Summary
This article identifies the theoretical and methodological foundations of knowl-edge creation in cyberspace. It points to the relations between the dynamics of digi-tal sphere and the occurrences of learning, unlearning, and collective mind. A vir-tual community is classified among complex adaptive systems which are character-ized by emergence – the capability to produce certain patterns of collective behavior. One of the best practical examples of these phenomena is the behavior of virtual communities of traders and investors acting on electronic and virtual capital markets in cyberspace.
Key words: cyberspace, system dynamics, complex adaptive system, virtual community, capital markets
1. Introduction
Cyberspace is usually associated with technological aspects, i.e., the Internet, World Wide Web plus mobile devices spreading around. Less known are social and psychological aspects of this digital sphere, although with the birth of Web 2.0 in 2004, everything seems to have turned “social”: social computing, social software, social search, collaborative tagging, socialization, to name but a few. And most of all, harnessing collective intelligence, as a leading call and catch-phrase of the second incarnation of WWW.
This article attempts to reveal the theoretical and methodological foundations of knowledge creation in cyberspace. This topic is still new and pretty much neglected, as all the interests in this area seem to have concentrated on business strategies and practical applications, especially in the software domain. Understanding the basic theoretical framework in this area, however, should be first and foremost, to be able to achieve the best results managing information in cyberspace. Phenomena such as the dynamics of cyberspace, collective knowledge, network effect, complex adaptive system, and virtual community – all have a very clear and visible common denominator, which ought to be revealed and applied in practice. Because of the theoretical, and hence histori-cal, connotations some sources cited in this article date back to the Web 2.0, and even pre-Internet era.
2. Knowledge and the Dynamics of Cyberspace
The basic phenomenon linking cyberspace with the virtual community immersed within is the dynamics of this digital sphere. Dynamics (Lat. dynamikos) pertains to “the motivating or driving forces, physical or moral, in any field” (Webster 2010). The dynamics of an Information System (IS) is a derivative of the processes occurring in its social subsystem (Unold 2010). Analogically, the dynamics of cyberspace results from the information processes generated by countless virtual communities, as well as individual cybernauts. Such defined dynamics reflects changes in
knowl-edge stocks and represents the processes of learning and unlearning (Eden and Spender 1998, p. 15). It follows that even though cyberspace is defined as a global electro-magnetic space accessi-ble via modern information technology, in a social approach it is a net of relations among indi-viduals, serving the exchange of information, which is emphasized by, inter alia, A. Barak (2008) in “Psychological Aspects of Cyberspace” or M. Smith (2007) in “Communities in Cyberspace”.
In this approach the basic concepts and determinants of the discussed phenomenon are knowl-edge, learning and unlearning. Collective knowledge cannot be understood without embracing and understanding the mutual relations and processes among the members of a given collectivity (Weick and Roberts 1993, p. 358). It means that collective information processes determine the dynamics of a system, and a special category of those processes are learning and unlearning.
Next, organizational learning is a metaphor pointing to the way an organization adapts to the constantly changing conditions of its environment. Organizational learning takes place when knowledge, acquired and developed by the individual members, is deposited in organizational memory. The basic features of this phenomenon, according to Probst and Buechel (1997) are:
• changes in organizational knowledge,
• increase of the potential organizational activities, • changes in the perception of the surrounding reality.
The most effective process of organizational learning occurs in so called “double loop.” The first stage is adaptation, based on learning within the former set of structures and values. The second stage of double loop is the actual learning, which results in the change of existing struc-tures and values (Argyris 2006).
Methodologically, the process of organizational learning can be identified on four levels: indi-vidual, group, organization and collectivity within and organization (Miner and Mezias 1996). S. Cook and D. Yanow (1993, p. 27) introduced a cultural perspective of this notion. Organizational learning is “acquiring, sustaining and changing commonly understood meanings throughout (…) collective actions”. This depiction refers to the universal definition of “dynamics, where the main subject is capability of action. Collective actions are therefore the next determinant of the dynam-ics of cyberspace.
Widely conducted empirical studies in such important corporations as Motorola Company or Fiat Auto Company (Nevis et al. 1995) confirmed that:
• all organizations are learning systems,
• learning process is compatible with organizational culture, • learning systems differ.
The dynamics of cyberspace, understood as a classic capability of action, refers to the activity of a system. This activity is sometimes called in literature “activity system.” The notion of activity system, combined with the notion of organizational culture, points to the next determinant of the dynamics of such a specific system as cyberspace. This phenomenon is called “collective mind.” The very existence of collective mind can only be identified within an activity system, and for many scholars the notions of organizational culture and collective mind are identical (e.g., Eden and Spender 1998, p. 15).
