,even obtain profits by illegal infringement. Instead,some innovative enterprises are constrained by unfair industry competition which makes it difficult to get their due innovative income. The risk of intelligent development of new energy equipment and uncertain cycle factors make appearance of effect lag. Therefore,the endogenous motivation of intelligent manufacturing development of new energy equipment is suppressed. And the new energy equipment manufacturers have no time to take care of the development of intelligent manufacturing.3. Enterprise capability can promote the development of intelligent manufacturing. New energy equipment manufacturing enterprises improve their technological innovation ability and strengthen core technology research and development,which plays an important role in promoting enterprises to take the path of innovation-driven development and to achieve intelligent manufacturing. Digital integration can be used to design,analyze and optimize every link of production process,operation steps,production units,production lines and even the whole factory. It is the only way which must be passed for new energy equipment manufacturing enterprises to realize intelligent manufacturing. New energy equipment manufacturing enterprises need to make information transfer independently in industry chain through upstream and downstream supply chain interconnection,information interconnection between supply and demand,interconnection between internal products and equipment,between people and equipment,in order to promote the transformation of enterprises from traditional manufacturing mode to intelligent manufacturing.4. The management level promotes the development of intelligent manufacturing by improving the ability of enterprises. From the point of view of the actual operation of the enterprise,the management level which is the " soft power" of the enterprise,mainly plays a supporting and service role. But it is difficult to have a direct impact on the improvement of the enterprise capacity. The management level is largely interacted with the external environment to promote the intelligent development of new energy equipment manufacturing enterprises. Speaking specifically,information management can quickly collect information about external environment changes for decision-makers. Organizational management can change organizational structure according to upstream and downstream industrial cooperation or industry competition in pursuit of meeting the development needs of new energy equipment manufacturing enterprises. Process management can ensure that new energy equipment manufacturing enterprises keep communication smooth,which can avoid production problems caused by inappropriate coordination,in the process of cooperation with upstream and downstream enterprises.
At present,China is at the intersection of energy revolution and equipment manufacturing towards intelligent manufacturing.The energy revolution requires increasing the proportion of new energy in the energy structure to promote low-carbon energy structure.But the intelligent manufacturing transition of equipment manufacturing requires the manufacturer of equipment to adapt to the Development and Change of Environment and to improve enterprise ability and management level. New energy equipment,in front of equipment manufacturing development in China,its intelligent manufacturing level in future will directly affect the development and utilization prospects of new energy in China,and then affect the low-carbon process of China's energy structure.The existing literature shows that the factors affecting the development of intelligent manufacturing include both external environment and internal capability. However,most of the previous research results are based on individual factors and lack of systematic and quantitative research. The mechanism of influencing factors on the development of intelligent manufacturing needs further study.This paper puts forward hypotheses of relevance among the external environment,enterprise capability,management level and intelligent manufacturing,as well as relevance between the external environment and enterprise capability. External environment has a direct positive impact on intelligent manufacturing. Enterprise capability variables which are measured by innovation,integration,interconnection and other secondary variables,has a direct positive impact on intelligent manufacturing of new energy equipment. External environment promotes intelligent manufacturing of new energy equipment through the direct positive impact on enterprise innovation capability,integration capability and interconnection capability,and then on enterprise capability. Management level and enterprise capability promote each other and have a positive impact on enterprise capability in the process of promoting the development of new energy equipment intelligent manufacturing. Management level has a direct and positive impact on enterprise capability,and then affects intelligent manufacturing.A small range of questionnaires were issued for predictive testing before the formal issuance of large sample questionnaires.The reliability and validity of variables were preliminarily tested. The subjects of the questionnaire were asked by 5 point likert scale. In the pre-test stage,questionnaires are sent out by mail and e-mail. In the empirical stage,questionnaires are sent out to leaders of new energy equipment manufacturing enterprises and scholars in the field of new energy equipment intelligent manufacturing. The validity rate of the questionnaire reached the general standard. The items in the