«The Lead User Method: A solution to improve new product success in rapidly changing markets? THE INNOVATION PROCESS: TYPOLOGY OF INNOVATIONS AND. ...» Document abstract
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Language : english
marketing
theses
date published
04/02/2006
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level : Expert
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SummaryInnovation, a crucial dilemma to be successful.
Innovating is crucial for a company in order to satisfy its customers ‘expectations and to cope with the competition in a market place which is everyday more and more challenging. However, coping with the competition doesn’t mean offering products which are somehow better or cheaper than the competition. Not at all. One must differentiate itself from the competition by offering innovative products, and the only way to be acknowledged as an innovative company is to stand one step further than the competition. Of course, it is easier to say than to implement.
Indeed, most of the companies try to innovate to rejuvenate their portfolio and to meet new trends. However, around 90% of the new mass consumer goods launched in Europe are failures compared to 95% rate in the USA . It is quite worrying and it is not only a reality in the mass consumer good market but also in all the rapidly evolving markets. These rates also stress the importance of new product development processes which can be used as major tools to decrease these risks of failures.
Most companies implement the traditional marketing research methods to generate new ideas, to develop and assess potential new concepts. These methods often try to discover new customer needs by analyzing customer complaints, buying patterns, preferences and enable to test the rate of customer acceptance once a prototype has been created through customer testing, pre-test market etc. However, these methods rarely offer insights to identify innovations that could have already been developed by users.
A professor of the MIT Sloan School of Management focused his studies on this poorly-known side of the new product development process. Prof. Eric von Hipple then defined the Lead User Method, a method designed to deepen our understanding of the innovation process and to improve the success of new product development by identifying who he calls “Lead users”.
Thus, a company undertaking a new product development process will experience a lot of pressure due to the high rates of new product failures.
How could we decrease the risks of failures and thus improve the chances of success of new products? Would the Lead user method provide a solution? Would it help better assess the needs and trends of the market and design a product that will fit these needs and trends?
This thesis will be aimed at understanding the reasons linked to new product failures and at assessing the conventional new product development methods and the Lead user method in order to provide an hypothesis that will improve the chances of success of new products.
Table of Contents- THE INNOVATION PROCESS: TYPOLOGY OF INNOVATIONS AND
- TYPOLOGY OF INNOVATIONS
- TYPOLOGY OF RISKS LINKED TO INNOVATION
- INPUTS PROVIDED BY TRADITIONAL NEW PRODUCT
- STEPS OF THE TRADITIONAL RESEARCH METHOD FOR NEW PRODUCT DEVELOPMENT
- THE ADOPTER CATEGORIZATION DURING INNOVATION DIFFUSION PROCESS
- ASSETS AND LIMITS OF THESE METHODS
- THE LEAD USER METHOD: A KEY TO SUCCESSFUL INNOVATION?
- DEFINITION OF THE LEAD USERS
- STEPS OF THE LEAD USER METHOD
- ASSESSING THE VALUE OF THE LEAD USER METHOD
- ASSESSING THE LEAD USER METHOD AS AN ASSET TO INNOVATE IN THE CLINICAL AND SCIENTIFIC RESEARCH
- PRESENTATION OF THE COMPANY
- THE STRATEGY OF INNOVATION WITHIN VENTANA
« Christened "cradle-to-cradle", this new method "proposes that human environment, these two trends can only lead us to a product for a defined user period - say ...» Document abstract
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Language : english
ecology & environment
term papers
date published
12/02/2007
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level : Advanced
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SummaryIn March 2005, the UN released its Millennium Ecosystem Assessment , the first comprehensive scientific audit of the state of the planet. Completed over four years by 2,000 experts, the survey demonstrates that economic activity has destroyed 60% of the Earth’s life-supporting ecosystems, threatening humanity’s ability to sustain its standards of living. Thus, even though the Industrial Revolution has brought about a tremendous rise in the standards of living of most in the Western World, and although globalization is spreading this wealth to an increasing number of people in the developing world, a growing number of worrisome environmental trends suggest that our current economic model is not sustainable in the medium- to short- run.
Table of Contents- Why our current economic model is unsustainable
- Why eco-efficiency alone is not the solution
- How C2C draws on nature to fix our model
- How to apply C2C to product design
- C2C in action: Herman Miller and the Mirra' Chair
- C2C: the next industrial revolution?
- Exhibits
« form the main mechanism behind the proposed solution to reconciling spillovers are strong enough to lead to a measured using a patent-based method (see also ...» Document abstract
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260 word format
Language : english
economics
theses
date published
27/07/2006
review : not yet assessed
level : Expert
requested 33 times
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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