Problems,theories,and governing the crowd

Abstract

Research and recommendations on innovation through crowdsourcing are diverse and often contradictory, providing little guidance on when, where, and under what conditions to use various forms of crowdsourcing. This article responds by arguing that focal economic actors, as organization designers, catalyze innovation when they efficiently match attributes of the problem or attributes of a domain of problems to modes of organizing problem finding and solution search. Four basic insights drive this approach. First, sourcing from the crowd is, fundamentally, a governance choice. Second, crowdsourcing is an amalgam of both problem finding and problem solving through the crowd. Third, the attributes of focal actors, including the theories of value creation they possess, shape problem formulation, solution-search, and the governance of these processes. Fourth, the act of defining problems reveals, and often generates, a vast residual domain of problems—often unseen by the focal economic actor—that is implicitly deferred to the crowd to find and potentially solve.

Keywords

crowdsourcing governance knowledge creation managerial cognition value creation vertical integration

Scholarly advice on how to accelerate value-generating innovation is abundant and diverse, encompassing organizational levers that range from the organizational structure and boundaries to team composition and process. Unfortunately, this advice is often fully contradictory. For instance, some studies highlight the merits of small firms in fueling innovation (Ács and Audretsch, 1990; Schumpeter, 1934), while others highlight large firms as the preferred choice (Cohen and Klepper, 1996; Schumpeter, 1942; Tether, 1998). Some studies highlight the virtues of integrating innovation as a means of accelerating it (see review in Stanko and Calatone, 2011; Zirpoli and Becker, 2011), while others point to the merits of outsourcing (Chesbrough, 2006; Von Hippel, 2005). Finally, some studies tout the merits of diverse teams to fuel innovation (Bantel and Jackson, 1989; Breschi et al., 2003), while others highlight the impediments to innovation that such diversity can create (West, 2002). The latest widely discussed driver of innovation is accessing the crowd. From programming challenges, idea competitions, prediction markets, and innovation contests to the engagement of user communities in product validation and project financing, crowds play an increasingly important role in innovative value creation. Yet, here as well, discussions about how to harness the crowd and the effectiveness of various approaches diverge widely. While some scholars argue that crowd-centric participative practices are crucial in providing advantage to firms seeking to innovate,¹ others take a more measured stance, suggesting that innovation contests and large-scale applications of “the wisdom of the crowd” typically fail to provide competitive advantage for the companies that sponsor them (Armisen and Majchrzak, 2015; McKinsey & Company, 2009).

Contradictory advice and confusing findings leave the individuals tasked with designing organizations to accelerate innovation with surprisingly little guidance, including when, where, and how to access the crowd. We suspect that the varying organizational prescriptions for innovations mentioned above are both correct and incorrect depending on the nature of the innovation being sought, studied, and measured, and that these contingencies also apply to the use of crowds. Unfortunately, largely missing from the innovation literature is a clear taxonomy of innovation types—a taxonomy that then might be predictive of some form of alignment between types of innovation and the use of these various organizational alternatives. When a taxonomy and predictive alignment are absent, innovation researchers are left to advocate and describe rather than provide useful discriminating predictions. Such logic, we argue, is directly applicable to the usefulness of crowds in fueling innovation. While crowdsourcing, amplified by continued advances in information technology, has become an important source of innovation, the boundaries of its useful application remain mostly underexplored. Unless crowdsourcing is some new, always superior mode of organizing innovation that much of the world is yet to discover, or at least yet to discover how to effectively use, the critical question for strategic organization is not whether crowdsourcing is a good idea but, rather, when, where, and under what conditions various kinds of crowdsourcing are effective, efficacious, and efficient.

