Moren Lévesque

Pharmaceutical firms are top lobbying spenders in the United States (US). While the potential benefits of lobbying are recognized in the literature, the criticism against unethical aspects of lobbying warrants pharmaceutical firms to strategize their lobbying activities. Our study addresses the question “How does a pharmaceutical firm’s resource allocation decision toward lobbying activities (and other non-market activities) influence that firm’s new drug launches and do these non-market activities interact with market activities?” Specifically, we investigate the interaction between lobbying and the intellectual capital (human, structural, and social capital) of firms. We use a formal model to develop our hypotheses, which we test on a sample of the largest US-listed pharmaceutical firms between 1999 and 2021. Our analyses suggest that human and structural capital weaken the effect of lobbying on the firm’s rate of new drug launches, whereas a firm’s social capital strengthens the relationship between lobbying and the rate of new drug launches.

Examining gender differences in business financing reveals important dimensions on which women- and men-owned businesses differ. Although considerable progress has been made in understanding gender differences in mobilizing resources, the role of time in business financing remains an underexplored topic, particularly among marginalized entrepreneurs, where decisions about and outcomes related to time play an important role in business success. Leveraging the literature on gender role congruity and risk preferences along with a sample of nearly 300,000 microloans funded on the kiva.org platform, we explore whether the timespan for women to reach their microloan funding goal differs from that of men and how borrowers’ strategies regarding the size and repayment duration of these microloans influence this gender difference.

Succession is often a critical event in the lifecycle of any organization. Consequently, an extensive body of literature explores family firm succession, and includes studies on integrated succession frameworks. Notwithstanding the large, illuminating body of literature, we believe that family firm succession is worth a fresh reexamination and consolidation to translate the findings into a powerful planning and communication tool, especially as all firms are facing a ‘new normal’ and their leaders are seeking novel perspectives and approaches amidst the COVID-19 disruption. We thus offer a systemic and systematic framework for family firm succession planning, incorporating ideas from the technology intelligence literature. Since relationship building can ease the succession process and relationships are built through communication, we also present a succession roadmap as a communication tool that can assist in making this process part of the regular business routines.

New product development (NPD) is a risky and expensive endeavor. Therefore, discontinuing less promising NPD projects, based on their development trajectories, is very important, yet firms face challenges when deciding whether and when to discontinue NPD projects. This article examines how characteristics of a firm’s prior success and failure experiences, such as the number of launched and discontinued past projects, their attributes (i.e., the codification and quality of the knowledge underlying these past projects), and their level of relatedness (i.e., similarity) to current projects, influence the risks of continuing and discontinuing NPD projects, thus impacting their future discontinuation decisions. We adopt a mixed method approach, where we formally model and empirically test the influence of prior experiences on future decision-making. A formal model enables us to offer reasoning that considers the risks of continuing a project versus discontinuing that project as the basis for theoretical arguments for a set of proposed testable relationships. We then empirically test these relationships on 2938 new drug development projects of biopharma firms worldwide. We find that firms with a greater amount of success and failure experiences tend to discontinue less promising NPD projects sooner than firms with less success and failure experiences. Also, we find that while the attributes (particularly knowledge codification) of successful experiences predominantly helped firms decide on timely discontinuation, failure experiences influenced firms’ decision on timely discontinuation only when the projects were closely related to their failure experiences.

The market for acquisitions has been a blind spot in exploration-exploitation research in the new venture context. The introduction of the acquisition exit outcome as a performance dimension for new ventures, especially among high-tech ventures, shifts the traditional temporal logic of exploration-exploitation theory by introducing previously unacknowledged short-term benefits of exploration. We bring the acquisition outcome into the picture and investigate the relationship between the exploration-exploitation continuum and profitability, survival, and acquisition likelihood simultaneously. Using the Kauffman Firm Survey data, we provide evidence for a link between exploration and the likelihood of acquisition (defined as the business being sold to or merged with another business), although industry technology level poses a boundary condition such that the association is not observed in low- and medium-technology firms. An inverse U-shaped relationship that is monotone negative for most of the data range was found between exploration and the profitability of low- and medium-tech firms, and a negatively linear relationship was found for exploration and the profitability of high-tech firms. Our findings lend some support to the viability of “born to flip” strategies involving comparatively higher exploration levels in high-tech start-ups and sacrifice of short-term profitability.

It is time for the entrepreneurship field to come to terms with leading-edge artificial intelligence (AI). AI holds great promise to transform entrepreneurship into a more relevant and impactful field, but it must overcome conflicts between the AI-driven research approach and that of the traditional, theory-based research process. We explore these opportunities and challenges and suggest concrete approaches that entrepreneurship researchers can use to harness the power of AI with rigor and enhance research relevance. We conclude that incorporating the power of AI in entrepreneurship research and managing the associated risks offer a new and “grand challenge” for the field.

