Evolution of advanced technology studies: searching for a communication core

Abstract

The term of advanced technology is primarily associated with computer electronics and microelectronics actively developing since 1960s. Although there is no single conventional definition of the notion or specific class of technology that is associated with it, discussions on what may be considered as technical advancements in the current perspective evolve over time. As long as there is continuous interest in rise, development and dissemination of new technologies, especially from the policy-making perspective, it is important to understand which specific issues arise in professional discourse over certain time periods. This paper focuses on evolution of a communication core in academic discussions on advanced technologies identified with the use of betweenness centrality and PageRank metrics applied to a co-citation network of publications from 1960 until 2015. It is shown that there is observable penetration of the term from social sciences to natural and engineering disciplines.

Keywords

• Advanced technology
• technology evolution
• graph analysis
• bibliometric analysis
• co-citation
• betweenness centrality
• page rank

Introduction

Since 1960-s, there is growing interest in the development and use of new technologies accompanied by a strong trend on behalf of decision makers to regulate related processes at institutional and national levels. As a result, a series of efforts were put to establish relevant classification categories and statistical frameworks, allowing standardised measurement of science and technology in terms of inputs and outputs (Gokhberg et al., 2013) .

One of the key categories, which emerged together with a set of definitions and distinction criteria for R&D, was a notion of advanced technology. Perhaps, first papers using the concept appeared in early 1960s in relation to a problem of growing need for sufficient training of technical specialists (e.g. see Venables, 1962) . Almost 30 years later the definition of advanced technology appears in the Frascati Manual in relation to manufacturing (OECD, 1994) . However, the definition vanishes from the later editions of the Manual as well as from other OECD manuals; it remains one of the key categories used in professional literature until present (see Fig. 1).

In our study, we suggest looking precisely at the identification and analysis of the communication core of those academic discussions that set up agenda for further research in advanced technology. 2

Literature review

A variety of methods have been developed to detect and analyse social and disciplinary structures of knowledge as well as dynamics of scientific networks. In offering their approaches authors suggested focusing on exploring the current ‘knowledge base’ of certain fields (Fagerberg & Verspagen, 2009; Fagerberg et al., 2012a, 2012b) or revisiting and conceptualising information on the current use of selected concepts (Rotolo et al., 2015) .

As long as our task is to identify the central part of communication network that feeds further academic discussions on advanced technology within the certain period, we refer to the approaches focusing on the analysis of citation distributions. Specifically, we pay attention to the co-citation analysis initially introduced in 1973 (Small, 1973; Marshakova-Shaikevich, 1973) for studies of linkages between the documents and adopted further to mapping invisible colleges (Gmür, 1973) and clusters of science (Small, 1999) and searching for emerging topics (Small, et al., 2014) . As a measure of the frequency with which at least two papers are cited together in other documents, cocitation analysis allows identification cognitively related knowledge clusters accepted (through citations) by a wider network of followers as mostly valuable in the field.

Similar approaches can be found in graph theory. It shows that spatial configuration of elements may characterise their role in a network. For instance, Bavelas (1948, 1950) demonstrated the relationship between centrality and communication processes in small networks. He showed that optimally positioned actors could accumulate information flows from dislocated parts of a network and therefore play a gatekeeping role. Smith (1950) and Leavitt (1951) suggested that authors holding central positions might also influence behaviour of other linked members.

