디지털 기술의 지속적인 발전에 따라 가상 관광과 디지털 문화유산 탐방은 실제 관광을 보완하는 중요한 수단으로 자리 잡고 있다. 본 연구는 기술수용모델(Technol ogy Acceptance Model, TAM)을 적용하여 인지된 용이성, 인지된 유용성, 외부 변 수 측면에서 가상 관광 체험의 성과를 살펴보고, 이러한 요인들이 사회와 온라인 환 경에서의 커뮤니케이션 효과에 어떠한 영향을 미치는지 살펴보고자 한다. 이에 본 연구는 관련 대상자와의 심층 인터뷰를 실시한 연구 결과를 보면 인지된 용이성과 인지된 유용성이 이용자의 가상 관광 체험 수용과 홍보에 영향을 미치는 주요 요인 으로 밝혀졌다. 그리고 대영박물관, 바티칸 박물관, 스미소니언 자연사 박물관, 운강석굴 등 다양한 가상 관광 플랫폼의 사례도 분석하였다. 본 연구는 가상 관광 연구 에 대해 새로운 관점을 제시하고 가상 관광을 효과적으로 설계하는 방법에 대해 의 견을 제안하였다. 또한, 문화유산 가상 관광의 전파 및 홍보를 위한 이론적인 지침과 실제적인 조언을 제시하였다.

Social media have emerged as one of the most important tools for firms to engage customers (e.g., Chandrasekaran et al., 2022; Cheng & Edwards, 2015; Lee et al., 2018; Wedel & Kannan, 2016). Within the tourism industry, scholars have investigated the role of social media communication in various contexts, such as online travel information search (Xiang & Gretzel, 2010), sharing travel experiences (So et al., 2018; Wang et al., 2022) and establishing positive customer relationships (Jamshidi et al., 2021). Insights into which social media content makes for generating positive engagement are, however, still largely based on marketers’ intuitions or focusing on message factors of social media posts such as message appeals (e.g., Wang & Lehto, 2020). It also often neglects the importance of the visual component of social media posts, and only a few research have investigated the effects of the image in social media on the travel industry (e.g., Fusté-Forné, 2022). The objective of this research is, therefore, to understand how textual features and image features generate user engagement in social media utilizing cutting-edge transfer learning techniques and to propose how these features should be customized to maximize user engagement for online travel shopping companies. We collect and analyze more than 10,000 Instagram posts from three online travel shopping companies, including Expedia, Priceline, and Kayak. The results from transfer learning algorithms utilizing 24 features, such as the number of people in the image, emotions expressed in the people in the image, hue, and RGB value, successfully predict the level of engagement measured by the number of likes and comments.

Following the military advance of Russian forces into Ukraine in February 2022, Russia became the most sanctioned country in the world (Shapiro, 2022) as global leaders attempted to condemn the act and impose several sanctions on the Russian Federation including the ban of Russian oil and gas imports, the closure of airspace to Russian airplanes and the removal of Russian banks from the Swift international payment network (BBC, 2022). Among the noticeable effects of the Russia-Ukraine conflict is the animosity expressed against Russians. In a marketing context, animosity has been studied mostly from the perspective of consumers and is conceptualized as the “anger related to previous or ongoing military, economic or diplomatic events” (Klein et al., 1998:90) which impacts purchasing behaviour. Given that animosity has been found to have enduring effects, it is worth examining the anti-Russian sentiments currently manifesting as these may have impacts in terms of tourism management and marketing.

This study investigates how travellers adopt information from travel review websites, i.e., Tripadvisor and how online travel reviews influence their intention to visit a tourist attraction. Based on the Information Adoption Model (IAM), a conceptual model was developed and tested using the data obtained from 227 valid respondents.

The challenge of adjusting to new travel trends has led to a quest to find ways to motivate people to travel again and to make the industry more resilient long term. The implementation of phygital marketing as an information source seems promising. This is the first study considering phygital marketing initiatives as an approach to trigger people’s travel intentions. An online questionnaire incorporating a scenario-based 2x2 factorial designed experiment with a longitudinal prospective (2 waves) explored the impact of a technology-based peer-to-peer versus human-machine interaction phygital marketing initiatives as an innovative approach to trigger travel intentions for long-distance and short distance destinations. Study 1 (n=330) shows that the experience of using phygital initiatives not only builds trust but also encourages people to visit destinations, leading to a dynamic experience. Study 2 is currently in the field which means after all most of the pandemic related restrictions have been removed to compare to Study 1’s results. Alongside theoretical contributions, this study presents practical implications on how destinations could implement phygital marketing initiatives.