scale of measurement cited the scale with good reliability and validity and high recognition from the relevant literature. In this paper,the cronbachs alpha coefficient method is used to test the reliability of the measurement scale. Confirmatory factor analysis is used to test the validity of the survey data,and to judge the fitness of the model.The detection result show that the internal consistency and reliability of all relevant variables such as external environment,enterprise capability,management level and intelligent manufacturing are high enough,and the structural model of variables are satisfactorily. On the basis of confirmatory factor analysis,the maximum likelihood method (ML) is used to validate the model and related hypothesis of the influencing factors of new energy equipment intelligent manufacturing. In the process of empirical research,some correlations of items in the model are added in pursuit of making the model pass the test.The empirical results based on structural equation model show that the factors affecting the development of new energy equipment intelligent manufacturing mainly include external environment,enterprise capacity and management level1. The external environment and management level indirectly drive the development of intelligent manufacturing with enterprise capability as the intermediate variable. Meanwhile,the external environment has a direct impact on the development of intelligent manufacturing. Policy orientation puts forward the overall requirements for the development of enterprise capability. The upstream and downstream industrial partnership promotes the communication between upstream and downstream enterprises in the process of intelligent manufacturing of new energy equipment,and it has a direct impact on the enterprise capability. Industry competition forces enterprises to seek comparative advantages and makes the differences comparing with other enterprises.2. The external environment has a negative effect on the development of new energy equipment intelligent manufacturing.Unfair competition has come into being because some enterprises occupy a monopoly position by non-market-oriented means,even obtain profits by illegal infringement. Instead,some innovative enterprises are constrained by unfair industry competition which makes it difficult to get their due innovative income. The risk of intelligent development of new energy equipment and uncertain cycle factors make appearance of effect lag. Therefore,the endogenous motivation of intelligent manufacturing development of new energy equipment is suppressed. And the new energy equipment manufacturers have no time to take care of the development of intelligent manufacturing.3. Enterprise capability can promote the development of intelligent manufacturing. New energy equipment manufacturing enterprises improve their technological innovation ability and strengthen core technology research and development,which plays an important role in promoting enterprises to take the path of innovation-driven development and to achieve intelligent manufacturing. Digital integration can be used to design,analyze and optimize every link of production process,operation steps,production units,production lines and even the whole factory. It is the only way which must be passed for new energy equipment manufacturing enterprises to realize intelligent manufacturing. New energy equipment manufacturing enterprises need to make information transfer independently in industry chain through upstream and downstream supply chain interconnection,information interconnection between supply and demand,interconnection between internal products and equipment,between people and equipment,in order to promote the transformation of enterprises from traditional manufacturing mode to intelligent manufacturing.4. The management level promotes the development of intelligent manufacturing by improving the ability of enterprises. From the point of view of the actual operation of the enterprise,the management level which is the " soft power" of the enterprise,mainly plays a supporting and service role. But it is difficult to have a direct impact on the improvement of the enterprise capacity. The management level is largely interacted with the external environment to promote the intelligent development of new energy equipment manufacturing enterprises. Speaking specifically,information management can quickly collect information about external environment changes for decision-makers. Organizational management can change organizational structure according to upstream and downstream industrial cooperation or industry competition in pursuit of meeting the development needs of new energy equipment manufacturing enterprises. Process management can ensure that new energy equipment manufacturing enterprises keep communication smooth,which can avoid production problems caused by inappropriate coordination,in the process of cooperation with upstream and downstream enterprises.
引文
[1]中国企业联合会.智能制造:中国视角与企业实践[M].北京:清华大学出版社,2016.China enterprise confederation.Intelligent manufacturing chinese perspective and enterprise practices[M].Beijing:Tsinghua University Press,2016.
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[3]Weyer S,Schmitt M,Ohmer M,et al.Towards industry 4.0-Standardization as the crucial challenge for highly modular,multi-vendor production systems[J].IFAC PapersOnLine,2015,48(3):579-584.
[4]Lyly-Yrjninen J,Holmstr9m J,Johansson M I,et al.Effects of combining product-centric control and direct digital manufacturing:The case of preparing customized hose assembly kits[J].Computers in Industry,2016,82(9):82-94.
