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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.

Service providers on highly competitive online outsourcing platforms employ various signals to entice buyers to make online purchases. One such signal—the solution exemplars—attracts attention through depictions of exemplary prior work completed by the service providers. Unfortunately, it is not known the extent to which solution exemplar characteristics affect sales performance nor is it clear how such signals perform in the presence of complementary signals such as service provider expertise. This paper explores these issues.

Extending signaling theory, the authors develop a model to explore the effects of solution exemplar characteristics (i.e. exemplar quantity, exemplar diversity and exemplar popularity) on sales performance under the moderating impact of service provider expertise. The authors test the model using proprietary data from ZBJ.com, a leading online outsourcing platform in China.

Exemplar quantity and exemplar popularity positively affect sales performance; exemplar diversity has no significant impact on sales performance and service provider expertise positively moderates the relationships between exemplar quantity, exemplar popularity and sales performance.

This work makes several significant contributions. First, the authors enrich the research on signals in online outsourcing by exploring the impact of solution exemplar characteristics on sales performance. Second, the authors analyze three solution exemplar characteristics: exemplar quantity, exemplar diversity and exemplar popularity. Third, this work shows that service provider expertise moderates the relationship between solution exemplar characteristics and sales performance. Important practical implications for both online outsourcing platforms and service providers are discussed.

Crowd logistics is a rising phenomenon in last-mile delivery that integrates technological applications and sources a large number of participants to do logistical activities, achieving sustainable shipping in urban environments. However, up until now, there has been limited literature in this field. This research aims to investigate the extrinsic and intrinsic factors that impact the participative behaviour of driver-partners in crowd logistics.

An integrated model is developed based on motivation theory, incorporating attitude as a contributor to both extrinsic and intrinsic motivations. A questionnaire was constructed and distributed to collect data from 303 respondents who are existing or potential driver-partners in Vietnam.

Our findings confirm (1) the influence of monetary rewards on extrinsic motivation and (2) the power of self-efficacy, trust and sense of belonging on intrinsic motivation. Further, we find that attitude positively impacts extrinsic motivation, whereas there is no effect between attitude and intrinsic motivation. Both extrinsic and intrinsic motivations are demonstrated to significantly influence driver-partners' participative intentions. Additionally, a positive association is found between extrinsic and intrinsic motivations.

Findings from this study theoretically enrich the literature on crowd logistics, especially on the supply side, and empirically contribute to implications that are valuable to crowd logistics firms on driver-partner recruitment and business strategy development.

Social interaction in comment sections has become a key factor for backers' decision making in crowdfunding platforms. However, current research on the two-way social interaction in crowdfunding is insufficient, and there exist inconsistent conclusions. This study focuses on the social interaction between creators and backers and explores its influence on the successful exit of crowdfunding projects.

The extended Cox model is used for the empirical analysis of 1,988 crowdfunding projects on the Modian (www.modian.com) platform, a crowdfunding platform for cultural and creative projects in China. The two-way social interaction is reflected in comment quantity and sentiment, as well as reply rate.

Results reveal an inverted U-shaped relationship between comment quantity/sentiment and the successful exit of crowdfunding projects. This relationship is strengthened by high reply rate.

This study focuses on comment quantity and sentiment. The inverted U-shaped results reconcile previous conclusions. Replies from creators are regarded as a separate factor, and their moderating role is explained. The study research proves the importance of social interaction in crowdfunding platforms and provides suggestions for backers, creators and platform managers.

This paper aims to investigate textual characteristics of customer reviews that motivate companies to respond (sentiment negativity and sentiment deviation) and how aspects of these company responses (response intensity, length and tailoring) affect subsequent customer review quality (comprehensiveness and readability) over time.

Leveraging a large data set from a leading app website (Shopify), the authors combine text mining, natural language processing (NLP) and big data analysis to examine the antecedents and outcomes of online company responses to reviews.

This study finds that companies are more likely to respond to reviews with more negative sentiment and higher sentiment deviation scores. Furthermore, while longer company responses improve review comprehensiveness over time, they do not have a significant influence on review readability; meanwhile, more tailored company responses improve readability but not comprehensiveness over time. In addition, the intensity (volume) of company responses does not affect subsequent review quality in either comprehensiveness or readability.

This paper expands on the understanding of online company responses within the digital marketplace – specifically, apps – and provides a new and broader perspective on the motivations and effects of online company responses to customer reviews. The study also extends beyond the short-term focus of prior works and adds to literature on long-term effects of online company responses to subsequent reviews. The findings provide valuable insights for companies (especially those with apps) to enhance their online communication strategies and customer engagement.

Academics and practitioners are increasingly discussing the role of crowdsourcing initiatives in dealing with the challenges imposed by the COVID-19 pandemic, along with their role in an emergency context in general. However, empirical evidence about the role of crowdsourcing initiatives in an emergency context is still scarce. This paper aims to address this gap in knowledge.

The authors adopted an inductive approach to investigate how companies leveraged crowdsourcing initiatives to address the issues posed by COVID-19. Data were collected through semi-structured interviews. The selection of the interviewees was based on a purposive sampling strategy. Data were analysed through thematic analysis.

