Integrating Big Data Analytics, Systems Thinking and Viable Systems Approach Towards a Shift from Individual to Collective Intelligence and Collective Knowledge Systems


  • Stefano Armenia Link Campus University
  • Francesca Loia University of Naples Federico II



Big Data, Systems Thinking, Collective Knowledge Systems, Viable System Approach


Purpose – The growing complexity of social systems and the faster technology evolution make central the role of the innovative information technology in complex organisations, geared towards collective intelligence processes among the various social actors and analytical tools. These are able to foster the participant knowledge, manage the feedback through a holistic approach and hence shift organisations from a plurality of voices to an interactive intelligence representing the ultimate identity of the organisation itself. In this regard, the aim of this paper is to offer a model for managing external and internal knowledge in order to support the viability of the organisation (system) in the longer term.

Design/methodology/approach – The paper adopts the interpretative lens provided by Systems Thinking, System Dynamics and Viable System Approach (vSa) to investigate the challenging domain of the knowledge and information management for complex systems as organisations. Therefore, a qualitative and interpretative approach is carried out to reflect upon Big Data approaches and Collective Knowledge Systems (CKS), embracing a system perspective.

Findings – The proposed conceptual model shows the crucial role covered by the holistic managing of the external and internal knowledge that permits to align the information variety of the organisation to the context and the entities that compose it in order to create harmonic relations. Leveraging on the concepts of vicariance, bricolage and exaptation, several advantages emerge that are correlated to the capacity of the complex system to reach a greater level of survival, by adapting and dynamically evolving itself.

Originality/value – The paper shows how Systems Thinking and Viable System Approach can provide deep insights into the field of information technology, evidencing the systems thinking contribution in analysing, understanding and managing dimensions and paths of social dynamics. A contribution to previous studies is provided with reference to themes as Big Data, information and knowledge management.


Alag, S. (2008), Collective Intelligence in Action, New York (NY): Manning.

Alavi, M., and Leidner, D.E. (2001), “Review: Knowledge Management and Knowledge Management Systems: Conceptual Foundations and Research Issues”, MIS Quarterly, 25 (1): 107–136.

Allee, V. (1997), The Knowledge Evolution, Oxford: Butterworth-Heinemann.

Armenia, S., Carlini, C., Onori, R., and Saullo, A.P. (2013), “Policy Modeling as a New Area for Research: Perspectives for a Systems Thinking and System Dynamics Approach?”, in Proceedings of the 13th European Academy of Management (EURAM) Conference, Istanbul, Turkey: EURAM 2013.

Armenia, S., Ferreira Franco, E., Mecella, M., and Onori, R. (2017), “Smart Model-Based Governance: From Big-Data to Future Policy Making”, in F. Nonino, S. Armenia and G. Dominici (eds), Model-based Governance for Smart Organizational Future: BSLab-SYDIC International Workshop, Rome, January 23-24 (Book of Abstract), 44–53. Available online at (last accessed: November 12, 2020).

Ashby, W.R. (1991), “Requisite Variety and Its Implications for the Control of Complex Systems”, in G.J. Klir (ed.), Facets of Systems Science, 405–417, Boston, MA: Springer. DOI: 10.1007/978-1-4899-0718-9_28.

Ashton, K. (2009), “That ‘Internet of Things’ Thing”, Radio Frequency Identification (RFID) Journal, 22 (7): 97–114.

Barile, S., and Calabrese, M. (2011), “Business Design and Context Consonance (Business Design e Consonanza di Contesto)”, Social Science Research Network (SSRN) Electronic Journal, 1–26. DOI: 10.2139/ssrn.2053618.

Barile, S., and Polese, F. (2010), “Linking the Viable System and Many-to-Many Network Approaches to Service-Dominant Logic and Service Science”, International Journal of Quality and Service Sciences, 2 (1): 23–42.

Barile, S., and Saviano, M. (2008), “Le Basi del Pensiero Sistemico: La Dicotomia Struttura-Sistema”, in S. Barile (ed.), L’Impresa come Sistema: Contributi sull’Approccio Sistemico Vitale (ASV), 63–81, Torino: Giappichelli.

