Online Innovation Communities Research Articles

From mindset to market: unveiling the nexus of cognition, behavior and environment in igniting students’ E-entrepreneurial intentions

PurposeIndia has witnessed a significant surge in internet users in recent years, creating an ideal environment for E-entrepreneurship. With the rise of E-commerce and the growth of the digital economy, there is tremendous potential for online businesses in developing nations. Our study outlines the behavioral, cognitive, and environmental aspects shaping students' E-entrepreneurial intentions (EEI).Design/methodology/approachOur study incorporated structural equation modeling (SEM), social cognitive theory (SCT), and entrepreneurial event model (EEM) to evaluate the EEI of 460 students from India's top five engineering institutes. The direct and indirect linkages in the model were examined by employing mediation and moderation analysis.FindingsOur findings reveal that behavioral, environmental, and cognitive factors facilitate evaluating feasibility, further igniting students' EEI. The cognitive factors and E-entrepreneurial feasibility (EEF) mediate the relationship between the underlying constructs. Furthermore, financial resource availability (FRA) strengthens, and loss aversion bias(LAB) weakens the linkage between EEF and EEM.Research limitations/implicationsThe study's findings may benefit online innovation communities, potential technopreneurs, financial institutions, and policymakers in improving the entrepreneurial ecosystem.Originality/valueThe study integrates psychological and sociological perspectives to understand the key facilitators of EEF and EEI. The study combines SCT and the EEM by appending crucial constructs such as FRA and LAB to broaden the horizons of EEI.

How does the online innovation community climate affect the user's value co-creation behavior: The mediating role of motivation.

Online Innovation Community (OIC) serves as a virtual space for users to exchange products and services, and share knowledge and information. Previous studies have indicated that community climate is an important factor affecting users' value co-creation behavior, however, the influencing process has not been clearly revealed from the perspective of motivation. In this study, we explored the relationship between online innovation community climate (supportive climate and controlling climate), user motivation and value co-creation behavior (user's participation behavior and user's citizenship behavior) based on the SOR model. The study sample included 29,835 pieces of information from 3,315 users in 14 product sections of the OnePlus Community which were analyzed with Mplus8.1. The findings revealed that: (1) The supportive climate had a positive impact on user's citizenship behavior(β = 0.042), while the controlling climate exerted a significant positive impact on user's citizenship behavior (β = 0.078) and user's participation behavior(β = 0.099); (2) The need for achievement played a suppressing effect between community climate and user's participation behavior, the need for power played a suppressing effect between supportive climate and user's value co-creation behavior, and the need for affiliation played a mediating role between supportive climate and user's citizenship behavior (β = 0.010) and user's participation behavior(β = 0.006); (3) Community trust positively moderated the relationship between the need for achievement and user's participation behavior(β = 0.058) as well as between the need for power and user's participation behavior(β = 0.043).

Focus on yourself: The impact of users' self-focus orientation on NPD ideas' attention allocation in online innovation communities

When users write up and post their new product development (NPD) ideas online, they differ in their self-focus orientation—meaning the extent to which they choose to focus on themselves in their posts, such as whether they include personal pronouns like “I” and “me.” However, the impact of this linguistic style choice on the attention allocated by company employees to users' NPD ideas is unknown. This study examines the role of users' self-focus orientation in shaping the NPD ideas' attention allocation of company employees in the context of online innovation communities. Drawing upon motivated information processing theory, we develop a theoretical model positing that online users' self-focus orientation influences the NPD ideas' attention allocation of company employees and that the effect of users' self-focus orientation on NPD ideas' attention allocation is contingent on various online community characteristics, including online community crowdedness and online community interaction. Analyzing 647,224 NPD ideas collected from one online innovation community, we show that users' self-focus orientation has a positive effect on NPD ideas' attention allocation. We also find that the positive effect of users' self-focus orientation on NPD ideas' attention allocation is made weaker when community crowdedness is high and that it is made stronger when community interaction is high. These results reveal two important underlying, context-specific boundary conditions. The study also challenges the predominant view in the social psychology literature regarding the negative impact of self-focus. Overall, this research sheds new light on how and when users' self-focus orientation in online innovation communities affects employees' attention allocation to NPD ideas beyond the impact of the actual content of the posted ideas. Additionally, we discuss how users can attract the attention of company employees so that the employees will focus on their NPD ideas, and we offer suggestions to community managers to realize the full potential of their online innovation communities.

