Simulation-based research in management accounting and control: an illustrative overview

Leitner, Stephan; Wall, Friederike

doi:10.1007/s00187-015-0209-y

Cited by 27 publications

(15 citation statements)

References 114 publications

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“…With this, we rely on a simulation approach which, though originated in evolutionary biology, has been widely used in managerial science (for an overview see, e.g., [11,19,31,44,48]). Our organizations use two means -first, in short-term they stepwise search for better solutions to a given decision problem for improving performance, and second, in mid-term they can change their organizational structure.…”

Section: Simulation Modelmentioning

confidence: 99%

Beneficial Effects of Randomized Organizational Change on Performance

Wall

2015

Advs. Complex Syst.

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In this paper, we investigate the effects on performance of inducing organizational dynamics in collaborative search processes. Using an agent-based simulation, we analyze different temporal modes and levels of scope of change. The organizational properties under change are chosen randomly out of three dimensions of organizational design. Results suggest that inducing organizational dynamics has the potential to increase the effectiveness of search, but that the temporal change mode, the frequency and the scope of change in conjunction with the complexity of the search problem considerably affect the order of magnitude of this beneficial effect. The paper characterizes conditions under which different modalities of organizational change are beneficial.

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Section: Simulation Modelmentioning

confidence: 99%

Beneficial Effects of Randomized Organizational Change on Performance

Wall

2015

Advs. Complex Syst.

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“…ABM is an approach to model complex adaptive systems that are composed of three main building blocks: (i) heterogeneous and autonomous 'agents', (ii) the environment in which agents operate, and (iii) interactions among agents and among agents and the environment [21,22,31]. ABM follows a generative science approach [10]: The modeling process takes place at micro-level, i.e., at the level of the three building blocks, and the ultimate goal of the simulation typically is to obtain macro-level insights from micro-level interactions over a longer period of time, i.e., insights about the collective behavior and emerging phenomena.…”

Section: Agent-based Modeling and Simulationmentioning

confidence: 99%

Understanding Longitudinal Dynamics of Recommender Systems with Agent-Based Modeling and Simulation

Adomavicius,

Jannach,

Leitner

et al. 2021

Preprint

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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. In reality, however, various important and interesting phenomena only emerge or become visible over time, e.g., when a recommender system continuously reinforces the popularity of already successful artists on a music streaming site or when recommendations that aim at profit maximization lead to a loss of consumer trust in the long run. In this paper, we discuss how Agent-Based Modeling and Simulation (ABM) techniques can be used to study such important longitudinal dynamics of recommender systems. To that purpose, we provide an overview of the ABM principles, outline a simulation framework for recommender systems based on the literature, and discuss various practical research questions that can be addressed with such an ABM-based simulation framework.

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“…The relaxation of assumptions reduces the model's mathematical tractability dramatically. We therefore set up an agent-based variant of the hidden-action problem which includes the relaxed assumptions (for simulation-based approaches in managerial science see, for example, Davis et al 2007;Leitner and Wall 2015;Wall 2016).…”

Section: Introductionmentioning

confidence: 99%

Decision-facilitating information in hidden-action setups: an agent-based approach

Leitner

Wall

2020

J Econ Interact Coord

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The hidden-action model captures a fundamental problem of principal-agent theory and provides an optimal sharing rule when only the outcome but not the effort can be observed (Holmström in Bell J Econ 10(1):74, 1979). However, the hidden-action model builds on various explicit and also implicit assumptions about the information of the contracting parties. This paper relaxes key assumptions regarding the availability of information included in the hidden-action model in order to study whether and, if so, how fast the optimal sharing rule is achieved and how this is affected by the various types of information employed in the principal-agent relation. Our analysis particularly focuses on information about the environment and about feasible actions for the agent. We follow an approach to transfer closed-form mathematical models into agent-based computational models and show that the extent of information about feasible options to carry out a task only has an impact on performance if decision makers are well informed about the environment, and that the decision whether to perform exploration or exploitation when searching for new feasible options only affects performance in specific situations. Having good information about the environment, on the contrary, appears to be crucial in almost all situations.

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Simulation-based research in management accounting and control: an illustrative overview

Cited by 27 publications

References 114 publications

Beneficial Effects of Randomized Organizational Change on Performance

Beneficial Effects of Randomized Organizational Change on Performance

Understanding Longitudinal Dynamics of Recommender Systems with Agent-Based Modeling and Simulation

Decision-facilitating information in hidden-action setups: an agent-based approach

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