Showing papers in "Organization Science in 2022"

We Are All Theorists of Technology Now: A Relational Perspective on Emerging Technology and Organizing

Abstract: Technologies are changing at a rapid pace and in unpredictable ways. The scale of their impact is also far-reaching. Technologies such as artificial intelligence, data analytics, robotics, digital platforms, social media, blockchain, and 3-D printing affect many parts of the organization simultaneously, enabling new interdependencies within and between units and with actors that many organizations have typically considered to be outside their boundaries. Consequently, today’s emerging technologies have the potential to fundamentally shape all aspects of organizing. This article introduces the special issue “Emerging Technologies and Organizing.” We treat these new technologies as “emerging” because their uses and effects are still varied and have yet to stabilize around a recognizable set of patterns and because the technologies themselves are, by design, always changing and adapting. To theorize the relationship between emerging technologies and organizing, we draw on relational thinking in philosophy and sociology to develop a relational perspective on emerging technologies. Our goal in doing so is to create a new way for organizational scholars to incorporate the ever-increasing role of technology in their theorizing of key organizational processes and phenomena. By developing a relational perspective that treats emerging technologies not as stable entities, but as a set of evolving relations, we provide a novel way for organizational scholars to account for the role of technology in their topics of interest. We sketch the outlines of this relational perspective on emerging technologies and discuss the implications it has for what organizational scholars study and how we study it.

To Engage or Not to Engage with AI for Critical Judgments: How Professionals Deal with Opacity When Using AI for Medical Diagnosis

Abstract: Artificial intelligence (AI) technologies promise to transform how professionals conduct knowledge work by augmenting their capabilities for making professional judgments. We know little, however, about how human-AI augmentation takes place in practice. Yet, gaining this understanding is particularly important when professionals use AI tools to form judgments on critical decisions. We conducted an in-depth field study in a major U.S. hospital where AI tools were used in three departments by diagnostic radiologists making breast cancer, lung cancer, and bone age determinations. The study illustrates the hindering effects of opacity that professionals experienced when using AI tools and explores how these professionals grappled with it in practice. In all three departments, this opacity resulted in professionals experiencing increased uncertainty because AI tool results often diverged from their initial judgment without providing underlying reasoning. Only in one department (of the three) did professionals consistently incorporate AI results into their final judgments, achieving what we call engaged augmentation. These professionals invested in AI interrogation practices—practices enacted by human experts to relate their own knowledge claims to AI knowledge claims. Professionals in the other two departments did not enact such practices and did not incorporate AI inputs into their final decisions, which we call unengaged “augmentation.” Our study unpacks the challenges involved in augmenting professional judgment with powerful, yet opaque, technologies and contributes to literature on AI adoption in knowledge work.

Expanding the Locus of Resistance: Understanding the Co-constitution of Control and Resistance in the Gig Economy

Abstract: Existing literature examines control and resistance in the context of service organizations that rely on both managers and customers to control workers during the execution of work. Digital platform companies, however, eschew managers in favor of algorithmically mediated customer control—that is, customers rate workers, and algorithms tally and track these ratings to control workers’ future platform-based opportunities. How has this shift in the distribution of control among platforms, customers, and workers affected the relationship between control and resistance? Drawing on workers’ experiences from a comparative ethnography of two of the largest platform companies, we find that platform use of algorithmically mediated customer control has expanded the service encounter such that organizational control and workers’ resistance extend well beyond the execution of work. We find that workers have the most latitude to deploy resistance early in the labor process but must adjust their resistance tactics because their ability to resist decreases in each subsequent stage of the labor process. Our paper, thus, develops understanding of resistance by examining the relationship between control and resistance before, during, and after a task, providing insight into how control and resistance function in the gig economy. We also demonstrate the limitations of platforms’ reliance on algorithmically mediated customer control by illuminating how workers’ everyday interactions with customers can influence and manipulate algorithms in ways that platforms cannot always observe.

