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The high-pressure accumulator has been widely used in the hydraulic system. Failure pressure prediction is crucial for the safe design and integrity assessment of the accumulators. The purpose of this study is to accurately predict the burst pressure and location for the accumulator shells due to internal pressure.

This study concentrates the non-linear finite element simulation procedure, which allows determination of the burst pressure and crack location using extensive plastic straining criterion. Meanwhile, the full-scale hydraulic burst test and the analytical solution are conducted for comparative analysis.

A good agreement between predicted and measured the burst pressure that was obtained, and the predicted failure point coincided very well with the fracture location of the actual shell very well. Meanwhile, the burst pressure of the shells increases with wall thickness, independent of the length. It can be said that the non-linear finite element method can be employed to predict the failure behavior of a cylindrical shell with sufficient accuracy.

This paper can provide a designer with additional insight into how the pressurized hollow cylinder might fail, and the failure pressure has been predicted accurately with a minimum error below 1%, comparing the numerical results with experimental data.

The basic purpose of this study is to increase the installation rate of mobile games and their life cycle. Little research has been conducted into the competitive market of mobile games and word-of-mouth (WOM), advertisement and quality simultaneously. In this paper, the authors aim to assist developers with a better understanding of how to invest in the game industry.

The primitive modeling has been made based on the Bass diffusion model and its extensions using features related to the game industry. Modeling and simulation have been performed using the system dynamics method.

The results show that if game developers only focus on advertising at the introduction of the game to the market, and neglect quality features, uninstall rate of adopters increases and the game life cycle decreases. And if developers only focus on the quality improvement of the game, and ignore advertisement, they couldn't create enough WOM and thus game installation wouldn't grow enough to create revenue. Furthermore, as long as the pleasure of the game is high for its adopters, developers shouldn't give up on investing in advertising to create even higher WOM. And also in communities with higher levels of variety-seeking among game players, quality is important at the start and advertisement is vital in the following steps of the game life cycle. And if the contact rate among people is high, developers could focus on quality more than the advertisement.

Even though WOM in mobile game installation is crucial, fewer studies have been done in this area and they only address the problem using qualitative or statistical methods. The quantitative system dynamics approach based on the Bass diffusion model, used in this research, fixes the shortcomings of the previous studies. Moreover, due to serious competition in the mobile game industry, only those developers can remain in the market who can predict the future trend of the game market. Furthermore, game development is a creative process and its key factors include engaging the gamers and monetizing.

The objective of this study is to examine how formal and informal institutional environment influences managers’ fair value opinion shopping behaviour in the largest International Financial Reporting Standards adopter, China.

To test the hypotheses, I conduct a 2 × 2 between-subject randomised experiment since the inferences about cause and effect are important in this study. The between-subject experimental situations are manipulated on the basis of the financial condition of companies and boards’ oversight.

I find that managers are likely to seek favourable fair value opinions from external valuation professionals when they are under the weak boards’ oversight and high stress to meet the regulation target of the China Securities Regulatory Commission. These results are more pronounced for managers with higher both rent-seeking and favour-seeking guanxi orientations are more likely to engage in fair value opinion shopping.

Consistent with theoretical analysis of Balfoort et al. (2017), this study provides empirical evidence that guanxi influences the neutrality and faithful representation in fair value measurement in China. In addition, the findings extend Salzsieder’s study (2015) and reflect the context-embeddedness nature of accounting.

This article proposes an architecture of an intelligent and autonomous recommendation system to be applied to any virtual learning environment, with the objective of efficiently recommending digital resources. The paper presents the architectural details of the intelligent and autonomous dimensions of the recommendation system. The paper describes a hybrid recommendation model that orchestrates and manages the available information and the specific recommendation needs, in order to determine the recommendation algorithms to be used. The hybrid model allows the integration of the approaches based on collaborative filter, content or knowledge. In the architecture, information is extracted from four sources: the context, the students, the course and the digital resources, identifying variables, such as individual learning styles, socioeconomic information, connection characteristics, location, etc. Tests were carried out for the creation of an academic course, in order to analyse the intelligent and autonomous capabilities of the architecture.

