Research on Knowledge Diffusion in Disciplines Based on Actor Network Theory

Transcription

1 Research on Knowledge Diffusion in Disciplines Based on Actor Network Theory Feifei Wu, Xin Li, Lucheng Huang Beijing University of Technology, School of Economics & Management, Beijing , China Abstract--This paper presents a hybrid approach using bibliometric method and network analysis method to analyze the knowledge transferring into different disciplines, exploring the knowledge diffusion mechanism based on Actor Network Theory. The magnetic resonance imaging technology transferring into different disciplines is provided to illustrate the application of the presented method. I. INTRODUCTION According to technology innovation diffusion model published by Bass in 1969, the achievements of innovation will diffuse continually into markets and application fields as time going. And the process of innovations diffusion can be described using the s-curve [1]. However, Rogers defined that the innovation diffusion was a process and the process through which an innovation spreads via communication channels over time among the members of a social system [3]. It is necessary to research the rules of the innovation process in order to know how the R&D can transfer to the products until the large scale commercialization. However, there are great difference between technology original application domains and large scale application domains. For example, the first electronic digital computer was designed to calculate the U.S. military firearms transmitters [4]. The changes of the technology application domains may create a new industry or develop a Creative destruction to the current industry. So it is more useful to research on the transfer of the technology to new domain of application. The emergence of emerging technologies is often a process which the technology transfers to a new domain of application. And understanding this process, the managers can better use it to their advantages [10]. The changes of technology application domains accompanied by the technological knowledge diffuse in the domains. Because science and technology are not only as a pair of intimate partner, but many modern high-tech and science are becoming almost indistinguishable [9]. Michael Rader and Alan Porter summarized the technology future analysis, and listed 48 kinds technology future analysis methods [8]. But these methods are focus on the technology intelligence, roadmapping, forecasting, assessment, and the economic, environmental and social effects of the technology development. The future applications fields of the technology, especially technological knowledge diffusing in the different domains which may create new market opportunities, were paid less attention to mention. The changes of technology application domains are impacted by not only the diffusion of technological knowledge, but also the market, government, organizations and other relevant factors. The Actor Network Theory (ANT) presented by Latour [6] provides a new perspective and new method for studying technology innovation involving multiple actors. ANT can sever as a useful theoretical lens for understanding sociopolitical phenomena such as business process change, especially where the technology plays a critical role[13]. Henry considered Bibliometric analysis can describe the trajectory of science channel, and presented the across disciplinary boundaries of scientific channels concept [14]. This paper uses Bibliometric method and network analysis method to analyze the technological knowledge transferring into the different fields, explores the technological knowledge diffusion mechanism based on Actor Network Theory. Then we can use the technological knowledge diffusion mechanism to predict and analyze the changes of technology application domains, and to grasp market opportunities of new technology for company s innovation development strategy. The rest of this paper is organized as follows. Section 2 illustrates the methodology. Section 3 describes the data collect. Section 4 provides the results and analysis. Finally, section 5, concludes and discusses the paper. II. METHODOLOGY Firstly, bibliometric method was used to study the changes of the technological knowledge into the different disciplines by academic papers. Technological knowledge transferring into the different disciplines can create the conditions for the application of technological innovation. Secondly, network analysis method was used to analyze the author network of the academic papers. The results of scientific cooperation were usually reflected by the researchers signed together to publish papers in academic journals [7]. Scientific cooperation made by different researchers with different academic backgrounds would improve the possibility of technology transferring into different applications fields. Then the multi factor mechanism of the technological knowledge transferring into different applications fields was analyzed by Actor Network Theory (ANT). Because the technological knowledge transferring into different applications fields lead to technology applied into new fields. It was not only the results of scientists efforts, but the interaction of multiple factors between technology and society. Finally, the magnetic resonance imaging (MRI) technology was provided to illustrate the application of the presented method for exploring the diffusion mechanisms of the technical knowledge transferring into the different fields. 1825