Following ideas of R.K. Merton (Merton, 1988) we can assume that those actors in academic networks that gain more attention from their colleagues through received citations will have a higher social status and therefore hold more central positions (Small, 2004) . Subsequently, a centrality position would mean the author’s association with a communication core. Recent papers suggest using PageRank algorithm for placing actors in co-citation networks (Ding et al., 2009) . Compared to other centrality metrics (e.g. Eigenvector Centrality, Katz Centrality), PageRank may be applied to any collection of entities with reciprocal quotations and references. It assigns a numerical weighting to each element of a linked set of documents with the purpose of measuring its relative importance within the set. This makes PageRank algorithm appropriate for further analysis. Following recommendations provided in (Ding et al., 2009) in order to compare different centrality measures for the verification of results, we also consider betweenness centrality to look at the group of authors connected by shortest paths passing through a vertex. Papers with high betweenness are essential in a network as long as they mark structural holes that provide opportunities for mediating knowledge flows in a wider community of actors (e.g. see Burt, 2002) . 3

Method

The concept of a communication core is based on the idea of natural social hierarchies that emerge in knowledge networks along with the evolution of the agenda in academic discussions. In order to identify a communication core in co-citaton networks that structure discussions on advanced technology within the selected periods the following four steps were taken.

First, a set of documents for further analysis was identified. The data were extracted from the Web of Science Core Collection database for the period from 1961 until the end of 2015. The dataset included 8190 documents of all types, extracted from all citation indexes (accessed: 15.04.2016).

Then, based on the overall publication dynamics we identified several shorter time periods of active growth. As seen from Fig. 1, while emergence of early papers in the field goes back to 1960s, the overall number of studies remains insufficient for the cocitation analysis until mid-1990s (by 1995 the overall amount of papers exceeds 300 with annual growth of 10 papers). Therefore, the first period taken into consideration was 1961 – 1990. Further periods include papers for the next two decades (1991 – 2000 and 2001 – 2010) and a 5-year interval from 2011 to 2015. At the third stage, we used VOSviewer software (http://www.vosviewer.com) for constructing co-citation networks for each of the distinguished time periods that were later analysed in UCINET (for betweenness calculation) and R programming language (for PageRank calculation). Formulas for centrality measures were adopted from (Ding et al., 2009) . Parameters of co-citation networks are provided in Table 1. Chosen thresholds allow conducting a not overwhelming analysis with redundant nodes, while providing sufficient data for core identification. Finally, after calculation of centrality metrics, we took top-30 authors according to each of the selected metrics and compared the lists. Key results of comparisons are provided below.

Results

The period from 1961 to 1990 is less connected and is likely to be associated with the primary accumulation of knowledge on advanced technology. Although subset of data for the period included 20 connected nodes, all betweenness measures are equal to zero; PageRank mean value is equal to 0.05. The latter centrality measure allowed distinction of the leader node, but no coinciding references were identified. 4.2

1991 – 2000 The network of the second period shows a greater variety in terms of values. Top-30 papers by both metrics is slightly matching: there are only three papers that are presented in both rankings (for details here and after see tables provided in the Appendix). Publications that appear in both lists consider specific issues related to economic and social effects of technology development. Hence, Bartlett & Ghoshal (1989) address management problems of companies that operate in multinational environment. A study of Howells (1990) focuses on the relationship between forms of organization and positioning of corporate R&D. Finally, Barley (1986) touches upon the role of new technologies on altering organizational structures (for the summary of top ranked papers see Fig. 2). The third period is characterised by a higher number of common papers (Table A.2 in the Appendix), all of which are still focusing on economic and social issues. Here, we can see two important works of innovation economists paying attention to the role of technologies in inovation development of a firm (Kline & Rosenberg, 1986) and to the idea of absorptive capacity (Cohen & Levinthal, 1990) , including, above all, an ability of a firm to be aware of, identify and take effective advantage of technology (e.g. see Seaton & Cordey-Hayes, 1993) . Other works of the period introduce methods of patent analysis to explore R&D spillovers and geographic location of inventions (Jaffe et al., 1993; Coe & Helpman, 1995) ; a book on relationship between new technologies and success of innovation (Christensen, 1997) ; papers on spillover effects of the activities of multinationals (Caves, 1974; Blomström & Kokko, 1998) . 4.4

