Access Journal

Access to Science, Business, Innovation in the Digital Economy
The journal uses continuous publication model. Current issue is in progress.
Published Online: Apr 11, 2025

Unravelling Economic Complexity: A Systematic Exploration of Themes and Trends through Literature and Keyword Network Analysis

Published Online: Apr 11, 2025

Sonali SINGH

Email: phd21004@iiml.ac.in
Indian Institute of Management Lucknow, Lucknow, India

Sanjay Kumar SINGH

Email: sanjay@iiml.ac.in
Indian Institute of Management Lucknow, Lucknow, India

Vijay Lakshmi SINGH

Email: vijaylakshmi.singh@jaipuria.ac.in
Jaipuria Institute of Management Lucknow, Lucknow, India

Mariana PETROVA

Email: m.petrova@ts.uni-vt.bg
St. Cyril and St. Methodius University of Veliko Tarnovo, Veliko Tarnovo, Bulgaria
University of Telecommunications and Post, Sofia, Bulgaria
Views: 109
Downloads: 22
Download PDF
Abstract:
Background: The Economic Complexity Index (ECI) is a robust and computationally viable measure that captures the diversity and sophistication of an economy's industrial sector, reflecting the knowledge and capabilities embedded in its export basket. The rapid growth in scholarly literature employing economic complexity measures necessitates a systematic review of how ECI has been studied, applied, and understood by economists, policymakers, and researchers. Objectives: This study synthesises 215 “Economic Complexity” articles published in Web of Science (WoS) journals from 2006 to 2022. Methods/Approach: Using Systematic Literature Network Analysis (SLNA) and Keyword Network Exploration (KNE), the review identifies key trends, critical issues, and emerging topics in the field. SLNA integrates bibliographic networks with systematic literature reviews, while KNE explores thematic interconnections through keyword co-occurrence analysis. Open-source tools such as Sci2, Pajek, Biblioshiny (R-Package), and VOSviewer facilitated network extraction and analysis. Results: The findings highlight future research directions, including innovation, regional studies, institutions, human capital formation, ecological footprint, and firm-level economic complexity. Conclusions: This research provides essential insights into the development of economic complexity studies and outlines a pathway for future exploration.
Keywords:
Economic Complexity, Systematic Literature Network Analysis, Citation Analysis, Circular Main Path, Keyword Network Analysis
Pages:
357-381
JEL Classification:
C80, L60, F10, F40, Q50, O11
DOI:
https://doi.org/10.46656/access.2025.6.2(7)
How to cite:
Singh, S., Singh, S.K., Singh, V.L., Petrova, M. (2025) Unravelling Economic Complexity: A Systematic Exploration of Themes and Trends through Literature and Keyword Network Analysis. Access to science, business, innovation in digital economy, ACCESS Press, 6(2), 357-381, https://doi.org/10.46656/access.2025.6.2(7)
References:
  • Agarwal, Y. (2008). Interdependence, integration and co-creation. Management Dynamics, 8(1), 23-32. https://doi.org/10.57198/2583-4932.1184
  • Aria, M., & Cuccurullo, C. (2017). Bibliometrix: An R-tool for comprehensive science mapping analysis. Journal of Informetrics, 11(4), 959-975. https://doi.org/10.1016/j.joi.2017.08.007
  • Balland, P.-A., Broekel, T., Diodato, D., Giuliani, E., Hausmann, R., O'Clery, N., & Rigby, D. (2022). The new paradigm of economic complexity. Research Policy, 51(3), Article 104450. https://doi.org/10.1016/j.respol.2021.104450
  • Batagelj, V. (2014). Understanding large temporal networks and spatial networks: Exploration, pattern searching, visualization and network evolution. Wiley
  • Boleti, E., Garas, A., Kyriakou, A., & Lapatinas, A. (2021). Economic complexity and environmental performance: Evidence from a world sample. Environmental Modeling & Assessment, 26(3), 251-270. https://doi.org/10.1007/s10666-021-09750-0
  • Can, M., & Gozgor, G. (2017). The impact of economic complexity on carbon emissions: Evidence from France. Environmental Science and Pollution Research, 24(19), 16364-16370. https://doi.org/10.1007/s11356-017-9219-7
  • Choi, J., Yi, S., & Lee, K. C. (2011). Analysis of keyword networks in MIS research and implications for predicting knowledge evolution. Information & Management, 48(8), 371-381. https://doi.org/10.1016/j.im.2011.09.004
  • Colicchia, C., Creazza, A., Noè, C., & Strozzi, F. (2019). Information sharing in supply chains: A review of risks and opportunities using the systematic literature network analysis (SLNA). Supply Chain Management: An International Journal, 24(1), 5-21. https://doi.org/10.1108/SCM-01-2018-0003
  • 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. https://doi.org/10.1108/13598541211246558