2 III. DATA COLLECT This paper uses ISI Web of Science database to search the published papers. The key words were magnetic resonance imaging and MRI. Then published papers were retrieved from the database from 1974 to The results were shown in Fig. 1. From the Fig. 1, we can see that the data were increasing in linearly. After that, 6345 papers with higher citation times which were not less than 30 times were selected. And the results were shown in Table 1. Using Bibexcel software [11] to extract discipline type in the results, we got 138 discipline fields involved the 6345 papers. And the results were shown in the Appendix A. Number Year Fig. 1 The trends of papers related the MRI technology from 1974 to 2009 Number Regression Trend TABLE 1. THE NUMBERS OF PAPERS RELATED THE MRI TECHNOLOGY WITH HIGHER CITATION TIMES FROM 1974 TO 2009 Year Number selected Year Number selected Year Number selected Year Number selected IV. RESULTS AND DATA ANALYSIS A. The technical knowledge transferring into the different discipline fields As to the 6345 papers related to the 138 discipline fields, we can find that there was only one discipline field - Radiology, Nuclear Medicine & Medical Imaging in But the new discipline fields were emerging per year after It means the MRI technical knowledge was transferring into different fields. The results were shown in Fig. 2. After 1978, emerging with the Radiology, Nuclear Medicine & Medical Imaging directly related to the subject areas shown in Fig. 3. These subjects continue to diffusion in the different fields. For example the field of physiology emerged in 1984, and then from it the knowledge transferred to many different subjects. The results were shown in Fig. 4. Fig. 2 The trends of MRI technology applied different discipline fields from 1978 to

3 Fig. 3 The relationship between Radiology and other disciplines Fig. 4 From Physiology to other disciplines We divided the 138 discipline fields into two application fields - non-medical application field and medical application field. We found that the trends of the MRI technology applied into medical application field were growing quickly, but relatively slower in non-medical application field. The results were shown in Fig. 5. The Actor Network Theory can better explain this phenomenon Medical Nonmedical Fig.5. The trends of MRI technology applied into non-medical application field and medical application field 1827

4 The process of constructing Actor Network Theory includes Scenario Problematization Interestement Enrollment Translation Simplification Juxtaposition Strategy Heterogeneous Engineering. Lauterbur published the article related to MRI in Nature in 1973, and foresaw the future potential applications of MRI technology in medical imaging field. After that the article was cited more than thousands times [5]. Therefore, it completed the Scenario, Problematization, Interestement, Enrollment in the process of constructing ANT. In 1984, the U.S. Food and Drug Administration (FDA) approved the MRI technology to apply into clinical treatment [15], which stimulated the FONAR, GE and other companies as actors to join the network. The MRI technology can quickly access the three-dimensional image with high-precision of the structure of the patients bodies under no harm to the bodies. Using the MRI technology, the doctors can diagnose the diseases, particularly in parts of the brain and spinal cord lesions diseases. And the MRI technology was useful for surgery with accurately track cancer development in vivo situation, which laid the foundation for better treat cancer. Therefore, many patients quickly joined the actor network because of the advantages of the MRI technology. On January 1 st, 1994, the Society of Magnetic Resonance in Medicine and the Society of Magnetic Resonance Imaging merged to form the Society of Magnetic Resonance (now named the International Society for Magnetic Resonance in Medicine, The International Society for Magnetic Resonance in Medicine (ISMRM) is a multi-disciplinary nonprofit association that promotes innovation, development, and application of magnetic resonance techniques in medicine and biology. It is a community made up of clinicians, physicists, engineers, biochemists, and technologistsprofessionals united by a common interest in the ongoing dialogue between the scientific and clinical communities [16]. The established association organizations enriched the key elements of the actor network, and strengthened the translation link of the actor network. We also used the key words - magnetic resonance imaging and MRI to search the published papers in the ISI Web of Science database. The retrieval time was 1.25, And then we analyzed the Funding Agency in the published papers Before Year We found that there were few papers funded by agency before But the numbers of the paper funded were growing up after The results were shown in Appendix C. Fund supports made the heterogeneous networks of MRI technology medical application to maturity. The actor network of the MRI technology medical application was shown in Fig.6. Fig.6 An ANT View of the MRI Medical Application The trends of the MRI technology applied into non-medical application fields include food science, agriculture, fisheries, ocean science and other non-medical fields had increased in recent years. So, in the actor network of the MRI technology applied into non-medical application fields, there was not lack of actor researchers, but lack of the other actors who would enter the actor network. Therefore, it didn t form the large -scale application as the medical application fields. For example, the MRI technology applied into the food science field. We used the discipline type - Food Science & Technology to select the papers in the retrieved papers. Then we selected 250 papers related the MRI technology applied into the food science field. The results were shown in Fig Fig.7 The numbers of papers related the MRI technology applied into the food science per year Paper Number 1828