The forth period include six common documents (Table A.3 in the Appendix) of which five come from natural and engineering sciences and are oriented towards the development and use of specific technologies. The occurence of these papers in the core network can be considered as a certain level of acceptance of the advanced technology concept by hard sciences and as its correspondence to certain groups of technologies like mathematical modelling of living systems (Stolk, et al., 1998) , remote sensing (Weng, et al., 2003) , simulation of technical processes (Asenov, et al., 2003) , and new materials (Geim & Novoselov, 2007; Simon & Gogotsi, 2008) . The only economic paper in the core addresses issues related to international diffusion if technology (Keller, 2004) . 5

Conclusion

The paper represents evolution of a communication core in academic discussions on advanced technologies identified with the use of betweenness centrality and PageRank metrics applied to co-citation networks for the period from 1961 to 2015. The combination of these methods allowed identifying and considering key alterations in professional discourse on advanced technology development. Further analysis of co-citation networks eliminated a common background for the papers in each of the observable time periods, while the application of centrality metrics helped to distinct key works. It was shown that there is an observable penetration of the concept from social sciences to natural and engineering disciplines. At least three phases with foci on different issues can be distinguished: studies in R&D and technology management (1991 – 2000), analyses of technology diffusion and innovation development (2001 – 2010), and discussions on specific technologies and materials (2011 – 2015). Further work can be aimed at deeper analysis of disciplinary structures in communication networks and at identification of specific technologies considered as advanced in certain time periods. Acknowledgements. The research leading to these results has received funding from the Ministry of Education and Science of the Russian Federation in 2015-2016 (project ID: RFMEFI60215X0008).

Appendix

Key statistics:

Coinciding references (in bold): 3 Mean top-30 betwenness: 1183.3 Mean top-30 PageRank: 0.0032

Betweenness

Nelson R., 1982 Cohen W., 1990 Moore J., 1969 Hoffert M., 1998 Prahalad C., 1990 Eisenhardt K., 1989

Christensen C., 1997 Jaffe A., 1993

March J., 1991 Jaffe A., 1989 Williamson O., 1985 Nelson R., 1993 Kline S., 1986 Von Hippel E., 1986 Wigley T., 1996 Rosenberg N., 1982 Teece D., 1997 Kogut B., 1992 Churchill G., 1979 Kaplan R., 1986 Caves R., 1996 Cooper R., 1993 Holland J., 1975

Blomstrom M., 1998

von Hippel, E. 1994 Caves R., 1974 Brown S., 1995 Hobday M., 1995 Cantwell J., 1995 Coe D.T., 1995

Key statistics:

Coinciding references (in bold): 7 Mean top-30 betwenness: 195.9 Mean top-30 PageRank: 0.012

Page Rank Blomstrom M., 1998

Betweenness

Bradley T., 2009 Rogers E., 1995 Tsang Y., 2007 Fornell C., 1981 Simon P., 2008 Hair J., 1998 Geim A., 2007 Tarascon J., 2001 Novoselov K., 2005 Kim K., 2009 Tian B., 2010 Asenov A., 2003 Weng F., 2003 Zhao W., 2006 Moore G., 1965 Borkar S., 2005 Griliches Z., 1957 Rogers E., 2003 Keller W., 2004 Asenov A., 1998 Mizuno T., 1994 Weng F., 2000 Shannon M., 2008 Asenov A., 2003 Stolk P., 1998 Benotti M., 2009 Baron R., 1986 Ferraro R., 2005 Kuhn K., 2007 Aitken B., 1999

Key statistics:

Coinciding references (in bold): 6 Mean top-30 betwenness: 1075.6 Mean top-30 PageRank: 0.0077

