Fr. Thomas Zain, Vicar General of the Antiochian Archdiocese, tells us about a US tour of the Choir of St. Romanos the Melodist from Beirut. More information can be found at the web site of the Antiochian Archdiocese.

Walking into an Orthodox Church can be pretty overwhelming. Join Steve as he offers a quick tour of what you'll typically see, and what that can teach us about our path to salvation.

England's Liz Young wins the Women's Indian Open by one shot to claim her second Ladies European Tour title.

Marco Penge needing a birdie on the 18th hole to keep alive hopes of retaining his DP World Tour card is what makes the sport worth watching, writes Iain Carter

Former Crucible champion Shaun Murphy says any player who joins a potential breakaway tour should not be allowed to play in snooker's biggest events.

Shabnam Younus-Jewell talks to Hungary's first professional snooker player.

Highland Council has proposed setting a 5% rate for its visitor levy.

The comic's hearse will travel through Edinburgh and on to Glasgow before her funeral on 30 November.

Dozens of new tourist businesses are opening in the South of Scotland as visitors escape to the great outdoors.

A Guernsey hotel manager says introducing a GST would mean higher prices for customers.

Figures show 137,691 fewer people visited the island in the summer compared to 2019.

More than 30 public toilets in Ceredigion could close to cut costs.

A review of the front page stories from the daily and weekly newspapers in Wales.

Jake Doyle is touring Northants rugby clubs to raise money

Jake Doyle is playing for a different rugby club every weekend to raise money for a support group.

The increased volume of accessible internet data creates an opportunity for researchers and practitioners to improve time series forecasting for many indicators. In our study, we assess the value of web traffic data in forecasting the number of short-term visitors travelling to Australia. We propose a feature-based model selection framework which combines random forest with feature ranking process to select the best performing model using limited and informative number of features extracted from web traffic data. The data was obtained for several tourist attraction and tourism information websites that could be visited by potential tourists to find out more about their destinations. The results of random forest models were evaluated over 3- and 12-month forecasting horizon. Features from web traffic data appears in the final model for short term forecasting. Further, the model with additional data performs better on unseen data post the COVID19 pandemic. Our study shows that web traffic data adds value to tourism forecasting and can assist tourist destination site managers and decision makers in forming timely decisions to prepare for changes in tourism demand.

1. La PS5 Slim avec lecteur de disque est de retour à prix réduit avec ce code promo spécial Black Friday  Frandroid
2. Les scalpers surestiment l’engouement pour la PS5 Pro et se retrouvent avec une console invendable  jeuxvideo.com
3. Test de la PS5 Pro : la nouvelle console de Sony est-elle faite pour vous ?  Frandroid
4. Test PS5 Pro : un tournant pour les consoles de jeu  Canard PC
5. La meilleure offre pour acheter la PS5 Pro dès son lancement !  Midi Libre

1. Aide à l'Ukraine : Antony Blinken met la pression sur les Européens avant le retour de Donald Trump  FRANCE 24
2. Les craintes des dirigeants ukrainiens face aux futures nominations annoncées par Donald Trump  Le Monde
3. «La confrontation entre Trump et Poutine est inévitable, mais que va-t-elle coûter à l’Ukraine et à l’Europe ?»  Libération
4. 24H Pujadas du mardi 12 novembre 2024 - 24 h Pujadas, l'info en questions | LCI  TF1+
5. Guerre en Ukraine : "Donald Trump souhaite parvenir à la paix le plus rapidement possible", en acceptant de céder à Poutine les territoires conquis par son armée  L'Indépendant

1. Your ultimate guide to Taylor Swift's The Eras Tour stops in Toronto  CP24
2. A Taylor Swift glossary to keep up with the Eras Tour fever gripping Canada this week  The Globe and Mail
3. IN PHOTOS | See Swiftmania sweep Toronto  CBC.ca
4. Is Taylor Swift the key to solving traffic in Toronto?  Canada NewsWire

 

Le 20 avril 2018, un appel au boycott a été lancé sur les réseaux sociaux marocains contre trois entreprises leaders dans leurs secteurs d’activités. L’eau minérale de Sidi Ali, le lait de Centrale Danone et les stations de services Afriquia (pétrole) ont été victimes d’une guerre d’information, justifiée selon les internautes par des prix de vente élevés. Les appels au boycott ont été relayés par les internautes Marocains via des groupes et des pages ...

