Search results

This article considers real options approaches through the lens of firm's resource reallocation processes. It explores some potential drivers and consequences of mismatches between initial resource allocation logics and subsequent reallocation realities, highlighting a process of rational escalation in the presence of sunk costs. It also presents a new perspective on the traditional stage-gate process, and considers some recent empirical evidence on the efficiency of resource reallocation processes in organizations.

There is a growing need for measures assessing technological changes in systemic contexts as business ecosystems replace standalone products. In these ecosystem contexts, organizations are required to manage their innovation processes in increasingly networked and complex environments. In this paper, we introduce the technology and ecosystem clockspeed measures that can be used to assess the temporal nature of technological changes in a business ecosystem. We analyze systemic changes in the personal computer (PC) ecosystem, explicitly focusing on subindustries central to the delivery of PC gaming value to the end user. Our results show that the time-based intensity of technological competition in intertwined subindustries of a business ecosystem may follow various trajectories during the evolution of the ecosystem. Hence, the technology and ecosystem clockspeed measures are able to pinpoint alternating dynamics in technological changes among the subindustries in the business ecosystem. We subsequently discuss organizational considerations and theoretical implications of the proposed measures.

This article considers the relationship between consumers’ valuation of performance improvements and technology development over the technology life cycle. Presenting a demand-based perspective, it explores how the character of life cycle maturity, the nature of competitive threats, and firms’ innovation incentives all change when consumer demand for performance matures in advance of a technology’s performance trajectories. It characterizes demand maturity by introducing the idea of a demand S curve as a complement to the traditional technology S curve. In doing so, it offers a new lens for assessing firms’ prospects of achieving superior performance through the commercialization of new technologies.

This paper explores the emergence and coordination of synchrony in networked groups like those that develop integrated product platforms in collaborative ecosystems. While synchronized actions are an important objective for many groups, interorganizational network theory has yet to explore synchrony in depth perhaps because it does not fit the typical diffusion models this research relies upon. By adding organizationally realistic features – sparse network structure and intentional coordination – to the firefly model from theoretical biology, I take some first steps in understanding synchrony in organizational groups. Like diffusion, synchrony is more effective in denser networks, but unlike diffusion clustering decelerates synchrony’s emergence. Coordination by a few group members accelerates group-wide synchrony, and benefits the coordinating organizations with a higher likelihood that it converges to the coordinating organization’s preferred rhythm. This likelihood of convergence to an organization’s preferred rhythm – what I term synchrony performance – increases in denser networks, but is not dependent on tie strength and clustering.

Firms tend to transfer more knowledge in technology joint ventures compared to contractual technology agreements. Using insights from new institutional economics, this chapter explores to what extent the alliance governance association with interfirm knowledge transfer is sensitive to an evolving industry norm of collaboration connected to the logic of open innovation. The chapter examines 1,888 dyad-year observations on firms engaged in technology alliances in the U.S. information technology industry during 1980–1999. Using fixed effects linear models, it analyzes longitudinal changes in the alliance governance association with interfirm knowledge transfer, and how such changes vary in magnitude across bilateral versus multipartner alliances, and across computers, telecommunications equipment, software, and microelectronics subsectors. Increases in industry-level alliance activity during 1980–1999 improved the knowledge transfer performance of contractual technology agreements relative to more hierarchical equity joint ventures. This effect was concentrated in bilateral rather than multipartner alliances, and in the software and microelectronics rather than computers and telecommunications equipment subsectors. Therefore, an evolving industry norm of collaboration may sometimes make more arms-length governance of a technology alliance a credible substitute for equity ownership, which can reduce the costs of interfirm R&D. Overall, the chapter shows that the performance of material practices that constitute innovation ecosystems, such as interfirm technology alliances, may differ over time subject to prevailing institutional norms of open innovation. This finding generates novel implications for the literatures on alliances, open innovation, and innovation ecosystems.

Rather than organize as traditional firms, many of today’s companies organize as platforms that sit at the nexus of multiple exchange and production relationships. This chapter considers a most basic question of organization in platform contexts: the choice of boundaries. Herein, I investigate how classical economic theories of firm boundaries apply to platform-based organization and empirically study how executives made boundary choices in response to changing market and technical challenges in the early mobile computing industry (the predecessor to today’s smartphones). Rather than a strict or unavoidable tradeoff between “openness-versus-control,” most successful platform owners chose their boundaries in a way to simultaneously open-up to outside developers while maintaining coordination across the entire system.