5 And then we used the Ucinet [11] software to study the co-occurrence analysis of these 250 papers, in order to clearly show the relationship between MRI technology and the other research contents. The results were shown in Fig.6. From the Fig.8, we can find that the MRI technology applied into the food science field main cover apples, potatoes, tomatoes and other vegetables; bread, pasta, wheat and other crops; oils, bubbles, water and other material structures. These researches were beneficial for the MRI technology transferring into the food science field. However, in this actor network, the translation process which attracts the application customers and the device manufacturers to join the actor network need to be done. Through the translation process to make them understand the benefits available to join the network, and for more research projects, research funding and licensing regulations, and improve the network of non-human actors, these would make the MRI technology broadly apply into the food science fields in the future. Fig.8 The MRI technology applied network into the food science B. The technological knowledge transferring into the different application fields analysis based on the author network. Scientific literatures are an important carrier of technological innovation. And the authors of the documents play the key actors in the technological knowledge transfer networks. Firstly, scientists showed their own innovation results through publishing papers to attract more researchers to participate in the same research fields. When the research results can benefit the research groups or meet the demands of customers, the customers, companies and other actors will be absorbed to join the actor network. Furthermore, when the application of research findings may lead to ethical and moral conflict, the government, law, public and other actors will join the network. So the various actors in the network continuously translate the problems. And then the application network of technology will be expanding and strengthening. We used the CiteSpace2.2.R11 [2] software to analyze the citation network of the Tab1 data. And then the Ucinet software was used to draw out the authors cooperation network diagram. The founders of MRI technology were Lauterbur, Mansfield and Damadian who majored in chemistry, physics and medicine respectively. In the 1970s, Lauterbur and Damadian worked in New York State University; Mansfield worked in the UK University of Nottingham. So the two authors groups who published the papers with higher citation times related to MRI technology came from US and UK. The higher citation times of authors network were shown in Fig. 9 from 1981 to When we analyzed the papers published in 1985, we found HART_HR which was the R&D department of GE Company with higher citation times in the cooperative network. The results were shown in Fig. 10. It showed that the GE company as an actor had joined the network. And its copartner was the University of Pennsylvania Department of Ophthalmology. So it indicated that the MRI technology had been combined with the eye knowledge in the medical application fields. 1829

6 Fig. 9 The authors network of MRI technology with higher citation times from 1981 to 1985 Fig. 10 The authors network of MRI technology with higher citation times in 1985 When we analyzed the papers published from 1986 to 1989, we found that the neuroradiology researchers who were from Canada and Germany emerged in the authors network of MRI technology with higher citation times. The results were shown in Fig