Identifying Valuable Knowledge Topics in Innovation Communities Using Innovation-LDA

<p>Researchers and practitioners have recognized that user-generated content in the innovation community plays an important role. However, it is challenging to automatically identify valuable knowledge from these unstructured texts. Thus, in this study, we propose an efficient model for extracting innovation-oriented topics and, simultaneously, for assigning discovered topics to each post in the online innovation community. Specifically, we introduce a variant of the latent Dirichlet allocation (LDA) topic model, called the Innovation-LDA model, which comprehensively considers users’ interests (reflected by pageviews and replies) and the structure of threads (e.g., header or body) to generate the valuable topics. We access the quality of discovered information through statistical fit as well as substantive fit. Based on our experimental results, we can conclude that our proposed method exhibits better performance than that of the contrasted method and can locate more meaningful innovation topics; that is, our innovation-LDA model is capable of not only identifying more rigorous topics for each thread by utilizing the text structure but is also capable of learning more semantic and coherent themes from user interests. This investigation expands topic identification research by providing both a new theoretical perspective and useful guidance for enterprises in product innovation.</p> <p> </p>

User Interaction Within Online Innovation Communities

In the digital era, enterprises have established online innovation communities to attract customers to participate. Presented in this study is user interactions within these communities using social network analysis. By identifying distinct subgroups within the network and comparing the user interactions among these subgroups, this research aims to identify the group diversity of online interactions. The findings indicate that dialogists are more willing to interact and hold a favorable network position, followed by questioners, while answerers have the lowest level of interaction. User subgroups are identified using k-core analysis. The higher the value of the core k, the more interactions between users in the k-core subgroup and the better the network position. By combining both ego-centered and group dimensions of online interaction characteristics, this paper also outlines an investigation into an empirical study on the influence of user interactions on community recognition. The results confirm heterogeneous effects among different subgroups.

How peer feedback affects knowledge contribution in online innovation communities: a social identity perspective

PurposeThe research aims to explore the influence mechanism of peer feedback and users' knowledge contribution behavior. This study draws on the social identity theory and considers social identity as a mediating factor into the research framework.Design/methodology/approachThis paper collected users' activity data of 142,191 ideas submitted by 76,647 users from the MIUI community between October 2010 and May 2018 via Python software, and data were processed using Stata 16.0.FindingsThe results indicate that knowledge feedback and social feedback positively influence users' knowledge contribution (quantity and quality), respectively. User's cognitive identity positively mediates the relationship between peer feedback and knowledge contribution behavior, affective identity positively mediates the relationship between peer feedback and knowledge contribution behavior, while evaluative identity positively mediates the relationship between peer feedback and knowledge contribution quality, but there is no mediating effect between peer feedback and knowledge contribution quantity.Originality/valueThis study advances knowledge management by highlighting peer feedback on online innovation communities. By demonstrating the significant mediating effect of social identity, this study empirically clarifies the relationships of peer feedback (knowledge feedback and social feedback) to specific dimensions of knowledge contribution, thereby providing managerial guidance to the online innovation community on incentivizing and managing user interaction to foster the innovation development of firms.

Novelty and the Structure of Design Landscapes: A Relational View of Online Innovation Communities

Design artifacts in online innovation communities are increasingly becoming a primary source of innovation for organizations. A distinguishing feature of such communities is that they are organized around design artifacts, not around people. The search for novel innovations thus equates to a search for novel designs. This is not a trivial problem since the novelty of a design is a function of its relationship to other designs, and this relationship changes as each design is added. These relations between artifacts affect both consumption and production. Moreover, these relations form a landscape whose structure affects the emergence of novelty. We find evidence for our theorizing using an analysis of over 35,000 Thingiverse design artifacts. This work identifies the differential effects of different forms of novelty, visual and verbal, on subsequent innovation, and identifies the differential effects of different degrees of structure in the landscape on novelty.

