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Successful Innovation Means Managing the Losers

Written by packagin on May 20th, 2009

packaging innovation
Carl Cullotta asked:


Most companies in the innovation game can proudly point to their winners–those new products/services that launched success fully and exceeded expectations for re venue/profit/market share. However, those same companies often express frustration/dissatisfaction with their overall return on innovation investment. Frank Lynn & Associates has worked with many companies that are considered innovators in their industries. This issue of the Client Communiqu shares some lessons learned from the firm’s experience with those leaders.

Lesson Learned: Even the leading innovators express frustration with the process.

We see three common issues that create dissatisfaction: metrics, project initiation, and the innovation process. Inappropriate metrics result in misplaced expectations–even the most successful innovators should expect fewer “hits” than “misses.” Misguided project initiation clogs the development pipeline with so many low-probability projects that the winners cannot be funded properly. And, poor process management sustains the ultimate losing bets in the pipeline for too long. Resources are fragmented across too many non-productive projects, again under-funding the high-probability opportunities.

Lesson Learned: Successful innovators have established metrics that highlight the process.

Most companies measure innovation based on the outputs. For example, a common benchmark demands that 20% of company revenues are generated from products/services launched in the last three to five years. This may be an appropriate strategic goal, but it does not measure the effectiveness of the innovation process. (Even the poorest process can meet this revenue goal if enough resources are thrown at it.)

We have found that the most effective metrics provide actionable insights to the process of innovation. Some of the better practices include:

> Revenue return/dollars invested–including both headcount and hard costs of innovation. This measure provides an indicator as to how well you are allocating resources. Actions derived from this metric could include a change in the project staffing model or changes to the timing of the hard costs (patent application, field tests, etc.) to help lower overall project costs without affecting positive outcomes

> Average number of projects/innovation employee–often, companies take the approach that “every idea is a good idea.” So many development projects are started that the staff cannot devote sufficient resources to any to effectively move them forward. “Addition by subtraction” can result by limiting, or even capping, the number of development projects allowed in the pipeline at any time. A second benefit of this approach is how potential development projects are screened and justified, which is likely to become more rigorous and disciplined

> Average project duration–companies that struggle with innovation have trouble saying “no.” The slimmest glimmer of hope is enough for the sponsor (often an executive) to keep the project alive. The pipeline remains clogged, and the best bet opportunities cannot receive the critical mass of resources they require to move forward. A metric to address this issue is a hard target for average project duration. This metric results in more frequent and disciplined project review. Even a goal to decrease average project duration by 10% will result in quicker “go/no go” decisions and better overall resource utilization

Lesson Learned: Successful innovators actively manage the source of development projects.

Historically, companies tended to take an “inside out” approach to innovation (i.e., “let the inventors invent”). The result was that the vast majority of projects had little direct relation to a market need. While these projects often resulted in neat new ways to use new technologies, they were usually considered ahead of their time. (A good example is a mainstream technology used in warehousing and distribution today–RFID (radio frequency identification). When introduced in the mid 1980’s, they were generally met with market indifference.)

As the “market driven” buzzword took hold, many companies moved to the other extreme. Every development project has to have justification from the marketplace. While hit rates on innovation did improve, this approach lost the “quantum leap” advances–too many of the projects resulted in small incremental improvements in features/benefits. These were certainly welcomed, but not market changing.

The most appropriate approach is a combination of the above extremes. We use a benchmark of 75%–75% of the projects initiated should be market driven. These projects are targeted from the outset to deliver a specific benefit to a specific market segment. The desired competitive advantage for the innovator is stated as part of the justification for the project. Effectively, these 75% of projects are sponsored by the marketing/sales organizations. The remaining 25% of projects are less constrained. Sponsorship can come from anywhere within the organization. The inventors are allowed to invent, and while the hit rate on these projects is substantially less than the market driven ones, the payoff can be substantially higher.

Lesson Learned: A key differentiator that separates innovation leaders is the discipline in process management.

A world class innovation process requires disciplined management. State of the art today is the “stage gate” process. Development projects are managed through a series of stages. Each stage culminates in a review and “go/no go” decision. Only those projects that pass through this gate are funded to the next stage. The discipline introduced through this review process assures that the development pipeline is kept lean, and resources are skewed to the highest probability opportunities.

