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Purpose An increasing number of companies have become aware of the considerable commercial potential of firm-hosted online communities (FOC) and initiated their own platform for different purposes. However, limited research has systematically explored oppositional loyalty and customer satisfaction in the context of FOC. By applying the expectation–confirmation model (ECM), the purpose of this paper is to investigate the determinants of oppositional loyalty and satisfaction from the perspective of social capital and e-quality. Design/methodology/approach A research model was tested by applying partial least squares technique, and data were collected from a survey of members (n=512) of two popular smartphone communities in China. Findings Results revealed that satisfaction, trust and shared language are the significant antecedents of oppositional loyalty. Benefits confirmation, information quality, service quality, trust and social tie exert strong effects on the formation of satisfaction. Originality/value This study is an original empirical research guided by several theories. It contributes to the information system usage literature and provides opinions regarding how users’ oppositional loyalty and satisfaction can be developed in the FOCs. This work also widens the application of ECM and provides an alternative theoretical framework for future research on oppositional brand loyalty.

Purpose Many users build personal projects in co-innovation community to accomplish their innovations. However, very few projects from such communities are successful and understanding of this phenomenon is limited. The purpose of this paper is to identify the factors facilitating user projects success in online co-innovation communities. Design/methodology/approach Based on the theories of persuasion and diffusion of innovation (DOI), a conceptual model is proposed to explain how project success likelihood is affected by the creator, project and user participation characteristics. Then, the model and hypotheses are tested through binary logistic regression on a secondary data set of 572 projects collected from a typical user co-innovation community, Local Motors. Findings The results show that creator characteristics (prior success rate), project characteristics (project popularity, length and duration) and user participation characteristics (participation users and degree) have significant and positive impacts on project success likelihood. The number of prior projects, which can hardly represent the creator’s credibility in open and unrestricted situations, has no significant influence on the project success likelihood. Practical implications This study offers project creators the keys to increase their projects successful possibility. Besides, this study recommends a new way to attract users and helps to identify creative and effective users for community practitioners. Originality/value This study expands the research scope in online co-innovation community by focusing on user personal projects. In addition, it combines persuasion theory and DOI theory to add the holistic understanding of user project success likelihood.

Purpose Analyzing the sentiment orientation of each product aspect/feature might be sufficient to assist the customer to make purchase/usage decisions, but such level of information obtained by sentiment analysis is not detailed enough to assist the company in making product improvement or design decisions. Therefore, this paper aims to propose a novel method to extract more detailed information of the product. Design/methodology/approach This paper proposed to use a set of trivial lexical-Part-of-Speech patterns to prepare candidate corpus and then adopted a topic model to find the optimal number of topics and get the words distributions in each topic. Finally, combined a priori analysis and compactness rules, the authors found out the expected strong rules in each topic, which make up the final problems. Findings Experimental results on a real-life data set from Xiaomi forum showed the proposed method can extract the product problems effectively. The authors also explained the errors of experiment, which suggested the direction for future research. Originality/value This paper proposed a novel method to obtain information of product problems in detail, which will be useful to assist companies to improve their product performance.

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