How Sense of Ritual in Tourism Impacts Tourists’Co-Creation of Tourism Experience Values:A Study Based on the Theory of Value Co-Creation

Establishing a sense of ritual within tourism consumption scenarios offers tourists the opportunity for interactive engagement.Drawing upon the value co-creation theory,this study constructed an influence mechanism model to examine tourists'active engagement in the process of co-creating tourism experience values.It employed Partial Least Squares Structural Equation Modeling(PLS-SEM)to empirically test the proposed hypotheses.The findings demonstrate that the model constructed in the present study exhibits robust reliability,validity,and explanatory power.The perception of the sense of ritual in tourism exerts a significant positive influence on tourists’co-creation of tourism experience values,thereby significantly enhancing both the communitas and flow experienced by tourists during their travels.Moreover,such communitas and flow can mediate the influence of the sense of ritual in tourism on tourists’co-creation of tourism experience values.This study contributes to advancing the current research on tourists’co-creation of tourism experience values and the sense of ritual in tourism,thereby providing theoretical foundations for cultivating a sense of ritual within tourism consumption scenarios.

The Mediating Effect of Social Media on the Relationship Between Travel Preference and Tourist Behavior of Local Tourists in Davao City

This paper aims to determine the mediating effect of social media on the relationship between travel behavior and tourist preference.This paper utilized the mediation analysis design to determine whether social media significantly affects the independent and dependent variables.For the statistical tools,the proponents of the study utilized descriptive statistics,Sobel’s test,mean and standard deviation.Also,the proponents of the study utilized data from questionnaires gathered through an online google form.Most of the respondents are single females,college-level,and use Facebook most of the time.Therefore,this is the social media platform that the majority utilize.It has been revealed in the study the three sets of correlated variables:Travel behavior vs.tourist behavior,travel preference vs.social media,and social media vs.tourist behavior,have a strong positive linear relationship between the two quantitative variables.Thus,the study proponents concluded that there is an indirect effect between the travel preference and tourist behavior of local tourists in Davao City via social media.Lastly,the study’s findings reveal the fundamentals of how visitors make decisions,which are essential for enhancing the competitive advantages of cultural destinations.Significant findings from the study are beneficial to the growth of cultural tourism in Davao City.

Tourists’Willingness to Pay for Recreation Services in Nyerere National Park,Tanzania:Are We Overvaluing or Undervaluing Our Nature Recreation Resources?

This study estimated tourists’Willingness to Pay(WTP)per day for recreation services in Nyerere National Park(NNP)and compared these values with daily travel costs that are incurred by tourists to visit NNP in order to inform whether recreation resources in the park are overvalued or undervalued.The study revealed that tourists’WTP per day for recreation services was estimated at$237.4 and$1521 for resident and non-resident tourists,respectively.The estimated tourists’WTP values exceed the daily travel costs currently incurred by tourists,which are$201.04 and$1517.97 for resident and non-resident tourists,respectively.This indicates that tourists are willing to spend more to enjoy recreation services in NNP,which signifies that recreation resources in NNP are slightly undervalued.In addi­tion,the findings disclosed that the largest share of tourist daily travel expenses is allocated to transportation services,and very little is paid to the park as a conservation fee.It was revealed that out of the daily travel expenses incurred by non-resident and resident tourists,only 4.62%and 2.23%are respectively paid directly to NNP as conservation fees.This study considers that allocation is not very fair;thus,NNP,in collaboration with TANAPA,needs to adjust the current entrance or conservation fee and reduce the transportation costs charged by tourist companies.The travel costs incurred by tourists,age,education,monthly income,site visited,substitute site,and quality of park were identified as significant factors in influencing tourists’WTP for recreation services in NNP.Thus,policies oriented to reduce tour­ists’transportation costs and improve the quality of national parks would attract more tourists to NNP.

Return of Chinese Tourists

South Africa on 29 March received the first group of 13 tourists from China over the past three years.The tourists,taking a flight from Air China,landed at O.R.Tambo International Airport in Johannesburg and were welcomed by people from different walks of life.