Annapoornima M. Subramanian, Moren Lévesque, and Vareska Van De Vrande were recognized as a runner up for the 2020 Ralph Gomory Best Industry Studies Paper Award.

We investigate the double-edged impacts of interorganizational knowledge flows in academia–industry collaboration on the innovation economic impacts of science-based firms. When a firm receives knowledge directly from more research institutes, its innovation economic impact improves subsequently. In contrast, when a firm receives knowledge indirectly from other firms through a research institute, its innovation economic impact declines subsequently. We also explore the moderation effects of firm technological originality and generality. We report empirical findings from a panel data of science-based firms in the United States. Our analysis yields theoretical implications for academia–industry collaborations in the science-based entrepreneurship literature and practical implications for management practitioners and policymakers in science-based firm creation and development.

Problem definition: We examine how the presence of capital market frictions influences the decision to invest in production cost reduction and the resultant production volume. This investment can increase the firm’s cash flow by increasing the profit margin, but it can also decrease the firm’s risk-free cash reserves and thus affect its exposure to capital market frictions. Academic/practical relevance: Process improvement aimed at production cost reduction has generated myriad of theoretical questions about efficient investment options and capacity choices. From a managerial perspective, process improvement is a fundamental concern in operations strategy. Nevertheless, its analysis typically excludes financial constraints by assuming a perfect capital market. Methodology: We formulate a two-stage profit maximization model in which a capital-constrained firm commits to a cost-reduction investment in the first stage in anticipation of its production decision in the second stage of this two-stage decision process. The firm considers capital market frictions when making decisions at each stage, while considering uncertainty in demand for its offering and in reducing its unit production cost. Results: When a firm faces small initial capital and low preinvestment unit production costs, it can benefit from investing in production cost reduction in the presence of capital market frictions more so than in their absence. Moreover, uncertainty in the production cost reduction mitigates the impact of market frictions on the net benefit (i.e., additional profit), whereas demand uncertainty decreases the feasible parameter space, where investing in production cost reduction is optimal. Managerial implications: A firm’s decision to invest in production cost reduction affects its operational and financial capabilities. Managers should thus consider this investment as an operational hedge not only against the uncertainty of matching supply and demand but also against exposure to capital market frictions and the resultant financial risk.

Biotechnology and pharmaceutical firms invest billions of dollars in R&D, primarily in new drug discovery. Nonetheless, the industry is facing declining returns on R&D investments. Failure to discontinue less-promising new drug discovery projects is a key driver of this decreased productivity. Hence, firms are scrambling to restructure the new drug discovery process to improve decision-making and to limit the attrition rate to the early stages of drug discovery. Drawing on insights from the exploration–exploitation literature, our study addresses this timing problem by using a formal model and empirically testing its implications on how the time to discontinuation of new drug discovery projects are impacted by project- and firm-specific characteristics, so that a firm’s resources can be promptly redeployed to more fruitful endeavors. Our findings, based on an analysis of 1274 early-stage drug discovery projects worldwide, suggest that the time to discontinuation of early-stage drug discovery projects requires careful consideration of these project- and firm-specific characteristics. These findings hold important implications for the industry, which is undergoing tremendous stress and transformation. The results also contribute to the exploration–exploitation literature by modeling and testing the time-allocation decision between exploratory and exploitative activities.

This editorial draws attention to time to advance entrepreneurship research by focusing on two aspects of time—time perspective and time management. We initiate a deeper conversation on time in entrepreneurship and illustrate the value of a time-based lens for entrepreneurship research through discussing examples at the individual, firm and context levels. These examples consider underdog and portfolio entrepreneurs; well-being; social and unethical entrepreneurial behavior; entrepreneurial teams and entrepreneur–investor dyads; firm strategy; industry and cultural contexts. We review promising methods for time-conscious entrepreneurship research: process, true longitudinal, diary, experience sampling, observational, work-shadowing and time-use studies; historical approaches; experiments; and simulations.

Purpose

Thanks to technological developments produced by scientists and engineers, franchising has grown to become a business model of choice for firm expansion in knowledge-intensive industries. We propose a formal model to explore to what degree franchisors should adapt their business practices or routines to successfully expand their franchises in newly targeted markets. By simultaneously considering the franchise’s need to adapt locally in a new market and the level of business routine tacitness at the time of expansion, we integrate previously separate agency cost logics into one model. We offer refinements to the belief that expanding through a franchisee is the best when the business routines need adaptation, but expanding through a company-owned unit is best when these routines can be replicated.

