Agent-based Simulation Design for Technology Adoption

Christensen, Kristoffer; Ma, Zheng; Varbak, Magnus; Demazeau, Yves; Jôrgensen, Bo Nørregaard

doi:10.1109/sii46433.2020.9025823

Cited by 4 publications

(5 citation statements)

References 8 publications

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“…Adoption means that consumers make full use of the innovation (Christensen, et al, 2020). In the retail payment ecosystem representation, rCBDC adoption occurs as consumers buy goods and services from merchants (C2M) and as consumers make transfers among themselves (C2C) with rCBDC.…”

Section: The Methodologymentioning

confidence: 99%

“…Likewise, tightly related to the adoption of a new form of money and payment instrument, ABM has been applied to studying the adoption of new consumer technologies (i.e., innovation diffusion) in social systems (see Bonabeau, 2002, Alexandrova-Kabadjova, et al, 2012, Rai & Robinson, 2015, Moglia, et al, 2018, Christensen, et al, 2020, Novizayanti, et al, 2021, Pakravan & MacCarty, 2021, Klioutchnikov, et al, 2022.…”

Section: Literature Reviewmentioning

confidence: 99%

“…We present the data we used for calibrating the digital twin, along with the calibration and scenarios designed to simulate the adoption of the rCBDC and the main results. Consistent with the concept of adoption as full use of the innovation (Christensen, et al, 2020), we focus on how payments were made.…”

Section: A Retail Payment Ecosystem Digital Twinmentioning

confidence: 99%

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Simulating the Adoption of a Retail CBDC

León,

Moreno,

Soramäki

2024

Jahrbücher Für Nationalökonomie Und Statistik

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We use agent-based modelling to build a digital twin of the retail payment system, where heterogeneous consumers and merchants interact, learn, and adapt as they meet and use different monies and payment instruments. As we introduce an rCBDC, the model simulates its adoption. We calibrate this digital twin to Spain’s retail payment ecosystem. We run hypothetical scenarios that correspond to public discussions about the digital euro. Results show that introducing an rCBDC without attractive design options and stimulus results in low and slow adoption. Results suggest that the reverse waterfall functionality, a positive remuneration spread, and the distribution of government subsidies via rCBDC are effective in fostering adoption; yet, the distribution of government subsidies via rCBDC is the only one that creates incentives to reduce the use of cash. Balance limits and top-up limits are effective in restraining adoption. Results also suggest that combining design options and stimulus with limits to holding rCBDCs could aid in achieving a sweet spot of adoption.

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Section: The Methodologymentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

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Simulating the Adoption of a Retail CBDC

León,

Moreno,

Soramäki

2024

Jahrbücher Für Nationalökonomie Und Statistik

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“…Ma et al (2019b) conducts a survey to investigate demand response control preferences, stakeholder engagement, and cross-national differences for retail stores' demand response adoption. Furthermore, technology evaluation and adoption of energy related solutions has been conducted with modeling and simulations, and applied for both energy efficiency (Christensen et al 2020a(Christensen et al , 2019 energy flexibility (Vaerbak et al 2019;Christensen et al 2020b), and CO2 emission reduction (Christensen et al 2020c).…”

Section: Technology Adoption Theories and Modelsmentioning

confidence: 99%

Ecosystem-driven business opportunity identification method and web-based tool with a case study of the electric vehicle home charging energy ecosystem in Denmark

Christensen

Rasmussen

et al. 2022

Energy Inform

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Understanding the local needs and challenges is critical for technology adoption in the energy sector. However, it is still a big challenge for most ecosystem stakeholders. Furthermore, technology adoption theories have mainly focused on the technology itself, and the business ecosystem perspective has been neglected. Therefore, this paper proposes an ecosystem-driven business opportunity identification method, a systematic approach for ecosystem stakeholders to conduct business opportunity analysis and evaluation based on the CSTEP ecosystem analysis and evaluation method. This method includes four correlated steps: Step 1: Identify the five CSTEP dimensions of the business ecosystem; Step 2: Identify potential changes in the business ecosystem; Step 3: Identify future ecosystem trends and timeline; Step 4: Select business opportunities; and Step 5: Potential solution identification. A web-based tool called opportunity identifier is developed for implementing the proposed method. A case study of the electric vehicle (EV) home charging energy ecosystem in Denmark is applied and demonstrates the application of the proposed method and the implementation of the developed web-based tool. Three value propositions are identified in the case study: (1) EV users can have optimal EV charging cost and optimal CO2 emission consumption with the intelligent EV charging algorithms that consider electricity prices, tariffs, and CO2 emission; (2) DSOs can avoid grid overloads and postpone the grid upgrade by applying intelligent EV charging algorithms; (3) Independent aggregators can aggregate EVs and participate in the ancillary service market or provide Vehicle-to-Grid services by using intelligent EV charging algorithms. Moreover, three feasible decentralized EV charging strategies (Real Time Pricing, Time-of-Use Pricing, and Timed charging) are identified as the potential solutions targeting the first value proposition.

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“…The model depicts the adoption process of the recommendation system in the form of an App. ABM has been used to study the adoption process of new technology in fields such as smart energy ( Christensen, Ma, Varbak, Demazeau, & Jorgensen, 2020 ), health systems ( Pardo & Coronado, 2016 ), business model ( Basingab et al, 2017 ), and telecommunications ( Jahng & Park, 2020 ). The adoption process in this work is based on the dynamic trust model of ( Choi & Nazareth, 2014 ).…”

Section: Proposalmentioning

confidence: 99%

Crowd management COVID-19

Polanco¹,

Siller²

2021

Annual Reviews in Control

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Crowds are a source of transmission in the COVID-19 spread. Contention and mitigation measures have focused on reducing people’s mass gathering. Such efforts have led to a drop in the economy. The application of a vaccine at a world level represents a grand challenge for humanity, and it is not likely to accomplish even within months. In the meantime, we still need tools to allow the people integration into their regular routines reducing the risk of infection. In this context, this paper presents a solution for crowd management. The aim is to monitor and manage crowd levels in interior places or point-of-interests (POI), particularly shopping centers or stores. The solution is based on a POI recommendation system that suggests the nearest safe options upon request of a particular POI to visit by the user. In this sense, it recommends places near the user location with the least estimated crowd. The recommendation algorithm uses a top-K approach and behavioral game theory to predict the user’s choice and estimate the crowd level for the requested POI. To evaluate the efficiency of this technological intervention in terms of the potential number of contacts of possible COVID-19 infections and the recommendation quality, we have developed an agent-based model (ABM). The adoption level of new technologies can be related to the end-user experience and trust in such technologies. As the end-user follows a recommendation that leads to uncrowded places, both the end-user experience and trust increased. We study and model this process using the OCEAN model of personality. The results from the studied scenarios showed that the proposed solution is widely adopted by the agents, as the trust factor increased from 0.5 (initial set value) to 0.76. In terms of crowd level, these are effectively managed and reduced on average by 40%. The mobility contacts were reduced by 40%, decreasing the risk of COVID-19 infection. An APP has been designed to support the described crowd management and contact tracing functionality. This APP is available on GitHub.

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Agent-based Simulation Design for Technology Adoption

Cited by 4 publications

References 8 publications

Simulating the Adoption of a Retail CBDC

Simulating the Adoption of a Retail CBDC

Ecosystem-driven business opportunity identification method and web-based tool with a case study of the electric vehicle home charging energy ecosystem in Denmark

Crowd management COVID-19

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