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Green demarketing, which promotes anti-consumption as a more extreme sustainability tactic, could help consumers and societies move toward healthier consumption patterns while building strong, long-lasting relationships with consumers. As even the most committed brands find the need to oscillate between demarketing and conventional marketing for survival, this research tests how the congruency of the campaign shown on a brand's home page (owned media) and a following retargeting ad (paid media) could impact perceived congruency and further downstream effects. In doing so, this research proposes that the media context (i.e. news or shopping browsing context) in which the retargeting ad is embedded could determine how much congruency of the demarketing campaign across owned and paid media matters.

An experiment with a 2 (home page content: green vs. demarketing) × 2 (retargeting ad content: product vs. demarketing) × 2 (browsing context: shopping vs. news) between-subjects factorial design was employed with an online panel of 430 participants. The participants first saw the brand's home page content, then were assigned to a website browsing context where the retargeting ad of the brand was embedded.

In a news browsing context, users perceived higher congruency when product retargeting ads (vs. demarketing) were shown after a green home page exposure and when demarketing retargeting ads (vs. products) were delivered after a demarketing home page. The elevated perceived congruency successfully led to higher ad argument and ad attitude. These differences were not present in a shopping browsing context. These results showed that the congruency between the home page and the retargeting ad for demarketing campaigns mattered more in certain media contexts (i.e. news browsing context).

The study closes the empirical gap in demarketing brand activism campaigns by demonstrating when and how congruency between multiple owned and paid channels for demarketing campaigns impacts consumer responses. This study provides evidence of how the match of the demarketing campaign shown on a brand's home page and a following retargeting ad could impact perceived congruency and further downstream effects of ad argument and ad attitude while considering different browsing context effects.

A clickbait is a deceptive headline designed to boost ad revenue without presenting closely relevant content. There are numerous negative repercussions of clickbait, such as causing viewers to feel tricked and unhappy, causing long-term confusion, and even attracting cyber criminals. Automatic detection algorithms for clickbait have been developed to address this issue. The fact that there is only one semantic representation for the same term and a limited dataset in Chinese is a need for the existing technologies for detecting clickbait. This study aims to solve the limitations of automated clickbait detection in the Chinese dataset.

This study combines both to train the model to capture the probable relationship between clickbait news headlines and news content. In addition, part-of-speech elements are used to generate the most appropriate semantic representation for clickbait detection, improving clickbait detection performance.

This research successfully compiled a dataset containing up to 20,896 Chinese clickbait news articles. This collection contains news headlines, articles, categories and supplementary metadata. The suggested context-aware clickbait detection (CA-CD) model outperforms existing clickbait detection approaches on many criteria, demonstrating the proposed strategy's efficacy.

The originality of this study resides in the newly compiled Chinese clickbait dataset and contextual semantic representation-based clickbait detection approach employing transfer learning. This method can modify the semantic representation of each word based on context and assist the model in more precisely interpreting the original meaning of news articles.

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.

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.

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.

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.

The purpose of this study is to investigate how much visual attention is given to banner ads embedded in Web page content dependent on whether the user’s task is goal- or not goal-oriented, as well as the interplay between attention, banner location, banner click and banner recognition.

The authors used a within-subjects design where 100 participants performed two tasks – reading a news and finding where to click next – on a Web page containing three banner ads embedded into the website content. The authors gathered behavioral and eye-tracking data.

Consumers disregard banner ads when they are performing a focused task (reading news). Visual attention paid to the banners while reading – but not while free browsing – and banner location do not impact ad clicking. In addition, it is not necessary to pay full attention to a banner ad to be able to recognize it afterward.

The strategy of embedding banners in the main content of a Web page leads to higher visual attention when consumers are browsing a Web page compared to a focused task (e.g. reading). It also increases ad recognition over time compared to benchmark levels for ads placed in traditional positions.

Previous studies mainly assessed effectiveness of banners located at the top or lateral of a Web page. The authors used eye tracking as an objective measure of visual attention to banner ads embedded in Web page content and behavioral metrics to assess ad interest and measured ad recognition over time.