While the concept of a stage gate process is easy to envision, what separates the successful innovators from the rest is the set of inputs used at each stage. Assessment of both technical and market feasibility are intertwined. A typical stage gate process would consist of the following stages and inputs:

> Stage One: Concept Definition–the purpose here is to articulate the logic behind the development concept, as well as the assumptions that justify the project investment

> From the technical perspective, the basic science/engineering hypotheses are introduced. The sponsor also provides a road map as to how the technology would be developed and scaled up. What assumptions would have to be tested? Where are the potential barriers? And what is the technical project plan for development?

> From the market perspective, some broad definition of the target market and potential benefit must be provided. To whom would this product/service be sold? Why would customers prefer it over existing solutions? Why not? Typically, this information is gathered through secondary data and/or a few conversations with potential customers to gauge desire to have an alternative solution

> Stage Two: Proof of Concept–the purpose of the proof of concept gate is to provide evidence that validates the concept behind the development project. Broad financial metrics are introduced to begin to flesh out the potential return on the innovation

> Proof of concept from the technical perspective means that the science/technology works. Whether in a lab or pilot plant environment, prototypes can be produced to meet the form and function requirements outlined in the concept design

> From the market perspective, positive reaction to the concept must be proven. Through some combination of qualitative market research (”what if” testing) and quantitative research methods, a sense for market acceptance, potential size of market and share, and broad price/value relationship versus existing alternatives must be established

> Stage Three: Commercial Viability–at this stage, the purpose is to assure the concept has “scalability”

> From a technical perspective, the ability to manufacture the product on production scale (or replicate the service model) must be proven. And, the economics or doing so must remain in parameters set earlier in the concept definition stages

> From the market perspective, the concept must pass “beta testing.” Prototypes should be accepted by target customers and the perceived benefits realized. Reactions of target customers at this stage will provide guidance to the timeframe and aggressiveness of the launch and ramp-up, along with the financial ramifications

> Stage Four: Commercial Positioning–the purpose of this final development stage is to define the most viable positioning of the product/service prior to launch. This stage serves as the bridge to the commercialization steps

> From a technical perspective, the positioning step proves that the product/service can be produced, packaged, and delivered to the target customer in a form that meets the promise of the concept for the customer and provides value relative to existing alternatives used by that customer

> From a market perspective, the parameters for launch must be established. These include all aspects of the offering, including price points, packaging, etc. Often, these are established by launching the product/service on a small scale (i.e., in a couple of test markets) and making the necessary modifications in the offering prior to broad commercialization

> Stage Five: Launch–the launch stage represents the handoff of ownership of the project from the development group to the mainstream organization. Product or market segment management takes ownership. Business plans are developed, including revenue goals, operational strategies, sales/marketing/channel strategies, etc. to bring the innovation into the mainstream of the business

Summary

If we look at the big picture, we find that the most successful innovators understand the importance of managing the process. In doing so, they address each of the drawbacks discussed above. These companies understand that the metrics must address the process. They are driven to initiate projects primarily from the “outside in.” And, they are disciplined in managing the low-probability opportunities out of the pipeline as soon as possible. The result of these disciplines is that innovation leaders differentiate themselves as much by treatment of the losers as by generating a wealth of ideas or commercializing the winners.



Lance

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Want Results? Avoid Beauty Contests When It Comes To Package Design

Written by packagin on April 19th, 2009

packaging innovation
Tim Robertson asked:


Marketers will often turn to focus groups for feedback on current or proposed packaging design. Unfortunately, traditional focus groups tend to mimic beauty contests. They turn into opinion gathering sessions that support a participant’s point of view, rather than providing feedback on consumers’ actual buying behavior within the store environment where products are purchased.

Participants play art director over design issues, confuse the brand with the package design, react emotionally to price increase questions, and talk about what they “like” and “don’t like”. As a result, the output quality of this type of research is minimal at best.

On the other hand, effective behavior-based focus group research measures the effect of brand influence, analyzes the buying behavior of participants in a comparative retail environment, and uses eye-tracking technology to find out what consumers pay attention to - and what they ignore.

The significance of brand influence

Effective brand value testing involves separating the brand name from the actual proposed or current package design. This measurement gives an indication of how the brand is perceived prior to seeing a packaged product. Participants are then introduced to the packaging and asked if the new or proposed package design adds, or detracts from, perceived brand value. Marketers may be making a costly mistake if the perceived value of a brand is negatively affected by a new design architecture.

Buying behavior of participants in a retail environment

Packaging design is measured and tested in the comparative marketplace for which it is intended. A comparative marketplace is one in which the competition sits side by side for comparison and consideration. This is a circumstance that does not usually occur in print and broadcast media; as competitors usually do not jockey to be side-by-side.