In this essay, we advocate an approach that adopts Simon’s (1991) unit of analysis, the problem, as a useful basis for generating a classification of innovation types. We present the processes of searching for problems, searching for solutions, and then composing their production and delivery as general steps in a path toward innovative value creation. We then argue that focal economic actors, as organization designers, catalyze value-creating innovation when they efficiently match attributes of the problem or attributes of a domain of problems to modes of organizing problem finding and solution search, including when and how to access the crowd (Felin and Zenger, 2014; Nickerson and Zenger, 2004). We then outline an approach to theory development that predicts when and under what conditions crowdsourcing and its various practices are likely effective, efficacious, and efficient in performing what we view as the key drivers of value creation: finding and solving problems. While developing a full theory is beyond the scope of this article, we attempt to highlight the parameters of a theory that illuminates when economic actors choose to organize search through crowds.

Four basic insights drive our approach to theory development.² First, we argue that sourcing from the crowd is, fundamentally, a governance choice—one of many alternative governance choices. In deciding to utilize a crowd to organize search, an economic actor selects it over an array of alternative governance choices, including vertical integration, collaboration supported by contracts and supply agreements, partnerships, joint ventures, and a potential host of other arrangements designed to support value-creating cooperation.

Second, crowdsourcing is an amalgam of both crowd finding—problem finding through the crowd—and crowd solving—problem solving through the crowd. Economic actors can elect to employ crowds to help an organization find problems, solve problems, or both. This distinction is important for theory development. Prior work has focused rather exclusively on the role crowds play in solving known problems, leaving questions about the potential role the crowd can play in problem finding undertheorized.

Third, attributes of a focal economic actor define both the problems to formulate and solve and the governance choices made in the pursuit of value. Developing a theory of crowd-enabled value creation necessitates an explicit treatment of how the cognitive biases and psychological makeup of focal economic actors (Furr et al., 2016) combine with their mental models/theories/problem representations (Csaszar and Levinthal, 2015; Felin and Zenger, 2009, 2015; Simon, 1991) to influence the decision to enjoin the crowd and design interactions with it.

Fourth, and by extension, these mental representations also define a potentially vast residual domain of problems—often unseen by the focal economic actor—that are typically and implicitly deferred to crowds and other actors outside the firm to first find and then potentially solve. Integrating insights about the crowds and innovation within the problem-finding and problem-solving perspective implies that economic actors are participants in an economy of problem finders and problem solvers, in which sometimes they elect to problem find or problem solve and other times they elect to defer those activities or the implications of those activities to external actors. The choice of which to do when is itself a critical value-seeking governance choice (Mayer and Salomon, 2006; Nickerson and Zenger, 2002).

The article proceeds by reviewing the literature on crowdsourcing and its ability to predict when crowds are used to create valuable knowledge. We then introduce the problem-finding and problem-solving perspective as a pathway to developing theory regarding when and under what conditions crowds may be effective, efficacious, and efficient for value creation. We highlight the value of the problem as a unit of analysis, discuss the need to highlight attributes of the problem or the domain of problem search, and explore the role of a distinctive model of economic actors focused on creatively composing theories that reveal problems and solutions. We conclude by discussing how an economic actor’s capacity to develop theories or problem representations profoundly shapes decisions about when and where, to use the crowd.

Background

Much of the crowdsourcing literature focuses on identifying the phenomenon, detailing how crowds generate new product ideas, support open innovation initiatives, collect geographic content, provide simple services such as text translation or logo design, and generally solve problems relevant to the focal firm. While early work related to crowds highlighted crowd-oriented innovation practices (Laursen and Salter, 2006; Teece, 1986; Urban and Von Hippel, 1988), more recent work has encompassed innovation markets, crowdsourcing, and communities of practice (scholarly surveys of these practices include Dahlander and Gann, 2010; Van de Vrande et al., 2010; West and Bogers, 2011). The practices and boundaries of “the crowd” are open to many definitions, but its various conceptions share a common theme of individuals, communities, or institutions willing to actively participate in the creation of knowledge.