Page Rank Weng F., 2003

Weng F., 2012 Grant R., 1996 Simon P., 2008 Geim A., 2007 Ahlbin J., 2009 Calin T., 1996 Wang H., 2010 Keller W., 2004 Aumann H., 2003 Seifert N., 2010 Stoller M., 2008 Weng F., 2013 Zhang L., 2009, Winter M., 2004 Nakada N., 2007 Cohen W., 1990 Surussavadee C., 2007 Surussavadee C., 2008 Surussavadee C., 2008 Chatterjee I., 2011 Takeuchi K., 2007 Han Y., 2007 Amusan O., 2006 Harris B., 2001 Nonaka I., 1995 Weng F., 1994 Asenov A., 2003 Stolk P., 1998 Copeland B., 2004

References

1. Asenov , A. , Brown , A. , Davies , J. , Kaya , S. , & Slavcheva , G. ( 2003 ). Simulation of intrinsic parameter fluctuations in decananometer and nanometer-scale MOSFETs . IEEE Transactions on Electron Devices , 50 ( 9 ), 1837 - 1852 .

2. Barley , S. ( 1986 ). Technology as an occasion for structuring: Evidence from observations of CT scanners and the social order of radiology departments . Administrative science quarterly , 3 ( 1 ), 78 - 108 .

3. Bartlett , C. , & Ghoshal , S. ( 1989 ). Managing across borders: The transnational solution . Harvard Business School Press.

4. Bavelas , A. ( 1948 ). A mathematical model for group structures . Human Organization (7) , 16 - 30 .

5. Bavelas , A. ( 1950 ). Communication patterns in task oriented groups . Journal of the Acoustical Society of America (22) , 271 - 282 .

6. Blomström , M. , & Kokko , A. ( 1998 ). Multinational corporations and spillovers . Journal of Economic Surveys , 12 ( 3 ), 247 - 77 .

7. Burt , R.S. ( 2002 ). The social capital of structural holes . In M. F. Guillén , R. Collins, P. England , & M. Russell (Ed.), New Directions in Economic Sociology. Thousand Oaks, CA: Sage Foundation, 203 - 47 .

8. Caves , R. ( 1974 ). Multinational firms, competition and productivity in host-country markets . Economica , 41 ( 162 ), 176 - 93 .

9. Christensen , C. ( 1997 ). The innovator's dilemma: When new technologies cause great firms to fail . Harvard Business Review Press.

10. Coe , D. , & Helpman , E. ( 1995 ). International R& D spillovers . European Economic Review , 39 ( 5 ), 859 - 87 .

11. Cohen , W. , & Levinthal , D. ( 1990 ). Absorptive capacity: A new perspective on learning and innovation . Administrative Science Quarterly , 35 ( 1 ), 128 - 52 .

12. Ding , Y. , Yan , E. , Frazho , A. , & Caverlee , J. ( 2009 ). PageRank for ranking authors in cocitation networks . Journal of the American Society for Information Science and Technology , 60 ( 11 ), 2229 - 43 .

13. Fagerberg , J. , & Verspagen , B. ( 2009 ). Innovation studies - The emerging structure of a new scientific field . . Research Policy , 38 ( 2 ), 218 - 33 .

14. Fagerberg , J. , Fosaas , M. , & Sapprasert , K. ( 2012a ). Innovation: Exploring the knowledge base . Research Policy , 41 ( 7 ), 1132 - 53 .

15. Fagerberg , J. , Landström , H. , & Martin , B. R. ( 2012b ). Exploring the emerging knowledge base of 'the knowledge society' . Research Policy , 41 ( 7 ), 1121 - 31 .

16. Forsgren , M. ( 1995 ). Division headquarters go abroad - a step in the internazionalization of the multinational corporation . Joumal of Managemmt Studies , 32 ( 4 ), 475 - 91 .

17. Geim , A. , & Novoselov , K. ( 2007 ). The rise of graphene . Nature Materials , 6 ( 3 ), 183 - 91 .

18. Gmür , M. ( 1973 ). Co-citation analysis and the search for invisible colleges: A methodological evaluation . Scientometrics , 51 ( 1 ), 27 - 57 .

