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Online customer reviews is an important information resource for product innovation. This study aims to investigate the impact of online customer reviews on iterative innovation of software products and the moderating roles of product complexity in the process of online reviews influencing product iterative innovation.

To empirically test the hypotheses, this paper built a panel data of 500 software products from 2019 to 2021 and applied Poisson regression analysis.

Empirically results reveal that both sentiment and quantity of online customer reviews have positive effects on iteration innovation of software products. In addition, the authors find that product complexity negatively moderates the relationship between online reviews and iterative innovation.

This study suggests that firms can acquire valuable information from customers’ online reviews for product iterative innovation and improvement. However, for high-complexity products, it may be difficult for enterprises to obtain useful information for iterative innovation from online reviews. On the other hand, this study provides a reference for firms to choose more useful online reviews from the perspective of sentiment.

This paper provides a new finding that there is a positive relationship between online customer reviews and iterative innovation of software products. Moreover, the authors also provide a deeper understanding of how online customer reviews affects iterative innovation by examining the moderating roles of product complexity.

The internal resources of a firm should not be regarded as the only source of innovation; organizations need to look at the external sources which can contribute greatly. This can happen through the recent development in technologies and the emergence of social media; such advancements have empowered consumers to have social interaction with their peers in online communities. As a source of generation of innovative ideas, company-based communities have not received enough attention, although they are strong drivers for co-creation of value by customers. Easy online communication channels, facilitated through online communities, have developed open innovation as an attractive means of customer involvement in value creation. However, literature in this area is devoid of empirical research on the way consumers can participate in open innovation communities using Web 2.0 technologies. The paper aims to discuss these issues.

This paper, therefore, looks at the opportunities offered by social media to firms for open innovation in the context of new product development (NPD). The study is based on social support theory and the concept of social media generating open innovation; a model for the research has thus been proposed. The model has been tested using partial least square through an online questionnaire.

The results indicate that social media is a cost-efficient way for firms to look at external sources of innovation, specifically in NPD. Online communities, developed specifically for new products, can support the innovation process for the business sector. The paper discusses the results of this empirical research and has some practical implications for practitioners in this field.

The study indicate that social media empower individuals to come online, get involved in social interaction and share their experiences about a new product with other peers in the network. Social media and informational support, as social capital of online communities, both have influence on participation of individuals in the online communities of open innovation for NPD.

This study aims to explore the different effects of inter-community group networks and intra-community group networks on group innovation.

The authors used a pooled panel dataset of 12,111 self-organizing innovation groups in 463 game product creative workshop communities from Steam support to test the hypothesis. The pooled ordinary least squares (OLS) model is used for analyzing the data.

The results show that network constraint is negatively associated with the innovation performance of online groups. The average path length of the inter-community group network negatively moderates the relationship between network constraint and group innovation, while the average path length of the intra-community group network positively moderates the relationship between network constraint and group innovation. In addition, both the network density of inter-community group networks and intra-community group networks can negatively moderate the negative relationship between network constraint and group innovation.

The findings of this study suggest that network structural characteristics of inter-community networks and intra-community networks have different effects on online groups’ product innovation, and therefore, group members should consider their inter- and intra-community connections when choosing other groups to form a collaborative innovation relationship.

With the proliferation of ideas submitted by users in firm-built online user innovation communities, community managers are faced with the problem of user idea overload. The purpose of this paper is to explore the influencing factors on the idea adoption to identify high quality ideas, and then propose a method to quickly filter high value ideas.

The authors collected more than 110,000 data submitted by Xiaomi community users and analyzed the factors affecting idea adoption using a multinomial logistic regression model. In addition, the authors also used BP neural network to predict the idea adoption process.

The empirical results show that idea semantics, number of likes, number of comments, number of related posts, the existence of pictures and self-presentation have positive impact on idea adoption, while idea length and idea timeliness had negative impact on idea adoption. In addition, this paper calculates the idea evaluation value through the idea adoption process predicted by neural network and the mean value of idea term frequency inverse document frequency (TF-IDF).

This empirical study expands the theoretical perspective of idea adoption research by using dual-process theory and enriches the research methods in the field of idea adoption research through the multinomial logistic regression method. Based on our findings, firms can quickly identify valuable ideas and effectively alleviate the information overload problem of online user innovation communities.