[5]冷单,王影.我国发展智能制造的案例研究[J].经济纵横,2015(8):78-81.Leng Dan,Wang Ying.China’s development of intelligent manufacturing case studies[J].Economic Review,2015(8):78-81.
[6]Zahra S A,Sapienza H J,Davidsson P.Entrepreneurship and dynamic capabilities:A review,model and research agenda[J].Journal of Management Studies,2006,43(4):917-955.
[7]Mathews J A.Competitive advantages of the latecomer firm:Aresource-based account of industrial catch-up strategies[J].Asia Pacific Journal of Management,2002,19(4):467-488.
[8]Martínez-Sánchez A,Vela-Jiménez M J,Pérez-Pérez M,et al.Inter-organizational cooperation and environmental change:Moderating effects between flexibility and innovation performance[J].British Journal of Management,2010,20(4):537-561.
[9]Kylheiko K,Sandstr9m J,Virkkunen V.Dynamic capability view in terms of real options[J].International Journal of Production Economics,2002,80(1):65-83.
[10]雍灏,陈劲.技术创新中的领先用户研究[J].科研管理,1999,20(3):57-61.Yong Hao,Chen Jin.Lead user research for technological innovation[J].Science Research Management,1999,20(3):57-61.
[11]赵历男,赵璞,冯宇.基于不同战略导向的组织柔性对技术创新选择的影响研究[J].中国科技论坛,2012(9):05-11.Zhao Linan,Zhao Pu,Feng Yu.Relationship of organizational flexibility and technological innovation based on strategic orientations theory[J].Forum On Science And Technology In China,2012(9):05-11.
[12]黄群慧,贺俊.“第三次工业革命”与中国经济发展战略调整---技术经济范式转变的视角[J].中国工业经济,2013(1):05-18.Huang Qunhui,He Jun.“The Third Industrial Revolution”and the adjustment of China’s economic trategy-Transformation of the techno-economic paradigm[J].China Industrial Economics,2013(1):05-18.
[13]苏竣,张汉威.从R&D到R&3D:基于全生命周期视角的新能源技术创新分析框架及政策启示[J].中国软科学,2012(3):93-99.Su Jun,Zhang Hanwei.From R&D to R&3D:A framework for new energy technology innovation and its policy implications:Perspective of full life cycle[J].China Soft Science,2012(3):93-99.
[14]罗来军,朱善利,邹宗宪.我国新能源战略的重大技术挑战及化解对策[J].数量经济技术经济研究,2015(2):113-128.Luo Laijun,Zhu Shanli,Zou Zongxian.Key technical challenges of Chinese new energy strategy and its countermeasures[J].The Journal of Quantitative&Technical Economics,2015(2):113-128.
[15]韩先锋,惠宁,宋文飞.信息化能提高中国工业部门技术创新效率吗[J].中国工业经济,2014(12):70-82.Han Xianfeng,Hui Ning,Song Wenfei.Can informatization improve the technology innovation efficiency of Chinese industrial sectors[J].China Industrial Economics,2014(12):70-82.
[16]Lee J,Bagheri B,Jin C.Introduction to cyber manufacturing[J].Manufacturing Letters,2016,8:11-15.
[17]Giret A,Garcia E,Botti V.An engineering framework for service-oriented intelligent manufacturing systems[J].Computers in Industry,2016,81(C):116-127.
[18]Richard O C,Murthi B P S,Ismail K.The impact of racial diversity on intermediate and long-term performance:The moderating role of environmental context[J].Strategic Management Journal,2010,28(12):1213-1233.
[19]Narasimhan R,Das A.Manufacturing agility and supply chain management practices[J].Production&Inventory Management Journal,1999,40(1):04-10.
[20]宋华,王岚.企业间关系行为对创新柔性的影响研究[J].科研管理,2012,33(3):01-10.Song Hua,Wang Lan.The impact of relational behavior between enterprises on innovation flexibility[J].Science Research Management,2012,33(3):01-10.
