Crowdsourcing as a problem solving strategy


Published on

ISPIM Conference, Helsinki, June 2013

  • Be the first to comment

  • Be the first to like this

No Downloads
Total Views
On Slideshare
From Embeds
Number of Embeds
Embeds 0
No embeds

No notes for slide

Crowdsourcing as a problem solving strategy

  1. 1. This paper was presented at The XXIV ISPIM Conference – Innovating in Global Markets: Challenges for Sustainable Growth in Helsinki, Finland on 16-19 June 2013. The publication is available to ISPIM members at 1 Cheer the crowd? Exploiting crowdsourcing as a problem-solving strategy Miia Kosonen* Lappeenranta University of Technology, School of Business, P.O.Box 20, 53851 Lappeenranta, Finland. E-mail: Kaisa Henttonen Lappeenranta University of Technology, School of Business, P.O.Box 20, 53851 Lappeenranta, Finland. E-mail: * Corresponding author Abstract: To gain more novel ideas and empower users to take part in innovation activities, many organizations outsource problem-solving tasks to voluntary crowds. Yet a significant body of current knowledge concerns the characteristics of innovative users at the expense of the hosting organization and its actions. By reviewing literature from the fields of innovation management, knowledge management, marketing and e-commerce, our study identifies 10 practices to facilitate innovation-related problem solving among external crowds. Firstly, breeding user motivation calls for providing stimulating tasks, giving timely feedback, encouraging interaction, rewarding appropriately, building sense of community, and selecting the right communication technologies. Secondly, putting crowd know-how into action is facilitated by assessing the degree and distribution of crowd know-how, specifying tasks appropriately, providing support for task interpretation, and encouraging collaboration. Keywords: Crowdsourcing; crowd; innovation; knowledge, knowledge creation, problem; problem-solving; idea generation 1 Introduction Today, many consumers want to create their own experience rather than solely being passive recipients of a firm’s offerings. For instance, online communities provide spaces where individual users may participate in developing and modifying products on an on- going basis, thus becoming co-creators of valuable knowledge (Sawhney and Prandelli, 2000, Füller et al., 2007). Another form of engaging consumers is crowdsourcing, where firms solicit input from voluntary users interested in the firm’s products or services (Leimeister et al., 2009, Poetz and Schreier, 2012, Afuah and Tucci, 2012). Crowdsourcing has been coined as “a strategic model to attract interested, motivated crowd of individuals capable of providing solutions superior in quality and quantity to
  2. 2. This paper was presented at The XXIV ISPIM Conference – Innovating in Global Markets: Challenges for Sustainable Growth in Helsinki, Finland on 16-19 June 2013. The publication is available to ISPIM members at 2 those that even traditional forms of business can” (Brabham, 2010, p. 79). However, the transformation from company-driven innovation into more user-driven models may also raise challenges which need to be addressed by both researchers and practitioners. Managers can no longer rely on the “if we build it, they will come” principle. Pouring money into different types of online platforms is wasted investment if managers do not understand how users are motivated and enabled to contribute. While there is a growing stream of studies focusing on the characteristics of the individual users participating in the generation of the innovative output (Lee and Cole, 2003, Bagozzi and Dholakia, 2006, Jeppesen and Frederiksen, 2006, Mahr and Lievens, 2012) also in idea crowdsourcing (Zheng et al., 2011, Kosonen et al., 2012a), less is known about 1) under which conditions and 2) using which kinds of management practices firms may successfully apply crowdsourcing. For the former, a notable exception is the pioneering study by Afuah and Tucci (2012), where the authors compare three problem-solving mechanisms: solving internally, applying crowdsourcing, and designating to an exclusive contractor. Based on their work, crowdsourcing in general has the potential to improve the efficiency and effectiveness of problem solving “under certain circumstances” (ibid., p. 355), which depend on the characteristics of the problem, the knowledge required, the crowd, and the solutions to be evaluated. However, an important question remains in how innovation managers outsource problem-solving tasks to an external crowd: which types of actions does this require from the hosting organization? In line with Santonen et al. (2012), we note how current research on crowdsourcing has limitations from the innovation-related knowledge perspective. Hereby, we make a basic assumption that there is a hosting organization – either private or public-sector organization – aiming at having benefit from the proposed solutions. To gain more benefit, there is a need to develop practical roadmaps not only for assessing the potential of crowdsourcing (Afuah and Tucci, 2012) but also for optimally facilitating problem solving among external crowds. As there is myriad of tasks and areas of interest where crowdsourcing has been applied (see Brabham, 2008, 2010), our study takes a narrower focus on types of problem-solving where new product ideas or designs are solicited from voluntary users. We believe this setting is justified as new product development and innovation-related tasks involve high degrees of