Uncovering the effectiveness of anthropomorphic communication on the country-of-origin stereotypes from the perspective of psychological elements.

With the development of social media, interactive activities such as anthropomorphic communications are more accessible and popular. The country-of-origin(COO) stereotype is one of the most important factors which influences individuals' attitudes toward brands. This study aims to investigate the feasibility and validity of anthropomorphic communication via social media on COO stereotypes in international competitions. Experimental results indicate that the strategy of using anthropomorphic communication has positive effects for developing countries, but not the same for developed countries; the perceived social presence mediates the relationship between anthropomorphic communication and COO stereotypes of developing countries. However, the mediating effect is not obvious in developed countries, the influence of anthropomorphic communication is effective and feasible only when individuals' mindset is global. The theoretical model in this paper is a useful supplement to the existing achievements of anthropomorphism and COO stereotypes, it provides a reference for enterprises in developing countries to use anthropomorphic strategies accurately to reduce negative COO stereotypes and improve international competitiveness, it also gives suggestions for companies in developed countries to adopt anthropomorphic communication strategies cautiously.

Under the different sectors: the relationship between low-carbon economic development, health and GDP.

Developing a modern low-carbon economy while protecting health is not only a current trend but also an urgent problem that needs to be solved. The growth of the national low-carbon economy is closely related to various sectors; however, it remains unclear how the development of low-carbon economies in these sectors impacts the national economy and the health of residents. Using panel data on carbon emissions and resident health in 28 province-level regions in China, this study employs unit root tests, co-integration tests, and regression analysis to empirically examine the relationship between carbon emissions, low-carbon economic development, health, and GDP in industry, construction, and transportation. The results show that: First, China's carbon emissions can promote economic development. Second, low-carbon economic development can enhance resident health while improving GDP. Third, low-carbon economic development has a significant positive effect on GDP and resident health in the industrial and transportation sector, but not in the construction sector, and the level of industrial development and carbon emission sources are significant factors contributing to the inconsistency. Our findings complement existing insights into the coupling effect of carbon emissions and economic development across sectors. They can assist policymakers in tailoring low-carbon policies to specific sectors, formulating strategies to optimize energy consumption structures, improving green technology levels, and aiding enterprises in gradually reducing carbon emissions without sacrificing economic benefits, thus achieving low-carbon economic development.

What makes a theme park experience less enjoyable? Evidence from online customer reviews of Disneyland China.

The aim of this study was to explore the causes of tourists' lesser enjoyment of theme parks through an unsupervised machine learning approach-structural topic modelling. Specifically, the research extracted a comprehensive list of discussion topics about the travel experience of tourists through the analysis of 112,000 customer reviews released by visitors to the Shanghai Disney Resort from 16 June 2016 to 4 March 2022. Then, we used sentiment analysis to distinguish positive and negative topics and to explore the relationship between tourists who buy different ticket types and sentiments in negative topics. The results show that problems such as "parking," "service attitude," "recommendation feeling," "experience comparison," and "entrance" may be the main reasons for an unpleasant experience. In addition, we also found that when tourists travel in groups (e.g., via family tickets), customers feel unhappy because of parking and fast track problems. Moreover, when tourists travel alone or with small groups, staff service attitudes, experience comparisons, and entrance processes are the sources of greater concern. Our findings can help theme park managers to better understand the expectations of tourists and take effective measures to tackle issues causing customer dissatisfaction, and they can also contribute to theme park studies in tourism management.

Is negative e-WOM more powerful? Multimodal data analysis on air passengers' perception of COVID-19 safety measures.