From a theoretical perspective, scholars have described crowds as filling structural holes (Ahuja, 2000), spanning boundaries (Fleming and Waguespack, 2007), and influencing the scope and impact of search for existing knowledge (Laursen and Salter, 2006). Frequently missing from these discussions are two crucial concepts: (1) the reason why a focal economic actor chooses to outsource to a crowd rather than select other plausible organizational alternatives and (2) the costs, competencies, and corresponding boundary conditions associated with crowdsourcing as a vehicle for creating new knowledge rather than merely finding, transmitting, or accessing existing knowledge. Thus, while the literature effectively articulates attributes of the crowd that generate positive innovation outcomes and the important incentives in play (Boudreau and Lakhani, 2013; Boudreau et al., 2011; Huston and Sakkab, 2006, Jeppesen and Lakhani, 2010; Lakhani and Jeppesen, 2007), much less attention has been paid to the role and decision processes of senior leadership tasked with selecting between organizational alternatives such as internal research and development, the adoption of an alliance or joint venture partner, or—more recently—the choice to leverage crowds.

Clearly, a key benefit to crowds is the broad access to knowledge that they provide, with the inherent assumption of more is better (Bongsun et al., 2015; Chesbrough, 2013; Fey and Birkinshaw, 2005; Foss et al., 2011; Leiponen and Helfat, 2010). Yet, research offers few investigations into boundary conditions of crowds, whether diminishing returns to the knowledge that crowds access or an inability of crowds to access or generate the types of knowledge organizations may be required. A few researchers have begun to offer a more comparative and governance-oriented approach to these more open, crowd-focused forms of governing innovation (e.g., Afuah and Tucci, 2012; Lakhani et al., 2012), but this literature remains nascent and has not fully responded to the call for a more “fine-grained, nuanced, and normative approach” (Felin and Zenger, 2014). Fundamentally, we argue that a theory of crowdsourcing requires an understanding of the comparative costs and benefits of alternative modes of organizing problem and solution search as evaluated by a focal economic actor. We contend that to date such a comprehensive theory remains elusive.

Foundations of a theory of crowdsourced value creation

Creating new value and then capturing some portion of it frames the goal of most organizations (Brandenburger and Stuart, 1996). Value creation (which, in our lexicon, differs from the process of imitating value created by others) is an innovative process of discovering what and how to produce and deliver through ongoing processes of problem finding and problem solving (Nickerson et al., 2007). Our focus in this article is to explore the foundations for a theory of sourcing from the crowd the discovery of problems and solutions, in order to predict under what conditions crowdsourcing can contribute to creating value efficiently. Fundamental to our perspective are the assumptions that that new value comes from creating new knowledge, that one particularly valuable type of knowledge informs what and how to produce and deliver, and finally that such knowledge is generated through problem finding and problem solving.

Grounded in this perspective, we draw upon recent scholarly insights that explain and predict when creating knowledge by accessing actors external to a firm is efficacious (e.g., Macher and Boerner, 2012; Nickerson and Zenger, 2004). One entailing implication from this literature is that choosing to harness the crowd to create value is fundamentally a choice concerning governance. Vertical integration, joint ventures, outsourcing, as well as crowdsourcing—to name but a few of the governance alternatives—can be conceptualized as competing organizational modes for creating valuable, new, and innovation-generating knowledge.³ While a comparative governance approach has proven useful in exploring organizational choices for effective problem solving (Felin and Zenger, 2014; Nickerson and Zenger, 2004), the efficient governance of problem finding remains largely unexplored.

Viewing the crowd as an alternative mode of governance theoretically connects and integrates crowdsourcing and its various practices to the broader literature on organizational choice and performance, leading to a more cumulative and consistent theory of organization. A comparative governance perspective for knowledge creation takes its cues from organizational economics, in particular the logic of transactions costs (Williamson, 1985, 1996), and builds on a still emerging problem-finding and problem-solving perspective, which offers a comparative organizational approach to knowledge creation and is consistent not only with transaction cost economics but also the resource-based and capabilities perspectives (Nickerson et al., 2012).