complexity (von Hippel, 1994), while they may also imply more potential value outcomes than simple or routine tasks. The research question can be formulated as follows: how to facilitate crowdsourcing and innovation-related problem solving within external crowds? Due to the newness of the research area, the study is conceptual in nature. The theoretical knowledge base related to crowdsourcing still seems to be in its infancy (Santonen et al., 2012) and therefore it is important to combine knowledge from existing research and adapt it to crowdsourcing settings. Building on the literature from the fields of innovation management, knowledge management, marketing and electronic commerce, our study critically assesses how to facilitate crowd participation in the idea generation phase of the crowdsourcing process. To provide practical insight, we incorporate three case examples to illustrate how crowdsourcing has been applied as a vehicle for problem-solving and spurring innovation. Further illustrations are drawn from four interviews conducted with the hosts of IdeasProject, which is a company-hosted site for idea crowdsourcing.
  3. 3. 2 Conceptual background In co-creation, a company seeks innovative ideas and commentary on new technologies and new improved products or services (Zwass, 2010). With our focus on innovation- related problem solving, we thus consider crowdsourcing participants as innovation co- developers (Chesbrough, 2003, Jeppesen and Frederiksen, 2006, Füller et al., 2007). Building on knowledge-based theory of the firm, it has recently been argued that a firm’s problem-solving effectiveness is key to organizational performance (Nickerson and Zenger, 2004, Jeppesen and Lakhani, 2010). Firms need both the capability to select high-value problems, and have them solved either through internal hierarchies of external markets (Nickerson and Zenger, 2004). Hereby, a focal question is under which conditions external solvers are able to produce better solutions than firm-internal agents. Jeppesen and Lakhani (2010) refer to “broadcast search” as a process of disclosing a description of a problem and inviting anyone deeming themselves qualified to solve such problem to participate. This brings us to the concept of crowdsourcing. In general, it is defined as “the act of taking a task traditionally performed by a designated agent (such as an employee or a contractor) and outsourcing it by making an open call to an undefined but large group of people” (Howe, 2008). A common feature to all forms of crowdsourcing is that they depend on the contribution by a certain crowd. Two main types of crowdsourcing initiatives are integrative, where complementary knowledge from a large number of users is pooled together, and selective, where competing users are identified and selected to give input (Schenk and Guittard, 2009). Selective crowdsourcing typically takes the form of idea contests, where the best ideas are selected and rewarded either materially or by giving recognition (Zheng et al., 2011). This could also be labelled Tournament-based crowdsourcing (Afuah and Tucci, 2012). Schenk and Guittard (2009) further distinguish crowdsourcing initiatives based on the complexity of tasks. Routine-types of tasks may involve e.g. data collection or identifying valuable pieces of information from a large mass of data, such as in the case of a medical institute which outsourced identifying cancer cells from tens of thousands of pictures. Complex tasks are related to problem solving within innovation projects and require creativity, such as in the case of design contests (Brabham, 2010) which involve a high amount of information and a broad set of potential alternatives (information diversity). Complexity thus implies there are a high number of elements and their multiple interrelationships involved in a task. In addition, potential changes may happen to both elements and relationships during task execution (Wood, 1986), reflecting its dynamic nature. At least a certain degree of complexity is typical for crowdsourcing with an aim at solving innovation-related problems. 3 Three modes of crowdsourcing – case examples Contest mode: InnoCentive was launched in 2001. It is designed as a two-sided platform where IC’s clients – solution seekers – may announce R&D related problems within a wide range of scientific domains. Thereafter, the problem solvers enter into contests to compete against
  4. 4. This paper was presented at The XXIV ISPIM Conference – Innovating in Global Markets: Challenges for Sustainable Growth in Helsinki, Finland on 16-19 June 2013. The publication is available to ISPIM members at 4 each other to find a winning solution, which is awarded a preannounced cash prize and recognition. The solutions are submitted through the web and reviewed by the seeker, who remains anonymous at least during the open phase. Potential solvers only need to provide contact information, while also identifying degrees earned and areas of research interest while registering as users. Similarly, providing solutions is easy, requiring only uploading a word-processes solution written into a template. Currently, there are more than 270,000 registered solvers from over 200 countries. (See Lakhani et al., 2007, Jeppesen and Lakhani, 2010, Brabham, 2010) Community mode: Lego Cuusoo The Danish toy company Lego closely works with its fan community in order to develop new designs and products. Lego Cuusoo was launched in 2008. It allows a cost-effective way to search for new designs, and a wider community for