Predicting Knowledge Creation Behavior in Organizations : A General Systems Theory Perspective

Knowledge creation has been widely recognized to be strategically important for organizational learning and innovation. The lack of empirical work in this area has limited our understanding of this important phenomenon. Previous studies have focused on limited aspects of the overall knowledge creation process, such as inter-organizational knowledge transfer, knowledge flows within the firms and the interplay of tacit and explicit knowledge. In developing countries, there is a sense that rich countries have failed to create knowledge that is appropriate to local needs. This study is a comprehensive analysis of the knowledge creation behavior by using general systems theory and HIV/AIDS epidemic which can help us to better understand of this process.


Introduction
The concept of knowledge is as old as the history of human civilization (Pillania, 2008a).In addition, Knowledge management has emerged as an important research topic for information systems and management researchers since the 1990s (e.g., Alavi and Leidner, 2001;Davenport and Grover, 2001;Hahn and Subramani, 2000;Nonaka, 1991Nonaka, , 1994)).
New knowledge creation has received increasing attention, recognition and importance in recent past in the business world.Knowledge has emerged as the most important strategic resource for organizations (Toffler, 1990;Nonaka, 1991;Barney, 1991;Bartlett and Ghosal, 1993;Drucker, 1993;Stewart, 1997;Pillania, 2005, b;Pillania, 2008b).It is not only the big organizations; new knowledge creation has increasingly become critical for small and medium-size enterprises (SMEs) also.The need for knowledge renewal is particularly acute in SMEs (Pillania, 2006;Martin et al., 2002).
While knowledge creation is fundamental to the survival of a business, it has not been extensively researched beyond organizational theory (Chen, 2005).Alavi and Leidner (2001) consider the firm's ability to create knowledge and to take action upon it as the basis for competitive advantage.
The enormous amount of studies and research carried out on the process of knowledge creation in organizations in recent years is an indisputable reality (Choo and Bontis, 2002;Crossan et al., 1999;Holmqvist, 2003;Leonard and Sensiper, 1998;Nonaka and Takeuchi, 1995;Wikström and Normann, 1994).
The propose of this article is better understanding of knowledge creation process by using of general systems theory as a powerful tool to linkage different area of science and using simulation without creating a separated model for this field.Therefore we can predict the behavior of knowledge creation by playing with AIDS epidemic parameters in the manner which is adapted by their organizational parameters.
In this article, we will introduce general systems theory in a nutshell, and then describe an agent-based approach to HIV/AIDS epidemic.For that purpose, at first AIDS epidemic will be presented, then agents and agent based modeling will be surveyed, after that HIV/AIDS will be modeled by using of agent based model and at the last, the behavior of knowledge creation will be predicted.

General Systems Theory
Ludwig von Bertalanffy gave us the General Systems Theory (GST).He did not merely give birth to a new field but also nurtured it and projected its future possibilities as an epistemology and ideology.
The time of GST's raise -the middle of the century -was the "hour of triumph" of science (particularly in nuclear physics, electronics and molecular biology).That partially explains Bertalanffy's choice to look for the solutions on complexity problems, wholeness and so on in the exact sciences: "GST is a logico-mathematical science of wholeness" (Skyttner, 1996).Bertalanffy, in his famous paper, described that (Bertalanffy, 1955): "There exist models, principles and laws that apply to generalized systems or their subclasses, irrespective of their particular kind, the nature of their component elements and the relations of forces between them.It seems legitimate to ask for a theory of universal principles applying to systems in general; not of systems of a more or less special kind."Therefore, a first consequence of this theory is the appearance of structural similarities or isomorphism in different fields.There are correspondences in the principles which govern the behavior of entities that are intrinsically, widely different (Bertalanffy, 1955).
By summarizing and totaling the researchers in this article, the aims of general systems theory are (Bertalanffy, 1955;Skyttner, 1996;Boulding, 1964;Mulej et al, 2004): 1) There is a general tendency towards integration in the various sciences.
2) Such integration seems to be centered in a general theory of systems.
3) Such theory may be an important means for aiming at exact theory in the non-physical fields of science.4) Developing unifying principles running vertically through the universes of the individual sciences, brings us to the goal of the unity of science.
5) This can lead to a much-needed integration in scientific education.

