In the wake of the wide spread economic crises of the past score of years, the economic view point of every aspect of human life has attracted a great deal of attention. This view believes that economic performance greatly depends on productivity and output.
There are a number of activities which relate to the increase in productivity and output. Research and Development (R&D) would immediately come to mind as a major player in increased productivity and output. However, there is a more widespread process which in recent years has become equally important---in fact, perhaps the most commonly accepted player is now the development and diffusion of new technologies---Innovation.
Interest in innovation is only about twenty five years old among the country members of Organization for Economic Co-operation and Development (OECD) (1). The study of the process of Innovation, or more recently debated National Systems of Innovation (NSI), has been the subject of my studies in the past few months. What follows is a collection of my understanding on some selected aspects of this study.
Since mid-1970s the OECD country members have experienced a general slowdown and instability in economic growth (2). This general trend has brought, into the center stage, the study of factors involved in enhancing economic growth and contributing towards its stability. It is commonly accepted that technological change and innovation are major players in increasing both productivity and output. "The pace and flexibility of technological change in products and processes seem to be key elements in economic performance." (3)
Research and Development (R&D) is also one major factor. However, R&D is one activity under the broader umbrella of Innovation.
The scope of innovation, as one would immediately notice, is a very broad one. Innovation can take place anywhere, by anyone, in any aspect of our lives. It is an all-encompassing phenomena.
"Is it possible to measure it?" is the question. If we are to better understand innovation and encourage it then we need to be able to measure it to begin with. Naturally, any discussion on innovation needs to be put into a conceptual framework to enable the participating parties to organize their thoughts, discourse, and findings.
As mentioned above, the economic concerns of the matter is prevalent. It dictates that we should adapt a framework that is focused on those aspects of innovation which have the greatest impact on economic performance. Thus, the decision to "consider the economic significance of technological change and innovation, the nature of innovation process and the importance of non-R&D input" by OECD (4).
It should be noted however that the study of Innovation by nature is much more difficult than R&D. That is perhaps why OECD has a longer record of activities measuring and reporting on R&D activities than Innovation activities. Frascati Manual, the main standard in this practice, is much more developed and has been around longer than Oslo Manual, its counter part in the study of Innovation.
Despite this difficulty it is not impossible to define a conceptual framework, gather data, and gain insights into the process of innovation. Some recent OECD reports are a testimony to this possibility (5). At the same time the same group admits that "we are still a long way from understanding all of the factors which shape the rate, direction and effects of technological change, at enterprise, industry, regional, or country level." (6)
Three models have been used, to various degree of popularity, to represent the process of innovation. The following is a brief description of each.
The most widespread model is the linear model. Much of the data that exists on innovation is shaped by the "linear" model. As the designation indicates it implies that innovation is perceived to take place in a linear fashion (7). It starts with research, then invention, moving onto innovation, and finally diffusion of new techniques. A parallel process would be the progression in basic research, to technical knowledge, and to practical engineering. In this model R&D would become a major indicator of innovation.
This model is of course criticized widely as it does not portray the process of movement, interaction, and feedback of knowledge and resources. Kuhn has also argued that the structure of scientific revolution does not follow the linear or accumulative model. In fact, Kuhn argues, it follows a paradigm shift jumping from one equilibrium to another. Its a stair-case effect.
However, "improved models have not yet come into widespread use. Consequently the linear model is still often invoked in current discussions, particularly in political discussions." (8)
This model perceives the process in terms of interactions between opportunities, capabilities, and strategies (9). The model is specific to firms. Opportunities are presented through a wide range of sources. Changes in technologies and market demands are among them. The key issue here is how the firms will capitalize on the opportunities presented. How they recognize, prepare for, and strategically position for these opportunities.
The Capabilities would be in the firm's know-how (scientific and technical knowledge) and its resources (human resources like engineers, technicians, researchers, marketing, etc.). The particular way the firm decides to combine its capabilities and opportunities would be its Strategy. The management plays a crucial role in this area. The success in the firm's competitive position in the industry depends on its deliberate search and recognition of opportunities, and alignment of its capabilities and differentiating its products and processes.