“Making Out” While Driving: Relational and Efficiency Games in the Gig Economy

Abstract: On-demand or “gig” workers show up to a workplace without walls, organizational routines, managers, or even coworkers. Without traditional organizational scaffolds, how do individuals make meaning of their work in a way that fosters engagement? Prior literature suggests that organizational practices, such as recruitment and socialization, foster group belonging and meaningfulness, which subsequently leads to engagement, and that without these practices alienation and attrition ensue. My four-year qualitative study of workers in the largest sector in the on-demand economy (ridehailing) suggests an alternative and more readily available mechanism of engagement—workplace games. Through interactions with touchpoints—in this context, the customer and the app—individuals turn their work into games they find meaningful, can control, and “win.” In the relational game, workers craft positive customer service encounters, offering gifts and extra services, in the pursuit of high customer ratings, which they track through the app’s rating system. In the efficiency game, workers set boundaries with customers, minimizing any “extra” behavior, in the pursuit of maximizing money per time spent driving and they create their own tracking tools outside the app. Whereas each game resulted in engagement—as workers were trying to “win”—games were associated with two divergent stances or relationships toward the work, with contrasting implications for retention. My findings embed meaning-making in what is fast-becoming the normal workplace, largely solitary and structured by emerging technologies, and holds insights for explaining why people remain engaged in a line of work typically deemed exploitative.

Alternative Futures for the Digital Transformation: A Macro-Level Schumpeterian Perspective

Abstract: This paper develops and deploys a theoretical framework for assessing the prospects of a cluster of technologies driving what is often called the digital transformation. There is considerable uncertainty regarding this transformation’s future trajectory, and to understand and bound that uncertainty, we build on Schumpeter’s macro-level theory of economy-wide, technological revolutions and on the work of several scholars who have extended that theory. In this perspective, such revolutions’ trajectories are shaped primarily by the interaction of changes within and between three spheres—technology, organization, and public policy. We enrich this account by identifying the critical problems and the collective choices among competing solutions to those problems that together shape the trajectory of each revolution. We argue that the digital transformation represents a new phase in the wider arc of the information and communication technology revolution—a phase promising much wider deployment—and that the trajectory of this deployment depends on collective choices to be made in the organization and public policy spheres. Combining in a 2 × 2 matrix the two main alternative solutions on offer in each of these two spheres, we identify four scenarios for the future trajectory of the digital transformation: digital authoritarianism, digital oligarchy, digital localism, and digital democracy. We discuss how these scenarios can help us trace and understand the future trajectory of the digital transformation.

Waging War from Remote Cubicles: How Workers Cope with Technologies That Disrupt the Meaning and Morality of Their Work

Abstract: Technologies are known to alter social structures in the workplace, reconfigure roles and relationships, and disrupt status hierarchies. However, less attention has been given to how an emerging technology disrupts the meaning and moral values that tether people to their work and render it meaningful. To understand how workers respond to such an emerging technology, we undertook an inductive, qualitative study of military personnel working in unmanned aerial vehicles, or drone operations, for the U.S. Air Force. We draw on multiple data sources, including personal diaries kept by personnel involved in drone operations. We identified three characteristics of drone technology: remote-split operations, remote piloting of unmanned vehicles, and interaction through iconic representations. Our analysis suggests that drone technology has revolutionized warfare by (1) creating distanciated intimacy, (2) dissolving traditional spatio-temporal boundaries between work and personal life, and (3) redefining the legal and moral parameters of work. Drone program workers identified with these changes to their working environment in contradictory ways, which evoked emotional ambivalence about right and wrong. However, their organization gave them little help in alleviating their conflicting feelings. We illuminate how workers cope with such ambivalence when a technology transforms the meaning and morality of their work. We extend theory by showing that workers’ responses to a changed working environment as a result of a remote technology are not just based on how the technology changes workers’ tasks, roles, and status but also on how it affects their moral values.

Organizations Decentered: Data Objects, Technology and Knowledge

Abstract: Data are no longer simply a component of administrative and managerial work but a pervasive resource and medium through which organizations come to know and act upon the contingencies they confront. We theorize how the ongoing technological developments reinforce the traditional functions of data as instruments of management and control but also reframe and extend their role. By rendering data as technical entities, digital technologies transform the process of knowing and the knowledge functions data fulfil in socioeconomic life. These functions are most of the times mediated by putting together disperse and steadily updatable data in more stable entities we refer to as data objects. Users, customers, products, and physical machines rendered as data objects become the technical and cognitive means through which organizational knowledge, patterns, and practices develop. Such conditions loosen the dependence of data from domain knowledge, reorder the relative significance of internal versus external references in organizations, and contribute to a paradigmatic contemporary development that we identify with the decentering of organizations of which digital platforms are an important specimen.

