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1 – 10 of over 9000Ming Li and Jing Liang
Knowledge adoption is the key to effective knowledge exchange in virtual question-and-answer (Q&A) communities. Although previous studies have examined the effects of knowledge…
Abstract
Purpose
Knowledge adoption is the key to effective knowledge exchange in virtual question-and-answer (Q&A) communities. Although previous studies have examined the effects of knowledge content, knowledge source credibility and the personal characteristics of knowledge seekers on knowledge adoption in virtual Q&A communities from a static perspective, the impact of answer deviation on knowledge adoption has rarely been explored from a context-based perspective. The purpose of this study is to explore the impact of two-way deviation on knowledge adoption in virtual Q&A communities, with the aim of expanding the understanding of knowledge exchange and community management.
Design/methodology/approach
The same question and the same answerer often yield multiple answers. Knowledge seekers usually read multiple answers to make adoption decisions. The impact of deviations among answers on knowledge seekers' knowledge adoption is critical. From a context-based perspective, a research model of the impact of the deviation of horizontal and vertical answers on knowledge adoption is established based on the heuristic-systematic model (HSM) and empirically examined with 88,287 Q&A data points and answerer data collected from Zhihu. Additionally, the moderation effects of static factors such as answerer reputation and answer length are examined.
Findings
The negative binomial regression results show that the content and emotion deviation of horizontal answers negatively affect knowledge seekers' knowledge adoption. The content deviation of vertical answers is negatively associated with knowledge adoption, while the emotion deviation of vertical answers is positively related to knowledge adoption. Moreover, answerer reputation positively moderates the negative effect of the emotion deviation of horizontal answers on knowledge adoption. Answer length weakens the negative correlation between the content deviation of horizontal and vertical answers and knowledge adoption.
Originality/value
This study extends previous research on knowledge adoption from a static perspective to a context-based perspective. Moreover, information deviation is expanded from a one-way variable to a two-way variable. The combined effects of static and contextual factors on knowledge adoption are further uncovered. This study can not only help knowledge seekers identify the best answers but also help virtual Q&A community managers optimize community design and operation to reduce the cost of knowledge search and improve the efficiency of knowledge exchange.
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Baofeng Huo, Xu Liu and Siyu Li
With more demand-driven innovation activities, manufacturers must proactively engage in information sharing activities with their customers for better innovation performance. This…
Abstract
Purpose
With more demand-driven innovation activities, manufacturers must proactively engage in information sharing activities with their customers for better innovation performance. This study aims to inquire into the impacts of information sharing activities between manufacturers and customers (including information system usage and information content sharing) on manufacturers’ innovation performance and considers interfirm justice (including distributive justice, procedural justice and interactional justice) as information sharing antecedents.
Design/methodology/approach
The social exchange theory is applied to develop the conceptual model. The authors examine the conceptual model with the structural equation modeling approach using data collected from 213 Chinese manufacturers.
Findings
Interactional justice promotes information system usage. Both interactional justice and procedural justice increase information content sharing, while distributive justice decreases it. Information content sharing directly improves innovation performance and fully mediates the relationship between information system usage and innovation performance.
Originality/value
This research enriches empirical studies on justice-information sharing relationships by systematically investigating the impacts of three types of justice on different information sharing activities. It also adds to the application of social exchange theory in the practices of interfirm justice and information sharing. Besides, it probes into influencing mechanisms of different information sharing activities, information system usage and information content sharing, on innovation performance. The findings can guide firms to implement interfirm justice and information sharing practices for superior innovation performance.
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Min Qin, Wei Zhu, Jinxia Pan, Shuqin Li and Shanshan Qiu
Enterprises build online product community to expect users to contribute: opinion sharing (content contribution) and product consumption (product contribution). Previous…
Abstract
Purpose
Enterprises build online product community to expect users to contribute: opinion sharing (content contribution) and product consumption (product contribution). Previous literature rarely focused on both. The purpose of this paper is to explain user contribution mechanism by identifying content contribution and product contribution.
