Determining response time factors of emergency medical services during the COVID-19 pandemic

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Nur Budi Mulyono ◽  
Noorhan Firdaus Pambudi ◽  
Lukni Burhanuddin Ahmad ◽  
Akbar Adhiutama
Keyword(s):  
Response Time ◽  
Medical Service ◽  
Traffic Density ◽  
Contributing Factors ◽  
Agent Based Simulation ◽  
Coverage Area ◽  
Content Type ◽  
Agent Based ◽  
Medical Response ◽  
Emergency Medical

PurposeThe lack of studies about the response time of emergency medical service during the coronavirus disease 2019 (COVID-19) pandemic in a dense city of a developing country has triggered this study to explore the factors contributing to a high response time of ambulance service to reach patients in need. An evaluation of contributing factors to the response time is necessary to guide decision-makers in keeping a high service level of emergency medical service.Design/methodology/approachThis research employed an agent-based modeling approach with input parameters from interviews with emergency medical service staff in Bandung city, Indonesia. The agent-based model is established to evaluate the relevant contribution of the factors to response time reduction using several scenarios.FindingsAccording to agent-based simulation, four factors contribute to the response time: the process of preparing crew and ambulance during the pandemic, coverage area, traffic density and crew responsiveness. Among these factors, the preparation process during the pandemic and coverage area significantly contributed to the response time, while the traffic density and crew responsiveness were less significant. The preparation process is closely related to the safety procedure in handling patients during the COVID-19 pandemic and normal time. The recommended coverage area for maintaining a low response time is 5 km, equivalent to six local subdistricts.Research limitations/implicationsThis study has explored the factors contributing to emergency medical response time. The insignificant contribution of the traffic density showed that citizens, in general, have high awareness and compliance to traffic priority regulation, so crew responsiveness in handling ambulances is an irrelevant factor. This study might have different contributing factors for less dense population areas and focuses on public emergency medical services provided by the local government.Practical implicationsThe local government must provide additional funding to cover additional investment for ambulance, crew and administration for the new emergency service deployment point. Exercising an efficient process in ambulance and crew preparation is mandatory for each emergency deployment point.Originality/valueThis study evaluates the contributing factors of emergency medical response time in the pandemic and normal situation by qualitative analysis and agent-based simulation. The performance comparison in terms of medical response time before and after COVID-19 through agent-based simulation is valuable for decision-makers to reduce the impact of COVID-19.

Modeling Consumer Decisions on Returning End-of-Use Products Considering Design Features and Consumer Interactions: An Agent Based Simulation Approach

2015 ◽  
Author(s):  
Ardeshir Raihanian Mashhadi ◽  
Behzad Esmaeilian ◽  
Sara Behdad
Keyword(s):  
Electronic Waste ◽  
Peer Pressure ◽  
Waste Stream ◽  
Contributing Factors ◽  
Agent Based Simulation ◽  
Design Features ◽  
Agent Based ◽  
Consumer Decisions ◽  
Take Back ◽  
The Impact

As electronic waste (e-waste) becomes one of the fastest growing environmental concerns, remanufacturing is considered as a promising solution. However, the profitability of take back systems is hampered by several factors including the lack of information on the quantity and timing of to-be-returned used products to a remanufacturing facility. Product design features, consumers’ awareness of recycling opportunities, socio-demographic information, peer pressure, and the tendency of customer to keep used items in storage are among contributing factors in increasing uncertainties in the waste stream. Predicting customer choice decisions on returning back used products, including both the time in which the customer will stop using the product and the end-of-use decisions (e.g. storage, resell, through away, and return to the waste stream) could help manufacturers have a better estimation of the return trend. The objective of this paper is to develop an Agent Based Simulation (ABS) model integrated with Discrete Choice Analysis (DCA) technique to predict consumer decisions on the End-of-Use (EOU) products. The proposed simulation tool aims at investigating the impact of design features, interaction among individual consumers and socio-demographic characteristics of end users on the number of returns. A numerical example of cellphone take-back system has been provided to show the application of the model.