Fear of missing out (FOMO) refers to the customer's perception of being anxious for not engaging in an experience. FOMO is an anxiety feeling positively associated with social media usage that one cannot catch up on something important in life. Fear of missing out (FOMO) marketing appeals initiated from social media usage were found to significantly affect consumer purchase decisions including choice of destination. Consumers usually browse social media and social networking sites such as forums and reviews in online tourism agents (OTAs) when they make travel decisions. Although FOMO is expected to affect tourists' perception and urgency in making a tourism decision, the use of FOMO-laden message to promote travel destination through different types of influencers has not yet been widely studied. This study fills this research gap by examining the effect of using FOMO laden content to promote travel destination through different types of influencers. An online experiment was conducted with four experimental conditions in which different influencers share about a destination using the same FOMO-laden message: (1) travel KOL, (2) tourists who post user-generated-content (UGC), (3) personal friends, and (4) a control condition with the absence of influencer and FOMO message. The 984 respondents were randomly assigned into one of the four experimental conditions. Data collected was analysed using PLS-SEM and PLS-MGA. Results indicated that anticipated elation, anticipated envy, and social influence predicted 30.2% variance of FOMO and FOMO explained 31.6% of variance of intention to visit the destination promoted. Multi-group analysis (PLS-MGA) found that exposure to message shared by travel KOL and personal friends significantly strengthen the FOMO feeling of participants resulting in strong intention to visit the destination promoted. UGC posted by tourists showed similar effect as the non-FOMO laden control group and are less significant in driving the FOMO feeling that leads to visit intention. Findings of this study provide insights into how effectiveness of destination promotion can be enhanced by using FOMO-laden message on social media through influential influencers.

A GoldSim Total System Performance Assessment has been developed and utilized for assessment of the various conceptual HLW repositories for spent nuclear fuels during last a few decades. Even though, almost all required parameter values associated with the repository system are frequently assumed or sometimes overestimated, they are still far from being highly reliable. Uncertainties nested in nuclide transport modeling around the repository are mainly dominated by these parametric uncertainties aside from intrinsic model uncertainty. Reliable estimate of the parameter values commonly expressed as probability density functions (PDFs) always require a large amount of measured data. Such input distributions are used as input to the probabilistic assessment program through Monte Carlo simulation to quantitatively provide possible uncertainty of the results. However, in most cases, especially in the safety assessment of the repository which is typically related with both long-time span and wide modeling domain, inefficient observed data from the field measurements are common, making conventional probabilistic calculations rather even uncertain. Since Bayesian approach is known to be especially powerful and efficient in the case of lacking of available data measured, such short data could be compensated by coupling with a priori belief, reducing uncertainty. By allowing the a priori knowledge for incorporating insufficient observed data, which include expert’ elicitation, their beliefs and judgment regarding the parameters as well as recent site-specific measurements, based on the Bayes’ theorem, the older parameter distributions, “prior” distribution can be updated to a rather newer and reliable “posterior” distribution. Newer distributions are not necessarily expressed as PDFs for probabilistic calculation. These updates could be done even iteratively as many times as data values are sequentially available, which calls sequential Bayesian updating, making belief of posterior distributions become much higher by reducing parametric uncertainty. To show a possible way to enhance the belief as well as to reduce the uncertainty involved in parameter for the Bayesian scheme, nuclide travel length in the far-field area of a hypothetical deep borehole spent fuel Repository was investigated. The algorithm and module that have been developed and implemented in GSTSPA through current study was shown to work well for all assumed prior, three sequential posterior distributions and likelihoods.

PURPOSES : The purpose of this study is to review a method to estimate the average travel speed of the Bus Rapid Transit(BRT) section using the bus departure and arrival time data collected using the Korean bus information system (BIS). METHODS : To determine an average travel speed estimation model suitable for the BRT system in Korea, the speed estimated using the speed estimation model of TCQSM, which is used in the U.S., and that using the proposed speed estimation model that used the bus departure and arrival time data were compared with the actual travel speed using a t-test. RESULTS : The average travel speed estimated using the proposed method was more suitable for the actual average travel speed than that estimated using the TCQSM model. CONCLUSIONS : As a result of estimating the average travel speed, if the length of the link is 900 m, SBRT can be constructed on the existing road, but at least 1,200 m must be ensured to build SBRT in the new city. The proposed bus average travel speed estimation model can be used to review the BRT operational efficiency considering the speed limit, traffic signal, and dwelling time at bus stops in the planning and operation stages of the BRT.

