A NovelMethod for Determining Tourism Carrying Capacity in a Decision-Making Context Using q−Rung Orthopair Fuzzy Hypersoft Environment

Tourism is a popular activity that allows individuals to escape their daily routines and explore new destinations for various reasons,including leisure,pleasure,or business.A recent study has proposed a unique mathematical concept called a q−Rung orthopair fuzzy hypersoft set(q−ROFHS)to enhance the formal representation of human thought processes and evaluate tourism carrying capacity.This approach can capture the imprecision and ambiguity often present in human perception.With the advanced mathematical tools in this field,the study has also incorporated the Einstein aggregation operator and score function into the q−ROFHS values to supportmultiattribute decision-making algorithms.By implementing this technique,effective plans can be developed for social and economic development while avoiding detrimental effects such as overcrowding or environmental damage caused by tourism.A case study of selected tourism carrying capacity will demonstrate the proposed methodology.

Decision-Making and Management of Self-Care in Persons with Traumatic Spinal Cord Injuries: A Preliminary Study

Patients and physicians understand the importance of self-care following spinal cord injury (SCI), yet many individuals with SCI do not adhere to recommended self-care activities despite logistical supports. Neurobehavioral determinants of SCI self-care behavior, such as impulsivity, are not widely studied, yet understanding them could inform efforts to improve SCI self-care. We explored associations between impulsivity and self-care in an observational study of 35 US adults age 18 - 50 who had traumatic SCI with paraplegia at least six months before assessment. The primary outcome measure was self-reported self-care. In LASSO regression models that included all neurobehavioral measures and demographics as predictors of self-care, dispositional measures of greater impulsivity (negative urgency, lack of premeditation, lack of perseverance), and reduced mindfulness were associated with reduced self-care. Outcome (magnitude) sensitivity, a latent decision-making parameter derived from computationally modeling successive choices in a gambling task, was also associated with self-care behavior. These results are preliminary;more research is needed to demonstrate the utility of these findings in clinical settings. Information about associations between impulsivity and poor self-care in people with SCI could guide the development of interventions to improve SCI self-care and help patients with elevated risks related to self-care and secondary health conditions.

Behavioral Decision-Making of Key Stakeholders in Public-Private Partnerships:A Hybrid Method and Benefit Distribution Study

Public-private partnerships(PPPs)have been used by governments around the world to procure and construct infrastructural amenities.It relies on private sector expertise and funding to achieve this lofty objective.However,given the uncertainties of project management,transparency,accountability,and expropriation,this phenomenon has gained tremendous attention in recent years due to the important role it plays in curbing infrastructural deficits globally.Interestingly,the reasonable benefit distribution scheme in a PPP project is related to the behavior decisionmaking of the government and social capital,aswell as the performance of the project.In this paper,the government and social capital which are the key stakeholders of PPP projects were selected as the research objects.Based on the fuzzy expected value model and game theory,a hybrid method was adopted in this research taking into account the different risk preferences of both public entities and private parties under the fuzzy demand environment.To alleviate the problem of insufficient utilization of social capital in a PPP project,this paper seeks to grasp the relationship that exists between the benefit distribution of stakeholders,their behavioral decision-making,and project performance,given that they impact the performance of both public entities and private parties,as well as assist in maximizing the overall utility of the project.Furthermore,four game models were constructed in this study,while the expected value and opportunity-constrained programming model for optimal decision-making were derived using alternate perspectives of both centralized decision-making and decentralized decision-making.Afterward,the optimal behavioral decision-making of public entities and private parties in four scenarios was discussed and thereafter compared,which led to an ensuing discussion on the benefit distribution system under centralized decision-making.Lastly,based on an example case,the influence of different confidence levels,price,and fuzzy uncertainties of PPP projects on the equilibrium strategy results of both parties were discussed,giving credence to the effectiveness of the hybrid method.The results indicate that adjusting different confidence levels yields different equilibriumpoints,and therefore signposts that social capital has a fair perception of opportunities,as well as identifies reciprocal preferences.Nevertheless,we find that an increase in the cost coefficient of the government and social capital does not inhibit the effort of both parties.Our results also indicate that a reasonable benefit distribution of PPP projects can assist them in realizing optimum Pareto improvements over time.The results provide us with very useful strategies and recommendations to improve the overall performance of PPP projects in China.