Stigmatized markets are those where either the products/services, or the consumers, or both, have been collectively, negatively stereotyped and devalued by one or more stakeholder audiences in ways that discredit the overall market. Many stigmatized markets exist, and many flourish, yet little systematic attention has focused on entry into such markets. Our article addresses this gap by conceptualizing various strategies for entering stigmatized markets. We further present propositions regarding the market-level factors that can influence which of these strategies firms will choose to employ. The contributions include: conceptually clarifying the nature of stigmatized markets; identifying additional types of entry strategies relevant for entering stigmatized markets; theorizing the conditions under which firms would choose one entry strategy over another; and opening up for consideration the effects that market entry may have on stigmatized actors in targeted markets.

We draw upon stewardship theory to formally derive bounds on the investment amount in a business prospect, and to characterize ownership sharing when investors offer two-stage financing along with know-how to increase the prospect’s valuation. In the early-development stage, we show that the direct effect of investor know-how increases the entrepreneur’s share while the indirect effect from that know-how due to its interaction with the investment size, decreases it. In the subsequent growth stage, the direct effect decreases the entrepreneur’s share while the indirect effect increases it. These tradeoffs offer theoretical and practical implications for writing investment contracts involving investor know-how.

We use agency theory to model equity division in venture capital financing with three complementary value-creation factors—the entrepreneur’s effort, the venture capitalist’s advising/monitoring service, and the investment amount. While considering that investors often base their funding decisions on gut feeling, even as they employ rational decision-making processes, we derive closed-form expressions for optimal ownership sharing. Our findings provide theoretical explanation to support the recent call for practitioners to allocate ownership equity based on the relative potential contributions of the entrepreneur and the venture capitalist to generate value for the new investment prospect.

The five papers in this special section explore the use of data analytics in current business and management decision making. Entrepreneurial ingenuity plays a crucial role in building new business enterprises, especially when resources are lacking, routines are nonexistent, a firm’s reputation is not established, and/or regulations are inadequate. Resources in the form of human capital are often the foundation of independent startups or new corporate business ventures. Routines in the form of organizational and technical processes are often key in building these new ventures. Reputation in terms of an entrepreneur’s accomplishments or network is essential for acquiring needed resources and developing fundamental routines to initiate, commit to, organize, and grow the startup. Examines the impacts of such shortages create threats or opportunities for independent startups and new business ventures spun off from established firms.

This paper’s novelty is the modeling of competition in production quantity and product-launch timing, which has been silent regarding the impact of these interdependent decisions on firm survival. We rigorously address the competitive interplay between a startup and an established rival by developing a game-theoretic model that captures the startup’s vulnerability to failure through maximizing its survival likelihood. We allow the established rival to behave strategically by anticipating the startup’s timing and production decisions prior to making its own production decision. We propose that unless the market-entry investment is low, a survival-maximizing startup should wait to launch its product, and do so with a larger production output than the established rival, when delaying the product launch enables the startup to charge a high price. Insights on the established firm involve the benefit from behaving strategically, which is when competing with either a survival-maximizing or profit-maximizing startup. If the market-entry investment is large, comparing a survival-maximizing startup with a profit-maximizing startup suggests that the former produces at a larger scale than the latter when either startup competes with an established rival, which in turn is forced to reduce its production level.

Technological innovation drives economic growth, and the pioneering activity of scientists and engineers produce technological innovation. We provide a mathematical model of pioneering strategic choice by adopting a perspective familiar to microeconomics, but less common in the engineering management literature. Instead of focusing on the specific features of a pioneer’s technology, we focus on the malleability of the profit equation involved. By considering the arguments of the profit function (i.e., entry and variable costs and potential market demand) as strategic levers, we derive propositions that identify the ranges of actions (lever pulling) available to managers to protect (and even increase) entrepreneurial rents in a simple yet robust partial equilibrium case. For each lever, we show that there are several value ranges (intervals) and that the pioneer’s incentives vary across these intervals. In addition, for each lever, we identify the existence of nontrivial profit discontinuities that change the pioneer’s incentives in surprising ways and lead to counterintuitive strategic choices. Lastly, we show that for some range of each lever’s values, welfare-improving transfer payments are possible and, therefore, pioneers and policy-makers both have an incentive to bargain. As in the case of patents, these transfers encourage the introduction of new technologies.

