This paper addresses the link between effective knowledge management in an organization and the organization as a complex adaptive system, which is required to deliver a rapid and high-quality response to social, media-related and technological changes in the environment. In an organization that possesses the characteristics of a complex adaptive system, it is legitimate for each employee and manager (as a fractal) to operate individually in the face of demands and changes in the environment; at the same time, constant processes of integration are at play among the employees and vis-a`-vis the managers. The research hypothesis was that the combination of the employee's independence as a fractal and a self-activated integration between the fractals is essential for maintaining effective knowledge management processes in the organization. The study was performed using qualitative research, enabling investigation of behavior within the organizational reality as it occurs, analyzing interviews and observation sessions conducted with about 60 employees at six private, government and public organizations. The study analysis relied on five criteria based on the functioning of the complex system and included synchronization of the goals of each employee as a fractal with the system as a whole, the ability to cope with the environment, decentralization of resources, work processes and knowledge transfer, and self-development of each fractal. The findings indicate that managers were perceived by employees and by themselves as leaders of organizational processes and as the parties responsible for synchronizing the resources, and not as the owners of specific 'knowledge'. Employees were perceived as specific knowledge owners and as bearing direct responsibility for the process of updating employees and managers and keeping abreast of the organizational information. This was found to be a condition for the employee becoming a fractal/knowledge worker. The conclusion of the study is that organizations that possess the characteristics of a complex adaptive system will achieve proven knowledge management capabilities, while improving the processes of knowledge performance and integration between employees. These organizations will be better able to respond correctly and quickly to dynamic changes in the environment.

PurposeThe purpose of this article is to discuss the necessity of access to the personal knowledge of each employee in order to cope with requirements in an organization's dynamic environment. The research question posed is which type of organizational structure, working environment and management style is most conducive to this access.Design/methodology/approachThe research was a qualitative study, allowing for examination of behavior in the organizational reality as is, by analyzing interviews and observations of about 60 employees in six private, government and public organizations. The research analysis was based on five criteria regarding performance of a complex adaptive system (CAS).FindingsThere are indications that in organizations where a higher number of CAS characteristics existed, employees were better able to provide immediate solutions to the dynamic requirements. To allow this, managers should focus more on the synchronization of organizational processes and less on the control and the direct command of their subordinates.Research limitations/implicationsOrganizations in a dynamic environment require a change in their structure and management method to resemble in line with CAS characteristics. In a CAS organization employees are autonomous, applying personal knowledge in developing immediate and systematic responses to change.Originality/valueThe research shows that the effective use of personal knowledge does not readily occur in hierarchical organizations. Knowledge management in organizations in the knowledge era requires a greater focus on process management than on people management.

Purpose -The purpose of this paper is to define optimal behavioral characteristics for members in digital social networks (DSNs). To this end, an assumption was tested that DSN members behave similarly to autonomous agents in a complex adaptive system (CAS) by maintaining a process of self-branding. Design/methodology/approach -Online questionnaires were presented to 94 DSN users. Their answers were used to assess: different parameters of their behavior on the DSN; and their perception of the DSN's effectiveness. Statistical analyses were conducted to examine possible correlations between these parameters and the optimal behavioral characteristics of individual agents in the CAS model. Findings -Subjects who reported a higher degree of functional autonomy and self-branding on the DSN also reported a higher degree of DSN effectiveness. A significant positive linear correlation was found between the degree of self-branding and optimal behavioral characteristics described previously for individual agents in a CAS. Practical implications -The study provides first empirical evidence that the CAS model parameters can be used to explain DSN-related phenomena in general, and the perception of DSN effectiveness in particular. This suggests that individual DSN members should generate and maintain a powerful self-brand through autonomous activities to increase DSN effectiveness. Such activities can be manifested through behavioral processes characterizing individuals in CAS, and especially through maximizing situational sensitivity and integration of information. Originality/value -This is the first study to empirically test the CAS theoretical model on DSNs. It specifies behavioral characteristics, which individual DSN members should incorporate to increase the perceived DSN effectiveness.

PurposeIn a competitive business environment, organizations must leverage their resources efficiently in order to provide system‐wide solutions and maintain the standards all customers expect. To do so, the resources must be integrated; however, the integration of information and resources within organizations has thus far not produced satisfactory results. In contrast, it has been found that efficient, ongoing and timely transfer of information is conducted over the internet. This research seeks to examine whether the use of internet technology within organizations can indeed enhance and streamline the ability of employees to function as fractals in complex organizations.Design/methodology/approachThe research is a qualitative study, allowing for the examination of behavior in the organizational reality as is, by analyzing interviews and observations of over 60 employees in different organizations.FindingsIt is found that the ability of a digital social network to create immediate system‐wide solutions, together with a management approach that transforms the organization into a complex adaptive system, allows employees to behave as fractals – i.e. to share applied‐knowledge, to take responsibility for performance and management of the processes, to update their superiors, and to develop self‐management abilities at the local level.Originality/valueSocial networks in organizations should be viewed as a shared “knowledge” system. Use of the network is “natural” and less rational and synchronized up front. However, it must be backed by a relevant management culture that enables all employees to serve as fractals in a complex adaptive system. In this manner, employees can contribute personally to work processes, determine their needs, and receive credit.

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PurposeThe purpose of this paper is to examine whether working environments possessing characteristics of a complex adaptive systems (CAS), such as organizational social networks (SNs), will be perceived by the individual worker as contributing to working efficiency. The author tested whether SNs increase the workers' sharing of knowledge, sensitivity to environmental changes and synchronization of resource, which contribute to the autonomic ability to create solutions according to changing demands in turbulent environments.Design/methodology/approachA research questionnaire distributed online assessed the views and behaviors of 94 subjects regarding SNs. An index was formed for each of the four CAS variables (Goal compliance; Situational sensitivity; Integration of information; and Resource synchronization) to evaluate how the subjects perceive SN effectiveness.FindingsA significant positive correlation was found between the degree of contribution to organizational working processes and the variables “Situational sensitivity” and “Integration of information”. This suggests that SNs allow workers to increase the degree of sensitivity to environmental changes; and that SNs allow a high degree of integration of information between the worker and other workers.Originality/valueThe utilization of SNs in organizations may allow quick and direct transfer of information between workers and answer immediate demands and requirements. Thus, organizations that are required to adapt to turbulent environments with high uncertainty factors and strong competition may benefit if their workers utilize SNs effectively. It can be concluded that SNs can be used as a friendly platform for the knowledge workers to update, be updated, sense environmental changes and integrate information in cooperation with other workers.

This research deals with the case of a smart intersection, where several cars approach the intersection from various directions, and a smart traffic light must decide about the time intervals of RED and GREEN in each direction, based not only on the number of vehicles in each lane, but also on other factors such as the type of vehicles (e.g. emergency vehicles), and the social characteristics of the passengers (e.g. a handicapped person, a student who is late for an exam). Those factors will be gleaned from the IoT (Internet of Things) network amongst cars, traffic lights, individuals, municipality data, and more. Once those priorities have been examined, they are fed into the algorithm we have devised, and outputted as a timing schedule for the different sides of the intersection. In this paper we present the algorithm, the prioritizing research, its implementation in the algorithm and initial results.

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