7 Fig. 11 The authors network of MRI technology with higher citation times from 1986 to 1989 After 1990s, many researchers who came from different countries such as Italy, Belgium, Netherlands, Japan, Korea and China emerged in the authors network of MRI technology with higher citation times. And the research contents were from radiology to diagnosis. Through analyzing the authors network of MRI technology with higher citation times from 1974 to 2009, we found the authors came from different research background and they played the key actors in the technological knowledge diffusion network. Therefore, in order to achieve the technological knowledge transferring into the different application fields, actors in the network should have different knowledge backgrounds and come from different research institutions, which will improve the technological knowledge transfer speed in the dynamic translation process of the actor network. V. CONCLUSIONS This paper presents a hybrid approach using bibliometric method and network analysis method to analyze the technological knowledge transferring into the different fields, exploring the technological knowledge diffusion mechanism based on Actor Network Theory. The magnetic resonance imaging technology transferring into different fields is provided to illustrate the application of the presented method. Through analyzing the trends of the MRI technology applied into medical field and non-medical field, we found the large - scale diffusion of technological knowledge in the different fields need not only a large number of researchers to join the actor network, but also the customers, companies, government, funding and association to join the actor network. Through analyzing the authors network of MRI technology with higher citation times, we found the researchers played the key actors in the technological knowledge diffusion networks and they accelerated the technological knowledge transferring into different application fields. ACKNOWLEDGEMENT This paper was supported by the National Natural Science Foundation of China under Grant , Funding Project for Academic Human Resources Development in Institution of Higher Learning under the Jurisdiction of Beijing Municipality (PHR-IHLB), the National Soft Science Research Program under Grant 2010GXS3K083 and the Science and Technology Project Foundation of Beijing under Grant Z REFERENCES [1] Bass, F.M.; A new product growth model for consumer durables, Management Science, vol.15,pp ,1969. [2] Chaomei Chen, CiteSpace, Retried 2/01/ [3] Everett M,Rogers,Una E.Medina,Mario A.Rivera and Cody J.Wiley, Complex adaptive systems and the diffusion of innovations,the public sector innovation journal,vol.10(3),article 30, Retried 9/02/ pdf [4] George David, Paul Shoemaker,Administration wharton on the emerging technologies. Huaxia Publishing House,Beijing,2002. [5] He Jiao,; The father of MRI Paul Lauterbur dies,retried 4/02/07 Science Net, [6] Latour, B.; Science in Action:How to Follow Scientists and Engineers through Society.Harvard University Press, Cambridge,1988. [7] Liu Bei, Yuan Yi and BOUTIN Eric, Application of Social Network Analysis in Information Science,Journal of the China Society for Scientific and Technical Information,vol.27(3),pp ,2008. [8] Michael Rader and Alan Porter., FTA Assumptions: Methods and Approaches in the Context of Achieving Outcomes, Retried 7/09/

8 [9] Narin F., E. Noma, Is technology becoming Science? Scientometrics, vol.(7),pp ,1985 [10] Persson, O., BIBEXCEL, a tool-box for scientometric analysis; Retried 5/02/ [11] Ron Adner, Daniel A Levinthal. The Emergence of Emerging Technologies, California management review,vol.45,pp3/pp23,2002, Retried 3/02/ rging%20technologies.pdf [12] Roberta Chase and Steve Borgatti, UCINET, Retried 9/01/ [13] Sarker S, Sarker S and Sidorova A, Understanding business process change failure: An actor-network perspective, Journal of management information systems,vol.23(1),pp.51-86,2006. [14] Small H.; A Passage Through Science: Crossing Disciplinary Boundaries, Library Trends, vol.48(1),pp ,1999. [15] Zhao Xiping,; From X-ray to MRI, Retried 1/17/06 Ningbo Xingaoyi Co.,LTD, [16] ISMRM, Retried 11/02/2010, APPENDIX A Materials Science, Biomaterials Geriatrics & Gerontology Psychiatry Polymer Science Clinical Neurology Otorhinolaryngology Linguistics Chemistry, Medicinal Physics, Multidisciplinary Veterinary Sciences Ecology Emergency Medicine Health Care Sciences & Services Social Sciences, Biomedical Neuroimaging Engineering, Multidisciplinary Instruments & Instrumentation Developmental Biology Oncology Horticulture Psychology, Developmental Behavioral Sciences Rehabilitation Mathematics, Applied Cardiac & Cardiovascular Systems Engineering, Mechanical Mechanics Agronomy Peripheral Vascular Disease Pharmacology & Pharmacy Spectroscopy Transplantation Medical Laboratory Technology Respiratory System Zoology Automation & Control Systems Meteorology & Atmospheric Sciences Medical Informatics Optics Construction & Building Technology Public, Environmental & Occupational Health Nutrition & Dietetics Social Issues Electrochemistry Astronomy & Astrophysics Anesthesiology Acoustics Engineering, Civil Mathematical & Computational Biology Chemistry, Inorganic & Nuclear Dermatology Engineering, Environmental Biotechnology & Applied Microbiology Nanoscience & Nanotechnology Toxicology Engineering, Manufacturing Multidisciplinary Sciences Psychology, Clinical Surgery Environmental Sciences Chemistry, Multidisciplinary Chemistry, Organic Immunology Medicine, Legal Endocrinology & Metabolism Chemistry, Physical Cell Biology Fisheries Medicine, General & Internal Health Policy & Services Ethics Forestry Gastroenterology & Hepatology Physics, Applied Biology Geosciences, Multidisciplinary Integrative & Complementary Medicine Chemistry, Applied Anthropology Obstetrics & Gynecology Computer Science, Information Systems Critical Care Medicine Rheumatology Limnology Engineering, Electrical & Electronic Genetics & Heredity Physiology Marine & Freshwater Biology Computer Science, Theory & Methods Statistics & Probability Pediatrics Materials Science, Paper & Wood Biochemistry & Molecular Biology Engineering, Biomedical Orthopedics Materials Science, Textiles Metallurgy & Metallurgical Engineering Substance Abuse Hematology Psychology, Multidisciplinary Food Science & Technology Evolutionary Biology Microscopy Medical Ethics Imaging Science & Photographic Technology Psychology, Biological Pathology Sport Sciences Urology & Nephrology History & Philosophy Of Science Neurosciences Microbiology Agriculture, Multidisciplinary Physics, Condensed Matter Plant Sciences Nuclear Science & Technology Biochemical Research Methods Reproductive Biology Gerontology Physics, Fluids & Plasmas Mathematics, Interdisciplinary Applications Anatomy & Morphology Psychology Physics, Mathematical Medicine, Research & Experimental Engineering, Chemical Biophysics Ophthalmology Physics, Atomic, Molecular & Chemical Infectious Diseases Economics Water Resources Dentistry, Oral Surgery & Medicine Radiology, Nuclear Medicine & Medical Imaging Allergy Computer Science, Artificial Intelligence Materials Science, Multidisciplinary Psychology, Experimental 1832