Problem finding and problem solving

The problem-finding and problem-solving perspective builds upon the intersection of two core organizational theories—the behavioral theory of the firm (Cyert and March, 1963; March and Simon, 1958; Simon, 1947, 1982) and transaction cost economics (Williamson, 1975, 1985, 1996). The former provides a foundation with respect to economic actors’ aspirations, cognitive limits of rationality, satisficing, and problem-solving search. The latter contributes comparative institutional analysis and the logic of a discriminating alignment between modes of governance and the attributes of what is being governed: economic exchange in transactions cost economics and the problem in the problem-finding and problem-solving perspective.

Building on these foundational elements, the problem-finding and problem-solving perspective argues that a given firm’s capacity to create and capture value reflects its ability to efficiently govern three key activities: the discovery and framing of problems, the search for their solution, and the composition, delivery, and capture of the value that those solutions reveal. While providing guidance to this latter activity is the focus of transactions cost economics, which can be recast as organizing the formation of necessary investments and then ensuring the capture of some of the envisioned value (Argyres and Zenger, 2012; Foss and Klein, 2005; Williamson, 1975, 1985), the prior two activities involve organizing processes of cognitive search for valuable problems and solutions. Typically, efficient search necessitates exploring beyond the thoughts and cognitive capacity of a single focal actor to access the knowledge and cognitive capacities of others, whether within or outside the organization. The central governance question then becomes how to efficiently organize these processes of collective cognitive search, including the use of the crowd, for either finding problems or solving them.

Four basic tenets of a problem-finding and problem-solving perspective are fundamental to advancing this agenda. First, problems (for problem-solving) and problem domains (for problem-finding) are the central units of analysis, and organizations elevate value creation by composing efficient search for problems and solutions. Second, alternative modes of governing both the search for problems and solutions, including the use of the crowd, differ with respect to their cost and competencies. Economic actors will choose governance modes with the aim of minimizing costs and maximizing likelihood of value creation. Third, the costs and competencies associated with governance choices vary with attributes of the problem and the problem domain. Fourth, economic actors are endowed with problem- and solution-revealing theories (or with a capacity to compose them), but are also burdened by bounded rationality including cognitive biases. Both profoundly shape decisions about how to govern search. Because we theoretically distinguish between problem finding and problem solving as distinct activities (though, see Von Hippel & Von Krogh (2015) for a counterpoint), the governance of each deserves separate discussion and treatment.

Governance, crowds, and problem finding

Karl Popper famously pronounced “all life is problem solving” (Popper 1999). While perhaps not fully descriptive of what constitutes “all life,” the life of an economic actor, whether an individual or a firm, is centrally focused on solving problems—problems that range from customer, client, and user problems to problems of production and delivery. Reflective of this logic, problemistic search has long been a focal element in the behavioral theory of the firm (Cyert and March, 1963). Yet, despite this central focus on problem solving, the search to find problems (or to effectively frame them) is arguably even more central to value creation; or, in Einstein’s (Einstein and Infeld, 1938) famous words, “The framing of a problem is often far more essential than its solution.” Nonetheless, we know comparatively less about this fundamental search process of framing a problem, and how a focal economic actor efficiently governs it.

Prior work in the problem-finding and problem-solving perspective has drawn from Simon (1962) to dimensionalize the attributes of problems, linking problem attributes to approaches for governing problem solving. In particular, this literature has emphasized the complexity of problems, their ill-structuredness, and the hiddenness of knowledge deemed relevant to solving them, and has then matched these problem attributes to various mechanisms for organizing the search for a solution (Felin and Zenger, 2014; Macher, 2006; Nickerson and Zenger, 2004). An expanding literature illuminates a range of governance forms including vertical integration, user communities, crowds, contracts, and joint ventures and how these governance modes match problem attributes (Felin and Zenger, 2014; Lakhani et al., 2012). For instance, complex problems requiring knowledge housed at known locations may be effectively solved within the firm, while well-specified problems requiring knowledge from unknown locations may benefit from problem solving through a crowd.

