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This paper aims to bridge the gap by understanding the context of ageing consumer behaviour in the online community. Specifically, this research seeks to identify which content typologies are critical to generating high engagement levels and, consequently, online brand advocacy and to understand the underlying motivation behind consumer online engagement.

A netnographic approach was used to comprehensively analyse older consumers’ online communities on Facebook, namely, “Silversurfers”. A total of 3,991 posts were included in the study and analysed using a content analysis approach over two years, from 2020 to 2022.

Results revealed that photography is the most active media type among older consumers. This study extends the literature on content marketing, identifying 17 new content types that reflect the four motivation states of older consumers to engage with the online community: cognitive/informative oriented, affective/emotional oriented, co-creation/interactive oriented and nostalgic oriented. Moreover, this investigation stressed affective/emotional oriented and nostalgic oriented as the primary motivations for higher engagement levels.

The older population is growing, which makes the ageing market potentially huge. However, more literature needs to address it, especially in online communities. Finally, to the best of the authors’ knowledge, this study develops an original content typology framework in which firms can consider implementing effective content typology strategies for the older consumer segment.

Enterprises build online product community to expect users to contribute: opinion sharing (content contribution) and product consumption (product contribution). Previous literature rarely focused on both. The purpose of this paper is to explain user contribution mechanism by identifying content contribution and product contribution.

This research chose Xiaomi-hosted online product community (bbs.xiaomi.cn) and Huawei-hosted online product community (club.huawei.com) where users can freely share ideas and buy products at the same time. Data were crawled from 109,665 community users to construct dependent variable measurement, and 611 questionnaires were used to verify research hypotheses.

The results indicate that both cognitive needs and personal integration needs have a significant positive impact on browse behavior; social integration needs and hedonic needs have a significant positive impact on content contribution behavior. Browse behavior not only directly affects but also indirectly influences product contribution through content contribution behavior.

Findings of this research provide community managers with useful insights into the relationship between content contribution and product contribution.

This study explains the formation mechanism of user product contribution and reveals the relationship between user content contribution and product contribution in online product community. This paper provides a different way of theorizing user contributions by incorporating uses and gratifications theory into the “Motivation-Behavior-Result” framework.

Since the success of online communities depend on physicians' participation, understanding factors that influence community participation and content contribution are critical for online health communities (OHCs). Drawing on the self-determination theory (SDT), an empirical model was proposed to explore the effects of social returns and economic returns on physicians' community participation, private content contribution and public content contribution, and the moderating effect of their online seniority. This paper aims to address these issues.

Empirical data of 4,343 physicians were collected from a Chinese OHC, and ordinary least squares (OLS) and negative binomial regression models were employed to verify the proposed theoretical model.

The authors’ results indicate that both social and economic returns have a positive effect on physicians' community participation and private content contribution, and their online seniority strengthens the positive effects of economic returns on community participation and private content contribution.

The authors’ research extends physicians' community participation by dividing content contribution into private and public, and enhances our understanding of the determinants of physicians' participation in OHCs by exploring the effects of social and economic returns, as well as the moderating effect of online seniority. Their findings contribute to the literature on e-Health and user participation, and provide management implications for OHC managers.

The peer review history for this article is available at https://publons.com/publon/10.1108/OIR-11-2021-0615/

The paper examines the content moderation practices and related public disclosures of the World's most popular social media organizations (SMOs). It seeks to understand how content moderation operates as a process of accountability to shape and inform how users (inter)act on social media and how SMOs account for these practices.

Content analysis of the content moderation practices for selected SMOs was conducted using a range of publicly available data. Drawing on seminal accountability studies and the concepts of hierarchical and holistic accountability, the authors investigate the design and appearance of the systems of accountability that seek to guide how users create and share content on social media.

The paper unpacks the four-stage process of content moderation enacted by the World's largest SMOs. The findings suggest that while social media accountability may allow SMOs to control the content shared on their platforms, it may struggle to condition user behavior. This argument is built around the limitations the authors found in the way performance expectations are communicated to users, the nature of the dialogue that manifests between SMOs and users who are “held to account”, and the metrics drawn upon to determine the effectiveness of SMOs content moderation activities.

This is the first paper to examine the content moderation practices of the World's largest SMOs. Doing so extends understanding of the forms of accountability that function in the digital space. Crucial future research opportunities are highlighted to provoke and guide debate in this research area of escalating importance.