Online innovation communities are central for many organizations seeking to advance their innovation portfolio. While these communities rely on consumers to collaborate in the innovation process, it remains unclear what drives these consumers to perform value co-creation activities and what value dimensions they derive as a result. This paper aims to advance the understanding of value co-creation in the online collaborative innovation context. Specifically, it aims to examine social and individual factors driving such activities, and the value derived from the perspective of the member.

A self-administered online questionnaire was used to collect data from collaborative innovation community members yielding 309 complete responses. Structural equation modelling was used to analyse the data, using variance-based structural equation modelling with partial least squares path modelling in SmartPLS.

Results confirm that distinct social and individual factors facilitate individual value co-creation activities, including the provision of feedback, helping, rapport building and information sharing. Furthermore, the research confirms the mediating role of learning on these relationships.

This study contributes to the micro-foundation movement in marketing by undertaking an independent examination of value co-creation activities and their nomological network.

A shift in the mindset of managing for collaborative innovation is required, from a focus on collaborative product development to the management of an online community where members derive value from their co-creation activities.

This research is the first to offer insight into important individual and social pre-conditions and subsequent value outcomes of four common value co-creation activities. It informs practice about how to facilitate value co-creation activities and contribute to the co-creation of value for online innovation community members.

The customer enables online reviews, discusses product features and enhances the user's experiences in online activities. Users generated product innovation and product reviews effect as market competition. This research study explains deep learning, online reviews and product innovation empirical evidence used by mobile apps.

Online reviews and product innovation are very important for every organization and firms to achieve a competitive advantage in a large business environment. When the authors see past traditional history, customers are not involved in product creating and innovating processes. Due to new technology changes, online systems and web 2.0 increase this ability.

For this research purpose, the authors use different analytical software to measure the impact among variables. This study is established on primary data; this study collected data from online customers and its users. For data collection, the authors use some questionnaires, and these questions are filled from 200 respondents.

This research study used data from the Google app store – Google product selling application – and gathered customers' online reviews. Research found that customers' online reviews and deep learning positively and significantly influence product innovation through networking technology. This research-based online mobile application and its research reviews found that organizations convert their own business online and effectively and efficiently enhance creditability.

This research study used data from the Google app store Google product selling application and gathered customers' online reviews. Research founded that customers' online reviews and deep learning are positively and significantly influence product innovation through networking technology. This research-based online mobile application and its research reviews found that organizations convert their own business online and effectively and efficiently enhance creditability.

This study aims to explore how and when learning from others promotes creative performance over the contributor’s tenure in the context of open innovation communities.

The authors analyze a publicly available data set that includes 25,923 innovative items developed by 2,194 contributors from an open innovation community of an online game spanning eight years. Logistic regression model is used for analyzing the data.

The results show that multicultural experiences are negatively related to contributor’s creative performance, and this negative relationship weakens as contributor’s tenure increases. While diverse skills are positively related to contributor’s creative performance, and this positive relationship strengthens as contributor’s tenure increases.

This research highlights the importance of online team collaboration in knowledge transfer through learning from others in open innovation communities. By identifying two outcomes of learning from others through online team collaboration, the authors demonstrate the double-edged role of learning from others and advance the understanding on how the effect of learning from others varies over the contributor’s tenure. These results expand the understanding of online team collaboration and provide a new perspective for research on learning from others.

The purpose of this paper is to explore the relationship between the actual usage of online methods for collaboration with customers and firms’ innovation performance. Drawing on theories of knowledge flows and knowledge creation, this study analyses the results of customer collaboration in the online mode in comparison to the offline mode.

The data for the econometric analysis comes from managers of 102 so-called “gazelles”, knowledge-intensive service firms that were characterized by exceptionally stable growth rates in Sweden during 2010 and 2011.

This study confirms the significance of information and communication technology (ICT)-supported collaboration with customers for a firm’s innovation performance. Interacting with customers using online methods has a positive effect on companies’ innovation output. Besides, knowledge-intensive service companies demonstrate more extensive though less intensive use of online channels for collaborating with customers compared to offline methods.

