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DOI: https://doi.org/10.2478/jdis-2025-0037

Research Papers

Smart community-driven sustainable urban transition: Knowledge mapping and innovation pathways

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  • 1Wenzhou University of Technology, Wenzhou 325000, China;
    2Shandong University, Weihai 264209, China;
    3City University of Macau, Macau, China;
    4Wenzhou University of Technology, Wenzhou 325000, China;
    5Department of Environmental Design, Dongseo University, Busan 47001, Republic of Korea
†Xinting Li (Email: 202099800008@email.sdu.edu.cn; ORCID: 0009-0009-1071-5468).

Received date: 2025-02-23

  Revised date: 2025-05-25

  Accepted date: 2025-06-04

  Online published: 2025-06-25

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Abstract

Purpose: With the deep integration of information technologies into urban governance, smart communities have emerged as pivotal platforms for advancing sustainable urban development. However, existing research has not offered a systematic analysis or clear presentation of the field's academic evolution and thematic structure. This study examines the literature on smart communities published between 2000 and 2024. Employing data analysis and visualization tools, it aims to trace the evolution and development trends of smart community research, map its core themes and their interrelationships, and provide actionable insights for policymaking and practical implementation.
Design/methodology/approach: Based on 2,347 publications indexed in the Web of Science from 2000 to 2024, this study employed CiteSpace and VOSviewer to conduct co-citation analysis, keyword co-occurrence mapping, national collaboration network analysis, author and institutional contribution assessment, burst detection, and hotspot term analysis. The literature screening adhered to predefined publication-type criteria and citation-count thresholds to ensure that the results were representative and reliable.
Findings: This study, through literature analysis and data visualization in the field of smart communities, yields the following principal conclusions. First, the application of digital twin technology in optimizing smart community resources has attracted growing attention, demonstrating considerable potential in urban management, infrastructure maintenance, and resident services. Second, as technology advances, digital-twin applications are evolving towards greater precision and efficiency, particularly by deepening their support for resource allocation and decision-making processes. Finally, the future development of smart communities will increasingly depend on the deep integration of digital twins with other cutting-edge technologies, thereby driving intelligent management and optimization of community resources.
Research limitations: This literature repository excludes grey literature and non-English publications, potentially underestimating the representativeness of grassroots innovation. Furthermore, the temporal analysis was constrained by the citation-lag effects of publications from 2000 to 2024.
Practical implications: This study proposes a decision-support toolkit tailored for municipal planners and policymakers. The toolkit comprises three core intervention strategies: multiscale environmental sensing, participatory governance protocols, and regenerative technology pathways. These measures are designed to advance the implementation of the United Nations Sustainable Development Goal 11: Sustainable Cities and Communities.
Originality/value: By explicitly defining and applying the “thematic knowledge framework,” this paper offers a concise roadmap for the evolution of smart community research. It also provides precise guidance for designing and implementing community development strategies that align with Sustainable Development Goals.

Key words： Smart communities; Thematic knowledge framework; Internet of Things (IoT) governance; Digital twins; Sustainable urban development

Cite this article

Lang Zhou, Xinting Li, Ziyi Ying, Siwei Zeng, Jun Xia . Smart community-driven sustainable urban transition: Knowledge mapping and innovation pathways[J]. Journal of Data and Information Science, 0 : 2 -2 . DOI: 10.2478/jdis-2025-0037