ideation. Any user may create a project in order to suggest a new product concept, which others may then vote for. Those having 10,000 supporters have a chance to become official products. Original contributors receive 1 % royalty of the net revenue of the designs chosen for production, where Shinkai 6500 submarine was the first project completing the process. In contrast to the contest mode, users do not directly compete with each other; instead, they share an enthusiasm towards LEGO products and willingness to develop even more fascinating designs. Such communities operate by freely accumulating and recombining ideas, and also by voting on the best designs. (Boudreau and Lakhani, 2013) Hybrid mode: IdeasProject is an open innovation and brainstorming community, enabling the two-way exchange of ideas between users and developers. The site was launched in 2011 firstly in English and less than one year later also in Chinese. IdeasProject is powered and hosted by telecommunications company Nokia. The common denominator for users is enthusiasm towards Nokia products and mobile lifestyle in general. A significant amount of the ideas derive from competitions organized by the hosting company (termed “challenges” as in the case of InnoCentive), but the community also provides an open idea space, where users may freely suggest ideas in different topic categories. In either case, they may comment or rate each others’ input to give feedback and help to develop ideas further. The site thus involves elements from both modes described above: contest and community (Kosonen et al., 2012b). 4 Facilitating crowd participation with managerial actions To provide insight on how to manage crowdsourcing, in the following we focus our lens to the nature of the crowd and facilitating its participation. We first review practices that a company can use when it is trying to motivate individuals taking part in the
  5. 5. crowdsourcing activities, and thereafter discuss how to get the best advantage of the know-how within the crowd. Breeding crowd motivation Firstly, the starting point in cheering voluntary crowds to participate is to provide mentally stimulating tasks. Several studies have underlined the importance of subjective experiences in order to participate in crowdsourcing tasks (Zheng et al., 2011, Kosonen et al., 2012a) and in community-based problem solving (Wasko and Faraj, 2000, Nambisan and Baron, 2007). Such experiences are related to both personal learning (e.g., gaining new knowledge, curiosity) and enjoyment provided by solving a given task (e.g., pleasure of sharing own ideas, helping to develop better solutions, challenging one’s mental boundaries). Respectively, organizations need to make sure the given tasks are appropriately designed and provide mental stimulus for the solvers. For instance, “pilot crowds” can be used to test the problem setting. Secondly, in community-based modes of crowdsourcing it seems beneficial that the organization provides feedback for users. For example, Jeppesen and Frederiksen (2006) studied voluntary contribution in a firm-hosted community. They found that company feedback was one motivating factor for user activity. Similar findings have been reported in idea crowdsourcing hosted by a company (Kosonen et al., 2012a). In organizational settings, Grant (2012) notes that when employees receive feedback concerning their performance and results of their tasks, they feel their self-enhancement motives are fulfilled and they are more willing to take part in valuable activities also in the future. Bandura (1977) pointed out how people who receive positive feedback are likely to produce more and make higher-quality contributions in comparison to those who receive negative feedback. Furthermore, the speed of company feedback may also impact user activity over time. Previous research in different settings has implied that timely feedback is important e.g. in group decision making (Xanthopulos et al., 2000). One of the hosts of IdeasProject described: “Once you have a prosperous community, you have to give credit back to its members, by giving attention and taking effort alike.” Thirdly, if the hosting organization is making an effort to facilitate interaction, favourable user beliefs are likely to emerge, as social interaction further motivates people to share information and engage in problem solving in online communities (Porter and Donthu, 2008, Wasko and Faraj, 2000). Both user-to-user and company-to-user interactions are considered valuable in this respect. Being recognized by the hosting organization has a positive effect on user participation in product development activities online (Jeppesen and Frederiksen, 2006). Idea generation is strengthened also by user-to- user interaction in terms of 1) quantity (frequency and time spent) 2) scope (topics discussed in depth and the diversity of topics) and 3) mode (number of participants and forms of communication) (Wu and Fang, 2010). Support for interaction calls for coherence in site content and structure, as well as appropriate tools on the site. For instance, knowledge creation needs to be organized using well-defined and structured
