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The primary purpose of this study is to investigate the influence of tourists' perceived value, satisfaction and behavioral intention on the development of Lipu Yi costume culture to promote the development of intangible cultural tourism and better construct a model of the influencing factors of Lipu Yi costumes in the development of intangible cultural heritage tourism.

The study site is the intangible cultural district of Panzhihua, Sichuan Province, China. This study examines the interrelationships between tourists' perceived value of experience, behavioral intention and satisfaction as the tourists relate to Lipu Yi costume and intangible cultural heritage tourism. A sample of 225 tourists who had visited Panzhihua at least once was selected for the study.

All seven of the survey's hypotheses were supported. Therefore, this study concludes that tourists' perceived value, satisfaction and behavioral intention directly affect the development of intangible cultural tourism and significantly positively impact the growth of Lipu Yi costumes culture. Descriptive analysis, confirmatory factor analysis (CFA) and structural equation modeling (SEM) investigation methods were used.

This paper analyzes tourists' perceived value of Lipu costume culture and tourists' satisfaction and behavioral intention during the tourism process. This study provides a more in-depth understanding of the relationship between Lipu Yi costume and non-heritage tourism factors. Practical methods and approaches are sought to further develop Lipu Yi costume non-heritage tourism.

This paper presents an original approach for learning models, partially known, of particular interest when performing source identification or structural health monitoring. The proposed procedures employ some amount of knowledge on the system under scrutiny as well as a limited amount of data efficiently assimilated.

Two different formulations are explored. The first, based on the use of informed neural networks, leverages data collected at specific locations and times to determine the unknown source term of a parabolic partial differential equation. The second procedure, more challenging, involves learning the unknown model from a single measured field history, enabling the localization of a region where material properties differ.

Both procedures assume some kind of sparsity, either in the source distribution or in the region where physical properties differ. This paper proposed two different neural approaches able to learn models in order to perform efficient inverse analyses.

Two original methodologies are explored to identify hidden property that can be recovered with the right usage of data. Both methodologies are based on neural network architecture.

The purpose of this paper is to explore an association between women experience lifetime intimate partner violence (IPV) and women decision making with utilization of reproductive and maternal health services in Cambodia.

An analysis of secondary data of Cambodia Demographic and Health Survey (CDHS) 2014. The total number of sample size was 1,539 married women who had birth in the last five years prior to the time of interview and completed the domestic violence module in the CDHS 2014 questionnaire. χ² test and binary logistic regression were performed in this study.

Results give an evidence that emotional violence had significant impact on receiving sufficient antenatal care (ANC) (OR: 0.7, 95%CI: 0.43–0.86) while physical violence had significant association with deliver with skilled birth attendance (SBA) (OR: 0.5, 95%CI: 0.27–0.79). Further, women’s participation in household decision making played as important factor in enabling women revive sufficient ANC (OR: 1.7, 95%CI: 1.19–2.29), and utilization of modern contraceptive method (OR: 1.5, 95%CI: 1.09–1.97).

This study provides significant finding on the impact of IPV and women’s decision making on reproductive and maternal health in Cambodia. Result has drawn an attention to policy makers, related ministries and stakeholder to promulgate and effectiveness of policies and program implementation within the country.

The goal was to improve the quality of the hospitalization process and the management of patients, allowing the reduction of costs and the minimization of the preoperative Length of Hospital Stay (LOS).

The methodology used to improve the quality of the hospitalization process and patient management was Lean Thinking. Therefore, the Lean tools (Value stream map and Ishikawa diagram) were used to identify waste and inefficiencies, improving the process with the implementation of corrective actions. The data was collected through personal observations, patient interviews, brainstorming and from printed medical records of 151 patients undergoing oral cancer surgery in the period from 2006 to 2018.

The authors identified, through Value Stream Map, waste and inefficiencies during preoperative activities, consequently influencing preoperative LOS, considered the best performance indicator. The main causes were identified through the Ishikawa diagram, allowing reflection on possible solutions. The main corrective action was the introduction of the pre-hospitalization service. A comparative statistical analysis showed the significance of the solutions implemented. The average preoperative LOS decreased from 4.90 to 3.80 days (−22.40%) with a p-value of 0.001.

The methodology allowed to highlight the improvement of the patient hospitalization process with the introduction of the pre-hospitalization service. Therefore, by adopting the culture of continuous improvement, the flow of hospitalization was redrawn. The benefits of the solutions implemented are addressed to the patient in terms of lower LOS and greater service satisfaction and to the hospital for lower patient management costs and improved process quality. This article will be useful for those who need examples on how to apply Lean tools in healthcare.

Dual design for additive manufacturing (DfAM) takes into account both the opportunities and constraints of AM simultaneously, which research shows is more effective than considering them separately. Unlike existing reviews, this paper aims to map DfAM research within the engineering design process, focusing solely on studies adopting dual DfAM. Additionally, it aims to suggest future research directions by analysing prominent research themes and their inter-relationships. Special emphasis is on theme inter-relationships concerning the conceptual, embodiment and detail design phases.

The study is based on a systematic literature review of 148 publications from January 2000 to February 2024. After screening, prominent research themes were identified and systematically analysed. Theme inter-relationships were explored using quantitative analysis and chord diagrams.

The findings reveal that studies either span the entire design process, the early design phases or the later design phases. Most research focuses on the later design phases, particularly within themes of design optimisation, design evaluation and AM-specific manufacturing constraints. The most frequent theme inter-relationship occurs between design optimisation and AM-specific manufacturing constraints. Overall, the findings suggest future research directions to advance dual DfAM research, such as development of design rules and guidelines for cellular structures.