References

[1] Abbasi A., Hossain L., Uddin S., & Rasmussen K. J. (2011). Evolutionary dynamics of scientific collaboration networks: multi-levels and cross-time analysis.Scientometrics, 89(2), 687-710.
[2] Abbasi A., Sarker S., & Chiang R. H. (2016). Big data research in information systems: Towards an inclusive research agenda.Journal of the association for information systems, 17(2), 3.
[3] Ahmad K., Maabreh M., Ghaly M., Khan K., Qadir J., & Al-Fuqaha A. (2022). Developing future human-centered smart cities: Critical analysis of smart city security, Data management, and Ethical challenges.Computer Science Review, 43, 100452.
[4] Allam, Z., & Dhunny, Z. A. (2019). On big data, artificial intelligence and smart cities.Cities, 89, 80-91.
[5] Bao H., Nikolaeva A., Xia J., & Ma F. (2025). Evolution Trends and Future Prospects in Artificial Marine Reef Research: A 28-Year Bibliometric Analysis.Sustainability, 17(1), 184.
[6] Belanger F., Hiller J. S., & Smith W. J. (2002). Trustworthiness in electronic commerce: the role of privacy, security, and site attributes.The journal of strategic Information Systems, 11(3-4), 245-270.
[7] Berkes, F. (2009). Evolution of co-management: Role of knowledge generation, bridging organizations and social learning.Journal of Environmental Management, 90(5), 1692-1702.
[8] Bibri, S. E., & Krogstie, J. (2017). Smart sustainable cities of the future: An extensive interdisciplinary literature review.Sustainable cities and society, 31, 183-212.
[9] Boehm K. M., Khosravi P., Vanguri R., Gao J., & Shah S. P. (2022). Harnessing multimodal data integration to advance precision oncology.Nature Reviews Cancer, 22(2), 114-126.
[10] Boyack, K. W., & Klavans, R. (2010). Co‐citation analysis, bibliographic coupling, and direct citation: Which citation approach represents the research front most accurately?Journal of the American Society for Information Science and Technology, 61(12), 2389-2404.
[11] Bozeman B., Fay D., & Slade C. P. (2013). Research collaboration in universities and academic entrepreneurship: the-state-of-the-art.The journal of technology transfer, 38(1), 1-67.
[12] Chen, C. (2003). Enabling techniques for science mapping. In Mapping scientific frontiers: The quest for knowledge visualization(pp. 101-133). Springer.
[13] Chen, C. (2006). CiteSpace II: Detecting and visualizing emerging trends and transient patterns in scientific literature.Journal of the American Society for information Science and Technology, 57(3), 359-377.
[14] Chen, C., & Leydesdorff, L. (2014). Patterns of connections and movements in dual‐map overlays: A new method of publication portfolio analysis.Journal of the association for information science and technology, 65(2), 334-351.
[15] Chen Y., Ardila-Gomez A., & Frame G. (2017). Achieving energy savings by intelligent transportation systems investments in the context of smart cities.Transportation Research Part D: Transport and Environment, 54, 381-396.
[16] Cui L., Xie G., Qu Y., Gao L., & Yang Y. (2018). Security and privacy in smart cities: Challenges and opportunities.Ieee Access, 6, 46134-46145.
[17] Cvar N., Trilar J., Kos A., Volk M., & Stojmenova Duh E. (2020). The use of IoT technology in smart cities and smart villages: similarities, differences, and future prospects.Sensors, 20(14), 3897.
[18] DeLeon, P., & Varda, D. M. (2009). Towards a theory of collaborative policy networks: Identifying structural tendencies.Policy Studies Journal, 37(1), 59-74.
[19] Ding J., Xu J., Weise T., & Wang H. (2022, April 25). Community services and social involvement in COVID-19 governance in urban China(Version 1) [Preprint]. Research Square. https://doi.org/10.21203/rs.3.rs-1550236/v1
[20] Dwivedi Y. K., Ismagilova E., Hughes D. L., Carlson J., Filieri R., Jacobson J., . . & Krishen, A. S. (2021). Setting the future of digital and social media marketing research: Perspectives and research propositions.International Journal of Information Management, 59, 102168.
[21] Eckhoff, D., & Wagner, I. (2017). Privacy in the smart city—applications, technologies, challenges, and solutions.IEEE Communications Surveys & Tutorials, 20(1), 489-516.
[22] Glänzel, W., & Moed, H. F. (2002). Journal impact measures in bibliometric research.Scientometrics, 53, 171-193.
[23] Goldsmith, S., & Crawford, S. (2014). The responsive city: Engaging communities through data-smart governance. Jossey-Bass.
[24] Guo Y.-M., Huang Z.-L., Guo J., Li H., Guo X.-R., & Nkeli M. J. (2019). Bibliometric analysis on smart cities research.Sustainability, 11(13), 3606.
[25] Healey, P. (2020). Collaborative planning: Shaping places in fragmented societies. Bloomsbury Publishing.
