The objective of this study is trying to develop a comprehensive model referring to previous research of Hwang and Griffith's model of intention to participate in Collaborative Consumption (CC). The study applied exploratory research design which implements previous researches regarding online collaborative consumption focusing on a study by Hwang and Griffith. Hwang and Griffith's model of intention to participate in Collaborative Consumption (CC) is unique in that it recognizes both attitudes and sympathy as the primary predictors of the intention to use the CC platform. The model is also relevant to CC as it encompasses different values, which are utilitarian, hedonic and symbolic. This Study results in a comprehensive model which incorporating several variables from previous studies, such as online initial trusts and perceived behavioral control. We conclude that by trying to put Technology Acceptance Model (TAM) and The Unified Theory of Acceptance and Use of Technology (UTAUT) will enrich the global-scale model from the higher point of view besides the cognitive perception itself. Moreover, this conceptual model is developed as a suggestion for future research as well as the implementation of more sophisticated statistical analysis method should be included.
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.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.