Serviceology Education Community Based on Social Networking Service

2014 ◽  
Vol 614 ◽  
pp. 513-516
Author(s):  
Feng Ding ◽  
Yu Liu

Since service science is becoming more popular, many universities or companies have now set up numbers of groups to attract researches. In this paper we will introduce a new platform, which based on a Personalized Service System, aiming at real-time information exchange.

2013 ◽  
Vol 10 (2) ◽  
pp. 747-765 ◽  
Author(s):  
Hae-Duck Jeong ◽  
Jiyoung Lim ◽  
WooSeok Hyun ◽  
Arisu An

Smartphone usage and data consumption have been sharply rising, and the disabled have also become smartphone users as the number of users of these phones has exponentially increased in recent years. The theme of this paper is how to create a better world for the disabled using the information that people want to exchange with each other between the disabled and the general population. The main goal is also to provide the information that they need from each other in a way that can be displayed on the map in real-time. We propose a new location-based SNS application for the disabled population (except those who are visually impaired or the disabled who are not able to use a smartphone) with three major characteristics of this application to be considered as follows: (i) the person uses a Social Networking Service (SNS) by constructing a friend matching system such as Facebook or Twitter, which are the most widelyused SNS in the world; (ii) the general population registers real-time information for a specific location on the map for the disabled population using SNS. This information with photos and messages is given and evaluated by users; and (iii) this system makes it easier to see that the menu in the GUI was implemented.


2003 ◽  
Vol 1854 (1) ◽  
pp. 152-161 ◽  
Author(s):  
Jinghua Xu ◽  
Kathleen L. Hancock ◽  
Frank Southworth

A simulation model called Trade and Transportation Multinetworks (TTMNet), constructed for the purpose of studying the effects of highly developed information technologies and logistic strategies (e.g., electronic commerce and real-time information) on freight transportation, is described. TTMNet is formulated as a multilevel product supply chain system that integrates the financial, informational, logistical, and physical aspects of transportation networks and allows interactions between each of these networks. Several simulators, including a freight traffic simulator, a supply chain decision-making simulator, and a pseudo-real-time information simulator, are involved. The freight traffic simulation is the focus of the present study. As part of this simulator, a learning model is set up to help decision makers estimate transportation costs on the basis of past experiences. Given the stochastic nature of these transportation costs and of the freight demands simulated by the system, the route for an origin–destination shipment may not remain optimal during a trip and may change along the way. A vehicle redirection procedure that handles this is presented. A numerical example is designed to compare a set of freight movements under two scenarios, one supported by and the other not supported by pseudo-real-time information on traffic conditions.


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