  6. 6. This paper was presented at The XXIV ISPIM Conference – Innovating in Global Markets: Challenges for Sustainable Growth in Helsinki, Finland on 16-19 June 2013. The publication is available to ISPIM members at 6 topics, which allow users to rate and comment each other’s input without being lost in the jungle of new ideas (Kosonen et al., 2012b). Fourthly, while mere enjoyment of problem-solving and striving for better solutions may be enough in community-based modes of crowdsourcing (see Wasko and Faraj, 2000, Jeppesen and Frederiksen, 2006, Kosonen et al., 2012a), current research demonstrates that users engaging in contests are motivated by material rewards such as cash prizes or awards (Leimeister et al., 2009, Zheng et al., 2011). From the hosting organization’s part, this notion calls for subtle understanding on what attracts users to contribute; a common fallacy is to rely on the mere existence of a crowdsourcing platform. Users’ participation is driven by the benefits they expect, being personal, social, hedonic or learning-related by nature (Nambisan and Baron, 2007). Hosting organizations need to gain insight on the expectations of users sharing an interest in the task in question, before sticking into a certain mode of crowdsourcing. While material rewards match with contest mode, in communities they should be applied with caution. Awards and cash prices may turn counterproductive by hampering intrinsic motivation, which is not returned even if there are no longer rewards offered (see Bock and Kim, 2002). Fifthly, an important implication concerns crowdsourcing settings involving on-going collaborative elements. This is related to building sense of community and feelings of being a part of a social collective. In technical terms, one workable solution could be using real-time connections in the ideation sessions. Users “should feel like they are sitting around same virtual table in same room” (Antikainen et al., 2010). Also when the hosting organization’s employees are involved as visible members of the community, it helps in creating a certain feeling of efficacy – “my input matters” – as these employees are just one or two mouse-clicks away and signal other users that they are a part of a professional community. This, in turn, may increase commitment. On the other hand, the hosting organization should avoid exaggerated control over user-driven interactions, as it may deteriorate commitment and identification: users no longer feel that this is also their place (Tonteri et al., 2011). Instead, community hosts need to publicize most active contributors and make success stories more visible, thus positively affecting users’ feelings of belonging to the collective. Finally, attention should be paid to the selected communication technologies. According to Antikainen et al. (2010), active participation calls for easy-to-use tools that allow users to express themselves and share their personal insight. Appropriate online tools reduce the cognitive effort of users to be able to develop new knowledge (Füller et al., 2007) and positively affect the usage experience. Easiness of use becomes even more important as the sites grow larger in content and also provide many kinds of functionalities simultaneously, including various types of textual and multimedia content, writing posts and reviews, rating and commenting (Kosonen et al., 2012b). In sum, the means to facilitate user motivation are stimulating tasks, giving feedback on a timely basis, encouraging interaction, rewarding appropriately, building sense of community, and selecting the right communication technologies. No matter of what the motivational factors are, the prevailing rule of thumb is “know your crowd” and its expectations. For instance, earlier studies indicate that women are generally more reluctant to participate in competitive problem-solving than men (Jeppesen and Lakhani, 2010) and will do so only when very confident of having a winning solution. Intuitively, targeting a crowd with high proportion of women engaging in problem solving would
  7. 7. thus favour community-based or hybrid modes. Even if crowdsourcing by nature implies designating problem-solving into large mass of users, it does not need to involve mere “shouting in the dark”. Putting crowd know-how into action In general, the ability of users to come up with potential new solutions depends most heavily on the underlying industry or product category, as well as the nature of the task in question. When the knowledge needed is directly linked to user experience, it is easier for users to succeed in formulating their ideas (Poetz and Scheier, 2012, Afuah and Tucci, 2012). Paradoxically, the more radical ideas the organization pursues, the more it seems to benefit from outsourcing a task to a “marginal” crowd possessing e.g. less technical expertise related to the field (Jeppesen and Lakhani, 2010, Poetz and Schreier, 2012), which is seen to derive from the fact that solving complex problems requires heterogeneous capabilities (Afuah and Tucci, 2012). The technical marginality should not, however, be interpreted as if solving the problem required no domain-specific knowledge at all, but rather it is conditional on the self-selection of solvers to participate (Jeppesen and Lakhani, 2010). Firstly, in any case of complex problem solving the limited size of the crowd makes assessing the degree of know-how and its distribution among potential solvers a necessity. For instance, Brabham (2008) notes how users of cannot submit design ideas unless they have access to problem-specific skills and technologies, such as editing software and graphics, and knowledge of their use. How can the practicing managers assess the levels of crowd know-how, then? There are methods they can use to identify lead users from the crowd, such as a process based on netnography (Belz and Baumbach, 2010). Also social network visualization and analysis