No abstract

No abstract

Online group purchasing or collective purchasing is the activity in which people who desire to buy the same merchandises join together so that they can negotiate with sellers for a better price through Internet. This paper utilizes fuzzy logic to develop a bargaining model for such activities. The model supports buyers to make group decision to set up their bargaining strategy; instead of using static rules, buyers can customize their fuzzy rule base that can infer to produce negotiation proposals to bargain with sellers. Experimental results show that (1) the prototype system with the fuzzy function is easy to use; (2) people enjoy online bargaining for better prices; (3) they think that online bargaining is very important and inevitable for electronic markets in the future.

Abstract. Recently, with the rise of crowdsourcing, the concept that problems can only be solved by known experts has gradually been replaced. More and more people try to solve the problems via crowdsourcing, with not only efficiency but also inexpensiveness. In this research, we develop a nearby expert discovering mechanism by combining mobile intelligence and social community, and taking crowd wisdom, context, and social impacts into considered. The proposed system allows users to find nearby people whom have certain expertise in handling with difficult problems in real-time via a mobile device.