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Owing to the limitations of traditional infectious disease dynamic systems in accurately encapsulating the nuances of China’s dynamic epidemic prevention policies and considering the varying sensitivity of local governments to the unfolding of public health emergencies (PHEs), this paper introduces a novel infectious disease dynamic system.

This system, rooted in the distinct characteristics of infectious diseases and nuanced prevention and control measures, leverages a learning model for enhanced precision. It intricately incorporates factors such as the infectivity in sealed and controlled areas and the role of asymptomatic patients, thereby refining the dynamics of isolation, sealing, control and the transition from asymptomatic to confirmed cases. Employing the Markov Chain Monte Carlo (MCMC) parameter estimation approach significantly augments the accuracy in pinpointing the valid parameters of disease spread. Empirical analysis was meticulously carried out, using data from the Shanghai epidemic from 1 Mar 2022 to 1 Jul 2022.

This analysis not only illuminates the profound impact of control efforts on the trajectory of the epidemic but also underscores the pivotal role of social distancing in curbing the rapid transmission of infectious diseases. Furthermore, it reveals that an accelerated detection rate during the swift spread and peak of the epidemic paradoxically leads to a surge in confirmed cases and a consequent strain on medical resources, thereby impeding the pace of medical intervention.

A stage-wise dissection of the Shanghai epidemic and comparative analyses against the evolution profiles in ASEAN countries elucidates the five stages of PHE risk evolution in alignment with the crisis lifecycle theory. These stages encompass hidden transmission, multi-point dissemination, multi-chain parallelism, rapid spread, fluctuation rebound and multi-community spread, each presenting unique challenges and dynamics in the control and management of the epidemic.

How to identify the critical success factors (CSFs) of public health emergencies (PHEs) is of great practical significance to carry out a scientific and effective risk assessment. The purpose of this paper is to address this issue.

In this paper, the authors propose a new approach to identify the CSFs by hesitant fuzzy linguistic set and a Decision-Making Trial and Evaluation Laboratory (DEMATEL) approach. First, a larger group of experts are clustered into three groups according to similarity degree. Then, the weight of each cluster is determined by the maximum consensus method, and the overall direct influence matrix is obtained by clustering with hesitant fuzzy linguistic weighted geometric (HFLWG) operators. Finally, the overall direct influence matrix is transformed into the crisp direct impact matrix by the score function, and 11 CSFs of PHEs are identified by using the extended DEMATEL method.

In addition, an example of PHEs shows that the approach has good identification applicability. The approach can be used to solve the problems of fuzziness and subjectivity in linguistic assessments, and it can be applied to identify the customer service framework with the linguistic assessments process in emergency management.

This paper extends the above DEMATEL method to study in the hesitant fuzzy linguistic context. This proposed hybrid approach has a wider application in the high-risk area where disasters frequently occur.

The purpose of this paper is to quantify the implications of China's recently adopted agricultural policies on domestic and international commodity markets.

A systematic, quantitative analysis is applied to address whether China's recent trade and production policies distort China's domestic and international commodity markets. The paper provides a clear picture of how trade‐restricting policies affect markets using a 42‐country partial equilibrium global dynamic agricultural simulation model.

The paper shows that recent agricultural policy reforms increase China's production slightly, causing imports to decrease while exports decline because of input subsidies, export taxes and the reduction of export value added tax rebates. Domestic prices to consumers decrease in real terms. The effects on world markets are small as the set of policies adopted partially offset each other in the international arena.

The paper indicates that the adoption of the policy reforms lower price levels domestically and benefit lower income urban and rural households, whose diets are largely based on rice and wheat as staple foods. Future model enhancements should include measures of producer and consumer welfare in order to capture the total impacts of policies and policy changes in China.

The paper quantifies the potential implications of the recent agricultural policy reforms in China. This contributes to the investigation of the effects of these policies implemented by the Chinese Government to achieve the country's policy objectives. Owing to the dynamics of China's policy implementation an in‐depth analysis sheds light and contributes to capturing the impacts of policy reforms on the domestic and international markets.