현재까지 송대의 기행문에 대한 연구는 남송 시기 가장 많은 작품을 남긴 周必大 가 아닌 陸遊와 范成大의 작품에 주로 편중되어 있다. 따라서 본 논문은 한국에서 연구되어진 바 없는 주필대의 기행문 중 『歸廬陵日記』, 『泛舟遊山錄』, 『奏事錄』, 『南歸錄』을 중심으로 주필대 기행문의 특징이 무엇인지 소개하는 동시에 그것이 송대 기행문의 형성과 발전에 있어서 어떠한 역할을 했는지 함께 고찰해 나아가려 한다.

PURPOSES : There are generally various driving behaviors in toll collection areas, including lane changing, merging and diverging, and other behaviors. Because of these behaviors, accident risk and traffic congestion may occur. To mitigate these problems, multi-lane electronic toll collection systems have been developed with a high-speed limit of 80 km/h. This study was conducted to investigate travel speed changes and effects through multi-lane electronic toll collection systems with a high-speed limit. METHODS : Traffic simulations were conducted using VISSIM. Before conducting simulations, driving behavior around the toll collection areas was observed, and field data were collected based on drones for peak and non-peak hours. In addition, safety effect evaluations were conducted based on conflict analyses using the SSAM software. RESULTS : Through multi-lane electronic toll collection systems with a high-speed limit, the travel speed on the toll collection area was increased, and traffic operational efficiencies were identified. However, different speed variations were produced as observation locations in toll collection areas. Speed variations were mitigated at most locations except the area within the tollbooth because of the high speed limit for multi-lane electronic tollbooth. CONCLUSIONS : It was important to manage lane-changing activities, and this may influence traffic operational effects. Safety effects were also identified through conflict analyses.

PURPOSES : This study defines travel time reliability as a concept that explains the change in travel time that passengers can hardly predict and calculates the value of travel time reliability based on travel objectives. METHODS : Because the reliability of passage time is difficult to estimate from actual passenger data, standard quantification measures have not been established despite various interests. In this study, the reliability of transit time was defined as the expense that passengers did not recognize in advance, such as an accidental delay caused by unforeseen circumstances. For analysis based on the individual behavior of users, the data were constructed using the optional experiment method (marginal rate of substitution method) of the stated preference survey, which has the advantage of controlling the correlation between attribute variables and maintaining the independence of the data of the study. RESULTS : Consequently, the reliability value of travel time in mandatory-purposed traffic was almost identical to the value of travel time, and the reliability value of travel time in return and shopping/leisure, which is not mandatory during non-business-purpose traffic, is lower than the value of travel time. Comparing and analyzing with existing studies on estimating the reliability value of transit time, both work/ non-work purposes are in line with the overall research results. CONCLUSIONS : Estimating the reliability value of transit time for each purpose of passage was the first attempt, and it is meaningful to suggest a direction for quantifying and applying the reliability value of transit time along with the passage time value of this study.

PURPOSES : The purpose of this study is to build an optimization model using the capacity and initial travel speed of the volume delay functions for network calibration performed in the traffic demand analysis process. METHODS : The optimization model contains an error term between the observed traffic volume and estimated traffic volume, based on the user equilibrium principle, and was constructed as a bi-level model by applying range constraints on capacity and travel time. In addition, we searched the split section to apply the method of adjusting the section instead of adjusting the single link. The optimization model is constructed by applying the warm-start method using the bush of the origin-based model so that parameter adjustment and traffic assignment are repeatedly executed within the model and the convergence of the model configured %RSSE. RESULTS : As a result of analysis using the toy network, the optimization model is that the observed traffic volume is estimated when there are no restrictions and, when the constraint conditions were set, the error with the observed traffic volume and error rate was significantly reduced. As a result of the comparative analysis of the trial-and-error methods, KTDB optimum values, and optimization models in empirical analysis using a large-scale network, the evaluation indexes (e.g., RMSE and %RMSE) were significantly improved by applying the optimization model. CONCLUSIONS : Based on the empirical analysis, the optimization model of this study can be applied to large-scale networks and it is expected that the efficiency and reliability of road network calibration will be improved by repeatedly performing parameter adjustment and traffic assignment within the model.

Memorable documents written in Dongba scripts, such as diaries and travels, record events in chronological order, which strongly reflect the value of Dongba applied documents. At present, few documents of this type can be seen. In January 2005, dongba He Xiudong, who comes from Tacheng Township, Lijiang City, Yunnan Province, accompanied Mr. Li Zaizhong to visit Aming Ling cave, after that He Xiudong wrote a travel note in Dongba scripts, which is a typical record. This article translates and interprets this travel note, and studies the writing phenomenon, phonetic complement, different graphs of the same word, multiple words in one graph, homographs and allographs of this document.