Design/methodology/approach
This research chose Xiaomi-hosted online product community (bbs.xiaomi.cn) and Huawei-hosted online product community (club.huawei.com) where users can freely share ideas and buy products at the same time. Data were crawled from 109,665 community users to construct dependent variable measurement, and 611 questionnaires were used to verify research hypotheses.
Findings
The results indicate that both cognitive needs and personal integration needs have a significant positive impact on browse behavior; social integration needs and hedonic needs have a significant positive impact on content contribution behavior. Browse behavior not only directly affects but also indirectly influences product contribution through content contribution behavior.
Research limitations/implications
Findings of this research provide community managers with useful insights into the relationship between content contribution and product contribution.
Originality/value
This study explains the formation mechanism of user product contribution and reveals the relationship between user content contribution and product contribution in online product community. This paper provides a different way of theorizing user contributions by incorporating uses and gratifications theory into the “Motivation-Behavior-Result” framework.
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Revanth Kumar Guttena, Cedric Hsi-Jui Wu and Ferry Tema Atmaja
This study aims to investigate how the gratifications obtained through brand-related social media content affect brand intimacy and thereby influence customer extra-role behavior.
Abstract
Purpose
This study aims to investigate how the gratifications obtained through brand-related social media content affect brand intimacy and thereby influence customer extra-role behavior.
Design/methodology/approach
Using the uses and gratification theory, this study proposes information, entertainment and remuneration content that motivates customers to develop brand intimacy and thereby perform customer extra-role behavior. The study also tests the moderated moderation effect of self-congruence and customer experience using 704 observations from South India in the food industry context.
Findings
The study’s results reveal the influence of entertainment and remuneration content on brand intimacy, which further influences customer extra-role behavior (civic virtue, cocreation, sportsmanship and helping behaviors). The study confirms a moderated moderation effect in the relationship between brand intimacy and civic virtue and brand intimacy and sportsmanship behaviors.
Practical implications
The study suggests that brands may include entertainment and remuneration elements in their social media content to build intimate customer relationships, further influencing customers’ extra-role behaviors. Besides, brands should focus on customers’ self-concepts and experiences to encourage them to act voluntarily.
Originality/value
This study makes a unique contribution by investigating the influence of brand-related social media content on customer extra-role behavior through brand intimacy. It uses self-congruence and customer experience to test their moderated moderation effect in the relationship between brand intimacy and customer extra-role behavior.
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Boryung Ju and J. Brenton Stewart
The purpose of this study is to examine the quality of information in articles in the online encyclopedia, Wikipedia, as perceived by readers and content contributors. This study…
Abstract
Purpose
The purpose of this study is to examine the quality of information in articles in the online encyclopedia, Wikipedia, as perceived by readers and content contributors. This study explored several dimensions and characteristics of information presented in Wikipedia by identifying new emerging dimensions in terms of readers’ perceptions of the quality of online information.
Design/methodology/approach
Two rounds of online surveys were conducted using a mixed-method approach. In the first survey, the authors conducted content analysis on 197 participants, and in the second survey, the authors conducted factor analysis on 107 study participants. The authors used Qualtrics Panel Services to recruit individuals who read and/or edited the English version of Wikipedia articles and resided in the United States.
Findings
The mixed-method approach employed in this study to explore the quality of online information had three core components: users’ perceptions of information quality, content analysis, and exploratory factor analysis of the perceived information quality structure. The study found a new information quality category, social aspect quality. Dimensions include fun, goodness, empowering and user generated.
Originality/value
The results demonstrate the emergence of novel quality attributes for information quality presented online, particularly in social media. Moreover, this study is one of the rare studies to employ a mixed-method approach that offers diverse but reliable perspectives on information quality as perceived by everyday users of Wikipedia.
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Qinglong Li, Jaeseung Park and Jaekyeong Kim
The current study investigates the impact on perceived review helpfulness of the simultaneous processing of information from multiple cues with various central and peripheral cue…
Abstract
Purpose
The current study investigates the impact on perceived review helpfulness of the simultaneous processing of information from multiple cues with various central and peripheral cue combinations based on the elaboration likelihood model (ELM). Thus, the current study develops and tests hypotheses by analyzing real-world review data with a text mining approach in e-commerce to investigate how information consistency (rating inconsistency, review consistency and text similarity) influences perceived helpfulness. Moreover, the role of product type is examined in online consumer reviews of perceived helpfulness.
