Narrow Results

Because of fundamental changes in the competitive environment, the amount of resources and knowledge needed in research and development (R&D) activities has become overwhelming for a single organisation. Moreover, new technologies create lucrative new possibilities for new service development, which are out of reach for a single organisation. Thus, there is a strong need to perform R&D activities in networks. This study increases the understanding of R&D networks by presenting an empirically grounded process model of the formation of such networks. The model has three main elements: the initial conditions, the role of network webber and the sub-processes through which the formation progresses. The process model highlights the importance of the network webber both in triggering the formation process and in managing the process. Moreover, the model suggests a view of the process that is overlapping and iterative, i.e., the sub-processes of enabling the network, acquiring actors, assuring continuity, formal structuring, learning and developing commitment do not follow each other in a certain order.

Inter-firm networking can facilitate new product development but "[…] it is not a panacea for success" (Harris et al., 2000:229). This article is not concerned with the potential of in-house innovations but tries to reinforce network innovation as a worthy alternative, if managed appropriately. Our research includes the spread of the interaction oriented network approach to innovation literature. Relying on this literature, we hypothesize that balanced network management enhances network retention by facilitating partner selection, resource allocation, regulation, and network evaluation. Balanced network management thereby increases the network retention of the innovation network participants. Our empirical results support our hypotheses. These findings imply that balanced network management affects innovation network retention. For this reason, innovation literature should include a detailed investigation of the four network management functions' effects on innovation network success figures, such as network retention. Assessing network stability and social interaction within innovation networks might allow a better understanding of underlying retention mechanisms in the innovation network context.

Innovation networks that aim at the joint development of products, services or processes represent a particular form of inter-organizational business networks. In order to yield useful results from these collaborations, networks need to be managed thoroughly. By appointing a dedicated network manager to administrate, coordinate, and regulate, the management of tasks is bundled and centralized within a single entity. However, to the best knowledge of the authors, no empirical research has yet been conducted, investigating the impact of a network manager's availability, relevance, and influence on network performance. Using the interaction-oriented network approach as conceptual foundation, we analyze network managers' direct and indirect influence on the network's relational and goal achievement performance. Our results suggest that a network manager enhances innovation network's core management functions, which in turn improve the relational performance (RP). Moreover, RP was found to significantly drive the goal achievement performance (GAP).

Active network is a new framework where network nodes not only forward packets, but also perform customized computation on the packet flowing through them. It provides a programmable interface to the user where users dynamically inject services into the intermediate nodes. However, the traditional prototype of network management does not accommodate to the management of active networks, it cannot utilize the distributed computing capabilities that active networks provides. This paper analyses the structure and mechanism of the active network management system, introduces a pattern of active network management, and studies the structure, management mechanism and studies the structure, management mechanism, design outline and each connection of the management system. The paper also studies the network topology discovery and traffic.

This article discusses the design of management information bases used in network management systems. We are proposing an object-oriented modeling method whose starting point is natural-language documentation. Our method parses a text previously analyzed at its finest level of granularity, i.e., the level of words. This method considers each word in the text leading first to an object-based model, then, eventually to an object-oriented model. Our approach is based on the analytic method of Vogel and the design methodology of Booch. Our ideas are illustrated with examples taken from the field of network management systems.

The inherent micro-structure (agent-agent/system) of human organizations has been introduced in Chapters 2 and 3. Fundamentally, human organizations are composite complex adaptive systems with human beings as interacting agents (each an intrinsic complex adaptive system). This chapter further analyzes the basic conceptual foundation of the multi-layer structure, including advantages of the intelligent biotic macro-structure (with inherent features similar to that of an intelligent biological being — a structural reform), and its unique and more integrative complex adaptive dynamic in intelligent human organizations (towards iCAD). The necessity of nurturing an intelligent biotic macro-structure with vital characteristics that better synchronize and enhance sophisticated information/knowledge-related activities is highly beneficial — achieving a higher structural capacity. Thus, the attributes, functions and higher structural capacity of the more intelligent biotic macro-structure can reinforced the competitiveness of any categories of human organizations extensively.

In this respect, connecting and engaging of intelligence/consciousness sources (individual and collective), organizing around intelligence, intelligence/ consciousness management, and the intelligent biotic macrostructure are mutually enhancing (towards higher coherency). Apparently, being intelligence/consciousness-centric is a beneficial and critical activator (strategic foundation) of the intelligence paradigmatic shift. In the present context, the roles and integration of intelligence, information and knowledge, as well as nurturing a ‘common’ language and elevating coherency in human organizations (with respect to the macro-structure and micro-structure, as well as their higher collectiveness — collectiveness capacity) must be more deeply scrutinized and utilized. The presence and significance of the individual intelligence enhancer encompassing three entities namely, intelligence, knowledge, and theory in the human thinking systems, and the necessity of nurturing a similar and effective intelligence enhancer at organizational level are analyzed. Subsequently, the supporting roles and contributions of artificial intelligence systems are also examined.

