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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.

This paper aims to analyze and provide insight on the algorithms for the optimization of construction site layout planning (CSLP). It resolves problems, such as the selection of suitable algorithms, considering the optimality, optimization objectives and representation of layout solutions. The approaches for the better utilization of optimization algorithms are also presented.

To achieve the above, existing records (results = 200) were selected from three databases: Web of Science, ScienceDirect and Scopus. By implementing a systematic protocol, the articles related to the optimization algorithms for the CLSP (results = 75) were identified. Moreover, various related themes were collated and analyzed according to a coding structure.

The results indicate the consistent and increasing interest on the optimization algorithms for the CLSP, revealing that the trend in shifting to smart approaches in the construction industry is significant. Moreover, the interest in metaheuristic algorithms is dominant because 65.3% of the selected articles focus on these algorithms. The optimality, optimization objectives and solution representations are also important in algorithm selection. With the employment of other algorithms, self-developed applications and commercial software, optimization algorithms can be better utilized for solving CSLP problems. The findings also identify the gaps and directions for future research.

The selection of articles in this review does not consider the industrial perspective and practical applications of commercial software. Further comparative analyses of major algorithms are necessary because this review only focuses on algorithm types.

This paper presents a comprehensive systematic review of articles published in the recent decade. It significantly contributes to the demonstration of the status and selection of CLSP algorithms and the benefit of using these algorithms. It also identifies the research gaps in knowledge and reveals potential improvements for future research.

This study aims to adopt a cognitive heuristic approach to investigate the interaction effect of a message source characteristic (reviewer expertise [RE]) and two message structure characteristics (review rating consistency [RC] and review valence [RV]) on the perceived credibility of hotel online reviews.

Data were collected from 242 university students and were analyzed by three-way analysis of variance through a 2 × 2 factorial experiments using a simulated hotel review page on TripAdvisor.

Results show a three-way interaction effect of RE, RC and RV on the perceived credibility of hotel online reviews. The main effects of the three factors are also determined. Higher perceived credibility scores are found for negative reviews, reviews written by experts and reviews with a consistent rating.

This study adopts an experimental approach and is the first to investigate the three-way interactions of message source and message structure characteristics of online hotel reviews. Data were collected from students in a university in Hong Kong. Results may not be generalizable to other markets.

Results suggest that reviews written by experts have higher perceived credibility. Hotels should pay attention to the content of online reviews and the expertise level of reviewers. Efforts should be exerted to create positive experiences for hotel guests that motivate expert reviewers to write positive reviews. Note that negative reviews have higher perceived credibility than positive ones. Hotels should promptly address negative reviews and provide professional responses to reviewers. Platform operators of user-generated content (UGC) should create well-defined reviewer profiles that can serve as cues that communicate the different expertise of reviewers.

This study is the first to test the three-way interaction effect of RE, RC and RV on the perceived credibility of hotel online reviews. Results provide recommendations to hotels and UGC operators and enable them to benefit from emerging UGC usage.

With more demand-driven innovation activities, manufacturers must proactively engage in information sharing activities with their customers for better innovation performance. This study aims to inquire into the impacts of information sharing activities between manufacturers and customers (including information system usage and information content sharing) on manufacturers’ innovation performance and considers interfirm justice (including distributive justice, procedural justice and interactional justice) as information sharing antecedents.

The social exchange theory is applied to develop the conceptual model. The authors examine the conceptual model with the structural equation modeling approach using data collected from 213 Chinese manufacturers.

Interactional justice promotes information system usage. Both interactional justice and procedural justice increase information content sharing, while distributive justice decreases it. Information content sharing directly improves innovation performance and fully mediates the relationship between information system usage and innovation performance.

This research enriches empirical studies on justice-information sharing relationships by systematically investigating the impacts of three types of justice on different information sharing activities. It also adds to the application of social exchange theory in the practices of interfirm justice and information sharing. Besides, it probes into influencing mechanisms of different information sharing activities, information system usage and information content sharing, on innovation performance. The findings can guide firms to implement interfirm justice and information sharing practices for superior innovation performance.

The purpose of this paper is to identify the key influencing factors of aviation accidents and to predict the aviation accidents caused by the factors.

This paper proposes an improved gray correlation analysis (IGCA) theory to make the relational analysis of aviation accidents and influencing factors and find out the critical causes of aviation accidents. The optimal varying weight combination model (OVW-CM) is constructed based on gradient boosted regression tree (GBRT), extreme gradient boosting (XGBoost) and support vector regression (SVR) to predict aviation accidents due to critical factors.

The global aviation accident data from 1919 to 2020 is selected as the experimental data. The airplane, takeoff/landing and unexpected results are the leading causes of the aviation accidents based on IGCA. Then GBRT, XGBoost, SVR, equal-weight combination model (EQ-CM), variance-covariance combination model (VCW-CM) and OVW-CM are used to predict aviation accidents caused by airplane, takeoff/landing and unexpected results, respectively. The experimental results show that OVW-CM has a better prediction effect, and the prediction accuracy and stability are higher than other models.

Unlike the traditional gray correlation analysis (GCA), IGCA weights the sample by distance analysis to more objectively reflect the degree of influence of different factors on aviation accidents. OVW-CM is built by minimizing the combined prediction error at sample points and assigns different weights to different individual models at different moments, which can make full use of the advantages of each model and has higher prediction accuracy. And the model parameters of GBRT, XGBoost and SVR are optimized by the particle swarm algorithm. The study can guide the analysis and prediction of aviation accidents and provide a scientific basis for aviation safety management.

