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Marginality and Team Building in Collaborative Crowdsourcing

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Abstract

Existing studies on crowdsourcing have focused on analyzing isolated contributions by individual participants and thus collaboration dynamics among them are under-investigated. The value of implementing crowdsourcing in problem solving lies in the aggregation of wisdom from a crowd. This study examines how marginality affects collaboration in crowdsourcing. With population level data collected from a global crowdsourcing community (openideo.com), this study applied social network analysis and in particular bipartite exponential random graph modeling (ERGM) to examine how individual level marginality variables (measured as the degree of being located at the margin) affect the team formation in collaboration crowdsourcing. Significant effects of marginality are attributed to collaboration skills, number of projects won, community tenure, and geolocation. Marginality effects remain significant after controlling for individual level and team level attributes. However, marginality alone cannot explain collaboration dynamics. Participants with leadership experience or more winning ideas are also more likely to be selected as team members. The core contribution this research makes is the conceptualization and definition of marginality as a mechanism in influencing collaborative crowdsourcing. This study conceptualizes marginality as a multidimensional concept and empirically examines its effect on team collaboration, connecting the literature on crowdsourcing to online collaboration.

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... Scholars argue that it is diversity in a crowd that makes crowdsourcing an innovative problem-solving model (Wang, 2020). However, few studies have examined how team diversity affects crowdsourcing outcomes (see Bayus, 2013 for an exception). ...
... In collaborative crowdsourcing, participants engage interactions in which different ideas and perspectives are discussed and integrated to achieve a collective solution (Wang, 2020). Collaborative crowdsourcing emphasizes the process of participants collaboratively cocreating innovative solutions through offering alternatives, modifying proposals, and generating collective ideas (Majchrzak & Malhotra, 2013). ...
... In crowdsourcing, experience diversity can be derived not only from individuals winning ideas but also winning a variety of challenges. Winning more ideas indicates experience in simply winning more; while winning more challenges would indicate skills in heterogeneous domains and also in navigating the crowdsourcing platform (Wang, 2020). These two dimensions of winning are related but entail different experience diversity. ...
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Whereas recent research on organizational innovation suggests that there is an ecology of roles supporting the innovation process, the majority of network research has concentrated on the role of inventors. In this paper, we contribute to research on organizational innovation by studying the social structural conditions conducive to individuals supporting, facilitating, and promoting the innovativeness of their colleagues-a role we refer to as catalysts of innovation. We consider an individual's network position and the type of knowledge available to her through her network as key enabling conditions. We argue that the unique configuration of having access to diverse knowledge through a closed network enables individuals to act as innovation catalysts. Based on a study of 276 researchers in the research and development division of a large multinational high-tech company, we find strong support for our prediction and demonstrate that catalysts make important contributions to the innovative outputs of other researchers in terms of their colleagues' patent applications.
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For a country to become fully democratic, the majority of the population needs to be involved in the politics of that country. This requires people to be aware of what is happening, and to be able to participate in the country's political processes. VotoSocial is a crowdsourcing system launched during the 2013 Honduran government elections. It retrieved the official polling table records in digitized form from the Supreme Electoral Tribunal (the Government's elections authority) and provided them to the Internet community to be counted and the digitizations verified. VotoSocial was thereby able to verify the accuracy of the official polling results. We found no evidence of fraud in the digitization process, but statistical analysis revealed a data behavior usually associated with incremental fraud in an electoral process. VotoSocial shows that social media-powered crowdsourcing systems can increase a population's political awareness during elections, thus providing a motive to build similar platforms in other countries with political systems marked by electoral fraud.
Article
In this study we investigate the interplay between knowledge workers’ formal project team memberships and their informal interactions from a multilevel network perspective. Conceptualizing knowledge workers’ affiliation with project teams as a membership network and their interactions as an advice network, we discuss how shared project team memberships as well as multiple memberships influence patterns of informal exchange in knowledge-intensive organizations. To empirically determine the impact of formal organization on informal exchange we apply exponential random graph models for multilevel networks to relational data collected on 434 R&D employees working on 218 project teams in a high-tech firm in Germany. Our results show that employees sharing project memberships create advice ties to each other but do not exchange advice reciprocally. In addition, we find a negative relationship between having a high number of project memberships and informally seeking or providing advice.