Already in 1895 G. Le Bon in his classic “The Crowd: A Study of the Popular Mind” pro-posed a thesis that collectivity is first and foremost a psychological phenomenon (Le Bon 2008). Any number of independent, and even separated in space, individuals can form a collectivity if united by a common cause. This common cause exerts pressure on each individual. According to Le Bon, “by forming a collectivity individuals posses something resembling a collective soul. This
soul makes them think, feel, and act differently than when they thought, felt and acted independ-ently. (…) Because of this a crowd is not a sum or a mean of its components, but a totally new substance is created, characterized by a totally different set of properties” (p. 51).
In the 1950s H. Simon explicitly permitted the existence of “collective mind.” Each subject, individual or collective, which has the potential of processing information, possesses a mind (Simon 1997). The most recent research shows that a living organism does not even need a brain to behave intelligently. Intelligence is a property arising from an adequate level of systemic organiza-tion, which allows a system to process information (Wheatley 2006, p. 98).
The concept of collective mind allows for the introduction of the notion of organizational in-telligence. Such defined intelligence does not depend on individual managers or experts. It is a system property which depends upon the level of system openness and its ability to acquire new information and adapt to it.
Moreover, the concept of collective mind introduces a crucial qualitative dimension into the theory of organization. It adds a missing social component to a strictly mechanistic approach characterizing the classic theory of organization. It is usually assumed in the literature that the notion of collective mind should refer to methodology and practical applications, rather than to theory and abstract knowledge, which is the domain of individuals and not groups.
3. Virtual Community as a Complex Adaptive System
It is important, from a methodological perspective of this analysis, to list the basic organiza-tional forms. The contemporary literature identifies the following structures (e.g., Turniansky and Hare, 1998, p. 101):
• bureaucratic organization,
• interactive post-bureaucratic organization, • team-based organization,
•
self-organization.
The technological and social circumstances unknown before – virtualization, digitization and globalization – brought about new projections as early as the beginning of the 1990s. The authors stressed the need for the evolution of teams toward self-regulating organizations. Discussing the properties of a complex adaptive system, Shipper and Mantz (1992, p. 48) noticed that:
• such a system consists of a network of agents acting independently without a central su-pervision,
• the working environment of those agents changes constantly because this environment is defined by a continuous stream of interactions among them,
• organized patterns of behavior are the result of simultaneous competition and cooperation among the agents,
• organizational structures emerge naturally, as an effect of interactions and mutual de-pendencies.
Self-regulation cannot be planned or imposed but it is a natural feature of a system. When the system encounters new information it begins to reconfigure itself to adapt to this new situation. Such systems are resilient as opposed to stable ones. According to M. Wheatley (2006, p. 90), the vitality of a complex adaptive system arises from its inner potential which allows to create struc-tures most suitable for a given moment. Neither form nor function decide independently about its structure. Instead, both form and functions take part in a fluent process thanks to the system can
keep its current form or evolve toward a new order. Such a system has the capacity to spontane-ously create new structures, according to current needs. It is never blocked in any form but always open to organize information in the most suitable structure. The only condition for such an organi-zation to exist is a constant access to new information.
Another feature of a complex adaptive system is its self-reference, sometimes referred to as autopoiesis (Lat. self-production, auto-creation). Undergoing changes the system constantly refers to itself, whatever form emerges it is always compatible with the identity defined earlier. Besides, such a system is concentrated on keeping its own integrity and capacity to regeneration.
It is also worth mentioning that special complexity is one of the characteristics of a cybernetic system. The science which deals with it, complexity theory, is an interdisciplinary domain, em-bracing such diverse fields as ecology, theory of evolution, genetics, philosophy, game theory, linguistics, artificial intelligence, social sciences, computer science and economics. Contrary to traditional sciences, studying idealized phenomena, complexity theory examines phenomena occurring in the real world, i.e., turbulences and states of non-equilibrium, self-organization, adaptation, system learning. These are some of the non-linear behaviors, typical for dynamic systems (Battram 2002, p. v).
Complexity theory enables a new look at the issue of socio-economic systems behavior. It ap-pears that creative and adaptive actions emerge when agents cooperate independently in the system. However, in complex adaptive systems the elements of the system are not quite free but they are limited by certain relations. There exists a specific superior structure which can result in unpredictable behavior of the agents. This phenomenon was defined by S. Kauffman (2010) as “order for free”: „Contrary to popular belief, systems in total chaos can spontaneously crystallize at much higher levels of order.” In a social system, for example, even if individual actions are not coordinated, we can speak of an emergence of certain patterns of group behavior. Such an order is never imposed from above or from the outside but it arises naturally, during the cooperation of the system’s elements (agents). It became a basis for the doctrine of emergence, also referred to as creative evolution or holism. Generally speaking, this doctrine describes the hierarchical organiza-tion of things and processes, which allows for the occurrence of certain qualities at higher levels, and which cannot be identified at lower levels of organization.
