153 research outputs found

    Business experience and start-up size: buying more lottery tickets next time around?

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    This paper explores the determinants of start-up size by focusing on a cohort of 6247 businesses that started trading in 2004, using a unique dataset on customer records at Barclays Bank. Quantile regressions show that prior business experience is significantly related with start-up size, as are a number of other variables such as age, education and bank account activity. Quantile treatment effects (QTE) estimates show similar results, with the effect of business experience on (log) start-up size being roughly constant across the quantiles. Prior personal business experience leads to an increase in expected start-up size of about 50%. Instrumental variable QTE estimates are even higher, although there are concerns about the validity of the instrument

    How managers can build trust in strategic alliances: a meta-analysis on the central trust-building mechanisms

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    Trust is an important driver of superior alliance performance. Alliance managers are influential in this regard because trust requires active involvement, commitment and the dedicated support of the key actors involved in the strategic alliance. Despite the importance of trust for explaining alliance performance, little effort has been made to systematically investigate the mechanisms that managers can use to purposefully create trust in strategic alliances. We use Parkhe’s (1998b) theoretical framework to derive nine hypotheses that distinguish between process-based, characteristic-based and institutional-based trust-building mechanisms. Our meta-analysis of 64 empirical studies shows that trust is strongly related to alliance performance. Process-based mechanisms are more important for building trust than characteristic- and institutional-based mechanisms. The effects of prior ties and asset specificity are not as strong as expected and the impact of safeguards on trust is not well understood. Overall, theoretical trust research has outpaced empirical research by far and promising opportunities for future empirical research exist

    Predicting new venture survival and growth: does the fog lift?

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    This paper investigates whether new venture performance becomes easier to predict as the venture ages: does the fog lift? To address this question we primarily draw upon a theoretical framework, initially formulated in a managerial context by Levinthal (Adm Sci Q 36(3):397–420, 1991) that sees new venture sales as a random walk but survival being determined by the stock of available resources (proxied by size). We derive theoretical predictions that are tested with a 10-year cohort of 6579 UK new ventures in the UK. We observe that our ability to predict firm growth deteriorates in the years after entry—in terms of the selection environment, the ‘fog’ seems to thicken. However, our survival predictions improve with time—implying that the ‘fog’ does lift

    A dynamic capabilities-based entrepreneurial theory of the multinational enterprise

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    Atomic-accuracy prediction of protein loop structures through an RNA-inspired ansatz

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    Consistently predicting biopolymer structure at atomic resolution from sequence alone remains a difficult problem, even for small sub-segments of large proteins. Such loop prediction challenges, which arise frequently in comparative modeling and protein design, can become intractable as loop lengths exceed 10 residues and if surrounding side-chain conformations are erased. This article introduces a modeling strategy based on a 'stepwise ansatz', recently developed for RNA modeling, which posits that any realistic all-atom molecular conformation can be built up by residue-by-residue stepwise enumeration. When harnessed to a dynamic-programming-like recursion in the Rosetta framework, the resulting stepwise assembly (SWA) protocol enables enumerative sampling of a 12 residue loop at a significant but achievable cost of thousands of CPU-hours. In a previously established benchmark, SWA recovers crystallographic conformations with sub-Angstrom accuracy for 19 of 20 loops, compared to 14 of 20 by KIC modeling with a comparable expenditure of computational power. Furthermore, SWA gives high accuracy results on an additional set of 15 loops highlighted in the biological literature for their irregularity or unusual length. Successes include cis-Pro touch turns, loops that pass through tunnels of other side-chains, and loops of lengths up to 24 residues. Remaining problem cases are traced to inaccuracies in the Rosetta all-atom energy function. In five additional blind tests, SWA achieves sub-Angstrom accuracy models, including the first such success in a protein/RNA binding interface, the YbxF/kink-turn interaction in the fourth RNA-puzzle competition. These results establish all-atom enumeration as a systematic approach to protein structure that can leverage high performance computing and physically realistic energy functions to more consistently achieve atomic resolution.Comment: Identity of four-loop blind test protein and parts of figures 5 have been omitted in this preprint to ensure confidentiality of the protein structure prior to its public releas

    A Project Portfolio Management Approach to Tacklingthe Exploration/Exploitation Trade-off

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    Organizational ambidexterity (OA) is an essen-tial capability for surviving in dynamic business environ-ments that advocates the simultaneous engagement inexploration and exploitation. Over the last decades,knowledge on OA has substantially matured, coveringinsights into antecedents, outcomes, and moderators of OA.However, there is little prescriptive knowledge that offersguidance on how to put OA into practice and to tackle thetrade-off between exploration and exploitation. To addressthis gap, the authors adopt the design science researchparadigm and propose an economic decision model asartifact. The decision model assists organizations inselecting and scheduling exploration and exploitation pro-jects to become ambidextrous in an economically reason-able manner. As for justificatory knowledge, the decisionmodel draws from prescriptive knowledge on projectportfolio management and value-based management, andfrom descriptive knowledge related to OA to structure thefield of action. To evaluate the decision model, its designspecification is discussed against theory-backed designobjectives and with industry experts. The paper alsoinstantiates the decision model as a software prototype andapplies the prototype to a case based on real-world data

    Catching-up in the global factory: analysis and policy implications

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    MNEs shape the location of activities in the world economy, linking diverse regions in what has been called the global factory. This study portrays the evolution of incomes and employment in the global factory using a quantitative input–output approach. We find emerging economies forging ahead relative to advanced economies in income derived from fabrication activities, handling the physical transformation process of goods. In contrast, convergence in income derived from knowledge-intensive activities carried out in pre- and post-fabrication stages is much slower. We discuss possible barriers to catching-up and policy implications for emerging economies in developing innovation capabilities, stressing the pivotal role of MNEs

    Sustainability in the face of institutional adversity : market turbulence, network embeddedness, and innovative orientation

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