Article
In this paper, we review the development of dependence structures for exponential random graph models for bipartite networks, and propose a hierarchy of dependence structures within which different dependence assumptions may be located. Based on this hierarchy, we propose a new set of model specifications by including bipartite graph configurations involving more than four nodes. We discuss the theoretical significance of the various effects that the extended models afford, and illustrate application of this hierarchy of models to several bipartite networks related to the political mobilization in Brazil in the early 1990s (Mische, 2007).
Article
This study investigates the self-assembly mechanisms of ad hoc project teams using a bipartite network perspective. Individuals and projects are modeled as two types of nodes and team membership as relations between them. This approach enables us to investigate factors that impact voluntary team assembly at the individual, dyadic, and team levels simultaneously. Using Exponential Random Graph Models (ERGM/p*), we study players' combat teams in a Massively Multiplayer Online Role-Playing Game (MMORPG) as a case of self-assembled project teams. Empirical results show that individuals are motivated to join ad hoc teams to complete difficult projects but not projects with long durations. We also found that individuals tend to collaborate with specific teammates who have complementary skills, those who have similar age or skill level, and those who are affiliated with the same organizational entity.
Article
Crowdsourcing for innovation is typically conducted as an "innovation challenge." Despite the popularity of innovation challenges, there appears to be a growing consensus that innovation challenges do not succeed at generating solutions with competitive advantage potential. This article presents three ways in which managers can assure that their innovation challenges are fruitful: foster different crowd roles to encourage contribution diversity; offer knowledge integration instructions and dual incentives; and offer explicit instructions for sharing different types of knowledge. (I nnovation challenges, also known as innovation tournaments and idea con-tests, are a manifestation of crowdsourcing. 1 When running an innovation challenge, a company posts an open call on the Web to solicit solutions from a diverse range of individuals. For example, GE's Innovation Challenge soli-cited new technologies for its sustainability product line and a Lego Challenge asked the public to suggest unique Lego products as new revenue streams. By 2017, over half of consumer goods producers are projected to employ crowdsourcing for 75% of their consumer innovations. 2
Conference Paper
Following the recent remarkable successes of crowdsourcing, there have been attempts to apply it to design. However a design problem is often too complex and difficult to break down into simpler, distributable tasks as required by the conventional crowdsourcing model. In this paper, we present Crowd vs. Crowd (CvC), a novel design crowdsourcing method, where several design teams made up of designers and crowd compete with each other. In each team, a designer coordinates effective communication between the crowd members and takes responsibility for the final design output, and the crowd contributes at different stages of design. We conducted an initial evaluation of CvC in comparison with other collaborative design methods, and found that: CvC can attract more people to participate; the crowd can make useful contribution in CvC; CvC can produce competent design outputs. We then applied CvC to two real-life design problems: first, designing a new logo for a university department; second, for a small tech company. With quantitative and qualitative analyses on these applications, we observed that the elements of competition and collaboration helped to sustain the crowd's motivation to participate, and to produce quality design outcomes with higher level of satisfaction for the stakeholders.
Article
Interdisciplinary teams are assembled in scientific research and are aimed at solving complex problems. Given their increasing importance, it is not surprising that considerable attention has been focused on processes of collaboration in interdisciplinary teams. Despite such efforts, we know less about the factors affecting the assembly of such teams in the first place. In this paper, we investigate the structure and the success of interdisciplinary scientific research teams. We examine the assembly factors using a sample of 1103 grant proposals submitted to two National Science Foundation interdisciplinary initiatives during a 3-year period, including both awarded and non-awarded proposals. The results indicate that individuals’ likelihood of collaboration on a proposal is higher among those with longer tenure, lower institutional tier, lower H-index, and with higher levels of prior co-authorship and citation relationships. However, successful proposals have a little bit different relational patterns: individuals’ likelihood of collaboration is higher among those with lower institutional tier, lower H-index, (female) gender, higher levels of prior co-authorship, but with lower levels of prior citation relationships.