In between the macro-structure and micro-structure are two meso-structures. In the intelligent organization theory, the complexity meso-structure encompasses spaces of complexity and punctuation points. In this respect, complexity is a highly significant focal point, and the exploitation of co-existence of order and complexity is a new necessity (complexity-centricity). Next, the network meso-structure encompassing complex network (network of networks) is also an inherent structure and dynamic in all human organizations. This meso-structure is briefly introduced, and will be more deeply analyzed with respect to governance (network-centricity, network governance).

Hence, it is crucial to lead and manage human organizations with a strategic approach that integrates the above multi-layer structure/ dynamic at all time so that a higher structural capacity, collectiveness capacity, adaptive capacity, self-organizing capacity, and emergence-intelligence capacity can be nurtured. In the current highly competitive context, possessing these positive capabilities to elevate coherency and synergetic characteristics (including social consensus and the construal aspect) and dynamic is also highly crucial — a key focus of the complexity-intelligence strategy (towards achieving higher organizational mental cohesion). Hence, the significance and impact of nurturing intelligent human organizations with the complexity-intelligence-centric and network-centric approach that leads to the emergent of smarter evolvers and emergent strategists must be better understood and adopted. (The conceptual foundation on structural-dynamic coherency and synergy in intelligent human organizations developed in this chapter will be more deeply reviewed and exploited in later chapters.)

Fundamentally, effective leadership is associated with its ability to achieve collective goals (agents and their organization, stability-inducing capability) and organizational sustainability, irrespective of the nature of the organizations (leadership capacity <=> relational capacity <=> unifying capacity). The mismatch of the bureaucratic mindset and its associated hierarchical/administrative leadership with the changing situation is escalating. Basically, the presence of an adaptive leadership is beneficial. In this respect, the collectiveness capacity and relational capacity of the organization are critical attributes. It has been recognized that the intense and quality of these two capacities is highly dependent on both the thinking and attributes of the leaders, as well as the other interacting agents (including non-actors, and quality of leader–agents exchanges). Overall, a high leadership capacity and organizational mental cohesion is a key necessity. In general, the success of today’s global turbulence can only be achieved through global mental cohesion.

In order to achieve this, fresh insights beginning with constructive intelligence-intelligence linkages is required. In the present state, it is significant to note that for any categories of human organizations (economic, social, education, political, and military) their agents (employees, citizens, members, stakeholders) are possessing redefined attributes (principles, values and expectations), due to better education, quick access to information, and high interconnectivity. This profound transition (supported by intensive usage of mobile/social media technology) transformed some other attributes including autonomy/ independency, autopoiesis, self-centricity, self-organizing communications, interdependency, symbiosis, and other self-organizing capabilities. Consequently, current human beings are more sophisticated interacting agents. Hence, leading these ‘transformed’ agents is drastically different from leading traditional setups. Agent-centricity is a new vital attribute that required deeper attention, and one commonality among agents at all levels must be achieved — stability-centricity (agent-centricity <=> intelligence/consciousness-centricity + stability-centricity).

The more intelligent, complex adaptive, and nonlinear evolving dynamic is driven by the intrinsic intelligence/consciousness of the individuals, and the collective intelligence and org-consciousness of the organization (anticipatory, adaptive capacity), as well as local spaces/ complex networks — the presence of networks (formal and informal) is becoming more dominant, and this development renders elevating collectiveness capacity (consensus and collaboration) at organizational level more complex. Apparently, coupled with the influence of the knowledge-intensive, fast-changing, more complex environment, and the modified agents’ attributes, an immense shift in strategic thinking, leadership attributes, governance characteristics, management abilities and operational style in the new generation of leaders is inevitable. In general, the leader–follower gap has been narrowed, and their relationship (relational parameter) is more complex and nonlinear, again, confirming that intelligence/consciousness-centricity must be a key focus of the new leadership.

In such a situation, a deeper insight into complexity is inevitable. In this case, a better comprehension of leadership strategy and organizational dynamic can be acquired by ‘bisociating’ some properties of the complexity theory, and the different perspectives of complexity-intelligence linkages. The resulting evolutionary model to be introduced in this chapter is the intelligence leadership theory/strategy for iCAS. In this model, an intelligence leader must recognize that a fundamental capability of intelligence is stability enhancement. Concurrently, an intelligence leader must be an effective lateral/collective actor (always encompassing agent-agent, intelligence-intelligence, agent-network, agent-system, and network-system linkages; and the intrinsic leadership capacity of all agents, and collective leadership capacity of networks and the organization) with a new set of attributes (encompassing enabler, smarter evolver, and unifying, emergent strategist and synergist capabilities).

Hence, an effective intelligence leader must possess certain relevant or appropriate attributes of the traditional leadership, as well as a set of new complexity-intelligence related attributes that can better ensure the survival of the agents, integrate networks, and elevate the resilience, and sustainability of the organization (achieving higher coherency, synergy, constructionist effect, self-organizing capacity, emergence-intelligence capacity, unifying capacity and organizational mental cohesion) — (constructionist effect <=> innovation and creativity) — that is, focusing on continuous acquisition of capacities improvement is critical. In addition, with this paradigmatic shift, possessing the latent leadership capability is highly beneficial.