Design/methodology/approach
The current study collected 61,900 online reviews, including 600 products in six categories, from Amazon.com. Additionally, 51,927 reviews were filtered that received helpfulness votes, and then text mining and negative binomial regression were applied.
Findings
The current study found that rating inconsistency and text similarity negatively affect perceived helpfulness and that review consistency positively affects perceived helpfulness. Moreover, peripheral cues (rating inconsistency) positively affect perceived helpfulness in reviews of experience goods rather than search goods. However, there is a lack of evidence to demonstrate the hypothesis that product types moderate the effectiveness of central cues (review consistency and text similarity) on perceived helpfulness.
Originality/value
Previous studies have mainly focused on numerical and textual factors to investigate the effect on perceived helpfulness. Additionally, previous studies have independently confirmed the factors that affect perceived helpfulness. The current study investigated how information consistency affects perceived helpfulness and found that various combinations of cues significantly affect perceived helpfulness. This result contributes to the review helpfulness and ELM literature by identifying the impact on perceived helpfulness from a comprehensive perspective of consumer review and information consistency.
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This article aims to elaborate the context-sensitive nature of credibility assessment by examining how such judgments are made in online discussion in times of uncertainty caused…
Abstract
Purpose
This article aims to elaborate the context-sensitive nature of credibility assessment by examining how such judgments are made in online discussion in times of uncertainty caused by Finland's intent to join the North Atlantic Treaty Organization (NATO) in spring 2022.
Design/methodology/approach
The empirical findings draw on the qualitative content analysis of 3,324 posts submitted to a Finnish online discussion in February–March 2022. It was examined how the participants of online discussion assess the credibility of information sources referred to in debates on the NATO membership. It is assumed that the believability of the author of information is indicative of his or her expert power, for example based on the credentials of a scholar, while the credibility of information content, for example the provision of factual evidence is indicative of the source's informational power.
Findings
Political decision-makers, particularly the President of Finland were assessed as most credible information sources, due to their access to confidential knowledge and long-time experience in politics. The credibility assessments differed more strongly while judging the believability of researchers. On the one hand, their expertise was praised; on the other hand, doubts were presented about their partiality. Fellow participants of online discussion were assessed most negatively because information sources of these types are associated with low expert and informational power.
Research limitations/implications
As the study concentrated on credibility assessments made in a Finnish online discussion group, the findings cannot be extended to concern the credibility judgments occurring information in other contexts.
Originality/value
The study is among the first to characterize the role of expert and informational power in credibility assessment in times of uncertainty.
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Xinhua Guan, Zhenxing Nie, Catheryn Khoo, Wentao Zhou and Yaoqi Li
This study aims to explore the connection between travel content consumption in social networks and social comparison, envy as well as travel intention. It analyzes whether…
Abstract
Purpose
This study aims to explore the connection between travel content consumption in social networks and social comparison, envy as well as travel intention. It analyzes whether tourists’ travel intention is affected by travel content consumption in social networks, and more importantly, whether social comparison and envy play a mediating role in this process.
Design/methodology/approach
Data was collected through intercept in four popular tourist spots in Guangzhou and Zhuhai in South China. A self-administered questionnaire was used. A total of 400 participants were recruited, and 291 valid questionnaires were obtained. Bias-corrected nonparametric percentile bootstrap mediation variable test method was used to test hypotheses.
Findings
The study yielded three results. First, travel content consumption in the social networks positively influences travel intention. Second, travel content consumption in social networks indirectly affects travel intention through social comparison and envy. Third, the control variables, such as gender, age, education and income, mainly affect envy.
Originality/value
This study constructs a theoretical framework of stimulus–cognitive appraisal–emotion–behavioral responses. To the best of the authors’ knowledge, it is the first study to reveal that the internal psychological mechanism of travel content consumption affects travel intention. It also discloses that envy of seemingly negative emotions can encourage positive behaviors in certain situations.