As it is obvious, there is no linear relationship between these elements. It represents a complex system of interaction and interdependence.
A model which includes the innovative activities as well as the elements of research, knowledge, and market is the Chain-Link model proposed by Kaline and Rosenberg (10).
The above figure is taken from the Oslo Manual. It represents the model and its concept of interaction between market opportunities and firm's knowledge and capabilities. I believe the following illustration presents the same concept more clearly:
The interactions between the four functions are clearly shown. Of course, each function would have sub-functions which are not shown in the figure. There is no simple progression here. For instance, market potential can induce activities in the four functions. There may be many interactions and movements from one function to another. Often detail design and testing may cause some redesign to overcome production and/or distribution problems. Also, the process may start from the frim's Research. New products, processes and services may be invented and added to its know-how repository. In turn, markets may be created for them.
In this model the strength of the interaction between each function and the competence in performing the functions stand out and would be subject of measurement and improvement.
There is another model which is not at the same level in our conceptual frame work as the models mentioned above which try to contain the system of innovation. Input/Output model pervades all the models. It forms our perception of any system in general. This approach is very popular among the economists. Its application to science and technology reveals that it is much easier to measure input than output. For instance, it is easy to measure the fund invested in R&D, number of scientists, or FTE, trained and engaged in the R&D activities. In describing these inputs, however, some difficulties arise as well. For example, it may be a relatively easy task to count the number of scientists engaged in R&D but not so easy to determine the quality and its distribution within this manpower (11). Despite this difficulty the measurement of input is commonly accepted to be easier than output.
There are limitations to this model as well, "...including difficulties of measuring proximate output and of relating input to output." (12). We shall explore this point later in this paper.
To assume that output would be directly proportional to input and therefore use input indicators implicitly to measure output is misleading.
R&D takes on different roles in these models. In the linear model research is seen as the starting point of the process of innovation. In chain-link model, however, R&D plays the role of problem solver. It may be called upon at any stage in the process to address problem. Firms will draw on their current knowledge base and, if successful, will extend its limits and generate new knowledge and hopefully solve the problem it was called upon to address. The chain-link model, therefore, defines R&D to be performed by many divergent parties in many areas. R&D is not necessarily done by highly qualified personnel in expensive laboratories. Research, therefore, is adjunct to innovation, not a precondition for it. (13)
The point here is not to define or adapt a particular model. The purpose is to display the complexity of the phenomena with its set of diverse elements and interactions.
Frascati Manual in its 1992 edition provides a working definition for technical innovation. This edition also reflects the "problem solving" role of R&D.
"Technological innovations comprise new products and processes and significant technological changes of products and processes. An innovation has been implemented if it has been introduced on the market (product innovation) or used within a production process (process innovation). Innovations therefore involve a series of scientific, technological, organizational, financial and commercial activities.
R&D is only one of these activities and may be carried out at different phases of the innovation process, acting not only as the original source of inventive ideas as a form of problem solving which can be called on at any point up to implementation." (14)
Our understanding of innovation is still in its infancy. It is true that some ground breaking work has been done, but most of the road is still ahead of us. A wide range of areas need to be studied, its data systematically collected and analyzed in order to gain further insights into its major elements and their relationships. Oslo manual outlines six areas of investigation at this stage: (15)
All the areas identified are obviously very important and in need of diligent study if characteristics of innovation, or National System of Innovation (NSI), is to be better understood. However, the last area, Innovation Outputs, is of special interest to me.
The measurement of output, as important as one would assume it to be, has been largely neglected in the science of indicators, whether pertaining to R&D or other surveys, and there is a good reason why. It presents certain challenge in its clear and conclusive measurement. Two major obstacles stand in the way:
The industrial world of a nation is unlike the controlled environment of laboratories where all, or almost all, major factors determining the output are kept constant. In this controlled environment the change in output of a single input can be measured conclusively and in a satisfactory manner.
Unlike the controlled environment of the laboratories, the science and technological system has an organic life form of its own. It has many inputs, processes, and resulting outputs. The input is numerous; the relations are complex; and the output takes many forms some internal to the system itself.
