Open Innovation Communities Research Articles

User idea implementation in open innovation communities: Evidence from a new product development crowdsourcing community

AbstractIn collaborative crowdsourcing communities for open innovation, users generate and submit ideas as idea co‐creators. Firms then select and implement valuable ideas for new product development. Despite the popularity and success of these open innovation communities, relatively little is known about the factors that determine the implementation of the user‐generated ideas. Based on research on individual creativity, we propose a conceptual model integrating users' previous experience, idea presentation characteristics and feedback valence to explain the likelihood of idea implementation. We validate our research model with a panel data analysis of 43 550 ideas submitted by 16 360 users in the MIUI new product development community hosted by Xiaomi, a large electronics manufacturing company in China. We find an inverted U‐shaped relationship between users' past successful experience and idea implementation. Furthermore, the length of ideas is positively associated with the likelihood of idea implementation. There is also an inverted U‐shaped relationship between supporting evidence and idea implementation. Finally, we demonstrate the negative effect of positive feedback and the positive effect of negative feedback on idea implementation. These findings offer rich insights to understand the phenomenon of open innovation better. Theoretical and practical implications are discussed.

Breaking the Chains of Open Innovation: Post-Blockchain and the Case of Sensorica

Open innovation is a concept in flux; from the practice of large-scale, internet-mediated collaboration, to a strategic option and business model for firms. However, the scope and breadth of its transformative dynamic is arguably restrained. Despite the theoretical and empirical benefits of openness, established firms face significant challenges deploying the coordination patterns of open innovation communities, further reducing the potential of spill-overs in the supply chain. Viewed differently, open innovation presents more user-centric and responsible innovation paths. These are manifested in the processes and outputs of open innovation by empowering participation and by successfully employing the capacities of user communities. To reap the benefits of open innovation, a rapid reconfiguration of the production and exchange structures is needed in intrafirm and interfirm relations. Sensorica is an open enterprise that achieves such forms of organization and a unique techno-social infrastructure supporting them. It illustrates a potential path that can realize the full potential of open innovation, for users, firms, and the economic system as a whole.

Robustness of open source product innovation community’s knowledge collaboration network under the dynamic environment

As a complex system with open characteristics, the open source product innovation community is often subjected to failures and attacks, and the users in the community are often in a state of frequent change and mass loss. In this paper, we use complex network analysis techniques to describe the complex system as a knowledge collaboration network. We discuss how the network’s structural robustness and functional robustness changes during the three stages of network development (i.e. the start-up, growth and maturation stages) for different user loss patterns (i.e. one random user loss pattern and two deliberate user loss patterns) under the dynamic environment. We find that the structural robustness is significantly higher when the network faces random user loss than when it faces deliberate user loss for all three network development stages. In contrast, the functional robustness is higher when the network faces random user loss than when it faces deliberate user loss only for the network’s start-up stage, not its growth and maturation stages. Based on the robustness results, we provide intervention and incentive strategies to prevent user loss for all three stages of an open source product innovation community’s network development. More importantly, we contribute a new approach for systematically analyzing the robustness of the open source product innovation community under the dynamic reality environment.

Impact of Open Innovation Communities on Enterprise Innovation Performance: A System Dynamics Perspective

Open innovation communities (OICs) can help enterprises make full use of external knowledge resources from users, but problems such as low user participation and low conversion rate of creative ideas impact the efficiency of OICs. Most studies on this topic employ qualitative or empirical methods from a static perspective, but ignore the effect of interaction between enterprises and users as well as the cumulative effect of time. A discussion on the dynamic evolution process of open innovation is lacking. Based on a review of the literature on OICs, innovation performance, and system dynamics, this study proposes a conceptual model of innovation performance impact, which comprises the knowledge management, governance mechanism, and user behavior subsystems. Xiaomi’s OIC in China was selected as the research object, and relevant data were collected through a web spider. According to the system dynamics modeling method, a causal relationship analysis was carried out on the three aforementioned interrelated subsystems. Then, a stock flow chart with 32 variables was constructed to determine the initial values and calculation equations for each variable. Finally, the model was constructed and verified using Vensim PLE software. The simulation results were as follows. (1) The number of product releases in the Xiaomi OIC was positively correlated with the number of posts, comments, and views. Compared with user interaction behavior (i.e., commenting and viewing), the impact of user innovation behavior (i.e., posting) on enterprise innovation performance (i.e., number of patents) is clearer. Specifically, regarding interaction behavior, the impact of the users’ commenting behavior on innovation performance (i.e., number of product releases) was relatively clearer than that of their viewing behavior. (2) Governance mechanism (i.e., R&D investment and management expense), which comprises technical and organizational mechanisms, positively affected the innovation performance of enterprises. Compared with the organizational mechanism (i.e., management expense), the impact of the technical mechanism (i.e., R&D investment) on the innovation performance was clearer. (3) Governance mechanism helped to increase the number of users in the OIC, and, in turn, affected the user innovation and interaction behavior. (4) The technical mechanism positively affected knowledge application capability, which, in turn, had a positive impact on the innovation performance of enterprises. Based on these findings, management strategies are proposed for the establishment and development of OICs.