According to Wharton School research, over one third of the brands displayed on the shelf are never seen. A colorful and exciting new design that is approved in the boardroom or chosen in a focus group may fail if all the other packages on the shelf in the same category are equally as colorful and exciting. Contrast is what makes a package design stand out on the shelf, and this can be achieved through the effective means of both design and structural innovation.

Eye-tracking technology

Consumers spend 2-3 seconds scanning a package for relevant information. If they do not immediately comprehend the benefit they will move on to a competitor’s brand. It is imperative to know what consumers are seeing and what they are not, and this can be done effectively with eye-tracking technology. This type of research gives marketers an idea of which messaging to prioritize, and which information to minimize.

Not surprisingly, the more text there is on a package, the less it will be read. Unfortunately, many well-meaning marketers think the opposite, and act accordingly. Some of the product designers at Microsoft have put together a great parody of this practice by showing how the Microsoft marketing department would redesign Apple’s iPod package. Instead of the simple and elegant messaging Apple created, it becomes a hodgepodge of system requirements, badges, call-outs, sub-branding logos, benefit statements, feature lists, and more!

Effective behavior-based focus group research goes beyond “opinion gathering”, giving researchers the feedback necessary to understand the impact and value of both present, and proposed packaging design in real-world terms.



Jaiden

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Increase Sales With These Innovative Tips

Written by packagin on February 23rd, 2009

packaging innovation
Paul Kellum asked:


Show your prospects how much enthusiasm you have for your product and business. If you’re convincing enough, they will be enthusiastic too.

2. End your sales letter or ad copy with a strong closing. It could be a free bonus, a discount price, a benefit reminder, an ordering deadline, etc.

3. Please your complaining customers. You can refund their money, give them a discount, give them a free gift, solve the problem quickly, etc.

4. Make your customers get excited about your business and they will tell their friends. Give them a free vacation certificate, a coupon, etc.

5. Give your prospects extra confidence so they will order. Use endorsements, testimonials, a strong guarantee or warranty, etc.

6. Build your opt-in list by allowing your visitors to sign up for a free e-zine, ebooks, software, contests, sweepstakes, etc.

7. Give your prospects or customers a breath of fresh air. Don’t be afraid to design your web site and ad copies different from everyone else.

8. Allow your customers to get part of your total offer right after they order. If you have to ship the item, make one of your bonuses available online.

9. Write and submit articles to e-zine publishers or webmasters. If you want it to be published, it should be like an article and not like an ad.

10. Show your prospects that you are an expert, because authority can persuade people to buy. You could publish an article, write an ebook, etc.

11. You could cross promote your product with other businesses’ products in a package deal. You can include an ad or flyer for other products you sell and have other businesses selling for you.

12. When you ship out or deliver your product, include a coupon for other related products you sell in the package. This will attract them to buy more products from you.

13. Send your customers a catalog of add-on products for the original product they purchased. This could be upgrades, special services, attachments, etc. If they enjoy your product they will buy the extra add-ons. 14. Sell gift certificates for your products. You’ll make sales from the purchase of the gift certificate, when the recipient cashes it in. They could also buy other items from your web site.

15. Send your customers free products with their product package. The freebies should have your ad printed on them. It could be bumper stickers, ball caps, t-shirts etc. This will allow other people to see your ad and order.

Kyleigh

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Trends Impacting the Ethical and Sustainable Packaging Market

Written by packagin on February 9th, 2009

packaging innovation
Bharat Book Bureau asked:


Ethical product development is now a major issue in the industry, and this trend includes the use and promotion of sustainable packaging formats. Ethical packaging is being driven by consumer environmental concern, retailer pressure and the development and promotion of manufacturer CSR. Retailers and manufacturers must be seen to be contributing to a greener and more sustainable way of life by the media, the industry and consumers alike. To remain competitive, retain consumer loyalty and be innovative, retailers and food and drinks manufacturers need to invest in ethical policies by either developing products in ethical packaging or promoting and reminding consumers to act ethically and responsibly.

Trends in Ethical and Sustainable Packaging is a new management report that examines the new innovations in ethical and sustainable packaging by category, region and material. It profiles major innovations within ethical and sustainable food and drinks packaging, including the latest packaging technologies and materials.

Discover the key trends impacting the ethical and sustainable packaging market and understand how these are changing packaging design with this new report…

This new report will enable you to

Gain insight into industry opinions on the usage and future of ethical and sustainable packaging through an exclusive survey of industry executives carried.