The data for this study has typical limitations resulting from the collection method of web-surveying. Future research should refine the findings of this study using various measures of firms’ innovation performance.

Firms should be more receptive towards online methods of collaboration with customers because using such strategy can increase their probability to introduce service innovations. The insights from this study are especially valuable for companies in knowledge-intensive service industries because the sample consist of companies that can be regarded as successful cases.

This study is one of the first that addresses the issue of the impact of collaborative technologies on innovation performance. The sample of steady-growing gazelle companies adds value to the results.

The purpose of this paper is to explore and highlight the particular innovation characteristics and modes of the Chinese online game industry from a networking perspective.

This research is qualitative. Both primary and secondary data are used, which is collected through desk research on related documents and long‐term participative observation and personal experiences. This paper begins with an overview of the online game industry's innovation process and types; then constructs a framework that contains four innovation modes with different networks to guide the analysis and organization on the empirical findings; finally, the paper proposes some implications for companies and government.

This paper is an attempt to open the black box of the innovation of the Chinese online game industry. Born as an incomplete and virtual product, the innovation modes evolve from closed to a combination of open and networking ones. Producer‐driven Innovation Network Mode shows that game companies can get innovation resources through its focal network. Producer‐user Interaction Mode shows that players' have tremendous innovation potential. Open Collaborative Network Mode shows that power is distributed and the roles of actors are blurred.

This paper offers an analysis of the Chinese online game industry from the innovation side and partly fills the research gap. Also, this paper emphasized the users' innovation ability and a hybrid of different innovation modes, which can be seen as a successful theory test of user innovation, innovation networks, and open innovation theories in the Chinese context.

This paper aims to conceptualize two patterns of user recognition mechanisms and two kinds of user contribution behavior in enterprise-hosted online product innovation community and explain their relationships between user recognition mechanisms and user contribution behavior of online product innovation community.

A Chinese enterprise-hosted online innovation community and an American enterprise-hosted online innovation community are selected as research objects. Four Logit models are developed and some hypotheses are supposed from the perspective of prosocial behavior theory. Objective user data with three months from two online product innovation communities are collected to test with Logit regression analysis.

Findings show that there are obvious correlations between user recognition mechanisms and user contribution behavior, and there is also an obvious difference in community user activity level between the quantity-based user recognition mechanism community and the quality-based user recognition mechanism community. More specifically, in the online product innovation community with quantity-based recognition mechanism, both variables of peer recognition and community image motivation significantly affect user proactive contribution behavior. In the online product innovation community with quality-based recognition mechanism, the variable of peer recognition significantly affects both user proactive contribution behavior and user responsive contribution behavior; the variable of community image motivation significantly affects both user proactive contribution behavior and user responsive contribution behavior.

Although it is voluntary, online user voluntary contribution behavior still need to be presented, recognized and affirmed by community. For enterprise-hosted online community managers, they should pay more attention to design the reasonable online community user recognition mechanism with the coexistence of quantity and quality.

The theoretical contribution in this study is to enrich the existing research theme about enterprise-hosted online product innovation community. First, it conceptualizes two patterns of user recognition mechanisms. Second, it regards the variable of user contribution behavior as the co-existence of proactive contribution and responsive contribution. Third, from the perspective of prosocial behavior theory, it is an important supplement to explain the mechanism of user contribution behavior in enterprise-hosted online product innovation community. Fourth, it deepens the overall understanding of the relationship between user recognition mechanism and user contribution behavior. This study provides theoretical guidance for enterprises how to design reasonable and efficient online product innovation community platform. The theoretical contribution in this study is to enrich the existing research theme about enterprise-hosted online product innovation community. First, it conceptualizes two patterns of user recognition mechanisms. Second, it regards the variable of user contribution behavior as the co-existence of proactive contribution and responsive contribution. Third, from the perspective of prosocial behavior theory, it is an important supplement to explain the mechanism of user contribution behavior in enterprise-hosted online product innovation community. Fourth, it deepens the overall understanding of the relationship between user recognition mechanism and user contribution behavior. This study provides theoretical guidance for enterprises how to design reasonable and efficient online product innovation community platform.