作者机构：
[Chi, Maomao; Li, Weiqing] Cent China Normal Univ, Sch Informat Management, Wuhan 430079, Peoples R China.;[Dan, Qianyi] Cent China Normal Univ, Sch Comp, Wuhan 430079, Peoples R China.;[Wang, Weijun] Cent China Normal Univ, Key Lab Adolescent Cyberpsychol & Behav, Minist Educ, Wuhan 430079, Peoples R China.
通讯机构：
[Chi, Maomao; Wang, Weijun] C;Cent China Normal Univ, Sch Informat Management, Wuhan 430079, Peoples R China.;Cent China Normal Univ, Key Lab Adolescent Cyberpsychol & Behav, Minist Educ, Wuhan 430079, Peoples R China.
关键词：
consumer information search behavior;price level;perceived price dispersion;durables and consumables;moderating effect
摘要：
<jats:p>The methods consumers use to reduce their perceived risk and make reasonable purchase decisions can be synthesized under the umbrella term “consumer information search behavior” (CISB). As one key factor that conveys a product’s value and quality, price has a significant impact on CISB. There are few studies that comprehensively consider the impact of price level (PL) and perceived price dispersion (PPD) on CISB, and there is a certain disagreement about the impact of PPD specific to the online shopping environment. To address this research gap, we construct a model using the data from 5515 consumers’ purchasing and browsing behavior on a B2C e-commerce website, selecting six products as our research objects. We use a hierarchical regression analysis method to study the influence of product PL and PPD on CISB, and to explore the moderating effect of product categories (durables and consumables) on the relationship between PL, PPD and CISB. The results show that PL significantly affects CISB, and that product categories have a significant moderating effect on the relationship between PL and CISB. For durable goods, when the PL is high, consumers tend to increase their search behavior, both in depth and in breadth, and for consumables with low PL but higher purchase frequency, consumers likewise tend to increase their search behavior. In the B2C online shopping environment, PPD has a significant positive effect on CISB, and product category has a moderating effect on the relationship between PPD and CISB. When consumers purchase consumables, the higher the PPD, the higher the depth of CISB. The findings have several implications for marketing practitioners and enterprises advertising, also can help customers save time and energy in their search behaviors.</jats:p>
作者机构：
[Meiyu P.] School of Information Management, Central China Normal University, Wuhan, 430079, China;E-commerce Research Center of Hubei Province, Central China Normal University, Wuhan, 430079, China;[Weijun W.] Key Laboratory of Adolescent Cyberpsychology and Behavior, Ministry of Education, Central China Normal University, Wuhan, 430079, China;[Maomao C.] School of Information Management, Central China Normal University, Wuhan, 430079, China, E-commerce Research Center of Hubei Province, Central China Normal University, Wuhan, 430079, China
通讯机构：
[Maomao, C.] S;[Maomao, C.] E;E-commerce Research Center of Hubei Province, China;School of Information Management, China
期刊：
Journal of Advertising,2019年48(4):356-365 ISSN：0091-3367
通讯作者：
Wang, Weijun
作者机构：
[Deng, Shasha] Shanghai Int Studies Univ, Sch Business & Management, Management Informat Syst, Shanghai, Peoples R China.;[Deng, Shasha] Shanghai Int Studies Univ, Sch Business & Management, Artificial Intelligence & Data Sci Applicat Ctr, Shanghai, Peoples R China.;[Tan, Chee-Wee] Copenhagen Business Sch, Dept Digitizat, Frederiksberg, Denmark.;[Wang, Weijun] Cent China Normal Univ, Sch Psychol, Wuhan, Hubei, Peoples R China.;[Pan, Yu] Shanghai Int Studies Univ, Informat Management, Shanghai, Peoples R China.
通讯机构：
[Wang, Weijun] C;Cent China Normal Univ, Sch Psychol, Key Lab Adolescent Cyberpsychol & Behav, 152 Luoyu Rd, Wuhan 430079, Hubei, Peoples R China.
摘要：
Artificial intelligence in programmatic advertising constitutes fertile grounds for marketing communication with tremendous opportunities. Yet, despite its touted benefits, contemporary implementations of programmatic advertising do not harness self-generative technologies so much so that different consumers are exposed to identical content. Consequently, we advance a smart generation system of personalized advertising copy (SGS-PAC) that can automatically personalize advertising content to align with the needs of individual consumers. Analytical results from a user experiment involving about 80 subjects underscore that personalized advertising copies generated by SGS-PAC can bolster click rate in online advertising platforms. Findings from this study bear significant implications for the application of artificial intelligence in online advertising.