Create more effective competitive strategies with this reports detailed analysis of packaging technologies including recyclable, lightweight, biodegradable and packaging from natural sources. Evalualte the pros and cons of these packaging innovations and decide whether these may be appropriate for your organisation.

Improve targeting and the effectiveness of your NPD strategies with this reports analysis of Productscan data of over 6,000 ethical and sustainable packaging product launches between 2005 and 2008. Detailed analysis of leading ethical packaging types and insights into key regions and packaging materials.

Your questions answered…

To what extent should manufacturers and retailers be investing in ethical and sustainable packaging?

Which countries are driving NPD in ethical and sustainable packaging?

What are the most innovative forms of ethical packaging?

How will packaging regulation affect NPD in ethical and sustainable packaging?

How are key players, including Wal-Mart and PepsiCo investing in ethical and sustainable packaging?

What is driving the trend of ethical and sustainable packaging?

Some key findings from this report…

Packaging from natural sources is a key ethical innovation. Other leading innovations include biodegradable, lightweight and packaging made from recycled sources.

There has been an increase in the share of food and drinks launched in ethical packaging between 2004-2007. Within this share recyclable took the greatest share with 89.5% in 2007. However the largest growth was seen in biodegradable packaging and packaging made from recyclable materials.

53.5% of industry executives believe that recyclable packaging will be significantly important or the most important ethical packaging innovation over the next 5 years. 37.5% believe reduced packaging will be the most important.

Leading retailers are investing in ethical packaging initiatives. This includes Wal-Mart who has pledged to eliminate all private label packaging waste by 2010, with a look to have zero packaging waste land filled by 2025.

For more reports of your interest, please visit the following link: http://www.bharatbook.com/Market-Research/Packaging.html

Or

Contact us at:

Bharat Book Bureau

207, Hermes Atrium, Sector 11, PO Box.54, CBD Belapur, Navi Mumbai - 400 614, India.

Phone : +91 22 2757 8668 / 2757 9438

Fax : +91 22 2757 9131

E-mail : info@bharatbook.com

Website : www.bharatbook.com



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Industrial Dynamics And Innovation: Progress And Challenges

Written by packagin on February 1st, 2009

packaging innovation
G.Jayalakshmi asked:


Industrial dynamics and innovation: progress and challenges

*G.Jayalakshmi., Ph.D Scholar

INTRODUCTION

The growing field of industrial dynamics, the analysis of innovation has witnessed major progress in several areas. Contributions at the empirical and modeling levels have greater advanced our understanding of innovation, industrial dynamics and evolution of industries. A discussion follows on three key challenges that are required for a better understanding of the relationship between innovation and the evolution of industries: the analyses of demand, knowledge, networks and co evolution.



Innovation and the Evolution of Industries

The analysis of innovation and the evolution of industries have witnessed major progress in several areas. In the last years, several contributions at the empirical and modeling levels have greatly advanced our understanding of innovation, industrial dynamics and the evolution of industries. This paper reviews these contributions. The main point of the paper is that in order to have a deeper and clearer view of the relationship between industrial dynamics and innovation, research has to progress on three fronts: the analysis of demand knowledge and networks.

1. Industrial dynamics as a growing research field

Since the late 1970s industrial dynamics has emerged as a major area of inquiry in industrial economics. The analysis of birth, growth and decline of firms and industries and the factors affecting them has generated a very rich empirical and theoretical literature and most of these contributions have recognized the central role of innovation for firms and industries.



In this Address I will start by recognizing the major recent growth of research in the area of industrial dynamics and then concentrate on the major progresses in the analysis of the relationship between industrial dynamics and innovation and on the challenges that lie ahead

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In the first part of the paper I will discuss the progress, while in the second I will focus on three big research topics that I think require in-depth research scrutiny: demand, knowledge and networks. I will place a specific emphasis on a longitudinal perspective, in that it allows to focus on sequences of events, changes and feedbacks in industrial dynamics. This perspective is very important not only for understanding industrial dynamics, but also for the analysis of the broader evolution of markets.

2. Industrial dynamics and innovation

Since the late 1970s, industrial dynamics has emerged as a major research area for industrial economists. the theoretical level have focused the attention of various researchers on the way industries change over time and on the dynamics processes of entry, selection and growth of firms within industries. Within the growing interest in industrial dynamics, innovation has been recognized as a key element affecting the dynamics of industries and the rate of entry, survival and growth of firms. Looking back at the last 25 years, one has to recognize that on this front progress has been indeed impressive at both the empirical and the theoretical levels.