Barile, S., and Saviano, M. (2011), “Foundations of Systems Thinking: The Structure-System Paradigm”, in S. Barile et al. (eds), Contributions to Theoretical and Practical Advances in Management: A Viable Systems Approach (VSA), 1-25, Avellino: International Printing Srl Editore.

Barile, S., and Saviano, M. (2018), “Complexity and Sustainability in Management: Insights from a Systems Perspective”, in

S. Barile, M. Pellicano and F. Polese (eds), Social Dynamics in a Systems Perspective, 39–63, Cham, Switzerland: Springer.

Barile, S., Saviano, M., and Polese, F. (2014), “Information Asymmetry and Co-Creation in Health Care Services”, Australasian Marketing Journal (AMJ), 22 (3): 205–217.

Barile, S., Fulco, I., Loia, F., and Vito, P. (2018), “Un Modello di Supporto alle Decisioni Territoriali tra Analisi dei ‘Sentiment’ e Consonanza Sistemica”, in C. Baccarani et al. (eds), Transformative Business Strategies and New Patterns for Value Creation: Referred Electronic Conference Proceedings, 257–273. Available online at (last accessed: November 12, 2020).

Barile, S., Saviano, M., Polese, F., and Di Nauta, P. (2012), “Il Rapporto Impresa-Territorio tra Efficienza Locale, Efficacia di Contesto e Sostenibilità Ambientale (The Firm-Territory Relationship between Local Efficiency, Context Effectiveness and Environmental Sustainability)”, in S. Barile, S., Saviano, M, Polese, F., Di Nauta, P. (2012), “Il Rapporto Impresa-Territorio tra Efficienza Locale, Efficacia di Contesto e Sostenibilità Ambientale”, in Referred Electronic Conference Proceeding Convegno Sinergie “Il Territorio come Giacimento di Vitalità per l’Impresa, 387–402.

Begoli, E., and Horey, J. (2012), “Design Principles for Effective Knowledge Discovery from Big Data”, 2012 Joint Working IEEE/IFIP Conference on Software Architecture and European Conference on Software Architecture, Helsinki, 2012, 215–218. DOI: 10.1109/WICSA-ECSA.212.32.

Berthoz, A. (2013), La Vicariance: Le Cerveau Créateur de Mondes, Paris: Odile Jacob.

Beyer, M.A., and Laney, D. (2012), The Importance of “Big Data”: A Definition, Stamford, CT: Gartner.

Calabrese, M., Iandolo, F., and Bilotta, A. (2011), “From Requisite Variety to Information Variety through the Information Theory the Management of Viable Systems”, in E. Gummesson, C. Mele and F. Polese (eds), Service Dominant Logic, Network & Systems Theory and Service Science: Integrating Three Perspectives for a New Service Agenda, Online

Proceedings of the 2011 Naples Forum on Service, Naples: Giannini.

Chen, C.P., and Zhang, C.Y. (2014), “Data-Intensive Applications, Challenges, Techniques and Technologies: A Survey on Big Data”, Information Sciences, 275: 314–347. DOI: 10.1016/j.ins.2014.01.015.

Chen, H., Chiang, R.H., and Storey, V.C. (2012), “Business Intelligence and Analytics: From Big Data to Big Impact”, Management Information Systems (MIS) Quarterly, 36 (4): 1165–1188.

Ciasullo, M.V., Troisi, O., Loia, F., and Maione, G. (2018), “Carpooling: Travelers’ Perceptions from a Big Data Analysis”, The TQM Journal, 30 (5): 554–571. DOI: 10.1108/TQM-11-2017-0156.

Cohen, N.J., Eichenbaum, H., Deacedo, B.S., and Corkin, S. (1985), “Different Memory Systems Underlying Acquisition of Procedural and Declarative Knowledge”, Annals of the New York Academy of Sciences, 444 (1): 54–71.

Coyle, K (2006), “Mass Digitization of Books”, The Journal of Academic Librarianship, 32 (6): 641–645.

Cricelli, L., and Grimaldi, M. (2008), “A Dynamic View of Knowledge and Information: A Stock and Flow Based Methodology”, International Journal of Management and Decision Making, 9 (6): 686–698.

