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Many new organizations adopt a platform business model that facilitates transactions among various parties. While the impacts of these platform firms on traditional business environments are visible in many industries, relatively little attention has been paid to their entrepreneurial origins. Analyzing 70 interviews with platform entrepreneurs, managers, and venture capitalists, we develop a grounded theoretical framework that extends existing perspectives in entrepreneurship and digital platforms and applies them to the context of entrepreneurial platforms. Our research suggests that platform firms emerge over three phases, with an initial emphasis on a marketplace or a core technology, while some may iterate between these two. Implications for entrepreneurial decision-making and the emergence of platform firms are discussed. [ABSTRACT FROM AUTHOR]

An important challenge facing contemporary society is whether and how firms will transition from established, fossil fuel-based technologies to green technologies such as electric vehicles, solar cells, and wind turbines. Prior research and policy discussions have recognized that these choices are based not on a comparison of the current state of these technologies but rather an assessment of technologies with varying trajectories of improvement. An environmentally friendly technology may initially be inferior (e.g., cost more) but become superior as the technology evolves. We argue that recognition of these trajectories is a necessary but not sufficient condition for understanding and guiding firms' technological choices. These technological trajectories are often clouded by substantial uncertainty. While uncertainty is often seen as a barrier to change, in this paper, we highlight how uncertainty in these technological trajectories may, in fact, stimulate technological change. We model competition between two technologies -- an older established technology and a new, presumed environmentally desirable technology. We find that the impacts of uncertainty are not uniform and that different levels and forms of uncertainty may encourage or discourage investment. Our core insight is that when uncertainty is large relative to the expected rate of technology improvement, it is uncertainty, rather than expectations about this rate of improvement, that determines the likelihood of choosing an environmentally friendly technology. [ABSTRACT FROM AUTHOR]

Although the effectiveness of the scientific decision-making approach has been demonstrated, most studies have focused on individual entrepreneurs. This panel symposium aims to expand the scope of this research by examining the implications of the scientific approach within large organizations. Our distinguished panelists will present their research, including insights on the challenges and opportunities, decision-making biases, measurement of the approach at scale, and how it differs in application between individual entrepreneurs and large organizations. The panelists will also talk about the topic from a cognitive neuroscience perspective and discuss ways to deal with the problems in current research that focuses on studying the approach and its effects. This panel will provide insights into the effective implementation and navigation of the scientific approach within large organizations while also addressing the unique challenges faced in this context. [ABSTRACT FROM AUTHOR]

In this symposium, we bring together the four papers that examine the origin and impact of what defines ecosystem rules. While recent work actively recognizes ecosystems as a ubiquitous architecture of economic activities, the literature often assumes ecosystem alignment structure as given. Less understood is how the common rules of ecosystems that define alignment structure emerge and how they drive differences in firms' market position in an ecosystem. The four papers discuss what structural and institutional conditions drive asymmetric power distribution in interdependency, and how firms shape and materialize technological interdependence to their advantages. Employing diverse theoretical perspectives and methodologies, the papers in this symposium address an interesting set of questions to advance our understanding of ecosystem alignment structure. The symposium should be of interest to scholars of strategic management and technology innovation management. * What Drives and Defines Digital Platform Power? * Presenter: Michael G Jacobides; London Business School * The Role of Institutional User Community in Technology Standard-setting and Ecosystem Evolution * Presenter: Najoung Lim; U. of Maryland * Presenter: Rajshree Agarwal; U. of Maryland * Shaping Ecosystem Rules: How Interdependencies Affect Firms' Shaping Success Through Tech Standard * Presenter: Ram Ranganathan; U. of Texas at Austin * Presenter: John S. Chen; U. of Florida * Presenter: Anindya Ghosh; Tilburg U. * Value Creation Trade-off in Ecosystems:Leveraging Complementarities While Managing Interdependencies * Presenter: Shiva Agarwal; U. of Texas at Austin * Presenter: Rahul Kapoor; The Wharton School, U. of Pennsylvania [ABSTRACT FROM AUTHOR]

We develop a computational simulation of entrepreneurial learning and decision-making to investigate four emergent propositions from the lean startup movement: (1) entrepreneurs should be prepared to pivot rather than commit to a single idea, (2) they should pivot often, (3) they should pivot early rather than wait to pivot, and (4) that pivoting is a remedy for bias. We find that, across a range of pivoting policies, entrepreneurs that consider pivoting perform better than those who do not. For unbiased entrepreneurs, however, a conservative pivot strategy, which leads to less frequent pivots, outperforms more aggressive approaches. Similarly, unbiased entrepreneurs optimally spend more time examining an initial idea before pivoting than the lean startup literature might seem to suggest. Finally, our model shows that pivoting does serve as a remedy for bias, and that overconfident entrepreneurs perform better when following more aggressive pivoting rules than their unbiased counterparts. [ABSTRACT FROM AUTHOR]