The notion of emergence is used as a category useful to explain different social, economic, psychological and biological phenomena. It is important that the qualities of individual compo-nents are not subject to observation. They can be recognized only theoretically. In quantum phys-ics an adequate phenomenon is called relational holism, when complicated systems are built based on the relations among individual particles (Dudgeon, 2008). Matter has two dimensions, as if two identities. It can exist in the form of elementary particles, like specific points in space, or it can exist in the form of waves, like dispersed energy. This phenomenon is described by the principle of complementarity, which, by the way, carries a deep philosophical message: unity expressed as diversity (Cottle et al. 2009). Both aspects cannot be analyzed simultaneously, as in one entity. As a result, either a molecular or a wave aspect can be analyzed, never both at the same time.
These discoveries ultimately shattered the traditional concept, according to which people live and act as independent units. At the same time, they questioned the former assumptions about determinism, predictability and control. Similarly to the behavior of electrons, it is impossible to predict the behavior of an individual human being, whereas the behavior of a large group, either human beings or electrons, can be predicted with a very high accuracy.
the molecular level the observer cannot observe without actively interfering with the observed processes. According to K. Weick (2009, s. 168–169), a similar dependencies occur in the life of an organization. And so, there is no such thing as impartial, objective reality or objective judg-ment. The organizational features are being created by observation itself.
One of the best illustrations of this phenomenon, in reference to cyberspace, is the behavior of an individual investor, making decisions on an electronic and virtual stock market. Participating directly in the game and investing his or her own money such a trader is unable to objectively assess the real market situation. Only after withdrawing from the game can such a person be impartial and reasonable.
Complex adaptive systems are themselves components of the systems of higher degree of or-der. Those systems constantly evolve and never reach equilibrium. As a result, its agents can never optimize their effectiveness or utility. However, a complex adaptive system can create structures which are most suitable for current situation, so called process structures (Gibson, 2008). Such structures must posses certain qualities: clear sense of their won identity and potential for free actions. These qualities refer to autopoiesis, mentioned earlier. Very recently the concept of autopoiesis has been applied in the area of Information Systems (Beeson, 2001), and it should follow that it will find its use in cyberspace as well.
If Nature uses its laws to create diversity and organization, it is highly probable that those same rules should refer both to human life and to the life of human-made organizations. Many scholars try to adapt the experiences of ecology, physics or evolution theory to the sciences of organization and management, especially in the domain of learning and adaptation (e.g., (Wheatley 2006, s.158). As a result, there is a new alternative to the traditional mechanistic metaphor – a biological metaphor containing such ideas as networking, organism and ecosystem. Since the mid-1990s the idea of organic organization has been discussed, and most recently a conceptual model of ecosystem penetrated cyberspace (e.g., the mash-up ecosystem).
4. Collective Knowledge and Capital Markets in Cyberspace
Which leads us to the title research area of cyberspace. The ideas of complexity, self-organization and emergence can be fully utilize in describing the dynamics of individual and group behavior in cyberspace. One of the best examples of a virtual community in cyberspace is the community of investors at the modern, electronic capital market. This can be a local (national) stock market, as the still emerging Giełda Papierów Warto ciowych in Warsaw. Or, this can be a huge community of international, even global, investors engaged on Forex (Foreign Exchange) – a global currency market. Actually, Forex is the biggest market in the world, its daily volume exceeds 4.5 trillion US dollars. It is open 24/7 five days a week. Its biggest advantage is unlimited liquidity, which means that selling or buying any quantity of any currency in any moment is not a problem. Also, what is important for this analysis, Forex acts as a OTC (Over The Counter) market, which means it is decentralized, without a single controlling entity. Forex, thus, can be recognized as the most sophisticated variety of a modern Information System or the best developed IS category found in cyberspace. The virtual community of its investors is a typical example of a social subsystem within such IS.
What is crucial for a potential quantitative analysis in this domain, contrary to other collectiv-ities, the behavior of virtual investors on capital markets are reflected in relatively simple and concrete indicators. The price or index movements are represented graphically by charts, and other
indicators of collective activity, like volume (number of stocks changing hands).