2.1 The empirical contributions

The empirical level, contributed to our appreciative understanding of the role of innovation in the evolution of industries, and it has shown that the relationship between innovation and industrial change is multidimensional, involves several actors and differs greatly across industries. Innovation in industries has been found to be the result of the interaction of different actors (firms, universities, public agencies, financial organizations) which are related both formally as well informally and have actions strongly influenced by their competences, learning processes, the knowledge base of sectors and institutions. In this frame, the notion of sect oral systems of innovation has provided to be a useful tool for examining innovation in a sector

Industries have been shown to follow life cycles of innovation, firms entry and growth and changes in market structure. It has also been convincingly found that that these dynamic sequences are different from one industry to another. In addition, with the availability of advanced computer technology and new firm level data, econometric analyses have moved from cross sections work during the 1960s and 1970s to longitudinal analyses of industrial dynamics and innovation since the early 1990s

2.2 The theoretical contributions

Also at the modeling level one can find different strands of research focusing on different aspects of the relationship between industrial dynamics and innovation. Technological learning by rational actors (be incumbents or entrants or both) and the competitive process weeding out the heterogeneity in firms population characterize a set of models that aim to explain empirical regularities such as the asymmetric distribution of firm size and different growth rates conditional on age (see for example,). Here there is passive learning and new firms do not know their own potential profitability. Major technological discontinuities create a shake out in industrial dynamics because a radical invention opens up the possibility of an increase in the efficient scale of production and in entry. Thus the transition to the new technology is associated to the exit of unsuccessful innovators and the survival of firms with larger scale technology.



On the contrary active learning by firms in industrial dynamics is present in where firms explore the economic environment, invest and, if successful, grow, so that industrial dynamics is driven by the growth of successful firms.



This results in corresponding Nash equilibrium on industry specific entry processes. Here however no attention is paid to the learning processes of firms, and less attention is also paid to industrial dynamics per se.



Another stream of models examines industry life cycle, analyzing together product and process innovations; rate and type of entrants; selection; firm size and growth; market concentration and market niches and shake outs. Finally, more attention to the specificities and histories of various industries is paid by history friendly models, which fall into the evolutionary tradition. They pay attention to the evidence and the dynamics of specific industries, intend to develop a dialogue with appreciative/qualitative/historical explanations and aim to model the sequence of events that have shaped a specific industry evolution. In sum, tremendous progress in the emerging field of industrial dynamics has been obtained in both the empirical studies of innovation in industries and the modeling of industrial dynamics and innovation.

3. Which research challenges for a deeper understanding of the relationship between Industrial dynamics and innovations?

The studies examined so far focused on technological change, the dynamics of incumbents as well as new firms and changes in market structure. Technology, firms and market structure are indeed key elements in the relationship between industrial dynamics and innovation. Let me show that industrial dynamics and innovation are greatly affected by a set of other factors: demand, the knowledge base of industries and networks. One could just start by noticing that in several industries demand has been a major factor affecting industrial dynamics and innovation. In semiconductors and computers, public demand such as military procurement has been important for innovation in the early stages of the industries. In computers experimental customers have been major actors in the emergent phase of the industry.

Similarly, the knowledge at the base of firms innovative activities and networks has played a major role in innovation and the dynamics of several industries. For example, in telecommunication equipment and services a convergence of different technologies, demand and industries has taken place, with processes of knowledge integration. This convergence has been associated with the creation of a wide variety of different specialized and integrated actors, ranging from large equipment producers to new service firms. In machine tools the evolution of the industry has been shaped by an application-specific knowledge base and has been characterized by extensive firms specialization In software, a highly differentiated knowledge base in which the context of application is relevant has created several different and distinctive product groups. In addition, the role of large computer suppliers in developing integrated hardware and software systems has been displaced by a lot of specialized software companies which innovate either in package software or in customized software. User-producer interaction and global and local networks for innovation are relevant. From these empirical cases, it is quite evident that demand, the knowledge base and networks have proven to be relevant for innovation and industrial dynamics in many sectors and yet, demand, knowledge and networks are not part of most analysis of industrial economics that concern industrial dynamics and innovation. Therefore in the following pages I am going to propose them as the next three key research challenges which need to be met if we want to advance our understanding of the relationship between industrial dynamics and innovation. Let me examine them in detail.