Exploration-exploitation research to date has not properly addressed the issue of multiple performance dimensions and their potential trade-offs, especially in the context of start-ups where unique performance dimensions such as acquisition likelihood are relevant and coveted. This paper utilizes the recently completed Kauffman Firm Survey data to investigate the relationship between exploration- exploitation and the profitability, survival, and acquisition likelihood of start-ups simultaneously and to investigate potential trade-offs among these performance dimensions. A balance-is-best relationship is found for profitability of survived firms and for the acquisition likelihood of high tech firms, while an exploitation focus is found to maximize the survival chances of low and medium tech firms. For low and medium technology start-ups our findings are consistent with a trade-off between survival likelihood and profitability-given-survival, and for high tech start-ups our findings are consistent with a differently shaped trade-off between acquisition likelihood and profitability-given-survival.

By analyzing observed interactions between entrepreneurs and business angels (BAs) on the Canadian reality TV show Dragons’ Den, we find that BAs use a non-compensatory decision-making process when evaluating anticipated risk and return. This is consistent with our hypotheses that BAs use decision heuristics (shortcuts) to conserve cognitive effort when deciding whether or not to invest in business opportunities proposed by entrepreneurs. Our results further our understanding of how and when behavioral decision theory can inform real-life BA investment decision processes. Additionally, the results offer practical implications for entrepreneurs interested in pitching proposals to BAs.

This paper explores a discrepancy between what the literature says about sustainability and how sustainability is actually practiced. Our analysis reveals that we are in a transition era in which firms incrementally offset – rather than eliminate – their negative impacts on the environment and society. We also argue that external stakeholders have yet to create the conditions that would compel firms to become truly sustainable. We further find that a firm’s response to external pressure to become truly sustainable greatly depends on its capabilities. For large firms, the decision to become truly sustainable is driven by their ability to manage external stakeholders’ expectations, with the most innovative of large firms remaining unsustainable even in the long term. In contrast, small innovative firms guide their decision-making based on their internal readiness to change and therefore will be the first to reach true sustainability. Finally, and regardless of size, firms that lack an innovation capability are unlikely to become truly sustainable; they will struggle to survive the transition era.

While strategy theory relies heavily on equilibrium theories of economic rents such as Ricardian and monopoly rents, we do not yet have a comprehensive theory of disequilibrium or entrepreneurial rents. We use cooperative game theory to structure computer simulations of the market process in which acts of creation and discovery disequilibrate and equilibrate the market over time. Using simulation experiments, entrepreneurial rents can be isolated from structural rents by keeping initial structural advantages constant. We impute entrepreneurial rents to underlying actions of creation and discovery under various combinations. Our results have relevant implications for entrepreneurship strategy, particularly for firm boundaries and resource allocation decisions.

The theory of exploration and exploitation is based on the logic of trade-offs and yet empirical research has rarely investigated these trade-offs as manifested between different dimensions of performance. In the context of start-ups, getting acquired is an additional performance dimension previously ignored in the ambidexterity literature. This paper utilizes the recently completed Kauffman Firm Survey data to investigate the relationship between exploration and the profitability, survival, and acquisition likelihood of start-ups simultaneously. A balance-is-best relationship is found for profitability of survived firms and for the acquisition likelihood of high tech firms, while an exploitation focus is found to maximize the survival chances of low and medium tech firms. For low and medium technology start-ups we find evidence of a trade-off between survival likelihood and profitability-given-survival, and for high tech start-ups we find evidence of a differently shaped trade-off between acquisition likelihood and profitability-given-survival.

We use a principal-agent model to examine how venture capitalists can determine the ownership division when fund-seeking entrepreneurs possess private information on their disutility of effort. This situation is especially applicable to early-stage first-time entrepreneurs seeking funding, since no history exists on their potential performance. The venture capitalist must thus consider this private information by forming a belief on the entrepreneur’s effort level toward the proposed investment opportunity. Formal modeling enables us to describe how the deal process unfolds and to build a simulation. We then identify a unique investor’s belief and resulting ownership sharing that maximizes the return to the entrepreneur, one that maximizes the return to the venture capitalist, as well as one that maximizes the deal welfare. We also conjecture an ordering relationship between these critical beliefs and between their resulting ownership allocations. Furthermore, we identify conditions under which the venture capitalist should choose to revise the investment offer if rejected by the entrepreneur. This paper thus moves us closer to a comprehensive theory of venture investment decisions.