Research on Demand Response Potential of Adjustable Loads in Demand Response Scenarios

To address the issues of limited demand response data,low generalization of demand response potential evaluation,and poor demand response effect,the article proposes a demand response potential feature extraction and prediction model based on data mining and a demand response potential assessment model for adjustable loads in demand response scenarios based on subjective and objective weight analysis.Firstly,based on the demand response process and demand response behavior,obtain demand response characteristics that characterize the process and behavior.Secondly,establish a feature extraction and prediction model based on data mining,including similar day clustering,time series decomposition,redundancy processing,and data prediction.The predicted values of each demand response feature on the response day are obtained.Thirdly,the predicted data of various characteristics on the response day are used as demand response potential evaluation indicators to represent different demand response scenarios and adjustable loads,and a demand response potential evaluation model based on subjective and objective weight allocation is established to calculate the demand response potential of different adjustable loads in different demand response scenarios.Finally,the effectiveness of the method proposed in the article is verified through examples,providing a reference for load aggregators to formulate demand response schemes.

A Combination Prediction Model for Short Term Travel Demand of Urban Taxi

This study proposes a prediction model considering external weather and holiday factors to address the issue of accurately predicting urban taxi travel demand caused by complex data and numerous influencing factors.The model integrates the Complete Ensemble Empirical Mode Decomposition with Adaptive Noise(CEEMDAN)and Convolutional Long Short Term Memory Neural Network(ConvLSTM)to predict short-term taxi travel demand.The CEEMDAN decomposition method effectively decomposes time series data into a set of modal components,capturing sequence characteristics at different time scales and frequencies.Based on the sample entropy value of components,secondary processing of more complex sequence components after decomposition is employed to reduce the cumulative prediction error of component sequences and improve prediction efficiency.On this basis,considering the correlation between the spatiotemporal trends of short-term taxi traffic,a ConvLSTM neural network model with Long Short Term Memory(LSTM)time series processing ability and Convolutional Neural Networks(CNN)spatial feature processing ability is constructed to predict the travel demand for urban taxis.The combined prediction model is tested on a taxi travel demand dataset in a certain area of Beijing.The results show that the CEEMDAN-ConvLSTM prediction model outperforms the LSTM,Autoregressive Integrated Moving Average model(ARIMA),CNN,and ConvLSTM benchmark models in terms of Symmetric Mean Absolute Percentage Error(SMAPE),Root Mean Square Error(RMSE),Mean Absolute Error(MAE),and R2 metrics.Notably,the SMAPE metric exhibits a remarkable decline of 21.03%with the utilization of our proposed model.These results confirm that our study provides a highly accurate and valid model for taxi travel demand forecasting.

Stochastic programming based coordinated expansion planning of generation,transmission,demand side resources,and energy storage considering the DC transmission system

With the increasing penetration of wind and solar energies,the accompanying uncertainty that propagates in the system places higher requirements on the expansion planning of power systems.A source-grid-load-storage coordinated expansion planning model based on stochastic programming was proposed to suppress the impact of wind and solar energy fluctuations.Multiple types of system components,including demand response service entities,converter stations,DC transmission systems,cascade hydropower stations,and other traditional components,have been extensively modeled.Moreover,energy storage systems are considered to improve the accommodation level of renewable energy and alleviate the influence of intermittence.Demand-response service entities from the load side are used to reduce and move the demand during peak load periods.The uncertainties in wind,solar energy,and loads were simulated using stochastic programming.Finally,the effectiveness of the proposed model is verified through numerical simulations.

Optimal dispatching strategy for residential demand response considering load participation

To facilitate the coordinated and large-scale participation of residential flexible loads in demand response(DR),a load aggregator(LA)can integrate these loads for scheduling.In this study,a residential DR optimization scheduling strategy was formulated considering the participation of flexible loads in DR.First,based on the operational characteristics of flexible loads such as electric vehicles,air conditioners,and dishwashers,their DR participation,the base to calculate the compensation price to users,was determined by considering these loads as virtual energy storage.It was quantified based on the state of virtual energy storage during each time slot.Second,flexible loads were clustered using the K-means algorithm,considering the typical operational and behavioral characteristics as the cluster centroid.Finally,the LA scheduling strategy was implemented by introducing a DR mechanism based on the directrix load.The simulation results demonstrate that the proposed DR approach can effectively reduce peak loads and fill valleys,thereby improving the load management performance.