9 APPENDIX B Funding Agency NIH DEPARTMENT OF RADIOLOGY UNIVERSITY OF FLORIDA COLLEGE OF MEDICINE DIVISION OF SPONSORED RESEARCH OF THE UNIVERSITY OF FLORIDA FLORIDA DIVISION OF THE AMERICAN CANCER SOCIETY INTERNAL GRANT AGENCY OF THE CZECH REPUBLIC JOHNS HOPKINS RADIOLOGY MOLECULAR IMAGING GRANT SCIENCE FOUNDATION OF APPLIED SPECTROSCOPY LABORATORY CHANGCHUN INSTITUTE OF APPLIED CHEMISTRY ACADEMIA SINICA APPENDIX C Funding Agency 1 NIH 16 FOUNDATION 17 NATIONAL INSTITUTE OF NEUROLOGICAL DISORDERS AND 2 NATIONAL NATURAL SCIENCE FOUNDATION OF CHINA STROKE 3 WELLCOME TRUST 18 EUROPEAN COMMISSION 4 NATIONAL SCIENCE FOUNDATION 5 NATIONAL INSTITUTE OF MENTAL HEALTH 19 NATIONAL INSTITUTE OF BIOMEDICAL IMAGING AND BIOENGINEERING 20 NATURAL SCIENCES AND ENGINEERING RESEARCH COUNCIL OF CANADA 6 NATIONAL INSTITUTE ON AGING 21 NOVARTIS 7 CANADIAN INSTITUTES OF HEALTH RESEARCH 22 PFIZER INC 8 DEUTSCHE FORSCHUNGSGEMEINSCHAFT 23 EPSRC 9 NATIONAL CENTER FOR RESEARCH RESOURCES 24 NATIONAL CANCER INSTITUTE 10 GLAXOSMITHKLINE 25 ACADEMY OF FINLAND 11 MEDICAL RESEARCH COUNCI 26 DEUTSCHE FORSCHUNGSGEMEINSCHAFT DFG 12 NATIONAL HEART LUNG AND BLOOD INSTITUTE 27 ALZHEIMER S ASSOCIATION 28 MINISTRY OF EDUCATION CULTURE SPORTS SCIENCE AND 13 AMERICAN HEART ASSOCIATION TECHNOLOGY OF JAPAN 14 EUROPEAN UNION 29 NATIONAL MULTIPLE SCLEROSIS SOCIETY 15 L SWISS NATIONAL SCIENCE 30 SWEDISH RESEARCH COUNCIL 1833