A Review on User Innovation Virtual Community and Suggestions for Future Research Da-liang Zhang 1, Yuan-yi Zhang2 1 2 Department of Business Management, Zhejiang University, Hangzhou, China Department of Business Management, Zhejiang University, Hangzhou, China (Zdl@zju.edu.cn,Zhangyuanyihao@163.com) Abstract - User innovation in virtual environment has become an important form, which companies need to promote. However, academic research on user innovation behavior in the virtual environment is far from sufficient. This study reviews user innovation research in the virtual community to discuss the basis and method of user innovation incentives in virtual community and summarizes existing research on innovation performance. Based on it, incentive objects, contextual factors, measurement are discussed for future research. Keywords - Virtue environment; user innovation; incentive; literature review I. INTRODUCTION With growing shortage of resources, enterprise innovation system is undergoing dramatic changes. Companies change their relatively closed innovation towards open innovation to take full advantage of resources and build a sustainable innovation system. In response to fast development of Internet economic and increasing number of Internet users, user innovation research has been gradually extended to the Internet context. User innovation in the virtual community gets researchers’ attention due to its rapid development and novel form. One of the important questions is how to motivate users. This study reviews the user innovation research in the virtual community, discusses ways to motivate user innovation in the virtual community, summarizes existing research on innovation performance, and lists valuable direction for future research. II. User innovation in virtual environment User innovation refers to new ideas or improvements on products or services by users of these products or services or improvements. There are various form of user innovation. It can be divided into concept and product innovation according to the tangibility level[1] (Hoffman, Kopalle, 2010) and to core-module and sub-module innovation according to product innovation domain. By user’s position it can be divided into the intermediary and end-user innovation [2] (Bogers, Afuah, 2010). By the platform, it can be divided into the traditional sense of innovation and IT-based innovation. The former appears in traditional product with special using context, such as sports equipment and medical equipment. The latter often appears with information technology, such as innovation on virtual platform [3] (Nambisan, 2002), Web 2.0-based innovation [4] (Bilgram, Brem, 2008), innovation in online communities, and innovation packages. By leading position, user innovation in the virtual environment can be divided into community-led and userled one. By different roles of development stages, Nambisan designed a virtual user innovation platform, including interactive mode, knowledge creation, user motivation, and integration with R & D team.[3] (Nambisan, 2002). Nambisan further integrated theories to discuss that different user motivation may lead to different contribution to community or company [5] (Nambisan and Baron, 2010). As for importance of different user, Von Hippel used lead user concept emphasizing willingness and ability differences ,while Trusov used influential, mainly referring to one who has major impact on other users in social networking site such as Blog and other content innovation media[6] (Trusov, Bodapati, 2010). Different theories have different interpretations for user behavior in virtual environment. It is believed by theory of social capital that relation can strengthen the commitment of members to help others among the groups, thus contributing to collective action [7] (Nahapiet and Ghoshal, 1998). Studies show that in a virtual environment, the more responsible members are, the more likely they could share knowledge and make contribution [8] (Wasko, and Faraj, 2005). In addition, social exchange theory. holds exchange is based on a mutually benefit. A support for this is study which finds reputation and learning promote user innovation behavior [9] (Harhoff, Henkel, 2003). Different theory interpretation enhances the interest of user innovation study in the virtual environment. However, above studies were conducted at individual level, little is known about differences among communities. III. User innovation incentives in virtual environment Although there is no systematic theory, guide for user innovation, however, has already developed in two aspects: What is the basis of incentives and the way of it. Incentives are mainly based on innovation motivation. Volker [4] (Bilgram, Brem, 2008) reviewed past research and found that in empirical research users innovate to seek happiness of the process, make use of potential ability and creativity and also are driven by external motivation such as money ,ease of use and use in special context. Xu Lan [11] (2007) introduced unique product and experience needs to innovation motivation studies, and found unique need affects consumer innovation. Nambisan divided motivation into four categories (Namibian and Baron, 2010),based on different theoretical background: community responsibility, selfimage enhancement expectation, professional skills enhancement expectations and the company's partnership. This classification underlines theoretical basis and helps to explain the type and size of the user contribution. Another basis of incentive is the place played by user in innovation, including the stage and the importance. In innovative design research in virtual community , Nambisan pointed out that users played different roles in different stages, thus leading to different management challenges [3] (Nambisan, 2002). He believed that in the stage of the product idea, users play the role of innovation resources and companies are mainly concerned about how to get user knowledge; play a co-creation role in product design and development stage and companies should focus on how to strengthen user knowledge; in product testing and support phase and companies should be concerned about how to promote interaction between users. As for importance, it involves the investigation into target capacity. Von Hipple and other scholars use lead user to depict users with strong innovation willingness and . Another concept is emergent nature, which refers to innovation characteristics that can identify product market trend[1] (Hoffman,, Kopalle, 2010). Companies should make different incentive policies based on different role user plays. According to social exchange theory, incentives can be broadly divided into social-emotional and economic kind (Foa, 1974). Social-emotional incentive will lead to social-emotional results, such as trust and acceptance of company.It shows that trust in business can affect user willingness to innovate [11] (Xu Lan, 2007). Virtual community studies have shown that the relationship will affect the user's sense of being respected, thereby affecting the willingness to cooperate in the new product development [13] (Porter and Donthu, 2008). The economic incentive is the incentive in the form of monetary incentives. There are some gaps. First, the current discussion just stays in the user level rather than the community level. From the community level, scholars can compare communities and find out key incentive model to help to build core competitive advantage. Second, it has not been discussed in depth how users feel as psychological process of incentives. IV.User innovation incentives measurement After discussion on innovation incentives, there is a need to know incentive performance. The study of organizational innovation performance measurement includes results-oriented and process-oriented measurement [16] (Adams, Bessant, 2006). The former focuses to the cost-benefit analysis from the perspective such as investment in human, material and financial resources, tools and their output market value. The latter considers innovation process, such as knowledge management including idea number, knowledge storage and information flow; innovation strategy including strategic direction and strategic leadership; organizational culture including culture, structure; project management including benefit analysis, communication, cooperation, and commercialization including market research, testing and sales. Table 1 summarizes ways of user innovation performance appraisal. TABLE I: Measurement on user involved innovation performance Key point Produc t attribu tes R e s u l t s o r i e n t e d B e h a v i o r o r i e n t e d Potenti al value Variable Area Paper Degree of customization, property quality, external sensitivity characteristics Perceived relative advantage, compatibility, community prevalence Investor evaluation Open design of online games platform for key product attributes Shu-Yu Yeh,2010 Key attributes of virtual user innovation Paul M.Di Gangi,2009 Evaluation of user improvement’s commercial value on library information system innovations adoption in sports community User innovations on medical device User innovation encouragement’s impact on business innovation cost User innovation ratio in total innovation of each industry User-oriented design Morrison,20 00 consumers ‘ intention to participate in hair design Non-economic incentives on different maturity user Lan Xu,2004 Marke t value Sales rate production Techni cal value Invest ment cost Number of patents Innova tion covera ge Innova tion cooper ation Intenti on to innova te Innova tion behavi or Innovation ratio Information costs ćsupport costs Information sharing, integration, design Have or not co- Innovation frequency, time Franke&Sha h,2002 Lu¨thje,2003 Lu¨thje,2003 Christian Lu¨thje,2004 Robert Veryzer,200 5 Yafeng Xie,2012 Learning from the above research, user innovation performance measurement in the virtual environment can also include results-oriented and process-oriented forms, as table 1 shows. A common practice is to measure product value. Paul M.Di Gangi [17] (Di Gangi and Wasko, 2009) defines key product attributes of innovation adoption, including the perception of relative advantage, compatibility, community prevalence and scaled it to measure user innovation value. V.Future direction for user innovation incentives in virtual environment A. Object There are two possible innovative behaviors to motivate: one is spontaneous user innovation and the other is under the influence of company or community. These two type is different in motivation and performance, which future research could focus on. The virtual community works as space for consumer to consumer interaction, in which they can interact in pairs or in groups.[18] (Libai, Bolton, 2010). Consumer to consumer interaction perspective is future direction of user innovation research. There is difference between single innovation behavior and group innovation. In addition, the difference between online and offline innovation is another problem for making incentive policy. How to make effective incentive to make online and offline innovation behavior promote each other has become valuable in future research. Finally, how to understand the lead user's contribution to the community and the company's growth and profits is also worthy of discussion. B. Context Innovation climate in organization studies provides a reference for study on user innovation in virtual community environment. As for definition of atmosphere, there are two different views: one defines atmosphere as objective environment [19] (Mauss, 1970) while the other as the overall perception of the environment by the innovation subject, as a product of cognitive experience [20] (Tesluk, Farr, 1997, Weick, 1995). Future research can focus on cognitive experience to examine the psychological impact of the climate on user innovation. For example, the innovation climate is measured by level and intensity. Level refers assessment of the level of community atmosphere and strength refers to the internal consistency in perception. Organizational innovation studies have demonstrated a positive relation between innovation climate level and performance. Climate strength moderate the relation. The higher the strength, the greater climate level’s impact on innovation performance. However, level and strength may have correlation, thus moderate effect may be weakened (Lindell & Brand, 2000). Future research can discuss the level and strength of climate on the incentive effects. The relationship between the community and the individual may affect the innovation incentives effect. Social identity theory (Ashforth, 1989) holds that the social identity of individual to his group may lead to some kind of interaction between individual and group, thereby enhances the participation behavior. Identification is critical for users to participate [22] (Muniz Jr., 2001). Community identity will increase user’s contribution to community innovation and corporate identity will increase user’s contribution to enterprise. Future research can use social identity to find out how relationship between the community and the individual affects the innovation incentives effect. For example, according to social identity theory, the identity of a thing may lead to psychological ownership of the things [23](Pierce, Kostova, 2001),which will help to understand the relationship between the individual and the community. Psychological ownership is a concept proposed by Pierce, which is different from formal ownership. It refers to mind state that one thinks the target is owned by his own and emphasizes the psychological control and possession of the target. There is no formal ownership to the community for users and the use of virtual space can meet the users’ self efficacy Future research can focus on potential value of psychological ownership in understanding user innovation. The type of product may moderate incentives mechanism. Past studies have shown that user innovation behavior is different for different products. Product with a strong "stickiness" will promote a higher level of innovative behavior. Future research could consider the moderate role of the product type on the incentives effect. Also, the life cycle of the product may lead to different types and level of innovation. Future research could consider different innovation incentive policies in different stages of life cycle. There may be different types of incentives for different virtual communities. Community as for management type can be divided into normative governance community and reputation-based community [18] (Libai, Bolton, 2010). Normative governance is established on normative force and it requires all parties involved to accept rules, make commitment and keep consensus based on reciprocity, dedication, trust. Its rules can be visible or not. Reputation-based community refers to the system designed by community managers with a feedback function, in which members of the different contributions have different social recognition and rewards. These two kinds of community management may also affect the implementation of the user innovation behavior and incentives. C. Measurement It can be drawn on other policy measurement for the measurement of innovation policies. For example, in the safety climate study, Zohar described security policy by three factors: Orientation, that is the relative importance compared with other policy, policy coherence, that is the degree of policy changes with environment and simplicity, that is the degree it can be identified [12] (Zohar and Luria, 2004). 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