Optimal Bidding Strategies of Microgrid with Demand Side Management for Economic Emission Dispatch Incorporating Uncertainty and Outage of Renewable Energy Sources

In the restructured electricity market,microgrid(MG),with the incorporation of smart grid technologies,distributed energy resources(DERs),a pumped-storage-hydraulic(PSH)unit,and a demand response program(DRP),is a smarter and more reliable electricity provider.DER consists of gas turbines and renewable energy sources such as photovoltaic systems and wind turbines.Better bidding strategies,prepared by MG operators,decrease the electricity cost and emissions from upstream grid and conventional and renewable energy sources(RES).But it is inefficient due to the very high sporadic characteristics of RES and the very high outage rate.To solve these issues,this study suggests non-dominated sorting genetic algorithm Ⅱ(NSGA-Ⅱ)for an optimal bidding strategy considering pumped hydroelectric energy storage and DRP based on outage conditions and uncertainties of renewable energy sources.The uncertainty related to solar and wind units is modeled using lognormal and Weibull probability distributions.TOU-based DRP is used,especially considering the time of outages along with the time of peak loads and prices,to enhance the reliability of MG and reduce costs and emissions.

A Novel Defender-Attacker-Defender Model for Resilient Distributed Generator Planning with Network Reconfiguration and Demand Response

To improve the resilience of a distribution system against extreme weather,a fuel-based distributed generator(DG)allocation model is proposed in this study.In this model,the DGs are placed at the planning stage.When an extreme event occurs,the controllable generators form temporary microgrids(MGs)to restore the load maximally.Simultaneously,a demand response program(DRP)mitigates the imbalance between the power supply and demand during extreme events.To cope with the fault uncertainty,a robust optimization(RO)method is applied to reduce the long-term investment and short-term operation costs.The optimization is formulated as a tri-level defenderattacker-defender(DAD)framework.At the first level,decision-makers work out the DG allocation scheme;at the second level,the attacker finds the optimal attack strategy with maximum damage;and at the third level,restoration measures,namely distribution network reconfiguration(DNR)and demand response are performed.The problem is solved by the nested column and constraint generation(NC&CG)method and the model is validated using an IEEE 33-node system.Case studies validate the effectiveness and superiority of the proposed model according to the enhanced resilience and reduced cost.

Vehicle routing optimization algorithm based on time windows and dynamic demand

To provide the supplier with the minimizum vehicle travel distance in the distribution process of goods in three situations of new customer demand,customer cancellation service,and change of customer delivery address,based on the ideas of pre-optimization and real-time optimization,a two-stage planning model of dynamic demand based vehicle routing problem with time windows was established.At the pre-optimization stage,an improved genetic algorithm was used to obtain the pre-optimized distribution route,a large-scale neighborhood search method was integrated into the mutation operation to improve the local optimization performance of the genetic algorithm,and a variety of operators were introduced to expand the search space of neighborhood solutions;At the real-time optimization stage,a periodic optimization strategy was adopted to transform a complex dynamic problem into several static problems,and four neighborhood search operators were used to quickly adjust the route.Two different scale examples were designed for experiments.It is proved that the algorithm can plan the better route,and adjust the distribution route in time under the real-time constraints.Therefore,the proposed algorithm can provide theoretical guidance for suppliers to solve the dynamic demand based vehicle routing problem.

A system-integrated approach for the design of tourist areas at the local level under changing conditions:A case study in the Altay Mountains

