Perceived quality is consumers’subjective perceptions of a product’s attributes,which directly influences the overall evaluation of the product.Existing research has suggested that the perceived quality of attribute...Perceived quality is consumers’subjective perceptions of a product’s attributes,which directly influences the overall evaluation of the product.Existing research has suggested that the perceived quality of attributes has an asymmetric effect on the overall evaluation,but limited research has been conducted on this asymmetric effect in the automobile industry and the moderating effect of sentiment.This paper investigates the asymmetric effect of perceived quality on overall evaluation using social media data from the automobile industry.First,the asymmetric effect of perceived quality on overall evaluation was identified for different attributes using penalty-reward contrast analysis(PRCA),and attribute classification was realized by calculating the IA index,i.e.,Appearance is an excitement attribute and the remaining attributes are basic attributes.Second,the differences in the asymmetric effects of each attribute category were analyzed,and the basic attributes were found to have a greater effect on the overall evaluation,with a positive moderating effect of sentiment on the effect.This study contributes to perceived quality research as well as consumer evaluation research and provides manufacturers with a prioritization method for attribute improvement.展开更多
Existing Web service selection approaches usually assume that preferences of users have been provided in a quantitative form by users. However, due to the subjectivity and vagueness of preferences, it may be impractic...Existing Web service selection approaches usually assume that preferences of users have been provided in a quantitative form by users. However, due to the subjectivity and vagueness of preferences, it may be impractical for users to specify quantitative and exact preferences. Moreover, due to that Quality of Service (QoS) attributes are often interrelated, existing Web service selection approaches which employ weighted summation of QoS attribute values to compute the overall QoS of Web services may produce inaccurate results, since they do not take correlations among QoS attributes into account. To resolve these problems, a Web service selection framework considering user's preference priority is proposed, which incorporates a searching mechanism with QoS range setting to identify services satisfying the user's QoS constraints. With the identified service candidates, based on the idea of Principal Component Analysis (PCA), an algorithm of Web service selection named PCA-WSS (Web Service Selection based on PCA) is proposed, which can eliminate the correlations among QoS attributes and compute the overall QoS of Web services accurately. After computing the overall QoS for each service, the algorithm ranks the Web service candidates based on their overall QoS and recommends services with top QoS values to users. Finally, the effectiveness and feasibility of our approach are validated by experiments, i.e. the selected Web service by our approach is given high average evaluation than other ones by users and the time cost of PCA-WSS algorithm is not affected acutely by the number of service candidates.展开更多
基金supported in part by the National Natural Science Foundation of China under Grant No.71871041,and the China Scholarship Council under Grant No.202106060118.
文摘Perceived quality is consumers’subjective perceptions of a product’s attributes,which directly influences the overall evaluation of the product.Existing research has suggested that the perceived quality of attributes has an asymmetric effect on the overall evaluation,but limited research has been conducted on this asymmetric effect in the automobile industry and the moderating effect of sentiment.This paper investigates the asymmetric effect of perceived quality on overall evaluation using social media data from the automobile industry.First,the asymmetric effect of perceived quality on overall evaluation was identified for different attributes using penalty-reward contrast analysis(PRCA),and attribute classification was realized by calculating the IA index,i.e.,Appearance is an excitement attribute and the remaining attributes are basic attributes.Second,the differences in the asymmetric effects of each attribute category were analyzed,and the basic attributes were found to have a greater effect on the overall evaluation,with a positive moderating effect of sentiment on the effect.This study contributes to perceived quality research as well as consumer evaluation research and provides manufacturers with a prioritization method for attribute improvement.
基金Supported by the National Natural Science Foundation of China(No.90818004and61100054)Program for New Century Excellent Talents in University(No.NCET-10-0140)+1 种基金Excellent Youth Foundation of Hunan Scientific Committee(No.11JJ1011)Scientific Research Fundof Hunan Educational Committee(No.09K085and11B048)
文摘Existing Web service selection approaches usually assume that preferences of users have been provided in a quantitative form by users. However, due to the subjectivity and vagueness of preferences, it may be impractical for users to specify quantitative and exact preferences. Moreover, due to that Quality of Service (QoS) attributes are often interrelated, existing Web service selection approaches which employ weighted summation of QoS attribute values to compute the overall QoS of Web services may produce inaccurate results, since they do not take correlations among QoS attributes into account. To resolve these problems, a Web service selection framework considering user's preference priority is proposed, which incorporates a searching mechanism with QoS range setting to identify services satisfying the user's QoS constraints. With the identified service candidates, based on the idea of Principal Component Analysis (PCA), an algorithm of Web service selection named PCA-WSS (Web Service Selection based on PCA) is proposed, which can eliminate the correlations among QoS attributes and compute the overall QoS of Web services accurately. After computing the overall QoS for each service, the algorithm ranks the Web service candidates based on their overall QoS and recommends services with top QoS values to users. Finally, the effectiveness and feasibility of our approach are validated by experiments, i.e. the selected Web service by our approach is given high average evaluation than other ones by users and the time cost of PCA-WSS algorithm is not affected acutely by the number of service candidates.
