| Innovation is the soul of a nation's progress and an inexhaustible motive for the development of a country.Innovation is not only an indispensable part of the social development,but also the core of the development of the enterprise.Without innovation,the enterprise will lose the soul,without innovation,the enterprise has no core competitiveness,and cannot survive in the fierce market competition.Enterprise innovation is to make full use of and optimize the allocation of resources and social resources and create and innovate from all levels of business management according to the development trend of market demand and products that meet the needs of the market.Since twenty-first Century,great changes have taken place in the global innovation mode,which makes the original closed innovation model have been a huge challenge:to enhance the competition environment and the uncertainty of product life cycles,for the needs of individual users,improve the degree of growth of enterprises,even abundant capital and advanced technology,are difficult to completely rely on the internal resources innovation activities,maintain competitive advantage.The original closed innovation has been unable to adapt to the needs of the times.Enterprises need to explore new ways of innovation,and gradually transform from closed innovation to open innovation.The concept of open innovation was originally proposed by Professor Chesbrough of Harvard University in 2003.He pointed out that enterprises should change the traditional mode of internal innovation,implement open innovation,use all the available suppliers and users as innovative resources and creative provider,and should not rely solely on internal knowledge and creativity;At the same time,not only enterprises can absorb knowledge from the outside,but also can spread the knowledge generated by enterprises.Open innovation refers to the innovation of the enterprise is no longer just the task of enterprise internal innovators,but more and more rely on external users to provide creative use of complementary inside and outside the enterprise innovation resources,effectively improve the efficiency of the allocation of resources,enhance the competitive advantage.In recent years,with the rapid development of computer technology,especially the wide application of Web2.0,the user generated content(UGC)showing explosive growth,every day many contents are uploaded to a variety of social media:blog,forum,website etc.These users generated content contains a lot of information,such as the connections between users,user preferences,and user emotions.Through deep mining of UGC,much valuable information can be found from it.The open innovation platform(OIP)is a virtual innovation community built on the Internet to collect user innovative content.Since the beginning of the establishment of OIP,it has aroused extensive concern and research in the business and academic circles.Although some enterprises improve their own innovation ability through the development and operation of OIP,but there are still a lot of problems,many scholars believe that the current practice is still about OIP more failures than successes,its development is facing four major challenges:(1)the successful understanding of user submitted ideas,and should be of heavy creative review task;(2)the lack of quantitative decision support system for recognition of outstanding ideas,and how to better integrate new knowledge and design into existing products and designs;(3)the balance of demand and the transparency of information disclosure;(4)maintain the sustainable development of the platform.Scholars have studied much on challenge(3)and(4),and they mainly focused on intellectual property management and platform management.This article focuses on the challenge(1)and(2),to focus on the platform users and ideas.Most of the previous studies only used the innovation value chain as a tool to distinguish the three stages of innovation and studied the input and output of innovation in different stages from the perspective of the enterprise.Few studies have studied the two different subjects of the users and ideas involved in the innovation value chain itself.This paper starts from the two main bodies of users and ideas,studies its users sharing behavior and ideas implemented in OIP,and refines the relevant research of multi-agent,multi-stage innovation value chain.This paper interprets the user's behavioral mechanism in OIP from the perspectives of social capital theory,social influence theory,and social learning theory,expands the scope of application of relevant theories,and explores the platform user behavior mechanism and ideas implemented mechanism from different perspectives.With the development of natural language technology,in-depth analysis of text has become a trend.Although text analysis and sentiment analysis have been widely applied and researched in many industries,in the field of open innovation,unstructured texts of OIP platforms is still a great deal of deficiencies in the research.This paper expands on the depth of the ideas and comments text,no longer limited to platform structured data.The main contents and conclusions of this paper are as follows:(1)Combining the user behavior data of the platform with the clustering algorithm(K-means algorithm)to classify the users based on the social capital status of different users on the platform.According to the theory of social capital,the characteristics of platform user behavior data can be divided into structural dimension social capital,relationship dimension social capital,and cognitive dimension social capital according to different roles and purposes.The structure dimension social capital is measured mainly through the interaction between users.In the platform user behavior data,it can be reflected in the user's interaction with other users mainly for ideas,questions,comments and answers;relationship dimension social capital mainly reflects the trust and recognition of the members in the social network to others.It is reflected in the user behavior of the platform is the attention behavior between users,including following(the number of users follow)and followers(the number of users being followed);the cognitive dimension is mainly reflected in the perceptions and values of the members of the community,including votes and best answers.The clustering results show that users of the open innovation platform can be classified into different types according to their behavioral characteristics on the platform.Different types of users have different social capital on the platform:The first type of user is lead user.The typical feature of this type of user is that he has a leading position in all activities of the platform.The three dimensions of structure,relationship,and cognition of social capital are also in a leading position on the platform.Compared with the other two dimensions of social capital,the cognitive dimension of social capital is slightly lower,which is also related to its leading position and relatively low recognition of other users.The second type of users is active user.The social capital in all dimensions belongs to the upper middle level.The third type is platform-supported users.The social dimensions of the structure dimension and the relationship dimension are all in the upper middle level,but their cognitive dimension is relatively higher.The main role of such users in the platform is to increase the confidence of other users and to support other users.The fourth category is that the platform guide user,whose overall social capital level to be uneven,among which the social dimension of the relationship dimension is relatively low.Such users do not pay much attention to other users,but by asking questions,they can also guide other users to share knowledge on the platform.The fifth category is effective user of the platform.The three dimensions of social capital are generally lower than the middle level.Compared with the other two dimensions,the cognitive dimension is relatively higher;and for the sixth type of one-time users,their social capital of each dimension belongs to the lowest level,which is in sharp contrast with the leading users' social capital.