IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v13y2021i6p3353-d519627.html
   My bibliography  Save this article

Knowledge Management for Sustainable Development in the Era of Continuously Accelerating Technological Revolutions: A Framework and Models

Author

Listed:
  • Meir Russ

    (Austin E. Cofrin School of Business, University of Wisconsin-Green Bay, Green Bay, WI 54311, USA)

Abstract

This conceptual, interdisciplinary paper will start by introducing the commencement of a new era in which human society faces continuously accelerating technological revolutions, named the Post Accelerating Data and Knowledge Online Society, or ‘ Padkos ’ (“food for the journey; prog; provisions for journey”—in Afrikaans) for short. In this context, a conceptual model of sustainable development with a focus on knowledge management and sharing will be proposed. The construct of knowledge management will be unpacked into a new three-layer model with a focus on the knowledge-human and data-machine spheres. Then, each sphere will be discussed with concentration on the learning and decision- making processes, the digital supporting systems and the human actors’ aspects. Moreover, the recombination of new knowledge development and contemporary knowledge management into one amalgamated construct will be proposed. The holistic conceptual model of knowledge management for sustainable development is comprised by time, cybersecurity and two alternative humanistic paradigms ( Homo Technologicus and Homo Sustainabiliticus ). Two additional particular models are discussed in depth. First, a recently proposed model of quantum organizational decision-making is elaborated. Next, a boundary management and learning process is deliberated. The paper ends with a number of propositions and several implications for the future based on the deliberations in the paper and the models discussed and with conclusions.

