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This study aims to conceptualize the characteristics of artificial intelligence (AI) dogs while exploring their applications in tourism and hospitality settings.

The total of 30 in-depth interviews were conducted, and data were analyzed through thematic analysis.

This study proposed differences between AI dogs and real dogs and human-like robots, core characteristics of AI dogs’ functions, a matrix of appearance and expectation regarding intelligence for AI dogs and human-like robots, the relationship between ethical barriers and task complexity, adoptions of AI dogs in different user segments and practical applications in hospitality and tourism settings, such as restaurants, city tour guides, extended-stay resorts and event organizations.

This research advances the field of tourism and hospitality studies by introducing the new concept of AI dogs and their practical applications. This present study adds new insights into the opportunities and contexts of human–robot interaction in the field of tourism and hospitality.

To the best of the authors’ knowledge, this research is one of the first studies of AI dogs in tourism and hospitality.

This paper's aim is to investigate how Chinese consumers' purchase intention of private label drugs is associated with price advantage, appearance, store trust, manufacturer trust, and drug quality.

A survey study was conducted in two large cities in China. Subjects were asked to decide whether they would purchase a private label drug over a national brand drug and to evaluate a set of related factors. Data were collected from 230 consumers.

A total of 45 percent of the variance in private label drug purchase intention is explained by the five predictors. Price advantage, store trust, manufacturer trust, and drug quality are all significantly related to purchase intention, whereas appearance is not. None of the control variables (age, gender, health literacy, and income) has a significant relationship with purchase intention. Product quality and service quality are significant predictors of store trust, accounting for 44 percent of its variance.

The private label drug market has great potential in China, yet little is known about what factors influence Chinese consumers' intention to purchase private label drugs.

This paper is one of the first attempts to achieve an in‐depth understanding in this area. The findings of this research will benefit drug retailers and manufacturers who are interested in the Chinese market.

With respect to the multiple-attribute decision-making problem with subjective preference for a certain attribute whose weight-value range have been given over other attributes whose weight values are unknown, a method based on the mean value of the grey number is proposed to analyse the decision-making problem. This method is used to choose a supply-chain partner under the condition that the decision makers have a preference for a certain attribute of various alternatives. The paper aims to discuss these issues.

First, the middle value of the preferred attribute’s weight-value range is supposed to be its weight value according to the content of the mean value of the grey number. Second, to reflect the decision maker’s subjective preference information, an improved optimisation model that requests the minimum deviation between the actual and expected numerical value of each attribute is constructed to assess the attributes’ weights. Third, the correlated degree and the correlation matrix, which are determined by the weight values of all attributes, are used to rank all the alternatives.

This paper provides a method for making a decision when decision makers have a preference for a certain attribute from an array of various alternatives, and the range of the certain attribute’s weight value is given but the weight value of the other attributes is unknown. When applied to supply-chain partner selection, this method proves feasible and effective.

This method is feasible and effective when applied to supply-chain partner selection, and can be applied to other kinds of decision-making problems. This means it has significant theoretical importance and extensive practical value.

Based on the mean value of the grey number, an optimisation model is built to determine the importance degree of each attribute, then the correlated degree of each alternative is combined to rank all the alternatives. This method can suit the decision makers’ subjective preference for a certain attribute well.

Founded in 2004, OPPO has experienced the boom of the Chinese mobile phone market, the trend of mobile Internet and the prosperity of the smartphone market. While adjusting its business structure based on changes in the market environment, it has transitioned itself from an audio device manufacturer to a smart-phone manufacturer that offers hardware, software, and service.

This case study focuses on OPPO's evolution and strategy, and provides an insight into its history, competition, and strategic choices based on whether or not OPPO should release a feature phone with a foldable display at the MWC 2019, and discusses the core competitiveness that helped OPPO succeed against the market downturn. This case study helps students understand the development of corporate strategies and the process of building core competitiveness in the microcompetition in the red ocean market. We also wish to help students understand how to come up with the most appropriate decision-making framework and conduct a critical analysis on the issues based on the internal and external factors of their businesses while they make strategic decisions. When it comes to different dimensions and indicators coming to contradictory conclusions in particular, what should the manager of a business do to make the correct strategic decision?

This study aims to investigate if smartphone sensors can be used in an unmanned aerial vehicle (UAV) localization system. With the development of technology, smartphones have been tentatively used in micro-UAVs due to their lightweight, inexpensiveness and flexibility. In this study, a Samsung Galaxy S3 smartphone is selected as an on-board sensor platform for UAV localization in Global Positioning System (GPS)-denied environments and two main issues are investigated: Are the phone sensors appropriate for UAV localization? If yes, what are the boundary conditions of employing them?

Efficient accuracy estimation methodologies for the phone sensors are proposed without using any expensive instruments. Using these methods, one can estimate his phone sensors accuracy at any time without special instruments. Then, a visual-inertial odometry scheme is introduced to evaluate the phone sensors-based path estimation performance.

