A Study on the Relationship between Supply Chain Concentration and Enterprise Technology Innovation Performance: An Analysis Based on MOA Theory

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1 A Study on the Relationship between Supply Chain Concentration and Enterprise Technology Innovation Performance: An Analysis Based on MOA Theory Xingye Xiao 1, Le Chang 2, Shuying Wang 3, Abstract The inherent mechanism of the existing theory for the influence of supply chain concentration on the technological innovation performance of listed companies is not clear. The confusion caused by the practice is how to integrate supply chain management to reshape the core competitiveness. Based on the MOA theory, this paper uses the data of 455 high-tech listed companies to explore the mechanism between supply chain concentration and enterprise technological innovation performance, and analyze the innovation strategy and collaborative innovation in the relationship the regulatory role. It is found that the concentration of enterprise supply chain, innovation strategy and collaborative innovation have a significant positive impact on the performance of enterprise technology innovation. Finally, from the strategic implementation mechanism, collaborative cooperation from the perspective of enterprise management policy recommendations for enterprises to enhance the performance of technological innovation provides practical guidance. Keywords supply chain concentration; technological innovation performance; innovation strategy; collaborative innovation; MOA theory 1 Introduction Under the background of globalization and knowledge, technological innovation is the source of the acquisition and maintenance of the core competitive advantage of listed companies. However, with the intensification of market competition, it is increasingly difficult for enterprises to gain continuous competitiveness with internal resources and need to find competitive advantage from the whole supply chain. From a practical point of view, Hewlett-Packard, General Motors, Chrysler, and other companies through the supply chain upstream suppliers to establish long-term tight supply chain partnership to jointly manage the organization and the organization between the process, in order to achieve efficient Product flow, service flow, information flow and capital flow, and ultimately improve the enterprise's technological innovation performance, shaping the competitive advantage (Huang Liping 2015). From the theoretical point of view, the supply chain focus on @qq.com 1 Xingye Xiao: Lecturer, College of Management Engineering, Zhengzhou University, Zhengzhou, , China 2 Le Chang: Lecturer, College of Management Engineering, Zhengzhou University, Zhengzhou, , China 3 Shuying Wang: Professor, College of Management Engineering, Zhengzhou University, Zhengzhou, , China

2 cooperation with the upper and lower reaches of enterprises to optimize the allocation of resources, thereby promoting the improvement of corporate performance, thereby enhancing the technological innovation performance (Chen Zhenglin 2014). In this context, supply chain concentration as an important part of the field of supply chain management has aroused great concern of scholars at home and abroad. The existing research has discussed the relationship between supply chain concentration and enterprise technological innovation performance from financial performance, inventory management and product market competition, and has provided rich material and experience for the research of this paper (Shen Chang e et al 2016; Chen JG et al 2011). However, few studies have studied the relationship between supply chain concentration and enterprise technology innovation performance based on MOA theory, especially the lack of analysis of the role of innovation strategy and collaborative innovation in supply chain concentration, and thus the confusion of core enterprises Is the supply chain concentration in the end can effectively enhance the technological innovation performance of enterprises? Under what circumstances can enterprises rely on supply chain management to drive the overall performance of technological innovation? The answer to these questions is of great theoretical and practical significance to promote the development and performance of enterprise technological innovation and to solve the effective integration of resources. Based on the above analysis, this paper integrates the supply chain concentration, innovation strategy, collaborative innovation and enterprise technology innovation performance in the unified analysis framework based on MOA theory, and uses 455 high-tech listed companies to analyze the supply chain And the relationship between innovation and technological innovation performance, and explore the regulatory role of innovation strategy and collaborative innovation in the relationship between the two, and deeply explore the internal mechanism and path of supply chain concentration influence enterprise technological innovation performance. In this paper, the existing research has been extended as follows: first, based on the concept of innovative integration of resources, the enterprise technology innovation performance as a driving force, opportunity and ability of the common results, which integrate the theoretical model to explain the formation of enterprise technology innovation performance mechanism; second, the supply chain concentration on the performance of enterprise technology innovation is relatively scarce, only to stay in the theoretical analysis and a small amount of empirical analysis level. In this paper, the data of listed companies as the sample supply chain concentration and enterprise technology innovation performance research, to make up for the lack of previous research. 2 Theoretical basis and research hypothesis 2.1 Supply Chain Concentration and Enterprise Technology Innovation Performance Most studies show that supply chain concentration has a positive effect on firm performance. Information sharing among supply chain members can help companies