The purpose of this study is to optimize and improve conventional welding using EMF assisted technology. Current industrial production has put forward higher requirements for welding technology, so the optimization and improvement of traditional welding methods become urgent needs.

External magnetic field assisted welding is an emerging technology in recent years, acting in a non-contact manner on the welding. The action of electromagnetic forces on the arc plasma leads to significant changes in the arc behavior, which affects the droplet transfer and molten pool formation and ultimately improve the weld seam formation and joint quality.

In this paper, different types of external magnetic fields are analyzed and summarized, which mainly include external transverse magnetic field, external longitudinal magnetic field and external cusp magnetic field. The research progress of welding behavior under the effect of external magnetic field is described, including the effect of external magnetic field on arc morphology, droplet transfer and weld seam formation law.

However, due to the extremely complex physical processes under the action of the external magnetic field, the mechanism of physical fields such as heat, force and electromagnetism in the welding has not been thoroughly analyzed, in-depth theoretical and numerical studies become urgent.

It is unclear what constitutes the tourism live streaming (TLS) servicescape and how it affects users' travel intention (TI). The study aims to explore the composition of the TLS servicescape, the influence mechanism of the TLS servicescape on users' TI and the formation of users' TI.

Based on stimulus organism response theory (SOR), we develop a mediation model to explore the influence of TLS servicescape on users' TI. This study collected data from 432 Chinese TLS users through an online questionnaire, and we used the structural equation model and the SPSS PROCESS macro to test the proposed model. In addition, we tested the variable relationships using fuzzy-set qualitative comparative analysis (fsQCA).

TLS servicescape is a second-order variable that can be categorized into physical element (PE), social element (SOE), symbolic element (SYE) and natural element (NE). TLS servicescape influences TI by affecting social presence (SP) and customer engagement (CE). The fsQCA reveals seven combinations of PE, SOE, SYE, NE, SP and CE that form a high TI for TLS users.

Using multiple data analysis methods, the study emphasizes the significance of the TLS servicescape for TLS. It explores how to evoke users' TI in TLS and provides a reference for TLS marketing.

This paper aims to identify the direct impact of fund style drift on the risk of stock price collapse and the intermediary mechanism of financial risk, so as to better protect the interests of minority investors.

This paper takes all the non-financial companies on the Chinese Growth Enterprise Market from 2011 to 2020 as study object and selects securities investment funds of their top ten circulation stocks to study the relationship between fund style drift and stock price crash risk.

Fund style drift is likely to add stock price crash risk. Financial risk is positively correlated with stock price crash risk. Fund style drift affects stock price crash risk via the mediating effect of financial risk, and fund style drift and financial risk have a marked impact on the stock price crash risk of non-state enterprises, yet a non-significant impact on that of state-owned enterprises.

This paper links fund style drift with stock price crash risk in an exploratory manner and enriches the study perspectives of relationship between institutional investors’ behaviors and stock price crash risk, thus enjoying certain academic value. On the one hand, it furnishes a new approach to the academic frontier issue concerning financial risk and stock price crash risk, and proves that financial risk is positively correlated with stock price crash risk. On the other hand, it regards financial risk as a mediating variable of fund style drift for stock price crash risk and further explores different influencing mechanism of institutional investors’ behaviors.

The purpose of this study is to investigate the influence of brand equity on corporate financial performance across various institutional factors in China, encompassing macro (regional economic development and product market development), meso (industry uncertainty), and micro (CEO overseas experience) levels.

Using archival data related to Chinese listed companies, this study employs standard error combined with fixed effect regression for model estimation to empirically evaluate the impact of brand equity on financial performance (Tobin’s q) and its boundary effects.

This study reveals that in China, the influence of brand equity on Tobin’s q isn’t significant. However, when considering institutional factors across various levels, its impact becomes significant. Specifically, the positive effect of brand equity on Tobin’s q in China is more pronounced in regions with higher economic or product market development, industries with high uncertainty, or when the CEO has overseas experience.

This study enriches the brand-related marketing literature in China and highlights the potential underperformance of brand equity within this context. Furthermore, this study advances the integration of resource-based view with institutional theory by combining brand equity with institutional factors at the macro-, meso-, and micro-level in China.

This study focuses on brand performance in China, the largest emerging market, emphasizing the importance of integrating brand equity with diverse institutional factors to amplify its beneficial influence on financial performance.

Hydrodynamic parameter estimation is significant for the velocity prediction of unmanned surface vehicles. Considering the field data’s uncertain nonlinearities (environmental disturbances and measurement noise), this paper aims to propose a hybrid adaptive parameter estimation (HAPE) strategy.

First, a rough estimation of hydrodynamic parameters is used by the least squares method. Second, an improved adaptive parameter estimation algorithm is applied to compensate for the influence of uncertain nonlinearities and adjust the parameters within the rough range. Finally, it is proved that the calculated velocity asymptotically converges to the actual value during the parameter estimation procedure.

The numerical simulation and pool experiments are conducted in two scenarios of steady turning and sinusoidal thrust to verify the effectiveness of the proposed HAPE method. The results validate that the accuracy of the predicted velocity using the hydrodynamic model obtained by the HAPE strategy is better than the APE algorithm. In addition, the hydrodynamic parameters estimated with the sinusoidal thrust data are more applicable than the steady turning data.

This study proposes a HAPE strategy that considers the uncertain nonlinearities of the field data. This method provides a more accurate predicted velocity. Besides, as far as we know, it is the first time to analyze the influence of different test conditions on the accuracy of the predicted velocity.