During the normalization stage of the COVID-19 epidemic prevention and control, the safety threats caused by improper epidemic prevention measures of airlines have become the primary concern for air passengers. Negative e-WOM related to safety perception obtained based on online multimodal reviews of travel websites has become an important decision-making basis for potential air passengers when making airline choices. This study aims to examine the relationship between potential air passengers' negative safety perception and the usefulness of online reviews, as well as to test the moderating effect of review modality and airline type. It also further explores the effectiveness and feasibility of applying big data sentiment analysis to e-WOM management. To this end, the theoretical model of negative safety perception, review modality, and airline type affecting review usefulness was constructed. Then we select 10 low-cost airlines and 10 full-service airlines, respectively, according to the number of reviews sorted by the TripAdvisor website, and use crawling techniques to obtain 10,485 reviews related to COVID-19 safety of the above companies from December 2019 to date, and conduct safety perception sentiment analysis based on Python's Textblob library. Finally, to avoid data overdispersion, the model is empirically analyzed by negative binomial regression using R software. The results indicate that (1) Negative safety perception significantly and negatively affects review usefulness, that is, extreme negative safety perception can provide higher review usefulness for potential air passengers. (2) Review modality and airline type have a significant moderating effect on the relationship between negative safety perception and review usefulness, in which multimodal reviews and full-service airlines both weakened the negative impact of negative safety perception on review usefulness. The theoretical model in this paper is both an extension of the application of big data sentiment analysis techniques and a beneficial supplement to current research findings of e-WOM, providing an important reference for potential air passengers to identify useful reviews accurately and thus reduce safety risks in online decision-making.

Evaluating the couriers' experiences of logistics platform: The extension of expectation confirmation model and technology acceptance model.

The current study integrated the Extended Technology Acceptance Model (TAM) and included information system quality (ISQ), user interface (UI), knowledge sharing motivation (KSM), the expectation confirmation model (ECM), safety management practices (SMP), interface aesthetics (IA), and perceived value (PV) to evaluate the logistics couriers' experience while using an Online logistics platform. This research examines the relationships of KSM, SMP, and ISQ on the TAM's, perceived usefulness (PU), and perceived ease of use (PEOU). In addition, it explores the relationship between UI on PEOU. Furthermore, to explore the impact of ECM, it examines the impact of confirmation (CON) on PU and satisfaction (SAT). Finally, this research explores the impact of logistics couriers' SAT on continuous intention (CI). According to the findings of this study, UI did not have a significant association with PEOU. Furthermore, KSM was found to significantly impact PEOU, while having no significant effect on PU. Moreover, SMP was found to have no significance on PEOU, however, SMP was discovered to be in a significant association with PU. In addition, ISQ was found to significantly impact PEOU, PU, and, PV. Moreover, CON was in a significant relationship with PU, while not having a significant impact on SAT. Furthermore, IA did not significantly impact PV. Also, SAT was significantly impacted by PU, while not having any significant impact from PEOU, and PV. Besides, PEOU was discovered to significantly impact PU. Finally, SAT was found to be in a significant relationship with CI.

Interaction between official institutions and influential users of rumor control in online social networks.

Online interactions have become major channels for people to obtain and disseminate information during the new normal of COVID-19, which can also be a primary platform for rumor propagation. There are many complex psychological reasons for spreading rumors, but previous studies have not fully analyzed this problem from the perspective of the interaction between official institutions and influential users. The purpose of this study is to determine optimal strategies for official institutions considering the impact of two different influential user types (trolls and reputed personalities) by designing two game-theoretic models, namely "Rumor Clarification and Interaction Model" and "Rumor Verification and Interaction Model," which can, respectively decide whether to clarify and when to clarify. The results of this article show that clarification strategies can be decided according to the characteristics of rumors and the influential user's reactions. Meanwhile, publishing verified information prevents trolls' "loophole advantages" and prevents reputed personalities from spreading false information due to the vague authenticity of rumors. Results also show that the verification strategy is limited by cost, period, and verification index.

Enterprise Information Security Management Using Internet of Things Combined with Artificial Intelligence Technology.

This work is conducted to deal with the information security of enterprise management under the background of current global informatization, popularize the modern Internet of Things (IoT) management technology of enterprises, and maintain the information security of enterprises and provide modern upgrading means for enterprise management. In this work, it firstly introduces the application scenarios of current Internet and Artificial Intelligence (AI) technology and expounds the IoT technology. Secondly, the enterprise management platform is designed, the requirements of enterprise modern management are analyzed, and then the design requirements of system functions and the design of the information security architecture of the IoT are proposed. Furthermore, an enterprise information security management platform is designed, which covers four parts: IoT data mining management, equipment management, key management, and database management. In addition, the performance of the security management platform is tested from four parts: concurrency testing, stress testing, large data volume testing, and security testing. The research results show that the IoT-based enterprise information security management platform designed in this work under the background of AI has perfect functions and stable performance of each module. Concurrency testing, stress testing, large data volume testing, and stability testing are performed on it, and the success rate of the platform in each task reaches 100%. The average response time of concurrent testing and stress testing is about 0.13 seconds, and that of the event entry events is 0.25 seconds. The central processing unit (CPU) occupancy rate in each monitoring task is always lower than 20%. Therefore, it is determined that the performance of the IoT-based enterprise information security management platform designed in this work is sufficient to meet the daily management of enterprises. This work can provide a guarantee for enterprise information security management using AI technology, setting an example for future related research.

