Considering meat consumption's massive impact on climate change, environmental NGOs are increasingly campaigning to encourage consumers to reduce unsustainable meat consumption, i.e., to eat less and/or better meat. They usually use messages based on environmental appeals to do so. Yet, the effectiveness of such appeals in international campaigns may depend on countries as cultural beliefs influence food consumption behaviors. Therefore, in this research, we explore the effectiveness of such campaigns across 5 European countries, controlling for individual cultural orientations. Considering an environmental degradation appeal, we first show that countries have no influence on the campaign’s effectiveness, unlike specific individual cultural orientations, including masculinity and uncertainty avoidance. We replicate these results in the same 5 countries considering an alternative appeal, i.e., animal welfare. Recommendations to international NGOs managers result from these results.

Food waste is a major sustainable development problem in the world, and the promotion of ugly food may help address this issue. According to cue utilization theory and the VAB model, the primary purpose of this research is to investigate the role of green packaging in ugly food with multiple internal and external cues. A conceptual model with eight hypotheses are proposed. Conclusion, contributions of study and research limitations are finally shown.

Fashion companies develop initiatives in the Metaverse, especially through Gamification, Non-Fungible Tokens or Shopping experience. Through a Systematic Literature Review in Metaverse and Fashion Communication and Systematic Content analysis in Vogue Business and The Business of Fashion we highlight the best actions in the metaverse and their future application.

This study proposes a new collaborative filtering model that integrates Restricted Boltzmann Machines. The proposed two-stage model is applied to household-level supermarket purchase data. Results show that our model fits the data better and outperforms existing collaborative filtering methods in predicting shopping patterns. The proposed model also improves interpretations of market complexity and common causes of coincidence associated with customers’ multi-category purchases.

With the evolution of Artificial intelligence (AI), emotional artificial intelligence service agents (AISA) have become common in service industry. However, how artificial empathy of AISA contributes to customer acceptance remains an open question. This study draws on Anthropomorphism Theory and Customer AI Experience Theory to examine whether and how artificial empathy has influence on customer acceptance of AISA. Evidence from three experiments (N=1057) designed by the Experimental vignette method (EVM) shows that: (1) artificial empathy including perspective-taking, empathic concern and emotional contagion has a positive impact on customer acceptance of AISA (study 1); (2) customer AI experience (emotional experience quality, social experience activation and social experience quality) mediates the relationship between artificial empathy and customer acceptance of AISA (study 2); (3) artificial empathy for hedonic (vs. utilitarian) services leads to a stronger effect on customer acceptance of AISA (study 3). This paper enriches our understanding of artificial empathy and provides practical guidance for practitioners strategically managing AISA services in AI-enabled marketing interactions.

In recent years, advances in the digital and live streaming economy have led to exponential growth in the number of self-employed streamers who have become an integral part of the self-driven digital labor force. However, previous research on the impact of streamers' work time arrangements on their virtual gifts remains scarce. To fill this gap in the literature, using large-scale data from Kuaishou live streaming platform, we demonstrate that several features of streamers' work time have an important impact on their virtual gifts. Specifically, our results suggest that work time duration and timing improve streamers' virtual gifts; meanwhile, work time tempo has an adverse effect on streamers' earnings. Taken together, our results provide novel and actionable insights for millions of self-employed streamers, agencies, platforms, and policymakers.

Artificial intelligence generated content (AIGC) refers to content produced by artificial intelligence that represents the perspectives of its users, and a new technique of content Generation. Continuous development in deep learning and algorithms have facilitated the adoption of AIGC. This research summarizes literature published under the topic of AIGC using bibliometric analysis method, aims to provide insightful research directions for future studies. 342 documents were collected from Database of Web of science, network visualization analysis among authors and citation analysis over publications are presented to scholars who wish to further research into this area.

The popularity of live streaming is driving the emergence of a new business model, known as live-streaming commerce (LSC). While there are more and more broadcasters in LSC, their behaviors and performance of them are significantly different. To have a better understanding of broadcasters, we employ different machine learning models to identify different portraits in both static and dynamic dimensions. We collect a rich live-streaming dataset from one leading platform in China. Our dataset features information for both broadcasters and viewers, including viewers’ purchasing behaviors, viewers’ records of posting words, broadcasters’ gender, the number of followers for broadcasters, and the live streaming show information, including the start and end time, and the viewers in each live streaming show. The rich textual information in broadcasters’ profile induction provides us a good opportunity to uncover different static portraits and the records in live streaming shows give us a chance to identify different dynamic behavioral portraits for broadcasters.

The popularity of live streaming is driving the emergence of a new business model, known as live-streaming commerce (LSC). Consumers spend more and more time on smartphones, and the emerging business model of live-streaming commerce (LSC) is flourishing in the retail industry. With highly interactive features, LSC social interactions influence viewer purchase behaviors. To examine the interactions between influencers and viewers, we collected a rich dataset from a leading LSC service platform and integrated research models from the natural language process (NLP) field and econometric models.