In the Land of the Blind, the One-Eyed Man Is King: Knowledge Brokerage in the Age of Learning Algorithms

Abstract: This paper presents research on how knowledge brokers attempt to translate opaque algorithmic predictions. The research is based on a 31-month ethnographic study of the implementation of a learning algorithm by the Dutch police to predict the occurrence of crime incidents and offers one of the first empirical accounts of algorithmic brokers. We studied a group of intelligence officers, who were tasked with brokering between a machine learning community and a user community by translating the outcomes of the learning algorithm to police management. We found that, as knowledge brokers, they performed different translation practices over time and enacted increasingly influential brokerage roles, namely, those of messenger, interpreter, and curator. Triggered by an impassable knowledge boundary yielded by the black-boxed machine learning, the brokers eventually acted like “kings in the land of the blind” and substituted the algorithmic predictions with their own judgments. By emphasizing the dynamic and influential nature of algorithmic brokerage work, we contribute to the literature on knowledge brokerage and translation in the age of learning algorithms.

CEO Power and Nonconforming Reference Group Selection

Abstract: Research shows that reference group selection underpins critical organizational processes, but less is known about publicly disclosed choices of reference groups, such as those for the evaluation of firm performance. Because audiences, such as investors and analysts, prefer reference groups created by independent entities they can trust, they disapprove of choices of custom peer groups created by reporting firms. Nevertheless, firms frequently choose reference groups that do not conform to audiences’ expectations. We seek to explain why firms deviate from these externally held standards even when incurring penalties by developing theory and formulating hypotheses about the influence of chief executive officer (CEO) power. Using data from 10-K filings, we find that firms led by high-power CEOs are more likely to use nonconforming, custom peer groups despite incurring penalties. However, the relationship between CEO power and the use of custom peer groups is weaker when CEOs face greater scrutiny from shareholders and analysts. We also find that low firm performance increases the use of custom peer groups among high-power CEOs. Contrary to our expectations, high CEO compensation attenuates the effect of CEO power on the choice of custom peer groups, arguably because high levels of CEO pay increase scrutiny. Although firms incur costs for using nonconforming reference groups, supplemental analyses reveal that CEOs benefit by receiving higher compensation, especially when performance is low. We conclude by discussing implications for research on publicly disclosed reference groups, the consequences of power, and information disclosure.

Organizing Form, Experimentation, and Performance: Innovation in the Nascent Civilian Drone Industry

Abstract: Our aim is to explore whether the benefits to firms of using community-based innovation extend to nascent markets: uncertain, high-velocity settings with novel, often complex products. Grounded in a rare empirical comparison, we closely track the two ventures (one using community-based innovation and the other firm-based) that pioneered the nascent civilian drone market. We unpack how each addressed the three major innovations that shaped this setting. Our primary insight is that the firm organizing form for innovation performs best relative to communities in nascent markets. Firms have a coordination advantage that enables quickly and accurately targeting experimentation and problem-solving processes to reduce the many specific uncertainties that characterize these markets. Although communities can help, their task self-selection advantage works best in stable settings such as established markets with simple products (e.g., modular software) and in ambiguous settings in which low-cost randomness pays off. Broadly, we contribute a theoretical framework that identifies how organizing form and problem type jointly shape innovation performance. Most important, uncertainty forms a boundary condition for when firms should rely on firm-based (versus community-based) organizing for innovation.

How Business Models Evolve in Weak Institutional Environments: The Case of Jumia, the Amazon.Com of Africa

Abstract: We advance research on the antecedents of business model design by integrating institutional and imitation theories to explore how the business model of new ventures evolves in a weak institutional environment. Based on a case study of Jumia—an online retailing company in Africa established with the aim to emulate the success of Amazon.com—we propose a process model entitled “imitate-but-modify” that explains how business models evolve through four distinct phases (i.e., clarification, legitimacy, localization, and consolidation). In essence, this model explains how new ventures surrounded by considerable uncertainty deliberately seek to learn vicariously by imitating the business model template of successful firms. However, because of significant institutional voids, the ventures’ intentional imitation is progressively replaced by experiential learning that blends business model imitation with innovation.