[21]Damanpour F.Organizational innovation:A meta-analysis of effects of determinants and moderators[J].Academy of management journal,1991,34(3):555-590.
[22]张蓉君,于秀明,胡静宜.基于智能制造评价指数的河南企业智能制造能力分析[J].标准科学,2016(7):24-27.Zhang Rongjun,Yu Xiuming,Hu Jingyi.Intelligent manufacturing capacities analysis of enterprises in Henan province based on intelligent manufacturing evaluation indexes[J].Standard Science,2016(7):24-27.
[23]孟凡生,赵刚.传统制造向智能制造发展影响因素研究[J].科技进步与对策,2018,35(1):66-72.Meng Fansheng,Zhao Gang.Research on the influence factors of traditional manufacturing to the development of intelligent manufacturing[J].Science&Technology Progress and Policy,2018,35(01):66-72.
[24]Robert N Anthony.Planning and Control Systems:A framework for analysis[M].Cambridge:Harvard University Graduate School of Business Administration,1965.
[25]郝臣.中小企业成长:政策环境与企业绩效---来自中国23个省市309家中小企业的经验数据[J].上海经济研究,2006(11):15-22.Hao Chen.SME growth:Policy environment and firm performance-Empirical data from 309 SMEs in 23 provinces and cities in China[J].Shanghai Economic Review,2006(11):15-22.
[26]Baron R M,Kenny D A.The moderator-mediator variable distinction in social psychological research:Conceptual,strategic,and statistical considerations[J].Journal of Personality and Social Psychology,1986,51(6):1173.
[27]Aiken L S,West S G.Multiple regression:Testing and interpreting interactions[M].Thousand Oaks,CA:Sage,1991.
[2]Cainelli G,Marchi V D,Grandinetti R.Does the development of environmental innovation require different resources?Evidence from Spanish manufacturing firms[J].Journal of Cleaner Production,2015,94:211-220.
[3]Weyer S,Schmitt M,Ohmer M,et al.Towards industry 4.0-Standardization as the crucial challenge for highly modular,multi-vendor production systems[J].IFAC PapersOnLine,2015,48(3):579-584.
[4]Lyly-Yrjninen J,Holmstr9m J,Johansson M I,et al.Effects of combining product-centric control and direct digital manufacturing:The case of preparing customized hose assembly kits[J].Computers in Industry,2016,82(9):82-94.
[5]冷单,王影.我国发展智能制造的案例研究[J].经济纵横,2015(8):78-81.Leng Dan,Wang Ying.China’s development of intelligent manufacturing case studies[J].Economic Review,2015(8):78-81.
[6]Zahra S A,Sapienza H J,Davidsson P.Entrepreneurship and dynamic capabilities:A review,model and research agenda[J].Journal of Management Studies,2006,43(4):917-955.
[7]Mathews J A.Competitive advantages of the latecomer firm:Aresource-based account of industrial catch-up strategies[J].Asia Pacific Journal of Management,2002,19(4):467-488.
[8]Martínez-Sánchez A,Vela-Jiménez M J,Pérez-Pérez M,et al.Inter-organizational cooperation and environmental change:Moderating effects between flexibility and innovation performance[J].British Journal of Management,2010,20(4):537-561.
[9]Kylheiko K,Sandstr9m J,Virkkunen V.Dynamic capability view in terms of real options[J].International Journal of Production Economics,2002,80(1):65-83.
[10]雍灏,陈劲.技术创新中的领先用户研究[J].科研管理,1999,20(3):57-61.Yong Hao,Chen Jin.Lead user research for technological innovation[J].Science Research Management,1999,20(3):57-61.
[11]赵历男,赵璞,冯宇.基于不同战略导向的组织柔性对技术创新选择的影响研究[J].中国科技论坛,2012(9):05-11.Zhao Linan,Zhao Pu,Feng Yu.Relationship of organizational flexibility and technological innovation based on strategic orientations theory[J].Forum On Science And Technology In China,2012(9):05-11.