Even though capital markets in different countries are distinguished by structure, legal regula-tions, etc., they posses certain common features. First of all, the community of investors is much larger and more difficult to grasp than the group of people conducting transactions at a given moment. Collectivities do not have to be specified groups of people. These are more phenomena of a psychological nature, which is especially visible at modern, electronic markets. Members of such groups are interconnected via different media: the Internet, TV, radio, telephones, which constitute the technological backbone of cyberspace. Besides, there are press commentaries and personal meetings, enriching such defined virtual collectivity. In this environment all pieces of information which can influence the prices diffuse instantly and investors sharing similar view split into two basic groups: bulls and bears. And so, after a devastating market crash in the summer of 1998, Alan Greenspan, Chairman of the US Federal Reserve came to the conclusion that markets are an expression of the deepest truths about human nature (Ramo 1999).
The basic subject of this game is an individual investor. Thousands of such transactions, inde-pendent and difficult to observe and analyze, very often irrational, cause the emergence of specific patterns of collective behavior. These phenomena are identified at a higher level of organization (collective, not individual), and their existence is proved by the existence of specific trends on the market: uptrend, downtrend or a horizontal trend. It follows that the collectivity of capital investors in cyberspace is a typical complex adaptive system. It is a system which:
• consists of individual traders acting without a centralized control;
• the working environment of those traders (agents) changes constantly because this envi-ronment is defined by a continuous stream of interactions among them,
• organized patterns of behavior are the result of simultaneous competition and cooperation among the traders,
• organizational structures emerge naturally, as an effect of interactions and mutual de-pendencies, and these structures can be represented by a current market trend.
5. Conclusions
The birth of Web 2.0 brought about “socialization” of practically all phenomena identified in cyberspace. It does not mean, however, any deeper interest in the theoretical foundations of these social occurrences. The prevailing body of specialized literature concentrates on “best practices,” “design patterns,” “business models,” and “strategies”, if we were to cite the subtitles of Web 2.0 works.
The key to understanding the processes of knowledge creation in cyberspace is the assumption that any virtual community constitutes a complex adaptive system, which consists of individual and independent “agents” on one hand, but on the other – revealing emergence of certain patterns of collective behavior. These phenomena are best exemplified by the group actions taken up by investors on capital markets in cyberspace: learning, unlearning and the almost “palpable” and visible creation of collective mind.
6. Literature
[1] Argyris C. (2006): Reasons and Rationalizations: The Limits to Organizational Knowledge. Oxford University Press.
[2] Barak A. (2008): Psychological Aspects of Cyberspace: Theory, Research, Applications. Cambridge University Press.
[3] Battram A. (2002): Navigating Complexity. The Essential Guide to Complexity Theory in Business and Management. Spiro Press.
[4] Beeson I. (2001): Implications of the Theory of Autopoiesis for the Discipline and Practice of Information Systems. W: “Realigning Research and Practice in Information Systems De-velopment: The Social and Organizational Perspective”, red. N. Russo i in. Kluwer Aca-demic Publishers, Boston.
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[9] Gibson J. (2008): Organizations: Behavior, Structure, Processes. McGraw-Hill/Irwin. [10] Kauffman S. (2010): Reinventing the Sacred: A New View of Science, Reason, and
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[20] Webster’s Online Dictionary, http://www.websters-online-dictionary.org, 14.04.2010.
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[23] Wheatley, M. (2006). Finding Our Way: Leadership for an Uncertain Time. San Francisco: Berrett-Koehler.
WIEDZA ZBIOROWA W WIETLE DYNAMIKI CYBERPRZESTRZENI Streszczenie
W artykule zidentyfikowano teoretyczno-metodologiczne podstawy kreacji wie-dzy w cyberprzestrzeni. Wskazano na zalenoci miwie-dzy dynamik cyberprzestrzeni a zjawiskami uczenia si, zapominania oraz tzw. umysłu zbiorowego. Społeczno wirtualn zakwalifikowano do kategorii złoonych systemów adaptacyjnych, które s charakteryzowane przez emergencj – zdolno wytwarzania specyficznych wzorców zachowa zbiorowych na wyszym poziomie uporzdkowania i organizacji. Dla ilu-stracji i egzemplifikacji omawianych zjawisk wybrano zachowania inwestorów gieł-dowych podejmujcych decyzje na współczesnej, elektronicznej giełdzie.
Słowa kluczowe: cyberprzestrze, dynamika system, złoony system adaptacyjny, społeczno wirtualna, rynki kapitałowe
Jacek Unold
Katedra Inynierii Systemów Informatycznych Zarzdzania Wydział Zarzdzania, Informatyki i Finansów
Uniwersytet Ekonomiczny we Wrocławiu ul. Komandorska 118/120, 50-345 Wrocław e-mail: jacek.unold@ue.wroc.pl