摘要：
<jats:p>With the development of national strategies (such as Industrial 4.0 and Made in China 2025), how to build digital enterprises and cultivate innovation capabilities of enterprises has become a critical problem to Chinese manufacturing enterprises. However, the literature on the specific path of information technology (IT) capabilities to the innovation of enterprises is still lacking a body of relevant empirical research. In particular, it has not yet thought to explore the information technology capabilities, digital transformation, and then innovation performance of manufacturing enterprises. By performing a questionnaire investigation for 138 Chinese manufacturing enterprises, this study adopted both a fuzzy-set qualitative comparative analysis (fsQCA) and structural equation modeling (SEM) to explore the set relations of the conjunctions and conditions and the statistical associations by studying the relationships among information technology capabilities, digital transformation and innovation performance. The results show that the positive impacts of information technology capabilities on the process innovation performance and the digital transformation, as well as the positive impacts of digital transformation on both process innovation performance and product innovation performance. Specifically, digital transformation takes on a new function of partial mediation of IT capabilities and process innovation performance, and digital transformation functions as a complete mediator for IT capabilities and product innovation performance. The combinations of causal recipes related to innovation performance are provided by a fuzzy-set qualitative comparative analysis (fsQCA). Through the analyses of SEM and fsQCA, this research develops the formation mechanisms of both process innovation performance and product innovation performance, and provides guidance for both IT and innovation management of manufacturing enterprises in China.</jats:p>
摘要：
Knowledge Base Question Answering (KBQA) is a hot research topic in natural language processing (NLP). The most challenging problem in KBQA is how to understand the semantic information of natural language questions and how to bridge the semantic gap between the natural language questions and the structured fact triples in knowledge base. This paper focuses on simple questions which can be answered by a single fact triple in knowledge base. We propose a topic enhanced deep structured semantic model for KBQA. The proposed method considers the task of KBQA as a matching problem between questions and the subjects and predicates in knowledge base. And the proposed model consists of two stages to match the subjects and predicates, respectively. In the first stage, we propose a Convolutional based Topic Entity Extraction Model (CTEEM) to extract topic entities mentioned in questions. With the extracted entities, we can retrieve the relevant candidate fact triples from knowledge base and obviously decrease the amount of noising candidates. In the second stage, we employ Deep Structured Semantic Models (DSSMs) to compute the semantic relevant score between questions and predicates in the candidates. And we combine the semantic level and the lexical level scores to rank the candidates. We evaluate the proposed method on KBQA dataset released by NLPCC-ICCPOL 2016. The experimental results show that our proposed method achieves the third place among the 21 submitted systems. Furthermore, we also extend the DSSM by using BiLSTM and integrate a convolutional structure on the top of BiLSTM layers. Our experimental results show that the extension models can further improve the performance.
作者机构：
Key Laboratory of Adolescent Cyberpsychology and Behavior, Ministry of Education, Central China Normal University, Wuhan 430079, China;Author to whom correspondence should be addressed.;School of Information Management, Central China Normal University, Wuhan 430079, China;[Ying Li; Tingting Zhang; Yinghui Huang; Hui Liu] School of Information Management, Central China Normal University, Wuhan 430079, China<&wdkj&>Key Laboratory of Adolescent Cyberpsychology and Behavior, Ministry of Education, Central China Normal University, Wuhan 430079, China;[Weijun Wang] Key Laboratory of Adolescent Cyberpsychology and Behavior, Ministry of Education, Central China Normal University, Wuhan 430079, China<&wdkj&>Author to whom correspondence should be addressed.
通讯机构：
[Weijun Wang] K;Key Laboratory of Adolescent Cyberpsychology and Behavior, Ministry of Education, Central China Normal University, Wuhan 430079, China<&wdkj&>Author to whom correspondence should be addressed.