Gastro-tourism extends beyond what to eat, but also the attractiveness and the environment. It encompasses a tourist experience journey starting from pre, during, until post-travel. Gastro tourism in the new normal engages with traditional vs novel value of experiences. This study aims to answer how Gen Z experiences gastro tourism and the impact of digital technologies using surveys on Tiktok Ads followed by an experiment with an immersive culinary adventure using 3D visual technology.

The economic harm and survival fear caused by environmental conflicts are most likely to become the psychological lever to drive individuals to adopt environmentally friendly behaviours. From the perspective of environmental conflict, this paper will explore the transmission mechanism of environmental conflict on individuals’ pro-environmental behaviour through three experiments.

Green product experience has become an important marketing strategy for corporations to tap potential green consumers. Based on the theory of planned behavior, this article explores the influence of attitude, subjective norm, and perceived behavioral control on consumers’ green purchasing intentions from the perspective of green product experience with consumers in China, Japan, and Korea as the research objects. Our findings suggest that green product experience of consumers in the three countries can directly affect consumers' green purchasing intentions. Green product experience has an indirect influence on consumers’ green purchasing intention through the mediating effect of attitude, subjective norm and perceived behavioral control. The multiple group comparison shows the external validity of TPB through an examination of green purchasing behavior in different cultural settings, which will help enterprises implement effective experience marketing strategies.

Throughout recent years, many physical establishments were forced to close, and events were canceled due to the outbreak of Covid-19. Consequently, brands, especially luxury brands, saw their contact with consumers greatly diminished and revenues decreased significantly (D’Arpizio et al., 2021). On the contrary, the global gaming industry saw its demand, exposure, and revenues increase. In fact, this industry is expected to exceed $200 billion by the end of 2023 (Gilliland, 2020), and there were more than 2.6 billion players worldwide in 2020 (Palframan, 2021). Thus, in 2020, many luxury brands opted to significantly upsurge their investments in the world of online gaming. The adoption of game advertising also represents a way for the luxury industry to adapt to its current target, as 81% of Gen Z and 77% of Millennials are gamers (Jain, 2021). By 2025, both generations are expected to account for 50% of the market, making them important players in the sector. However, there is still little empirical research regarding consumers’ perceptions of game advertising in the context of luxury brands. Thus, this research aims to study the impact that brand credibility and the use of game advertising have on the perceived coolness of luxury brands and, subsequently, on their equity.

Artificial intelligence (AI) technology is recognized as essential in the 4th industrial revolution (Schwab, 2017), which is capable of interacting with the environment and processing and transforming data information to inform goal-directed behavior (Paschen, Kietzmann, & Kietzmann, 2019). Due to the advances in intelligent systems and the incorporation of AI agents in smart devices, more than eight billion digital voice assistants will be used globally by 2024 (Thormundsson, 2022; Gilkson & Woolley, 2020). For successful and positive consumer-brand relationships, constructs such as trust, satisfaction, and commitment are vital (Garbarino & Johnson, 1999; Nyadzayo & Khajehzadehb, 2016). Unlike humans, Artificial intelligence agents could achieve relationship marketing engagement by encouraging users to anthropomorphize the other parties in their technology-mediated interactions, such as applications like chatbots, virtual assistants, and service robots (Steinhoff et al., 2019). Those applications can also use humanoid traits to engage customers in organizations (van Doorn et al., 2017).

As the use of artificial intelligence (AI) grows, so do the questions regarding this new technology and its potential uses. Among the various possibilities and employment that could be offered by AI is personalized news technology. Nowadays, it is already possible to produce journalistic content through AI (Carlson, 2014; Graefe & Haim, 2018). Digital storytelling has become a reality through automated journalism powered by AI (Caswell & Dörr, 2018; Galily, 2018; Linden, 2017; Thorne, 2020). “Artificial intelligence applies advanced analysis and logic-based techniques, including machine learning, to interpret events, support and automate decisions, and take actions” (Gartner Group, 2019). In personalized news technology, algorithms are responsible for selecting content and sorting it according to the personalization criteria (Powers, 2017). So far, AI has been studied in different fields with distinct research focuses (Loureiro et al., 2021). Studies of news-personalization technologies have mainly focused on research engines and filtering mechanisms (Darvishy et al., 2020; Haim et al., 2017; Manoharan & Senthilkumar, 2020). Few studies examine news aggregators (Haim et al., 2018; Kwak et al., 2021) and the effects of news personalization on audiences (Merten, 2021; Swart, 2021; Thurman et al., 2019), thus demanding further research. AI is an imminent reality for the future, reshaping the news media (Brennen et al., 2022; Linden, 2017; Thorne, 2020). Hence, it is still necessary to investigate the impacts that this technology potentially offers to users. Therefore, the current study seeks to respond to this need to deepen research into the area of news personalization through AI, by analyzing the response of audiences toward current and future technological tendencies. The main aim of this research is to investigate the levels of trust that users have in AI-generated personalized video news.