  • Crisp, R., Waite, D., Green, A., Hughes, C., Lupton, R., MacKinnon, D., & Pike, A. (2023). 'Beyond GDP' in cities: Assessing alternative approaches to urban economic development. Urban Studies, 61(7),1209-1229. https://doi.org/10.1177/00420980231187884
  • Dahmani, M. (2023). Environmental quality and sustainability: Exploring the role of environmental taxes, environment-related technologies, and R&D expenditure. Environmental Economics and Policy Studies, 26(2), 449-477. https://doi.org/10.1007/s10018-023-00387-9
  • Dam, A. van, & Frenken, K. (2022). Variety, complexity and economic development. Research Policy, 51(8), Article 103949. DOI:10.1016/j.respol.2020.103949
  • Denyer, D., & Tranfield, D. (2009). Producing a systematic review. In D. A. Buchanan & A. Bryman (Eds.), The Sage handbook of organizational research methods (pp. 671-689). Sage Publications Ltd.
  • Di Cosmo, A., Pinelli, C., Scandurra, A., Aria, M., & D'Aniello, B. (2021). Research trends in octopus biological studies. Animals, 11(6), Article 1808. https://doi.org/10.3390/ani11061808
  • Ding, Y., Chowdhury, G. G., & Foo, S. (2001). Bibliometric cartography of information retrieval research by using co-word analysis. Information Processing & Management, 37(6), 817-842. https://doi.org/10.1016/S0306-4573(00)00051-0
  • Donthu, N., Kumar, S., Mukherjee, D., Pandey, N., & Lim, W. M. (2021). How to conduct a bibliometric analysis: An overview and guidelines. Journal of Business Research, 133, 285-296. https://doi.org/10.1016/j.jbusres.2021.04.070
  • Durlauf, S. N. (1998). What should policymakers know about economic complexity? The Washington Quarterly, 21(1), 155-165. https://doi.org/10.1080/01636609809550302
  • Gao, J., & Zhou, T. (2018). Quantifying China's regional economic complexity. Physica A: Statistical Mechanics and Its Applications, 492, 1591-1603. https://doi.org/10.1016/j.physa.2017.11.084
  • Guide to HistCite reports. (n.d.). Retrieved August 24, 2023, from http://garfield.library.upenn.edu/histcomp/guide.html#lcs
  • Hartmann, D., Guevara, M. R., Jara-Figueroa, C., Aristarán, M., & Hidalgo, C. A. (2017). Linking economic complexity, institutions, and income inequality. World Development, 93, 75-93. https://doi.org/10.1016/j.worlddev.2016.12.020
  • Hausmann, R., Hidalgo, C., Bustos, S., Coscia, M., Simoes, A., Yıldırım, M., Bahar, D., Klinger, B., Lawrence, R., Rodriguez, F., Rodrik, D., Sabel, C., Wagner, R., Throughout, A., Carranza, A., Siegel, M., Whitney, V., Hoyos, A., Wattie, E., . . . Cowan, G. (2014). The Atlas of economic complexity: Mapping paths to prosperity. Choice Reviews Online, 51(11), Article 51-5931. https://growthlab.hks.harvard.edu/files/growthlab/files/atlas_2013_part1.pdf
  • Hausmann, R., & Hidalgo, C. A. (2011). The network structure of economic output. Journal of Economic Growth, 16(4), 309-342. https://doi.org/10.1007/s10887-011-9071-4
  • Hausmann, R., Pritchett, L., & Rodrik, D. (2005). Growth accelerations. Journal of Economic Growth, 10(4),303 329. https://doi.org/10.1007/s10887-005-4712-0
  • Hidalgo, C. A. (2021). Economic complexity theory and applications. Nature Reviews Physics, 3(2), 92-113. https://doi.org/10.1038/s42254-020-00275-1
  • Hidalgo, C. (2015). Why information grows: The evolution of order, from atoms to economies. Penguin UK
  • Hidalgo, C. A., & Hausmann, R. (2009). The building blocks of economic complexity. Proceedings of the National Academy of Sciences, 106(26), 10570-10575. https://doi.org/10.1073/pnas.0900943106
  • Hidalgo, C. A., Klinger, B., Barabási, A.-L., & Hausmann, R. (2007). The product space conditions the development of nations. Science, 317(5837), 482-487. https://doi.org/10.1126/science.1144581
  • Hopwood, B., Mellor, M., & O'Brien, G. (2005). Sustainable development: Mapping different approaches. Sustainable Development, 13(1), 38-52. https://doi.org/10.1002/sd.244
  • Jha, A. P., Mahajan, A., Singh, S. K., & Kumar, P. (2022). Renewable energy proliferation for sustainable development: Role of cross-border electricity trade. Renewable Energy, 201, 1189-1199. https://doi.org/10.1016/j.renene.2022.11.046
  • Knoke, D., & Yang, S. (2008). Social network analysis. SAGE Publications, Inc
  • Kumar, K. (2003). WTO: Expectations and realities. Management Dynamics, 4(1). https://doi.org/10.57198/2583-4932.1231
  • Leitão, N., Leitão, N., Balsalobre-Lorente, D., & Cantos-Cantos, J. (2021). The impact of renewable energy and economic complexity on carbon emissions in BRICS countries under the EKC scheme. Energies, 14(16), Article 4908. https://doi.org/10.3390/en14164908
  • Lucio-Arias, D., & Leydesdorff, L. (2008). Main-path analysis and path-dependent transitions in HistCite™-based historiograms. Journal of the American Society for Information Science and Technology, 59(12), 1948-1962. https://doi.org/10.1002/asi.20903
