Abstract
Partly fueled by the pervasiveness of information technologies that facilitate the broadcasting of problems to crowds, and by anecdotal examples of phenomenally high-value solutions from outsourcing some problems to crowds, growth in the research and practice of crowdsourcing for problem solving has been remarkable. Research streams have been emerging in different disciplines. In this introduction to the volume, we introduce twelve chapters by scholars—from different disciplines—who explore interesting topics from some of these emerging research streams. The chapters fall into different groups distinguished by whether value is created and captured via tournament-based, collaboration-based, or hybrid crowdsourcing activities. We also offer future research directions and conclusions.
For decades, transaction cost economics, the problem-solving view, and other theoretical perspectives have been used to understand, explain, and make predictions about why and when a firm would want to solve a problem through hierarchies, hybrids, or markets (e.g., Williamson, 1985, 2002; Nickerson & Zenger, 2004). In that research, getting a problem solved through “markets” has meant that a focal firm finds someone whom it believes can solve the problem, and designates that someone—through an ex ante contract or other agreement/commitment specific to the problem—as the contractor to solve the problem (Afuah, 2018a). The challenge is that, for many problems, finding that someone to solve a problem can be as difficult as finding a needle in a haystack (Afuah & Tucci, 2012; Afuah, 2016). Even more challenging is the fact that some problems require a collection of solvers that the focal firm cannot identify, ex ante, to collaborate with and solve the problem.
This is where crowdsourcing—a portmanteau of the words “crowd” and “outsourcing,” as in outsourcing to a crowd rather than a designated contractor (Howe, 2006)—comes in. Because it can be difficult for focal firms, individuals, or even nations to identify, ex ante, who can solve a problem, they broadcast the problem to a crowd so that potential solvers can self-select to solve it with no ex ante agreements/commitments to solving the problem (Afuah & Tucci, 2012).
Partly fueled by the pervasiveness of information technologies that facilitate the broadcasting of problems to crowds, and by anecdotal examples of phenomenally high-value solutions from outsourcing some problems to crowds, growth in the research and practice of crowdsourcing has been remarkable. Importantly, different crowdsourcing research streams have emerged. Some scholars see crowdsourcing as an online phenomenon (e.g., Brabham, 2008), while others see it as a governance mechanism that goes back to at least the Longitude Prize of 1714, with information technology only serving as an enabler (Afuah & Tucci, 2012). Yet others see crowdsourcing as a mechanism for selling and buying on-demand labor that has the potential to disrupt the way firms create and capture value. Symbolic of these differences are the different research silos that explore crowdsourcing and the different terms that have been used to describe the phenomenon. Authors have used terms such as broadcast search, distributed innovation, crowdfunding, collective intelligence, innovation tournaments, innovation contests, and so on to describe crowdsourcing.
Fortunately, much research has been conducted on outsourcing and crowds— research that can help us to better theorize about crowdsourcing. In particular, much has been written about using tournaments to get crowds to solve problems, how crowds collaborate in solving problems, and what motivates crowds to solve problems—that is, much has been written about using crowds to create and capture value. The chapters in this volume fall into different groups, distinguished by whether value is created and captured via tournament-based, collaboration-based, or hybrid crowdsourcing activities.
The papers in Part I introduce the reader to crowdsourcing and the crowds and communities that are foundational to the phenomenon. More specifically, Afuah (2018a) presents a crowdsourcing primer and framework with the goal of introducing scholars to some of the constructs and concepts that academics may find useful in exploring theoretically interesting research questions. Viscusi & Tucci (2018) examine some important characteristics of crowds such as the goal orientation and the “seriality” of interactions and activities, thus clarifying how crowds may differ from communities and other kinds of collective entities. This difference is particularly relevant for identifying which kind of collective entity would be most effective when designing crowdsourcing initiatives, especially considering the different kinds of investments that might be required by the different kinds of crowds and communities.
West & Sims (2018) focus on the role that crowds and communities play during open innovation, especially focusing on problem formulation in innovation contests and the role of managerial actions in facilitating it. To this end, the authors analyze multiple case studies to inductively build a theoretical framework defining mechanisms for seeker firms’ formulations of sharable problems in innovation contests. The last chapter in Part I, by Butticè et al. (2018), provides an extensive overview of crowdfunding, which is one of the most popular forms of crowdsourcing (if one conceptualizes a lack of funding as a problem to be solved). In particular, the chapter specifies the main characteristics of crowdfunding and how they relate to crowdfunding success.