on the patterns of replies for each user in an event could be used to find different types of participants and evaluate their input, as demonstrated e.g. by Hutter et al. (2011) in their study of OSRAM LED crowdsourcing contest. Analogously, Liu et al. (2005) applied social network analysis to evaluate the impact of an individual author in a co-authorship network. However, such evaluation can only be conducted a posteriori. Thus it is best applicable in community-based modes of crowdsourcing where it is likely that the same users will engage in solving problems also in the future, whereas in contest-based modes the hosting organization relies on the above mentioned self-selection of most knowledgeable users. Secondly, the hosting organization needs to develop capabilities for the task/problem specification to avoid mismatch between the desired output and the crowd’s cognitive limits. According to a prior study by Zheng et al. (2011), it is desirable that crowdsourced tasks require a set of different skills, but are explicitly specified to reduce complexity and allure crowds to use their skills in a creative way. Like one of the hosts of Nokia’s IdeasProject described: “At times, we have had challenges [contests] with less ideas provided by the crowd. These have been moments of learning to us: the core things are, firstly,
  8. 8. This paper was presented at The XXIV ISPIM Conference – Innovating in Global Markets: Challenges for Sustainable Growth in Helsinki, Finland on 16-19 June 2013. The publication is available to ISPIM members at 8 finding the right community, and secondly, kind of having the right level of specifying what we are actually looking for. We had to be more accurate.” Thirdly, not only may the small amount of potential problem-solvers or their lack of domain-specific knowledge limit the applicability of crowdsourcing (Afuah and Tucci, 2012), but the ability to interpret the given problems also raises challenges. Novel solutions to problems may be difficult to propose when crowds pick only “the lowest hanging fruits” which are already widely available, or problem-solvers misinterpret the task due to tacitness and complexity of the knowledge involved (Cramton, 2001). One possible solution could be using “marginal” crowds also in problem design and definition phases (Jeppesen and Lakhani, 2010) – an act that has traditionally been assigned to firm managers and employees, but carries the risk that the problem is conceived differently than the problem holder originally intended. This holds particularly for contest-based crowdsourcing where there is less opportunity to interact around the problem after it has been designed, due to the cost of such interactions (Afuah and Tucci, 2012). For community-based crowdsourcing, a workable solution is to provide ongoing support for users’ interpretation of the tasks on the community site. To help solvers to outperform, the community may provide additional knowledge resources and feedback, which support taking a more detailed perspective into problem and providing a richer understanding of the knowledge domain in question. In this manner, the cognitive workload of users is eased and attention focused towards proposing more feasible solutions to problems (Kosonen et al., 2012b). Finally, the need to interact not only concerns the features of the problem itself as described above, but also the solutions to follow. This supports users in specifying their ideas further, reflecting back, and learning from each other (Hutter et al., 2011). Depending on the mode of crowdsourcing, user collaboration could be encouraged e.g. by targeting “sub-crowds” with a smaller amount of users all having specific domain knowledge and a specific problem to solve. These subgroups may eventually compete with each other to find a winning solution. At simplest, providing interactive features such as commenting may be enough to facilitate collaboration. Like one host of Nokia’s IdeasProject described idea development: “There are many examples of long discussions and comment threads. Building ideas on ideas has operated perfectly in this recent case [an idea competition around one specific product]. Thereafter, the original ideator adds ‘Hey, look at my idea, I’ve revised it, I’ve made it better based on your feedback’.” It is worth noting that while problem solving in this case was originally organized using the Tournament-based/competition mode, it functionally resembled the Collaboration- based/community mode. Such ‘hybrid’ form and interactions among dispersed problem- solvers allowed the hosting firm to harvest ideas of better quality. Hutter et al. (2011) refer to ‘communitition’ as a form of community-based collaboration among competing participants engaged in a crowdsourcing contest. On organizational and network levels, simultaneous competition and co-operation has been coined as co-opetition (Brandenburger and Nalebuff, 1996), reducing risks and cost associated with e.g. new product development. Hutter et al. (2011) come into the conclusion that the benefits of simultaneous collaboration and competition are high also on individual level, yielding the greatest potential for successful innovation outcomes in crowdsourcing. A certain crowd