Our interest here, however, is on understanding how economic actors govern the search for problems themselves, particularly the decision of when to invite and access the crowd to conduct this search. At the outset, we note two interesting observations that are revealed by turning our attention to the search for problems themselves rather than the solution to a known problem. Our first observation is that the attributes of a yet-to-be-discovered or currently unknown (undefined, under-specified, or unrevealed) problem cannot precisely drive the choice of how to search for problems. At the point the governance choice is made, the attributes of any undiscovered problem are necessarily unknown. Therefore, to theorize about the role of the crowd in finding problems, we must find a unit of analysis that serves as a proxy for the problem, is useful for the search for problems, and coheres with extant and well-developed theories of solution search.

Largely as a theoretical placeholder, we reference here the concept of problem domains, or classes of problems. While some emergent research is exploring the notion of problem domains in terms of the cost of experiments and approximate measures of complexity and ill-structuredness of the problem landscape (Furr et al., 2016), we leave for further work the development of problem-domain attributes that shape governance choices about problem finding. Instead, in this essay, we explore in more detail how attributes of the focal economic actors and the theories they possess shape these decisions.

Our second observation is that economic actors already explicitly or implicitly defer significant portions of problem finding to crowds of others. Said another way, the vast majority of valuable problem finding is performed by employees, customers, end-users, suppliers, and consultants, along with a wide range of organizations and potential vendors completely unknown to the focal economic actor. For instance, suppliers may see production or input problems that plague the focal economic actor and set about solving them in hopes of capturing a portion of the value. Other prospective suppliers and vendors similarly seek to uncover and understand the focal economic actor’s problems in activities ranging from employment and procurement to marketing and sales, again with the aim of capturing some portion of the value created from these solutions. Meanwhile, users of the focal actors’ products and services are constantly seeking to discover new innovative uses and applications (Ben-Menahem et al., 2015; Von Hippel, 1994). Through a variety of processes, users and customers identify new problems that existing products and services can be adapted to solve.

With the bulk of problem finding taken up by actors in the crowd, in many ways, the central governance question facing a focal economic actor is, curiously, the choice of which forms of problem finding not to defer to the crowd. With the various crowds that surround a focal economic actor possessing a standing invitation to find problems they deem valuable to that focal actor, the central governance choice for the economic actor can be conceptualized as: what domains of problems should be chosen for exploration and how should search for those problems be organized? Additionally, what will the focal economic actor’s stance be in relationship to the vast domain of problems and solutions implicitly deferred to crowds composed of end-users, communities, service providers, consultants, and even our own employees?

Theories, crowds, and a model of actors

We suspect that the answer to the question of which domains should be outsourced to a crowd centrally revolves around the cognitive attributes of the focal economic actor, including the knowledge, theories, and cognitive biases they possess. For a given domain of problems, governance choices to either “crowd find” or “self-find” problems fundamentally involve an economic actor comparing their self-possessed capacity to effectively problem find with the capacities of various crowds, and economic actors within them, to do similarly. Consequently, to understand this governance choice requires a clear understanding of how economic actors armed and saddled with cognitive capacities and limitations engage in governing problem finding. As Herbert Simon (1985) observed, “Nothing is more fundamental in setting our research agenda and informing our research methods than our view of the nature of human beings whose behaviors we are studying” (p. 293). Two behavioral and cognitive attributes are central to understand economic actors’ choices of when and where to use the crowd.

First, as Simon (1991) has argued, economic actors find problems by forming “problem representations” or theories of value within given problem-domains (Felin and Zenger, 2009, 2015). A theory or problem representation may illuminate a distinctive customer problem or an unmet need, reveal a novel production problem, or forecast evolving customer tastes. Theories that are valuable are ones that reveal unique problems unseen by others. The theories of value that economic actors typically compose are actor-specific, reflecting the existing knowledge they possess and the cognitive capacities and biases they bring. Even economic actors with access to the same knowledge will compose theories that differ in terms of their content and resolution (Felin and Zenger, 2009). Thus, while divergence in theories and the problems they illuminate may reflect differences in knowledge, they also reflect the varying creativity and cognition with which knowledge is recombined to form theories. In this sense, theories reveal problems or an architecture of problems and, thus, bind, shape, and select the solution spaces in which solutions are sought; theories reveal problems that define and direct internal problem-solving efforts, or influence invitations to others to engage in problem solving.