The papers in Part II of the volume are about tournament-based crowdsourcing and extend the arguments discussed in Part I. In the first paper in the group, Wallin et al. (2018) remind us that problem formulation is so fundamental to problem solving that—for some problems—formulation can be more important than the solution. Using seven case studies, they detail rare accounts of the intra-organizational activities and implications of problem formulation for contests. Ranade & Varshney (2018) consider the other side of the spectrum of crowdsourcing contests, focusing on the utility generated for different types of tasks, including but not limited to idea generation. In particular, the authors identify a set of relevant factors for crowdsourcing contest design such as knowledge about the relative strengths of the participating solvers/workers and their awareness of the strength of internal competitors.
The papers in Part III are about collaboration-based crowdsourcing. Cordella et al. (2018) focus on the public sector to understand how and why co-production can be a valuable solution to delivering public services, improving both their public value and the administrative activities behind them. The authors propose that collaboration-based crowdsourcing in the public sector implies a change of perspective from focusing merely on the production processes of public services to first targeting public value creation. Levina & Fayard (2018) consider digital platforms enabling crowdsourcing contests and compare how consulting companies approach the translation and integration of diverse ideas and expertise to how they are addressed in innovation-focused crowdsourcing platforms. In particular, the authors analyze the role of boundary-spanning practices for knowledge collaboration, necessary due to the complexity of the task in crowdsourcing exercises where many new boundaries must be managed, in comparison with, e.g., online communities (cf. Faraj et al., 2011).
To conclude Part III, Šundić & Leitner (2018) analyze cases from A1 Telekom Austria to understand co-creation in both public and internal crowdsourcing initiatives, thus also contributing to the literature on internal crowdsourcing (cf. Zuchowski et al. 2016). The three approaches proposed comprise: (1) the open, external co-creation approach with customers and users of the A1 Support Community; (2) the semi-open, internal tool-based co-creation approach with selected employees; and (3) the internal offline co-creation approach with employees.
The papers in Part IV are about hybrid crowdsourcing—that is, they explore questions that involve both tournament- and collaboration-based crowdsourcing. Afuah (2018b) argues that simultaneous competition to solve modules of a decomposable problem and collaboration to aggregate the module solutions produce a higher-value solution to the problem than collaboration alone. Just as important, simultaneous cooperation to reduce crowdsourcing frictions, and competition to solve a non-decomposable problem yield a higher-value solution than competition alone. Horn et al. (2018) take us into the world of prediction markets, and demonstrate how these markets can be used as a crowdsourcing mechanism to get crowds that will more effectively solve problems. More specifically, they demonstrate that when prediction markets are used in getting internal crowds to solve a problem, the crowd can outperform external crowds in solving some problems.
To round out the book, Curto-Millet & Nisar (2018) review the extent to which stakeholder theory might be applicable to understanding the ethical dimension of crowdsourcing. They discuss many of the ethical consequences of crowdsourcing and propose recommendations on how stakeholder theory can provide a response to such ethical dilemmas, and they provide one of the first attempts to debate the role of stakeholder theory for future research directions in the context of crowdsourcing.
As shown in Table 1.1, we have identified seven key cross-cutting topics from the chapters in this book that represent potential research themes and challenges for disciplines such as Innovation Management and Strategy, but also Organization Science, Political Science, and Information Systems. The first theme draws out some of the distinctions and similarities between crowds and communities, what they have in common, and how to take advantage of some of the differences for firms’ innovation processes. The second theme is about the relation between open innovation and crowdsourcing, how companies might think about crowdsourcing as part of their open innovation portfolio, and when crowdsourcing might be different from open innovation. The third theme has to do with the differences and commonalities between internal and external crowds and many of the nuances of using external and internal agents in different contexts.
Table 1.1. Cross-cutting themes developed in this book.
| Cross-cutting topic | Chapters | Disciplinary areas |
|---|---|---|
| 1. The relation and difference between crowds and communities |
• Innovation Management
• Organization Science
• Information Systems
|
|
| 2. The relation and difference between open innovation and crowdsourcing |
• Chapter 2 (Afuah)
• Chapter 4 (West & Sims)
• Chapter 9 (Levina & Fayard)
• Chapter 13 (Curto-Millet & Nisar)
|
• Innovation Management
• Organization Science
• Strategy
|
| 3. The advantages and disadvantages of internal versus external crowds; inter- and intra-organizational processes to facilitate crowdsourcing |
• Chapter 2 (Afuah)
• Chapter 9 (Levina & Fayard)
• Chapter 6 (Wallin et al.)