Religious tourism is one of the most important touristic segments globally. Yet, the cognitive and emotional processes shaping destination loyalty in this context, and the impacts of Augmented Reality (AR) technology were not fully investigated. This study takes a unique approach to examine how awe influences recommendation and revisiting intentions through the mediation of rational (e.g., authenticity) and affective (e.g., emotional) mechanisms. Furthermore, our research unveils the role of AR for reinforcing the future intentions of tourists towards a religious site.

Technologies such as Artificial Intelligence (AI) or Robotics are emerging as a new way of improving services, readjusting and impacting all business industries and relationships among people (Loureiro et al., 2021; Makridakis, 2017; Mingotto et al., 2020). The hospitality industry is no exception to this (Mingotto et al., 2020) since a quick growth in the use of robots and AI in this industry has been seen, registering a turnover of 249 million U.S. dollars (International Federation of Robots, 2021). This demonstrates that these technologies have a huge potential to grow, being relevant to deeply study them. Since very few of the existing studies highlight the robot-human interactions, further studies on the enhancement of human well-being through transhumanistic technologies, close relationship marketing capabilities, and the evolution of the engagement process between humans and AI-enabled machines are needed (Loureiro et al., 2021). To address the existing gaps and consider Susan Fournier’s (1998) study on customer-brand relationships, the main goal of this study is to find support for this researcher by associating customer-brand relationship studies with a customer-robot relationship. It also aims to understand individuals’ attitudes towards different types of social robots and the relationship process between social robots and humans, in the hospitality industry, and the influence of identification in the creation of attachment, connection, and commitment. The possible contributions of the customer-robot emotional relationship on customers’ feelings of wellness were also studied.

The Net Promotor Score (NPS) is one of the most well-known metrics for measuring customer loyalty. Originally designed by Reichheld (2003), the measure asks participants to rate their likelihood to recommend the brand on a scale of 0-10, after which respondents are placed into a ‘detractors’ group, ‘passive’ group or ‘promotors’ group. While the measure has attracted much attention due to its simplicity and ease of use, there has equally been much criticism of its reliability, nomological validity and how it is connected to business outcomes. Therefore, the current study aims to understand whether the NPS can be used to identify brand advocacy, and secondly, does the NPS work in a care-based, low switching service context. The study included three unique contexts: at home care, residential care and disability care. In total, there were 611 participants, all of which were based in Australia. A questionnaire was developed and administered to each group and included both quantitative and qualitative questions to understand the consumer experience. The findings supported NPS as an effective metric in a care-based, low-switching context for identifying positive customer advocacy. The implication is that the NPS can be used to track organizational performance; and the extended NPS allows organizations to understand and encourage (address) positive (negative) advocacy. In addition, suggestions for an ‘earned advocacy score’ were provided which may offer a more effective way of understanding consumer experience, while providing clearer, more detailed and more actionable data. The current study provides much needed insight for brand and care organizations to understand how the NPS might be used effectively to facilitate better brand outcomes.

Automation of frontline service encounters, or the replacement of frontline employees by technologies, is increasingly more common. This new service style, often called self- service, has attracted the attention of service providers who are looking to cut costs (Lin & Hsieh, 2007; Walker et al., 2002) and increase efficiency (Bitner et al., 2002; Curran et al., 2003; Dabholkar, 1996). On the other hand, a major disadvantage of self-service is that it puts the burden of service delivery on consumers (Lu et al., 2019). In other words, the introduction of self-service means a shift from consumers being served by frontline employees to their serving themselves by interacting with technologies. This means that consumers’ acceptance is key for self-service to be implemented successfully.

The Belt and Road Initiative (BRI) is one of the bridges to the globalization of trade. The BRI will achieve all its goals and help each participant nation's economy flourish. Expanding international commerce and reducing inequality among participating nations are indicators of stronger economic growth. This study intends to investigate how the Belt and Road Initiative affects global trade and equality among its participants and elaborate the people perception on BRI in Indonesia and Malaysia. This study uses secondary data to compare the BRI members, while the original data was collected using a survey approach. The four factors evaluated in secondary data are globalization, international trade, equality, and business environment. K-mean cluster, One-way ANOVA, and Partial Least Squares were used for data analysis. The survey is conducted in English on two platforms (online and offline), they are analyzed by Homogeneity of Variances test. The findings indicated foreign debt, political stability, level of corruption, education index, and life expectancy are the differences in the business environments that account for this. If the member nations in the Belt and Road Initiative have favorable conditions in terms of political stability, education, and life expectancy, they will succeed in terms of globalization, international trade, and equality. In addition, the nation should have little foreign debt and less corruption. The last, both Malaysia and Indonesia have positive perception on the BRI and support the country to participate on it.