  9. 9. may thus act both in competitive and cooperative manner even with the same task - or, simply put, one crowd involves both highly competitive and highly cooperative users and needs to be managed accordingly. While contributions differ in nature based on the role users take in the community, it is of particular importance 1) to identify communititors (i.e. users who most likely embody the necessary combination of co-opetitive behaviour) and 2) attract and reward communititors to take part in ideation and design (Hutter et al., 2011). In sum, the means to facilitate putting know-how into action are related to assessing the degree and distribution of crowd know-how, appropriate task/problem specification to avoid too broad or complex tasks, providing support for task interpretation, and encouraging collaboration in order to establish more high-quality solutions. Table 1 summarizes our findings. Table 1 Modes of organization-hosted crowdsourcing and their management practices Practices Contest mode Community mode Breeding motivation Provide stimulating tasks x x Give feedback on a timely basis x Encourage interaction x Reward appropriately material immaterial Build sense of community x Select the right communication technologies x x Putting know-how into action Assess the degree and distribution of know-how self-selection based on user data Specify tasks/problems on an appropriate level x x Support task interpretation beforehand on-going basis Encourage collaboration, support communititors x x 5 Discussion and conclusions Crowdsourcing has raised increasing debate among innovation management scholars and practitioners. For the hosting organization, its benefits seem two-fold: not only gaining more novel solutions to problems when compared to those deriving from employees or contractors (Poetz and Schreier, 2012, Jeppesen and Lakhani, 2010), but also increasing commitment and interest e.g. towards a firm’s product offerings by empowering users to take an active role in developing and modifying products (Nambisan and Baron, 2007, Füller et al., 2007). Hence, we asked how to best facilitate crowdsourcing and innovation-related problem solving among external crowds. As a result, we identified 10 practices that are likely to favour users’ motivation and putting know-how into action. Our study has implications within the emerging research on crowdsourcing, where most
  10. 10. This paper was presented at The XXIV ISPIM Conference – Innovating in Global Markets: Challenges for Sustainable Growth in Helsinki, Finland on 16-19 June 2013. The publication is available to ISPIM members at 10 studies so far have dealt on individual users’ level and neglected the hosting organization’s perspective. Firstly, our study contributes to innovation management literature by presenting a preliminary framework of the factors that support innovation-related problem solving among external crowds. We encourage future research establishing measures for the identified factors and testing their effect on the problem-solving outcomes within different types of crowdsourcing sites. Secondly, we contribute to the evolving discussion on crowdsourcing by outlining its different modes to be applied by hosting organizations: Tournament/contest-based, Collaboration/community-based, and hybrid, involving elements from both contest and community. To our knowledge, the simultaneous competition and collaboration in crowdsourcing has not been tackled in existing research except for the study by Hutter et al. (2011). Their study focused on individual users and their role in engaging in problem-solving tasks, thus lacking the hosting organization’s point of view, whereas we aimed at understanding how to facilitate participation in 1) contests and 2) communities. We welcome future research endeavours where each mode of crowdsourcing is studied more in detail. For instance, the suitability of contest-based, community-based and hybrid modes for solving different types of problems deserve further attention. For innovation managers, our study gives practical insight on how to cultivate the know-how and motivation of external crowds in organization-hosted crowdsourcing settings. Indeed, our results underline that facilitation is a task to be taken seriously in terms of internal resourcing and learning from experience, particularly when aiming at applying the community-based mode. We offered guidelines for organizations aiming to develop their management practices that support co-creative innovation processes among crowds. Our lenses were in managing crowdsourcing and also in evaluating its potential critically instead of focusing on the “hype” side of the phenomenon. As a limitation, it is noteworthy that we only outlined the managerial practices that concern the nature of crowds (Afuah and Tucci, 2012). The actual knowledge processes in creating new knowledge, developing an appropriate technical infrastructure, and evaluating the potential solutions remain important issues for further research in solving innovation-related problems with external crowds. For simplicity, we limited our investigation to the idea generation phase within the organization-user interface. In line with di Gangi and Wasko (2009) who studied the path of adopting innovations from a user community, we believe it is important for crowdsourcing researchers to gain more understanding on the process from original ideas into the market, while further examining the overall value of new ideas and designs suggested by voluntary crowds. References Afuah, A. & Tucci, C.L. (2012). Crowdsourcing As a Solution to Distant Search. Academy of Management Review, Vol. 37, No. 3, pp. 355-375. Antikainen, M., Mäkipää, M. & Ahonen, M. (2010). Motivating and supporting collaboration in open innovation. European Journal of Innovation Management, Vol. 13, No. 1, pp. 100-119.