The easiest aspect of this system to measure, on one hand, would be its input. Oslo manual as already mentioned has its focus on industrial innovation (16). In this light the funding and human resources are to be measured as inputs.
The most difficult aspect, on the other hand, would be the measurement of its output (17). Even more challenging would be to determine the relationship of input to output. Detailed records, over a long period of time, is required to allow the recognition of patterns between input and output. A few relationship are already being identified and commonly accepted. For instance, there is evidence that basic research shapes the innovation output (18).
The wide form of the output presents another problem in its measurement. Results of innovation can be seen from increased economical stability, improved and reliable technology, all the way to better human relationship, strengthening of family life, health and morals. What we decide, consciously or unconsciously, to occupy the central stage in the study of the output of innovation has implication that are far-reaching.
OECD explicitly is concerned with the economical impact of innovation(19)---its a choice and comes with its implications. Take for instance the sex industry pervading the Internet. According to the working definition of innovation it qualifies as the innovation of the century! It has introduced new goods; it has created new methods of production of its goods; new market has definitely been opened; its source of supply is the latest in the technology; and has revolutionize its own industrial organization! Under this definition sex industry qualifies as innovation with its economic impact calculated in our GNP.
The purpose of this section was to identify the difficulty in measuring the output of innovation. Also, the choice of what to measure is not trivial and carries implications to be considered.
Once a model is decided upon or commonly accepted the subject of indicators would take the center of our attention. The hypothesis here is that if the model represents a system of innovation or some aspects of it, then the measurement of the strength of the elements and their relationships would shed light on the system of innovation, its strength and weaknesses, forces and obstacles. Indicators are instruments of this measurements.
According to the basic definitions, and areas of investigation that is agreed upon, Oslo Manual suggests a list of indicators to be reported on by the OECD countries. What follows is a synopsis of the indicators for innovation that are suggested by the Oslo Manual.
The aim is to codify the indicators for ease of understanding and helping to remember its detail. This section is a starting point to help me understand the indicators, their usage, source of data, and limitations. It also includes reference to the base material.
The same exercise should be performed on Measuring the Cost of Innovation, and Classifications and Survey Procedures, and Analysis and Policy chapters. I hope to undertake these in the near future.
A few words about columns of this table. "Ref." column contains the paragraph numbers where the indicator is introduced and discussed. "Cf." provides further cross references to other sections, e.g. V5.1 is Chapter V, Section 5.1; 120 is paragraph 120. Also numbers appearing in the ()'s are references to the paragraph numbers. The 1992 edition of the Oslo Manual is used.
"Type" indicates the data type of the indicator. "Binary" means one of the two values, e.g.
1. relevant, or 2. not relevant. "Ordinal" is the scale assessment, e.g. 1. not important, 2. somewhat important, 3. important 4. very important, 5. extremely important.
In analysis of the suggested indicators one more column can be added to indicate the strength and weakness of the indicator. it should also be cross referenced to the Frascati Manual to identify the common elements ---my future projects!
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Ref Indicator Notes/Description Type Cf.
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125-7 1. Objectives of Innovation: Determining the firm's reason for engaging Binary (relevance) or
in innovative activities. Data related to the Ordinal (scale of
last 3 years are gathered. importance)
125 1.1 Technological objectives
126 1.2 Economic objectives:
1.2.1 Product innovations
1.2.2 Process innovations
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128- 2. Factors Assisting or Hampering Data related to the last 3 years are gathered. Binary (importance)
31 Innovation: or Ordinal
130-1 2.1 Source of innovative ideas: Some of these items can be further divided
2.1.1 Internal sources to domestic and foreign sources (131)
2.1.2 External Sources
132 2.2 Factors contributing to the suc Can be modified to meet the specific
cess of innovative projects: national requirements
2.2.1 Internal factors
2.2.2 External factors
133-4 2.3 Factors hampering innovative Includes obstacles or berries considered rel
activities: evant in some countries (133). May com
2.3.1 Economic factors bine information on obstacles with
2.3.2 Innovation potential information on projects never started as a
2.3.3 Other reasons direct consequence of severe barriers (134)
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135- 3. Identifying Innovating Enterprises Relates to the population of innovating Numeric / Quantita V5.1,
44 and Numbers of Innovations firms (136). New or significantly improved tive. Expressed as a V5.2
products or processes alone should be iden proportion of the
tified (137). The number of innovations total number of firms
become meaningful only when compared in the same industry
with the total number of products or process across the economy
in the enterprise (139). Data covers the past (136)
three years.