The present study is intended to develop an effective approach to the real-time modeling of general dynamic nonlinear systems based on the multidimensional Taylor network (MTN).

The authors present a detailed explanation for modeling the general discrete nonlinear dynamic system by the MTN. The weight coefficients of the network can be obtained by sampling data learning. Specifically, the least square (LS) method is adopted herein due to its desirable real-time performance and robustness.

Compared with the existing mainstream nonlinear time series analysis methods, the least square method-based multidimensional Taylor network (LSMTN) features its more desirable prediction accuracy and real-time performance. Model metric results confirm the satisfaction of modeling and identification for the generalized nonlinear system. In addition, the MTN is of simpler structure and lower computational complexity than neural networks.

Once models of general nonlinear dynamical systems are formulated based on MTNs and their weight coefficients are identified using the data from the systems of ecosystems, society, organizations, businesses or human behavior, the forecasting, optimizing and controlling of the systems can be further studied by means of the MTN analytical models.

MTNs can be used as controllers, identifiers, filters, predictors, compensators and equation solvers (solving nonlinear differential equations or approximating nonlinear functions) of the systems of ecosystems, society, organizations, businesses or human behavior.

The operating efficiency and benefits of social systems can be prominently enhanced, and their operating costs can be significantly reduced.

Nonlinear systems are typically impacted by a variety of factors, which makes it a challenge to build correct mathematical models for various tasks. As a result, existing modeling approaches necessitate a large number of limitations as preconditions, severely limiting their applicability. The proposed MTN methodology is believed to contribute much to the data-based modeling and identification of the general nonlinear dynamical system with no need for its prior knowledge.

Though daycare centres are built to facilitate children's social and physical growth, divergent stakeholder perceptions yield conflicts while managing risks for each space due to the minimal guidelines in the Republic of Korea. Due to the unclearly defined knowledge and experience gap between representative stakeholders, teachers have difficulties in operating it with high satisfaction. This study therefore was conducted to systematically identify which parts of performance should be increased to preferentially increase end-user satisfaction in limited resources.

This research conducted quantitative analysis gradually. Importance–performance analysis (IPA) grasped the perceptions of construction practitioners and end-users after identifying space composition and representative risks of daycare centres. Based on the factors influencing perception differences, principal component analysis and structural equation modelling (SEM) were conducted to determine which space improves the performance preferentially to increase overall end-user satisfaction.

As the utilisation of indoor spaces increases after COVID-19, improvement of indoor spaces except for indoor playroom is necessary, especially, advancement of the quality of teachers' rooms.

Outputs by reflecting the end-user experiences support to understand which spaces are managed from the limited resources.

Theoretical framework for daycare centre was established in Korea where guidelines were insufficient, and differences in perception of each risk of stakeholders were identified. Moreover, gradual statistical analysis was set to construct end-user-focused centres by extracting where the performance of space should be improved in prior.

Broiler meat is the most commonly used meat product worldwide. Although China is regarded as one of the three largest broiler producers, the per capita chicken consumption remains low. Consumers' cognitive bias and the information acquisition channels are believed to be the main factors contributing to this. This paper aims to discuss the aforementioned issue.

To explore the phenomenon empirically, the current study uses the survey data of 1,056 consumers from China and analyses them using ordered logistic regression.

The results revealed that consumers' cognitive bias significantly affects their behaviour toward broiler products, and the order of influence is cognitive bias regarding industry cognitive > product nutrition and taste > food safety. The study further revealed that the more diverse the information acquisition channels, the more likely they are to promote consumer behaviour toward broiler chickens. The order of influence of the channels was self-organising > new media > traditional media.

Overall, the findings suggest that the government and enterprises should strengthen and upgrade information channels to boost both the broiler industry and consumer consumption behaviour regarding poultry products.