What Makes Resource Provision an Effective Means of Poverty Alleviation? A Resourcing Perspective

Abstract: Adequately addressing the grand challenge of poverty requires addressing resource scarcity. However, efforts to provide resources as a means of poverty alleviation have met with mixed success. We explore what makes resource provision effective as a means of poverty alleviation. We adopt a resourcing perspective, which focuses on the relationship between potential resources and schemas, or shared understandings, that shape how resources are used. Consistent with prior research, we find that schemas shape how resources are used in practice. However, we also find that who can access the resources is as consequential as how they are used. In exploring this issue, we identify a new category of schemas related not to use but to access, which we refer to as access schemas. We define access schemas as shared understandings regarding who can appropriately access potential resources. We find that different social groups have distinct schemas regarding access, and we identify three mechanisms—precedence, complementarity, and scaffolding—that shape the way that access schemas are enacted in resource-scarce settings. Our study contributes to the literature on grand challenges by clarifying the link between resource provision and resource use. We also contribute to the literature on resourcing by uncovering mechanisms that shape schema enactment in the presence of conflicting access schemas held by different social groups.

Algorithm-Augmented Work and Domain Experience: The Countervailing Forces of Ability and Aversion

Abstract: Past research offers mixed perspectives on whether domain experience helps or hurts algorithm-augmented worker performance. Reconciling these perspectives, we theorize that intermediate levels of domain experience are optimal for algorithm-augmented performance, due to the interplay between two countervailing forces—ability and aversion. Although domain experience can increase performance via increased ability to complement algorithmic advice (e.g., identifying inaccurate predictions), it can also decrease performance via increased aversion to accurate algorithmic advice. Because ability developed through learning by doing increases at a decreasing rate, and algorithmic aversion is more prevalent among experts, we theorize that algorithm-augmented performance will first rise with increasing domain experience, then fall. We test this by exploiting a within-subjects experiment in which corporate information technology support workers were assigned to resolve problems both manually and using an algorithmic tool. We confirm that the difference between performance with the algorithmic tool versus without the tool was characterized by an inverted U-shape over the range of domain experience. Only workers with moderate domain experience did significantly better using the algorithm than resolving tickets manually. These findings highlight that, even if greater domain experience increases workers’ ability to complement algorithms, domain experience can also trigger other mechanisms that overcome the positive ability effect and inhibit performance. Additional analyses and participant interviews suggest that, even though the highest experience workers had the greatest ability to complement the algorithmic tool, they rejected its advice because they felt greater accountability for possible unintended consequences of accepting algorithmic advice.

Attention to Exploration: The Effect of Academic Entrepreneurship on the Production of Scientific Knowledge

Abstract: We study how becoming an entrepreneur affects academic scientists’ research. We propose that entrepreneurship will shift scientists’ attention away from intradisciplinary research questions and toward new bodies of knowledge relevant for downstream technology development. This will propel scientists to engage in exploration, meaning they work on topics new to them. In turn, this shift toward exploration will enhance the impact of the entrepreneurial scientist’s subsequent research, as concepts and models from other bodies of knowledge are combined in novel ways. Entrepreneurship leads to more impactful research, mediated by exploration. Using panel data on the full population of scientists at a large research university, we find support for this argument. Our study is novel in that it identifies a shift of attention as the mechanism underpinning the beneficial spillover effects from founding a venture on the production of public science. A key implication of our study is that commercial work by academics can drive fundamental advances in science.

Taking Your Team Behind the Curtain: The Effects of Leader Feedback-Sharing and Feedback-Seeking on Team Psychological Safety

Abstract: Although scholars have highlighted the benefits of psychological safety, relatively few studies have examined how leaders establish it. Whereas existing research points to the importance of seeking feedback, we draw on theories of self-disclosure, trust, and implicit voice to propose that leaders can also promote psychological safety by sharing feedback—openly discussing criticisms and suggestions they have already received about their own performance. In Study 1, naturally-occurring feedback-seeking and feedback-sharing by CEOs independently predicted board member ratings of top management team psychological safety. In Study 2, a longitudinal field experiment, randomly assigning leaders to share feedback had a positive effect on team psychological safety one year later, whereas assigning leaders to seek feedback did not. In Study 3, to explore the processes through which feedback-sharing had an enduring effect but feedback-seeking did not, we conducted qualitative interviews with participating leaders and employees two years later. We found that leaders initiated vulnerability through seeking feedback, but it dissolved due to defensiveness and inaction. In contrast, sharing feedback normalized and crystallized vulnerability as leaders made a public commitment to keep sharing and employees reciprocated, which opened the door for more actionable feedback, greater accountability, and ongoing practices that allowed psychological safety to endure. Our research suggests that to achieve enduring improvements in psychological safety, it may be particularly effective for leaders to share criticism they have received—and that doing so does not jeopardize their reputations as effective and competent.