Cyert, R.M., and March, J.G. (1963), A Behavioral Theory of the Firm, Englewood Cliffs, NJ: Prentice-Hall.

De Jarnett, L. (1996), “Knowledge the Latest Thing: Information Strategy”, The Executives Journal, 12 (2): 3–5.

Dominici, G., Roblek, V., and Lombardi, R. (2016), “A Holistic Approach to Comprehending the Complexity of the Post-Growth Era: The Emerging Profile”, in Ş.Ş. Erçetin (ed.), Chaos, Complexity and Leadership 2014, 29–42, Cham, Switzerland: Springer.

Dooley, K.J. (1997), “A Complex Adaptive Systems Model of Organization Change”, Nonlinear Dynamics, Psychology, and Life Sciences, 1 (1): 69–97.

Drucker, P.F. (1995), “The New Productivity Challenge”, Quality in Higher Education, 37: 45–53.

Fan, W., and Bifet, A. (2013), “Mining Big Data: Current Status, and Forecast to the Future”, ACM sIGKDD Explorations Newsletter, 14 (2): 1–5.

Forrester, J.W. (1961), Industrial Dynamics, New York/London: Massachusetts Institute of Technology and Jon Wiley and Sons.

Forrester, J.W. (1994), “System Dynamics, Systems Thinking, and Soft OR”, System Dynamics Review, 10 (2‐3): 245–256.

Frakes, W.B., and Baeza-Yates, R. (eds) (1992), Information Retrieval: Data Structures & Algorithms, Englewood Cliffs, NJ: Prentice Hall.

Gaeta, M., Loia, F., Sarno, D., and Carrubbo, L. (2019), “Online Social Network Viability: Misinformation Management Based on Service and Systems Theories”, International Journal of Business and Management, 1 (1): 17–35. DOI: 10.5539/ijbm.v14n1p17.

Golinelli, G.M. (2010), Viable Systems Approach (VSA): Governing Business Dynamics, Padua: CEDAM.

Gould, S.J., and Vrba, E.S. (1982), “Exaptation: A Missing Term in the Science of Form”, Paleobiology, 8 (1): 4–15.

Gruber, T. (2008), “Collective Knowledge Systems: Where the Social Web Meets the Semantic Web”, Web Semantics: Science, Services and Agents on the World Wide Web, 6 (1): 4–13.

Gummesson, E. (2008), “Extending the Service-Dominant Logic: From Customer Centricity to Balanced Centricity”, Journal of the Academy of Marketing Science, 36 (1): 15–17.

Gummesson, E., and Mele, C. (2010), “Marketing as Value Co-Creation through Network Interaction and Resource Integration”, Journal of Business Market Management, 4 (4): 181–198.

Holland, J.H. (1995), Hidden Order: How Adaptation Builds Complexity, New York, NY: Addison-Wesley.

Holling, C.S. (1996), “Engineering Resilience versus Ecological Resilience”, in National Academy of Engineering (ed.), Engineering Within Ecological Constraints, 31–44, Washington, DC: The National Academies Press. DOI: 10.17226/4919.

Holling, C.S., and Gunderson, L.H. (2002), “Resilience and Adaptive Cycles”, in L.H. Gunderson (ed.), Panarchy: Understanding Transformations in Human and Natural Systems, 25–62, Washington, DC: Island Press.

Iandolo, F., Barile, S., Armenia, S., and Carrubbo, L. (2018), “A System Dynamics Perspective on a Viable Systems Approach Definition for Sustainable Value”, Sustainability Science, 13: 1245–1263. DOI: 10.1007/s11625-018-0565-2.

Janssen, M., van der Voort, H., and Wahyudi, A. (2017), “Factors Influencing Big Data Decision-Making Quality”, Journal of Business Research, 70: 338–345.

Johnson, J.E. (2012), “Big Data + Big Analytics = Big Opportunity”, The Financial Executive, 28 (6): 50–54.

Lam, A. (2000), “Tacit Knowledge, Organizational Learning and Societal Institutions: An Integrated Framework”, Organization Studies, 21 (3): 487–513.