The existing approaches for the design of tourist areas often lead to limited flexibility in project implementation.To realize a more flexible approach,in this study,we formulated a model for planning and designing tourist areas at the local level.Moreover,specific tools for analyzing tourist areas and ensuring sustainable development under changing conditions were developed.This study was conducted in two tourist regions,Biryuzovaya Katun tourist complex and Belokurikha destination(including Belokurikha City with Belokurikha 2 Gornaya tourist complex and surrounding areas),in the Altay Mountains.We employed the recreation opportunity spectrum and proposed a system-integrated programming approach for the design of tourist areas at the destination and site levels.The key of this approach was the collection and analysis of current spatial data,including the spatial distribution of attractions and visitor flows.We constructed heat maps using video recording and unmanned aerial vehicle(UAV)observation data.Moreover,we analyzed the video stream using an image-analyzing framework You Only Look Once(YOLO)v5 software.The heat map of visitor flows based on video recording data in the Andreevskaya Sloboda museum of Belokurikha 2 Gornaya tourist complex allowed us to highlight the most attractive sites in this area and classify them into one of three types:points of functional concentration,points of transitional concentration,and points of attractions.The heat maps in Biryuzovaya Katun tourist complex,created using UAV observation data,allowed us to determine the spatiotemporal patterns of visitor flows and tourists’preferences throughout the day within four time intervals:09:00-12:00,13:00-14:00,14:00-15:00,and 16:00-18:00(LST).The maximum visitor flow density occurred from 16:00 to 18:00 in the beach area of the artificial lake.A comparison between the visitor-concentrated sites and the current facilities provided insights into the demand for attractions and facilities and the lacking areas.Heat maps are useful in analyzing the land use at the site level,while zoning based on the recreation opportunity spectrum can be used to design tourist areas at the destination level.The proposed methods for analyzing the use of tourist areas contribute to the development of adaptive tourism design.

A Note on an Order Level Inventory Model with Varying Two-Phased Demand and Time-Proportional Deterioration

The main purpose of this paper is to generalize the effect of two-phased demand and variable deterioration within the EOQ (Economic Order Quantity) framework. The rate of deterioration is a linear function of time. The two-phased demand function states the constant function for a certain period and the quadratic function of time for the rest part of the cycle time. No shortages as well as partial backlogging are allowed to occur. The mathematical expressions are derived for determining the optimal cycle time, order quantity and total cost function. An easy-to-use working procedure is provided to calculate the above quantities. A couple of numerical examples are cited to explain the theoretical results and sensitivity analysis of some selected examples is carried out.

Tourists' Demand for Heritage Utilization Based on Fuzzy Comprehensive Evaluation:A Case Study of the Summer Palace

Under the background of whole-region tourism,heritage is utilized in a more diversified and various way.With the continuous deepening of the experience economy,the integration of various technical means such as VR and AR,and the construction of Internet platforms,it is more necessary to integrate various utilization methods,so that tourists can get more humanized and personalized experience in addition to traditional displays,and more intuitively feel the space,history,allusions,handicrafts and other aspects of Chinese heritage,showing the charm of Chinese traditional culture.In this paper,based on literature analysis,the utilization methods of heritage were sorted out,and the survey questionnaires were analyzed by analytic hierarchy process (AHP).A model was established to obtain the weight of various utilization methods,and the fuzzy comprehensive evaluation method was used to conduct empirical research with the Summer Palace as an example.It is concluded that in the future utilization of heritage,on the basis of heritage protection as much as possible,combining traditional festivals,special themes,etc.to carry out various forms of activity and experience utilization will more effectively improve the satisfaction of tourists and achieve the purpose of inheriting culture.

Fuzzy Inventory Model under Selling Price Dependent Demand and Variable Deterioration with Fully Backlogged Shortages

The objective is to develop a model considering demand dependent on selling price and deterioration occurs after a certain period of time, which follows two-parameter Weibull distribution. Shortages are allowed and fully backlogged. Fuzzy optimal solution is obtained by considering hexagonal fuzzy numbers and for defuzzification Graded Mean Integration Representation Method. A numerical example is provided for the illustration of crisp and fuzzy, both models. To observe the effect of changes in parameters, sensitivity analysis is carried out.

Demand and Analysis of Clinical Research Curriculum in Medical Universities

Objective:To investigate the needs of medical students regarding clinical research curricula to provide scientifically sound offerings and cultivate their clinical research thinking.Methods:From June to October 2022,medical students at medical universities in Shaanxi Province were surveyed using online questionnaires.The survey covered their demographic information,awareness of their major,understanding of clinical research,and preferences for curriculum content.Results:A total of 341 valid questionnaires were analyzed.Medical students demonstrated a strong awareness of their majors but a relatively low awareness of clinical research.There was significant demand for clinical research courses,with preferences for professionally oriented(81.8%),market-oriented(100%),theoretically and practically integrated teaching(78.6%),and application-focused(73.0%)courses.Conclusion:Medical colleges and universities should align clinical research curricula with the actual needs of medical students and clinical practice.Reforms in curriculum design and teaching methods are essential to better prepare students for careers in public health.