The impact of price transparency of bundled vacation packages on travel decision making: An experimental study.

Price transparency is a vital factor in consumers' judgements and decisions. When selecting a bundled vacation package, travelers are often influenced by transparency in the prices of individual elements of the package. However, because of the diversity of elements bundled in a vacation package, it is a challenge to research the impact of price transparency. To try to overcome this challenge, our study used five experiments to examine the primary impact of element price transparency on travelers' purchases, along with the moderating effects of consumer involvement and the vertical position of element prices in product descriptions. For the primary effect, we found that tourists preferred vacation packages with low transparency in element prices. We also found that the primary effect of price transparency remained consistent and robust across both revised and actual vacation packages. For moderating effects, we found that tourists with low involvement attached greater importance to price transparency than those with high involvement when the element price was presented higher in the product description of the travel package. The findings of the five experiments have theoretical implications for price transparency and Heuristic-systematic Model and practical implications for tourism professionals designing and marketing vacation packages.

Exploring user-generated content related to vegetarian customers in restaurants: An analysis of online reviews.

This study aimed to explore and evaluate factors that impact the dining experience of vegetarian consumers within a range of vegetarian-friendly restaurants. To explore the factors and understand consumer experience, this study analyzed a vast number of user-generated contents of vegetarian consumers, which have become vital sources of consumer experience information. This study utilized machine-learning techniques and traditional methods to examine 54,299 TripAdvisor reviews of approximately 1,008 vegetarian-friendly restaurants in London. The study identified 21 topics that represent a holistic opinion influencing the dining experience of vegetarian customers. The results suggested that "value" is the most popular topic and had the highest topic percentage. The results of regression analyses revealed that five topics had a significant impact on restaurant ratings, while 12 topics had negative impacts. Restaurant managers who pay close attention to vegetarian aspects may utilize the findings of this study to satisfy vegetarian consumer requirements better and enhance service operations.

Will Costliness Amplify the Signalling Strength of Past Pro-Environmental Behaviour? Exploratory Study on Autonomy.

Research has shown that the extent to which previous environmental actions are linked to people's environmental self-identity influences subsequent environmentally-friendly behaviour. The study empirically examined the influences of recycling efforts on subsequent pro-environmental behaviour by PLS (partial least squares) structural equation modelling based on the survey data of 426 respondents in China. The results indicate that recycling efforts have a positive effect on pro-environmental behaviour through the mechanism of feelings of pride and environmental self-identity. We hypothesise that past pro-environmental behaviour is more likely to promote an individual's environmental self-identity when the behaviour is incurred with a higher costliness. However, the results show that only when individuals autonomously perform costly recycling behaviour, the signalling strength of previous recycling efforts is higher to promote environmental self-identity. On the contrary, the high costliness weakens the signalling strength of previous recycling efforts through producing negative emotions. Our results show that when reminding people of their past pro-environmental behaviour in order to promote future pro-environmental behaviour, it is useful to emphasize the autonomously taken costliness of behaviour as it can strongly signal that one is a pro-environmental person, thus as to strengthen environmental self-identity.

Effects of Self-Expressive Brand and Susceptibility to Interpersonal Influence on Brand Addiction: Mediating Role of Brand Passion.

Although the concept of the consumer-brand relationship has undergone rapid change over the past two decades, the issue of brand addiction is still generally neglected in the literature. Based on social identity theory, the research develops a conceptual model of the influence of self-expressive brands (SEBs) and susceptibility to interpersonal influence (SUSCEP) on brand addiction. The results of this research demonstrate both separate and joint effects of SEBs and SUSCEP on brand addiction. In addition, harmonious brand passion and obsessive brand passion positively mediate the relationships among SEB, SUSCEP, and brand addiction. The research explores the formation mechanism of brand addiction from a new perspective and has important practical implications for brand marketers concerned with finding the most effective means to enhance the consumer-brand relationship.