Investigar cuánta atención visual se presta a los banners publicitarios incrustados en el contenido de una página Web en función de si la tarea del usuario está orientada a un objetivo o no, así como la interacción entre la atención, la ubicación del banner, el clic en el banner y el reconocimiento del banner.

Se utilizó un diseño entre sujetos en el que 100 participantes realizaban dos tareas – leer una noticia y encontrar dónde hacer clic a continuación – en una página Web que contenía tres banners publicitarios incrustados en el contenido del sitio Web. Se recogieron datos conductuales y de seguimiento ocular.

Los consumidores no prestan atención a los banners publicitarios cuando están realizando una tarea concentrada (leer noticias). La atención visual prestada a los banners durante la lectura – pero no durante la navegación libre – y la ubicación de los banners no influyen en el hecho de hacer clic en los anuncios. Además, no es necesario prestar toda la atención a un banner publicitario para poder reconocerlo después.

Los estudios anteriores evaluaban principalmente la eficacia de los banners situados en la parte superior o lateral de una página Web. Nosotros utilizamos el seguimiento ocular como medida objetiva de la atención visual a los banners incrustados en el contenido de la página Web y métricas de comportamiento para evaluar el interés por el anuncio, y medimos el reconocimiento del anuncio a lo largo del tiempo.

La estrategia de incrustar banners en el contenido principal de una página Web aumenta la atención visual de los consumidores cuando navegan por una página Web en comparación con una tarea específica (por ejemplo, leer). También aumenta el reconocimiento del anuncio a lo largo del tiempo en comparación con los niveles de referencia de los anuncios colocados en posiciones tradicionales.

研究用户对嵌入在网页内容中的横幅广告的视觉注意程度, 取决于用户的任务是否以目标为导向, 以及注意、横幅位置、横幅点击和横幅识别之间的相互作用。

我们采用了主体内设计, 100名参与者在一个含有三个嵌入网站内容的横幅广告的网页上执行两项任务–阅读新闻和寻找下一步的点击位置。我们收集了行为和眼球追踪数据。

消费者在执行重点任务（阅读新闻）时忽略了横幅广告。阅读时对横幅广告的视觉关注–而不是自由浏览时–以及横幅广告的位置并不影响广告点击。此外, 不一定要完全注意横幅广告才能在事后认出它。

以前的研究主要评估位于网页顶部或侧面的横幅广告的效果。我们用眼动仪作为对嵌入网页内容的横幅广告的视觉注意力的客观测量, 用行为指标来评估广告的兴趣, 并测量了广告在一段时间内的识别度。

在网页的主要内容中嵌入横幅广告的策略导致消费者在浏览网页时, 与重点任务（如阅读）相比, 视觉注意力更高。与放置在传统位置的广告的基准水平相比, 它也会随着时间的推移增加广告识别度。

The purpose of this study is to examine the knowledge gap hypothesis in the context of smartphone use for news to understand whether mobile news consumption could bridge or widen the knowledge gap between people of higher and lower socioeconomic status (SES).

The authors examine how smartphone news consumption is associated with the knowledge gap hypothesis by analyzing a survey dataset from Hong Kong. This study focuses specifically on a moderated mediation model in which the indirect effect of mobile news consumption on political knowledge via discussion network heterogeneity is contingent on level of education.

Smartphone use for news/information was positively associated with level of discussion network heterogeneity. The indirect effect of smartphone news use on political knowledge via discussion network heterogeneity was stronger for those with lower levels of education.

This study advances the understanding of the role of smartphone use in contributing to the functioning of deliberative democracy as this use enhances discussion network heterogeneity and general levels of political knowledge. Moreover, our study contributes to the literature on the knowledge gap by not only examining the relationship between smartphone use, discussion heterogeneity, and political knowledge but also taking into consideration individual levels of education.

This research investigates how consumers who are most active on Facebook during the day vs in the evening differ, differ in their ad consumption, and how advertising effects vary as a function of a key moderator: gender.

