Influence of Vicarious Learning on Start-up enterprises Survival

다국어 초록 (Multilingual Abstract)

Abstract
The enterprise is the main body of the market, the survival and development of the enterprise is not only related to its own, but also will have an impact on social stability and economic development. The problems of short survival time and difficult access to capital are common in Chinese enterprises, especially in small and medium-sized private enterprises. Therefore, it is very necessary to study the factors affecting the survival of enterprises. This study explores the relationship between vicarious learning and firm survival, tries to divide firm vicarious learning into leader learning and codelearning, and focuses on the relationship between codelearning, leader learning and firm survival, as well as the effect of vicarious learning on firm survival under the influence of policy incentives and firm size. Furthermore, this paper studies the following questions :(1) does the vicarious learning behavior of start-ups significantly improve the survival time of enterprises? (2) Does codelearning and leader learning intensity increase the survival time of enterprises? (3) Does policy incentive and support play a moderating role in the relationship between indirect learning and enterprise survival time? (4) Does the internal resources of the firm -- the size of the firm affect the relationship between indirect learning and the duration of the firm?
This article first to the leader of the study, codelearning, the concept of enterprise survival is defined, then the logical relationship between the three variables for literature, then, in the vicarious learning theory, system theory, signal theory, enterprise based on the analysis of the competitive advantage theory put forward in this paper, the hypothesis that build regression model. Select China Industrial enterprise database enterprises as the research object, collect and manually sort out the relevant data, eliminate the incomplete data of enterprise samples, and put forward the hypothesis of this paper on the basis of the analysis of the logical relationship between variables, take the 2011-2015 China industrial enterprise database related data as the research sample. It was processed and analyzed using Excel2010 and Stata 16.0. Descriptive statistical analysis, correlation analysis, multiple regression analysis and robustness test were conducted for the relationship among leader learning, codelearning and firm survival.
After research and analysis, this paper draws the following conclusions: Start-up companies first, instead of learning behavior significantly influence the survival time of the enterprise, including codelearning is significant positive enhancement effect, leader of the study is significant negative effects, because the leader of the enterprise has the area lies between sex, leader of the enterprise itself has the key resource is different from a competitor's unique resources, is the enterprise sustainable development support, That is to say, the leader enterprise has key resources that the codeenterprise does not have. The simple learning and imitation of the leader enterprise by the start-up enterprise may not improve the performance of the enterprise, because there is no early basis for the implementation of its strategy. Second, government incentive has a significant positive moderate effect on the main effect. When the industrial policy environment is in a positive and encouraging situation, enterprises will form a positive judgment on the future development of their own industry, and form a good incentive effect on the survival and development of enterprises. Thirdly, the enterprise size has a significant positive moderate effect on the main effect. The larger the enterprise has a higher sunk cost, which means a higher exit barrier, leading to a relatively long survival time of the enterprise. Finally, this part analyzes the empirical results and conclusions, and puts forward relevant suggestions from the perspective of the country, the government and enterprises respectively.
The innovation of this paper includes the following points:
First, this paper divides the codevicarious learning behavior of enterprises into two types, namely "leader learning" and "codelearning", and verifies the empirical analysis to enrich the existing research on the effect of organizational learning. Most of the previous studies only examined the impact of vicarious learning behavior on firm performance, but few further distinguished codevicarious learning and studied the relationship between such behavior and firm survival. In this regard, this paper expands the previous research basis, which is helpful to deepen the understanding of learning imitation effect of enterprises, and provides some reference for enterprises' strategic decision-making.
Second, corporate behavior is embedded in a certain social context, and social context factors will also have an important impact on corporate behavior. This paper focuses on the convergence learning and imitation behavior of enterprises in the context of macro policies and enterprises, especially on the two important moderating factors of policy incentive and enterprise size, which provides a new perspective for in-depth understanding of the formation of the mechanism of the influence of enterprise learning behavior on enterprise survival.
Third, most of the existing studies measure the impact of policies on enterprise decisions with dummy variables, and fail to carry out quantitative analysis on policy intensity, persistence and enterprise policy solutions, which weakens the practical application of relevant conclusions. Moreover, it cannot show the industry heterogeneity preference of government policies, so there is a lack of relevant research on the response of industry differentiation policies. Therefore, this paper adopts text analysis tools and word frequency analysis as the main means to measure policy incentive variables, so as to explore the industry heterogeneity of policy measurement and deepen the understanding and recognition of the impact of firm learning behavior on firm survival.
Fourthly, existing studies on the relationship between vicarious learning and firm survival in start-ups are scarce, and a systematic research framework has not yet been formed, making it difficult to fully reveal the causal relationship and conditional effect between the two. Combining with the Chinese government policy situation and enterprise internal resources of special research, emphatically analyzes the policy incentives, firm size moderate under the action of start-ups vicarious learning behavior and the relationship between the enterprise survival, enrich the research of enterprise relationship between learning and enterprise survival theme, also for related research provides a relatively complete theoretical framework.
Key words: Vicarious Learning business survival
policies encourage business size

목차 (Table of Contents)

• Contents
• Ⅰ.Introduction 12
• 1 Research background and significance 12
• 2 Reasearch content and framework 24
• 3 Research innovation point 29
• Ⅱ.Literature review and theoretical review 32
• 1 Concept definition 32
• 2 Theoretical basis 45
• 3 Literature review 66
• Ⅲ.Logical relationship between variables and hypothesis 81
• 1 learn from leader and enterprise survival 82
• 2 learn from code and enterprise survival 85
• 3 chapter summary 88
• Ⅳ.Research 90
• 1 Sample selection and data sources 90
• 2 Variable definitions and descriptive statistics 92
• 3 Moderl construction 101
• Ⅴ.Results and analysis 103
• 1 Descriptive statistical analysis 103
• 2 Correlation analysis 105
• 3 VIF test 107
• 4 Regression analysis 108
• 5 Robustness test of the influence of learning from leader and learning from code on enterprise survival 118
• 6 Results 119
• Ⅵ.Conclusions and recommendations 122
• 1 Conclusion 122
• 2 Research on enlightenment and suggestions 128
• 3、Insufficient research and outlook 132
• References: 135

참고문헌 (Reference)

1 Xia Qing.Business, "Environment and Opportunity Entrepreneurship", Wuhan University.55, 2019

2 Chen Lin, "to explore the use of Chinese industrial enterprise database", ( 06 ) : Pages 140-153 ., 2018

3 Cao Shengnan, "Study on the Impact of Financial Market Division on Enterprise Life Term", Henan University.66, 2019

4 Zhang Tianyu.An, "Empirical Study on the Peer Effect and Generation Mechanism of Capital Structure Decision-Making", Northeastern University.182, 2017

5 Li Yinlong.Study, "on the Relationship between Enterprise Age and Innovation Performance Based on Innovation Environment Type [ J ]", 08 ) :30-35, 2015