Person:

Wu, Andy

Equity compensation is widely used for incentivizing skilled employees, particularly in new technology businesses. Traditional theories explaining why firms offer equity suggest that workers with higher rank should receive compensation packages more heavily weighted in equity. However, we observe the puzzle that many firms adopt an equality-in-equity strategy: they offer different cash salaries across all jobs but the same equity compensation. We propose a behavioral theory of domain-contingent inequality aversion to explain this finding: we argue that workers view salary and equity as two domains and are more inequality averse in the equity domain. Inequality in equity has a negative asymmetric effect on effort whereas the effect of inequality in salary can be positive. Our experimental findings are consistent with the existence of domain-contingent inequality aversion; we also find that inequality aversion in equity is more severe than in salary because of the perceived scarcity of equity.

The mobilization of resources is a central and defining feature of entrepreneurship. As the body of empirical research on entrepreneurial resource mobilization has grown, the literature has become increasingly fragmented. We review the literature on entrepreneurs’ mobilization of resources, spanning human, social, financial, and other forms of capital. We identify five critical issues that hold back progress in resource mobilization research. We then propose a path ahead for future research guided by two overarching goals. First, we advocate for a process perspective, focusing attention on how an individual actor’s disposition and situation shape her responses, how these responses interact with those of other actors, and how these individual and collective responses unfold over time to generate outcomes. Second, we call for stronger unification of theory within the entrepreneurial resource mobilization literature and across contiguous conversations in strategy and organization theory. Theoretical consilience will enable the accumulation of empirical research into a cohesive body of knowledge on entrepreneurial resource mobilization.

We study how learning by experience across projects affects an entrepreneur's strategic foresight. In a quantitative study of 314 entrepreneurs across 722 crowdfunded projects supplemented with a program of qualitative interviews, we counterintuitively find that entrepreneurs make less accurate predictions as they gain experience executing projects: they miss their predicted timeline to bring a product to market by nearly six additional weeks on each successive project. Although learning should improve prediction accuracy in principle, we argue that entrepreneurs also learn of opportunities to augment each successive product, which drastically expands the interdependencies beyond what an entrepreneur can anticipate. We find that entrepreneurs encounter more unforeseen interdependencies in their subsequent projects, and they sacrifice on-time delivery to address these interdependencies.

Our study introduces board committees as a crucial determinant of board actions. We examine how directors who structurally link different board committees—referred to as multi-committee directors (MCDs)—explain why some board actions are merely symbolic while others are more substantive. As a baseline, we argue that boards in general respond to financial restatements at peer firms by symbolically appointing new directors who are relatively inexperienced and unlikely to have a substantive impact. In contrast, boards with audit–nomination MCDs are more likely to take the substantive action of appointing new directors with the prior experience necessary to reduce the risk of their own future financial restatement. We combine qualitative interviews and a causal identification strategy using an original dataset covering Russell 3000 firms from 2001 to 2014.

Gregory, Henfridsson, Kaganer, and Kyriakou (2020) highlight the important role of data and AI as strategic resources that platforms may use to enhance user value. However, their article overlooks a significant conceptual distinction: the installed base of decentralized users who connect with a platform lie outside the boundaries of the platform-owning firm, whereas the accumulated data derived from that installed base exists internal to the boundaries of the firm and under firm control. Accounting for this distinction brings forth two key departures from their theory. First, the decentralized structure of a platform ecosystem makes value capture by the platform an essential consideration when analyzing the implications of data-driven learning for users. Because AI and data allow a platform to increase the share of value the platform owner captures from the users, the value perceived by users can often decline. Second, as an internal asset of the platform firm, data from users and complementors exhibits different dynamics compared with the dynamics that govern the installed base itself. As a result, the quantity and quality of the platform’s stock of data are only loosely coupled with the size of the platform’s installed base. We highlight the strategic implications of this distinction for a manager launching a new multi-sided platform.

An innovating organization faces the challenge of how to prioritize distinct goals of novelty and value, both of which underlie innovation. Popular practitioner frameworks like Agile management suggest that organizations can adopt an iterative approach of frequent meetings to prioritize between these goals, a practice we refer to as iterative coordination. Despite iterative coordination’s widespread use in innovation management, its effects on novelty and value in innovation remain unknown. With the information technology firm Google, we embed a field experiment within a hackathon software development competition to identify the effect of iterative coordination on innovation. We find that iterative coordination causes firms to implicitly prioritize value in innovation: Although iteratively coordinating firms develop more valuable products, these products are simultaneously less novel. Furthermore, by tracking software code, we find that iteratively coordinating firms favor integration at the cost of knowledge-creating specialization. A follow-on laboratory study documents that increasing the frequency and opportunities to reprioritize goals in iterative coordination meetings reinforces value and integration, while reducing novelty and specialization. This article offers three key contributions: highlighting how processes to prioritize among multiple performance goals may implicitly favor certain outcomes; introducing a new empirical methodology of software code version tracking for measuring the innovation process; and leveraging the emergent phenomenon of hackathons to study new methods of organizing. Supplemental Material: The online appendix is available at https://doi.org/10.1287/orsc.2021.1499.

Prior research on corporate headquarters (CHQ) characteristics identifies the impact of CHQ location and composition on the innovation outcomes of internal subsidiaries. However, given that external strategic alliances with high-tech entrepreneurial firms represent a key source of innovation for the corporation, corporations must also consider how their choices of CHQ location and composition affect the innovation outcomes of these partners. In a study of 36 incumbent pharmaceutical corporations in 377 strategic alliances with 143 VC-backed biotechnology startups, we leverage detailed hand-collected data on CHQ locations and functions to estimate the effect of the CHQ on the innovation performance of the corporations’ entrepreneurial alliance partners. We find that a 1000-km decrease in CHQ–partner distance leads to an increase of 28 forward citations for the alliance partner, i.e., a 1% decrease in the distance is associated with a 1.7% increase in innovation performance. We find that the co-located presence of the corporation’s R&D function at the CHQ attenuates the benefit of CHQ–partner proximity, particularly for alliances structured for horizontal collaboration at the same part of the value chain. This study contributes to the literatures on both CHQ design and technology alliances.

Software platforms create value by cultivating an ecosystem of complementary products and services. Existing explanations for how a prospective complementor chooses platforms to join assume the complementor has rich information about the range of available platforms. However, complementors lack this information in many ecosystems, raising the question of how complementors learn about platforms in the first place. We investigate whether attending a temporary gathering—a hackathon—impacts the platform choices of software developers. Through a large-scale quantitative study of 1,302 developers and 167 hackathons, supported by qualitative research, we analyze the multiple channels—sponsorship, social learning, knowledge exchange, and social coordination—through which hackathons serve as a social forum for the diffusion of platform adoption among attendees.