Matrices and Their Application to Science and Technology
Chapter One
AIMS AND OBJECTIVES
The main objective of this work is to assess matrices and their application to science and technology. The following are the specific objectives;
To apply matrices to science and technology and a system of Linear Equations
To improve the methods by which increase in production out-put can be achieved
To show ways at which sensitive information can be passed across mathematically.
To disseminate these improved methods to the relevant communities and end-use.
CHAPTER TWO
LITERATURE REVIEW
CONCEPTUAL REVIEW
This paper presents matrices of science and technology interactions and suggests how they may inform development policies in the twenty-first century.
These matrices organize information on how technology is dependent on science and, as we compare these matrices over time, they uncover how science is becoming more important to technology. Indeed, as Narin et al. (1997) has put forward, the increasing linkage between technology and science.
Once the matrices are presented, this paper shows its first original contribution: the preparation of these matrices both for developed and undeveloped countries. With this global overview, it is possible to uncover how stages of development are affected by patterns of science and technology interactions. To improve the analysis of these matrices and their global and cross-country significance, in a second original contribution of this paper, three indicators are proposed. Finally, one of these indicators—matrices inter- temporal correlation—provides information for a third contribution of this paper: the identification of patterns of structured growth that differentiate developed and non- developed countries.
These patterns of structured growth inform suggestions for public policies for devel- opment, emphasizing the need for an articulation between the industrial and technological dimension and scientific side. The intertwinement of these two dimensions is a key component of developmental policies for the twenty-first century.
This paper is organized in seven sections. ‘‘The matrix of science and technology interactions’’ section explains what is a matrix of science and technology interactions. ‘‘Previous literature on these matrices’’ section surveys previous literature on patents and their citations of science and technology literature and shows how this literature informs the preparation of this matrix. ‘‘Database preparation and the three indicators’’ section describes how this matrix is prepared and proposes three indicators to analyze them. ‘‘Matrices and intertemporal changes’’ section uses the matrices to illustrate the increasing scientific content of technology over time and to show how our indica- tors differentiate countries. ‘‘Matrices and development issues’’ section presents the contributions of these matrices to development issues. ‘‘Concluding remarks’’ section concludes this paper.
CHAPTER THREE
RESEARCH METHODOLOGY
DATABASE PREPARATION AND THE THREE INDICATORS
The database prepared for this paper consists of 514,894 USPTO patents granted in selected years: 59,669 were granted in 1974, 55,610 in 1982, 87,805 in 1990, 142,478 in 1998 and 169,332 in 2016.
The first step for the preparation of this database was the elaboration of a software program to search and download all USPTO patents from 1974, 1982, 1990, 1998 and 2016 (www.uspto.gov).
This software collected the following fields for each patent:
CHAPTER FOUR
RESULTS AND DISCUSSION
To analyze quantitatively these matrices we propose three indicators.
First, there is an indicator to demonstrate the overall level of interactions between science and technology in a country. As an empty cell represents the lack of linkage between an OST-technological domain and an ISI-discipline, the identification of the level of matrix filling is very important. Therefore a Matrix Filling Index is proposed.
CHAPTER FIVE
CONCLUSION AND RECOMMENDATION
CONCLUSION
The investigation of S&E literature citations in patents is a useful tool to investigate the nature of science and technology linkages both in developed and under-developed countries, inter alia for it allows dialogues with other tools available both for developed (Cohen et al. 2002) and under-developed countries (Rapini 2007).
The scientific content of technology, as measured by S&E literature citations in patents, is increasing steady both in developed and under-developed countries, but the nature of these increases differs across countries and levels of development.
The elaboration of three dimensional matrices (OST-technological domain, ISI-disciplines, and number of references per matrix cell) for each country and each year is a powerful tool for evaluation of the stage and the dynamics of interactions between science and technology.
The indicators about Matrix Filling and Matrix Rugosity provide important qualitative insights about these interactions. Once these qualitative insights are available, the implications for development are not difficult to see. The problem is not only the scarcity of patents, but also the quality of those important but few patents from developing countries, the countries within regimes I and II, in our previous work (Ribeiro et al. 2016a, b).
The inter-temporal correlations between matrices’ surfaces are the basis for the identification of patterns of structured growth, a key difference between countries within regime III (mature NSIs) and the rest (immature NSIs).
RECOMMENDATIONS
Given these conclusions, there are important implications for development, in an era when science, technology and their linkages matter:
(1) The interconnections between science and technology may indicate which S&E fields should be supported for specific industrial policies, and provide policy makers a tool for designing industrial policies that take into account the interactions between science and technology as a key factor for development.
(2) The role of persistence over time must be stressed. This involves long-term planning by firms and public agencies (probably interacting with policies to mitigate the high mortality rates of new firms, firms so necessary to change the technological landscape of underdeveloped countries).
(3) More evidence in favor of a very simple argument: a broad science and technology infrastructure is necessary for development, and this necessity grows over time. The argument is very simple: to catch up, a country needs to improve its innovation capabilities. Over time, the scientific content of technology is increasing. Therefore, inter alia, a greater and deeper scientific infrastructure is necessary to support these innovative activities. This process seems to be unavoidable and demands larger investments in science in LDCs than have been done so far.
(4) New arguments for the necessary combination between industrial policies and science and technology policies: the evidence presented in this paper suggests that for a quantitative increase in patent figures, a precondition is a correspondent growth in science and engineering publications. No quantitative increase in patent figures is possible without a qualitative improvement in the patents generated; in other words, in their science and engineering content. Therefore, this paper suggests that dynamically, over time, there is a deep relationship between the quantity of patents and the quality of these patents.
REFERENCES
- Bassecoulard, E., & Zitt, M. (2004). Patents and publications: The lexical connection. In H. Moed, W. Gla¨nzel, & U. Schmoch (Eds.), Handbook of quantitative science and technology research: The use of publication and patent statistics in studies of S&T systems (pp. 665–694). Dordrecht: Kluwer Aca- demic Publishers.
- Bernardes, A. T., & Albuquerque, E. M. (2003). Cross-over, thresholds, and interactions between science and technology: Lessons for less-developed countries. Research Policy, 32(5), 865–885.
- Bhattacharya, S., & Meyer, M. (2003). Large firms and the science-technology interface: Patent, patent citations, and scientific output of multinational corporations in thin films. Scientometrics, 58(2), 265–279. Braun, T., Glanzel, W., & Grupp, H. (1996). The weight of 50 nations in 27 science areas, 1989–1993 (part I). Scientometrics, 33(3), 263–293.
- Callaert, J., van Looy, B., Verbeek, A., Debackere, K., & Thus, B. (2016). Traces of prior art: An analysis of non-patent references found in patent documents. Scientometrics, 69(1), 3–20.
- Cohen, W., Nelson, R., & Walsh, J. (2002). Links and impacts: The influence of public R&D on industrial research. Management Science, 48(1), 1–23.
- Colyvas, J., Crow, M., Gelijns, A., Mazzoleni, R., Nelson, R., Rosenberg, N., et al. (2002). How do university inventions get into practice? Management Science, 48(1), 61–72.
- Freeman, C. (1994). The economics of technical change: Critical survey. Cambridge Journal of Economics, 18, 463–514.
- Freeman, C. (1995). The ‘‘National System of Innovation’’ in historical perspective. Cambridge Journal of Economics, 19(1), 5–24.
- Freeman, C., & Soete, L. (1997). The economis of industrial innovation. London: Pinter.