BIBLIOMETRIC ANALYSIS: THE ROLE OF BIG DATA IN ADVANCING GREEN PRODUCT INNOVATION
DOI:
https://doi.org/10.55197/qjssh.v6i6.875Keywords:
bibliometric analysis, big data, green production, sustainable development, research collaboration, innovationAbstract
This study aims to conduct a bibliometric analysis to examine the role of big data in driving green product innovation for achieving sustainable development. By analyzing publication trends, citation growth, research disciplines, country contributions, and author networks, this research provides valuable insights into the progression of studies within this domain. This study employed a bibliometric approach to analyze scientific publications related to big data and green product innovation. Data were sourced from the Scopus database, encompassing publications from 2015 to 2024. The research assesses key bibliometric indicators, including citation trends, document types, and distribution of subject areas, international collaborations, and prominent authors in the field. The results reveal a notable increase in research focus on big data-driven green product innovation, particularly following 2020, as demonstrated by the rising number of citations. The majority of the published works comprise journal articles (46%) and conference papers (26%), showcasing a robust interest from both academic and industrial sectors. The principal research fields identified are engineering, business, and computer science, underscoring the technological and economic facets of green product innovation. Additionally, strong international collaborations are evident, with significant contributions from Asia, North America, and Australia. The authorship distribution indicates a diverse and cooperative research landscape. The findings offer valuable insights for researchers, policymakers, and industry practitioners on utilizing big data for sustainable production. Understanding research trends and collaboration networks can enhance resource allocation and strategic decision-making for sustainable industrial transformation. This study advances the literature by delivering a comprehensive bibliometric analysis of the role of big data in green product innovation. The insights derived from this analysis can guide future research, particularly in integrating interdisciplinary approaches, enhancing the application of big data, and promoting collaboration to achieve sustainable development goals.
References
[1] Al-Shboul, M.A. (2024): Do reliable big and cloud data analytics capabilities in manufacturing firms’ supply chain boosting unique comparative advantage? A moderated-mediation model of data-driven competitive sustainability, green product innovation and green process innovation. – International Journal of Productivity and Performance Management 73(8): 2598-2628.
[2] Ardito, L., Ernst, H., Messeni Petruzzelli, A. (2020): The interplay between technology characteristics, R&D internationalisation, and new product introduction: Empirical evidence from the energy conservation sector. – Technovation 16p.
[3] Bag, S., Wood, L.C., Xu, L., Dhamija, P., Kayikci, Y. (2020): Big data analytics as an operational excellence approach to enhance sustainable supply chain performance. – Resources, Conservation and Recycling 153: 10p.
[4] Bai, Y., Song, S., Jiao, J., Yang, R. (2019): The impacts of government R&D subsidies on green innovation: Evidence from Chinese energy-intensive firms. – Journal of Cleaner Production 233: 819-829.
[5] Dangelico, R.M. (2017): What Drives Green Product Development and How do Different Antecedents Affect Market Performance? A Survey of Italian Companies with Eco-Labels. – Business Strategy and the Environment 26(8): 1144-1161.
[6] Dangelico, R.M., Pujari, D. (2010): Mainstreaming green product innovation: Why and how companies integrate environmental sustainability. – Journal of Business Ethics 95(3): 471-486.
[7] Davenport, T.H., Dyché, J. (2013): Big data in big companies. – Baylor Business Review 32(1): 20-21.
[8] 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.
[9] El-Kassar, A.N. (2019): Green innovation and organizational performance: The influence of big data and the moderating role of management commitment and HR practices. – Technological Forecasting and Social Change 144: 483-498.
[10] Elkington, J. (1997): Cannibals With Forks, The Triple Bottom Line of 21st Century Business. – Capstone Publishing Limited 407p.
[11] Fantke, P., Cinquemani, C., Yaseneva, P., De Mello, J., Schwabe, H., Ebeling, B., Lapkin, A.A. (2021): Transition to sustainable chemistry through digitalization. – Chem 7(11): 2866-2882.
[12] Fontoura, P., Coelho, A. (2022): How to boost green innovation and performance through collaboration in the supply chain: Insights into a more sustainable economy. – Journal of Cleaner Production 359: 16p.
[13] Fosso Wamba, S., Akter, S., Edwards, A., Chopin, G., Gnanzou, D. (2015): How “big data” can make big impact: Findings from a systematic review and a longitudinal case study. – International Journal of Production Economics 165: 234-246.
[14] George, G., Haas, M.R., Pentland, A. (2014): From the editors: Big data and management. – Academy of Management Journal 57(2): 321-326.
[15] Guo, H., Liang, D., Sun, Z., Chen, F., Wang, X., Li, J., Shirazi, Z. (2022): Measuring and evaluating SDG indicators with Big Earth Data. – Science Bulletin 67(17): 1792-1801.
[16] Halbusi, H.A., Soto-Acosta, P., Popa, S., Hassani, A. (2023): The role of green digital learning orientation and big data analytics in the green innovation–sustainable performance relationship. – IEEE Transactions on Engineering Management 71: 12886-12896.
[17] Kumar, S., Sureka, R., Lim, W.M., Kumar Mangla, S., Goyal, N. (2021): What do we know about business strategy and environmental research? Insights from Business Strategy and the Environment. – Business Strategy and the Environment 30(8): 3454-3469.
[18] McKinsey Global Institute (2011): Big data: The next frontier for innovation, competition and productivity. – McKinsey & Company 143p.
[19] Melander, L., Pazirandeh, A. (2019): Collaboration beyond the supply network for green innovation: insight from 11 cases. – Supply Chain Management 24(4): 509-523.
[20] Ortega-Requena, S., Rebouillat, S. (2015): Bigger data open innovation: potential applications of value-added products from milk and sustainable valorization of by-products from the dairy industry. – Green Chemistry 17(12): 5100-5113.
[21] Porter, M.E., Van Der Linde, C. (1995): Toward a new conception of the environment-competitiveness relationship. – Journal of Economic Perspective 9(4): 97-118.
[22] Rodrigues, M., Franco, M. (2023): Green Innovation in Small and Medium-Sized Enterprises (SMEs): A Qualitative Approach. – Sustainability (Switzerland) 15(5): 1-12.
[23] Tan, K.H., Zhan, Y.Z., Ji, G., Ye, F., Chang, C. (2015): Harvesting big data to enhance supply chain innovation capabilities: An analytic infrastructure based on deduction graph. – International Journal of Production Economics 165: 223-233.
[24] United Nation (UN) (1987): Report of the World Commission on Environment and Development: Our Common Future. – UN 300p.
[25] Waqas, M., Honggang, X., Ahmad, N., Khan, S.A.R., Iqbal, M. (2021): Big data analytics as a roadmap towards green innovation, competitive advantage and environmental performance. – Journal of Cleaner Production 323: 14p.
[26] Yang, Z., Jianjun, L., Faqiri, H., Shafik, W., Talal Abdulrahman, A., Yusuf, M., Sharawy, A.M. (2021): Green internet of things and big data application in smart cities development. – Complexity 15p.
[27] Yuan, B.Z., Sun, J. (2022): Bibliometric analysis of rice and climate change publications based on Web of Science. – Theoretical and Applied Climatology 150(1-2): 347-362.
[28] Zhan, Y., Tan, K.H., Ji, G., Chung, L., Tseng, M. (2017): A big data framework for facilitating product innovation processes. – Business Process Management Journal 23(3): 518-536.
Downloads
Published
Issue
Section
License
Copyright (c) 2025 WIRAYANTI SODELI, ANDI WIJAYANTO
This work is licensed under a Creative Commons Attribution 4.0 International License.