Second, economic actors also are saddled with a variety of biases. In particular, they often become stubbornly committed to the theories they generate or problem representations they compose and are reluctant to adopt theories about problems generated externally (Dyer et al., 2009; Spender and Grant, 1996). Not only can economic actors errantly hold on to their own theories and reject others but, also, their biases can influence the design, execution, and interpretation of experiments to confirm their theories instead of rigorously testing them (Furr et al., 2016). Despite mounting disconfirming evidence, economic actors will often hold to their theories long past what the evidence warrants. Efficient search for problems (or solutions) becomes profoundly difficult and perhaps corrupted when economic actors’ acceptance of others’ ideas and problem representations is influenced by an attitude of “not invented here” or “not discovered here.”

These two insights have important implications for the efficient governance of problem finding. If economic actors are theorists actively engaged not only in problem solving but also problem finding, then crowds are more than sets of actors with disparate knowledge; they are aggregations of actors with the potential for competing theories that reveal competing problems. Moreover, an economic actor’s adoption of a given theory and commitment to pursuing solutions to the problems it reveals, implicitly defers a potentially vast residual domain of problem finding and problem solving to others.⁴ Consequently, a focal economic actor’s governance choice to problem-find through the crowd is driven in a large measure by an expectation that the actor’s capacity to compose a valuable problem-revealing theory is less effective than the capacity of the multitude of actors in a select crowd. In this sense, within a crowd, each economic actor’s theory and the problems revealed potentially compete both with the focal economic actor’s theory and the distributed theories from other actors in the crowd.

A significant challenge, in accessing theories from the crowd is that actors—whether the focal economic actor or actors in the crowd—are not only fiercely loyal to their own theories, but often fully incapable of cognitively seeing the problem or value revealed by the theories of others. An important implication is that an economic actor’s humility relative to hubris may profoundly shape governance choices regarding whether to self-find or crowd-find problems.

The crowd and efficient problem finding

As discussed in the Introduction, an economic actor’s value creation efforts demand a sequence of critical governance decisions. This array of decisions includes how to search for problems, solve them, and organize the ultimate delivery of solutions. While our focus here is on the governance of problem finding, these additional governance decisions about finding, solving, and composing value are interdependent. And, the range of governance combinations encompassing these decisions is substantial.

Thus, for a given domain of problems, a focal economic actor may defer problem finding to the crowd but, once found and framed, choose to internally search for solutions. For other problem domains, the focal actor may internalize both problem finding and solving to the crowd. For still other problem domains, a focal actor may find problems, but defer their solving to others. Finally, the focal actor may defer both finding and solving, accepting what Von Hippel and Von Krogh (2015) label as “need-solution” pairs—essentially, problems found and solved by others. And, of course, for all problems solved, the focal actor faces a range of governance choices with substantial value capture implications concerning how to compose that value.

The logical thread through all of these combinations of choices is that the focal economic actor seeks to efficiently create and capture value by finding, solving, and delivering value through efficient governance choices. At times, value creation and capture may be at odds in shaping these choices. For instance, value capture—otherwise referred to as the appropriability of value (Teece, 1986)—may dictate self-finding problems, internal problem solving, and the internal provision of co-specialized activities, even though deferring to the crowd for problem search, solution search, or value composition offers more efficient value creation. A full discussion of these interactions is beyond the scope of this essay, but the general principle is that governance choices about finding, solving, and sourcing through the crowd are shaped by this effort to jointly optimize the creation and capture of value.