How Value Homophily Between Ideators and Commenter Influences Ideators’ Subsequent Online Engagement

This study examines the motivation of user engagement in online innovation communities from a new perspective of the value homophily between the ideators and commenters instead of focusing on the interaction behavior as past research did. Specifically, this study highlights how value homophily inferred from ideators and commenters’ shared knowledge background in the online community assists them to identify credible learning sources and learn from them and how this process influences their further engagement behavior. We propose that value homophily between ideators and commenters implies that the commenter is a credible learning source, which effectively promotes the ideator to absorb and integrate the focal comment into subsequent engagement behaviors. Besides, this study further examines the moderation effect of past experience of public recognition and failure. The findings suggest that ideators’ past failures like low social support positively moderate the main effects by adjusting the ideator’s perception of the credibility of the commenter resulting in an increasing salience of value homophily between them. While commenters’ past recognition will not strengthen the main effect if they share no knowledge background with the ideators. Using a sample of 168074 observations from an online innovation community from 2011 to 2020, the findings support our theoretical predictions.

Identifying contributory domain experts in online innovation communities

Identifying contributory domain experts in online innovation communities

They didn't ask: Online innovation communities as a latent dynamic capability

Many contemporary video games demand considerable involvement from players, but in general, researchers have not considered such contributions as an innovation activity. To address the nature of gamer contribution, we conducted a longitudinal qualitative case study of the community surrounding the EVE Online video game. We employed grounded theory to investigate how the role played by community members changes over time, which influences their contribution to the innovation process. A dynamic classification model that highlights patterns of innovation contributions by different subgroups of the community emerged from this investigation. The findings were further analyzed utilizing Hirschman's theoretical framework, which was integrated with research on innovation communities. The results indicate that when properly activated, gamer communities can function as online innovation communities capable of contributing not only to product development but also to co-creation and strategy processes, constituting an external dynamic capability. This paper contributes to the literature concerning innovation communities and the dynamic capabilities of companies. Such insights also have practical implications because identifying different subgroups within communities is of strategic importance for companies, assisting managers in targeting segments of the community that could contribute more to the innovation process, as well as to other business operations.

Promoting product idea contribution of heterogeneous users for product improvement in online innovation communities

ABSTRACT Collaboration between firms and product users has been widely practiced to enhance the efficiency and quality of product development. We consider a collaborative product improvement setting where a sponsoring firm and product users jointly create or promote product design ideas through firm-sponsored online user innovation communities (FOUICs). Using a differential-game framework, we study a benchmark case in which product users involved in FOUICs are homogeneous in their innovative contribution capacities and propensities. We then incorporate users’ heterogeneity such that product users are distinguished into lead users and common users. Our analytical result shows that the equilibrium effort levels and utilities of both the sponsoring firm and product users may increase or decrease with a change in the output elasticities of product design ideas or in the cost elasticities of the effort levels. Moreover, lead users’ equilibrium effort level and utility are more sensitive to the elasticity parameters of product users’ effort than those of common users, and lead users obtain a higher total incentive reward than that of common users. Last, we compare the benchmark model and the extended model to identify the condition under which one model outperforms the other one for both the sponsoring firm and product users.

Knowledge Topic-Structure Exploration for Online Innovative Knowledge Acquisition

Researchers and practitioners have long realized the importance of acquiring innovative knowledge from online innovation communities. However, it has still been a challenge to identify valuable information of interest from unstructured and noisy user-generated text. The extant research trying to solve this problem is limited by the generalizability issue and the lack of topic-level investigation. In this article, we proposed an automatic hybrid model to simultaneously extract knowledge topics and knowledge structures from free text in online innovation communities. By employing a topic model, one important contribution of this article is the elimination of manual intervention and addressing of the generalizability issue faced by existing supervised approaches. Another major contribution of this article is the design of a novel solution for knowledge structure construction by combining a topic model with association analysis; this solution addresses the weakness of the traditional topic model. We evaluate the validity of the proposed hybrid model in experiments with a real-world dataset. The results show that by providing a new angle for innovative knowledge acquisition and management, this proposed method is effective in extracting meaningful innovative knowledge and in uncovering knowledge structures.

