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The evolution of "Technological and Economic Development of Economy“: a bibliometric analysis

    Dejian Yu Affiliation
    ; Zeshui Xu Affiliation
    ; Jonas Šaparauskas Affiliation

Abstract

The Technological and Economic Development of Economy (TEDE) journal was founded 25 years ago and it plays an important role in the economic field. The purposes of this study are to present a bibliometric analysis of the TEDE publications that are included in the Social Science Citation Index (SSCI) database and identify the characteristics and evolution of the TEDE journal through some commonly used as well as various kinds of newly designed indicators. Firstly, annual and geographical distributions, author and manuscript characteristics of the TEDE publications are explored. Secondly, leading contributors including countries/territories, institutions, and authors are presented. The thematic analyses based on co-occurrence of keywords are presented lastly. The main advantages of this study are that all the analysis results are entirely based on objective data and the complex and important results are visualized. This study helps in understanding the development of the TEDE journal and has certain reference value for scholars in the economic field.

Keyword : bibliometric analysis, evolution, Technological and Economic Development of Economy, characteristics

How to Cite
Yu, D., Xu, Z., & Šaparauskas, J. (2019). The evolution of "Technological and Economic Development of Economy“: a bibliometric analysis. Technological and Economic Development of Economy, 25(3), 369-385. https://doi.org/10.3846/tede.2019.10193
Published in Issue
Apr 26, 2019
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This work is licensed under a Creative Commons Attribution 4.0 International License.

References

Bornmann, L., & Daniel, H. D. 2007. What do we know about the h index? Journal of the American Society for Information Science and Technology, 58(9), 1381-1385. https://doi.org/10.1002/asi.20609

Calma, A., & Davies, M. 2016. Academy of Management Journal, 1958–2014: A citation analysis. Scientometrics, 108(2), 959-975. https://doi.org/10.1007/s11192-016-1998-y

He, X. R., Wu, Y. Y., Yu, D. J., & Merigó, J. M. 2017. Exploring the ordered weighted averaging operator knowledge domain: a bibliometric analysis. International Journal of Intelligent Systems, 32(11), 1151-1166. https://doi.org/10.1002/int.21894

Hirsch, J. E. 2005. An index to quantify an individual’s scientific research output. Proceedings of the National academy of Sciences, 102(46), 16569-16572. https://doi.org/10.1073/pnas.0507655102

Hirsch, J. E. 2007. Does the h index have predictive power? Proceedings of the National Academy of Sciences, 104(49), 19193-19198. https://doi.org/10.1073/pnas.0707962104

Laengle, S., Merigó, J. M., Miranda, J., Słowiński, R., Bomze, I., Borgonovo, E., Dyson, R. G., Oliveira, J. F., & Teunter, R. 2017. Forty years of the European Journal of Operational Research: A bibliometric overview. European Journal of Operational Research 262(3), 803-816. https://doi.org/10.1016/j.ejor.2017.04.027

Liao, H. C., Tang, M., Luo, L., Li, C., Chiclana, F., & Zeng, X. J. 2018. A bibliometric analysis and visualization of medical big data research. Sustainability, 10(1), 166. https://doi.org/10.3390/su10010166

Liu, W., Hu, G., Tang, L., & Wang, Y. 2015. China’s global growth in social science research: Uncovering evidence from bibliometric analyses of SSCI publications (1978–2013). Journal of Informetrics, 9(3), 555-569. https://doi.org/10.1016/j.joi.2015.05.007

Liu, W., Hu, G., & Tang, L. (2018). Missing author address information in Web of Science – An explorative study. Journal of Informetrics, 12(3), 985-997. https://doi.org/10.1016/j.joi.2018.07.008

Martínez-López, F. J., Merigó, J. M., Valenzuela-Fernández, L., & Nicolás, C. 2018. Fifty years of the European Journal of Marketing: A bibliometric analysis. European Journal of Marketing, 52(1/2), 439-468. https://doi.org/10.1108/EJM-11-2017-0853

Merigó, J. M., Mas-Tur, A., Roig-Tierno, N., & Ribeiro-Soriano, D. 2015. A bibliometric overview of the Journal of Business Research between 1973 and 2014. Journal of Business Research, 68(12), 2645-2653. https://doi.org/10.1016/j.jbusres.2015.04.006

Paschen, J., Wilson, M., Nehajowich, J., & Prpić, J. 2016. Fine wine through time: a review of the Journal of Wine Research. Journal of Wine Research, 27(2), 91-104. https://doi.org/10.1080/09571264.2016.1173534

Price, D. D. S. 1976. A general theory of bibliometric and other cumulative advantage processes. Journal of the American Society for Information Science, 27(5), 292-306. https://doi.org/10.1002/asi.4630270505

Van Oorschot, J. A., Hofman, E., & Halman, J. I. 2018. A bibliometric review of the innovation adoption literature,.Technological Forecasting and Social Change, 134, 1-21. https://doi.org/10.1016/j.techfore.2018.04.032

Van Eck, N. J., & Waltman, L. 2010. Software survey: VOSviewer, a computer program for bibliometric mapping. Scientometrics, 84(2), 523-538. https://doi.org/10.1007/s11192-009-0146-3

Van Eck, N. J., & Waltman, L. 2017. Citation-based clustering of publications using CitNetExplorer and VOSviewer. Scientometrics, 111(2), 1053-1070. https://doi.org/10.1007/s11192-017-2300-7

Yu, D. J. 2015. A scientometrics review on aggregation operator research. Scientometrics, 105(1), 115-133. https://doi.org/10.1007/s11192-015-1695-2

Yu, D. J., Xu, Z. S., Pedrycz, W., & Wang, W. R. 2017. Information Sciences 1968–2016: A retrospective analysis with text mining and bibliometric. Information Sciences, 418, 619-634. https://doi.org/10.1016/j.ins.2017.08.031

Yu, D. J., Xu, Z. S., Kao, Y., & Lin, C. T. 2018. The structure and citation landscape of IEEE Transactions on Fuzzy Systems (1994–2015). IEEE Transactions on Fuzzy Systems, 26(2), 430-442. https://doi.org/10.1109/TFUZZ.2017.2672732

Yu, D. J., Xu, Z. S., & Wang, W. R. 2018. Bibliometric analysis of fuzzy theory research in China: A 30-year perspective. Knowledge-Based Systems, 141, 188-199. https://doi.org/10.1016/j.knosys.2017.11.018

Yu, D. J., Xu, Z. S., & Fujita, H. 2019. Bibliometric analysis on the evolution of applied intelligence. Applied Intelligence, 49(2), 449-462. https://doi.org/10.1007/s10489-018-1278-z

Zavadskas, E. K., & Turskis, Z. 2011. Multiple criteria decision making (MCDM) methods in economics: an overview. Technological and Economic Development of Economy, 17(2), 397-427. https://doi.org/10.3846/20294913.2011.593291