Human-Like Decision-Making of Autonomous Vehicles in Dynamic Traffic Scenarios

With the maturation of autonomous driving technology, the use of autonomous vehicles in a socially acceptable manner has become a growing demand of the public. Human-like autonomous driving is expected due to the impact of the differences between autonomous vehicles and human drivers on safety.Although human-like decision-making has become a research hotspot, a unified theory has not yet been formed, and there are significant differences in the implementation and performance of existing methods. This paper provides a comprehensive overview of human-like decision-making for autonomous vehicles. The following issues are discussed: 1) The intelligence level of most autonomous driving decision-making algorithms;2) The driving datasets and simulation platforms for testing and verifying human-like decision-making;3) The evaluation metrics of human-likeness;personalized driving;the application of decisionmaking in real traffic scenarios;and 4) The potential research direction of human-like driving. These research results are significant for creating interpretable human-like driving models and applying them in dynamic traffic scenarios. In the future, the combination of intuitive logical reasoning and hierarchical structure will be an important topic for further research. It is expected to meet the needs of human-like driving.

On the role of impulsivity and decision-making in suicidal behavior

Suicide risk constitutes a complex set of interacting demographic, clinical, psychobiological and environmental variables. Impulsivity is a long-known risk factor for suicide attempts. However, research based on clearer conceptual refinement in this area is imperative. One emerging field of study is that of decision-making. Impulsivity involves a failure of higher-order control, including decision-making. Using standardized operational definitions that take into consideration relevant aspects of impulsivity, including state- and trait-components and a deeper understanding of the process of decision-making in the suicidal mind, we may come a step closer to understanding suicidality and winning the fight in this scourge of human suffering.

Modeling and TOPSIS-GRA Algorithm for Autonomous Driving Decision-Making Under 5G-V2X Infrastructure

This paper is to explore the problems of intelligent connected vehicles(ICVs)autonomous driving decision-making under a 5G-V2X structured road environment.Through literature review and interviews with autonomous driving practitioners,this paper firstly puts forward a logical framework for designing a cerebrum-like autonomous driving system.Secondly,situated on this framework,it builds a hierarchical finite state machine(HFSM)model as well as a TOPSIS-GRA algorithm for making ICV autonomous driving decisions by employing a data fusion approach between the entropy weight method(EWM)and analytic hierarchy process method(AHP)and by employing a model fusion approach between the technique for order preference by similarity to an ideal solution(TOPSIS)and grey relational analysis(GRA).The HFSM model is composed of two layers:the global FSM model and the local FSM model.The decision of the former acts as partial input information of the latter and the result of the latter is sent forward to the local pathplanning module,meanwhile pulsating feedback to the former as real-time refresh data.To identify different traffic scenarios in a cerebrum-like way,the global FSM model is designed as 7 driving behavior states and 17 driving characteristic events,and the local FSM model is designed as 16 states and 8 characteristic events.In respect to designing a cerebrum-like algorithm for state transition,this paper firstly fuses AHP weight and EWM weight at their output layer to generate a synthetic weight coefficient for each characteristic event;then,it further fuses TOPSIS method and GRA method at the model building layer to obtain the implementable order of state transition.To verify the feasibility,reliability,and safety of theHFSMmodel aswell as its TOPSISGRA state transition algorithm,this paper elaborates on a series of simulative experiments conducted on the PreScan8.50 platform.The results display that the accuracy of obstacle detection gets 98%,lane line prediction is beyond 70 m,the speed of collision avoidance is higher than 45 km/h,the distance of collision avoidance is less than 5 m,path planning time for obstacle avoidance is averagely less than 50 ms,and brake deceleration is controlled under 6 m/s2.These technical indexes support that the driving states set and characteristic events set for the HFSM model as well as its TOPSIS-GRA algorithm may bring about cerebrum-like decision-making effectiveness for ICV autonomous driving under 5G-V2X intelligent road infrastructure.

Summarizing vehicle driving decision-making methods on vulnerable road user collision avoidance

With the development of intelligent vehicles and autonomous driving technology,the safety of vulnerable road user(VRU)in traffic has been more guaranteed,and many research achievements have been made in the key area of collision avoidance decision-making methods.In this paper,the knowledge mapping method is used to mine the available literature in depth,and it is found that the research focus has shifted from the traditional accident cause analysis to emerging deep learning and virtual reality technology.This paper summarizes research on the three core dimensions of environmental perception,behavior cognition and collision avoidance decision-making in intelligent vehicle systems.In terms of perception,accurate identification of pedestrians and cyclists in complex environments is a major demand for VRU perception;in terms of behavior cognition,the coupling of VRU intention identification and motion trajectory prediction and other multiple factors needs further research;in terms of decision-making,the intention identification and trajectory prediction of collision objects are not included in the risk assessment model,and there is a lack of exploration specifically for cyclists'collision risk.On this basis,this paper provides guidance for the improvement of traffic safety of contemporary VRU under the conditions of intelligent and connected transportation.