An agent-based simulation model for IING’s adoption from a perspective of kinetic energy and potential energy

Kybernetes ◽  
2018 ◽  
Vol 47 (3) ◽  
pp. 605-635 ◽  
Author(s):  
Li Wang ◽  
Qingpu Zhang
Keyword(s):  
Decision Making ◽  
Kinetic Energy ◽  
Potential Energy ◽  
Agent Based Simulation ◽  
Content Type ◽  
Agent Based ◽  
Factors Influencing ◽  
Social Physics ◽  
Physical Energy ◽  
Energy Theory

Purpose Internet-based intangible network good (IING) has revolutionized multiple industries in recent years. This paper aims to reveal the laws of consumer’s decision-making on IING from a perspective of kinetic energy and potential energy. Design/methodology/approach In this paper, 4 aspects and 17 factors influencing IING adoption were generalized. Based on the theory of social physics, an agent-based simulation model, introducing physical energy theory to depict consumer’s decision-making, was built. An agent’s kinetic energy reflects the agent’s perceived effect of mass media on the agent’s decision-making on IING adoption. An agent’s potential energy reflects the agent’s perceived effect of social interactions on the agent’s decision-making on the adoption of IING. An agent’s final energy is the sum of the kinetic energy and potential energy, which reflects the agent’s final decision. Findings Some factors mainly influence the diffusion velocity, while other factors have a dramatic impact on both diffusion velocity and diffusion scale. The agent’s personality can make a difference at the early and middle stages of IING adoption, but a faint impact at the later stage because of the effects of network externalities and word of mouth. There is a critical value of the number of initial adopters which can dramatically speed up IING adoption. Practical implications This study provides new insights for firms on the effects of factors influencing consumers’ decision-making on IING adoption. Originality/value This paper defines a new kind of innovation, IING, and generalizes IING’s special characteristics. As a new application of social physics, the physical energy theory has been creatively introduced to depict consumer’s decision-making on IING adoption. A kinetic and potential energy model of IING adoption has been built. Based on simulation experiments, new insights of IING adoption have been gained.

Factors Influencing the Emergency Medical Service Response Time for Cardiovascular Disease in Guangzhou, China

2019 ◽  
Vol 39 (3) ◽  
pp. 463-471
Author(s):  
Xiao-qian Chen ◽  
Zi-feng Liu ◽  
Shi-kun Zhong ◽  
Xing-tang Niu ◽  
Yi-xiang Huang ◽  
...  
Keyword(s):  
Cardiovascular Disease ◽  
Response Time ◽  
Emergency Medical Service ◽  
Medical Service ◽  
Factors Influencing ◽  
Emergency Medical ◽  
Service Response Time

Time, island and ambulance type characteristics of patient transfers from two Turkish islands

2019 ◽  
Vol 9 (1) ◽  
pp. 47-55
Author(s):  
Cuneyt Caliskan ◽  
K. Hakan Altintas
Keyword(s):  
Emergency Medical Service ◽  
Medical Service ◽  
Helicopter Emergency Medical Service ◽  
Cross Sectional ◽  
Content Type ◽  
Patient Transfers ◽  
Patient Registration ◽  
Emergency Medical ◽  
Ground Ambulance ◽  
Ground Ambulances

Purpose The purpose of this paper is to evaluate the time, place and ambulance types specified on the ambulance patient registry forms for cases transferred through 112 EMS in the Bozcaada and Gökçeada island districts of the province of Çanakkale. Design/methodology/approach The universe of the descriptive – cross-sectional epidemiological study was composed of the ambulance patient registration forms of the cases which were transferred from Bozcaada and Gökçeada islands between January 1, 2009 and December 31, 2013. Findings Of the transfers made, 28.1 percent were in the year 2012, 39.5 percent were in summer, 16.6 percent were in July, 17.9 percent were on Monday, 37.1 percent were between 12.00 and 17.59 h and 61.5 percent were from Gökçeada island. Ground ambulances were more common in the transfers from Bozcaada island, while ambulance boat and helicopter ambulance were more common for transfers from Gökçeada island. Helicopter-Emergency Medical Service (HEMS) (p<0.001), which is commonly preferred for patient transfers, inversely affects the use of Ambulance Boat-Emergency Medical Service (BEMS) and ground ambulances. Transfers from Bozcaada island were found to be shorter in duration, and the number of transfers from Bozcaada island between 00.00 and 05.59 h were found to be higher than from Gökçeada island (p<0.001), while the number of transfers via ground ambulance between 00.00 and 05.59 h were found to be higher than the other ambulance types (p<0.001). Practical implications This study reveals the current state of the various referral routes from the islands. Originality/value This paper is the first study to demonstrate the characteristics of patients referred from the island belongs to Turkey.