Division of Labor Through Self-Selection

Abstract: Self-selection–based division of labor has gained visibility through its role in varied organizational contexts such as nonhierarchical firms, agile teams, and project-based organizations. Yet, we know relatively little about the precise conditions under which it can outperform the traditional allocation of work to workers by managers. We develop a computational agent-based model that conceives of division of labor as a matching process between workers’ skills and tasks. This allows us to examine in detail when and why different approaches to division of labor may enjoy a relative advantage. We find a specific confluence of conditions under which self-selection has an advantage over traditional staffing practices arising from matching: when employees are very skilled but at only a narrow range of tasks, the task structure is decomposable, and employee availability is unforeseeable. Absent these conditions, self-selection must rely on the benefits of enhanced motivation or better matching based on worker’s private information about skills, to dominate more traditional allocation processes. These boundary conditions are noteworthy both for those who study as well as for those who wish to implement forms of organizing based on self-selection.

The Mechanisms and Components of Knowledge Transfer: The Virtual Special Issue on Knowledge Transfer Within Organizations

Abstract: Knowledge transfer within organizations has important implications for organizational performance and competitive advantage. In this virtual special issue, we review articles on this topic published in Organization Science between 2014 and 2020 and identify 53 articles for their theoretical and empirical contributions. These articles examine knowledge transfer through five transfer mechanisms: social networks, routines, personnel mobility, organizational design, and search. We consider the intersection of each transfer mechanism with important components of knowledge transfer (characteristics of sources/recipients, characteristics of knowledge, and characteristics of contexts). We present 15 exemplar articles, each of which reflects the intersection of a mechanism and a component of knowledge transfer. We also present an overview of the methodological approaches and empirical contexts that are utilized. We conclude our article with a discussion of future research opportunities. The articles published in Organization Science have advanced understanding of both the mechanisms through which knowledge transfer occurs and the conditions under which it is most likely.

Problemistic Search of the Embedded Firm: The Joint Effects of Performance Feedback and Network Positions on Venture Capital Firms’ Risk Taking

Abstract: The Behavioral Theory of the Firm suggests that performance below aspirations triggers problemistic search that can lead to risk taking. This prediction has received empirical support from most studies on the topic. However, this literature has typically focused on the internal determinants of firm search and risk-taking behavior and given little attention to the influences of social networks in which firms are embedded. To this end, we incorporate the network embeddedness perspective regarding firms’ network positions and their roles in firm decision making. We suggest that a firm’s search behavior is jointly directed by its performance feedback and network positions. Specifically, network brokerage and centrality play important yet distinct roles in guiding firm search behavior by differentially shaping the direction of problemistic search: high brokerage directs problemistic search to high-risk solutions, whereas high centrality directs problemistic search to low-risk solutions. Our theoretical predictions receive general empirical support based on analyses using longitudinal data from the Chinese venture capital industry. Our approach incorporates the crucial role of network structures into the problemistic search model and works toward building a problemistic search theory of the embedded firm.

A New Take on the Categorical Imperative: Gatekeeping, Boundary Maintenance, and Evaluation Penalties in Science

Abstract: Extant theory suggests that candidates with an unfocused identity—those spanning different categories—suffer from a valuation penalty because evaluators are confused by their profile and concerned they lack the required skills. We argue that unfocused candidates may be penalized for another reason; they threaten established social boundaries. This happens in contexts where evaluators act as gatekeepers for social entities, such as professions. We test how the penalty applied to unfocused candidates varies in an academic accreditation process, a setting where evaluators decide on admitting candidates to an academic discipline and where candidates’ prior performance is observable. We find using data on the 2012 national scientific qualification in Italian academia that the valuation penalty applied to unfocused (multidisciplinary) candidates was most pronounced for the most high-performing candidates. High-performing yet ill-fitting candidates threaten the distinctiveness and knowledge domain of the discipline and are hence penalized by evaluators. High-performing multidisciplinary candidates suffered the greatest penalty in small and distinctive academic disciplines and when accreditors were highly typical members of their discipline. Our theory and findings suggest that the categorical imperative may be driven not only by cognitive or capability considerations as typically argued in the literature but also, by attempts to maintain social boundaries.