Analysis of Influencing Factors Tourists1 Purchase Decision-making Behavior in Kunming

Based on the theory of consumer behavior,this paper analyzes the current situation of tourism shopping market in Kunming,and analyzes the decision-making behavior of tourists shopping in Kunming with the questionnaire survey,and clarifies the influencing factors of the decision-making behavior of visitors to Kunming.In the future,the influencing factors of Kunming tourists'shopping decision-making behavior are combined with the current situation of Kunming's tourism shopping market.The problems of cheating-induced shopping,the high price of shopping products,the low level of tourism shopping experience and the imperfect after-sales service are analyzed.Finally,the corresponding countermeasures and suggestions are proposed from four aspects:rectifying the tourism shopping market,establishing a sound price supervision mechanism,strengthening the tourism shopping experience,and improving after-sales service.

Unlocking the Network Traffic Password of the Sudden Popularity of Oriental Selection:Consumer Behavior Decision-Making Mechanism Based on Mental Accounting Theory

This paper explores the decision-making mechanism of the consuming behavior hidden behind the sudden popularity of the Oriental Selection Company in terms of the mental accounting theory.Firstly,according to the“Non-alternative”characteristics of mental accounting,this paper expounds how the strategy of the bilingual live-streaming of Oriental Selection promoters stimulates consumers’desire to buy the advertised products and services whilst using the utility theory of mental accounting to analyze how Oriental Selection promoters improve consumers’acquisition utility and total utility.Secondly,we sum up the successful experiences of Oriental Selection:The live-streaming industry should apply the theory of mental accounting in effectively overcoming the shortcomings of the live-streamed marketing by stimulating consumers’desire and influencing their decision-making behavior through the streaming of content that triggers them to make purchases.This is achievable by abandoning the traditional ways of loudly urging consumers to buy goods.Finally,this paper puts forward some suggestions on how to use the mental accounting theory in promoting sustainable consumption and points out the prospects for Oriental Selection.

COLLISION AVOIDANCE DECISION-MAKING MODEL OF MULTI-AGENTS IN VIRTUAL DRIVING ENVIRONMENT WITH ANALYTIC HIERARCHY PROCESS

Collision avoidance decision-making models of multiple agents in virtual driving environment are studied. Based on the behavioral characteristics and hierarchical structure of the collision avoidance decision-making in real life driving, delphi approach and mathematical statistics method are introduced to construct pair-wise comparison judgment matrix of collision avoidance decision choices to each collision situation. Analytic hierarchy process （AHP） is adopted to establish the agents＇ collision avoidance decision-making model. To simulate drivers＇ characteristics, driver factors are added to categorize driving modes into impatient mode, normal mode, and the cautious mode. The results show that this model can simulate human＇s thinking process, and the agents in the virtual environment can deal with collision situations and make decisions to avoid collisions without intervention. The model can also reflect diversity and uncertainly of real life driving behaviors, and solves the multi-objective, multi-choice ranking priority problem in multi-vehicle collision scenarios. This collision avoidance model of multi-agents model is feasible and effective, and can provide richer and closer-to-life virtual scene for driving simulator, reflecting real-life traffic environment more truly, this model can also promote the practicality of driving simulator.

Neural mechanism of proposer's decision-making in the ultimatum and dictator games

Previous studies have demonstrated that reactions to unfair offers in the ultimatum game are correlated with negative emotion. However, little is known about the difference in neural activity between a proposer＇s decision-making in the ultimatum game compared with the dictator game. The present functional magnetic resonance imaging study revealed that proposing fair offers in the dictator game elicited greater activation in the right supramarginal gyrus, right medial frontal gyrus and left anterior cingulate cortex compared with proposing fair offers in the ultimatum game in 23 Chinese undergraduate and graduate students from Beijing Normal University in China. However, greater activation was found in the right superior temporal gyrus and left cingulate gyrus for the reverse contrast. ＂The results indicate that proposing fair offers in the dictator game is more strongly associated with cognitive control and conflicting information processing compared with proposing fair offers in the ultimatum game.