A new agent-based simulation model of bilateral negotiation

2019 ◽  
Vol 31 (1) ◽  
pp. 115-148
Author(s):  
Frieder Lempp
Keyword(s):  
Simulation Model ◽  
Computational Models ◽  
Future Research ◽  
Bilateral Negotiation ◽  
Agent Based Simulation ◽  
Diverse Range ◽  
Content Type ◽  
Agent Based ◽  
Negotiation Strategies ◽  
Negotiation Research

Purpose The purpose of this paper is to introduce a new agent-based simulation model of bilateral negotiation based on a synthesis of established theories and empirical studies of negotiation research. The central units of the model are negotiators who pursue goals, have attributes (trust, assertiveness, cooperativeness, creativity, time, etc.) and perform actions (proposing and accepting offers, exchanging information, creating value, etc). Design/methodology/approach Methodologically, the model follows the agent-based approach to modeling. This approach is chosen because negotiations can be described as complex, non-linear systems involving autonomous agents (i.e. the negotiators), who interact with each other, pursue goals and perform actions aimed at achieving their goals. Findings This paper illustrates how the model can simulate experiments involving variables such as negotiation strategy, creativity, reservation value or time in negotiation. An example simulation is presented which investigates the main and interaction effects of negotiators’ reservation value and their time available for a negotiation. A software implementation of the model is freely accessible at https://tinyurl.com/y7oj6jo8. Research limitations/implications The model, as developed at this point, provides the basis for future research projects. One project could address the representation of emotions and their impact on the process and outcome of negotiations. Another project could extend the model by allowing negotiators to convey false information (i.e. to bluff). Yet another project could be aimed at refining the routines used for making and accepting offers with a view to allow parties to reach partial settlements during a negotiation. Practical implications Due to its broad scope and wide applicability, the model can be used by practitioners and researchers alike. As a decision-support system, the model allows users to simulate negotiation situations and estimate the likelihood of negotiation outcomes. As a research platform, it can generate simulation data in a cost- and time-effective way, allowing researchers to simulate complex, large-N studies at no cost or time. Originality/value The model presented in this paper synthesizes in a novel way a comprehensive range of concepts and theories of current negotiation research. It complements other computational models, in that it can simulate a more diverse range of negotiation strategies (distributive, integrative and compromise) and is applicable to a greater variety of negotiation scenarios.

Mitigating sustainability risk in supplier populations: an agent-based simulation study

2020 ◽  
Vol 40 (7/8) ◽  
pp. 897-920 ◽  
Author(s):  
Sara Hajmohammad ◽  
Anton Shevchenko
Keyword(s):  
Experimental Data ◽  
Population Ecology ◽  
Management Strategies ◽  
Population Level ◽  
High Rate ◽  
Business Practices ◽  
Effective Population ◽  
Agent Based Simulation ◽  
Content Type ◽  
Agent Based

PurposeMany modern firms strive to become sustainable. To this end, they are required to improve not only their own environmental and social performance but also the performance of their suppliers. Building on population ecology theory, we explore how buyers' exposure to supplier sustainability risk and their subsequent risk management strategies at the buyer–supplier dyad level can lead to adherence to sustainability by the supplier populations.Design/methodology/approachWe rely on a bottom-up research design, in which the actions of buyers within buyer–supplier dyads lead to population-wide changes on the supplier side. Specifically, we use experimental data on managing sustainability risk to build an agent-based simulation model and assess the effect of evolutionary processes on the presence of sustainable/unsustainable business practices in the supplier population.FindingsOur findings suggest that buyers' cumulative actions in managing sustainability risk do not necessarily result in effective population-wide improvements (i.e. at a high rate and to a high degree). For example, in high risk impact conditions, the buyer population is usually able to decrease the population level risk in a long run, but they would need both power and resources for quickly achieving such improved outcomes. Importantly, this positive change, in most cases, is due to the fact that the buyer population selects out the suppliers with high probability of misconduct (i.e. decreased supplier population density).Originality/valueDrawing on the organizational population ecology theory, we explore when, to what degree and how quickly the buyers' cumulative efforts can lead to population-wide changes in the level of supplier sustainability risk, as well as the composition and density of supplier population. Methodologically, this paper is one of the first studies which use a combination of experimental data and agent-based modeling to offer more valuable insights on supply networks.

