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The purpose of this study was to identify the status of using crowdsourcing to develop information services through the Twitter platform and to determine the factors affecting such usage.

A qualitative action research approach was employed to achieve the objectives of the study and to provide answers to the research questions. The effectiveness of using crowdsourcing technique for improving information services has been explored through five procedural stages: diagnostics, action planning, action taking, evaluation and determined learning. Three tools were used to collect data: open interviews, content analysis of the sampled accounts on Twitter and users' perceptions regarding information services.

The results of the study revealed that crowdsourcing was not used in the development of information services per se, but it has been used for other purposes. The results also revealed that several factors influenced the adoption of using crowdsourcing to develop information services, including factors related to the institutional trust in crowds' capabilities, the nature of service and type of the needed development, and finally, the platform used to conduct crowdsourcing. The results of the action research proved that using crowdsourcing to develop information services could be effective.

The study suggests a model that can be used to test changes implemented in organizations, especially regarding adoption of crowdsourcing as a framework to achieve the objectives of the institution, particularly in the planning processes.

This research paper produces new knowledge through using a qualitative action research approach to understand the potential of social media in crowdsourcing. There have been no similar studies conducted in the region for the specified research design. The results add to the level of learning and raise awareness within the research community regarding the effectiveness of using crowdsourcing via social media platforms to improve the efficiency of information services.

The purpose of the presented research paper is to explore the different aspects of crowdsourcing and its evolution over time. Supported by three different case studies, the research focuses on the different factors that affect crowdsourcing for open innovation. Moreover, the findings give us a proposed managerial framework to be considered when adopting crowdsourcing in addition to factors that proved its huge effect on crowdsourcing activities.

A qualitative research approach for this research was the most convenient. It focuses on providing an in-depth understanding of the phenomena. Qualitative research represents the views and perspectives of the participants in a study besides it is driven by a desire to explain these events, through existing or emerging concepts (Yin, 2016). Adopting a case study research method that investigates a contemporary phenomenon (the “case”) in depth and within its real-world context, especially when the boundaries between phenomenon and context may not be evident (Yin, 2018) as in crowdsourcing based business model for open innovation.

The researchers presented the benefits and challenges when considering crowdsourcing establishing a managerial framework for open innovation. Additionally, the researchers identified the different factors that highly affect crowdsourcing proposing a model that can be used for adopting crowdsourcing. The research also presented insights about how crowdsourcing was introduced in the Egyptian market and how it evolved through the years.

The study had some limitations to be considered in the following work. Company X used crowdsourcing within a high degree of limitations and confidentially consequently, restricting the effects and results of crowdsourcing. Another limitation was that the study has been only qualitative, and the addition of the quantitative approach will numerically support the findings. Moreover, the research depended on the businesses only as of the source of information and neglected the crowd sample.

The main aim of this study was to address the lack of research evidence on what it means to adopt crowdsourcing for open innovation in Egyptian firms. The authors have done so by adopting three case studies which enabled them to directly observe and report on the daily work of trust CEOs, with special attention to the practices. Whereby, these executives made themselves knowledgeable for all practical purposes, as dictated by their specific job. Accordingly, the first major contribution of the present research is that it provides much-needed empirical data on the actual practices of crowdsourcing in three Egyptian, yet international companies. Moreover, the results could be used as a guideline when considering crowdsourcing activities highlighting the advantages and disadvantages of such activities.

The paper discusses different perspectives of crowdsourcing presenting a new categorization for its types. Moreover, how these types have been used especially in the Egyptian market. On the other hand, the paper investigated and documented three different sized companies' experiences utilizing crowdsourcing for innovation. The collected information was used to suggest a new model by which companies can avoid the difficulties others had. Moreover, the research highlighted the benefits and challenges of using crowdsourcing for open innovation.

This paper aims to examine how the relationship norms established between customers and brands influence customer perceptions of crowdsourcing (vs firm-generated) cues.

Four studies (N = 851) examine the moderating role of relationship norms on product labeling cues (crowdsourcing vs firm-generated) effects on brand engagement, and the underlying mechanism of self-brand connection.

The findings suggest that crowdsourcing (vs firm-generated) cues lead to higher brand engagement (Studies 1A–1B), mediated by self-brand connection (Studies 2–3). In addition, relationship norms moderate the effects (Study 3), such that under exchange brand relationships crowdsourcing (vs firm-generated) cues yield higher brand engagement, whereas communal brand relationships reverse such effects.