An agent-based approach to HIV/AIDS epidemic
Since AIDS was first discovered, mathematical models of the transmission dynamics of HIV have been developed to determine the drivers of the epidemic.It has become apparent that the most profound factor in the proliferation of this disease is the aggregate effects of individual behavior and perception of risk.Agent-based models (ABM) allow one to simulate the social and sexual interactions which may describe the societal context in which HIV may spread.
Ultimately, the purpose of HIV transmission models is to hypothesize about drivers of the epidemic which will then shed light on appropriate interventions and prevention measures.ABMs facilitate the development of network-based public health interventions.Such interventions, like home-based care programs, may have great promise in anywhere.

The AIDS epidemic
UNAIDS estimates more than 60 million people have contracted HIV/AIDS worldwide in the past two decades and 25 million have died as a result -it is the fourth-leading cause of death in the world (Hein and Wilson, 2002).
Currently, Sub-Saharan Africa is the most seriously impacted region in the world -with 9% of all its inhabitants between the ages of 15 -49 infected with HIV.Eurasia, however, is expected to be the next major area of infection, and the region includes three of the world's largest nations, China, Russia and India.The toll, in terms of human suffering will be tremendous, but, combined with the potential economic, social and political impacts, the epidemic will have staggering implications inside and outside the region (Hein and Wilson, 2002).
The HIV/AIDS model has two key modules: the disease progression module and the economic module, but the approach consists of a collection of integrated analytic solutions.The disease module is primarily a model of heterosexual transmission that incorporates multiple risk groups.In the economic module models specific industrial segments: information technology, financial services, and automotive.Economic impact of HIV/AIDS was captured through worker morbidity and mortality.There were a variety of program and policy options that were incorporated into our model.Programs included both prevention and treatment options.Prevention programs were modeled both at the industry and national levels and consisted of: general education and wellness, voluntary counseling and testing, condom distribution, and mother to child transmission prevention programs (Markus, 2004).

What is an agent?
Up to now, no general agreement on the term agent has yet been established (Tripathi et al., 2005).Parunak et al. (1998) define an agent as being a software entity with its own thread of control able to execute operations without being externally invoked, while Jennings et al. (1998) define an agent as a self-contained, problem-solving entity.The Merriam web dictionary defines "agent" as an entity that produces or is capable of producing an effect for an active or efficient cause (Web: Merriam-Webster online dictionary, 2009).
The agents perceive the state of the environment, and then act according to the information they possess.They may change either some objects in the environment or themselves, for instance by moving relative to the other agents (Laine, 2006).
The simulation of agent and their interactions in known by several names, including agent based modeling, bottom-up modeling and artificial social systems (Axelord, 1997a).This type of modeling was introduced below.

Agent based modeling
Many social systems such as organizations are inherently nonlinear.That is the effects of independent variables representing policy decisions on dependent variables or outcomes are not proportional and directly predictable.It is difficult to model such nonlinear systems because they cannot be understood analytically (Gilbert N, 1999).The behavior of the system cannot be predicted from a set of equations.The only effective way of exploring the behavior of nonlinear systems is by building and running simulation models.Two different approaches to modeling nonlinear systems have been developed; system dynamics and agent based modeling (Anderson, 2007).Forrester's (1969) early studies represent efforts within the systems dynamics field to simulate the growth of urban areas and systems dynamicity continue to explore social system and organizational dynamics (Richardson, 1996).In contrast, ABM represents a new paradigm in modeling and simulation of dynamic systems distributed in time and space (Jennings et al., 1998;Lim and Zhang, 2003).It examines the global consequences of interactions among individual agents (Wakeland, 2004).The ABM approach is highly appropriate for these types of systems (Lim and Zhang, 2003;Nilsson, 2005;Wakeland et al., 2004).There is a growing interest in using ABM in several business-related areas, such as manufacturing (Chun et al., 2003;Kotak et al., 2003;Lim and Zhang, 2003;Zhou et al., 2003) and logistics and supply chain management (Gerber et al., 2003;Kaihara, 2003;Knirsch and Timm, 1999;Santos et al., 2003;Schieritz and Grossler, 2003).ABM is considered important for developing industrial systems (Davidsson and Wernstedt, 2002;Fox et al., 2000;Karageorgos et al., 2003) and it provides a pragmatic approach for the evaluation of management alternatives (Swaminathan et al., 1998).
In ABM the focus is on agents and their relationships with other agents or entities (Axelrod, 1997b;Cicirello and Smith, 2004;d'Inverno and Luck, 2001;Jennings et al., 1998).The state of agents making up the environment varies as the simulation moves through time.Thus, an agent based model consists of two distinct parts: An environment and agents.