Using a survey of 281 people, the research identifies Facebook users who are more intensely using mobile social media during the day versus in the evening, and measures five Facebook mobile advertising outcomes: brand and product recall, clicking on ads, acting on ads and purchases.

The results show that women who are using social media more intensely during the day are more likely to use Facebook to seek information, hence, Facebook mobile ads tend to be more effective for these users compared to those in the evening.

This contributes to the literature by analyzing how the time of day affects social media behavior in relation to mobile advertising effectiveness, and broadening the scope of mobile advertising effectiveness research from other than just clicks on ads to include measures like brand and product recall.

By analyzing the effectiveness of mobile advertising on social media as a function of the time of day, advertisers can be more targeted in their media buys, and so better use their social media budgets, i.e. advertising is more effective for women who use social media (Facebook) more intensely during the day than for those who use social media more intensely in the evening as the former tend to seek more information than the latter.

This research extends media ecology theory by drawing on circadian rhythm research to provide a first demonstration of how the time of day relates to different uses of mobile social media, which in turn relate to social media mobile advertising consumption.

While research on social media advertising has been steadily increasing, little has been explored on how users consume ads when they engage with social media at different periods along the day. This paper extends media ecology theory by investigating time of day, drawing on the circadian rhythm literature, and how it relates to social media usage.

With the deep development of the new technological revolution and industrial transformation, the development, application, expansion and integration of digital technology provide opportunities for transforming the manufacturing industry from traditional manufacturing to intelligent manufacturing. However, little research currently focuses on analyzing the influencing factors of intelligent development in this field. There is a lack of research from the perspective of the digital innovation ecosystem to explore the intrinsic mechanism that drives intelligent development. Therefore, this article starts with high-end equipment manufacturing enterprises as the research subject to explore how their digital innovation ecosystem promotes the effectiveness of enterprise intelligent development, providing theoretical support and policy guidance for enterprises to achieve intelligent development at the current stage.

This article constructs a logical framework for the digital innovation ecosystem using a “three-layer core-periphery” structure, collects data using crawling for subsequent indicator measurement and assessment and uses the fuzzy set Qualitative Comparative Analysis method (fsQCA) to explore how the various components of the digital innovation ecosystem in high-end equipment manufacturing enterprises work together to promote the development of enterprise intelligently.

This article finds that the various components of the digital innovation ecosystem of high-end equipment manufacturing enterprises, through mutual coordination, can help improve the level of enterprise intelligence. Empirical analysis shows four specific configuration implementation paths for the digital innovation ecosystem of high-end equipment manufacturing enterprises to promote intelligent development. The core conditions and their combinations that affect the intelligent development of enterprises differ in each configuration path.

Firstly, this article discusses the practical problems of intelligent transformation and development in the manufacturing industry and focuses on the intelligent development effectiveness of various components of the digital innovation ecosystem of high-end equipment manufacturing enterprises in the context of digitalization. Secondly, this article uses crawling, text sentiment analysis and other methods to creatively collect relevant data to overcome the research dilemma of being limited to theoretical analysis due to the difficulty in obtaining data in this field. At the same time, based on the characteristics of high-end equipment manufacturing enterprises, the “three-layer core-periphery” digital innovation ecosystem framework constructed in this article helps to gain a deep understanding of the development characteristics of the industry's enterprises, provides specific indicator analysis for their intelligent development, opening the “black box” of intelligent development in the industry's enterprises and bridging the gap between theory and practice. Finally, this study uses the fsQCA research method of configuration analysis to explore the complexity of the antecedents and investigate the combined effects of multiple factors on intelligent development, providing new perspectives and rich research results for relevant literature on the intelligent development of high-end equipment manufacturing enterprises.

The case was devised using both primary and secondary data sources. Primary sources of data consisted of in-depth interviews with individuals using the cycle hire project. The researcher also had first-hand experiences of using the cycles. The case study has been tested with undergraduate and graduate students taking management information systems courses.