In an era where complex technological advances increasingly govern service delivery, it is incumbent on service firms to pioneer innovative strategies to sustain customer engagement and cultivate loyalty. This conceptual paper examines the transformative potential of artificial intelligence (AI) in the realm of online customer communities, with a particular focus on its creation, management and enhancement facets. The authors explore how AI can revolutionize the dynamics of customer interaction, feedback mechanisms and overall engagement within the service industry.

This conceptual paper draws from marketing and management literature focusing on customer communities and AI in service and customer engagement contexts with a robust future research agenda.

A classification of online customer community engagement is provided along with a conceptual framework to guide our understanding of the integration of AI into online customer communities.

This exploration underscores the imperative for service firms to embrace AI-driven approaches to online customer community management, not only as a means to optimize their operations but as a vital strategy to stay competitive in the ever-evolving digital landscape. This paper examines the novel combination of AI with online customer communities and provides the framework in the form of an input-process-output (IPO) model for future research into this integration.

The research study intends to gain a better understanding of members' behaviors in the context of crowdsourcing contests. The authors examined the key factors that can motivate or discourage contributing to a team and within the community.

The authors conducted 21 semi-structured interviews with Kaggle.com members and analyzed the data to capture individual members' contributions and emerging determinants that play a role during this process. The authors adopted a qualitative approach and used standard thematic coding techniques to analyze the data.

The analysis revealed two processes underlying contribution to the team and community and the decision-making involved in each. Accordingly, a set of key factors affecting each process were identified. Using Holbrook's (2006) typology of value creation, these factors were classified into four types, namely extrinsic and self-oriented (economic value), extrinsic and other-oriented (social value), intrinsic and self-oriented (hedonic value), and intrinsic and other-oriented (altruistic value). Three propositions were developed, which can be tested in future research.

The study has a few limitations, which point to areas for future research on this topic. First, the authors only assessed the behaviors of individuals who use the Kaggle platform. Second, the findings of this study may not be generalizable to other crowdsourcing platforms such as Amazon Mechanical Turk, where there is no competition, and participants cannot meaningfully contribute to the community. Third, the authors collected data from a limited (yet knowledgeable) number of interviewees. It would be useful to use bigger sample sizes to assess other possible factors that did not emerge from our analysis. Finally, the authors presented a set of propositions for individuals' contributory behavior in crowdsourcing contest platforms but did not empirically test them. Future research is necessary to validate these hypotheses, for instance, by using quantitative methods (e.g. surveys or experiments).

The authors offer recommendations for implementing appropriate mechanisms for contribution to crowdsourcing contests and platforms. Practitioners should design architectures to minimize the effect of factors that reduce the likelihood of contributions and maximize the factors that increase contribution in order to manage the tension of simultaneously encouraging contribution and competition.

The research study makes key theoretical contributions to research. First, the results of this study help explain the individuals' contributory behavior in crowdsourcing contests from two aspects: joining and selecting a team and content contribution to the community. Second, the findings of this study suggest a revised and extended model of value co-creation, one that integrates this study’s findings with those of Nov et al. (2009), Lakhani and Wolf (2005), Wasko and Faraj (2000), Chen et al. (2018), Hahn et al. (2008), Dholakia et al. (2004) and Teichmann et al. (2015). Third, using direct accounts collected through first-hand interviews with crowdsourcing contest members, this study provides an in-depth understanding of individuals' contributory behavior. Methodologically, this authors’ approach was distinct from common approaches used in this research domain that used secondary datasets (e.g. the content of forum discussions, survey data) (e.g. see Lakhani and Wolf, 2005; Nov et al., 2009) and quantitative techniques for analyzing collaboration and contribution behavior.

The authors advance the broad field of crowdsourcing by extending the literature on value creation in the online community, particularly as it relates to the individual participants. The study advances the theoretical understanding of contribution in crowdsourcing contests by focusing on the members' point of view, which reveals both the determinants and the process for joining teams during crowdsourcing contests as well as the determinants of contribution to the content distributed in the community.

The current study aims to investigate the factors that impact the feedback received on answers to questions in social Q&A communities and whether the expertise-required question influences the role of these factors on the feedback.

To understand the antecedents and consequences that influence the feedback received on answers to online community questions, the elaboration likelihood model (ELM) is applied in this study. The authors use web data crawling methods and a combination of quantitative analyses. The data for this study came from Zhihu; in total, 353,775 responses were obtained to 1,531 questions, ranging from 49 to 23,681 responses per question. Each answer received 0 to 113,892 likes and 0 to 6,250 comments.