The Impact of Open Innovation Community on Enterprise Innovation Performance

The Impact of Open Innovation Community on Enterprise Innovation Performance

Identification of the unique attributes and topics within Smart Things Open Innovation Communities

One of the main challenges of open innovation communities is how to create value from shared content either by selecting those ideas that are worthy of pursuit and implementation or by identifying the users' preferences and needs. These tasks can be done manually when there is an overseeable amount of content or by using computational tools when there are massive amounts of data. However, previous studies on text mining have not dealt with the identification of unique attributes, which can be defined as those contributions that are inextricably linked with a specific tag or category within open innovation websites. The uniqueness of these ideas means that they can only be obtained through a selection of one choice among several alternatives. To obtain such unique ideas and thus to also obtain innovations, this paper proposes a novel methodology called co-occurrence differential analysis. The proposed methodology combines traditional co-occurrence analysis with additional statistical processing to obtain the unique attributes and topics associated with different alternatives. The identification of unique content provides valuable information that can reveal the strengths and weaknesses of several options in a comparative fashion.

Selecting an open innovation community as an alliance partner: Looking for healthy communities and ecosystems

Organizations build strategic alliances with other firms with the intent of tapping into partners’ resources and capturing long-term value from these relationships. Such partnerships are typically governed by contractual or equity arrangements with clear mutual obligations. More recently, however, organizations have begun to seek strategic partnerships with open innovation communities, which are novel digitally enabled forms of organizing, and where contractual commitments are not possible. Thus, selecting the right open innovation community as an alliance partner becomes a more complex decision. We follow how the organizational decision makers, in two technology firms that were pioneers of forming strategic alliances with open innovation communities, developed metrics around making such decisions. We build upon Shah and Swaminathan’s (2008) contingency model of alliance partner selection and consider how it applies to the case of partnering with open innovation communities. This framework was useful in to frame our findings, yet our work recognizes and builds upon two key differences: 1) the evaluation metrics used in selecting an open innovation community were more focused on value creation than value capture; and 2) open ecosystem considerations, and not just partner-specific metrics, featured prominently in this type of alliance partner evaluation. We develop the notions of community and ecosystem health to refer to these new metrics.

Identifying Useful Information from Open Innovation Community

Identifying Useful Information from Open Innovation Community

Write Code, Save Lives: How a Community Uses Open Innovation to Address a Societal Challenge

This study explores how a community uses open innovation over time to tackle a global societal challenge. we conduct an in‐depth case study of OpenMRS, an open‐source software community providing affordable medical record‐keeping software in developing nations. We develop a process model that describes how inbound, outbound, and coupled open innovation influenced the community through four discrete phases of community development. We explain how the founders’ vision led to the creation of the community, and how increasing community participation and community governance facilitated its growth. Interestingly, we found that economic opportunities made possible by open innovation may paradoxically create challenges to community sustainability. Ultimately, this study expands our understanding of open innovation communities in different settings, and their role in addressing societal challenges.

A System Dynamics Model for Open Innovation Community

In order to promote the development speed of the open innovation community, a dynamical system model of it is constructed, and the simulation is carried out to find out the rules of the running rules for the open innovation community. First, the basic characteristics of open innovation community are summarized. Second, the system dynamics model of open innovation community is constructed. Finally, the simulation analysis based on dynamic system model of the open innovation community is carried out, and the effect of different factors on the variables of the open innovation community is obtained. Results show that system dynamics is an effective tool for analyzing the open innovation community.

Complexity as an Antecedent for External Collaboration in New Product Development Projects

This study examines how project complexity in low technology-intensive small- and medium-sized enterprises (SMEs) contribute in implementation of open innovation practices, during their new product development projects. The main focus of this paper is to investigate the critical role of complexity in the project level to identifying the compatibility of those external sources involved in NPD. The low technology-intensive sector in Spain were chosen as a target context, there were many innovative SMEs operating in these industries and because these sectors were going through significant changes. Four external knowledge sources, Universities, suppliers, customers and competitors and four open innovation practices, Community, Platform, Partnership and seller-buyer agreement, in the new product development were identified. The study shows that in SMEs, project complexity plays an important role in selecting the external source and implementation of open innovation practices. The main conclusion of the study is that the external collaboration in new product development projects is determined by different dimensions of project complexities and in projects with different type of complexity, the SMEs follow different external knowledge sources and open innovation practices. The study results imply that SMEs benefit from opening up their innovation process in the new product development projects. The firms in this study employed a blend of strategies that is more compatible with dimensions of project complexity. They collaborated actively with different external knowledge source and different modes of collaboration, when they have determination of different dimensions of project complexity. Also, the study extends understanding of the strategic use of open innovation in SMEs by demonstrating how SMEs balance the risk of project complexity built on new product development and the benefit of creating a wider capability base with partnerships.