The analysis led to the identification and examination of drivers (e.g. preserving relationships with customers), advantages (e.g. increased demand for services) and disadvantages (e.g. increased platform cost) of implementing crowdsourcing initiatives during COVID-19. By leveraging the findings, this paper suggests future research opportunities. Relevant future research opportunities include: (1) quantitatively evaluating the economic impact of crowdsourcing initiatives during a disruptive event and (2) examining how the sector in which the company operates influences the beneficial and detrimental effects of crowdsourcing initiatives on company performance.

The involvement of crowds as innovation partners has provided unique opportunities for companies to innovate and address the challenging scenario. The scientific literature about the role of crowdsourcing during COVID-19 is growing. However, there is still a scarcity of empirical evidence about the mechanisms underpinning the use of crowdsourcing during the pandemic. By leveraging semi-structured interviews, this paper addresses this relevant gap in knowledge.

The development of information technologies has fueled the emergence of online self-organizing teams that involve members with diverse backgrounds to work on a shared goal voluntarily. However, the differences in members' attributes give rise to diversity. Therefore, the authors’ research is to figure out how diversity affects team performance in the context of online self-organizing teams and how this effect changes over team tenure.

The authors use a dynamic approach to the diversity-team performance relationship and collect a publicly longitudinal dataset on 3,970 collaborative items from 2,550 online self-organizing teams spanning nine years in an open innovation community of an online game.

The empirical results show that culture separation is negatively related to team performance, and this negative relationship weakens as team tenure increases. While skill variety and contribution disparity are positively related to team performance, and these positive relationships strengthen as team tenure increases.

The study provides a research framework to examine the relationship between diversity and team performance and explore how this relationship varies over team tenure in the context of online self-organizing teams. The results not only demonstrate the double-edged role of diversity in affecting the success of online self-organizing teams but also advance the understanding on the temporal effect of diversity on team performance.

Managing the growing word-of-mouth (WOM) of brand fans has become a new challenge for companies in the fan economy era. The purpose of this paper is to examine the effect of language intensity of brand fan WOM on customers' willingness to adopt WOM based on psychological resistance theory and to reveal the underlying mechanism of this process.

A research model was developed to test the proposed hypotheses. Two experiments were conducted on an online platform using data from 708 participants. The independent samples t-test and analysis of variance were used to analyze the data.

The results show that, in the context of WOM among brand fans, high-intensity language leads to a lower willingness to adopt than low-intensity language and threats to freedom mediate this effect. Moreover, the restoration postscript moderates the effect of language intensity on threats to freedom and customers' willingness to adopt WOM.

Unlike previous studies that focused on electronic word-of-mouth (eWOM) language content, this paper focuses on language intensity to reveal the psychological process of customers' willingness to adopt brand fan WOM. The findings not only enrich the research related to the language effect in eWOM, but also deepen the understanding of the influence effect on brand fan WOM, providing effective guidance for brands to manage fan WOM.

Waiting time, as an important predictor of queue abandonment and patient satisfaction, is important for resource utilization and patient experience management. Medical institutions have given top priority to reforming the appointment system for many years; however, whether the increased information transparency brought about by the appointment scheduling mechanism could improve patient waiting time is not well understood. In this study, the authors examine the effects of information transparency in reducing patient waiting time from an uncertainty perspective.

Leveraging a quasi-natural experiment in a tertiary academic hospital, the authors analyze over one million observational patient visit records and design the propensity score matching plus the difference in difference (PSM-DID) model and hierarchical linear modeling (HLM) to address this issue.

The authors confirm that, on average, improved information transparency significantly reduces the waiting time for patients by approximately 6.43 min, a 4.90% reduction. The authors identify three types of uncertainties (resource, process and outcome uncertainty) in the patient visit process that affect patients' waiting time. Moreover, information transparency moderates the relationship between three sources of uncertainties and waiting time.

The authors’ work not only provides important theoretical explanations for the patient-level factors of in-clinic waiting time and the reasons for information technology (IT)-enabled appointment scheduling by time slot (ITASS) to shorten patient waiting time and improve patient experience but also provides potential solutions for further exploration of measures to reduce patient waiting time.

This study aims to investigate the relationship between self-determined motivation and organizational commitment, with the mediating role of cross-cultural adjustment of low-skilled workers who come from an emerging economy working in a developed economy. This study also aims to determine the interaction effect between intrinsic and extrinsic motivation on organizational commitment.

This study collects a sample data of 236 Vietnamese laborers in Taiwan. Structural equation modeling is used to analyze data and test hypotheses.

Results show that intrinsic and extrinsic motivations are positively related to organizational commitment. Cross-cultural adjustment positively mediates the relationship between intrinsic motivation and organizational commitment and that between extrinsic motivation and organizational commitment. Furthermore, extrinsic motivation positively moderates the relationship between intrinsic motivation and organizational commitment.

This study helps to untangle the relationship between self-determined motivation and organizational commitment of low-skilled workers in an unfamiliar environment. Furthermore, this study also clarifies the mediating and moderating mechanisms of cross-cultural adjustment and extrinsic motivation in this relationship. The findings provide implications for researchers and managers to plan and implement policy and management systems that combine tangible and intangible incentives to motivate foreign workers and induce positive outcomes for companies in a new cultural context.