Rather than the usual focus on the impact of consumer cognition on consumer behaviour, this study examines the impact of cognitive bias on consumer behaviour. Further, centring on broiler products with high protein, low fat and feed-to-meat ratios, this study explores the reasons the per capita consumption of broiler products in China is far lower than the national average.

The purpose of this study is to understand the effect of different brand positions (underdog vs top dog) and comparative advertising on consumers’ brand attitudes. Additionally, this study also aims to demonstrate the effects of inspiration, self-relevance and empathy on the relationship between brand positioning and comparative advertising.

A two-by-three factorial design was employed with brand positions (underdog vs top dog) and three types of comparative advertising (noncomparative, indirect comparative and direct comparative) as the independent variables. Inspiration serves as the mediator, while self-relevance and empathy act as moderators and brand attitude is the dependent variable.

The results show that different brand positions significantly affect brand attitudes, with respondents having a better brand attitude toward the underdog brand. Brand attitude is partially mediated by inspiration. Self-relevance moderates the relationship between brand positioning and brand attitude. However, brand positioning, comparative advertising and empathy do not have interaction effects.

This study contributes to a better understanding of the effect of psychological variables on brand positioning and comparative advertising.

The results suggest that the underdog setting requires a real and honest story because consumers will spot a fake underdog story, which will damage consumer trust in the brand and harm the brand image.

There is a lack of research using psychological variables to demonstrate the effect of being the underdog brand. This study contributes to the literature by employing psychological variables to illustrate the effect of underdog positioning. These findings can help brands develop branding positioning strategies.

This study aims to investigate how artificial intelligence (AI)-powered smart home devices affect young consumers' requirements for convenience, support, security and monitoring, as well as their ability to advance environmental sustainability. This study also examines the variables that impact users' motivation to use AI-powered smart home devices, such as perceived value, ease of use, social presence, identity, technology security and the moderating impact of trust.

The responses from residents of Sarawak, Malaysia, were collected through online questionnaires. This study aimed to examine the perceptions of millennials and zillennials towards their trust and adoption of AI-powered devices. This study used a quantitative approach, and the relationships among the study constructs were analysed using partial least squares - structural equation modelling.

The present study found that perceived usefulness, ease of use and social presence were the main motivators among actual and potential users of smart home devices, especially in determining their intentions to use and actual usage. Additionally, there was a moderating effect of trust on the relationship between perceived ease of use, social presence, social identity and intention to use AI-powered devices in smart homes.

To the best of the authors’ knowledge, this is one of the first studies to examine the factors influencing smart technology adoption. This study provided meaningful insights on the development of strategies for the key stakeholders to enhance the adoption and usage of AI-powered smart home devices in Sarawak, one of the promising Borneo states. Additionally, this study contributed to the growing body of knowledge on the associations between technology acceptance model dimensions, intention and actual usage of smart technology, with the moderating impact of trust.

This study empirically examined consumer adoption attitudes and behaviors toward nonfungible tokens (NFTs). Findings indicate that consumer attitudes toward NFTs are influenced by perceived usefulness, reliability and profit expectancy and that strong attitudes are associated with purchase intentions. Additionally, the relationship between attitudes and purchase intentions was moderated by technology optimism.

The authors utilized a partial least squares (PLS) model to examine the hypotheses in this empirical analysis. Obtaining a sample of actual NFT holders or experienced users is challenging. A total of 105 individuals participated in the study as valid responders by answering the screening question in the questionnaire. The authors opted for the PLS model as a research approach due to the limited size of the consumer population in the NFT market.

This study discovered that the adoption of NFTs was affected by technical aspects such as usefulness and reliability and the potential for future asset growth. Furthermore, the degree of attitude-to-intention conversion varied based on optimism, an inherent characteristic.

This study offers valuable insights for NFT owners, content providers and trading firms. For the NFT market to expand, it must meet consumers' expectations for the desired content features and asset investment attributes. Additionally, customer targeting strategies should attract and appeal to technology enthusiasts with an optimistic outlook on technology.

The authors conducted an initial empirical analysis of actual NFT consumers, an area of research studied sparingly despite its significance.