Laudon, K.C., and Laudon, J.P. (1999), Management Information Systems, Upper Saddle River, NJ: Prentice Hall.

Laudon, K.C., and Laudon, J.P. (2011), Essentials of Management Information Systems, Upper Saddle River, NJ: Pearson.

LaValle, S., Hopkins, M.S., Lesser, E., Shockley, R., and Kruschwitz, N. (2010), “Analytics: The New Path to Value”, MIT Sloan Management Review, 52 (1): 1–25.

Levin, S.A. (1998), “Ecosystems and the Biosphere as Complex Adaptive Systems”, Ecosystems, 1 (5): 431–436.

Lévi-Strauss, C. (1962), La Pensée Sauvage (Vol. 289), Paris: Plon.

Lévy, P., and Bononno, R. (1997), Collective Intelligence: Mankind’s Emerging World in Cyberspace, New York, NY: Perseus Books.

Liew, A. (2007), “Understanding Data, Information, Knowledge and Their Inter-Relationships”, Journal of Knowledge Management Practice, 8 (2): 1–16.

Lincoln, Y.S., and Denzin, N.K. (1994), “The Fifth Moment”, in N.K. Denzin and Y.S. Lincoln (eds), The Handbook of Qualitative Research (1st edn.), 575–586, Thousand Oaks, CA: SAGE.

Malone, T.W., Laubacher, R., and Dellarocas, C. (2010), “The Collective Intelligence Genome”, MIT Sloan Management Review, 51 (3): 21–31.

McAdam, R., and McCreedy, S. (1999), “A Critical Review of Knowledge Management Models”, The Learning Organization, 6 (3): 91–101.

McAfee, A., and Brynjolfsson E. (2012), “Big Data: The Management Revolution”, Harvard Business Review, 90 (10): 60–68.

Meadows, D.H. (2008), Thinking in Systems: A Primer, London: Chelsea Green Publishing.

Miller, H.G., and Mork, P. (2013), “From Data to Decisions: A Value Chain for Big Data”, It Professional, 1: 57–59.

Mirchi, A., Madani, K., Watkins, D., and Ahmad, S. (2012), “Synthesis of System Dynamics Tools for Holistic Conceptualization of Water Resources Problems”, Water Resources Management, 26 (9): 2421–2442.

Morecroft, J.D. (1983), “System Dynamics: Portraying Bounded Rationality”, Omega, 11 (2): 131–142.

Nickols, F. (2000), “The Knowledge in Knowledge Management”, in J.W. Cortada and J.A. Woods (eds), The Knowledge Management Yearbook 2000-2001, 12–21, Oxford: Butterworth-Heinemann.

Nonaka, I., and Takeuchi, H. (1995), The Knowledge-Creating Company: How Japanese Companies Create the Dynamics of Innovation, Oxford: Oxford University Press.

O’Connor, J., and McDermott, I. (1997), The Art of Systems Thinking, San Francisco, CA: Thorsons.

Polese, F., Mele, C., and Gummesson, E. (2017), “Value Co-Creation as a Complex Adaptive Process”, Journal of Service Theory and Practice, 27 (5): 926–929.

Powell, W.W., and Snellman, K. (2004), “The Knowledge Economy”, Annual Review of Sociology, 30: 199–220. DOI: 10.1146/annurev.soc.29.010202.

Prescott, E.M. (2014), “Big Data and Competitive Advantage at Nielsen”, Management Decision, 52 (3): 573–601.

Reuchlin, M. (1978), “Processus Vicariants et Différences Individuelles”, Journal de Psychologie, 75: 133–145.

Rowley, J. (2007), “The Wisdom Hierarchy: Representations of the DIKW Hierarchy”, Journal of Information Science, 33 (2): 163–180.

Rubenstein-Montano, B., Liebowitz, J., Buchwalter, J., McCaw, D., Newman, B., Rebeck, K., and Team, T.K.M.M. (2001), “A Systems Thinking Framework for Knowledge Management”, Decision Support Systems, 31 (1): 5–16.

Senge, P. (1990), The Fifth Discipline, New York, NY: Currency Doubleday.