Analysis on Behavior Characteristics of Tourists under Perspective of Sustainable Development of Tourism Destinations: A Case Study of Mugecuo Scenic Area in Kangding City of Sichuan Province

Tourists are the subject of tourism activity,and it is conducive to promoting sustainable development of tourism destination by studying their behavior characteristics and tourism perception.Mugecuo Scenic Area in Kangding City,Ganzi Tibetan Autonomous Prefecture,Sichuan Province is taken as research case,and visitors and managers in the scenic area are surveyed by using semi-structured interview method.Based on survey data,the research aims to put forward corresponding policy suggestions for sustainable development of Mugecuo Scenic Area by deeply analyzing tourists’ access to information of scenic area,tourists’ travel purpose,tourists’ satisfaction with services of scenic area and willingness to revisit.

Strengthening Mechanisms to Promote Tourists' Environmental Responsible Behaviors in the Context of All-for-One Tourism

The overall promotion of all-for-one tourism requires tourists' civilized behaviors. This paper focused on tourists' environmental responsible behaviors in the context of all-for-one tourism. On the basis of clarifying the connotation, dimension and driving factors of tourists' environmental responsible behaviors, this paper firstly analyzed the relationship between all-for-one tourism and tourists' environmental responsible behaviors, and proposed that the development of all-for-one tourism was an important path to optimize and upgrade China's tourism industry and a new concept of sustainable development of tourism industry. The emergence of all-for-one tourism has formed a new tourism trend, which will drive tourists to behave more civilly. Tourists' environmental responsible behaviors are a "subject and share" concept, and from tourists' point of view, all-for-one tourism development is the most basic requirement. Secondly, based on the theory of "value-belief-norm", this paper focused on the strengthening mechanism of "interaction effect" between all-for-one tourism and tourists' environmental responsible behaviors, and put forward the idea of "double internalization strengthening" to guide tourists' environmental responsible behaviors from being passive to active, from individuals to groups. Finally, this paper discussed the promotion of environmental responsible behaviors of tourist's specific strategies from two aspects, "external drive" and "internal drive" to enhance the level of all-for-one tourism construction and strengthen the environment responsibility of tourists. "External drives" were as follows:(1) to make a scientific development plan to implement the "host and guest sharing" mechanism;(2) to optimize the landscape, the environment, services, enhance the local attachment of visitors;(3) to improve the infrastructure system, pay attention to the details of visitors' experience;(4) to strengthen environment education and publicity, deepening the quality of tourists' civilization construction, and strengthen the environmental responsible behaviors of tourists. "Internal drives" were as follows:(1) to strengthen the sense of environmental responsibility of tourists;(2) to establish a model of environmental responsible behaviors;(3) to strengthen the supervision of environmental responsible behaviors.

A Theoretical Approach to the Effective Decision-Making Process

This research develops and elaborates studies done for a contribution to the 2019 PIC International Conference 2019 in Malta, about the decision-making process. Decision-making is the act of choosing between two or more courses of action. In the wider process of problem-solving, decision-making involves choosing between possible solutions to a problem, and these decisions can be made through either an intuitive or reasoned process, or a combination of the two. The study of decision-making processes, to be understood as the role of human factors, becomes particularly interesting in complex organizations. This research aims to analyze how an effective team, within organizations, can develop a more correct and effective decision-making, in order to get an optimal solution, overcoming the typical uncertainty. The paper describes the point of departure of decision in complex, time-pressured, uncertain, ambiguous and changing environments. The use of a leading case (the Tenerife air accident, 1977), will lead us to the desired results, i.e. to demonstrate how an effective decisional process, including team dynamics, can be useful to reduce the risk, present in all decisions, and reduce errors. The case of Tenerife air disaster, confirm our research. In that case, in fact, the group dynamics prove not to have worked. Thus, we can state that if a team approach had been followed instead of a more individual one, the results would probably have been different. The central belief of the research, is that classic decision theory could benefit from a team approach, which reduces the risk that a decision may lead to undesirable consequences. As demonstrated with the case study, within organizations, the decision-making is not a solitary action. Decisions, in fact, are made within a team and in order to be able to function effectively in a group, and manage group situations, there are essential skills. The team can then become a resource for the decisional process and problem solving, but it is necessary to understand the dynamics.

A Study on the Impacting Path Mechanism of User Behavior Habits for Tourism Social Website

Along with the development of socialized media and self-help tourism,tourism industry has been going into tourism social times.Based on technology acceptance model,use and gratifications approach,and weighted and calculated needs theory,this study explored the impact of perceived popularity,perceived characteristics,and perceived need on the use of tourism social network site and being a member of it.This study also discussed the interaction of perceived popularity,perceived characteristics,and perceived need.The findings of this paper could be used to help the management operator pay attention to strengthen the function of tourism social network site in order to provide better information for users and satisfied the needs of users.