140 3.1 Total number of product at the 93, 95
end of the year
3.1.1 major product innovation (93)
3.1.2 incremental innovation (95)
3.1.3 product not changed
140 3.2 Total number of processes at the 97
end of the year
3.2.1 process innovations (97)
141 3.3 Optional: The use or market launch is scheduled for
3.3.1 innovation under development the next 3 years
141 3.3.2 planned innovation Whose development has not yet begun
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145- 4. Qualitative Aspects of Innovation To help evaluate the significance of innova Check boxes: ticking V3
51 tion (145) relevant categories
(147)
146-9 4.1 Type of novelty It may be useful to break the information
down by product group (147)
146 4.1.1 product innovation classification using technical variables 93, 97
4.1.2 process innovation
148 4.1.3 new for industry: worldwide or classification by market
in country
4.1.4 new only to the firm
150-1 4.2 Nature of innovation It gives some indication of the source of
innovation (150)
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153- 5. Impact of Innovations on the Per Data covers the previous 3 years (157-8) Numeric. Should be
77 formance of the Enterprise weighted by the
sales of the firms (i.e.
percentage of sales)
(158)
153 5.1 Proportion of sales due to new Innovation and diffusion both effect PNP V3
products (PNP): (155). It may change overtime due to
changes in sales of old products (155).
Firms that are new or engaged in custom
production are dealt with separately (156)
159 Percentage share of sales due to: commercialized during the last 3 years 93
5.1.1 major product innovation
5.1.2 incremental product innova 95
tion
5.1.3 unchanged or differentiated 98-9
products
161-6 5.2 Proportion of sales due to prod Indicates the result of innovation process 152-5
ucts in the introduction phase (SPI) (167). The medium-term growth prospects
of a given industry are good when SPI is
greater than the SPD, sales due to products
in the decline phase (161). life-cycle theory
(161) is not universally accepted. Some
products have no clear life-cycle. In this
cases SPI is not very meaningful (164).
More difficult to apply to custom produc
tion (165)
167- 5.3 Results of innovative efforts Indicates how results of innovation influ Scale assessment
70 ences the performance of the enterprise (169)
(167)
171-4 5.4 Impact of innovation on the use Determines the change in production func Descriptive
of factors of production tion due to innovation (171)
175-7 5.5 Descriptive information on inno Case studies are better means of collecting
vation output descriptive information (176). Includes
most important innovations only (176).
Problem of confidentiality.
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178- 6. Diffusion of Innovation Check boxes: ticking 9
85 categories
179- 6.1 User sectors More appropriate for innovations in inter
80 mediate and investment goods; less appro
priate for consumer goods (180)
181-4 6.2 Use of new technologies in man The extend to which innovations in the form
ufacturing of new technology are used in production
185 6.3 Use of new technologies in inno
vative activities
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186- 7. Special Questions These are not included in the Frascati Man V2,
206 ual (186) VI 2.3
7.1 Special questions on R&D
190 Frequency of performing R&D in: Binary: continuous,
7.1.1 R&D firms or occasional
190 7.1.2 Non-R&D firms planned for the next few years Binary: no plans, or
some plans
191-2 R&D Units in firms: Binary: Yes, no
7.1.3 Is there an R&D unit
191 7.1.4 Its share of total R&D expen Number: percentage
diture of total R&D
193-5 R&D Decision making: Listed by partner and country group (195) List
7.1.5 R&D co-operation
198- 7.2 Questions on patents The questions (199) provide information on Check boxes: ticking
201 patenting policies. Used in evaluating trends one best describing
in the numbers of applications and patents. the firm (199)
202-6 7.3 Questions on the technology bal Methodology described in OECD TBP Binary: Yes, no
ance of payments (TBP) Manual.