Boundary conditions of using smartphone in a UAV navigation system are found. Both indoor and outdoor localization experiments are carried out and experimental results validate the effectiveness of the boundary conditions and the corresponding implemented scheme.

With the phone as a payload, UAVs can be further realized in smaller scale at lower cost, which will be used widely in the field of industrial robots.

Online ratings (review valence) have been found to exert a strong influence on hotel room prices. This study aims to systematically synthesize research estimating the impact of online ratings on room rates using a meta-analytical method.

From major academic databases, a total of 163 estimates of the effects of online ratings on room rates were coded from 22 studies across different countries through a systematic review of relevant literature. All estimates were converted into elasticity-type effect sizes, and a hierarchical linear meta-regression was used to investigate factors explaining variations in the effect sizes.

The median elasticity of online ratings on hotel room rates was estimated to be 0.851. Meta-regression results highlighted four categories of factors moderating the size of this elasticity: data characteristics, research settings, variable measures and publication outlet. Among sub-ratings, results revealed value rating and room rating to exert the largest impact on room rates, whereas staff and cleanliness ratings demonstrated non-significant impacts.

This study provides practical implications on the relative importance of different types of online ratings for online reputation and revenue management.

This study represents the first research effort to understand factors moderating the effects of online ratings on hotel room rates based on a quantitative review of the literature. Moreover, this study provides beneficial insights into the specification of empirical hedonic pricing models and data-collection strategies, such as the selection of price variables and choices of model functional forms.

This purpose of the study is to evaluate areas of application of internet of things (IoT) in the construction industry, with the view of increasing the level of usage of technology. This will help in understanding the areas where IoT can be applied in the construction industry for better improvement.

A quantitative approach was adopted for this study, and the adopted questionnaire was structured on a five-point Likert scale to elicit the opinion of respondents in the areas of application of IoT in the construction industry. The respondents included are quantity surveyors, land surveyors, builders, architects and engineers. Bar chart, mean item score, one sample t-test and Kruskal–Wallis H test were used in analyzing the retrieved data.

The results showed that building information modeling, construction management, remote usage monitoring, equipment services and repair, construction tools and equipment tracking are areas where IoT is mostly applied in the industry. Site monitoring is the only factor that has significant difference in the opinions of professionals, while others do not have. One sample t-test revealed that three factors out of 12 do not have significance attached by professionals.

The study gives insight into different areas where IoT can be applied in the construction industry. It also highlights how its application can be improved through workshops, training, seminar and conference for construction professionals to keep themselves abreast of information and communication technology trends, especially in the aspect of IoT. The IoT adoption helps in accomplishing sustainable infrastructural projects with more convenience.

The purpose of this paper is to assess the adoption of internet of things (IoT) element with the view of increasing usage so that benefits of convenience, increased performance and timely completion of work can be improved. This research was conducted so that there can be increase in the usage of IoT elements for construction performance and sustainability.

The study adopted survey design and various construction professionals were used to assessing the level of adoption of IoT elements. Convenience sample was used by distributing the structured questionnaire to registered professionals. Mean score, bar chart, Kruskal–Wallis H test, one-sample t-test and Shapiro–Wilk were used for analyzing the data gathered.

The findings revealed that wireless fidelity, visualization, wireless sensor networks, Bluetooth, electronic product code and internet protocol are the most adopted element of IoT in the industry. The study also shows that there are areas where there is no significance attached by construction professionals in the usage of IoT elements. These are data storage and analytics, barcode, Zigbee, gateway, near field communication and actuators. It is recommended that less significant areas can be improved through training and educating professionals about the whole concept of IoT and other design professionals. When the importance of IoT elements are understood it will help in the level of adoption.

This paper highlights the possible ways of increasing the adoption of IoT elements with a view to achieving better usage for convenience, high productivity of workers and easy access to information.

The purpose of this study is to examine how the implementation of edge computing can enhance the progress of the circular economy within supply chains and to address the challenges and best practices associated with this emerging technology.

This study utilized a streamlined evaluation technique that employed Latent Dirichlet Allocation modeling for thorough content analysis. Extensive searches were conducted among prominent publishers, including IEEE, Elsevier, Springer, Wiley, MDPI and Hindawi, utilizing pertinent keywords associated with edge computing, circular economy, sustainability and supply chain. The search process yielded a total of 103 articles, with the keywords being searched specifically within the titles or abstracts of these articles.

There has been a notable rise in the volume of scholarly articles dedicated to edge computing in the circular economy and supply chain management. After conducting a thorough examination of the published papers, three main research themes were identified, focused on technology, optimization and circular economy and sustainability. Edge computing adoption in supply chains results in a more responsive, efficient and agile supply chain, leading to enhanced decision-making capabilities and improved customer satisfaction. However, the adoption also poses challenges, such as data integration, security concerns, device management, connectivity and cost.

This paper offers valuable insights into the research trends of edge computing in the circular economy and supply chains, highlighting its significant role in optimizing supply chain operations and advancing the circular economy by processing and analyzing real time data generated by the internet of Things, sensors and other state-of-the-art tools and devices.