Extension of Goal-Directed Behavior Model for Post-Pandemic Korean Travel Intentions to Alternative Local Destinations: Perceived Risk and Knowledge

Since the outbreak of COVID-19,tourists have been increasingly concerned over various risks of international travel,while knowledge of the pandemic appears to vary significantly.In addition,as travel restrictions continue to impact adversely on international tourism,tourism efforts should be placed more on the domestic markets.Via structural equation modeling,this study unearthed different risk factors impacting Korean travelers’choices of alternative local destinations in the post-pandemic era.In addition,this study extended the goal-directed behavior framework with the acquisition of perceived risk and knowledge of COVID-19,which was proven to hold a sig-nificantly superior explanatory power of tourists’decisions of local alternatives over foreign countries during the COVID-19 pandemic.Furthermore,desire was found to play an imminent mediating role in the conceptual mod-el,maximizing the impact of perceived risk on travel intentions.Henceforth,this research offers meaningful the-oretical implication as thefirst empirical study to deepen the goal-directed behaviour framework with perceived risk and knowledge in the context of post-COVID-19 era.It also serves as insightful knowledge for Korean tour-ism authorities and practitioners to understand local tourists’decision-making processes and tailor effective recovery strategy for domestic tourism.

Influence mechanism of tourists' environmentally responsible behavior in ethnic villages

With the economic development and multicultural exchange of ethnic villages,more and more ethnic villages have embarked on the road of tourism to become rich,but also brought the problem of ecological pollution.Few existing literatures discuss how to alleviate the ecological pollution in ethnic villages from the perspective of tourists’environmentally responsible behavior.In the context of ethnic villages,from the perspective of integration and the attitude-context-behavior theory,this paper constructs an EV-ABC-TERB model with four variables,namely environmental attitude,local atmosphere,emotional experience and tourists’environmentally responsible behavior,to explore the characteristics,influencing factors and influencing mechanism of tourists’environmental responsibility behavior in ethnic villages.Taking Xijiang Hmong Village as the research case,questionnaire survey method and structural equation model method were used.The results show that environmental attitude positively affects emotional experience and tourists’environmentally responsible behavior.Local atmosphere positively influences tourists’environmentally responsible behavior.Emotional experience negatively affects tourists’environmentally responsible behavior and plays an intermediary role in the way that environmental attitudes affect tourists’environmentally responsible behavior.The influence of environmental attitude on emotional experience is negatively regulated by local atmosphere.Finally,based on the analysis conclusion,it provides new ideas and inspiration for the sustainable development of the ethnic village tourism.

元宇宙视域下数字文旅用户参与行为的影响因素

元宇宙为数字文旅提供了全新的表现形式,探究元宇宙视域下数字文旅用户的参与行为有助于元宇宙技术方和数字文旅内容生产方明确如何激励用户参与,改善交互方式使用户获得更好的互动体验。文章选取相关研究对象进行访谈,应用扎根理论,结合SOR理论和MOA框架构建元宇宙视域下数字文旅用户参与行为的影响因素模型。研究发现:感知因素直接影响元宇宙视域下数字文旅用户的参与行为,内部动机和外部反馈两个维度通过感知因素的中介作用间接影响元宇宙视域下数字文旅用户的参与行为,机会条件和能力限制会调节感知因素对参与行为的影响。

民族村寨旅游者表演行为的生成机制研究——以德夯苗寨为例

在旅游研究的“表演转向”思潮下,客观审视民族村寨旅游者表演行为的生成逻辑,可为深化表演性理论和优化民族村寨旅游管理提供参考依据。文章从表演性理论视角切入,以湘西德夯苗寨为考察样本,采用扎根理论研究方法划分受访者文本内容,探析民族村寨旅游者表演行为特征的生成机制。结果显示:(1)舞台设置、角色互动、独自表演和感知距离4项主范畴,共同组成了民族村寨旅游者表演行为生成的核心要素,文章据此构建了旅游者表演行为特征分析框架。(2)旅游者是具有能动性的表演者,其表演行为既包含角色协商和运作一致的角色互动特征,也包括反叛与服从的独自表演特征。(3)感知距离分为心理距离、认知距离,以及个体远离与超越,三者揭示出旅游者表演行为特征生成的深层次因素,影响着旅游者在民族村寨剧场舞台的具身性和认同感建构。最后,文章从增强旅游者游憩体验、加快非遗活化实践、优化民族村寨开发管理等方面提出建议启示。