Disentangling the collective motivations for user innovation in a 3D printing community

Online innovation communities encourage innovators to build upon others' prior work (i.e., remixing). This generative user innovation necessitates new theorization to better understand the interplay between characteristics of the source innovation and the community's collective motivation. Motivation is a heightened concern in online communities where contributors often select which problems warrant their effort. Two studies improve our understanding of how the community's motivations compel remixing and impact two aspects of the depth of these remixes (improvement and differentness). First, hypotheses regarding the community's collective remix response are developed and tested. After this, an exploratory (fsQCA) study seeks out configurations of these motivations that consistently result in improved and different remixes. Using data from thingiverse.com, we show that established motivations for user innovation (enjoyment, learning, use-value) motivate remixing, but learning and use-value's effects are moderated by source innovation quality. Learning and use-value are only impactful for high quality source objects. We also demonstrate that originality of the source object has an inverted-U relationship with remixing; innovations need to be novel, but not drastically different from expectations to generate a remix response from the community.

Exploring the Impact of Crowd Members’ Motivation on Idea Quality in Online Innovation Communities

Since many years, several firms host Virtual Idea Communities (VIC), in which the crowd focuses on voluntarily developing ideas for new product development (NPD). Both, scholars and practitioners share a strong interest in understanding the factors that enhance crowd members’ individual ideation outcome, meaning the quality of ideas, since the value of user ideas is not only essential for the survival of a VIC, but it also directly affects the innovation effects of firm’s NPD. Although there exist first insights on what influences idea quality, empirical studies that provide evidence of which forms of crowd members motivations are positively linked to higher ideation outcome are neglected. In this research, we build a theoretical model explaining which motives of crowd members for engaging in ideation have a positive impact on the quality of ideas they developed. To test our theory, we employed empirical data from users of the VIC by the software manufacturer SAP. For the first time, we found that crowd members of VIC are motivated to send capability signals through their ideas and thus be more creative. Further, crowd members with higher levels of fun and learning motivation produce ideas of higher quality, whereas this association depends on their level of flow experience. Our empirical results provide important contributions to IS research and practice. On the basis of our findings it is possible to design socio-technical artefacts for VICs that stimulate users’ capability-, fun- and learning motives and in turn will lead to ideas of higher quality.

How creative versus technical constraints affect exploring a design space

The creative design process can be conceptualized as the repeated search for highly-evaluated novel solutions within a design space of possibilities. Such design spaces are bounded by creative constraints of what are considered appropriate solutions as well as technical constraints of what solutions are possible given the tools in place. Past research on the role of constraints in creative design and innovation have found mixed results, hindered in part by not separating out the type of constraint—creative versus technical—and in part by focusing on singular projects that neglect the learning effects of repeated exploration of a design space. We analyzed ten years of data from an online innovation community hosting repeated creative design competitions, and we examined how creative and technical constraints in a design space affected how individuals learned to improve their performance as evaluated by their audience. We find that creative constraints lead to high rates of learning only if technical constraints are sufficiently relaxed. Our findings have implications for the management of creative design work in both online and offline settings.

The 3D printing revolution is here? The impact of 3D printing on managers and the innovation process