Recommending valuable ideas in an open innovation community

PurposeOpen innovation communities are a growing trend across diverse industries because they provide opportunities of collaborating with customers and exploiting their knowledge effectively. Although open innovation communities can be strategic assets that can help firms innovate, firms nonetheless face the challenge of information overload incurred due to the characteristic of the community. The purpose of this paper is to mitigate the problem of information overload in an open innovation environment.Design/methodology/approachThis study chose MyStarbucksIdea.com (MSI) as a target open innovation community in which customers share their ideas. The authors analyzed a large data set collected from MSI utilizing text mining techniques including TF-IDF and sentiment analysis, while considering both term and non-term features of the data set. Those features were used to develop classification models to calculate the adoption probability of each idea.FindingsThe results showed that term and non-term features play important roles in predicting the adoptability of ideas and the best classification accuracy was achieved by the hybrid classification models. In most cases, the precisions of classification models decreased as the number of recommendations increased, while the models’ recalls and F1s increased.Originality/valueThis research dealt with the problem of information overload in an open innovation context. A large amount of customer opinions from an innovation community were examined and a recommendation system to mitigate the problem was proposed. Using the proposed system, the firm can get recommendations for ideas that could be valuable for its business innovation in the idea generation phase, thereby resolving the information overload and enhancing the effectiveness of open innovation.

Customer-favourable idea versus company-adoptable idea: comparative analysis through elaboration likelihood model

Recent years have witnessed the growing trend of open innovation, and participating customers have become an important source of innovation for companies. The effectiveness of this open approach remains a matter of controversy, however. We examine the value of customer ideation in a coffee brand community by employing the ideas posted by community members and investigating whether they are customer-favourable and/or company-adoptable. Using the elaboration-likelihood model (ELM) that explains the factors for persuasion, we propose several hypotheses on how the content/contextual factors of ideas relate to both customer favourableness and company adoption. The hypothesis tests, via ordinary least-squares and binomial logistic regression models, show that customer-favourable ideas have a positive but marginal effect on company adoption, while the antecedents of customer favourableness differ from those of company adoption. We also confirm that peer engagement has a moderating effect on the relationship between idea content factors and company favourableness. This study offers theoretical implications by extending the ELM research stream and also provides managerial implications that can lead to a more effective exploitation of open innovation communities.

Endogenous growth of open collaborative innovation communities: a supply-side perspective

This article analyzes the conditions under which open collaborative innovation communities can be generated and are able to grow and prosper in the long run. We build a formal model of the interaction between such communities and the alternative institutional setting based on intellectual property rights that we call Technology. The model accounts for both the communitarian social process taking place inside the community and for the presence of spillovers both across and within each institution. We prove that communities grow endogenously above a certain size threshold, and that such growth depends on supply-side mechanisms centered on the developers’ social motivations and interactions. In a comparative statics analysis, we show that the community’s innovative performance rests not only on its own characteristics (strength of social motivations and/or of protection of the community-produced knowledge) but also on factors outside its scope, namely, the institutional characteristics of Technology. We discuss the managerial and policy implications of our findings.

The Impact of Release Management on Open-Source Software Co-Creation

The open-source software (OSS) production model has been gaining ground and even expanding to a broader class of products. A central virtue of OSS is co-creation through contributions and feedback from the user community, yet our knowledge of how to coordinate and maximize the benefit of such co-creation for market success is limited. In this paper, we propose that deliberate product release timing can be an important capability to orchestrate open source community contributions and maximize their benefit. We develop, formalize, and estimate a dynamic structural model to study the impact of product release management as a coordinating mechanism in peer production. We find that a deliberate and moderate release frequency, contingent on the installed base of the project, its quality enhancement, and the license type of the software, contributes to project success. Our results show that it would be optimal for early-stage projects to release more often. As the installed base increases, it is beneficial to release less often. We also find that there exists a curvilinear (inverse-U) relationship between the release frequency and the community contributions. Hence, excessive releasing may risk exhausting the community. Furthermore, even though the project may benefit from a new release, there also exists a release cost. The OSS team then has to balance between the two by carefully managing the release pace. We also find that projects with different license types may have different optimal release timing. These results may have important implications for managing technology-enabled, crowd-based collaboration in open innovation communities beyond open-source software development, launch, and adoption.