Une gigantesque panne d'électricité a affecté lundi une large partie du Pakistan, dont ses plus grandes villes Lahore et Karachi, avant que les autorités n'annoncent en soirée le retour progressif du courant.

Les coupures d'électricité sont fréquentes au Pakistan, englué depuis des années dans de graves problèmes budgétaires et énergétiques, et dont le système de distribution est complexe et vétuste.

La panne a été causée par un dysfonctionnement survenu à 07H30 locales (02H30 GMT) à la suite de mesures d'économies prises sur le réseau.

"Nous espérons que le courant sera rétabli partout dans le pays d'ici ce (lundi) soir", a déclaré dans un communiqué vidéo le ministre de l'Energie, Khurram Dastagir Khan.

La nuit avançant, il a assuré sur Twitter que l'électricité commençait à être rétablie progressivement.

Le ministère a tweeté que le courant était revenu dans le centre d'Islamabad et à Gujranwala, à quelque 200 km au sud-est de la capitale.

M. Khan a également retweeté le message d'un usager qui se félicitait qu'il y ait à nouveau "de la lumière à Lahore", la deuxième ville la plus peuplée du pays, avec plus de 10 millions d'habitants.

La panne a été causée par une variation de la fréquence électrique sur le réseau national, au redémarrage des unités de production électrique lundi matin.

Ces unités sont temporairement éteintes la nuit en hiver pour économiser du carburant, a expliqué M. Khan à la presse.

La plupart des hôpitaux, industries et institutions gouvernementales sont équipées de générateurs. Mais les ménages et petits commerces n'ont souvent pas les moyens de s'offrir un tel équipement.

Dans le nord du Pakistan, les températures devaient tomber lundi soir en dessous de 0°. Le chauffage au gaz est le plus répandu, mais n'est pas non plus toujours très fiable, les délestages étant fréquents en raison d'une pénurie de gaz.

Les réseaux de téléphonie mobile ont été également perturbés par la panne, selon un tweet du régulateur pakistanais des télécoms.

L'économie pakistanaise est déjà chancelante avec une inflation galopante, une devise nationale - la roupie - en chute libre et des réserves de change au plus bas. Une telle coupure d'électricité ne fait qu'accroître la pression sur les petits commerces.

A Rawalpindi, ville voisine de la capitale, Muhammad Iftikhar Sheikh, 71 ans, un vendeur d'électroménager, a déploré ne pas pouvoir tester ses appareils devant les clients.

"Les clients n'achètent jamais sans essayer d'abord", pestait-il. Du coup, "on est tous assis là, à ne rien faire".

Dans les écoles, les cours ont souvent eu lieu dans la pénombre, pour celles ne disposant pas d'éclairage sur batterie.

A Karachi (sud), où les températures étaient plus élevées, un commerçant a indiqué à l'AFP craindre que son stock entier de produits laitiers ne soit perdu, sans réfrigération.

Et Khurrum Khan, un imprimeur de 39 ans, voyait les commandes s'empiler, sans pouvoir y répondre. Les problèmes d'électricité sont "une malédiction permanente dont nos gouvernements n'ont pas réussi à se débarrasser", regrettait-il.

Une panne similaire en janvier 2021 avait plongé l'essentiel de ce pays de 220 millions d'habitants dans le noir pendant plusieurs heures, après qu'un dysfonctionnement technique dans le sud eut déclenché une réaction en chaîne dans plusieurs centrales électriques.

Les coupures d'électricité sont un problème récurrent au Pakistan. Mais la situation s'est encore détériorée ces derniers mois, la situation financière dramatique du pays aggravant un peu plus ses difficultés d'approvisionnement énergétique.