This teaching case study charts the London cycle hire project, mostly from its first inception in July 2010, right through to the planned expansion of electric cycles from Summer 2022. The main aim of the case is to introduce students to project management challenges which are part of the London cycle hire project. While the project was filled with enthusiasm from its early beginnings, various challenges were encountered including issues associated with the project procurement/sourcing process, software and technical problems, as well as other project management issues. Problems became so severe in 2011 that the service provider was hit with a penalty and had to make critical project improvements. Would these accountability measures prompt the service provider to resolve these issues? How would the service provider go about undertaking a fact-finding exercise to verify the existence of the challenges and address them to ensure renewed project success?

The case was written for classes at both the undergraduate and graduate levels. The focus of the case is particularly well suited for exploring topics and issues relating to types of information systems, project management and accountability, multiple global supplier procurement, as well as challenges associated with hardware integration and software design. While the case was targeted at MIS students, the case study would also be effective for an introductory level project management course or a general management course. The subject of the case, the bicycle rental program, is likely to appeal to students, and the basic underlying business issues, processes and objectives of the project are easily understood.

This study aims to examine an emerging product–place co-branding marketing practice in China’s rural areas. The role of this practice in inclusive development is analyzed from the perspectives of value proposition innovation, market legitimacy, media coverage and brand value. Both research and practice indicate value proposition innovation to exert an important influence on brand value enhancement, but little is known about the mediating and moderating mechanisms underlying this relation.

A moderated mediation model is constructed to examine whether market legitimacy mediates the relationship between value proposition innovation and brand value. vWhether this mediating process is moderated by media coverage is also examined. The primary data are collected from semi-structured interviews and observations conducted with two common cases to develop proper scales for value proposition innovation and market legitimacy. The research includes 100 product–place co-brandings published by the Ministry of Agriculture and Rural Affairs in 2019. Hypotheses are tested using hierarchical regression and a Bootstrap model.

Value proposition innovation has a positive effect on brand value, and market legitimacy partially mediates this relationship. Media coverage positively moderates the relationship between value proposition innovation and market legitimacy, and positively moderates the mediating effect of market legitimacy; the higher the media coverage, the stronger the mediating effect of market legitimacy.

Based on data availability and accessibility, the study sample focused on indicators from 100 brands in 2019. If the Ministry of Agriculture and Rural Affairs discloses consecutive annual information for other years, future studies could explore panel data to further test the study’s conclusions from a longitudinal perspective.

First, this paper adds to the emerging literature on product–place co-branding business models by examining the relationship between value proposition innovation and brand value. Second, this paper enriches institutional theory by including market legitimacy as a mediator between value proposition innovation and brand value. Third, this paper identifies the moderating role of media coverage, thus broadening the theoretical implications of institutional theory with respect to improving market legitimacy.

This study aims to examine the impact of consumer risk appetite, biases (specifically negative recency bias), and the importance of reviews in enhancing information quality. By analyzing these variables, the authors gain insights into their role in enriching the overall information spectrum available to consumers. The findings contribute to a better understanding of how risk appetite, biases and consumer reviews shape the quality of information.

The questionnaire assessed the relationship between dependent and independent variables by asking participants to rate their experiences in relevant scenarios. Variance-based structural equation modeling with the ADANCO program was used to examine the data. ADANCO software is used explicitly for variance-based structural equation modeling. To evaluate research models and test hypotheses, partial least square path modeling is used.

The efficiency of reviews and ratings is greatly influenced by consumer risk appetite. Businesses should focus on clients who are willing to take risks and balance positive and negative feedback. It is essential to comprehend how customers understand reviews. Credibility is increased by taking biases into account and encouraging unbiased criticism. Promoting thorough reviews strengthens influence. Monitoring and making use of these elements improve online reputation and commercial success.

The research has limitations due to the simplicity of the attributes taken into account and the requirement for a larger sample size. Overcoming barriers to promote consistent client feedback is essential, and tailored emails can help with assessment generation. Increased customer participation in writing evaluations can be achieved by removing obstacles and highlighting the advantages of participation.

Businesses and buyers rely on this “organically” generated content as the basis of their promotional strategy and buying decisions. Most of the research is related to consumer reviews, their behavior and the importance of social validation. However, some critical aspects related to this need further investigation.