Research Article
Counterbalancing Asymmetric Information: A Process Driven Systems Thinking Approach to Information Sharing of Decentralized Databases
@INPROCEEDINGS{10.1007/978-3-030-67101-3_18, author={Mark Hoksbergen and Johnny Chan and Gabrielle Peko and David Sundaram}, title={Counterbalancing Asymmetric Information: A Process Driven Systems Thinking Approach to Information Sharing of Decentralized Databases}, proceedings={Context-Aware Systems and Applications, and Nature of Computation and Communication. 9th EAI International Conference, ICCASA 2020, and 6th EAI International Conference, ICTCC 2020, Thai Nguyen, Vietnam, November 26--27, 2020, Proceedings}, proceedings_a={ICCASA \& ICTCC}, year={2021}, month={1}, keywords={Information asymmetry Transactions Decision making Integrated decentralized databases Real estate Disruption System dynamic models}, doi={10.1007/978-3-030-67101-3_18} }- Mark Hoksbergen
Johnny Chan
Gabrielle Peko
David Sundaram
Year: 2021
Counterbalancing Asymmetric Information: A Process Driven Systems Thinking Approach to Information Sharing of Decentralized Databases
ICCASA & ICTCC
Springer
DOI: 10.1007/978-3-030-67101-3_18
Abstract
This paper explores asymmetric information and how to counterbalance it. It utilizes the case study of a hypothetical company called “Hashable”. The purpose of this case study is to exemplify a proposed solution to address the information asymmetry faced by buyers of residential real estate in New Zealand. A procedural response is provided for organizing the information needed to make an informed decision on purchasing a property. A causal loop diagram is introduced to develop an understanding of the various stakeholders involved in the proposed solution and their interaction with the information they provide. This paper highlights the core problems regarding information asymmetry within a transaction. It also provides procedural and technological solutions to counterbalance this information asymmetry while simultaneously reducing information costs and increasing reliability of the information provided.