The findings provide valuable managerial implications by highlighting the importance of using relationship norms as diagnostic cues to successfully implement crowdsourcing initiatives.

This research adds to the customer-brand relationship literature by revealing an accessibility-diagnosticity perspective of consumers’ reactions to crowdsourcing (vs firm-generated) cues.

This study aims to examine consumers’ responses to crowdsourcing campaigns in the request initiation stage using the signaling theory from economics. The purpose of the research is threefold. First, it provides a comprehensive classification of various task types within crowdsourcing. Second, it conceptualizes crowdsourcing announcements as signals of customer orientation and empirically tests the differential effects of the two most common crowdsourcing task types (product- and communication-related) on customer orientation perceptions. Third, it illuminates the downstream behavioral consequences of crowdsourcing campaign announcements.

The authors conducted secondary data analysis of 883 crowdsourcing campaigns (pilot study) to provide evidence on the differential effects of crowdsourcing task types. In addition, four laboratory experiments were conducted to test the theoretical arguments. To test the main effect of crowdsourcing task types, Study 1A (N = 252 MTurk workers) used a one-factor (product- vs communication-related crowdsourcing vs control) between-subject design, whereas Study 1B (N = 171 undergraduate students) used a 2 (task type: product- vs communication-related) by 2 (product category: restaurant vs fashion) between-subject design. Study 2 (N = 93 MTurk workers) explored the underlying mechanism using a one-factor (product- vs communication-related) between-subject design. Study 3 (N = 375 MTurk workers) investigated the boundary condition for the effect of task type with a 2 (task type: product- vs communication-related) by 3 (company credibility: low vs neutral vs high) between-subject design.

The pilot study provides evidence for the conceptualized typology and the differential effects of crowdsourcing task types. Study 1A reveals that product-related crowdsourcing tends to have a more substantial impact than communication-related crowdsourcing on how customer-oriented consumers perceive a company. Study 1B validates the results of Study 1A in a different product category and population sample. Study 2 shows that the differential customer-orientation effect is mediated by the perceived cost of implementing the crowdsourcing outcome and unravels the differences in consumers’ purchase and campaign participation intentions depending on task type. Study 3 highlights that the customer-orientation effect attenuates as company credibility increases.

This research contributes to the crowdsourcing literature by categorizing the various types of crowdsourcing campaigns companies undertake and revealing the differential impact of the different types of crowdsourcing campaigns on consumers’ perceptions and behavioral intentions. In doing so, this research converges two lines of consumer research on crowdsourcing, i.e. product- and communication-related crowdsourcing. The findings add to the debate over the returns from research and development (R&D) versus advertising and extend it from marketing strategy to crowdsourcing literature.

The findings highlight the importance of choosing specific task types for crowdsourcing and lead to practical recommendations on designing crowdsourcing campaigns to maximize their benefits to crowdsourcing brands.

To the best of the authors’ knowledge, this is the first study that differentiates crowdsourcing task types and compares their effectiveness from a consumer perspective.

The purpose of this paper is to evaluate the effectiveness of a novel method for performing content analysis in managerial research – crowdsourcing, a system where geographically distributed workers complete small, discrete tasks via the internet for a small amount of money.

The authors examined whether workers from one popular crowdsourcing marketplace, Amazon's Mechanical Turk, could perform subjective content analytic tasks involving the application of inductively generated codes to unstructured, personally written textual passages.

The findings suggest that anonymous, self-selected, non-expert crowdsourced workers were applied content codes efficiently and at low cost, and that their reliability and accuracy compared to that of trained researchers.

The authors provide recommendations for management researchers interested in using crowdsourcing most effectively for content analysis, including a discussion of the limitations and ethical issues involved in using this method. Future research could extend the findings by considering alternative data sources and coding schemes of interest to management researchers.

Scholars have begun to explore whether crowdsourcing can assist in academic research; however, this is the first study to examine how crowdsourcing might facilitate content analysis. Crowdsourcing offers several advantages over existing content analytic approaches by combining the efficiency of computer-aided text analysis with the interpretive ability of traditional human coding.

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 purpose of this paper is to explore how social value orientation and domain knowledge affect cooperation levels and transcription quality in crowdsourced manuscript transcription, and contribute to the recruitment of participants in such projects in practice.