Another key factor shaping the pattern of governance choices is that an economic actor may both be fiercely loyal to a particular theory, but also fully unable to convey to others the value of the theory and the valuable problem domain the theory reveals. This inability or, at least, the high cost associated with the need to convince others, is closely related to Foss and Klein’s (2012) notion that judgment is difficult to delegate in entrepreneurial settings, and that the cost of convincing others has implications for economic organization (Demsetz, 1988; Van den Steen, 2010; Wuebker and Zenger, 2016). Developing a theory of the crowd, by extension, requires careful treatment of the implications of the kinds of theories that a crowd might generate. A key challenge that actors in the crowd face is that the theories that they possess can be idiosyncratic and ultimate value may be difficult, if not impossible, to convey. Theories are lenses that reveal problems that are not only unseen by others, but may be potentially un-seeable by others.

The cognitive limitations that make sharing theories and their value difficult has two important consequences. First, for actors in the crowd to compose value for a focal economic actor and position themselves to capture some portion of it, they may have to do more than simply find a problem and pitch it to the focal economic actor as a problem that merits solving. For instance, lacking the user’s theory or problem representation, manufacturers may struggle to recognize value in the problems that users see. Consequently, these users or problem-finders in the crowd may instead need to both identify and frame the problem, but also solve it, perhaps even physically composing either a solution or an “existence proof” as a prototype to convince the focal actor of its value (Von Hippel, 2007).

Second, focal economic actors may need to deliberately compose their organizations to limit the overbearing influence of their own theories and problem representations on the problem finding and problem solving efforts of others both within the firm and within the crowds that surround it. In other words, given actors’ allegiance to their own theories and the problems they reveal, effectively engaging with the crowd in problem finding and problem solving may necessitate explicit governance choices and associated organizational designs that sequester the influence of a focal actor’s (or firm’s) theory (for a theoretical elaboration see Furr et al., 2016). Deliberately outsourcing innovation or isolating exploratory units that are more open to engagement with the crowd from exploitative units with well-defined problems to solve may prove particularly useful in this regard (O’Reilly and Tushman, 2004; Raisch et al., 2009). Alternatively, adopting aggressive efforts to decentralize decision-making during periods of time when new problems and new sources of value are sought, but at other times organizing in a more integrated manner consistent with selected problems may also prove useful (Boumgarden et al., 2012).

Discussion

In recent years, open innovation—broadly conceptualized as “the use of purposive inflows and outflows of knowledge to accelerate internal innovation, and expand the markets for external use of innovation” (Chesbrough, 2006)—has evolved from a narrow set of techniques focused on high-technology organizations to a more widely understood and disparate set of practices that share a common interest in sourcing contributions from the vast crowd outside of an organization and, in some instances, integrating them within the focal firm. Despite the obvious conceptual connection, these practices have tended to be isolated from one another in the scholarly literature and often speak to a specialized audience quite familiar with the phenomena in question. And, within each of these practices, theory development has been slow-going.

What all these practices have in common is an acknowledgement of an economic fact of life: the vast majority of value-creating knowledge that focal economic actors access emerges through problems externally, rather than internally, discovered and solved. Simon (1991) likens this process to the activity of an academic research lab noting that “in any given research laboratory, only a tiny fraction of the new knowledge acquired by the research staff is knowledge created by that laboratory; most of it is knowledge created by research elsewhere” (p. 130). As academics, we know all too well that “much more information comes through the eye that is scanning journals than the eye that is looking through the laboratory microscope” (Simon, 1991: 30). Despite the growing importance of crowdsourcing for creating valuable knowledge, many firms experience challenges in actively managing crowdsourcing practices. With much of literature focused on identifying the phenomenon, existing theoretical perspectives struggle to explain the conditions under which crowdsourcing is beneficial to economic actors trying to solve problems.

Building on Simon’s insight, we have argued for a state of affairs where one of the most important governance choices that managers face is deciding when to query outside actors, accepting the problems they identify and solve, and when to identify their own problem and “look through the microscope” to solve it. Fundamentally, a theory of crowdsourcing requires the ability to understand its costs and benefits, when an economic actor would choose it over alternative forms of organization, and the factors that, on the margin, affect its boundary conditions. As we have noted, managers face a sequence of nested, and often interdependent, governance choices that have been conceptually collapsed in previous scholarly work. They must decide when and where to problem-find themselves, and when and where to defer to the crowd. And, finally, they must decide how to govern the process of composing the solution to problems found and solved. Through all of these governance choices, economic actors must consider both the efficiency of value creation and the effectiveness of value capture that these governance choices ultimately deliver.

