scholarly journals Modeling and Simulation of Consumer Preference Decision for Commercial Complex Location Based on System Dynamics

2022 ◽  
Vol 2022 ◽  
pp. 1-10
Author(s):  
Bin Guo ◽  
Bing Zhang ◽  
Yang Li

The influencing factors of consumer shopping behavior play a key role in the later performance of commercial real estate enterprises. On the basis of analyzing the influence factors of customer patronage and the influence factors of commercial complex site selection decision and their relationship, a causal relationship graph and a system dynamic model are established, which can describe the influence of customer preference on commercial complex site selection decision. And introducing customer subjective factors optimize the original pure objective factors site selection decision model. The model is implemented by using the system dynamics modeling tool Vensim. At the same time, the model is verified by using the data of the first-hand investigation. The results show that the calculated data of the model is in good agreement with the actual data. The results show that the system dynamics method can effectively simulate the influence of various factors on the decision-making of the commercial complex. As the forecast of the model, the key indexes of the decision-making of the city commercial complex are discussed, and the measures to be taken are put forward, which can provide reference for the decision-making of the location.

Author(s):  
Xuesong Guo ◽  
Naim Kapucu

Abstract Participatory System Dynamics modeling is presented as a methodology to engage stakeholders in collaborative decision making in scenarios involving humanitarian logistics. Using the System Dynamics (SD) model, we simulated different scenarios, the results of which yielded factors that influence performance of humanitarian logistics. Once these were identified and discussed, different options on performance improvement were tested. This approach showed that the SD model can facilitate system thinking for stakeholders and form shared mental models critical to reaching consensus-based decisions in humanitarian logistics situations.


2009 ◽  
Vol 3 (3) ◽  
pp. 253-279 ◽  
Author(s):  
Robert Patterson ◽  
Lisa Fournier ◽  
Byron J. Pierce ◽  
Marc D. Winterbottom ◽  
Lisa M. Tripp

Two types of decision-making processes have been identified in the literature: an analytical process and an intuitive process. One conceptual model of the latter is the recognition-primed decision (RPD) model (e.g., Klein, 2008). According to this model, decision making in naturalistic contexts entails a situational pattern-recognition process that, if subsequent expectancies are confirmed, leads the decision maker to render a decision to engage in a given course of action. In this paper, we describe a system dynamics model of Klein's RPD framework that focuses upon the dynamics of the decision-making process. The structure of our RPD model is based on a model of a set of laboratory phenomena called conjunction benefits and costs (e.g., L. R. Fournier, Patterson, Dyre, Wiediger, & Winters, 2007), which was extended to encompass the RPD framework. The results of our simulations suggest that decision priming (a bias toward rendering a given decision based on prior information) is a phenomenon that should occur in many naturalistic settings.


Safety ◽  
2021 ◽  
Vol 7 (4) ◽  
pp. 75
Author(s):  
Guilherme Deola Borges ◽  
Angélica Muffato Reis ◽  
Rafael Ariente Neto ◽  
Diego Luiz de Mattos ◽  
André Cardoso ◽  
...  

Human–Robot Collaboration (HRC) systems are often implemented seeking for reducing risk of Work-related Musculoskeletal Disorders (WMSD) development and increasing productivity. The challenge is to successfully implement an industrial HRC to manage those factors, considering that non-linear behaviors of complex systems can produce counterintuitive effects. Therefore, the aim of this study was to design a decision-making framework considering the key ergonomic methods and using a computational model for simulations. It considered the main systemic influences when implementing a collaborative robot (cobot) into a production system and simulated scenarios of productivity and WMSD risk. In order to verify whether the computational model for simulating scenarios would be useful in the framework, a case study in a manual assembly workstation was conducted. The results show that both cycle time and WMSD risk depend on the Level of Collaboration (LoC). The proposed framework helps deciding which cobot to implement in a context of industrial assembly process. System dynamics were used to understand the actual behavior of all factors and to predict scenarios. Finally, the framework presented a clear roadmap for the future development of an industrial HRC system, drastically reducing risk management in decision-making.


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