The authors conducted a quasi-experiment using Transcribe-Sheng, which is a well-known crowdsourced manuscript transcription project in China, to investigate the influences of social value orientation and domain knowledge. The experiment lasted one month and involved 60 participants. ANOVA was used to test the research hypotheses. Moreover, inverviews and thematic analyses were conducted to analyze the qualitative data in order to provide additional insights.

The analysis confirmed that in crowdsourced manuscript transcription, social value orientation has a significant effect on participants’ cooperation level and transcription quality; domain knowledge has a significant effect on participants’ transcription quality, but not on their cooperation level. The results also reveal the interactive effect of social value orientation and domain knowledge on cooperation levels and quality of transcription. The analysis of the qualitative data illustrated the influences of social value orientation and domain knowledge on crowdsourced manuscript transcription in detail.

Researchers have paid little attention to the impacts of the psychological and cognitive factors on crowdsourced manuscript transcription. This study investigated the effect of social value orientation and the combined effect of social value orientation and domain knowledge in this context. The findings shed light on crowdsourcing transcription initiatives in the cultural heritage domain and can be used to facilitate participant selection in such projects.

The aim of this research was to identify the importance of trust as a determinant of participants’ behaviour and the weight of different motivational factors that enhance the amount and the quality of contribution.

Quantitative research methods (online survey of 450 respondents and content analysis of 250 reviews) were applied on a Romanian crowdsourcing platform founded in 2008, with the mission to help potential tourists to take the most informed decision in their travel choices.

The data collected showed that the majority of the active members have a positive outlook over their experience within the community, admitting its trustworthy characteristics. The findings show that most of the top-rated members of the community were not motivated by material rewards such as money or prizes, but rather by socially related factors or by individual factors (positive feedback through comments or acquiring knowledge).

The findings cannot be generalised to other crowdsourcing models, which are subject to different task designs, outcomes, local contexts and even functionalities.

The results of this research can contribute to the design and implementation of customer-centred platforms, which might represent a way of development of organisational communication in the future.

The research posits that individuals’ experience within colloraborative crowdsourcing communities needs to be meaningful, as participants act based on a reciprocity norm, of giving something back to the community which is useful for fulfilling their own information-seeking purposes.

Firms increasingly rely on both external and internal crowdsourcing to capture ideas more broadly and enhance innovative problem-solving. Especially in internal crowdsourcing, knowledge sharing that contributes to develop or further the understanding of the problem the idea is focused on solving can take place between critical employees, and in that way improve ideas generated by others. This far, most crowdsourcing practices have focused on identifying solutions to proposed problems, whereas much less is known about how crowds can be used to share problem-related knowledge. There is thus an untapped potential in leveraging crowds not just to generate solution-oriented ideas but also to share knowledge to improve ideas and even to reframe problems. This paper aims to explore the effect of problem- and solution-related knowledge sharing in internal crowdsourcing for idea development.

Data on ideas and comments were collected from an idea management system in a Swedish multinational company. The investigation captures the influences of the problem- and solution-related knowledge sharing on ideas based on content analysis and logistic regression analysis.

The results from this study show that sharing knowledge related to solutions in idea development impacts idea acceptance positively, whereas sharing knowledge related to problems in idea development has a negative effect on the likelihood of idea acceptance and these effects of knowledge sharing are moderated by the active author responses.

This research provides managerial implications for firms to deliberately manage knowledge sharing in peer communities in internal crowdsourcing, especially by providing suggestions on problem reframing and solution refining for ideas.

The results contribute to existing theory in terms of extending the view of crowdsourcing in ideation to include how crowds contribute to the development of the problem and the solution during the development of ideas and providing new insights on knowledge sharing in internal crowdsourcing based on problem-solving theory.

The purpose of this paper is to explore the underlying mechanisms through which interactivity and fairness perception impart influence on solvers’ continuance intention in crowdsourcing contest settings.

On basis of self-determination theory and social exchange theory, this study focuses on the mediating roles of motivation and platform trust to explain the underlying influence processes of interactivity and fairness perception on continuance intention. A sample of 306 solvers was obtained from an online crowdsourcing platform through two separated surveys. The hypotheses were tested using the partial least squares method and bias-corrected bootstrapping method.

The empirical results indicate that motivation and platform trust together fully mediate the effect of interactivity on continuance intention, and the effect of fairness perception on continuance intention is also fully mediated by motivation and platform trust. While motivation is found to have a stronger mediating effect than platform trust does.

This study contributes to the crowdsourcing research by figuring out the pathway through which interactivity and fairness perception influence solvers’ continuance intention.