Suggested Citation

  • Meir Russ, 2021. "Knowledge Management for Sustainable Development in the Era of Continuously Accelerating Technological Revolutions: A Framework and Models," Sustainability, MDPI, vol. 13(6), pages 1-32, March.
  • Handle: RePEc:gam:jsusta:v:13:y:2021:i:6:p:3353-:d:519627
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/13/6/3353/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/13/6/3353/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Jarrahi, Mohammad Hossein, 2018. "Artificial intelligence and the future of work: Human-AI symbiosis in organizational decision making," Business Horizons, Elsevier, vol. 61(4), pages 577-586.
    2. Cegarra-Sánchez, Jorge & Cegarra-Navarro, Juan-Gabriel & Chinnaswamy, Anitha K & Wensley, Anthony, 2020. "Exploitation and exploration of knowledge: An ambidextrous context for the successful adoption of telemedicine technologies," Technological Forecasting and Social Change, Elsevier, vol. 157(C).
    3. Carmen M. Reinhart & Kenneth S. Rogoff, 2014. "This Time is Different: A Panoramic View of Eight Centuries of Financial Crises," Annals of Economics and Finance, Society for AEF, vol. 15(2), pages 215-268, November.
    4. Macmillan, Ian C. & Zemann, Lauriann & Subbanarasimha, P. N., 1987. "Criteria distinguishing successful from unsuccessful ventures in the venture screening process," Journal of Business Venturing, Elsevier, vol. 2(2), pages 123-137.
    5. David Autor & David Dorn & Lawrence F Katz & Christina Patterson & John Van Reenen, 2020. "The Fall of the Labor Share and the Rise of Superstar Firms [“Automation and New Tasks: How Technology Displaces and Reinstates Labor”]," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 135(2), pages 645-709.
    6. Meir Russ, 2014. "Introduction—What Kind of an Asset Is Human Capital, How Should It Be Measured, and in What Markets?," Palgrave Macmillan Books, in: Meir Russ (ed.), Management, Valuation, and Risk for Human Capital and Human Assets, pages 1-33, Palgrave Macmillan.
    7. Solaimani, Sam & Haghighi Talab, Ardalan & van der Rhee, Bo, 2019. "An integrative view on Lean innovation management," Journal of Business Research, Elsevier, vol. 105(C), pages 109-120.
    8. Thomas Johnsen, 2009. "Supplier involvement in new product development and innovation: Taking stock and looking to the future," Post-Print hal-00771091, HAL.
    9. Meir Russ, 2017. "The Trifurcation of the Labor Markets in the Networked, Knowledge-Driven, Global Economy," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 8(2), pages 672-703, June.
    10. Haridimos Tsoukas, 2017. "Don't Simplify, Complexify: From Disjunctive to Conjunctive Theorizing in Organization and Management Studies," Journal of Management Studies, Wiley Blackwell, vol. 54(2), pages 132-153, March.
    11. Santini, Cristina & Marinelli, Elisabetta & Boden, Mark & Cavicchi, Alessio & Haegeman, Karel, 2016. "Reducing the distance between thinkers and doers in the entrepreneurial discovery process: An exploratory study," Journal of Business Research, Elsevier, vol. 69(5), pages 1840-1844.
    12. Olivera Kostoska & Ljupco Kocarev, 2019. "A Novel ICT Framework for Sustainable Development Goals," Sustainability, MDPI, vol. 11(7), pages 1-31, April.
    13. Martin Gudem & Martin Steinert & Torgeir Welo, 2014. "From Lean Product Development To Lean Innovation: Searching For A More Valid Approach For Promoting Utilitarian And Emotional Value," International Journal of Innovation and Technology Management (IJITM), World Scientific Publishing Co. Pte. Ltd., vol. 11(02), pages 1-20.
    14. Baruch Lev, 2019. "Ending the Accounting-for-Intangibles Status Quo," European Accounting Review, Taylor & Francis Journals, vol. 28(4), pages 713-736, August.
    15. Yosef Jabareen, 2008. "A New Conceptual Framework for Sustainable Development," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 10(2), pages 179-192, April.
    16. Saeed Nosratabadi & Amir Mosavi & Puhong Duan & Pedram Ghamisi, 2020. "Data Science in Economics," Papers 2003.13422, arXiv.org.
    17. Andrea De Mauro & Marco Greco & Michele Grimaldi, 2019. "Understanding Big Data Through a Systematic Literature Review: The ITMI Model," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 18(04), pages 1433-1461, July.
    18. Yao-Chin Lin & Ching-Chuan Yeh & Wei-Hung Chen & Wei-Chun Liu & Jyun-Jie Wang, 2020. "The Use of Big Data for Sustainable Development in Motor Production Line Issues," Sustainability, MDPI, vol. 12(13), pages 1-24, July.
    19. Xiao-Yu Zhang & Stefanie Kuenzel & José-Rodrigo Córdoba-Pachón & Chris Watkins, 2020. "Privacy-Functionality Trade-Off: A Privacy-Preserving Multi-Channel Smart Metering System," Energies, MDPI, vol. 13(12), pages 1-30, June.
    20. Nosratabadi, Saeed & Mosavi, Amir & Duan, Puhong & Ghamisi, Pedram & Filip, Ferdinand & Band, Shahab S. & Reuter, Uwe & Gama, Joao & Gandomi, Amir H., 2020. "Data science in economics: comprehensive review of advanced machine learning and deep learning methods," MetaArXiv haf2v, Center for Open Science.