We investigate how an entrepreneur’s behaviors during an initial interaction with a business angel can build, damage, or violate trust, and how the investor’s level of trust (prompted by the entrepreneur’s behavior) can affect his/her decision to make an investment offer. Our empirical analysis shows that entrepreneurs who receive offers from business angels exhibit a larger number of trust–building behaviors during the initial interaction and a smaller number of unintentional trust–damaging behaviors than those who do not receive an offer, and display few deliberate trust–violating behaviors. We further observe that the investor’s deployment of a control mechanism is a prerequisite for receiving an investment offer for all entrepreneurs who damage or violate trust.

This special issue contains articles that exemplify the role of operations management across the entrepreneurial value chain. This value chain encompasses all stages of the entrepreneurial phenomenon, including technology commercialization, where discovery, commitment, organization, and growth must take place. We report on a literature search that identifies research questions categorized with respect to topics crucial to operations management scholars and classify these questions under each stage of this value chain. The search guides the development of an evolutionary path for the use of resources, routines, and reputation (3Rs), often lacking in this process, and enables us to propose modeling and topical gaps in the literature. We offer a framework to set up exemplars for operational tradeoffs uniquely associated with the entrepreneurial value chain. We also articulate how five contributed articles in this issue tackle some of these tradeoffs, prior to introducing four perspective pieces. We hope this discussion motivates follow-on work and triggers a significant increase in the flow of articles that make it to both entrepreneurship and operations management top-tier academic and practitioner publications.

Potential followers are heterogeneous because of their access to alternative levels of complementary assets and the different degrees of relatedness of these assets. Using a decision-theory approach, we build a model that enables us to identify under what conditions a follower can afford to wait to enter a market, and for how long the delay is viable. We demonstrate that these conditions not only depend on the effect of industry age on the follower’s complementary asset characteristics, but also on both a direct and indirect effect of industry age on performance. Specifically, we show that a high degree of relatedness in the follower’s complementary assets does not necessarily afford the opportunity to wait, as the ability to wait depends on whether these direct and indirect effects are weakened or intensified by the strength of the relatedness.

Empirical observation suggests that several industrial clusters originate from employees who break off and locate their new firms close to former employers. The reasons for such a choice are complex and include a variety of costs’ considerations. We present a two-player three-stage simultaneous game with interdependent decisions concerning break-offs, deterrent compensations, location, and profit-maximizing production outputs. The structure of the game explains under what conditions a break-off is desirable, what location’s choice makes it optimal, and why the break-off process may lead to the birth of a cluster. We demonstrate how marginal production/congestion cost, degree of product differentiation, R&D investment in a region, and market size, all influence the likelihood of a firm’s break-off and its subsequent location decision. Our results provide a rationale for why, in industries in which technology plays a significant role, an increase in R&D investment in the region may encourage the break-off firm to locate away from the incumbent. We also show that subsidies aimed at increasing manufacturing activities and diffusing commercializable innovations can be ineffective in promoting clustering and unnecessary in larger markets, and their exact size is crucial in determining their effectiveness.

“Hybrid entrepreneurs” — those who maintain a wage job while starting a new enterprise — outnumber pure entrepreneurs in many countries. Yet, how hybrid entrepreneurs allocate their working hours between these two activities is not well understood. To better understand the relationship between hybrid entrepreneurs’ division of time between their wage jobs and new enterprises we develop a model that captures hybrid entrepreneurs’ decisions on the tradeoffs between financial risk and return as it relates to time allocation. We test two hypotheses based on utility theory, and challenge them with two hypotheses based on regulatory focus theory in a controlled experiment with 25 early stage entrepreneurs and 29 undergraduate students. In the computer-based experiment, entrepreneurs’ and students’ time allocation decisions (tied to monetary incentives) are used to test what would motivate them to work more or less hours in their entrepreneurial startups. We find that the actual time allocation decisions of the student group are somewhat in tune with utility theory, but that the entrepreneurs’ time allocation decisions are better explained by regulatory focus theory.

A dynamic view of the resource based theory (RBT) examines how a firm builds its resources over time, considering variations in resources’ growth rates while the firm attempts to grow. Accordingly, we consider the elasticity of accumulated resources to assess conditions where these resources might serve as substitutes for rather than complements to COGS during periods of growth. We specify a production function that links aggregate resource allocation among SG&A, R&D and COGS expenses to a firm’s revenue. This function yields a set of hypotheses on the elasticity of SG&A and R&D, and the productivity of COGS, while controlling for the revenue growth rate. We test these hypotheses on a dataset of 64 randomly selected firms that recently underwent an IPO, and a comparable set of 64 established public firms from four high-technology sectors. Results show that the accumulated stocks of resources can serve as substitutes for rather than complements to COGS, and the manner in which recent-IPO firms allocate and use resources differs from their established counterparts. We discuss the implications of associated elasticity and productivity results.