3 reduce bullwhip effect and market uncertainty to improve overall supply chain performance (Chen 2011). Supply chain concentration refers to the concentration of supply chain partnership in manufacturing enterprises, which is an important manifestation of supply chain partnership. It includes the concentration of purchasing in the upstream of supply chain and the sales concentration in the downstream of supply chain (Jr D L 2010). From a theoretical point of view, the higher the concentration of procurement, the fewer the number of suppliers, and the core suppliers to trade the total amount of procurement will rise, the higher the concentration of sales, the fewer the number of customers, with the main The total volume of customer transactions will increase (Zhuang Bochao et al 2015); Second, the closer the partnership between the manufacturing enterprise and the customer, the higher the level of information sharing, can reduce the impact of the bullwhip effect, reduce the uncertainty of demand (Chen F 2000). From the empirical point of view, Pan Wenan (2006) pointed out that enterprises to establish partnerships to strengthen the external integration of supply chain, help to improve innovation performance and enhance competitive advantage (Pan Wenan 2006); Zhuangbao Chao (2015) to China's manufacturing industry 1132 listed companies as a sample study pointed out that the supply chain concentration and help enterprises to improve business performance and market performance, thereby enhancing the performance of technological innovation; The results showed that the higher the concentration of the supply chain, the more the advantage of cooperation and the improvement of the technological innovation performance of the company (Cao M and Zhang Q 2011). Therefore, based on the above analysis, this paper proposes the following research hypothesis: H1: supply chain concentration is positive to promote enterprise technology innovation performance 2.2 Innovation Strategy and Enterprise Technology Innovation Performance Enterprise-level innovation, including product innovation, process innovation, organizational innovation and market innovation, reflects the enterprise to participate in market competition, a strategic attitude (Gao Suying et al 2011). Innovation strategy is the enterprise to carry out technological innovation activities with the overall, long-term, directional planning (Peng Can and Yang Ling 2009). From a theoretical point of view, the more innovative strategies that are more adventurous, open and willing to cooperate can gain market information resources and technical resources in a timely manner to compensate for the shortage of innovative resources within the enterprise and improve innovation performance (Kotlar 2013); Second, the choice and effective implementation of the appropriate innovation strategy of the enterprise, its technical capacity will be improved rapidly, so as to enhance the performance of technological innovation. From the empirical point of view, Peng Can (2008) study pointed out that the successful implementation of innovation strategy can enable enterprises in the technology and market two aspects of the first to become

4 a technology leader and market monopoly; Burgelman (2001) pointed out that the existence of clear and clear innovation strategies is a crucial factor in the formation of innovative enterprises, regardless of the type of innovation strategy adopted. The improvement of enterprise technology innovation performance is largely dependent on the innovation strategy adopted by enterprises; Bai Junhong (2008) pointed out that the consistency of innovation strategy is conducive to enterprises to obtain new product development efficiency and ability to help enterprises get innovative performance on the competitive advantage; He Jianhong (2012) study pointed out that the enterprise innovation strategy has a significant positive impact on innovation performance. Therefore, based on the above analysis, this paper proposes the following research hypothesis: H2: Innovation Strategy Affects Enterprise Technology Innovation Performance 2.3 Cooperative Innovation and Enterprise Technology Innovation Performance At present, collaborative innovation management has become a hot issue in the field of innovation. Enterprises in their collaborative innovation process, on the one hand, as the beneficiaries of the synergies from the organization outside the border to obtain the necessary resources; On the other hand, as a contributor to collaboration, and other innovative subjects together for the "invisible hand" to provide strength(xie Xuemei and Liu Siyu 2015). From the theoretical point of view, first, collaborative innovation model means that the enterprise and the external coordination between the resources of a commitment to reciprocity, on the basis of coordination within the main body, external resources for their own use, in order to achieve technological innovation performance ; Second, collaborative innovation is an important means to realize the process of knowledge accumulation and enterprise learning process, which can promote the improvement of organizational dynamic ability and improve the performance of enterprise technological innovation (Gils 2004). From the empirical point of view, Xie Xuemei (2015) based on the Yangtze River Delta metropolitan area of 16 cities in 427 small and medium manufacturing enterprises empirical data, the use of structural equation model, the results show that collaborative innovation on innovation performance has a significant positive effect; Based on the questionnaire survey data of 168 science and technology enterprises in Taiyuan City, Tang Yongyong (2016) shows that collaborative innovation network has a significant positive impact on innovation performance by using correlation analysis and multiple regression analysis; Zhang Yanfei (2015) uses the data of the listed companies on the GEM to construct the enterprise innovation synergy index, and uses the measurement model to study the relationship between the degree of collaborative innovation and the innovation performance. The results show that the degree of collaborative innovation has a significant positive impact on the enterprise technical effect. Therefore, based on the above analysis, this paper proposes the following research hypothesis: H3: Collaborative Innovation Affects the Performance of Enterprise Technology Innovation