This review proposes a model by mapping prominent themes of dual DfAM research in relation to the engineering design process. Another original contribution lies in analysing theme inter-relationships and visualising them using chord diagrams – a novel approach that did not exist before.

This paper introduces a new mathematical model for analyzing the economic benefits of incorporating the fourth party logistics (4PL), which is a contractor (i.e. agent) for the supply chain coordination and construction based on the division of community and the outsourcing development. Based on the physical theory and the wave-particle duality, a supply chain is the special organization whose characteristic has wave-particle duality. The mathematical model enriches the connotation of 4PL and it broadens the thought for 4PL development. Secondly, the proposed mathematical model predicated on transaction costs, is supported by Transaction Cost Theory (TCT) and acts as the theoretical analysis tool of 4PL for coordinating 3-party generic supply chain. Through the model, some trendy conclusions can be drawn to provide theoretical support for 4PL’s practices. Finally, a case illustrates our conclusions.

The evolution of crowd intelligence is a mainly concerns issue in the field of crowd science. It is a kind of group behavior that is superior to the individual’s ability to complete tasks through the cooperation of many agents. In this study, the evolution of crowd intelligence is studied through the clustering method and the particle swarm optimization (PSO) algorithm.

This study proposes a crowd evolution method based on intelligence level clustering. Based on clustering, this method uses the agents’ intelligence level as the metric to cluster agents. Then, the agents evolve within the cluster on the basis of the PSO algorithm.

Two main simulation experiments are designed for the proposed method. First, agents are classified based on their intelligence level. Then, when evolving the agents, two different evolution centers are set. Besides, this paper uses different numbers of clusters to conduct experiments.

The experimental results show that the proposed method can effectively improve the crowd intelligence level and the cooperation ability between agents.

This paper proposes a crowd evolution method based on intelligence level clustering, which is based on the clustering method and the PSO algorithm to analyze the evolution.

In a supply-constrained region like Asia, promoting exports has always been a challenge particularly at a time when Asia’s trade has been severely affected by lack of external demand. This paper argues that price barriers have taken a new shape during the global financial crisis period which may generate differential impacts on trade flows as we proceed toward recovery. The size and shape of price barriers would be higher if NTBs, applied by the countries during the crisis period, were counted. One of the conclusions of this paper is that ‘price’ barrier is still more important than ‘non-price’ barrier in enhancing Asia’s trade and integration. The higher the price barrier between countries in a pair, the less they trade. In other words, a 10 percent increase in the ad-valorem price (transport and tariff) lowered trade by 6 percent. Tariff and transport costs, each considered separately, also influence the trade flow in the same direction, to more or less the same extent. There are indications of huge domestic infrastructure bottlenecks in countries in Asia. Based on direct and indirect evidence related to trade barriers, this paper concludes that complementary trade policies focusing on price and non-price barriers have immense importance in enhancing international trade and integration in the post-crisis period.

This study aims to investigate the impact of the 2022 collapse of the Terra-Luna ecosystem on volatility correlations among digital assets, including U.S. Terra, Luna, Bitcoin, Ether, a Decentralized Finance index and U.S.-sourced conventional assets stocks, bonds, oil, gold and the dollar index. The primary research question addresses whether correlations increased between digital and conventional assets during the collapse.

A dynamic conditional correlation generalized autoregressive conditional heteroskedasticity model was used to examine changes in volatility correlations during the market crash. Specifically, a data set of 1,442 close prices from 30-minute interval candles of digital and conventional asset prices are considered to provide a granular view of market dynamics during the sample period from January 3rd, 2022, to May 31st, 2022, including the crash event.

While the dynamic conditional correlation plots of the model indicate increased volatility, the results do not offer sufficient evidence to confirm an increase in correlations between digital and conventional assets during the Terra-Luna downfall. Furthermore, the authors confirm Bitcoin’s role as a diversifier with oil and observe the dollar index maintaining a negative correlation with Bitcoin during the crash, supporting Bitcoin’s function as a hedge against the U.S. dollar. However, the findings during the crash diverge from previous studies, reflecting shifts in correlation patterns in broader market downturns. Specifically, the authors identify the need for adaptive capital allocation strategies, as gold’s oscillation during the period suggests it may not serve as an effective hedge during black swan events.

The findings provide insights for investors, financial institutions and regulators to improve risk management, portfolio diversification, trading strategies and the formulation of consumer protection regulations. In addition, the results underscore the challenges of mitigating risks beyond regulatory measures and emphasize the importance of exercising caution for investors.

This study addresses the research gap in changes between conventional and digital asset volatility correlations during collapses in the digital asset space.

This paper aims to identify the relationship between participation motivation, satisfaction and exercise adherence intention of golf range users on the basis of self-determination theory.

For this purpose, the authors proposed research questions and a conceptual research model as well. Then, the authors surveyed users of golf ranges located in Seoul Metropolitan City and Gyeonggi-do province.

By applying convenience sampling, the authors received a total of 313 questionnaires. Results were as follows. First, among the participation motivation sub-factors, health-oriented motivation, achievement motivation, pleasure-oriented motivation and self-displayed motivation had a significant effect on emotional satisfaction, while achievement motivation and pleasure-orientation motivation had a significant effect on performance satisfaction. Second, the following participation motivation factors had a significant effect on exercise adherence intention: health-orientation motivation, achievement motivation and pleasure-orientation motivation. Third, among the satisfaction factors, emotional satisfaction and performance satisfaction both had a significant effect on exercise adherence intention.

This is one of the first papers to examine the relationships that exist between golf range users’ participation motivation, satisfaction and exercise adherence intention.