Our essay has argued for the central role of comparative governance in deciding how to organize problem finding and problem solving. Indeed, efficiently, effectively, and efficaciously choosing to use the crowd or some other organizational structure for finding and solving problems depends on comparatively assessing the costs and competencies of alternative governance modes with respect to the attributes of the problem or its domain. Yet, the comparison also needs to account for an economic actor’s theories of value—theories that reveal problems (Felin and Zenger, 2015). As we have discussed, these theories have profound implications for an economic actor’s decisions regarding when and where to find problems through the crowd. The problem-finding and problem-solving perspective illuminates the crucial importance of governing the process of value-creating search and the role of theories in that process. Without a comparative governance choice, search is unlikely to be efficient. Theories define and direct internal problem-solving efforts, shape invitations to others to problem solve, and, ultimately, function as an anchor for value-creating search. Developing a theory about governing the crowd grounded in a comparative governance perspective will necessarily require carefully identifying the set of discrete attributes by which governance choices, including the choice to crowd find, are matched; and, it will also likely require a deep consideration of the focal actors making these choices and the knowledge, theories, and biases they bring to bear in the process.

Footnotes

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

Notes

Author biographies

Jackson A Nickerson is the Frahm Family Professor of Organization and Strategy at Olin Business School, Washington University in St Louis. Jackson is the author of several leadership books, including Leading Change from the Middle: A Practical Guide for Building Extraordinary Capabilities. He is the Associate Dean and Director of Brookings Executive Education, is a non-resident Senior Fellow in Governance Studies at the Brookings Institution, and was a visiting Senior Fellow at the Grameen Foundation. Jackson’s current research interests include the problem-finding and problem-solving perspective, knowledge and organizational choice, entrepreneurship, research and development (R&D), and comparative adjustment costs. He has published in numerous journals including Administrative Science Quarterly, Journal of Political Economy, Management Science, Strategic Management Journal, Organization Science and Strategic Organization. Address: Olin Business School, Washington University in St Louis, Campus Box 1133, 1 Brookings Drive, St Louis, MO 63130, USA. [email: nickerson@wustl.edu]

Robert Wuebker is an Assistant Professor of Entrepreneurship and Strategy at the Eccles School of Business, University of Utah. He received his PhD from Rensselaer Polytechnic Institute. His current research interests include entrepreneurship and value creation, theories of the entrepreneurial firm, and entrepreneurial finance. He has published in journals that include Academy of Management Review, Journal of Management, Journal of Business Venturing, Journal of Corporate Finance, Small Business Economics, and Strategic Entrepreneurship Journal and is the co-editor of The Handbook of Research on Energy Entrepreneurship (Edward Elgar, 2011). Address: David Eccles School of Business, University of Utah, Salt Lake City, UT 84112, USA. [email: robert.wuebker@eccles.utah.edu]

Todd Zenger is now the Nathan (N.) Eldon Tanner Professor of Strategy and Strategic Leadership and Presidential Professor at the Eccles School of Business, University of Utah, after spending 24 years at Washington University in St Louis. He received his PhD from University of California, Los Angeles (UCLA). His research interests include corporate strategy, theories of the firm, entrepreneurship and value creation, and organization design. He has published in journals that include Organization Science, Strategic Management Journal, Administrative Science Quarterly, Management Science, Strategy Science, Academy of Management Review, and Academy of Management Journal, and is author of the recently published book, Beyond Competitive Advantage (Harvard Business Review Press, 2016). Address: David Eccles School of Business, University of Utah, Salt Lake City, UT 84112, USA. [email: todd.zenger@eccles.utah.edu]

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