GREENCOMMUTE： AN INFLUENCE-AWARE PERSUASIVE RECOMMENDATION APPROACH FOR PUBLIC-FRIENDLY COMMUTE OPTIONS

作     者：Shiqing Wu Quan Bai Sotsay Sengvong 

作者机构：School of Engineering Computer and Mathematical Sciences Auckland University of Technology New Zealand 

出 版 物：《Journal of Systems Science and Systems Engineering》 (系统科学与系统工程学报（英文版）)

年 卷 期：2018年第27卷第2期

页      面：250-264页

核心收录：

学科分类：0821[工学-纺织科学与工程] 12[管理学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 08[工学] 081201[工学-计算机系统结构] 082103[工学-纺织化学与染整工程] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：FP7 Health(A005965  AA013521) 

主　　题：Recommendation system agent-based modelling social influence reward public transport 

摘      要：Negative impacts produced by transportation sector have increased in parallel with the increase of urban mobility. In this paper, we introduce GreenCommute, a novel recommendation system which can facilitate commuters to take public fi＇iendly commute options, while provide support to alleviate the external cost in society, such as traffic pollution, congestion and accidents. In the meanwhile, a rewarding mechanism for persuading commuters is embedded in the proposed approach for balancing the conflict between personal needs and social aims. The allocation of reward values also takes users＇ influential degrees in the social network into consideration. Experimental results show that the GreenCommute can promote public friendly commute options more effectively in comparison to the traditional recommendation system.