The symposium features five papers that examine how firms' engagement in the reduction of various types of uncertainty influence their entry strategies and inventive activity as well as impact their performance. The five papers use diverse theoretical frameworks, methodologies, levels of analysis, and empirical contexts. Together, they address an interesting set of questions and advance our knowledge about firm and industry evolution, with implications for firm performance, subsequent entry patterns, innovation, and entrepreneurial actions. The symposium should be of interest to scholars of strategic management, technology management, and entrepreneurship. [ABSTRACT FROM AUTHOR]

This symposium focuses on the question of how diversified firms should allocate resources among their different areas of business -- a fundamental issue within strategic management research. Despite the importance of the topic, after early classic studies (e.g. Bower, 1970), there was a decline in the strategy field in research in which the topic of resource allocation was in the foreground of the studies. Instead, resource allocation played a secondary role in papers which focused on issues such as international expansion, corporate entrepreneurship initiatives, or divestment decisions (Birkinshaw, 1997; Hoskisson, Johnson, and Moesel, 1994; Tan and Vertinsky, 1996; Wright and Ferris, 1997). Recently, there has been a resurgence in research which directly focuses on the topic of resource allocation and redeployment (for overviews, see Busenbark, Wiseman, Arrfelt, & Woo, 2017; Folta, Helfat, & Karim, 2016; Sengul, Almeida Costa, & Gimeno, 2019). Results from these recent empirical studies yielded mixed findings regarding the question of how efficiently multi-business firms are able to allocate resources internally among their different business units. In order to move our understanding of this important issue forward, there is a pressing need for more theory building and empirical research in corporate strategy. In order to assist in this re-energizing of resource allocation research, it is the goal of this symposium to bring together contributions from different angles on the topic of resource allocation. Specifically, the symposium considers four diverse perspectives on resource allocation; namely regarding (i) innovation-related outcomes of different resource allocation strategies on the headquarters level, (ii) the interrelationships between different areas of business in the portfolio of a diversified firm, (iii) the management of uncertainty when discovering opportunities for resource redeployment, and (iv) a capabilities-based understanding of why some firms are more successful than others in allocating resources. This symposium therefore contributes to the broadening of our understanding about how diversified firms should allocate resources among their different areas of business. [ABSTRACT FROM AUTHOR]

The existence of a learning curve, in which costs decline with cumulative experience, suggests that early entry (and production) provides learning opportunities that create competitive advantage by reducing future production costs relative to later entrants. We argue that this proposition is subject to an under-appreciated limitation -- that progress down the learning curve may be uncertain. If there is uncertainty in the learning curve, then the taken-for-granted wisdom regarding the benefits of learning curves may over- or under-emphasize the value of early entry. We consider two forms of uncertainty -- prospective (future production costs) and contemporaneous (current production costs). We demonstrate computationally that while prospective uncertainty in the learning curve enhances the learning benefits of early entry and production, contemporaneous uncertainty reduces these benefits. Further, we examine the implication of these findings for learning curve spillovers between leader and laggard firms. We conclude with implications for future research regarding learning curves and the pursuit of early mover advantage. [ABSTRACT FROM AUTHOR]

Startups are commonly founded by teams rather than single individuals. We develop a computational model that examines the differential performance among alternative decision-making structures in entrepreneurial teams, when teams seek to exploit an opportunity of unknown quality, receive noisy information about the opportunity's quality both prior to and following entry, and are potentially subject to multiple forms of confidence bias. We find that the optimal decision structure for an entrepreneurial team depends on what is known ex ante about the biases of team members. In particular, decision-making structures in which all team members must agree are advantageous when those team members initially over-estimate the likelihood of the new ventures' success (i.e., are subject to overestimation bias). Similarly, decision-making structures in which all team members must agree are advantageous when all members have accurate initial beliefs, but update these beliefs too slowly (i.e., are subject to overprecision bias). By contrast, when team members' estimation and precision biases are not known precisely ex ante but are drawn independently from distributions with mean zero bias, equal partnerships (in which all agents must agree) perform relatively poorly, and it is advantageous to pre-commit to a decision structure in which one agent can buy out the others at the end of the pre-entry learning period. [ABSTRACT FROM AUTHOR]

Strategic investment decisions often involve substantial uncertainty. Real options theory suggests a decision logic emphasizing the value of small initial investments that provide the opportunity to make additional investments after uncertainty is resolved. However, real options theory is grounded in financial market assumptions that ignore the challenges associated with the decision to exercise or terminate an option. We develop a behavioral theory of real options that formally embeds realistic assumptions about informational properties of the environment and behavioral properties of firms. We recognize that an option model of decision-making and a bandit model of experiential learning are fundamentally interrelated models of sequential decision-making under uncertainty. Our theory predicts conditions under which over- or under-execution errors (exercising or terminating an option erroneously) are likely, and policies that will shift the relative balance between them. One implication is that firms formally applying Black-Scholes mathematics are likely to overestimate the value of a real option. [ABSTRACT FROM AUTHOR]