Skip to main content
Log in

A few notes on main path analysis

  • Published:
Scientometrics Aims and scope Submit manuscript

Abstract

The last few years have seen a growing interest in main path analysis among scholars across a wide spectrum of disciplines. Hummon and Doreian first introduced this method, and it has since become an effective technique for mapping technological trajectories, exploring scientific knowledge flows, and conducting literature reviews. Nevertheless, there are issues not broadly discussed in applying the method, including the handling of citation data, choosing a proper traversal weight scheme, search options, and interpretation of the resulting paths. This note aims to deepen the discussions and concludes with several suggestions and strategies in applying main path analysis.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3

Notes

  1. Revision history of Pajek can be found on the website http://mrvar.fdv.uni-lj.si/pajek/history.htm.

  2. The number of references for 4751701 is 22, or much higher than that of its neighbors on the main paths, 5012467, 4560984 and 4598285, which are 10, 7 and 6, respectively.

References

  • Aksnes, D. W. (2003). A macro study of self-citation. Scientometrics, 56(2), 235–246.

    Article  Google Scholar 

  • Barberá-Tomás, D., Jiménez-Sáez, F., & Castelló-Molina, I. (2011). Mapping the importance of the real world: The validity of connectivity analysis of patent citations networks. Research Policy, 40(3), 473–486.

    Article  Google Scholar 

  • Batagelj, V. (2003). Efficient algorithms for citation network analysis. In Preprint series, University of Ljubljana, Institute of Mathematics, Physics and Mechanics, Department of Theoretical Computer Science.

  • Batagelj, V., Ferligoj, A., & Squazzoni, F. (2017). The emergence of a field: a network analysis of research on peer review. Scientometrics, 113(1), 503–532.

    Article  Google Scholar 

  • Batagelj, V., & Mrvar, A. (1998). Pajek-program for large network analysis. Connections, 21(2), 47–57.

    MATH  Google Scholar 

  • Bekkers, R., & Martinelli, A. (2012). Knowledge positions in high-tech markets: Trajectories, standards, strategies and true innovators. Technological Forecasting and Social Change, 79(7), 1192–1216.

    Article  Google Scholar 

  • Bhupatiraju, S., Nomaler, Ö., Triulzi, G., & Verspagen, B. (2012). Knowledge flows: Analyzing the core literature of innovation, entrepreneurship and science and technology studies. Research Policy, 41(7), 1205–1218.

    Article  Google Scholar 

  • Brysbaert, M., & Smyth, S. (2011). Self-enhancement in scientific research: The self-citation bias. Psychologica Belgica, 51(2), 129–137.

    Article  Google Scholar 

  • Calero-Medina, C., & Noyons, E. C. (2008). Combining mapping and citation network analysis for a better understanding of the scientific development: The case of the absorptive capacity field. Journal of Informetrics, 2(4), 272–279.

    Article  Google Scholar 

  • Chuang, T. C., Liu, J. S., Lu, L. Y., Tseng, F.-M., Lee, Y., & Chang, C.-T. (2017). The main paths of eTourism: Trends of managing tourism through Internet. Asia Pacific Journal of Tourism Research, 22(2), 213–231.

    Article  Google Scholar 

  • Colicchia, C., & Strozzi, F. (2012). Supply chain risk management: A new methodology for a systematic literature review. Supply Chain Management: An International Journal, 17(4), 403–418.

    Article  Google Scholar 

  • Consoli, D., & Mina, A. (2009). An evolutionary perspective on health innovation systems. Journal of Evolutionary Economics, 19(2), 297.

    Article  Google Scholar 

  • De Nooy, W., Mrvar, A., & Batagelj, V. (2005). Exploratory social network analysis with Pajek. Cambridge: Cambridge University Press.

    Book  Google Scholar 

  • De Nooy, W., Mrvar, A., & Batagelj, V. (2018). Exploratory social network analysis with Pajek (3rd ed.). Cambridge: Cambridge University Press.

    Book  Google Scholar 

  • Epicoco, M. (2013). Knowledge patterns and sources of leadership: Mapping the semiconductor miniaturization trajectory. Research Policy, 42(1), 180–195.

    Article  Google Scholar 

  • Fontana, R., Nuvolari, A., & Verspagen, B. (2009). Mapping technological trajectories as patent citation networks. An application to data communication standards. Economics of Innovation and New Technology, 18(4), 311–336.

    Article  Google Scholar 

  • Glänzel, W., Debackere, K., Thijs, B., & Schubert, A. (2006). A concise review on the role of author self-citations in information science, bibliometrics and science policy. Scientometrics, 67(2), 263–277.

    Article  Google Scholar 

  • Glänzel, W., & Thijs, B. (2004). The influence of author self-citations on bibliometric macro indicators. Scientometrics, 59(3), 281–310.

    Article  Google Scholar 

  • Harris, J. K., Beatty, K. E., Lecy, J. D., Cyr, J. M., & Shapiro, R. M. (2011). Mapping the multidisciplinary field of public health services and systems research. American Journal of Preventive Medicine, 41(1), 105–111.

    Article  Google Scholar 

  • Ho, J. C., Saw, E.-C., Lu, L. Y., & Liu, J. S. (2014). Technological barriers and research trends in fuel cell technologies: A citation network analysis. Technological Forecasting and Social Change, 82, 66–79.

    Article  Google Scholar 

  • Ho, M. H.-C., Liu, J. S., & Chang, K. C.-T. (2017). To include or not: the role of review papers in citation-based analysis. Scientometrics, 110(1), 65–76.