    21. Raquel Sanchis & Maria Rosa Sanchis-Gisbert & Raul Poler, 2020. "Conceptualisation of the Three-Dimensional Matrix of Collaborative Knowledge Barriers," Sustainability, MDPI, vol. 12(3), pages 1-24, February.
    22. Akansha Gautam & Indranath Chatterjee, 2020. "Big Data and Cloud Computing: A Critical Review," International Journal of Operations Research and Information Systems (IJORIS), IGI Global, vol. 11(3), pages 19-38, July.
    23. Nosratabadi, Saeed & Mosavi, Amir & Duan, Puhong & Ghamisi, Pedram & Filip, Ferdinand & Band, Shahab S. & Reuter, Uwe & Gama, Joao & Gandomi, Amir H., 2020. "Data science in economics: comprehensive review of advanced machine learning and deep learning methods," LawArXiv kczj5, Center for Open Science.
    24. Philipp Lorenz-Spreen & Stephan Lewandowsky & Cass R. Sunstein & Ralph Hertwig, 2020. "How behavioural sciences can promote truth, autonomy and democratic discourse online," Nature Human Behaviour, Nature, vol. 4(11), pages 1102-1109, November.
    25. Nosratabadi, Saeed & Mosavi, Amir & Duan, Puhong & Ghamisi, Pedram & Filip, Ferdinand & Band, Shahab S. & Reuter, Uwe & Gama, Joao & Gandomi, Amir H., 2020. "Data science in economics: comprehensive review of advanced machine learning and deep learning methods," SocArXiv 9vdwf, Center for Open Science.
    26. Alfani, Guido, 2015. "Economic Inequality in Northwestern Italy: A Long-Term View (Fourteenth to Eighteenth Centuries)," The Journal of Economic History, Cambridge University Press, vol. 75(4), pages 1058-1096, December.
    27. Luoma, Jukka, 2016. "Model-based organizational decision making: A behavioral lens," European Journal of Operational Research, Elsevier, vol. 249(3), pages 816-826.
    28. Eichacker, Nina, 2015. "Financial liberalization and the onset of financial crisis in Western European states between 1983 and 2011: An econometric investigation," The North American Journal of Economics and Finance, Elsevier, vol. 34(C), pages 323-343.
    29. Josefina Fernandez-Guadaño & Manuel Lopez-Millan & Jesús Sarria-Pedroza, 2020. "Cooperative Entrepreneurship Model for Sustainable Development," Sustainability, MDPI, vol. 12(13), pages 1-11, July.
    30. Manuel Woschank & Erwin Rauch & Helmut Zsifkovits, 2020. "A Review of Further Directions for Artificial Intelligence, Machine Learning, and Deep Learning in Smart Logistics," Sustainability, MDPI, vol. 12(9), pages 1-23, May.
    31. Nosratabadi, Saeed & Mosavi, Amir & Duan, Puhong & Ghamisi, Pedram & Filip, Ferdinand & Band, Shahab S. & Reuter, Uwe & Gama, Joao & Gandomi, Amir H., 2020. "Data science in economics: comprehensive review of advanced machine learning and deep learning methods," OSF Preprints yc6e2, Center for Open Science.
    32. Ehsan Samiei & Jafar Habibi, 2020. "The Mutual Relation Between Enterprise Resource Planning and Knowledge Management: A Review," Global Journal of Flexible Systems Management, Springer;Global Institute of Flexible Systems Management, vol. 21(1), pages 53-66, March.
    33. Nosratabadi, Saeed & Mosavi, Amir & Duan, Puhong & Ghamisi, Pedram & Filip, Ferdinand & Band, Shahab S. & Reuter, Uwe & Gama, Joao & Gandomi, Amir H., 2020. "Data science in economics: comprehensive review of advanced machine learning and deep learning methods," Thesis Commons auyvc, Center for Open Science.
    34. Lilas Demmou & Irina Stefanescu & Axelle Arquie, 2019. "Productivity growth and finance: The role of intangible assets - a sector level analysis," OECD Economics Department Working Papers 1547, OECD Publishing.
    35. Nosratabadi, Saeed & Mosavi, Amir & Duan, Puhong & Ghamisi, Pedram & Filip, Ferdinand & Band, Shahab S. & Reuter, Uwe & Gama, Joao & Gandomi, Amir H., 2020. "Data science in economics: comprehensive review of advanced machine learning and deep learning methods," EdArXiv 5dwrt, Center for Open Science.
    36. Samuele Lo Piano, 2020. "Ethical principles in machine learning and artificial intelligence: cases from the field and possible ways forward," Palgrave Communications, Palgrave Macmillan, vol. 7(1), pages 1-7, December.
    37. Lara Agostini & Anna Nosella & Roberto Filippini, 2017. "Ambidextrous organisation and knowledge exploration and exploitation: the mediating role of internal networking," International Journal of Business Innovation and Research, Inderscience Enterprises Ltd, vol. 14(1), pages 122-138.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Koc, Kerim & Ekmekcioğlu, Ömer & Işık, Zeynep, 2023. "Developing a probabilistic decision-making model for reinforced sustainable supplier selection," International Journal of Production Economics, Elsevier, vol. 259(C).
    2. Gopalakrishnan Sriraman & Shriram Raghunathan, 2023. "A Systems Thinking Approach to Improve Sustainability in Software Engineering—A Grounded Capability Maturity Framework," Sustainability, MDPI, vol. 15(11), pages 1-16, May.
    3. Hanlie Smuts & Alta Van der Merwe, 2022. "Knowledge Management in Society 5.0: A Sustainability Perspective," Sustainability, MDPI, vol. 14(11), pages 1-27, June.