Modeling HIV/AIDS by agent based model
Alisa Joy Rhee (2006) in her thesis, inspected AIDS epidemic by using of agent based modeling.She supposed three scenarios which has different epidemic probabilities which are shown in table1.She also ran her model with 2000 as its population size and 0.005 per day as probability of epidemic.The model was run at one hundred 9000 time step Monte Carlo realizations.Suppose that k 3 is described to quantify the amount of partnerships in a network and mathematically is approximated by: Where 2 and µ are the variance and mean of the number of relations per person observed in the network.
Scenarios 1-3 are ordered by degree of concurrency: scenario 1 has the greatest proportion of agents in monogamous partnerships, and the lowest proportion of multiple concurrent partnerships; scenario 3 has the greatest amount of concurrency, with a greater proportion of individuals in multiple concurrent partnerships.
The epidemic curves of the three scenarios are plotted in Figure 1.
The epidemic begins the slowest in scenario 3 because the scale-free network also has the highest proportion of singles of all three scenarios; the epidemic is slow to spread immediately after HIV is seeded in the population.In Figure 1, HIV prevalence begins to increase more rapidly in scenario 3 than the others at the end of 30 months.
As shown in Figure 2, after one year, the prevalence in scenario 3 increases faster than scenarios 1 and 2 which have fewer concurrent partnerships.Therefore prevalence is growing fastest in scenario 3 and slowest for scenario 1.

Similarities between AIDS epidemic and knowledge creation
There are some similarities between AIDS epidemic and knowledge creation which can help us to use general systems theory to link their behavior to each other.Therefore in Table 2, we have proved that the properties of knowledge creation in an organization and AIDS epidemic are similar and according to general systems theory we can claim that their behavior under specific situations are the same.

Results
As shown above, the properties of AIDS epidemic and knowledge creation are the same and we can predict the behavior of knowledge creation in an organization by using of general systems theory and the agent model of HIV/AIDS epidemic.Therefore, we can predict that whether employees in different departments can have interactions with each other and share their knowledge, the process of knowledge creation becomes faster and is performed better (scenario 3) because proportion of individuals is greater and amount of concurrency is at the greatest level but in those situations whose proportion of individuals in monogamous partnerships is greatest, and proportion of multiple concurrent partnerships is at the lowest level (scenario 1 and 2) the process of knowledge creation is slower and don't perform as well as the process in scenario 3.
We can infer that the work groups in an organization should contain different experts in various fields who have great agreement with each others.In these group types, we can have the highest level of knowledge creation with better quality.We should notice that, each organization have their own situation and parameters and these result can be quite different in some organizations.They can play with HIV/AIDS model's parameters and gain their suitable results.

Conclusion
As a result, our understanding of knowledge creation is limited to certain micro-level aspects, rather than understanding the process in its entirety.Therefore, having a model which can predict knowledge creation behavior is very important.
Whereas building a suitable model for each organization with their own situation is a too hard work, in this article we applied one of the most applicable models of epidemic to our research.As we look further back into the knowledge creation process we see that informal networking is crucial.However, senior managers are uncomfortable with things that cannot be managed.Hence, it is important to understand that although informal networking is critical there is a link between formal and informal networking.The used agent based model of HIV/AIDS epidemic considers the both formal and informal factors and by using of general systems theory, we deduced the knowledge creation behavior in organizations.

Table 2 .
Comparison of knowledge creation and AIDS epidemic