  11. 11. Bagozzi, R.P. & Dholakia, U.M. (2006). Open Source Software User Communities: A Study of Participation in Linux User Groups. Management Science, Vol. 52, No. 7, pp. 1099-1115. Bandura, A. (1977). Social Learning Theory. Englewood Cliffs, NJ: Prentice Hall, 1977. Belz, F-M. & Baumbach, W. (2010). Netnography as a Method of Lead User Identification. Creativity and Innovation Management, Vol. 19, No. 3, pp. 304-313. Bock, G. & Kim, Y-G. (2002). Breaking the myth of rewards: An exploratory study of attitudes about knowledge sharing. Information Resources Management Journal, Vol. 15, No. 2, pp. 14-21. Boudreau, K.J. & Lakhani, K.R. (2013). Using the Crowd as an Innovation Partner. Harvard Business Review, April 2013, pp. 61-69. Brabham, D.C. (2008). Crowdsourcing as a Model for Problem Solving: An Introduction and Cases. Convergence: The International Journal of Research into New Media Technologies, Vol. 14, No. 1, pp. 75-90. Brabham, D.C. (2010). Moving the crowd at Threadless. Motivations for participation in a crowdsourcing application. Information, Communication & Society, Vol. 13, No. 8, pp. 1122-1145. Brandenburger, A. & Nalebuff, B. (1996). Co-opetition. New York, Doubleday/Currency. Chesbrough, H.W. (2003). Open Innovation: The New Imperative for Creating and Profiting from Technology. Harvard Business School Press, Boston. Cramton, C.D. (2001). The Mutual Knowledge Problem and Its Consequences for Dispersed Collaboration. Organization Science, Vol. 12, No. 3, pp. 346-371. di Gangi, P. & Wasko, M. (2009). Steal my idea! Organizational adoption of user innovations from a user innovation community: A case study of Dell IdeaStorm. Decision Support Systems, Vol. 48, pp. 303-312. Füller, J., Jawecki, G. & Mühlbacher, H. (2007). Innovation creation by online basketball communities. Journal of Business Research, Vol. 60, No. 1, pp. 60–71. Grant, A. (2012). Giving time, time after time: Work design and sustained employee participation in corporate volunteering. Academy of Management Review, Vol. 37, No. 4, pp. 503–523. Howe, J. (2008). Crowdsourcing: why the power of the crowd is driving the future of business. New York: Crown Business.