(2)What are the factors that affect the ideas sharing of platform users?Based on the division of social capital in front of the behavioral characteristics of users,a model was constructed for the influence of different dimensions of social capital on user ideas sharing.The model was tested by counting regression(Poisson regression and negative binomial regression).The results showed that the user's structural dimension social capital has a significant positive impact on users' ideas sharing on the platform,but the impact of the other dimensions on users' ideas sharing behavior have not been significantly tested.This shows that,on OIP,users who like to comment and vote on the ideas of other users have recognition and trust in the platform,can devote energy and time to the platform,and therefore also contribute to publish their own ideas to support the development and maintenance of the platform.Through statistics on ideas data,it is found that about 50%of users of the platform will no longer continue to share ideas after they have published a creative idea.This is unfavorable for the platform.Therefore,the factors that influence the user's continued ideas sharing on the platform need to be studied.Therefore,in this part of the study,we continue to build a user-continuing idea sharing influencing factor model to conduct in-depth exploration of user-continuing knowledge sharing behavior.By supplementing the user characteristics data,starting from psychology and social learning theory,this paper proposes that the user's self-display,peer recognition,social learning,and employee identities,etc.,may all be the reason for promoting continuous knowledge sharing on the platform.The empirical results show that self-presentation and social learning positively affect the user's continuous ideas sharing behavior,but peer recognition and employee identity have not been significantly tested.(3)In the ideas transformation stage,the most important thing is how to select valuable creative ideas that can be implemented from many user ideas.Therefore,this section study selects the ideas-related features,including not only structured features,such as total ideas scores and the number of the comments,but also innovative,in-depth text mining and sentiment analysis of idea and comment texts.For structured variables,get five variables of idea title length,idea content length,idea title sentiment,idea content sentiment and idea comment sentiment,and suppose that the influence of comments sentiment on ideas implemented is regulated by the number of comments.Logistic regression was used to test the model.The research results show that the idea title and the length of the content have a significant positive effect on ideas adoption.Idea title with sentiment tendencies has a significant negative effect on idea adoption,while the negative effects of idea content with sentiment tendencies on idea adoption have not been achieved.In the significance test,the total number of idea scores has a significant positive effect on idea adoption,and the interaction item of the number of comments and comment sentiment is significantly tested.(4)Construct a idea adoption forecasting model based on user feature data and idea feature data to provide a basis for companies to quickly screen creative ideas.The research results show that random forests have relatively higher accuracy in predicting idea adoption than support vector machine algorithms,but the prediction effect of adopted creative ideas is also not satisfactory.Therefore,in later studies,we can choose a more appropriate model to continue exploration.The innovation of this article is mainly reflected in the following three aspects:(1)Most of the previous studies used the innovation value chain as a tool to divide innovation activities,and from the perspective of the company to study the innovation investment and performance of companies in different stages.This paper applies this theory to an open innovation platform and combines the characteristics of OIP to optimize and improve the innovation value chain.The original chain structure is improved to a structure with a feedback mechanism.The research from the generation of ideas to the transformation of ideas is defined as the research of user's idea sharing mechanism.The research of idea transformation into idea diffusion is defined as the research of enterprise idea adoption mechanism,and an innovation value chain model suitable for OIP is constructed.From the perspective of users and ideas to study the internal mechanism of idea generation and transformation,formed the research theme of this article,namely,research on OIP idea management,and enriched the research and application scope of existing innovation value chain theory.(2)Innovatively applying the classic theories of social capital theory and social impact theory to the research of the open innovation platform has expanded the scope of application of the original theory and expanded the perspective of OIP research.Through social capital analysis of platform users,according to the distribution of social capital in three dimensions of different users,the platform users are divided into six different types from a new perspective,and on this basis,continue to study the different impact of the three different dimensions of social capital on the user's idea sharing mechanism.From the perspective of user psychology and sociology,this article also deeply studies the factors that influence the user's continuous sharing of ideas on the platform.In the process of research on idea adoption mechanism,from the perspective of social impact theory,comprehensively combining the essential characteristics of users and creative ideas and studying the influencing factors that influence the adoption of creative ideas by enterprises,is an in-depth improvement and supplement to existing OIP research.(3)This paper conducts a comprehensive and in-depth data mining of enterprise OIP users and idea information,starting with the essential characteristics of users and ideas,and adopting a combination of theoretical analysis and empirical research methods.The research results enrich the existing OIP theory and have a strong theoretical innovation and practical significance.In previous studies,most of the research on OIP users and ideas used structured data,and few studies started from the essence of the idea texts and comment texts.In this study,in-depth text analysis and sentiment analysis of platform idea and comment are taken as an important research variable and whether the research on creative ideas and commentary sentiment variables has a significant influence on the adoption of ideas by enterprises.The in-depth analysis of the essential features of users and ideas is a useful supplement and intensification of existing research. |
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