95 research outputs found
The culture of European high-tech start-ups:an empirical exploration of its influence on strategic cooperation and partner selection
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Implications of work effort and discretion for employee well-being and career-related outcomes: an integrative assessment
How does work effort affect employee outcomes? The authors bridge distinct literatures on the well-being versus career-related implications of work effort by analyzing the relation of overtime work and work intensity to both types of outcomes. They also extend examination of the role of discretion in modifying the effects of work effort from well-being to career-related outcomes. Using data from the fifth and sixth European Working Conditions Surveys, the authors show that greater work effort relates strongly to reduced well-being and modestly to inferior career-related outcomes, while discretion may attenuate these adverse implications. Even with discretion, work intensity generally is a stronger predictor of unfavorable outcomes than overtime work. Implications include the need for employees to become aware of the broader limitations of excessive work effort, for employers to give discretion when viable, and for public policy to devise strategies that help limit the adverse consequences of work intensity
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The gloomy side of embeddedness: The effects of overembeddedness on inter-firm partnership formation
We discuss the ‘gloomy’ side of firms’ embeddedness in networks of inter-firm partnerships. We propose a nested understanding of the effects of three levels of overembeddedness – environmental, inter-organizational and dyadic overembeddedness – on subsequent inter-firm partnership formation and argue for a joint examination of these three levels and their interactions over time. As a whole, increases in firms’ embeddedness will generate decreasing returns to the firms involved, prompting (i) the search for and attachment to novel partners and (ii) the dissolution of extant partnerships. On the flipside, overembeddedness thus sparks network evolution – by cueing firms to look beyond their embedded partnerships
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When does knowledge acquisition in R&D alliances increase new product development? The moderating roles of technological relatedness and product-market competition
In studying the performance consequences of research and development (R&D) alliances, one stream of research has concentrated on the acquisition of partners’ technological knowledge whereas another has focused on firms’ new product development outcomes. Bridging these two research streams, this study directly connects knowledge acquisition through R&D alliances to new product development and examines when R&D alliances enable firms to apply acquired technological knowledge in the product domain. Using unique longitudinal data on a sample of firms engaged in R&D alliances in the information technology industry, I find that knowledge acquisition is on average positively associated with firms’ numbers of new products. However, I also find that knowledge acquisition is substantially more beneficial for new product development both when firms and their partners are active in similar technology domains and when they operate in distinct product markets
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Characteristics of innovation-driven interfirm alliances, 1957-2006: Analysis and research directions
Learning horizon and optimal alliance formation
We develop a theoretical Bayesian learning model to examine how a firm’s learning horizon, defined as the maximum distance in a network of alliances across which the firm learns from other firms, conditions its optimal number of direct alliance partners under technological uncertainty. We compare theoretical optima for a ‘close’ learning horizon, where a firm learns only from direct alliance partners, and a ‘distant’ learning horizon, where a firm learns both from direct and indirect alliance partners. Our theory implies that in high tech industries, a distant learning horizon allows a firm to substitute indirect for direct partners, while in low tech industries indirect partners complement direct partners. Moreover, in high tech industries, optimal alliance formation is less sensitive to changes in structural model parameters when a firm’s learning horizon is distant rather than close. Our contribution lies in offering a formal theory of the role of indirect partners in optimal alliance portfolio design that generates normative propositions amenable to future empirical refutation
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