From Lock-In to Transformation: A Path-Centric Theory of Emerging Technology and Organizing

Abstract: We offer a path-centric theory of emerging technology and organizing that addresses a basic question. When does emerging technology lead to transformative change? A path-centric perspective on technology focuses on the patterns of actions afforded by technology in use. We identify performing and patterning as self-reinforcing mechanisms that shape patterns of action in the domain of emerging technology and organizing. We use a dynamic simulation to show that performing and patterning can lead to a wide range of trajectories, from lock-in to transformation, depending on how emerging technology in use influences the pattern of action. When emerging technologies afford new actions that can be flexibly recombined to generate new paths, decisive transformative effects are more likely. By themselves, new affordances are not likely to generate transformation. We illustrate this theory with examples from the practice of pharmaceutical drug discovery. The path-centric perspective offers a new way to think about generativity and the role of affordances in organizing.

Local Adaptation Without Work Intensification: Experimentalist Governance of Digital Technology for Mutually Beneficial Role Reconfiguration in Organizations

Abstract: This 1.5-year ethnographic study of a U.S. medical center shows that avoiding loss of autonomy and work intensification for less powerful actors during digital technology introduction and integration presents a multisited collective action challenge. I found that technology-related participation problems, threshold problems, and free rider problems may arise during digital technology introduction and integration that enable loss of autonomy and work intensification for less powerful actors. However, the emergence of new triangles of power allows for novel coalitions between less powerful actors and newly powerful third-party actors that can help mitigate this problem. I extend the political science perspective of experimentalist governance to examine how a digital technology-focused, iterative collective action process of local experimentation followed by central revision can facilitate mutually beneficial role reconfiguration during digital technology introduction and integration. In experimentalist governance of digital technology, local units are given discretion to adapt digital technologies to their specific contexts. A central unit composed of diverse actors then reviews progress across local units integrating similar digital technology to negotiate a new shared understanding of mutually beneficial technology-related tasks for each group of actors. The central unit modifies both local routines and the technology itself in response to problems and possibilities revealed by the central revision process, and the cycle repeats. Here, accomplishing mutually beneficial role reconfiguration occurs through an experimentalist, collective action process rather than through a labor-management bargaining process or a professional-led tuning process.

A Founding Penalty: Evidence from an Audit Study on Gender, Entrepreneurship, and Future Employment

Abstract: There is both widespread interest in encouraging entrepreneurship and universal recognition that the vast majority of these founders will fail, which raises an important unanswered question: What happens to ex-founders when they apply for jobs? Whereas existing research has identified many factors that facilitate movement out of an established organization and into entrepreneurship, far less attention has been devoted to understanding what transpires during the return journey—most notably, how employers evaluate entrepreneurial experience at the point of hire. We propose that employers penalize job candidates with a history of founding a new venture because they believe them to be worse fits and less committed employees than comparable candidates without founding experience. We further predict that the discount for having been an entrepreneur will diminish when other stereotypes about the candidate, particularly those based on gender, will contradict the negative beliefs about ex-founders. We test our proposition using a résumé-based audit and an experimental survey. The audit reveals that founding significantly reduces the likelihood that an employer interviews a male candidate, but there is no comparable penalty for female ex-founders. The experimental survey confirms the gendered nature of the founding penalty and provides evidence that it results from employers’ concerns that founders are less committed and worse organizational fits than nonfounders. Critically, the survey also indicates that these concerns are mitigated for women, helping to explain why they suffer no equivalent founding penalty.

Open Source Collaboration in Digital Entrepreneurship

Abstract: Emerging digital technologies give rise to digital entrepreneurship and the widespread phenomenon of open source collaboration (OSC) on GitHub for entrepreneurial pursuits. Although openness is a common theme in digital entrepreneurship, it is unclear how digital startups—that is, startups that that have digital artifacts at the core of their business model for value creation and capture—actually realize value from their OSC engagement. We develop a theoretical framework to explain how the engagement in OSC may affect the value of digital startups and how the effect is contingent on the stage of venture maturity (conception, commercialization, or growth) and the mode of OSC engagement (inbound or outbound). In analyses that pool 17,552 matched digital startups with monthly panel observations between 2008 and 2017, we find digital startups in the conception and commercialization stages benefit more from inbound OSC whereas the ones in the growth stage benefit more from outbound OSC. As digital startups increasingly use OSC for ideation, experimentation, and scaling, our contribution is to show whether, when, and how knowledge flows through OSC might affect the value of digital startups. We discuss implications for research on organizing for digital entrepreneurship as well as open innovation.

