«Characteristics of effective leadership A comparison between theory and business reality. Characteristics of effective leadership ...» Document abstract
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4 word format
Language : english
management
case study
date published
29/04/2008
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level : General public
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SummaryThis practicum field project is the result of an interview conducted with the VP Corporate Communications in Alcatel-Lucent, Paris, France.* The goal of this project is to compare the views of a successful executive with the theoretical approach provided by several scholars about the characteristics of leadership. In other words, my goal is to compare theory with business reality. The above individual possesses profound academic background and diverse working experience. She is in managerial positions for the last five years and she has contributed significantly to all the organizations she has been engaged in the course of her professional career. In relation to my questions, in most of the cases she meets the theoretical approach of the topic as presented in this project. However, there are slight differentiations in particular aspects of the topic. Hence, after each theoretical approach I present my conclusions and critical analysis on what has been discussed with the above executive.
« is defined as the number of effective units of studies work done on relations between several variables that the influence some firm characteristics exert on ...» Document abstract
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260 word format
Language : english
economics
theses
date published
27/07/2006
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level : Expert
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SummaryFor several reasons, knowledge cannot be treated like any other commodity. One of these reasons is the nonrivalrous nature of knowledge, which means that one person’s use of certain knowledge does not diminish another person’s use of the same knowledge (at the same time). This important property of knowledge is used in several early models of R&D-based growth1,
e.g. Romer (1990), Grossman and Helpman (1991), and Aghion and Howitt (1992). In these models this property leads to a scale effect, which boils down to larger economies growing faster than smaller economies (with the measure of size suitably defined (cf. Backus, Kehoe and Kehoe 1992)).
In an influential paper, Jones (1995a) pointed out that growth with scale effects, as predicted
by the early models of R&D-based growth, is inconsistent with empirical facts. Over the last
40 years the OECD countries have experienced a tremendous rise in the number of people involved in R&D activities whereas the growth rates of per-capita income have shown no corresponding increase. This is a puzzling observation and has led to new models of R&D- based growth that did not incorporate scale effects e.g. Jones (1995b), Smulders and van de Klundert (1995), Young (1998), Li (2000), and Peretto and Smulders (2002).
Generally, however, these models suffer from the ‘Solow critique’; Solow (1994) criticizes
(some) growth theorists because they “… often just insert favorable assumptions in an unearned way; and then when they put in their thumb and pull out the vary plum they have inserted, there is a tendency to think that something has been proved.” (p. 53). In the models
of growth without scale effects the prediction of a scale effects in growth of the early models
of R&D-based growth is removed by limiting the extent of the spillovers associated with knowledge’s nonrivalrousness, but often the much-needed (micro-)economic foundation for
the crucial assumption in these models regarding the extent of knowledge spillovers - and the
mechanism limiting their extent - is lacking. Assuming that knowledge is rivalrous (not nonrivalrous) to limit spillovers and dispose of the scale effects prediction of the early models
of R&D-based growth simply does not shed much light on the issue of growth without scale effects however.
provide background information regarding, amongst others, work discussed in the main text, data used in figures, etc.
e.g. Romer (1990), Grossman and Helpman (1991), and Aghion and Howitt (1992). In these models this property leads to a scale effect, which boils down to larger economies growing faster than smaller economies (with the measure of size suitably defined (cf. Backus, Kehoe and Kehoe 1992)).
In an influential paper, Jones (1995a) pointed out that growth with scale effects, as predicted
by the early models of R&D-based growth, is inconsistent with empirical facts. Over the last
40 years the OECD countries have experienced a tremendous rise in the number of people involved in R&D activities whereas the growth rates of per-capita income have shown no corresponding increase. This is a puzzling observation and has led to new models of R&D- based growth that did not incorporate scale effects e.g. Jones (1995b), Smulders and van de Klundert (1995), Young (1998), Li (2000), and Peretto and Smulders (2002).
Generally, however, these models suffer from the ‘Solow critique’; Solow (1994) criticizes
(some) growth theorists because they “… often just insert favorable assumptions in an unearned way; and then when they put in their thumb and pull out the vary plum they have inserted, there is a tendency to think that something has been proved.” (p. 53). In the models
of growth without scale effects the prediction of a scale effects in growth of the early models
of R&D-based growth is removed by limiting the extent of the spillovers associated with knowledge’s nonrivalrousness, but often the much-needed (micro-)economic foundation for
the crucial assumption in these models regarding the extent of knowledge spillovers - and the
mechanism limiting their extent - is lacking. Assuming that knowledge is rivalrous (not nonrivalrous) to limit spillovers and dispose of the scale effects prediction of the early models
of R&D-based growth simply does not shed much light on the issue of growth without scale effects however.
provide background information regarding, amongst others, work discussed in the main text, data used in figures, etc.
Table of Contents- Grouth and scale effects
- Knowledge, R&D and spilovers, at the firm
- Grouth without scale effects and structural
- Measurement issues in the study of R&D-based
- The product life cycle, demand
1
knowledge network
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