    Article  Google Scholar 

  • Hummon, N. P., & Doreian, P. (1989). Connectivity in a citation network: The development of DNA theory. Social Networks, 11(1), 39–63.

    Article  Google Scholar 

  • Hung, S.-C., Liu, J. S., Lu, L. Y., & Tseng, Y.-C. (2014). Technological change in lithium iron phosphate battery: The key-route main path analysis. Scientometrics, 100(1), 97–120.

    Article  Google Scholar 

  • Hyland, K. (2003). Self-citation and self-reference: Credibility and promotion in academic publication. Journal of the American Society for Information Science and Technology, 54(3), 251–259.

    Article  Google Scholar 

  • Kim, J., & Shin, J. (2018). Mapping extended technological trajectories: integration of main path, derivative paths, and technology junctures. Scientometrics, 116(3), 1439–1459.

    Article  MathSciNet  Google Scholar 

  • Liu, J. S., Chen, H. H., Ho, M. H. C., & Li, Y. C. (2014). Citations with different levels of relevancy: Tracing the main paths of legal opinions. Journal of the Association for Information Science and Technology, 65(12), 2479–2488.

    Article  Google Scholar 

  • Liu, J. S., & Lu, L. Y. (2012). An integrated approach for main path analysis: Development of the Hirsch index as an example. Journal of the Association for Information Science and Technology, 63(3), 528–542.

    Google Scholar 

  • Liu, J. S., Lu, L. Y., & Lu, W.-M. (2016). Research fronts in data envelopment analysis. Omega, 58, 33–45.

    Article  Google Scholar 

  • Liu, J. S., Lu, L. Y., Lu, W.-M., & Lin, B. J. (2013a). Data envelopment analysis 1978–2010: A citation-based literature survey. Omega, 41(1), 3–15.

    Article  Google Scholar 

  • Liu, J. S., Lu, L. Y., Lu, W.-M., & Lin, B. J. (2013b). A survey of DEA applications. Omega, 41(5), 893–902.

    Article  Google Scholar 

  • Lu, L. Y., Lan, Y., & Liu, J. S. (2012). A novel approach for exploring technological development trajectories. In: 2012 IEEE International Conference on Management of Innovation and Technology (ICMIT) (pp. 504–509). IEEE.

  • Lu, L. Y., & Liu, J. S. (2013). An innovative approach to identify the knowledge diffusion path: The case of resource-based theory. Scientometrics, 94(1), 225–246.

    Article  MathSciNet  Google Scholar 

  • Lu, L. Y., & Liu, J. S. (2016). A novel approach to identify the major research themes and development trajectory: The case of patenting research. Technological Forecasting and Social Change, 103, 71–82.

    Article  Google Scholar 

  • Lucio-Arias, D., & Leydesdorff, L. (2008). Main-path analysis and path-dependent transitions in HistCite™-based historiograms. Journal of the Association for Information Science and Technology, 59(12), 1948–1962.

    Google Scholar 

  • MacRoberts, M. H., & MacRoberts, B. R. (1989). Problems of citation analysis: A critical review. Journal of the American Society for information Science, 40(5), 342–349.

    Article  Google Scholar 

  • MacRoberts, M. H., & MacRoberts, B. R. (1996). Problems of citation analysis. Scientometrics, 36(3), 435–444.

    Article  Google Scholar 

  • Martinelli, A. (2012). An emerging paradigm or just another trajectory? Understanding the nature of technological changes using engineering heuristics in the telecommunications switching industry. Research Policy, 41(2), 414–429.

    Article  Google Scholar 

  • Mina, A., Ramlogan, R., Tampubolon, G., & Metcalfe, J. S. (2007). Mapping evolutionary trajectories: Applications to the growth and transformation of medical knowledge. Research Policy, 36(5), 789–806.

    Article  Google Scholar 

  • OuYang, K., Weng, C. S. J. T. F., & Change, S. (2011). A new comprehensive patent analysis approach for new product design in mechanical engineering. Technological Forecasting and Social Change, 78(7), 1183–1199.

    Article  Google Scholar 

  • Tu, Y. N., & Hsu, S. L. (2016). Constructing conceptual trajectory maps to trace the development of research fields. Journal of the Association for Information Science and Technology, 67(8), 2016–2031.

    Article  Google Scholar 

  • Verspagen, B. (2007). Mapping technological trajectories as patent citation networks: A study on the history of fuel cell research. Advances in Complex Systems, 10(01), 93–115.

    Article  MATH  Google Scholar 

  • Yeo, W., Kim, S., Lee, J.-M., & Kang, J. (2014). Aggregative and stochastic model of main path identification: A case study on graphene. Scientometrics, 98(1), 633–655.

    Article  Google Scholar 

Download references

Acknowledgements

We thank two anonymous reviewers for their constructive comments which have greatly improved the accuracy and readability of this article. This work is partially supported by Taiwan's Ministry of Science and Technology grants MOST 105-2410-H-011-021-MY3, 107-2410-H-155-046, and 106-2410-H-011-028-MY2.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to John S. Liu.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Liu, J.S., Lu, L.Y.Y. & Ho, M.HC. A few notes on main path analysis. Scientometrics 119, 379–391 (2019). https://doi.org/10.1007/s11192-019-03034-x

Download citation

  • Received:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11192-019-03034-x

Keywords

Navigation