Parallel to these advances in user involvement and user roles in NPD based on user characteristics, research started to focus on the possibilities and methodologies for involvement of ‘ordinary’ users in NPD. Duverger and Hassan (2008) suggest that unsatisfied users, or users that have stopped using a certain service or product (also known as ‘defectors’), are a potential source of innovative ideas. They make this observation in the context of service innovation. This is in line with Reichwald and Piller (2006) who found that dissatisfaction with existing solutions motivates consumers to participate in forms of product innovation. Magnusson (2009) states that too much expertise and knowledge might inhibit development of novel, original and creative knowledge, therefore pleading to involve end- users that do not display Lead User-characteristics. This is contradictory with Lüthje (2003) and Piller and Ihl (2009) who argue that technical expertise to develop new solutions may qualify an ‘expert user’ to stimulate technical innovation and assist in the development of products that are technically feasible. Kristensson and Magnusson (2010) also state that, in the context of service innovation, ‘ordinary’ users with contextual use experience and without too much restriction (caused by fundamental technological expertise or knowledge on the potential feasibility), can contribute to the innovation process, but situate this contribution in the provision of innovative ideas.
From this overview, we gather that the involved users are not Lead Users as defined in the previous sections, nor are they carefully selected users with certain characteristics. However, they cannot be labeled as ‘ordinary users’ either as they seem to display certain characteristics with regards to the innovation domain, such as dissatisfaction with the current product offering (defectors), or personality-related characteristics such as creativity or enthusiasm. Instead of carefully selecting these users, it is assumed that the ‘right’ type of ‘ordinary user’ is reached through self-selection in the process of user involvement. Therefore, researchers started investigating ways of user involvement and how this affected the self-selection process. Poetz and Schreier (2011) researched the characteristics and motivations of participants in an online idea generation contest. They found that participating
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users tend to have experience with the underlying problem, a sound technical knowledge of the related products, score higher on the Lead User characteristics ‘high expected benefits from innovations’ and ‘being ahead of a trend’, and creative personalities. However, none of these measures appeared to be significantly correlated to the quality of the submitted ideas. The quality of the submitted ideas was assessed by an expert panel. The authors also concluded that not all participants were true Lead Users, but that the crowdsourcing process had attracted qualified users to participate. Similar results were found in studies by Kleemann et al. (2008) and Reichwald and Piller (2006). When compared to ideas from professionals, the user ideas scored even higher in terms of novelty and customer benefit, and slightly lower on feasibility. Research by O’Hern and Rindfleisch (2008) discovered four types of user co- creation: co-designing (spontaneous design of innovation), collaborating (active participation in NPD-activities), submitting (spontaneous ideation), and tinkering (modification by using). They also see self-selection and motivation as more important factors than using a screening method to select the right customers. Kristensson et al. (2008) conclude out of empirical research that actually experiencing certain situations was of great significance for users when developing ideas for innovative NPD. The further argue: “As users are experiencing various situations in which they encounter difficulties (their own and those of others), certain emotions and cognitions are triggered. Through such experiences, users become aware of their needs, and these needs then stimulate ideas that stem directly from real experience.” This view also extends the previous works in this section, as these viewed user involvement mostly from the angle of ‘customer’ involvement. By adding the concrete use experience, something which customers per definition have, as a separate factor in the equation, this broadens the potential of ‘useful’ users beyond the current customer base, as users can acquire usage experience through specific research methodologies. In the next chapters, we will further argue that this ‘experiencing’, that facilitates need awareness and valuable user contribution for the NPD process, is a central aspect of Living Lab projects that evolve around an intervention that enables the users to experience (certain aspects of) the innovation.
Summarizing, most of the studies in this area are influenced by criticisms on the Lead User and user characteristics research, and consist of empirical research into user ideas and contributions, especially in the ideation stages. The authors that argue for the involvement of ordinary users in NPD base their ideas on a rather limited amount of empirical studies, situated mostly in the domain of service innovation and focusing on ideation, although some of the online crowdsourcing and idea contest platforms and methods are also used in other stages of the NPD process. They warn against too much technological knowledge as a killer of unburdened creativity, but the involvement of ordinary users is situated almost exclusively in the front-end of innovation. Therefore, this line of reasoning does not contradict the other User Innovation authors, but rather complements them, demonstrating that a large variety of
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ideas can enrich the innovation process, and that multiple user types might play a role in innovation. The literature dealing with crowdsourcing and idea contests turns the equation upside down and looks for methodologies and (online) platforms to attract the ‘right’ users and user input through self-selection. So instead of generating difficult and lengthy screening processes, attention turned towards solutions that would perform this screening by itself. An example of these platforms are the socalled innovation contest platforms, such as InnoCentive, where challenges are broadcasted to an undefined audience of ‘solvers’ that can return ‘solutions’ in order to obtain a (mostly monetary) reward (Allio, 2004), or other crowdsourcing platforms such as Wikipedia that rely on user contributions for its content generation and aggregation (Bruns, 2008). The participating users are labeled as ‘ordinary users’ as often their innovation related characteristics are not known, but through the self- selection mechanism they do exhibit the characteristic ‘motivation to participate’ that can be linked to intrinsic as well as extrinsic motivations, depending on the platform and mechanism that is used (Lakhani & Wolf, 2005). For an overview of the research in this field, see Bullinger and Moeslein (2011), but conclusive findings with regards to user motivations and characteristics are not available yet. Moreover, we also gathered that actual usage or situational experience with the innovation in development is able to facilitate relevant user contributions and to abstract need-related knowledge.