Three-dimensional printing is widely used across industries and has led to substantial technological, organizational, institutional and societal changes worldwide. Because 3D printing is fundamentally reshaping the ways in which innovation-related knowledge is combined, shared, designed and implemented, this digital technology is challenging existing organizational logics, occupations as well as innovation and entrepreneurial processes. Our interdisciplinary symposium, organized by three scholars from New York University, Ivey Business School and the Lawrence N. Field Center for Entrepreneurship, Baruch College, aims to shed light on the impact of 3D printing for theory and practice. We include four scholars to share their insights from their research that investigates 3D printing as a research context within and outside organizations and discuss the implications of their studies for the field of innovation, management, information systems, strategy, and entrepreneurship. Minimal and Adaptive Coordination: How Hackathons’ Projects Accelerate Innovation without Killing it Presenter: Hila Lifshitz-Assaf; New York U. The role of pre-innovation platform activity for diffusion success: Presenter: Maria Anna Halbinger; City U. of New York, Baruch College Product architecture as a strategic variable: The impact of digital technologies on the organization Presenter: Stefano Brusoni; ETH Zürich How Generative Technologies Govern Online Innovation Communities Presenter: Harris Kyriakou; IESE Business School Presenter: Ann Majchrzak; U. of Southern California Presenter: Jonathan D. Wareham; ESADE

Leadership in innovation communities: The impact of transformational leadership language on member participation

AbstractMany organizations seek to establish online innovation communities (ICs) to obtain valuable knowledge and innovative ideas, though both research and practice suggest that they also struggle to sustain continued, high‐quality member participation. Designated IC moderators might be able to stimulate IC members to participate regularly and make high‐quality contributions. In response to calls to integrate organizational behavior and IC research, this study addresses the impact of community moderators’ uses of transformational leadership (TFL) language on member participation. By operationalizing the TFL dimensions—charisma, individualized consideration, and intellectual stimulation—with language cues, this article uses an automated text analysis approach to review 64 firm‐hosted ICs with 538,805 posts, analyzed with two hierarchical linear models. The findings show that moderators’ charismatic language cues enhance members’ participation quality and quantity. Although individualized consideration and intellectual stimulation increase participation quality, they decrease participation quantity. Organizations thus should assign moderators to lead ICs by using TFL language strategically, in accordance with the focal IC goals, in terms of the quality and quantity of member contributions to their innovation processes. This article contributes to the literature by exploring how leadership language in online communities can facilitate the development of innovative ideas. In addition, this study offers a more nuanced view on the effects of TFL by revealing both positive and negative outcomes in firm‐hosted online ICs and it introduces a new, objective measure of TFL built on linguistic markers. This article also includes specific guidelines for how moderators can achieve effective leadership through their language use, as well as managerial implications for the effective selection, training, and support of IC moderators.

Examining the antecedents of idea contribution in online innovation communities: A perspective of creative self-efficacy

In recent decades, firms have increasingly utilized online innovation communities to facilitate product development and improvement by encouraging users' product idea submission. An emerging research stream examines the driver of users' idea contributions. The present study explores the impact of peer feedback on the basis of creative self-efficacy theory, sponsoring firm feedback, direct mastery experiences, and social learning on idea contribution. Using data from 13,116 users of MIUI Forum, our empirical results show that peer feedback and sponsoring firm feedback are positively related to the quantity and quality of users' ideas. Although social learning positively affects the number of user's ideas, it is negatively associated with idea quality. Direct mastery experiences have no significant effect on idea quantity but reduce idea quality. The negative impact of direct mastery experiences on idea quality is stronger with users' higher membership status. These findings offer significant implications for online innovation community management.

Technology Forecasting Based on Topic Identification of Online Innovation Communities and S-Curve

Technology Forecasting Based on Topic Identification of Online Innovation Communities and S-Curve

Multiple Time Series Perceptive Network for User Tag Suggestion in Online Innovation Community

User tag suggestion technique, aiming at learning users’ preferences over knowledge products from their historical behaviors, plays an important role in generating personalized recommendation in online innovation community. However, most current user tagging solutions only utilize a single kind of behavior to predict a single tag for users, resulting in weak generalization of user profile. In this paper, we propose a multiple time series perceptive network (MTSPN) for user tagging tasks in online innovation community. In particular, MTSPN takes multiple kinds of user behaviors into consideration for collaborative perception purpose, in which multi-scale sequential features are extracted from different sequential behaviors, and a multi-label classification module is built-in the proposed MTSPN model to predict multiple tags for users. Our encouraging experimental results on a real-world dataset collected from “Thingiverse” community validate the superiority of the our MTSPN model over several existing user tagging methods.