The purpose of this paper is to identify the historical trends and status of the national development of artificial intelligence (AI) from a nationwide perspective and to enable governments at different administrative levels to promote AI development through policymaking.

This paper analyzed 248 Chinese AI policies (36 issued by the state agencies and 212 by the regional agencies). Policy bibliometrics, policy instruments and network analysis were used to reveal the AI policy patterns. Three aspects were analyzed: the spatiotemporal distribution of issued policies, the policy foci and instruments of policy contents and the cooperation and citation among policy-issuing agencies.

Results indicate that Chinese AI development is still in the initial phase. During the policymaking processes, the state and regional policy foci have strong consistency; however, the coordination among state and regional agencies is supposed to be strengthened. According to the issuing time of AI policies, Chinese AI development is in accordance with the global situation and has witnessed unprecedented growth in the last five years. And the coastal provinces have issued more targeted policies than the middle and western provinces. Governments at the state and regional levels have emphasized familiar policy foci and played the role of policymakers, along with regional governments that also functioned as policy executors as well. According to the three-dimension instruments coding, the authors found an uneven structure of policy instruments at both levels. Furthermore, weak cooperation appears at the state level, while little cooperation is found among regional agencies. Regional governments cite state policies, thus leading to the formation of top-down diffusion, lacking bottom-up diffusion.

The paper contributes to the literature by characterizing policy patterns from both external attributes and semantic contents, thus revealing features of policy distribution, contents and agencies. What is more, this research analyzes Chinese AI policies from a nationwide perspective, which contributes to clarifying the overall status and multi-level relationships of policies. The findings also benefit the coordinated development of governments during further policymaking processes.

The purpose of this paper is to analyse the policy instruments used by the China's Government on prefabricated construction (PC) development, with the aim to clarify the pattern and discover the focus of the policy instruments using the methods of bibliometric analysis and content analysis.

Through a thorough screening by all researchers, 25 policies were identified from 1995 to 2021 were selected and analysed. The external attribute analysis clarified the issuing year, organisation, and the format of each policy. The content analysis was adopted firstly to analyse the policy instrument. An analysis framework including environmental instruments, supply instruments and demand instruments was applied in categorising and counting of each policy instrument. The bibliometric analysis was then carried out to extract keywords of the policy instruments, construct a co-word network and complete the cluster analysis.

The results indicate that the policies lack consistency and had relatively low authority. The results of content analysis show that the policy system relies heavily on environmental and supply instruments, whilst the use of demand instruments seems to be grossly inadequate. The results of the bibliometric analysis identify the core ideas of each policy instrument category, discuss the existing problems and then put forward the corresponding countermeasures.

This study comprehensively and systematically analysed the policy instruments on facilitating the development of PC in China which broaden the research perspectives of the PC development by introducing the methods of political science. The research findings afford helpful information for future policy adjustments and elucidate the effective delivery of policies to facilitate PC development for developing countries.

This study provides an in-depth understanding of policy instruments used by China's Government on PC development. By integrating the policy instrument analysis framework into the mixed methods of content analysis and bibliometric analysis, this study provides an innovative way to conduct policy instrument analysis.

For a better understanding of the preferences and differences of young consumers in emerging wine markets, this study aims to propose a clustering method to segment the super-new generation wine consumers based on their sensitivity to wine brand, origin and price and then conduct user profiles for segmented consumer groups from the perspectives of demographic attributes, eating habits and wine sensory attribute preferences.

We first proposed a consumer clustering perspective based on their sensitivity to wine brand, origin and price and then conducted an adaptive density peak and label propagation layer-by-layer (ADPLP) clustering algorithm to segment consumers, which improved the issues of wrong centers' selection and inaccurate classification of remaining sample points for traditional DPC (DPeak clustering algorithm). Then, we built a consumer profile system from the perspectives of demographic attributes, eating habits and wine sensory attribute preferences for segmented consumer groups.