scholarly journals Improving bystander defibrillation in out-of-hospital cardiac arrests at home

2020 ◽  
Vol 9 (4_suppl) ◽  
pp. S74-S81
Author(s):  
Lena Karlsson ◽  
Carolina M Hansen ◽  
Christina Vourakis ◽  
Christopher LF Sun ◽  
Shahzleen Rajan ◽  
...  
Keyword(s):  
Response Time ◽  
Emergency Medical Service ◽  
Medical Service ◽  
Automated External Defibrillator ◽  
Automated External Defibrillators ◽  
Bystander Activation ◽  
Emergency Medical ◽  
Service Response Time ◽  
External Defibrillator ◽  
At Home

Aims: Most out-of-hospital cardiac arrests occur at home with dismal bystander defibrillation rates. We investigated automated external defibrillator coverage of home arrests, and the proportion potentially reachable with an automated external defibrillator before emergency medical service arrival according to different bystander activation strategies. Methods and results: Cardiac arrests in homes (private/nursing/senior homes) in Copenhagen, Denmark (2008–2016) and registered automated external defibrillators (2007–2016), were identified. Automated external defibrillator coverage (distance from arrest to automated external defibrillator) and accessibility at the time of arrest were examined according to route distance to nearest automated external defibrillator and emergency medical service response time. The proportion of arrests reachable with an automated external defibrillator by bystander was calculated using two-way (from patient to automated external defibrillator and back) and one-way (from automated external defibrillator to patient) potential activation strategies. Of 1879 home arrests, automated external defibrillator coverage ≤100 m was low (6.3%) and a two-way bystander could potentially only retrieve an accessible automated external defibrillator before emergency medical service in 31.1% ( n=37) of cases. If a bystander only needed to travel one-way to bring an automated external defibrillator (≤100 m, ≤250 m and ≤500 m), 45.4% ( n=54/119), 37.1% ( n=196/529) and 29.8% ( n=350/1174) could potentially be reached before the emergency medical service based on current automated external defibrillator accessibility. Conclusions: Few home arrests were reachable with an automated external defibrillator before emergency medical service if bystanders needed to travel from patient to automated external defibrillator and back. However, nearly one-third of arrests ≤500 m of an automated external defibrillator could be reached before emergency medical service arrival if the bystander only needed to travel one-way from the automated external defibrillator to the patient.

On the contributions and the validation of an agent-based simulation model of innovation diffusion

2016 ◽  
Vol 50 (3/4) ◽  
pp. 647-657 ◽  
Author(s):  
Mohammad G. Nejad
Keyword(s):  
Simulation Modeling ◽  
Agent Based Modeling ◽  
Test Theory ◽  
Future Research ◽  
Agent Based Simulation ◽  
Content Type ◽  
Agent Based ◽  
Points Of View ◽  
Complex Phenomena ◽  
Specific Paper

Purpose This paper provides an overview of agent-based modeling and simulation (ABMS) and evaluates the questions that have been raised regarding the “assumptions and mechanisms used” by a well-cited paper that has used this methodology. Design/methodology/approach This work provides a review of agent-based simulation modeling and its capabilities to advance and test theory. The commentary then evaluates and addresses the raised questions and reservations. Findings Agent-based modeling offers unique capabilities that can be used to explore complex phenomena in business and marketing. Some of the raised reservations may be considered as directions for future research. However, the criticisms are for most part unsupported by existing research and do not undermine the contributions of the paper that is being discussed. Practical implications Given its relative novelty, reservations regarding agent-based simulation modeling are quite natural. Discussions like this one would bring together different points of view and lead to a better understanding of how using ABMS can benefit academia and industry. Originality/value This commentary is part of an intellectual dialogue that seeks to provide different points of view about agent-based simulation modeling using a specific paper as an example.

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