  • McKinnon, R. I. (1988). Monetary and exchange rate policies for international financial stability: A proposal. The Journal of Economic Perspectives, 2(1), 83-103. https://doi.org/10.1257/jep.2.1.83
  • Mealy, P., & Teytelboym, A. (2020). Economic complexity and the green economy. Research Policy, 51(8), Article 103948. https://doi.org/10.1016/j.respol.2020.103948
  • Moral-Muñoz, J. A., Herrera-Viedma, E., Santisteban-Espejo, A., & Cobo, M. J. (2020). Software tools for conducting bibliometric analysis in science: An up-to-date review. El Profesional De La Informacion, 29(1), Article e290103. https://doi.org/10.3145/epi.2020.ene.03
  • Mostafa, M. M. (2020). A knowledge domain visualization review of thirty years of halal food research: Themes, trends and knowledge structure. Trends in Food Science & Technology, 99, 660-677. https://doi.org/10.1016/j.tifs.2020.03.022
  • Narayan, P. K., & Smyth, R. (2006). Dead man walking: An empirical reassessment of the deterrent effect of capital punishment using the bounds testing approach to cointegration. Applied Economics, 38(17), 1975-1989. https://doi.org/10.1080/00036840500427288
  • Newbert, S. L. (2007). Empirical research on the resource-based view of the firm: An assessment and suggestions for future research. Strategic Management Journal, 28(2), 121-146. https://doi.org/10.1002/smj.573
  • Nooy, W. de, Mrvar, A., & Batagelj, V. (2011). Exploratory social network analysis with Pajek (Rev. and expanded 2nd ed.). Cambridge University Press
  • Rejeb, A., Rejeb, K., Abdollahi, A., & Treiblmaier, H. (2022). The big picture on Instagram research: Insights from a bibliometric analysis. Telematics and Informatics, 73, Article 101876. https://doi.org/10.1016/j.tele.2022.101876
  • Rejeb, A., Rejeb, K., & Treiblmaier, H. (2023). Mapping metaverse research: Identifying future research areas based on bibliometric and topic modeling techniques. Information, 14(7), Article 356. https://doi.org/10.3390/info14070356
  • Shahzad, U., Fareed, Z., Shahzad, F., & Shahzad, K. (2021). Investigating the nexus between economic complexity, energy consumption and ecological footprint for the United States: New insights from quantile methods. Journal of Cleaner Production, 279, Article 123806. https://doi.org/10.1016/j.jclepro.2020.123806
  • Sikdar, S. (2020). Principles of macroeconomics. Oxford University Press
  • Snyder, H. (2019). Literature review as a research methodology: An overview and guidelines. Journal of Business Research, 104, 333-339. https://doi.org/10.1016/j.jbusres.2019.07.039
  • Sonis, M., & Hewings, G. J. D. (1998). Economic complexity as network complication: Multiregional input-output structural path analysis. The Annals of Regional Science, 32(3), 407-436. https://doi.org/10.1007/s001680050081
  • Strozzi, F., Colicchia, C., Creazza, A., & Noè, C. (2017). Literature review on the 'Smart Factory' concept using bibliometric tools. International Journal of Production Research, 55(22), 6572-6591. https://doi.org/10.1080/00207543.2017.1326643
  • Sutton, J., & Trefler, D. (2016). Capabilities, wealth, and trade. Journal of Political Economy, 124(3), 826-878. https://doi.org/10.1086/686034
  • Tacchella, A., Cristelli, M., Caldarelli, G., Gabrielli, A., & Pietronero, L. (2012). A new metrics for countries' fitness and products' complexity. Scientific Reports, 2(1), Article 723. https://doi.org/10.1038/srep00723
  • Tacchella, A., Cristelli, M., Caldarelli, G., Gabrielli, A., & Pietronero, L. (2013). Economic complexity: Conceptual grounding of a new metrics for global competitiveness. Journal of Economic Dynamics and Control, 37(8), 1683-1691. https://doi.org/10.1016/j.jedc.2013.04.006
  • Van Dam, A., & Frenken, K. (2020). Variety, complexity and economic development. Research Policy, 51(8), Article 103949. https://doi.org/10.1016/j.respol.2020.103949
  • Van Eck, N. J., & Waltman, L. (2009). Software survey: VOSviewer, a computer program for bibliometric mapping. Scientometrics, 84(2), 523-538. https://doi.org/10.1007/s11192-009-0146-3
  • Wang, M., & Chai, L. (2018). Three new bibliometric indicators/approaches derived from keyword analysis. Scientometrics, 116(2), 721-750. https://doi.org/10.1007/s11192-018-2768-9
  • Wilczewski, M., & Alon, I. (2023). Language and communication in international students' adaptation: A bibliometric and content analysis review. Higher Education, 85(6), 1235-1256. https://doi.org/10.1007/s10734-022-00888-8
  • Zhang, L., Padhan, H., Singh, S. K., & Gupta, M. (2024). The impact of renewable energy on inflation in G7 economies: Evidence from artificial neural networks and machine learning methods. Energy Economics, Article 107718. https://doi.org/10.1016/j.eneco.2024.107718