Simon, H.A. (1955), “A Behavioral Model of Rational Choice”, The Quarterly Journal of Economics, 69 (1): 99–118.

Stacey, R. (2003), Complex Responsive Processes in Organizations: Learning and Knowledge Creation, London: Routledge.

Sterman, J.D. (1994), “Learning in and about Complex Systems”, System Dynamics Review, 10 (2‐3): 291–330.

Sterman, J.D. (2000), Business Dynamics: Systems Thinking and Modeling for a Complex World, Boston, MA: Irwin/McGraw-Hill.

Sterman, J.D. (2001), “System Dynamics Modeling: Tools for Learning in a Complex World”, California Management Review, 43 (4): 8–25.

Sterman, J.D. (2012), “Sustaining Sustainability: Creating a Systems Science in a Fragmented Academy and Polarized World”, in M. Weinstein and R. Turner (eds), Sustainability Science, 21–58, New York, NY: Springer. DOI: 10.1007/978-1-4614-3188-6_2.

Svyantek, D.J., and Brown, L.L. (2000), “A Complex-Systems Approach to Organizations”, Current Directions in Psychological Science, 9 (2): 69–74.

Ten Berge, T., and Van Hezewijk, R. (1999), “Procedural and Declarative Knowledge: An Evolutionary Perspective”, Theory & Psychology, 9 (5): 605–624.

Troisi, O., D’Arco, M., Loia, F., and Maione, G. (2018), “Big Data Management: The Case of Mulino Bianco’s Engagement Platform for Value Co-Creation”, International Journal of Engineering Business Management, 10: 1–8. DOI: 10.1177/1847979018767776.

Uddin, M.F., and Gupta, N. (2014), “Seven V’s of Big Data: Understanding Big Data to Extract Value”, in Proceedings of the 2014 Zone 1 Conference of the American Society for Engineering Education, Bridgeport, CT, 1–5. DOI: 10.1109/ASEEZone1.2014.6820689.

von Bertalanffy, L. (1952), Problems of Life: An Evaluation of Modern Biological Thought, New York, NY: Wiley & Sons.

von Bertalanffy, L. (1956), “A Biologist Looks at Human Nature”, The Scientific Monthly, 82 (1): 33–41.

von Bertalanffy, L. (1967), “General Theory of Systems: Application to Psychology”, Social Science Information, 6 (6): 125–136. DOI: 10.1177/053901846700600610.

Wise, S., Paton, R.A., and Gegenhuber, T. (2012), “Value Co-Creation through Collective Intelligence in the Public Sector: A Review of US and European Initiatives”, Vine, 42 (2): 251–276.

Wu, X., Zhu, X., Wu, G.Q., and Ding, W. (2014), “Data Mining with Big Data”, IEEE Transactions on Knowledge and Data Engineering, 26 (1): 97–107.

Wu, J., Dai, L., Chiclana, F., Fujita, H., and Herrera-Viedma, E. (2018), “A Minimum Adjustment Cost Feedback Mechanism-Based Consensus Model for Group Decision Making under Social Network with Distributed Linguistic Trust”, Information Fusion, 41: 232–242.

Yolles, M. (2000), “Organisations, Complexity, and Viable Knowledge Management”, Kybernetes, 29 (9-10): 1202–1222.

Yolles, M. (ed.) (2006), Organizations as Complex Systems: An Introduction to Knowledge Cybernetics, Greenwich, CT: Information Age Publishing.

Zaslavsky, A., Perera, C., and Georgakopoulos, D. (2013), “Sensing as a Service and Big Data”, in Proceedings of the International Conference on Advances in Cloud Computing (ACC), Bangalore, India, arXiv:1301.0159.

Zikopoulos, P., and Eaton, C. (2011), Understanding Big Data: Analytics for Enterprise Class Hadoop and Streaming Data, New York, NY: McGraw-Hill Osborne Media.


How to Cite

Armenia, S., & Loia, F. Integrating Big Data Analytics, Systems Thinking and Viable Systems Approach Towards a Shift from Individual to Collective Intelligence and Collective Knowledge Systems. PuntOorg International Journal.