Survey on the Demand for Elderly Care Services of Community Residents in Beijing and Analysis of Influencing Factors

Objective: To investigate the current situation of the demand for geriatric care services of community residents in Beijing and analyze the influencing factors to provide a reference basis for meeting the demand for diversified and professional geriatric care services. Methods: A self-made questionnaire was used to randomly survey 1558 elderly individuals at community health service centers in 8 urban districts where elderly care centers were planned to be built. The influencing factors of the different characteristics of elderly care service needs from three aspects were analyzed using a dichotomous logistic regression model: predisposing, enabling, and, need factors. Results: 69.7% of the elderly required home care services, 22.8% wanted to get care services at elderly care centers, 15.9% wanted to get care services at nursing homes, 12.3% required community care services, and 7.4% didn’t know where to access care services. 68.5% of the elderly required care services for disabilities/semi-disabilities, 58.0% for dementia, 54.7% for common diseases, 34.9% for rehabilitation training, 33.0% for plumbing care, and 7.5% for hospice care. At the same time, there were urban- rural differences in the demand for elderly care services, with suburban elderly having a higher demand for care services than those living in urban areas (P < 0.05). The elderly’s demand for care services was mainly related to age, place of residence, and gender in the causative factors, mode of residence and physical condition among able factors, and mode of care services and care needs among need factors (P < 0.05). Conclusion: The demand for elderly care services was differentiated by factors including place of residence, age, and gender. It is crucial to accurately match the demand for elderly care services, innovate the mode of elderly care services, and improve the service quality to improve the elderly health service system.

Research on Adaptability Analysis of Environmental Space Demand and Design Optimization of Daycare Centers: Taking Chongqing’s Community F as an Example

Currently,there is a lack of research on the detailed environmental spatial design of community daycare centers at the micro level.This study focuses on Community F in Chongqing,using the elderly’s“willingness to demand”as a central aspect.It examines indoor and outdoor environmental space needs at a micro level,considering both functional requirements and spiritual needs based on existing research.The analysis incorporates three adaptive elements:current construction,surrounding environment,and operational management.It explores the feasibility of restructuring spatial layouts,utilizing local resources,and integrating Bayu cultural characteristics.Finally,through design optimization practices,the study proposes three strategies for aging optimization:functional integration and interaction,user-friendly facilities,and emotional connections to place.

Study on the Alignment Between Talent Training Directions and Employment Market Demands in the Landscape Architecture Industry

Currently,talent training in Chinese universities for landscape architecture is mainly divided into three directions:“landscape planning and design,”“landscape construction management,”and“landscape plant planting and maintenance.”However,with the background of the slowing urbanization process and the widespread demand for composite talents in society,it remains to be verified whether the traditional three major talent training directions in landscape architecture align with the job demands in the current construction market.Based on a survey and analysis of over 300 industry practitioners,this study found a clear trend of merging the three major employment directions into“landscape design and construction”and“landscape plant planting and maintenance.”This presents new requirements and directions for the skill training of landscape architecture majors in universities and provides insights into the alignment between talent training and employment demands in other industries.

Investigation on Tourists' Satisfaction Degree in Xionger Mountain of Shandong Province

Through the field investigation in Xionger Mountain,it was found that the scenic area is rich in tourism resources.However,the development of tourism is lagging behind.By the method of random sampling,a survey for visitors was conducted.A total of 100 questionnaires were issued,100 of which were valid.With the help of TSI evaluating model,tourists' satisfaction degree was calculated accurately.The results showed that ratio of tourism performance to price in Xionger Mountain wasn't high,of which tourists generally expressed dissatisfaction;that the overall environment was quite good,of which tourists showed higher satisfaction degree;that some tourists' expectations to this scenic area were not high;that revisit willing was comparatively high;that there was a certain gap compared with other scenic spot.Tourists' satisfaction degree on Xionger Mountain is 55.89% through calculating TSI index.Finally,aiming at the existent problems,some countermeasures for improving the tourists' satisfaction degree on Xionger Mountain were put forward from the aspects of tour value,environmental perception,marketing philosophy and modes.