• Chapter 10 (Šundić & Leitner)
• Chapter 12 (Horn et al.)
|
• Innovation Management
• Organization Science
• Information Systems
• Strategy
|
| 4. The different ways to organize crowds from the common sense understanding of crowdsourcing as an input into the problem-solving process to co-production and co-creation |
|
• Innovation Management
• Organization Science
• Political Science
|
| 5. Governance of and value capture from crowdsourcing |
• Chapter 11 (Afuah)
• Chapter 13 (Curto-Millet & Nisar)
|
• Strategy
• Organization Science
• Ethics
|
| 6. “Non-traditional problems” solved by crowdsourcing, from monetary value in crowdfunding to public value in the public sector |
• Innovation Management
• Strategy
• Political Science
• Entrepreneurship
|
|
| 7. The role of information and information systems capacity in designing and managing crowdsourcing |
|
• Innovation Management
• Information Systems
|
The fourth cross-cutting theme is concerned with an exploration of the co-production and co-creation processes enabled by crowdsourcing and how they might differ from more traditional problem-solving approaches. The fifth theme is about capturing value from crowdsourcing: who are the stakeholders, how is the contest governed, how is the contest designed to increase overall value, and how is the value shared? If crowdsourcing is about problem solving, the sixth theme revolves around “non-traditional” problems to be solved and expands our repertoire of what constitutes effective contexts of crowdsourcing. Finally, the seventh cross-cutting theme is about the role of information and how information systems can be used in designing crowdsourcing exercises. Table 1.1 links each of these themes to multiple chapters as a convenient cross-reference and suggests different disciplines to which the themes might be relevant.
Together, these chapters provide critical elements for pursuing research in crowdsourcing, and constitute an excellent starting point for crowdsourcing scholarship. Because the research opportunities in crowdsourcing are inherently large, and there are only twelve further chapters in this volume, there are still many research gaps and therefore many opportunities for future research. These gaps fall within four generic domains. First, although the volume is entitled Creating and Capturing Value through Crowdsourcing, there is still a bigger emphasis in the volume on value creation relative to value capture. This asymmetrical attention to value creation at the expense of value capture in crowdsourcing literature has been recognized for a while, but to date little has been accomplished towards addressing it (Afuah & Tucci, 2013; Bloodgood, 2013). Future research could more explicitly focus on value capture questions, especially the roles of complementary assets and business models (Teece, 1986; Massa et al., 2017).
Second, little attention has been given to date to how seekers could organize to better formulate, delineate, and broadcast problems, so as to evaluate and assimilate the solutions from crowds. We know very little about the types of organizational structures, systems, culture, and strategies that seeker organizations may want to pursue to increase their chances of creating and capturing superior value via crowdsourcing. Third, although internal crowdsourcing research has recently attracted some interest (including at least two of the chapters in this volume), much of the attention has been focused on external crowdsourcing. Future research could tease apart many of the nuances that distinguish internal from external crowds. Fourth, these chapters, like most crowdsourcing research so far, have focused largely on the advantages of the phenomenon, with less of an emphasis on its pitfalls. Future research could look into the disadvantages of crowdsourcing and how they might be mitigated, or the contingencies that might distinguish success from failure.
Fifth and most important, good research explains and predicts. However, as mentioned previously, most of the chapters in this book are conceptual, qualitative, or descriptive, focusing on the “pre-theorizing” that is natural at this stage of evolution of the field. The emphasis in this book was not on clearly defining constructs, developing and testing hypothesized relationships, or on linking constructs with causal logic. The full potential—both scientific and practical—of crowdsourcing is likely to be attained when researchers take the field to the next level and explore explanation and prediction. Luckily, as the identified research gaps suggest, there are plenty of opportunities to write papers that make meaningful contributions to advancing knowledge in crowdsourcing.
We hope this volume stimulates even more interest in the topic so that our research community can grow into a large, open crowd, teeming with excitement about crowdsourcing’s potential!