0.8
journal impact factor™ (2023)
0.23
journal citation indicator™ (2023)


Call for papers: OPEN

Submit Article

We use continuous publication model:
3 times on the year (January / May / September)


The National Reference List (NRL) of contemporary Bulgarian scientific publications with scientific review, maintained by the Minister of Education and Science through the National Center for Information and Documentation (Ref №: 3818)

The journal is included in the official list of peer-reviewed scientific journals of the Ministry of Education and Science of Poland from July 17, 2023. (Ref №: 31621)
ErihPlus DOAJ VIEW INDEXES

Our proposal

Check out our proposal if you wish to be part of "ACCESS: Access to science, business, innovation in digital economy" Journal

View Proposal

Special issues

From our latest issue

Archive

View full archive

Keywords

artificial intelligenceinnovationconsumer behaviorKnowledge managementgreen economyEntrepreneurshipmachine learningefficiencycorruptiongross domestic productinnovationssustainable developmentSocial entrepreneurshipmanagementeconomic growthCOVID-19 pandemicsustainabilitytourismForeign Direct Investmentinvestment

Indexes

Zenodo
Google Scholar
Web Of Science
DOAJ
ErihPlus
Publons
RePEc
EconPapers
ELibrary.Ru
Index Copernicus International - World of Journals
Polska Bibliographia Naukowa
DRJI
ESJI
RootIndexing
ResearchBib
Base
International Services for Impact factor and indexing
WorldCat
InfoBase Index
Europub
Advanced Science Index
Dimensions
ISSUU

Publish your science journal

If you like ACCESS journals system, you can publish your journal with us at a reasonable price

Contact ACCESS PRESS!