关键词：
mood states;cyber psychometrics;Profile of Mood State (POMS);sentiment analysis;microblog
摘要：
Analyzing people’s opinions, attitudes, sentiments, and emotions based on user-generated content (UGC) is feasible for identifying the psychological characteristics of social network users. However, most studies focus on identifying the sentiments carried in the micro-blogging text and there is no ideal calculation method for users’ real emotional states. In this study, the Profile of Mood State (POMS) is used to characterize users’ real mood states and a regression model is built based on cyber psychometrics and a multitask method. Features of users’ online behavior are selected through structured statistics and unstructured text. Results of the correlation analysis of different features demonstrate that users’ real mood states are not only characterized by the messages expressed through texts, but also correlate with statistical features of online behavior. The sentiment-related features in different timespans indicate different correlations with the real mood state. The comparison among various regression algorithms suggests that the multitask learning method outperforms other algorithms in root-mean-square error and error ratio. Therefore, this cyber psychometrics method based on multitask learning that integrates structural features and temporal emotional information could effectively obtain users’ real mood states and could be applied in further psychological measurements and predictions.
作者机构：
[Li, Jingjing; Wang, Wei] College of Literature, Bohai University, Jinzhou, 121000, China;[Wang, Weijun] School of International Business &, Management, Shanghai International Studies University, Shanghai, 200083, China;[Liu, Kai; Wang, Weijun] Key Laboratory of Adolescent Cyberpsychology and Behavior, Ministry of Education, Central China Normal University, Wuhan, 430079, China
通讯机构：
Key Laboratory of Adolescent Cyberpsychology and Behavior, Ministry of Education, Central China Normal University, Wuhan, China
会议名称：
第二届信息获取与知识服务国际会议
会议时间：
2016-10-21
会议地点：
武汉
会议论文集名称：
第二届信息获取与知识服务国际会议论文集
关键词：
Mobile Situation;News APP;Privacy Violation;Risk
作者机构：
[Song Yanqiu; Chen Boyang; Wang Weijun] Cent China Normal Univ, Sch Informat Management, Wuhan 430079, Peoples R China.;[Song Yanqiu; Chen Boyang; Wang Weijun] Cent China Normal Univ, Key Lab Adolescent Cyber Psychol & Behav, Minist Educ, Wuhan 430079, Peoples R China.
会议名称：
International conference on Engineering Management, Engineering Education and Information Technology (EMEEIT)
会议时间：
OCT 24-25, 2015
会议地点：
Guangzhou, PEOPLES R CHINA
会议主办单位：
[Wang Weijun;Chen Boyang;Song Yanqiu] Cent China Normal Univ, Sch Informat Management, Wuhan 430079, Peoples R China.^[Wang Weijun;Chen Boyang;Song Yanqiu] Cent China Normal Univ, Key Lab Adolescent Cyber Psychol & Behav, Minist Educ, Wuhan 430079, Peoples R China.
会议论文集名称：
ACSR-Advances in Comptuer Science Research
关键词：
online product reviews;score deviation;Appraisal Theory
摘要：
Product reviews and scores have a direct impact on consumers' buying behavior. However, there are inconsistency between reviews and scores. Based on the linguistic Appraisal Theory from the perspective of engagement in the theory-construction index system, this article puts forward online product reviews-scores correction method. The method is applied to verify and correct the real product reviews data. The result shows that this method cannot only explain the differences between reviews and scores and reflect the real scores of the products, but also help consumers make better decisions and improve the network evaluation mechanisms.
摘要：
Online product reviews is an important information source which affects consumer purchasing decision-making deeply, but the inconsistency between reviews and scores brings troubles in the process of decision-making for consumers. So the importance of solving reviews' authenticity is focused on. This paper attempts to introduce the Discourse Markers Theory to make a correction on review scores by analyzing the content of reviews, achieving a breakthrough in the semantic and pragmatic level. Firstly, we build a library of discourse markers in the field of online product reviews and design a correction system including credibility, position, emotional attitude. Then, we get the weight of each index through the questionnaire and propose a algorithm to correct deviation of reviews scores. In the last, the verification results from Jingdong mall show the method has better feasibility and validity.
作者机构：
[Liu, Kai; Zhang, Tingting; Liu, Qiping; Wang, Weijun] School of Information Management, Central China Normal University, Wuhan;430079, China;Key Laboratory of Adolescent Cyber psychology and Behavior, Ministry of Education, Central China Normal University, Wuhan;[Liu, Kai; Zhang, Tingting; Liu, Qiping; Wang, Weijun] 430079, China <&wdkj&> Key Laboratory of Adolescent Cyber psychology and Behavior, Ministry of Education, Central China Normal University, Wuhan;[Liu, Kai; Zhang, Tingting; Liu, Qiping; Wang, Weijun] 430079, China
通讯机构：
School of Information Management, Central China Normal University, Wuhan, China