206 7.3.1 Acquired technology from
domestic or foreign market
206 7.3.2 Sold technology to domestic or
foreign market
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In recent years the concept of National System of Innovation (NSI) has claimed an increased level of attention in the work of many authors. The concept is newly developed by Lundval in mid-1980s (20). It is very closely based on Friefrich List's concept of national production systems. NSI has been very popular and subject of studies and discussion among economists, and policy makers of science and technology.
The main purpose in studying NSI is perhaps the idea that it will help explain the gap between the nation's development and deployment of science and technology. That is, comparative studies of NSI in various nations would highlight certain structural differences. Factors promoting or hampering innovation then maybe identified. Recent works, such as R. Nelson's (21), are attempts to describe the NSI of a set of countries and provide insights into their structures and ways of conducting and dealing with technical change. It takes the approach of identifying, describing, analyzing, and comparing the key processes and institutional actors involved ---industry, university, government, etc.; identifying and documenting similarities and differences of these national systems, and the extend to which it can explain the variation of national economic performance.
There are two items to be mentioned here in connection with the concept of NSI and the prevalent approach taken to study it.
First, the current global events which tend to be taking the world to a global interdependence raises the question of the validity of the concept of NSI. These global trends are many. Some directly related to science and technology, while others exercise their impact indirectly. Systemic openness and the globalization of science and technology; increased R&D by multinational firms; international technical alliances, transfer, trade of capital goods, and flows of R&D personnel; joint international science projects--- are identified and discussed by Niosi and Bellon (22) as trends that effect science and technology directly. They conclude that trends to globalization does exist and is supported by the substantial international flows. There is, however, a different degree of globalization in different countries. They also conclude that international networks are developed on the basis of NSIs. Internationalization grows and expands but does not necessarily suppress the regional or national activities, it modifies and integrates them.
Another set of events effecting the national systems indirectly may be seen in an ever-shrinking global habitat through the wonders of communication systems reaching the speed of light and covering the entire planet; an ever-awakening of global issues facing the collective humanity such as women, family, child rights, access to knowledge, and justice; an ever-widening scope of social issues rising from the local, regions, or national levels to the level of universal debate; a promise of world peace; in short, a reemergence of topics covering all aspect of human life with a new global focus.
In effect, there is very little facing the people of any nation that will not have its percussions on the rest of humanity. How British Columbia solves its conflicts with its Native population, for instance, will echo across Canada and reflect off to the entire continent of Americas to its most southern point. French nuclear testing in a far-flug island of Tahiti causes demonstrations of the public in Europe, and North America. Examples are numerous and in our regular daily news.
This shift of paradigm from "national" to "global" is perhaps an indication of a new stage in the development of the current human civilization on this planet. This new focus is the next natural stage in the progression of our history. "History has thus far recorded principally the experience of tribes, cultures, classes, and nations. With the physical unification of the planet in this century and acknowledgment of the interdependence of all who live on it, the history of humanity as one people is now beginning" (23).
Second, the study of NSI in terms of its giant players and their relationships may leave in their shadows some very important elements. Lipsett and Smith report on the findings of CPROST's research on the landscape of innovation in the province of British Columbia (24). They ask "what might lie in the shadows" of aggregated figures such as GERD, and "suggest that innovation is much more widespread than commonly thought---at least in Canada.". They report that the extend of R&D community of Canada is vastly unknown. Innovation is healthy and happening all over.
CPROST's project of building a detailed demographic database has already yielded its fruits. In the same document as mentioned above the key findings are reported as the following:
Another CPROST document (25) reports on the industrial make up of BC. The study shows empirically that the number of small firms that are innovative is more than the large players. These figures say something about the traditional approach of concentrating on the giant players only. It disregards and belittles the smaller players who we now know that, thanks to CPROST's research, out number the giants to a degree that can no longer be ignored in a study of national system of innovation.
For forty years various studies and statistics have informed the policy maker and formulated government policies. International standards stated, agreed upon, continuously updated, and put in to practice by many countries. Indicators have been identified, cataloged, laboriously collected and closely monitored. National statistics have been compared with the hope of explaining the gap between various countries in dealing with technical change ---a certain perception of system of innovations has thus been created.