[26] Hoekman J., Frenken K., & Tijssen R. J. (2010). Research collaboration at a distance: Changing spatial patterns of scientific collaboration within Europe.Research policy, 39(5), 662-673.
[27] Hollingsworth, J. R. (2000). Doing institutional analysis: implications for the study of innovations.Review of international political economy, 7(4), 595-644.
[28] Hou J., Yang X., & Chen C. (2018). Emerging trends and new developments in information science: A document co-citation analysis (2009-2016).Scientometrics, 115, 869-892.
[29] Jiang, H. (2022). Design and implementation of smart community big data dynamic analysis model based on logistic regression model.Computational Intelligence and Neuroscience, 2022(1), 4038084.
[30] Jin Y., Ji S., Li X., & Yu J. (2017). A scientometric review of hotspots and emerging trends in additive manufacturing.Journal of Manufacturing Technology Management, 28(1), 18-38.
[31] Joss S., Sengers F., Schraven D., Caprotti F., & Dayot Y. (2019). The smart city as global discourse: Storylines and critical junctures across 27 cities.Journal of Urban Technology, 26(1), 3-34.
[32] Kastrin, A., & Hristovski, D. (2021). Scientometric analysis and knowledge mapping of literature-based discovery (1986-2020).Scientometrics, 126(2), 1415-1451.
[33] Kim M. J., Cho M. E., & Chae H. H. (2014). A smart community for placemaking in housing complexes.Journal of Asian Architecture and Building Engineering, 13(3), 539-546.
[34] Komninos, N. (2009). Intelligent cities: towards interactive and global innovation environments.International Journal of Innovation and regional development, 1(4), 337-355.
[35] Li X., Lu R., Liang X., Shen X., Chen J., & Lin X. (2011). Smart community: An internet of things application.IEEE Communications magazine, 49(11), 68-75.
[36] Liu X., Zhao S., Tan L., Tan Y., Wang Y., Ye Z., . . & Wang, G. (2022). Frontier and hot topics in electrochemiluminescence sensing technology based on CiteSpace bibliometric analysis.Biosensors and Bioelectronics, 201, 113932.
[37] Liu, Y., & Hu, S. (2016). Renewable energy pricing driven scheduling in distributed smart community systems.IEEE Transactions on Parallel and Distributed Systems, 28(5), 1445-1456.
[38] Liu Z., Yin Y., Liu W., & Dunford M. (2015). Visualizing the intellectual structure and evolution of innovation systems research: A bibliometric analysis.Scientometrics, 103, 135-158.
[39] Luukkonen T., Tijssen R. J., Persson O., & Sivertsen G. (1993). The measurement of international scientific collaboration.Scientometrics, 28, 15-36.
[40] Malek J. A., Lim S. B., & Yigitcanlar T. (2021). Social inclusion indicators for building citizen-centric smart cities: A systematic literature review.Sustainability, 13(1), 376.
[41] Moody, J. (2004). The structure of a social science collaboration network: Disciplinary cohesion from 1963 to 1999.American sociological review, 69(2), 213-238.
[42] Mora L., Bolici R., & Deakin M. (2017). The first two decades of smart-city research: A bibliometric analysis.Journal of Urban Technology, 24(1), 3-27.
[43] Mylonas G., Kalogeras A., Kalogeras G., Anagnostopoulos C., Alexakos C., & Muñoz L. (2021). Digital twins from smart manufacturing to smart cities: A survey.Ieee Access, 9, 143222-143249.
[44] National Academies of Sciences, Engineering, & Medicine. (2022). Equitable and resilient infrastructure investments. The National Academies Press. https://doi.org/10.17226/26633
[45] Niu S., Yang X., Li H., & Zhang J. (2024). Evaluation of smart community resilience: empirical evidence from Heilongjiang province, China.Environment, Development and Sustainability, 1-31.
[46] Nižetić S., Šolić P., Gonzalez-De D. L.-d.-I., & Patrono L. (2020). Internet of Things (IoT): Opportunities, issues and challenges towards a smart and sustainable future.Journal of cleaner production, 274, 122877.
[47] O’Dwyer E., Pan I., Acha S., & Shah N. (2019). Smart energy systems for sustainable smart cities: Current developments, trends and future directions.Applied energy, 237, 581-597.
[48] Okolo, C. (2020). AI in the “Real World”: Examining the Impact of AI Deployment in Low-Resource Contexts. Cornell University. In.
[49] Powell W. W., White D. R., Koput K. W., & Owen-Smith J. (2005). Network dynamics and field evolution: The growth of interorganizational collaboration in the life sciences.American journal of sociology, 110(4), 1132-1205.
[50] Purkayastha A., Palmaro E., Falk-Krzesinski H. J., & Baas J. (2019). Comparison of two article-level, field-independent citation metrics: Field-Weighted Citation Impact (FWCI) and Relative Citation Ratio (RCR).Journal of informetrics, 13(2), 635-642.