Details
Keywords
- Social networks
- Content consumption
- Social comparison
- Envy
- Travel intention
- Cognitive appraisal theory of emotion
- Redes sociales
- consumo de contenido
- comparación social
- envidia
- intención de viaje
- teoría de evaluación cognitiva emocional
- 社交网络
- 内容消费
- 社会比较
- 嫉妒
- 旅游意向
- 情感认知评价理论
- Redes sociales
- Consumo de contenido
- Comparación social
- Envidia
- Intención de viaje
- Teoría de evaluación cognitiva emocional
Na Ye, Dingguo Yu, Xiaoyu Ma, Yijie Zhou and Yanqin Yan
Fake news in cyberspace has greatly interfered with national governance, economic development and cultural communication, which has greatly increased the demand for fake news…
Abstract
Purpose
Fake news in cyberspace has greatly interfered with national governance, economic development and cultural communication, which has greatly increased the demand for fake news detection and intervention. At present, the recognition methods based on news content all lose part of the information to varying degrees. This paper proposes a lightweight content-based detection method to achieve early identification of false information with low computation costs.
Design/methodology/approach
The authors' research proposes a lightweight fake news detection framework for English text, including a new textual feature extraction method, specifically mapping English text and symbols to 0–255 using American Standard Code for Information Interchange (ASCII) codes, treating the completed sequence of numbers as the values of picture pixel points and using a computer vision model to detect them. The authors also compare the authors' framework with traditional word2vec, Glove, bidirectional encoder representations from transformers (BERT) and other methods.
Findings
The authors conduct experiments on the lightweight neural networks Ghostnet and Shufflenet, and the experimental results show that the authors' proposed framework outperforms the baseline in accuracy on both lightweight networks.
Originality/value
The authors' method does not rely on additional information from text data and can efficiently perform the fake news detection task with less computational resource consumption. In addition, the feature extraction method of this framework is relatively new and enlightening for text content-based classification detection, which can detect fake news in time at the early stage of fake news propagation.
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Duen-Ren Liu, Yang Huang, Jhen-Jie Jhao and Shin-Jye Lee
Online news websites provide huge amounts of timely news, bringing the challenge of recommending personalized news articles. Generative adversarial networks (GAN) based on…
Abstract
Purpose
Online news websites provide huge amounts of timely news, bringing the challenge of recommending personalized news articles. Generative adversarial networks (GAN) based on collaborative filtering (CFGAN) can achieve effective recommendation quality. However, CFGAN ignores item contents, which contain more latent preference features than just user ratings. It is important to consider both ratings and item contents in making preference predictions. This study aims to improve news recommendation by proposing a GAN-based news recommendation model considering both ratings (implicit feedback) and the latent features of news content.
Design/methodology/approach
The collaborative topic modeling (CTM) can improve user preference prediction by combining matrix factorization (MF) with latent topics of item content derived from latent topic modeling. This study proposes a novel hybrid news recommendation model, Hybrid-CFGAN, which modifies the architecture of the CFGAN model with enhanced preference learning from the CTM. The proposed Hybrid-CFGAN model contains parallel neural networks – original rating-based preference learning and CTM-based preference learning, which consider both ratings and news content with user preferences derived from the CTM model. A tunable parameter is used to adjust the weights of the two preference learnings, while concatenating the preference outputs of the two parallel neural networks.
Findings
This study uses the dataset collected from an online news website, NiusNews, to conduct an experimental evaluation. The results show that the proposed Hybrid-CFGAN model can achieve better performance than the state-of-the-art GAN-based recommendation methods. The proposed novel Hybrid-CFGAN model can enhance existing GAN-based recommendation and increase the performance of preference predictions on textual content such as news articles.
Originality/value
As the existing CFGAN model does not consider content information and solely relies on history logs, it may not be effective in recommending news articles. Our proposed Hybrid-CFGAN model modified the architecture of the CFGAN generator by adding a parallel neural network to gain the relevant information from news content and user preferences derived from the CTM model. The novel idea of adjusting the preference learning from two parallel neural networks – original rating-based preference learning and CTM-based preference learning – contributes to improve the recommendation quality of the proposed model by considering both ratings and latent preferences derived from item contents. The proposed novel recommendation model can improve news recommendation, thereby increasing the commercial value of news media platforms.
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