In this study, 10 typical public datasets and 6 basic test algorithms are used to evaluate the proposed method, and the results showed that the ADPLP algorithm was optimal or suboptimal on 10 datasets with accuracy above 0.78. The average improvement in accuracy over the base DPC algorithm is 0.184. As an outcome of the wine consumer profiles, sensitive consumers prefer wines with medium prices of 100–400 CNY and more personalized brands and origins, while casual consumers are fond of popular brands, popular origins and low prices within 50 CNY. The wine sensory attributes preferred by super-new generation consumers are red, semi-dry, semi-sweet, still, fresh tasting, fruity, floral and low acid.

Young Chinese consumers are the main driver of wine consumption in the future. This paper provides a tool for decision-makers and marketers to identify the preferences of young consumers quickly which is meaningful and helpful for wine marketing.

In this study, the ADPLP algorithm was introduced for the first time. Subsequently, the user profile label system was constructed for segmented consumers to highlight their characteristics and demand partiality from three aspects: demographic characteristics, consumers' eating habits and consumers' preferences for wine attributes. Moreover, the ADPLP algorithm can be considered for user profiles on other alcoholic products.

This study addresses the integration of Industry 4.0 (I4.0) technologies with circular economy (CE) principles in the UAE construction sector, aligning with the UAE Circular Economy Policy 2021–2031 (UAECEP). It explores how digital tools can facilitate sustainable construction practices by enhancing resource efficiency, reducing waste and supporting circularity across the building life cycle.

A systematic literature review (SLR) was conducted to identify frameworks that integrate I4.0 technologies with CE principles. Based on the review, a conceptual framework was developed and refined to meet the UAE construction sector’s specific needs, focusing on applying digital tools at different stages of construction.

Integrating I4.0 tools, including building information modeling (BIM), the Internet of Things (IoT) and artificial intelligence (AI), can enhance resource efficiency, reduce waste and promote sustainability in the UAE’s construction sector. The framework aligns digital transformation efforts with the UAECEP, indicating these technologies’ applicability in design, construction, operation and end-of-life stages. Key challenges include high initial costs, technical limitations and the need for regulatory support.

This study offers a novel framework tailored to the UAE construction sector, bridging the gap between policy objectives and practical implementation. It provides strategies to overcome local challenges through stakeholder collaboration and digital innovation, contributing to the UAE’s sustainability goals.

Conventional frequent itemsets mining ignores the fact that the relative benefits or significance of “transactions” belonging to different customers are different in most of the relevant applied studies, which leads to failure to obtain some association rules with lower support but from higher-value consumers. Because not all customers are financially attractive to firms, it is necessary that their values be determined and that transactions be weighted. The purpose of this study is to propose a novel consumer preference mining method based on conventional frequent itemsets mining, which can discover more rules from the high-value consumers.

In this study, the authors extend the conventional association rule problem by associating the “annual purchase amount” – “price preference” (AP) weight with a consumer to reflect the consumer’s contribution to a market. Furthermore, a novel consumer preference mining method, the AP-weclat algorithm, is proposed by introducing the AP weight into the weclat algorithm for discovering frequent itemsets with higher values.

The experimental results from the survey data revealed that compared with the weclat algorithm, the AP-weclat algorithm can make some association rules with low support but a large contribution to a market pass the screening by assigning different weights to consumers in the process of frequent itemsets generation. In addition, some valuable preference combinations can be provided for related practitioners to refer to.

This study is the first to introduce the AP-weclat algorithm for discovering frequent itemsets from transactions through considering AP weight. Moreover, the AP-weclat algorithm can be considered for application in other markets.

Claims that, in Singapore, there is intense competition among local banks, hence increasing emphasis is being placed on offering a high quality customer service. Investigates how customers choose which banks to use, taking into account factors such as non‐verbal communication (including behavioural/interpersonal communication and environmental – deriving meaning from one’s surroundings); convenience; reputation; supply of information; and cosmetic factors such as the bank’s stationery. Uses a verbal questionnaire survey to examine the effect non‐verbal communication has on bank patrons’ attitudes. Evaluates banks’ businesslike approach, competency, friendliness, warmness, environment, electronic tellers, location and queueing. Makes a number of recommendations on how banks can improve their image and the service they offer.