Yet, one prominent organization in this effort openly states that we are far from having formed an even near-complete understanding of the process of innovation (26).
Nevertheless, the experience is of course valid. It offers a great deal of data. Perhaps new perspectives and approaches maybe required to compliment the current image. These new approaches can contribute in those areas where current approach ---Frascati & Oslo--- maybe suffering from shortcomings. Many shortcomings can be identified ranging from conceptual to missing data. For instance three points are identified with regards to Frascati manual (27). First, it focuses on the R&D performer and ignores fiscal incentives, even though these incentives are main elements of many national programs. Second, it does not include in its data gathering part-time or occasional R&D performer. Third, it does not consider the national climate in which the innovation is suppose to take place.
Of particular interest would be the identification of the number of part-time performers and its economic value in a system. There are evidences that point to a surprise in such investigation such as CPROST's that reports on a number of regional SMEs with the same order of magnitude as national (28)
The field is indeed immense, the task urgent. Economic stability is believed to be squarely dependent on innovation and its national performance. Many researching parties from different perspectives---social, cultural, and ideological---need to take up the task and contribute to a better understanding of the Innovation.
Compendium of Related Terminologies and Definitions
There are many working definitions and acronyms found in the core manuals on Innovation. As the subject of my thesis will be very closely related to it, I decided to start compiling a glossary of terms covering acronyms and definitions and major references for each one. Such a compendium is essential to help finding the exact definition and reference of various terminologies quickly. As such this collection is a starting point but essential to my research in the immediate future.
Entries are alphabetically ordered. Major references are also included for each definition or description.
Bahá'í International Community, The Prosperity of Humankind, public statement made in UN's World Summit for Social Development conference in Copenhagen, March 1995.
Franklin, Ursula, The Real World of Technology, Ontario: Anansi, 1992.
Hatzichronoglou, Thomas, "Indicators of Industrial Competitiveness: results and Limitations", Technology and National Competitiveness: Oligopoly, Technological, Innovation, and International Competition, Montreal: McGill-Queen's university Press, 1991, pp. 177-224.
Kuhn, Thomas S. The Structure of Scientific Revolutions. Chicago: The University of Chicago Press, 1962.
Lipsett, Morely S. and Smith, Richard K. "Cybernetics, and (real) National Innovation Systems," School of Communications, and Center for Policy Research on Science and Technology (CPROST), Simon Fraser University. Paper prepared for 1995 IEEEE International Conference on Systems, Man, and Cybernetics, October 22-25, 1995 Vancouver, British Columbia, Canada.
Lipsett, Morley S., and Holbrook, A., and Lipsey, Richard G. "R&D and Innovation at the Firm Level: Improving the S&T Policy Information Base," CPROST, Report CP 95-9. Paper presented at the Fourth International Conference on S&T Indicators, Antwerp, October, 1995.
Morita-Lou, H. ed. Science and Technology Indicators for Development. Colorado: Westview Press, Inc., 1985.
Nelson, R. R. ed., National Innovation Systems, New York: Oxford University Press, 1993.
Niosi and Bellon, "The Global Interdependence of National Innovation Systems: Evidence, Limits, and Implications," Technology In Society, Vol. 16, No. 2, pp. 173-197
OECD, Policies for the Stimulation of Industrial Innovation --- Country Reports, vol. II-1, Section II-Canada, pp. 55-136.
OECD, Frascati Manual 1992: Proposed Standard Practice for Survey of Research and Experimental Development, September 17, 1992.
OECD, Proposed Guidelines for Collecting and Interpreting Technological innovation Data (Oslo Manual), 12-Sept.-1991.
Patel P, and Pavet K., "National Innovation Systems: Why They Are Important, and How They May be Measured and Compared," Economics of Innovation and New Technology, Vol. 3, No. 1, pp. 77-95
Foad Shodjai shodjai@sfu.ca Centre for Policy Research on Science and Technology (CPROST) Simon Fraser University Vancouver, BC, CANADA