The answers' cognitive and emotional components and the answerer's influence positively affect user feedback behavior. In addition, the expertise-required question moderates the effects of the answer's cognitive component and emotional component on the user feedback, moderating the effects of the answerer's influence on the user approval feedback.

This study builds upon a limited yet growing body of literature on a theme of great relevance to scholars, practitioners and social media users concerning the effects of the connotation of answers (i.e. their cognitive and emotional components) and the answerer's influence on user feedback (i.e. approval and collaborative feedback) in social Q&A communities. The authors further consider the moderating role of the domain expertise required by the question (expertise-required question). The ELM model is applied to explore the relationships between questions, answers and feedback. The findings of this study add a new perspective to the research on user feedback and have implications for the management of social Q&A communities.

Users' knowledge contribution behaviors are critical for online Q&A communities to thrive. Well-organized question threads in online Q&A communities enable users to clearly read existing answers and their evaluations before contributing. Based on the social comparison and peer influence literature, the authors examine peer influence on the informativeness of knowledge contributions in competitive settings. The authors also consider three levels of moderating factors concerning individuals' perception of competitiveness: question level, thread level and contributor level.

The authors collected data from one of the largest online Q&A communities in China. The hypotheses were validated using hierarchical linear models with cross-classified random effects. The generalized propensity score weighting method was employed for the robustness check.

The authors demonstrate the peer influence due to social comparison concerns among knowledge contribution behaviors in the same question thread. If more prior knowledge contributors choose to contribute long answers in the question thread, the subsequent contributions are more informative. This peer influence is stronger for factual questions and questions with higher popularity of answering but weaker in recommendation-type and well-answered questions and for contributors with higher social status.

This research provides a new cue of peer influence on online UGC contributions in competitive settings initiated by social comparison concerns. Additionally, the authors identify three levels of moderating factors (question level, thread level and contributor level) that are specific to online Q&A settings and are related to a contributor's perception of competitiveness, which affect the direct effect of peer influence on knowledge contributions. Rather than focus on motivation and quality evaluation, the authors concentrate on the specific content of online knowledge contributions. Peer influence here is not based on an actual acquaintance or a following relationship but on answering the same question. The authors also illustrate the competitive peer influence in subjective and personalized behaviors in online UGC communities.

As fertile soil for product promotion, online interest communities have gradually come into brands' view. However, existing research does not clarify whether brand engagement in consumer interaction is beneficial to the development of online interest communities. This study attempts to investigate the effects of brand engagement on the online interest community operation.

The authors propose a model that delineated the influence of brand engagement on consumers' citizenship behavior in the online interest community from the commitment-trust perspective. Scenario-based experiments were conducted and 536 data were collected by simple random sampling.

Results shows that a stronger perception of brand engagement has a positive influence on the relationship (trust and commitment) between the community and its users, which further influences online community citizenship behavior (feedback, advocacy and tolerance) of both posters and lurkers, especially for the posters. Although relationships are more complex, brand engagement activates the development of online interest communities to some extent.

This original study contributes to the commitment-trust theory by examining the impact of brand engagement on citizenship behavior via community commitment and trust in the online interest community context. In addition, this study compares the moderating effect of posters vs lurkers on the relationship between brand engagement and citizenship behavior in the online interest community.

While providing users with important innovation resources, an enterprise's open innovation community also encounters numerous challenges. The purpose of this study is to develop and implement a set of evaluation systems that can identify the ecological characteristics of open innovation communities. The ultimate goal is to provide guidance for the construction and establishment of these communities.

Firstly, from the perspective of information ecology, according to the connotation requirements of the four information elements of “people, information, technology and environment” in the information ecosystem, this paper determines the evaluation indicators of enterprise's open innovation community from the aspects of integrity and dynamics. Then, based on the improved analytic hierarchy process, the weight of each index is calculated, and a complete evaluation system of open innovation community is established. Finally, the fuzzy comprehensive evaluation method is used to conduct empirical research on Haier Open Partnership (HOPE) platform, analyze its ecological situation and existing problems and put forward the corresponding construction recommendations.

The application of HOPE platform shows that the evaluation index system built in this study has good applicability, and the whole research process and research method have certain reference value for future studies. At the same time, the study found that the HOPE platform has good ecological characteristics, but there are also some problems. This study can directly promote the construction of the platform.

This paper, for the first time, combines the information ecology theory with the open innovation community. The results demonstrate that the open innovation community is an information ecosystem, which can be evaluated ecologically. Furthermore, to ensure the calculation's scientific accuracy, the index weight is determined by constructing a judgment matrix based on expert questionnaires.