Article
After many years of developing in small islands scattered around different disciplines, small group research has reached a point where interdisciplinary scholarship has the potential to foster major progress. The goal of this special issue on interdisciplinary perspectives is to capitalize on the theoretical advances made over the last 50 years by synthesizing and integrating models and theories on small groups proposed by various disciplines into a set of general theoretical perspectives. In this introduction, the authors identify nine general theoretical perspectives from which small groups have been examined: the psychodynamic, functional, temporal, conflict-power-status, symbolic-interpretive, social identity, social-evolutionary, social network, and feminist perspectives. This article summarizes each theoretical perspective briefly and then offers some observations about the perspectives as a whole. Articles describing three of these interdisciplinary perspectives appear in this special issue, and four other perspectives will be introduced in the next issue.
Article
Similarity breeds connection. This principle - the homophily principle - structures network ties of every type, including marriage, friendship, work, advice, support, information transfer, exchange, comembership, and other types of relationship. The result is that people's personal networks are homogeneous with regard to many sociodemographic, behavioral, and intrapersonal characteristics. Homophily limits people's social worlds in a way that has powerful implications for the information they receive, the attitudes they form, and the interactions they experience. Homophily in race and ethnicity creates the strongest divides in our personal environments, with age, religion, education, occupation, and gender following in roughly that order. Geographic propinquity, families, organizations, and isomorphic positions in social systems all create contexts in which homophilous relations form. Ties between nonsimilar individuals also dissolve at a higher rate, which sets the stage for the formation of niches (localized positions) within social space. We argue for more research on: (a) the basic ecological processes that link organizations, associations, cultural communities, social movements, and many other social forms; (b) the impact of multiplex ties on the patterns of homophily; and (c) the dynamics of network change over time through which networks and other social entities co-evolve.
Article
This article provides an introductory summary to the formulation and application of exponentialrandomgraphmodels for socialnetworks. The possible ties among nodes of a network are regarded as random variables, and assumptions about dependencies among these random tie variables determine the general form of the exponentialrandomgraphmodel for the network. Examples of different dependence assumptions and their associated models are given, including Bernoulli, dyad-independent and Markov randomgraphmodels. The incorporation of actor attributes in social selection models is also reviewed. Newer, more complex dependence assumptions are briefly outlined. Estimation procedures are discussed, including new methods for Monte Carlo maximum likelihood estimation. We foreshadow the discussion taken up in other papers in this special edition: that the homogeneous Markov randomgraphmodels of Frank and Strauss [Frank, O., Strauss, D., 1986. Markov graphs. Journal of the American Statistical Association 81, 832–842] are not appropriate for many observed networks, whereas the new model specifications of Snijders et al. [Snijders, T.A.B., Pattison, P., Robins, G.L., Handock, M. New specifications for exponentialrandomgraphmodels. Sociological Methodology, in press] offer substantial improvement.
This article reviews how current social network analysis might be used to investigate individual and group behavior in sporting teams. Social network analysis methods permit researchers to explore social relations between team members and their individual-level qualities simultaneously. As such, social network analysis can be seen as augmenting existing approaches for the examination of intra-group relations among teams and provide detail of team members' informal connections to others within the team. Social network analysis is useful in addressing the issue of interdependencies in the data inherent in team structures. Social network terms are introduced and explained by way of an example team, software and resources are discussed, and a statistical approach to social network analysis is introduced.
Article
Personal network analysts usually want to know which types of people are in such network, what kinds of relationships they contain, and what kinds of resources flow through different kinds of networks. These research interests affect how analysts define populations, approach gathering data, and obtain information. Analysts want to identify ties wherever they lead, without being confined to groups, neighborhoods or organizations. All of the articles in this issue use the network paradigm to analyze community and social support. The article's authors did more than 100 interviews with newspapers, magazines, television and radio. This special issue builds on classical personal network research into community and social capital. The basis of this special issue are the three papers presented at a personal network session of the 2004 Sunbelt Social Network Conference. The articles reflect the continuing personal network concern with the "community question" about the interrelationship between large-scale structural phenomena (such as urbanization and technological change) and the composition, structure and content of interpersonal relationships. (PsycINFO Database Record (c) 2012 APA, all rights reserved)
Article
The increased use of teams in organizations, coupled with an increasingly diverse workforce, strongly suggests that we should learn more about how team diversity affects functioning and performance. The purpose of this study was to explore the differential impact of surface-level diversity (gender, ethnicity), deep-level diversity (time urgency, extraversion), and two moderating variables (team orientation, team process) on relationship conflict over time. Hypotheses were tested by tracking 45 student project teams in a longitudinal design. Results revealed that team orientation and team process moderated the diversity–conflict link. Specifically, team orientation helped to neutralize the negative effects of surface-level (gender) diversity on relationship conflict. In a similar manner, team processes worked to weaken the deleterious effects of deep-level diversity (time urgency) on relationship conflict. In addition, relationship conflict resulted in lower perceived performance by team members. Copyright © 2004 John Wiley & Sons, Ltd.