5 3 Research design 3.1 Sample selection and data sources This paper chooses the data of 455 high-tech industries (communication equipment, software development, semiconductor, electrical equipment) listed in China and Shanghai in 2015 as a sample, the comparative study on the relationship between supply chain concentration and enterprise technology innovation performance. Screen the sample company according to the following principles: (1) the choice of R & D activities more frequent high-tech industry listed companies; (2) excluding listed companies that have or will be ST, * ST, SST, S * ST and S; (3) excluding the lack of data listed companies. Eventually get 455 listed companies sample. Limited by the length of the list, did not detail the specific list of sample companies. The original data from the listed company's annual report and the Shanghai Stock Exchange and the Shenzhen Stock Exchange website disclosure of listed companies information. 3.2 Variable measurement Dependent variable: technical innovation performance (R&D). Based on the study of Weiwu (2016), this paper uses the natural logarithm of R&D as the dependent variable. Argument: Supply Chain Concentration (SC). Based on the research method of Chen Zhenglin, based on the scale of supply chain integration, the time characteristic of supply chain integration is added, and the supply chain is constructed by the ratio of the mean and variance of the proportion of five customers and the proportion of suppliers Integrated proxy variable [2]. Innovation Strategy (M). The company's R & D behavior to some extent reflects a company's innovative strategic posture, usually by the proportion of the total staff of science and technology staff, whether to set up R&D institutions, R&D investment or the number of patent applications and other indicators to express. This paper refers to the research method of Gao Suying et al. (2011), which means the degree of emphasis on the innovation strategy of the company with the proportion of the total staff. Collaborative Innovation (SD). This paper draws on the research method of Zhang Yanfei (2015), and evaluates the description of the cooperative innovation behavior in the prospectus according to the prospectus. The main criteria include: cooperation more objects for more than 5; established long-term cooperation of institutions and organizations, such as joint laboratories, research and development centers, research and development base, etc; with a number of objects With a long period of time, more than 3 years; cooperation is effective, innovative resources to enhance the efficiency of integration; lead the establishment of technology alliances, and actively participate in technical alliances, or with a number of institutions to participate in industry technical standards. The main criteria are: through contract, agreement and other forms of cooperation with other colleges and universities, but the cooperation is mainly concentrated in the technical and project level, but the enterprise technology research and development supplement. General innovation exchanges and cooperation scoring for 1, the main

6 criteria include: there are production and research cooperation or exchange and cooperation, but the cooperation of the project, the object, duration and content are more vague. No obvious cooperation score is 0, the main feature is the search is not obvious on the technical cooperation of the relevant description, or clearly that no research and development cooperation. Control variables: In order to control the influence of other factors on the research model, this paper chooses the scale of assets, firm size, net profit and company age as the control variables. Table 1. Variable definitions and variable design Variable type Variable name Variable symbol Variable definitions Dependent variable Independent variable Technical innovation performance Supply chain concentration Innovation strategy Collaborative Innovation RD SC M SD R&D expenditure logarithm The ratio of the mean and the variance of the proportion of the five customers and the proportion of the suppliers in the past three years Number of technical staff / number of employees Collaborative innovation 3, production and research cooperation 2, the general exchange and cooperation 1, no obvious cooperation 0 Control variable Asset size ASSET The natural logarithm of the total assets at the end of the year Enterprise scale SIZE The total number of employees in the year Net profit P The natural logarithm of net profit at the end of the year Company age AGE To reduce the year of incorporation by Descriptive statistical analysis The mean value of the variables, the standard deviation and the correlation coefficient are shown in Table 2. It can be seen from Table 2 that the correlation coefficient between variables is not significant. In addition, further calculations show that the variable variance expansion factor is less than 2, less than the critical value of 10. This shows that the multicollinearity of variables is not serious. Mean 1RD Table 2. Mean, Standard Deviation and Correlation Coefficient Standard deviation 2SC M ** SD ** ASSET *