The first section of this chapter is an introduction to relativistic complexity (a significant component of the intelligent organization theory). The presence of intense intelligence/consciousness-centricity and 3^rd order stability-centricity in the human world renders complexity relativistic. The impact of the human mental space is so tremendous that complexity is in the mind of the beholder, and predictability becomes highly subjective. In this situation, the state of relativistic static equilibrium may be beneficial. Certain spaces of complexity appear as spaces of relativistic order with surface patterns becoming more apparent. Such spaces must be creatively explored and exploited (higher exploratory capacity) leading to a more advanced level of intelligence advantage. In this respect, effective self-transcending constructions, high self-organizing capacity and emergence-intelligence capacity are significant attributes that the new leadership and governance system in intelligent human organizations must exploit. Holistically, the two strategies focus on concurrent exploitation of intelligence/consciousness-centricity and relative complexity, and optimizing the more comprehensive contributions of the integrated deliberate and emergent strategy.

Many issues/problems that present human organizations (nations, political systems, communities, business organizations, markets) are encountering due to accelerating changes (mindset, thinking, values, perceptions, expectations, redefined boundaries and high interactive dynamics) that cannot be well-managed with traditional knowledge and hierarchical practices are affecting governance and governance systems. Fundamentally, governance deals with power, interest, and conflict. The traditional governance systems are hierarchical, highly directed, controlled and managed, and the relational aspect has not been allocated sufficient priority resulting in extensive disparities. In the current complex dynamical and high interdependency environment, its weaknesses and constraints are highly apparent. The latter includes ‘space-time compression’; incoherency in thinking, values, perceptions, and expectations between the leadership and the other agents; diversification in stakeholders’ needs not accommodated; and constraints of current governance theories. Thus, a new theory that provides a more ‘realistic’ foundation is essential for deeper contemplation.

Primarily, recognizing the inherent strengths of human agents and the fundamental constraints/weaknesses of human organizations is a key foundation towards better adaptation, leadership, governance, resilience and sustainability. In all human organizations, the agents are intrinsic intense intelligence/consciousness sources that could easily transform their behavioral schemata. This observation contradicts the Newtonian/design paradigm, as the organizational dynamic of human agents is complex, nonlinear, constantly/continuously changing with limited predictability. In addition, human agents are self-centric, self-powered, stability-centric, independent and interdependent, network-centric and self-organizing due to high awareness. In this situation, high self-organizing capacity and emergence-intelligence capacity are new niches. However, this phenomenon can create new opportunities, innovation, and elevates competiveness; or destruction.

In particular, effective leadership and governance are spontaneously emerging key requirements in all human groupings — a primary trait for human collective survival. Historically, many organizations disintegrated because of the weaknesses in leadership and governance. Currently, with more knowledge-intensive and higher participative new agents (self-powered intrinsic leadership) possessing modified attributes that are dissimilar from the older generations (also due to the deeper integration of the economic, social, political, and environmental perspective), reduces consensus and collaboration, and renders governance and leadership even more nonlinear or dysfunctional. In particular, the traditional governance systems of more organizations are manifesting their constraints and incompetency, including incoherency due to new values and cultural pressure, and the wider spread of self-organizing networks. The emergent of informal networks is a more commonly observed phenomenon worldwide. Apparently, a deeper comprehension on the diminishing effect of the traditional organizational thinking (political, social, economic), governance capacity, precise strategic planning, decision making, hierarchical structure, communications and engagement, empowerment leadership, management, operations, and the highly nonlinear relational parameter is essential. Apparently, new principles of governance must emerge (intelligent human organization > thinking system + feeling system).

The new paradigmatic path of the intelligence governance strategy that exploits intelligence/consciousness-centricity, complexity-centricity, and network-centricity concurrently, introduces a new basic strategic path towards better adaptive governance and acceptance governance. The latter focuses on integrating self-powered self-organizing governance, reducing direct governance, and increasing e-governance and network-centric governance as a new necessity. In this case, the merits of adopting the intelligence leadership strategic approach simultaneously are more apparent. Hence, the new governance focal points must include more and better interconnected actors, the critical ability of self-organizing communications (supported by mobile/social media development), immersion of leadership nodes in networks (better exploitation of e-governance), increasing coherency of complex networks (exploiting interdependency of network of networks, and better network management), and elevating self-transcending constructions capability (higher self-organizing governance capacity and emergence-intelligence capacity) that better facilitates emergence through multi-level and ‘multi-lateral’ dynamics (complex adaptive networks <=> intelligent networks). Thus, the intelligence governance strategy emphasizes that mass lateral collectivity (acceptance governance) rather than selective enforced hierarchical empowerment as the more constructive approach in the present contact. In particular, the stabilityinducing role of leaders and institutions are critical. Apparently, optimizing the ‘everybody is in charge’ phenomenon (whenever necessary) is a more viable option.

Traditional centralized network management model cannot meet the management needs nowadays, and active network management can only be deployed in active network. In this paper, we propose an efficient network management architecture based on active network techniques. The proposed model has the active network management feature, thus agile and traffic saving compared traditional management model. The proposed model can be directly deployed in the real network, thus practical compared with active network management model.