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Institution

London Business School

EducationLondon, England, United Kingdom
About: London Business School is a education organization based out in London, England, United Kingdom. It is known for research contribution in the topics: Portfolio & Equity (finance). The organization has 1138 authors who have published 5118 publications receiving 437980 citations. The organization is also known as: LBS.


Papers
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Journal ArticleDOI
TL;DR: In this article, the authors argue that academic research related to the conduct of business and management has had some very significant and negative influences on the practice of management, and that these influences have had a negative impact on the management practice.
Abstract: This article argues that academic research related to the conduct of business and management has had some very significant and negative influences on the practice of management. These influences ha...

3,299 citations

Journal ArticleDOI
TL;DR: In this article, the authors investigated contextual organizational ambidexterity, defined as the capacity to simultaneously achieve alignment and adaptability at a business-unit level, and found that a context characterized by a combination of stretch, discipline, support, and trust facilitates contextual ambidextrousness.
Abstract: We investigated contextual organizational ambidexterity, defined as the capacity to simultaneously achieve alignment and adaptability at a business-unit level. Building on the leadership and organization context literatures, we argue that a context characterized by a combination of stretch, discipline, support, and trust facilitates contextual ambidexterity. Further, ambidexterity mediates the relationship between these contextual features and performance. Data collected from 4,195 individuals in 41 business units supported our hypotheses. A recurring theme in a variety of organizational literatures is that successful organizations in a dynamic environment are ambidextrous—aligned and efficient in their management of today’s business demands, while also adaptive enough to changes in the environment that they will still be around tomorrow (Duncan, 1976; Tushman & O’Reilly, 1996). The simple idea behind the value of ambidexterity is that the demands on an organization in its task environment are always to some degree in conflict (for instance, investment in current versus future projects, differentiation versus low-cost production), so there are always trade-offs to be made. Although these trade-offs can never entirely be eliminated, the most successful organizations reconcile them to a large degree, and in so doing enhance their long-term competitiveness. Authors have typically viewed ambidexterity in structural terms. According to Duncan (1976), who first used the term, organizations manage trade-offs between conflicting demands by putting in place “dual structures,” so that certain business units—or groups within business units—focus on alignment, while others focus on adaptation (Duncan, 1976).

3,009 citations

Journal ArticleDOI
TL;DR: In this article, the authors evaluate the out-of-sample performance of the sample-based mean-variance model, and its extensions designed to reduce estimation error, relative to the naive 1-N portfolio.
Abstract: We evaluate the out-of-sample performance of the sample-based mean-variance model, and its extensions designed to reduce estimation error, relative to the naive 1-N portfolio. Of the 14 models we evaluate across seven empirical datasets, none is consistently better than the 1-N rule in terms of Sharpe ratio, certainty-equivalent return, or turnover, which indicates that, out of sample, the gain from optimal diversification is more than offset by estimation error. Based on parameters calibrated to the US equity market, our analytical results and simulations show that the estimation window needed for the sample-based mean-variance strategy and its extensions to outperform the 1-N benchmark is around 3000 months for a portfolio with 25 assets and about 6000 months for a portfolio with 50 assets. This suggests that there are still many "miles to go" before the gains promised by optimal portfolio choice can actually be realized out of sample. The Author 2007. Published by Oxford University Press on behalf of The Society for Financial Studies. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org, Oxford University Press.

2,809 citations

Journal ArticleDOI
TL;DR: In this paper, the authors present a method for measuring beta when share price data suffer from this problem, using a one-in-three random sample of all U.K. Stock Exchange shares from 1955 to 1974.

2,690 citations

Journal ArticleDOI
TL;DR: The results indicate that the social interaction and network ties dimensions of social capital are indeed associated with greater knowledge acquisition, but that the relationship quality dimension is negatively associated with knowledge acquisition.
Abstract: Employing a sample of 180 entrepreneurial high-technology ventures based in the United Kingdom, we examine the effects of social capital in key customer relationships on knowledge acquisition and knowledge exploitation. Building on the relational view and on social capital and knowledge-based theories, we propose that social capital facilitates external knowledge acquisition in key customer relationships and that such knowledge mediates the relationship between social capital and knowledge exploitation for competitive advantage. Our results indicate that the social interaction and network ties dimensions of social capital are indeed associated with greater knowledge acquisition, but that the relationship quality dimension is negatively associated with knowledge acquisition. Knowledge acquisition is, in turn, positively associated with knowledge exploitation for competitive advantage through new product development, technological distinctiveness, and sales cost efficiency. Further, our results provide evidence that knowledge acquisition plays a mediating role between social capital and knowledge exploitation. Copyright © 2001 John Wiley & Sons, Ltd.

2,556 citations


Authors

Showing all 1156 results

NameH-indexPapersCitations
Stephen J. Wood10570039797
Viral V. Acharya9937631776
Michael Frese9738437375
James Taylor95116139945
E. Tory Higgins9436348833
Howard Thomas8350426945
John Roberts7836545997
Dinesh Bhugra7068218690
Jiju Antony6841117290
David De Cremer6529713788
Andy Neely6522226624
Gerard George6414527363
Julian Birkinshaw6423329262
Geoffrey C. Williams6423119261
Alan Manning6324517975
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
20237
202250
2021179
2020165
2019166
2018145