7 6SIZE ** ** 0.13 * 0.82 ** P ** ** 0.57 ** AGE Note: Significant level P * <0.1, P ** <0.05, (2-tailed). 3.4 Model setting and regression analysis Based on the research and research variables, this paper constructs the empirical analysis model of supply chain concentration and enterprise technology innovation performance. Among them, companies at year t, concentration, represents the technological innovation performance of listed that listed companies in the year i year in the supply chain means that the listed company i in the year of innovation strategy index, means that the co-innovation index of listed company i at time t, denotes the set of control variables, denotes random error term. The model was analyzed by SPSS The results are shown in Table 3. Table 3. Hypothesis Test RD Basic model Model 1 Model 2 Model 3 Control variable P SIZE ASSET AGE Independent variable SC 0.01 * M 0.35 *** SD 0.12 *** 2 R Adjusted R F Statistics Note: Significant levels of P * <0.1, P *** <0.001, all coefficients are normalized It can be seen from the regression results that supply chain concentration has a significant positive impact on the performance of enterprise technological innovation (β = 0.01, P <0.1), assuming that H1 is supported; innovation strategy has significant positive performance to enterprise technological innovation performance (Β = 0.12, P <0.001). Assuming that H2 is supported, synergistic innovation has a significant positive effect on the performance of technological innovation (β = 0.12, P <0.001), assuming that H3 is supported. 4 The conclusion This paper systematically discusses the influence of supply chain concentration,

8 innovation strategy and collaborative innovation on the performance of enterprise technology innovation based on the MOA theory, which is the core issue of whether the concentration of supply chain promotes the performance of enterprise technological innovation. In this paper, by constructing the theoretical model, according to the selection of listed companies in China in 2015 as a sample, the theoretical model of the hypothesis of testing, The results show that the concentration of enterprise supply chain, innovation strategy and collaborative innovation have a significant positive impact on the performance of enterprise technology innovation. The conclusion of this paper deepens the understanding and grasp of the current literature on the performance of enterprise technology innovation, and provides management enlightenment for rational implementation of supply chain integration and enhancement of local enterprise core competitive advantage. Although this article has provided some valuable conclusions to the enterprise supply chain concentration and technological innovation, there are still some shortcomings. First of all, this study uses the cross-sectional data for regression analysis, which may lead to temporary causal relationship between variables, dynamic data contribute to a deeper understanding of the causal relationship; Secondly, this paper does not study the performance of enterprise technological innovation according to the industry division. The future scholars can compare the relationship between supply chain concentration and technological innovation performance in different industries, and strengthen the general applicability of the research conclusion. Thirdly, this study is based only on the data of A-share listed companies in Shanghai and Shenzhen markets. It does not consider the high-tech enterprises such as small plates and GEMs. Future research can apply the research of this paper to these enterprises and realize further deepening the understanding of supply chain Relationship with technological innovation performance. References Huang Liping 2015 Connotation, theoretical basis and economic consequences of supply chain integration - A review of the relationship between supply chain integration and firm performance in foreign countries. China Township Enterprise Accounting. (8): Chen Zhenglin, Wang Yu 2014 Empirical Study on the Effect of Supply Chain Integration on Financial Performance of Listed Companies. Accounting Research. (2): Shen Chang'e, Wei Ronghuan, Tian Zhou 2016 Supply Chain Integration, Working Capital Management Efficiency and Capital Structure [J]. Academic Forum. 39 (12): Zhang Meng 2013 Supply chain integration, product market competition and enterprise performance. Financial Supervision. (29): Chen J G. Chen JG, Zhu J, Zhang YH, et al 2011 Cancer survival in Qidong, China, In: Sankaranarayanan R, Swaminathan R, eds. Cancer Survival in Africa, Asia, the Caribbean and Central America. IARC Sci Pub No. 162, Lyon: IARC, 2011:43-53 Jr D L, Wempe W F, Zacharia Z G 2010 Concentrated supply chain membership and financial performance: Chain- and firm-level perspectives. Journal of Operations Management. 28(1):1-16

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