Complexity and organizational architecture

Management Science, 2009

S tarting from the premise that individuals within an organization are fallible, this paper advances the study of relationships between the organization's decision-making structure and its performance. We offer a general treatment that allows one to analyze the full range of organizational architectures between extreme centralized and decentralized forms (often referred to as hierarchies and polyarchies). Our approach furthermore allows designers to examine the change in the overall reliability of the organizational structure as the number of actors within the organization changes. We provide general proofs that show how decision-making structures can be constructed so they maximize reliability for a given number of agents. Our model can be used directly for a qualitative assessment of decision-making structures. It is thereby useful for assessment of the many complicated hybrid structures that we see in actual decision-making organizations, such as banks, purchasing departments, and military intelligence. An application from a bank illustrates how our framework can be used in practice.

2006

Abstract A Multi-Agent System (hereafter MAS) is an organization of coordinated autonomous agents that interact in order to achieve common goals. Considering real world organizations as an metaphor, this paper proposes architectural styles for MAS which adopt concepts from organizational theories. The styles are modeled in i*/Tropos, using the notions of actor, goal and actor dependency and are intended to capture needs/wants, delegations and obligations.

Capitalizing on Complexity in Modern Business Environments: A Network-Based Perspective for Projects and Organizations, 2019

The advancement of technology has substantially changed the way knowledge is created and transmitted. Modern interaction platforms allow information to expand at proportions and speeds without precedents, enhancing the potential to access and combine perspectives from different settings and shaping the mechanisms of collaboration and competition. The evolution of modern business environments has made more evident the agent-based nature of knowledge creation and has challenged the linearity in traditional models where growth is visualized as the combined effect of aggregated contributions of agents, the efficiency of adequate organizational structures and the optimization of resources. By building on the characteristics and dynamics of Networks, it is possible to engineer organizational architectures that induce transformation and dynamically capitalize on changes in the business environment, strategically adjusting structures and synchronizing organizational growth with the evolution of internal and external contexts. To achieve this, it is necessary to adopt an open-systems approach that allows visualizing the dynamics and permanent reconfiguration of organizational networks, understanding the role and contributions of agents in these reconfigurations and setting strategic initiatives to effectively orchestrate information flows and resources.

Cost and schedule overruns have become increasingly common in projects that set out to design and deliver complex engineered systems. Noting the well-established relationship between products and the organizations that design them, this study evaluates the effectiveness of different organizational networks at designing complex engineered systems using agent-based modeling. Specifically, it compares matrix and military staff organizational networks to random and multiscale networks, modeling design as an activity that requires organizations to create design artifacts and share information. It examines the nature of design, the role of product architecture, the nature of complexity and how it affects projects, and the characteristics that improve organizational robustness to congestion. Results indicate matrix organizations are particularly susceptible to congestion failure, while military staff and multiscale networks are more robust to congestion failure, with military staff networks having performance comparable to multiscale networks over a range of scenarios. Results further indicate simple changes to organizational behavior improve performance and robustness to congestion, with decentralization being especially beneficial. Finally, results confirm the utility of agentbased modeling for understanding the dynamics of complex systems.

2004

In this paper, we explore the decomposition of organizational processes and decision-making, the coexistence of organization’s command and communication networks, and their effects on team performance. We present a methodology to design mission-based strategies and novel heterarchical organizational structures based on exploring information/command transfer and processing in the organizations. This methodology allows synthesising alternative C3I organizational structures, which outperform traditional hierarchies in environments with heavy information volume, scarce resources, and strict knowledge & communication constraints. 1.

Journal of Economic Interaction and Coordination, 2008

and Chuma ) suggests that firms' environments are becomeing more complex and uncertain. This paper investigates the relationship between the complexity of firm activities, environmental uncertainty and organizational structure. We assume that the firm-as-information-processing organization is arranged hierarchically, but that decisions can be made at different levels; that is, we study the role that the centralization of decision making can have on firm performance and speed. We model a firm's activity set as a modified N K landscape. Via simulations, we explore which types of organizational structures and level of decision making maximize firm performance, given the complexity and uncertainty of the environment. We find that centralized decision making generates a higher value for more complex and uncertain environments, and that a flatter structure is better for the organization with centralized decision making, provided the cost of information processing is low enough.

SSRN Electronic Journal, 2005

We consider a hierarchical organization with two fully rational agents. The goal of the organization is that of selecting the best alternative out of several available, and agents are heterogenous in the accuracy with which they screen the alternatives. We show that, if internal communications between agents is not possible, the ordering of agents affects the performance of the organization. More specifically, we find that the expected payoff of the organization improves when the more accurate agent screens first. Finally, we note that such optimal ordering makes the hierarchy formally identical to one in which the internal communication flow is perfect. * We are indebted to Maarten Janssen for many discussions and helpful suggestions. We also thank seminar participant at Erasmus University for useful comments.

The Knowledge Engineering Review, 2004

Many researchers have demonstrated that the organizational design employed by an agent system can have a significant, quantitative effect on its performance characteristics. A range of organizational strategies have emerged from this line of research, each with different strengths and weaknesses. In this article we present a survey of the major organizational paradigms used in multi-agent systems. These include hierarchies, holarchies, coalitions, teams, congregations, societies, federations, markets, and matrix organizations. We will provide a description of each, discuss their advantages and disadvantages, and provide examples of how they may be instantiated and maintained. This summary will facilitate the comparative evaluation of organizational styles, allowing designers to first recognize the spectrum of possibilities, and then guiding the selection of an appropriate organizational design for a particular domain and environment.

2017 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM), 2017

Agent-based simulation models provide a means of analyzing and understanding the functioning of complex socioeconomic systems, which often involve multiple interacting entities and non-linear and stochastic interactions. In such models, agents may be individuals or organizations, characterized by such properties as objectives, values, capabilities and resources. Project networks are temporary inter-organizational networks of heterogeneous actors whose purpose is to accomplish a complex set of tasks and reach shared goals. The variety of actors in project networks and the complexity of their interactions makes agent-based simulation a logical choice for simulating such networks. This paper present a design of an agent-based simulation for simulating governance in project network. Key design principles are introduced, along with practical examples of how specific governance mechanisms can be implemented in the model. Additionally, advantages and challenges of agent-based simulation as a research method is discussed.

2002

A Multi-Agent System (MAS) is an organization of coordinated autonomous agents that interact in order to achieve common goals. Considering real world organizations as an analogy, this paper proposes architectural styles for MAS which adopt concepts from organization theory and strategic alliances literature. The styles are intended to represent a macro-level architecture of a MAS, and they are modeled using the i* framework which offers the notions of actor, goal and actor dependency for modeling multi-agent settings.