  12. 12. This paper was presented at The XXIV ISPIM Conference – Innovating in Global Markets: Challenges for Sustainable Growth in Helsinki, Finland on 16-19 June 2013. The publication is available to ISPIM members at 12 Hutter, K., Hautz, J., Füller, J., Mueller, J. & Matzler, K. (2011). Communitition: The Tension between Competition and Collaboration in Community-Based Design Contests. Creativity and Innovation Management, Vol. 20, No. 11, pp. 3-21. Jeppesen, L.B. & Lakhani, K.R. (2010). Marginality and Problem-Solving Effectiveness in Broadcast Search. Organization Science, Vol. 21, No. 5, pp. 1016-1033. Jeppesen, L.B. & Frederiksen, L. (2006). Why Do Users Contribute to Firm-Hosted User Communities? The Case of Computer-Controlled Music Instruments. Organization Science, Vol. 17, No. 1, pp. 45-63. Kosonen, M., Gan, C., Blomqvist, K. & Vanhala, M. (2012a). Users’ motivations and knowledge sharing in an online innovation community. ISPIM Barcelona, Spain, 17-20 June, 2012. Kosonen, M., Gan, C., Olander, H. & Blomqvist, K. (2012b). Supporting user-driven innovation activities in a crowdsourcing community. ISPIM Innovation Symposium, Seoul, Korea, 9-12 December, 2012. Lakhani, K., Jeppesen, L.B., Lohse, P.A. & Panetta, J.A. (2007). The Value of Openness in Scientific Problem Solving. Harvard Business School Working Paper, No. 07-050. Lee, G.K. & Cole, R.E. (2003). From a firm-based to a community-based model of knowledge creation: The case of the Linux kernel development. Organization Science, Vol. 14, No. 6, pp. 633-664. Leimeister, J.M., Huber, M., Bretschneider, U., & Kremar, H. (2009). Leveraging Crowdsourcing: Activation-Supporting Components for IT-Based Ideas Competition. Journal of Management Information Systems, Vol. 26, No. 1, pp. 197-224. Liu, X., Bollen, J., Nelson, M.L. & Sompel, H.V.D. (2005). Co-authorship networks in the digital library research community. Information Processing and Management, Vol. 41, No. 6, pp. 1462-80. Mahr, D. & Lievens, A. (2012). Virtual lead user communities: Drivers of knowledge creation for innovation. Research Policy, Vol. 41, No. 1, pp. 167-177. Nambisan, S. & Baron, R.A. (2007). Interactions in virtual customer environments: Implications for product support and customer relationship management. Journal of Interactive Marketing, Vol. 21, No. 2, pp. 42-62. Nickerson, J.A. & Zenger, T.R. (2004). A knowledge-based theory of the firm: The problem solving perspective. Organization Science, Vol. 15, No. 6, pp. 617-632. Poetz, M. & Schreier, M. (2012). The Value of Crowdsourcing: Can Users Really Compete with Professionals in Generating New Product Ideas? Journal of Product Innovation Management, Vol. 29, No. 2, pp. 245-256.
  13. 13. Porter, C.E. & Donthu, N. (2008). Cultivating Trust and Harvesting Value in Virtual Communities. Management Science, Vol. 54, No. 1, pp. 113-128. Santonen, T., Hossain, M. & Simula, H. (2012). An Evolutionary Network Analysis of Crowdsourcing Research Community. ISPIM Symposium, Seoul, Korea, 9-12 December, 2012. Sawhney, M. & Prandelli, E. (2000). Communities of creation: Managing distributed innovation in turbulent markets. California Management Review, Vol. 42, No. 4, pp. 24- 54. Schenk, E. & Guittard, C. (2009). Crowdsourcing: What can be Outsourced to the Crowd, and Why? Workshop on Open Source Innovation, Strasbourg, France. Tonteri, L., Kosonen, M., Ellonen, H. & Tarkiainen, A. (2011). Antecedents of an experienced sense of virtual community. Computers in Human Behavior, Vol. 27, pp. 2215-23. von Hippel, E. (1994). Sticky information and the locus of problem solving: Implications for innovation. Management Science, Vol. 40, pp. 429-439. Wasko, M.M. & Faraj, S. (2000). ’It is What One Does’: Why People Participate and Help Others in Electronic Communities of Practice. Journal of Strategic Information Systems, Vol. 9, Nos. 2-3, pp. 155-173. Wood, R.E. (1986). Task complexity: Definition of the construct. Organizational Behavior and Human Decision Processes, Vol. 37, pp. 60–82. Wu, S-C. & Fang, W. (2010). The effect of consumer-to-consumer interactions on idea generation in virtual brand community relationships. Technovation, Vol. 30, pp. 570-581. Xanthopulos, Z., Melachrinoudis, E. & Solomon, M.M. (2000). Interactive multi- objective group decision making with interval parameters. Management Science, Vol. 46, No. 12, pp. 1585–1601. Zheng, H., Li, D. & Hou, W. (2011). Task Design, Motivation, and Participation in Crowdsourcing Contests. International Journal of Electronic Commerce, Vol. 15, No. 4, pp. 57-88. Zwass, V. (2010). Co-creation: Toward a taxonomy and an integrated research perspective. International Journal of Electronic Commerce, Vol. 15, No. 1, pp. 11–48.