[12]黄群慧,贺俊.“第三次工业革命”与中国经济发展战略调整---技术经济范式转变的视角[J].中国工业经济,2013(1):05-18.Huang Qunhui,He Jun.“The Third Industrial Revolution”and the adjustment of China’s economic trategy-Transformation of the techno-economic paradigm[J].China Industrial Economics,2013(1):05-18.
[13]苏竣,张汉威.从R&D到R&3D:基于全生命周期视角的新能源技术创新分析框架及政策启示[J].中国软科学,2012(3):93-99.Su Jun,Zhang Hanwei.From R&D to R&3D:A framework for new energy technology innovation and its policy implications:Perspective of full life cycle[J].China Soft Science,2012(3):93-99.
[14]罗来军,朱善利,邹宗宪.我国新能源战略的重大技术挑战及化解对策[J].数量经济技术经济研究,2015(2):113-128.Luo Laijun,Zhu Shanli,Zou Zongxian.Key technical challenges of Chinese new energy strategy and its countermeasures[J].The Journal of Quantitative&Technical Economics,2015(2):113-128.
[15]韩先锋,惠宁,宋文飞.信息化能提高中国工业部门技术创新效率吗[J].中国工业经济,2014(12):70-82.Han Xianfeng,Hui Ning,Song Wenfei.Can informatization improve the technology innovation efficiency of Chinese industrial sectors[J].China Industrial Economics,2014(12):70-82.
[16]Lee J,Bagheri B,Jin C.Introduction to cyber manufacturing[J].Manufacturing Letters,2016,8:11-15.
[17]Giret A,Garcia E,Botti V.An engineering framework for service-oriented intelligent manufacturing systems[J].Computers in Industry,2016,81(C):116-127.
[18]Richard O C,Murthi B P S,Ismail K.The impact of racial diversity on intermediate and long-term performance:The moderating role of environmental context[J].Strategic Management Journal,2010,28(12):1213-1233.
[19]Narasimhan R,Das A.Manufacturing agility and supply chain management practices[J].Production&Inventory Management Journal,1999,40(1):04-10.
[20]宋华,王岚.企业间关系行为对创新柔性的影响研究[J].科研管理,2012,33(3):01-10.Song Hua,Wang Lan.The impact of relational behavior between enterprises on innovation flexibility[J].Science Research Management,2012,33(3):01-10.
[21]Damanpour F.Organizational innovation:A meta-analysis of effects of determinants and moderators[J].Academy of management journal,1991,34(3):555-590.
[22]张蓉君,于秀明,胡静宜.基于智能制造评价指数的河南企业智能制造能力分析[J].标准科学,2016(7):24-27.Zhang Rongjun,Yu Xiuming,Hu Jingyi.Intelligent manufacturing capacities analysis of enterprises in Henan province based on intelligent manufacturing evaluation indexes[J].Standard Science,2016(7):24-27.
[23]孟凡生,赵刚.传统制造向智能制造发展影响因素研究[J].科技进步与对策,2018,35(1):66-72.Meng Fansheng,Zhao Gang.Research on the influence factors of traditional manufacturing to the development of intelligent manufacturing[J].Science&Technology Progress and Policy,2018,35(01):66-72.
[24]Robert N Anthony.Planning and Control Systems:A framework for analysis[M].Cambridge:Harvard University Graduate School of Business Administration,1965.
[25]郝臣.中小企业成长:政策环境与企业绩效---来自中国23个省市309家中小企业的经验数据[J].上海经济研究,2006(11):15-22.Hao Chen.SME growth:Policy environment and firm performance-Empirical data from 309 SMEs in 23 provinces and cities in China[J].Shanghai Economic Review,2006(11):15-22.
[26]Baron R M,Kenny D A.The moderator-mediator variable distinction in social psychological research:Conceptual,strategic,and statistical considerations[J].Journal of Personality and Social Psychology,1986,51(6):1173.
[27]Aiken L S,West S G.Multiple regression:Testing and interpreting interactions[M].Thousand Oaks,CA:Sage,1991.