    4. Meir Russ, 2021. "The Individual and the Organizational Model of Quantum Decision-Making and Learning: An Introduction and the Application of the Quadruple Loop Learning," Merits, MDPI, vol. 1(1), pages 1-13, June.
    5. Meir Russ, 2022. "Knowledge Sharing and Sustainable Development," Sustainability, MDPI, vol. 14(5), pages 1-3, March.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Yong-Chao Su & Cheng-Yu Wu & Cheng-Hong Yang & Bo-Sheng Li & Sin-Hua Moi & Yu-Da Lin, 2021. "Machine Learning Data Imputation and Prediction of Foraging Group Size in a Kleptoparasitic Spider," Mathematics, MDPI, vol. 9(4), pages 1-16, February.
    2. Mei-Li Shen & Cheng-Feng Lee & Hsiou-Hsiang Liu & Po-Yin Chang & Cheng-Hong Yang, 2021. "An Effective Hybrid Approach for Forecasting Currency Exchange Rates," Sustainability, MDPI, vol. 13(5), pages 1-29, March.
    3. Urko Aguirre-Larracoechea & Cruz E. Borges, 2021. "Imputation for Repeated Bounded Outcome Data: Statistical and Machine-Learning Approaches," Mathematics, MDPI, vol. 9(17), pages 1-27, August.
    4. Marcus Vinicius Santos & Fernando Morgado-Dias & Thiago C. Silva, 2023. "Oil Sector and Sentiment Analysis—A Review," Energies, MDPI, vol. 16(12), pages 1-29, June.
    5. ErLe Du & Meng Ji, 2021. "Analyzing the regional economic changes in a high-tech industrial development zone using machine learning algorithms," PLOS ONE, Public Library of Science, vol. 16(6), pages 1-18, June.
    6. David G. Green, 2023. "Emergence in complex networks of simple agents," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 18(3), pages 419-462, July.
    7. Lin, Yong & Wang, Renyu & Gong, Xingyue & Jia, Guozhu, 2022. "Cross-correlation and forecast impact of public attention on USD/CNY exchange rate: Evidence from Baidu Index," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 604(C).
    8. Steve J. Bickley & Benno Torgler, 2021. "Behavioural Economics, What Have we Missed? Exploring “Classical” Behavioural Economics Roots in AI, Cognitive Psychology, and Complexity Theory," CREMA Working Paper Series 2021-21, Center for Research in Economics, Management and the Arts (CREMA).
    9. Oliver Hümbelin & Lukas Hobi & Robert Fluder, 2021. "Rich Cities, Poor Countryside? Social Structure of the Poor and Poverty Risks in Urban and Rural Places in an Affluent Country. An Administrative Data based Analysis using Random Forest," University of Bern Social Sciences Working Papers 40, University of Bern, Department of Social Sciences, revised 10 Nov 2021.
    10. Petr Suler & Zuzana Rowland & Tomas Krulicky, 2021. "Evaluation of the Accuracy of Machine Learning Predictions of the Czech Republic’s Exports to the China," JRFM, MDPI, vol. 14(2), pages 1-30, February.
    11. Saeed Nosratabadi & Nesrine Khazami & Marwa Ben Abdallah & Zoltan Lackner & Shahab S. Band & Amir Mosavi & Csaba Mako, 2020. "Social Capital Contributions to Food Security: A Comprehensive Literature Review," Papers 2012.03606, arXiv.org.
    12. Cheng Zhang & Nilam Nur Amir Sjarif & Roslina Ibrahim, 2023. "Deep learning models for price forecasting of financial time series: A review of recent advancements: 2020-2022," Papers 2305.04811, arXiv.org, revised Sep 2023.
    13. Xiaodong Zhang & Suhui Liu & Xin Zheng, 2021. "Stock Price Movement Prediction Based on a Deep Factorization Machine and the Attention Mechanism," Mathematics, MDPI, vol. 9(8), pages 1-21, April.
    14. Teddy Lazebnik & Tzach Fleischer & Amit Yaniv-Rosenfeld, 2023. "Benchmarking Biologically-Inspired Automatic Machine Learning for Economic Tasks," Sustainability, MDPI, vol. 15(14), pages 1-9, July.
    15. Amir Masoud Rahmani & Efat Yousefpoor & Mohammad Sadegh Yousefpoor & Zahid Mehmood & Amir Haider & Mehdi Hosseinzadeh & Rizwan Ali Naqvi, 2021. "Machine Learning (ML) in Medicine: Review, Applications, and Challenges," Mathematics, MDPI, vol. 9(22), pages 1-52, November.
    16. Ren, Yi-Shuai & Ma, Chao-Qun & Kong, Xiao-Lin & Baltas, Konstantinos & Zureigat, Qasim, 2022. "Past, present, and future of the application of machine learning in cryptocurrency research," Research in International Business and Finance, Elsevier, vol. 63(C).
    17. Di Wu & Zhenning Xu & Seung Bach, 2023. "Using Google Trends to predict and forecast avocado sales," Journal of Marketing Analytics, Palgrave Macmillan, vol. 11(4), pages 629-641, December.
    18. Liang She & Jianyuan Wang & Yifan Bo & Yangyan Zeng, 2022. "MACA: Multi-Agent with Credit Assignment for Computation Offloading in Smart Parks Monitoring," Mathematics, MDPI, vol. 10(23), pages 1-18, December.
    19. Angelos A. Antzoulatos & Dimitris Karanastasis & Thomas Syrmos, 2022. "The Puzzling Convergence of Intangible Investments," International Advances in Economic Research, Springer;International Atlantic Economic Society, vol. 28(3), pages 171-182, November.
    20. Martin Fleming, 2021. "Productivity Growth and Capital Deepening in the Fourth Industrial Revolution," Working Papers 010, The Productivity Institute.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:13:y:2021:i:6:p:3353-:d:519627. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.