Engaging in knowledge exchange: The instrumental psychological ownership in open innovation communities

Online communities have become a vital channel for professionals to expand their networks and initiate new strategic collaborations. Such online behaviors have led to multiple types of innovation potential that are based on the co-creation of ideas toward new solutions. Yet, very little is known about the role of psychological ownership of knowledge in professionals’ knowledge exchange in these communities that are based on voluntary contributions. We apply the psychological ownership theory and posit that psychological ownership of knowledge is instrumental to increased knowledge exchange intentions of professionals. Informed by the theory, our model incorporates several enablers of online engagement which could be associated with psychological ownership. Our exploratory quantitative study evidences that perceived ownership of knowledge plays a critical instrumental role in idea exchange behavior. We evidence how personal outcome expectations, organizational innovativeness and affective community commitment are associated with psychological ownership of knowledge which is an important predictor of intentions to exchange knowledge in open innovation communities. Implications for theory and practice are discussed.

Identification of innovation solvers in open innovation communities using swarm intelligence

Open innovation communities represent an effective strategy to provide organizations with a wider range of ideas, reducing the costs associated to R&D. Its main problem is the large volume of information generated in the form of proposed innovations that should be internally processed and executed by employed experts. The purpose of this work consists of identifying the profiles of the so-called innovation solvers using only their participation characteristics extracted from open innovation communities, which are modelled as social networks, and applying particle swarm optimization. Findings can improve the absorptive capacity of organizations by focusing on those users with more chances of generating potentially adoptable ideas.

Who creates value in a user innovation community? A case study of MyStarbucksIdea.com

Purpose – Successful open innovation requires that many ideas be posted by a number of users and that the posted ideas be evaluated to find ideas of high quality. As such, successful open innovation community would have inherently information overload problem. The purpose of this paper is to mitigate the information problem by identifying potential idea launchers, so that they can pay attention to their ideas. Design/methodology/approach – This research chose MyStarbucksIdea.com as a target innovation community where users freely share their ideas and comments. We extracted basic features from idea, comment and user information and added further features obtained from sentiment analysis on ideas and comments. Those features are used to develop classification models to identify potential idea launchers, using data mining techniques such as artificial neural network, decision tree and Bayesian network. Findings – The results show that the number of ideas posted and the number of comments posted are the most significant among the features. And most of comment-related sentiment features found to be meaningful, while most of idea-related sentiment features are not in the prediction of idea launchers. In addition, this study show classification rules for the identification of potential idea launchers. Originality/value – This study dealt with information overload problem in an open innovation context. A large volume of textual customer contents from an innovation community were examined and classification models to mitigate the problem were proposed using sentiment analysis and data mining techniques. Experimental results show that the proposed classification models can help the firm identify potential idea launchers for its efficient business innovation.

Role of transitory communities of practice in business school collaborative knowledge-sharing projects: from the partner's perspective

This paper explores the essential roles that academics, graduates/post-graduates and small enterprise owner-managers play when working together on knowledge-sharing projects. The study uses six projects to explore the life cycle of these transitory communities of practice (CoP) and how they can provide an effective means for sharing knowledge and expertise. This investigation is significant as such sharing of knowledge and expertise is the basis of the increasingly informal knowledge management structures such as networks and open innovation communities. How this is achieved, we suggest is based on two factors: the stakeholders and the transitory CoPs. The stakeholders are the SME managers, academics and newly employed graduates (associates), who co-create value by capturing, analysing and disseminating new-to-enterprise knowledge and experience. They achieve this via temporary CoPs which have their own life cycle of creation, growth and maturity/destruction.

Open innovations, innovation communities and firm's innovative activities

The open innovation paradigm emphasizes the fact that firms can improve their performance by opening their business models and reduce their R&D costs by effective incorporation of external knowledge. In other words, companies are able to capture value through knowledge that exists outside the boundaries of their organization. The shift from closed to open model of innovation has imposed the necessity to adopt more open approach to innovation within traditional academic view of business strategy. The adoption of this innovative approach is emphasized even more, by the necessity for stronger connection and cooperation among the participants of the innovation process. Free will and collaboration are the main characteristics of open source software, which is recognized in literature as the role model of open innovation and is a rapidly growing method of technology development. Furthermore, innovative communities represent a great opportunity for improvement of the companies' innovation activities, since they have become an important source for identifying the needs and problems of the users. Their development has been fostered by information technologies and recent social changes in user behavior. Recognizing and better understanding the motivation of the members of the innovation communities that guide them to participate in the process of idea generation, can have significant influence on their incorporation within the innovation process. Equally important is to define the incentives that are suited for stimulating and fostering innovative user activities. Taking this topic in consideration, the purpose of this article is to address the following questions: In what way does the collaboration in open source software projects have positive effect on companies' innovation performance? What are the innovation communities and how can companies establish successful interaction with them? Why does the interaction with innovation communities lead to improvements of innovation process? What motivates the members of innovation communities to participate in creating the innovation? What are adequate incentives for stimulating user innovation activities?.