Authors:
Hazleen Aris
and
Marina Md Din
Affiliation:
Universiti Tenaga Nasional, Malaysia
Keyword(s):
Mobile Crowdsourcing, Price Comparison, Information Sharing Model, Information Solicitation Model.
Related
Ontology
Subjects/Areas/Topics:
Agents
;
Artificial Intelligence
;
Biomedical Engineering
;
Distributed and Mobile Software Systems
;
Health Engineering and Technology Applications
;
Health Information Systems
;
Mobile Software and Services
;
Mobile Technologies
;
Mobile Technologies for Healthcare Applications
;
Neural Rehabilitation
;
Neurotechnology, Electronics and Informatics
;
Pervasive Computing
;
Software Engineering
;
Telecommunications
;
Web-Based Software Development
;
Wireless Information Networks and Systems
Abstract:
The increase in goods prices year after year has directly affected consumer expenditures. Survey from a number of countries showed that the average household expenditures had also increased, notably in the past two years. One way to alleviate the impact of the rise in goods prices is by being more selective in buying the items. Being selective means buying the items at the stores that offer the lowest prices. To do that, a mechanism to compare the prices of items between stores is needed, in which, the local pricewatch information solicitation and sharing (LoPrice) model was proposed. The challenge to the design of such model is in the choice of suitable approach for collecting the information on prices from different stores in a timely manner. In this paper, mobile crowdsourcing is proposed to be the approach that is able to address the challenge. Review on existing price comparison applications, including their advantages and disadvantages is also included. An exploratory survey wa
s also performed, which revealed that the use of mobile crowdsourcing is able to provide timely information solicitation and sharing of prices.
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