[51] Qi, L., & Guo, J. (2019). Development of smart city community service integrated management platform.International Journal of Distributed Sensor Networks, 15(6), 1550147719851975.
[52] Qiu J.-P., Dong K., & Yu H.-Q. (2014). Comparative study on structure and correlation among author co-occurrence networks in bibliometrics.Scientometrics, 101, 1345-1360.
[53] Radhakrishnan S., Erbis S., Isaacs J. A., & Kamarthi S. (2017). Novel keyword co-occurrence network-based methods to foster systematic reviews of scientific literature.PloS one, 12(3), e0172778.
[54] Rehman G. U., Ghani A., Zubair M., Saeed M. I., & Singh D. (2023). SOS: Socially omitting selfishness in IoT for smart and connected communities.International Journal of Communication Systems, 36(1), e4455.
[55] Rujano M. A., Boiten J.-W., Ohmann C., Canham S., Contrino S., David R., . . & Custers, I. (2024). Sharing sensitive data in life sciences: An overview of centralized and federated approaches. Briefings in Bioinformatics, 25(4), bbae262.
[56] Sakshi S., Srivastava P. R., Mangla S. K., & Singh A. (2023). A contemplative overview of smart communities: A hybrid analytical approach.Journal of Enterprise Information Management, 36(5), 1185-1208.
[57] Schaffers H., Komninos N., Pallot M., Trousse B., Nilsson M., & Oliveira A. (2011). Smart cities and the future internet: Towards cooperation frameworks for open innovation. Springer Berlin Heidelberg.
[58] Schaffers H., Ratti C., & Komninos N. (2012). Special issue on smart applications for smart cities-new approaches to innovation: Guest editors’ introduction. Journal of theoretical and applied electronic commerce research, 7(3), ii-v.
[59] Shao B., Li X., & Bian G. (2021). A survey of research hotspots and frontier trends of recommendation systems from the perspective of knowledge graph.Expert Systems with Applications, 165, 113764.
[60] Stratigea, A. (2012). The concept of ‘smart cities’. Towards community development?Netcom. Réseaux, communication et territoires, 26(3/4), 375-388.
[61] Su Z., Wang Y., Xu Q., Fei M., Tian Y.-C., & Zhang N. (2018). A secure charging scheme for electric vehicles with smart communities in energy blockchain.IEEE Internet of Things Journal, 6(3), 4601-4613.
[62] Sun Y., Song H., Jara A. J., & Bie R. (2016). Internet of things and big data analytics for smart and connected communities.Ieee Access, 4, 766-773.
[63] Tene, O., & Polonetsky, J. (2013). Big data for all: Privacy and user control in the age of analytics. Northwestern Journal of Technology and Intellectual Property, 11(5), 239.
[64] Torraco, R. J. (2016). Writing integrative literature reviews: Using the past and present to explore the future.Human resource development review, 15(4), 404-428.
[65] Van Eck, N., & Waltman, L. (2010). Software survey: VOSviewer, a computer program for bibliometric mapping.Scientometrics, 84(2), 523-538.
[66] Woolliscroft, T. (2020). Defining smart community in the context of healthcare efficiency in the UK: mapping the evolution of a concept.International Journal of Intelligent Information Technologies, 16(4), 1-18.
[67] Wu J., Yu Y., Yao X., Zhang Q., Zhou Q., Tang W., . . & Ye, C. (2022). Visualizing the knowledge domains and research trends of childhood asthma: A scientometric analysis with CiteSpace.Frontiers in Pediatrics, 10, 1019371.
[68] Xie L., Chen Z., Wang H., Zheng C., & Jiang J. (2020). Bibliometric and visualized analysis of scientific publications on atlantoaxial spine surgery based on Web of Science and VOSviewer. World neurosurgery, 137, 435-442. e434.
[69] Zaidan E., Ghofrani A., Abulibdeh A., & Jafari M. (2022). Accelerating the change to smart societies-a strategic knowledge-based framework for smart energy transition of urban communities.Frontiers in energy research, 10, 852092.
[70] Zhang J., Chen B., Zhao Y., Cheng X., & Hu F. (2018). Data security and privacy-preserving in edge computing paradigm: Survey and open issues.Ieee Access, 6, 18209-18237.
[71] Zhou W., Chen J., & Huang Y. (2019). Co-citation analysis and burst detection on financial bubbles with scientometrics approach.Economic research-Ekonomska istraživanja, 32(1), 2310-2328.
[72] Zuo, C., & Chen, Q. (2023). Intelligent Smart Community Public Service Supply Optimization Algorithm “under Big Data Background for Smart City.Journal of Testing and Evaluation, 51(3), 1617-1628.
[73] Zygiaris, S. (2013). Smart city reference model: Assisting planners to conceptualize the building of smart city innovation ecosystems.Journal of the knowledge economy, 4, 217-231.
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