19. Gokhberg , L. , Fursov , K. , Miles , I. , & Perani , G. ( 2013 ). Developing and using indicators of emerging and enabling technologies . In F. Gault Handbook of Innovation Indicators and Measurement . Cheltenham: Edward Elgar Publishing Ltd., 349 - 80 .

20. Howells , J. ( 1990 ). The location and organisation of research and development: New horizons . Research Policy , 4 ( 30 ), 133 - 46 .

21. Jaffe , A. , Trajtenberg , M. , & Henderson , R. ( 1993 ). Geographic localization of knowledge spillovers as evidenced by patent citations . The Quarterly Journal of Economics , 108 ( 3 ), 577 - 98 .

22. Keller, W. ( 2004 ). International technology diffusion . Journal of Economic Literature , 42 ( 3 ), 752 - 82 .

23. Kline , S. , & Rosenberg , N. ( 1986 ). An Overview of innovation. In the positive sum strategy: Harnessing technology for economic growth . Washington, DC: The National Academies Press.

24. Leavitt , H. ( 1951 ). Some effects of communication patterns on group performance . Journal of Abnormal and Social Psychology (46) , 38 - 50 .

25. Marshakova-Shaikevich , I. ( 1973 ). Sistema svyazey mezhdu documentami, postroennaya na osnove ssylok: po dannym Science Citation Index (in Russian) . Nauchno-tehnicheskaya informatsiya , 2 ( 6 ), 3 - 8 .

26. Merton , R. ( 1988 ). The Matthew effect in science, 2: cumulative advantage and the symbolism of intellectual property . ISIS , 79 ( 299 ), 606 - 23 .

27. OECD. ( 1994 ). Frascati Manual 1993 : Proposed standard practice for surveys of research and experimental development . Paris.

28. Porter , M. ( 2000 ). Location, competition, and economic development: Local clusters in a global economy . Economic Development Quarterly , 14 ( 1 ), 15 - 34 .

29. Rotolo , D. , Hicks , D. , & Martin , B. ( 2015 ). What is an emerging technology? Research Policy , 1827 - 1843 .

30. Seaton R.A.F. & Cordey-Hayes M. ( 1993 ). The Development and application of interactive models of industrial technology transfer . Technovation , 13 , 45 - 53 .

31. Simon , P. , & Gogotsi , Y. ( 2008 ). Materials for electrochemical capacitors . Nature Materials , 7 ( 11 ), 845 - 54 .

32. Small , H. ( 1973 ). Co-citation in the scientific literature: a new measure of the relationship between two documents . Journal of the American Society for Information Science , 24 ( 2 ), 265 - 69 .

33. Small , H. ( 1999 ). Visualizing science by citation mapping. . Journal of the American Society for Information Science , 50 ( 9 ), 799 - 813 .

34. Small , H. ( 2004 ). On the shoulders of Robert Merton: Towards a normative theory of citation . Scientometrics , 60 ( 1 ), 71 - 79 .

35. Small , H. , Boyack , K. W. , & Klavans , R. ( 2014 ). Identifying emerging topics in science and technology . Research Policy , 43 ( 8 ), 1450 - 67 .

36. Smith , S. ( 1950 ). Communication Pattern and the Adaptability of Task-oriented Groups: an Experimental Study . Cambridge, MA: Group Networks Laboratory, Research Laboratory of Electronics, Massachusetts Institute of Technology.

37. Stolk , P. , Widdershoven , F. , & Klaassen , D. ( 1998 ). Modeling statistical dopant fluctuations in MOS transistors . IEEE Transactions on Electron Devices , 45 ( 9 ), 1960 - 71 .

38. Venables P.F.R. ( 1962 ). The colleges of advanced technologies . Chemistry & Industry , 36 , 1596 - 99 .

39. Weng , F. , Zhao , L. , Ferraro , R. , Poe , G. , Li , X. , & Grody , N. ( 2003 ). Advanced microwave sounding unit cloud and precipitation algorithms . Radio Science , 38 ( 4 ), 8068 .