He’s Overqualified, She’s Highly Committed: Qualification Signals and Gendered Assumptions About Job Candidate Commitment

Abstract: Evidence suggests that possessing more qualifications than is necessary for a job (i.e., overqualification) negatively impacts job candidates’ outcomes. However, unfair discounting of women’s qualifications and negative assumptions about women’s career commitment imply that female candidates must be overqualified to achieve the same outcomes as male candidates. Across two studies, experimental and qualitative data provide converging evidence in support of this assertion, showing that gender differences in how overqualification impacts hiring outcomes are due to the type of commitment—firm or career—that is most salient during evaluations. Overqualified men are perceived to be less committed to the prospective firm, and less likely to be hired as a result, than sufficiently qualified men. But overqualified women are perceived to be more committed to their careers than qualified women because overqualification helps overcome negative assumptions that are made about women’s career commitment. Overqualification also does not decrease perceptions of women’s firm commitment like it does for men: supplemental qualitative and experimental evidence reveals that hiring managers rationalize women’s overqualification in a way they cannot for men by relying on gender stereotypes about communality and assumptions about candidates’ experiences with gender discrimination at prior firms. These findings suggest that female candidates must demonstrate their commitment along two dimensions (firm and career), but male candidates need only demonstrate their commitment along one dimension (firm). Taken together, differences in how overqualification impacts male versus female candidates’ outcomes are evidence of gender inequality in hiring processes, operating through gendered assumptions about commitment.

Congruence Between Leadership Gender and Organizational Claims Affects the Gender Composition of the Applicant Pool: Field Experimental Evidence

Abstract: The extent to which men and women sort into different jobs and organizations—namely, gender differences in supply-side labor market processes—is a key determinant of workplace gender composition. This study draws on theories of congruence to uncover a unique organization-level driver of gender differences in job seekers’ behavior. We first argue and show that congruence between leadership gender and organizational claims is a key mechanism that drives job seekers’ interest. Specifically, many organizational claims are gender-typed, such that social claims activate the female stereotype, whereas business claims activate the male stereotype. Thus, whereas female-led organizations making social claims are gender-congruent, male-led firms making the same claims are gender-incongruent. Beyond demonstrating a general preference among job seekers for congruence, we also find that female job seekers are most interested in working for organizations that are simultaneously congruent and provide credible signals that they are fair and equitable employers. The congruence of leadership gender and organizational claims thus affects the gender composition of applicant pools for otherwise identical jobs.

Transferring Knowledge by Transferring Individuals: Innovative Technology Use and Organizational Performance in Multiunit Firms

Abstract: Transferring individuals who possess relevant knowledge from one organizational unit to another—a form of resource redeployment—may help to overcome impediments to knowledge transfer. Despite the promise of this mechanism, which often occurs through intrafirm geographic mobility, relatively little research has examined how the knowledge and expertise of individuals interacts with the organizational resources of the units to which individuals move. This study examines whether intrafirm geographic mobility improves organizational performance by providing a conduit for the transfer of knowledge while accounting for the interaction between individual knowledge and factors at the organization-unit level of analysis. We analyze the performance effects of the transfer of engineers who have expertise in innovative process technologies. The results from a large multinational company show that the innovative process technology-related expertise of an individual engineer who moves to a new organizational unit is positively associated with the performance of that unit, suggesting that intrafirm geographic mobility improves organizational performance by providing a conduit for the transfer of knowledge. The results also show that the technology-related knowledge of engineers is a substitute for organization-level factors when a unit uses only technologies with which it is already familiar, whereas the technology-related knowledge of engineers is a complement to organization-level factors when units introduce new technologies. Thus, individuals who bring novel expertise to their organizational units through intrafirm mobility may be important vehicles for organizational learning and building new competences, helping to diffuse best practices.