4. Demand

The first challenge that I want to explore is the one concerning the role of demand in innovation and industrial dynamics. As a way of introduction, let me first disagree with the usual complaint that demand has not been studied in its relationships with innovation in the last decades. In the literature, we have various empirical and theoretical strands, from the old debate demand pull vs. technology push, to the analysis of demand, market structure and innovation and advertising, bandwagon and networks have been shown to be important factors in influencing the magnitude and orientation of inventive effort and the degree of industry concentration. Demand has also been related to the emergence of disruptive technologies.



Here the early development of disruptive technologies serves niche segments that value highly their non standard performance attributes. Further developments in the performance and attributes of disruptive technologies lead these technologies to a level sufficient to satisfy mainstream customers and also the whole vast literature on diffusion is nothing else than research aimed at understanding the relationship between demand and innovation. Moreover, several contributions on diffusion concern the relationship between new technologies, demand and the changes in the structure of the supplier and the user industries. The same holds for the literature on competing technologies which pays a lot of attention to externalities and increasing returns. Contrary to all these research developments in the realm of demand and innovation, however, the insertion of demand in the analysis of the relationship between industrial dynamics and innovation is still in its infancy.



Therefore, answers to the questions posed above start from the identification of the various dimensions of demand that affect industrial dynamics and innovation. One dimension is the well known one related to the provision of incentives to firms R-D expenditures and innovative efforts. Here the preferences of consumers, market differentiation and segmentation, and the size and growth of demand affect innovative efforts and therefore technical change in various ways. In this Address I would like to add two other aspects that are relevant for innovation in industries: consumer behavior and consumer capabilities. Consumer behavior plays a major role in affecting innovation. It includes the presence of information asymmetries and imperfect information with respect to new products and technologies as well as routines, inertia and habits concerning existing products and technologies. Also consumer capabilities influence technological change in an industry: as an example one could only mention the role of absorptive capabilities and their distribution among consumers and users.



The focus on the behavior and capabilities of consumers and users opens the way for a very productive analysis of how demand affects innovation and the specific patterns of industrial dynamics. In this respect let me mention some fruitful directions. One relates to users involvement in innovation. This is a quite common phenomenon in industries. It may range from user-producer interaction to user initiated innovation.

5. Knowledge

The emphasis on (passive as well as active) learning and the role of absorptive capabilities in models and econometrics of innovation and diffusion identifies a second challenge: the analysis of the role of knowledge at the base of learning by firms in an industry and its effects on innovation and industrial dynamics.



However I remain rather positive in the use of patent citations in providing some evidence of a paper trail about knowledge links, and in describing some features of knowledge and knowledge networks in an industry, as flows of knowledge can be captured by patent citations even when inventors are unaware of those citations.



In sum, the research challenge regarding knowledge implies that a given knowledge base defines the nature of the problems firms have to solve, affects the division of labour in an industry and influences market structure and in a dynamic fashion, the very knowledge base of industries also changes as an effect of the behavior of firms and of technological change

6. Networks

Let me move to the last challenge: networks. Here with networks I do not mean network Externalities. Rather I refer to the different relationships cooperative and competitive, market and non market ones that firms have with other firms and non-firm organizations when they innovative. The relevance of networks for industrial economists is due from the broad recognition that innovative activity is highly affected by the interaction of heterogeneous actors with different knowledge, competences and specialization.



Various explanations have been advanced for the importance of networks in innovation, ranging from spillovers of various types, to the presence of Variety in technologies, knowledge and capabilities, to the role of complementarities. And the relevance of networks for innovation as well as for production and exchange has been recognized by game theory, transaction cost theory and resource based theory. Models of networks among economic agents abound now, from game theoretic to small world models, including evolutionary game theory, percolation theory and neural networks. They range from static models regarding the effects of different network architectures on performance, to dynamic ones in which the structure influences individual actions and performance and attention is paid to the networks efficiency, stability and feedbacks.









CONCLUSION

In this Address I have suggested that within the growing field of industrial dynamics, in the last twenty years the analysis of industrial dynamics and innovation has witnessed a rich and highly diversified set of contributions at the empirical and theoretical levels. So, progress has been substantial. The main point of the paper however is that a deeper understanding of the relationship between industrial dynamics and innovation pushes research in this area to face new challenges related to a finer grained analysis of the role of demand, knowledge and networks.



This paper has suggested that these coupled dynamics involve knowledge, technology, firms, demand and institutions. These dynamics are often path-dependent, take the form of co evolutionary processes and are industry-specific. In the three elements such as technology, demand and firms, one could claim that in sectors characterized by a system product and consumers with a rather homogeneous demand, the dynamics leads to the emergence of a dominant design and industrial concentration.







Kimberly

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