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Found 18 papers, 1 papers with code
Interactions between dynamic team composition and coordination: An agent-based modeling approach
In this paper, we follow the contingency theory and characterize dynamic team composition as a design choice that interacts with other choices such as the coordination mode, and with additional contextual factors such as individual learning and task complexity.
Building resilient organizations: The roles of top-down vs. bottom-up organizing
Organizations face numerous challenges posed by unexpected events such as energy price hikes, pandemic disruptions, terrorist attacks, and natural disasters, and the factors that contribute to organizational success in dealing with such disruptions often remain unclear.
Designing organizations for bottom-up task allocation: The role of incentives
In recent years, various decentralized organizational forms have emerged, posing a challenge for organizational design.
The benefits of coordination in (over)adaptive virtual teams
Specifically, the effect of coordination on task performance depends on aspects such as the team members' learning and the changes in team composition over time.
Controlling replication via the belief system in multi-unit organizations
We find that the effect of network structures on the diffusion of knowledge depends on the interdependencies between divisions, and that peer-to-peer exchange of information is more effective in reaching synchrony than unilateral sharing of knowledge from one division.
Collaborative search and autonomous task allocation in organizations of learning agents
This paper introduces a model of multi-unit organizations with either static structures, i. e., they are designed top-down following classical approaches to organizational design, or dynamic structures, i. e., the structures emerge over time from micro-level decisions.
Interactions between the individual and the group level in organizations: The case of learning and autonomous group adaptation
We explore organizations that promote learning and group adaptation either simultaneously or sequentially and analyze the interactions between the activities and the effects on performance.
Dynamic groups in complex task environments: To change or not to change a winning team?
Previous research comes to ambiguous results regarding the effects of group adaptation on task performance.
Balancing Consumer and Business Value of Recommender Systems: A Simulation-based Analysis
Our simulations show that a hybrid strategy that puts more weight on consumer utility but without ignoring profitability considerations leads to the highest cumulative profit in the long run.
Understanding Longitudinal Dynamics of Recommender Systems with Agent-Based Modeling and Simulation
Today's research in recommender systems is largely based on experimental designs that are static in a sense that they do not consider potential longitudinal effects of providing recommendations to users.
Micro-level dynamics in hidden action situations with limited information
The hidden-action model provides an optimal sharing rule for situations in which a principal assigns a task to an agent who makes an effort to carry out the task assigned to him.
Limited intelligence and performance-based compensation: An agent-based model of the hidden action problem
This paper is particularly concerned with the model of the hidden action problem, which proposes an optimal performance-based sharing rule for situations in which a principal assigns a task to an agent, and the action taken to carry out this task is not observable by the principal.
Effects of limited and heterogeneous memory in hidden-action situations
This paper introduces an agent-based model of the hidden-action problem that includes limitations in the cognitive capacity of contracting parties.
On the Role of Incentives in Evolutionary Approaches to Organizational Design
This paper introduces a model of a stylized organization that is comprised of several departments that autonomously allocate tasks.
On the effect of social norms on performance in teams with distributed decision makers
We use the NK-framework to build an agent-based model, in which agents work on a set of interdependent tasks and exchange information regarding their past behavior with their peers.
Multi-level Adaptation of Distributed Decision-Making Agents in Complex Task Environments
We implement the multi-level adaptation process by a second-price auction mechanism for self-organization at the team level.
Interactions between social norms and incentive mechanisms in organizations
We place the interaction between social norms and performance-based incentive mechanisms in the complex environment of an organization with distributed decision-makers, in which a set of interdependent tasks is allocated to multiple agents.
On the Effectiveness of Minisum Approval Voting in an Open Strategy Setting: An Agent-Based Approach
This work researches the impact of including a wider range of participants in the strategy-making process on the performance of organizations which operate in either moderately or highly complex environments.