We Cannot Direct the Wind, but We Can Adjust the Sails: Prosocial Ventures’ Responses to Potential Resource Threats

Abstract: One of entrepreneurs’ key tasks is mobilizing resources from external resource holders. Although we know how entrepreneurial ventures gain initial access to resources, we do not yet fully understand how they maintain their resource mobilization, particularly in the face of potential threats. During our 11-month study of prosocial ventures that emerged to alleviate the suffering of refugees in Germany, four attacks on the European public occurred that were allegedly committed by refugees. These attacks disrupted the German welcoming culture for refugees, potentially threatening the legitimacy of the prosocial ventures’ core activities. Thus, the attacks provide a starting point for examining how new prosocial ventures are able to maintain access to resources in the face of the potential withdrawal of resource holders. Theorizing from our data, we identify three distinct approaches to explain how prosocial ventures responded to the potential threat undermining the legitimacy of their activities to maintain access to resources. These approaches differ in their initial resource mobilization (i.e., based on the venture’s goal for alleviating suffering), threat appraisals, and responses to maintain resource mobilization in the face of the potential delegitimization of their core activities. Our model provides novel insights into resource mobilization and prosocial venturing.

Network Centralization and Collective Adaptability to a Shifting Environment

Abstract: We study the connection between communication network structure and an organization’s collective adaptability to a shifting environment. Research has shown that network centralization—the degree to which communication flows disproportionately through one or more members of the organization rather than being more equally distributed—interferes with collective problem-solving by obstructing the integration of existing ideas, information, and solutions in the network. We hypothesize that the mechanisms responsible for that poor integration of ideas, information, and solutions would nevertheless prove beneficial for problems requiring adaptation to a shifting environment. We conducted a 1,620-subject randomized online laboratory experiment, testing the effect of seven network structures on problem-solving success. To simulate a shifting environment, we designed a murder mystery task and manipulated when each piece of information could be found: early information encouraged an inferior consensus, requiring a collective shift of solution after more information emerged. We find that when the communication network within an organization is more centralized, it achieves the benefits of connectivity (spread of novel better solutions) without the costs (getting stuck on an existing inferior solution). We also find, however, that these benefits of centralization only materialize in networks with two-way flow of information and not when information only flows from the center of the network outward (as can occur in hierarchical structures or digitally mediated communication). We draw on these findings to reconceptualize theory on the impact of centralization—and how it affects conformity pressure (lock-in) and awareness of diverse ideas (learning)—on collective problem-solving that demands adaptation.

Crowd-Based Accountability: Examining How Social Media Commentary Reconfigures Organizational Accountability

Abstract: Organizational accountability is considered critical to organizations’ sustained performance and survival. Prior research examines the structural and rhetorical responses that organizations use to manage accountability pressures from different constituents. With the emergence of social media, accountability pressures shift from the relatively clear and well-specified demands of identifiable stakeholders to the unclear and unspecified concerns of a pseudonymous crowd. This is further exacerbated by the public visibility of social media, materializing as a stream of online commentary for a distributed audience. In such conditions, the established structural and rhetorical responses of organizations become less effective for addressing accountability pressures. We conducted a multisite comparative study to examine how organizations in two service sectors (emergency response and hospitality) respond to accountability pressures manifesting as social media commentary on two platforms (Twitter and TripAdvisor). We find organizations responding online to social media commentary while also enacting changes to their practices that recalibrate risk, redeploy resources, and redefine service. These changes produce a diffractive reactivity that reconfigures the meanings, activities, relations, and outcomes of service work as well as the boundaries of organizational accountability. We synthesize these findings in a model of crowd-based accountability and discuss the contributions of this study to research on accountability and organizing in the social media era.

Generalized Trust, External Sourcing, and Firm Performance in Economic Downturns

Abstract: Going beyond prior research that has focused on dyadic, party-specific trust, this study investigates the importance of generalized trust, which is not specific to a counterparty and originates from a broader context. We analyze how generalized trust at the regional level affects the extent to which a firm relies on external suppliers and the performance effects of doing so. Furthermore, we assess how these relationships are impacted by an economic downturn. We exploit differences in generalized trust across 145 regions in 12 European countries and use data on more than a million small- and medium-sized enterprises (SMEs) before and during the Great Financial Crisis (from 2008 to 2010). Control variables are selected via a double-selection procedure based on machine learning. We find that firms in high generalized trust regions, compared with those in low generalized trust regions, source more externally (but do not reduce external sourcing less in an economic downturn) and benefit more from external sourcing during an economic downturn.