Article
A number of factors cause individuals to use diverse strategies to solve problems. This paper presents a methodology for examining these differences in strategy. Verbal protocols are elicited to collect data on the cognitive processes occurring during problem solving. These data, codified into propositional representations, and non-parametric statistical comparisons are then used to evaluate the significance of strategy differences. These strategies are then mapped with dynamical graphs, with which we examine the task-independent and the task-specific cognitive representations the participants used. As an illustrative example we apply this methodology to study the influence of two contributing factors, professional training and national culture, on the strategies adopted by professionals to solve a complex and ill-structured problem (hunger in a country). The problem-solving strategies of professionals from different countries and trained in architecture, engineering, law or medicine are analyzed to show some intriguing differences in the general strategies adopted by individuals belonging to different professions, and the outcomes from using these strategies.
Article
Appointing a good leader to the position of team manager and having competent workers collaborate as team members is a key to success in business activities of an enterprising institution. The traditional methodologies of human resource management have defined the required abilities for team managers and team members, and evaluated those abilities of employees. However, it is difficult to consider those abilities systematically in practice. In addition, the current management paradigm undergoes rapid transitions into knowledge management. In step with these trends, this study presents a framework for analyzing the knowledge of the candidates for managers and team members for the new team, and proposes a genetic algorithm and social network measures for choosing a team manager and team members. A prototype was built for testing the feasibility of the model. The testing data are from an R&D institute’s human resource management department. The results show that our proposed approach is a quantitative and systematic method for selecting proper personnel for appropriate teams.
Article
A substantial amount of economic activity involves problem solving, yet economics has few, if any, formal models to address how agents of limited abilities find good solutions to difficult problems. In this paper, we construct a model of heterogeneous agents of bounded abilities and analyze their individual and collective performance. By heterogeneity, we mean differences in how individuals represent problems internally, their perspectives, and in the algorithms they use to generate solutions, their heuristics. We find that while a collection of bounded but diverse agents can locate optimal solutions to difficult problems, problem solving firms can exhibit arbitrary marginal returns to problem solvers and that the order that problem solvers are applied to a problem can matter, so that the standard story of decreasing returns to scale may not apply to problem solving firms. Journal of Economic Literature Classification Numbers: C6, D2.
Article
The global scale and distribution of companies have changed the economy and dynamics of businesses. Web-based collaborations and cross-organizational processes typically require dynamic and context-based interactions between people and services. However, finding the right partner to work on joint tasks or to solve emerging problems in such scenarios is challenging due to scale and temporary nature of collaborations. Furthermore, actor competencies evolve over time, thus requiring dynamic approaches for their management. Web services and SOA are the ideal technical framework to automate interactions spanning people and services. To support such complex interaction scenarios, we discuss mixed service-oriented systems that are composed of both humans and software services, interacting to perform certain activities. As an example, consider a professional online support community consisting of interactions between human participants and software-based services. We argue that trust between members is essential for successful collaborations. Unlike a security perspective, we focus on the notion of social trust in collaborative networks. We show an interpretative rule-based approach to enable humans and services to establish trust based on interactions and experiences, considering their context and subjective perceptions.
Conference Paper
Crowdsourcing is emerging as the new on-line distributed problem solving and production model in which networked people collaborate to complete a task. Enterprises are increasingly employing crowdsourcing to access scalable workforce on-line. In parallel, cloud computing has emerged as a new paradigm for delivering computational services, which seamlessly interweave physical and digital worlds through a common infrastructure.This paper presents a sample crowdsourcing scenario in software development domain to derive the requirements for delivering a general-purpose crowdsourcing service in the Cloud. It proposes taxonomy for categorization of crowdsourcing platforms, and evaluates a number of existing systems against the set of identified features. Finally, the paper outlines a research agenda for enhancing crowdsourcing capabilities, with focus on virtual team building and task-based service provisioning, whose lack has been a barrier to the realization of a peer-production model that engages providers from around the world.