Les ménages ont été touchés, mais l'industrie également, notamment le textile, qui représente environ 60% des exportations pakistanaises.

Word of mouth (WOM) and electronic word of mouth (eWOM) are very effective and important communication tools to persuade consumers for purchasing the products/services. These become more significant with products that are difficult to assess before consumption, e.g., hospitality. The tourism industry is reviving, and the consumer is conscious when booking a particular destination. Thus, it is important to understand how WOM and eWOM are impacting the various factors in distinct ways while choosing the tourist destination. The seven factors identified, for the present study, are channel engagement, expertise, homophily, resource helpfulness, source credibility, tie-strength, and trustworthiness. The PLS-SEM was used to test the theoretical model of this study. The study shows that both WOM and eWOM impact an individual in different ways. The expertise of the reviewer is the most important factor in the case of WOM and channel engagement is the most significant factor for eWOM. Resource helpfulness is common for both WOM and eWOM.

This study inquires about the COVID-19-generated momentum and how it resulted in transformative opportunities for the hard-hit tourism industry in Hawai'i. It also investigates the type of sustainability-based management strategies that were favoured by actors from the industry to help navigate uncertain times and capture transformative opportunities. Findings indicate that actors from the tourism industry in Hawai'i perceived the COVID-19 pandemic as a huliau, or a point of transformation, to reflect and re-evaluate the tourism industry's responsibility and shift toward a recovery focused on sustainability. This research confirms that the pandemic-driven momentum accelerated opportunities for changing and transforming traditional business models and indicators of progress within the tourism industry in Hawai'i. Further research may explore additional Pacific Island countries to gain a deeper understanding of the problem within the region's context.

Aim/Purpose: The main goal of this systematic literature review was to look for studies that provide information relevant to business intelligence’s (BI) framework development and implementation in the tourism sector. This paper tries to classify the tourism sectors where BI is implemented, group various BI functionalities, and identify common problems encountered by previous research. Background: There has been an increased need for BI implementation to support decision-making in the tourism sector. Tourism stakeholders such as management of destination, accommodation, transportation, and public administration need a guideline to understand functional requirements before implementation. This paper addresses the problem by comprehensively reviewing the functionalities and issues that need to be considered based on previous business intelligence framework development and implementation in tourism sectors. Methodology: We have conducted a systematic literature review using the Preferred Reporting Items for Systematic Reviews and Guidelines for Meta-Analysis (PRISMA) method. The search is conducted using online academic database platforms, resulting in 543 initial articles published from 2002 to 2022. Contribution: The paper could be of interest to relevant stakeholders in the tourism industry because it provides an overview of the capabilities and limitations of business intelligence for tourism. To our knowledge, this is the first study to identify and classify the BI functionalities needed for tourism sectors and implementation issues related to organizations, people, and technologies that need to be considered. Findings: BI functionalities identified in this study include basic functions such as data analysis, reports, dashboards, data visualization, performance metrics, and key performance indicator, and advanced functions such as predictive analytics, trend indicators, strategic planning tools, profitability analysis, benchmarking, budgeting, and forecasting. When implementing BI, the issues that need to be considered include organizational, people and process, and technological issues. Recommendations for Practitioners: As data is a major issue in BI implementation, tourism stakeholders, especially in developing countries, may need to build a tourism data center or centralized coordination regulated by the government. They can implement basic functions first before implementing more advanced features later. Recommendation for Researchers: We recommend further studying the BI implementation barriers by employing a perspective of an adoption framework such as the technology, organization, and environment (TOE) framework. Impact on Society: This research has a potential impact on improving the tourism industry’s performance by providing insight to stakeholders about what is needed to help them make more accurate decisions using business intelligence. Future Research: Future research may involve collaboration between practitioners and academics in developing various BI architectures specific to each tourism industry, such as destination management, hospitality, or transportation.

Aim/Purpose: In this study, the research proposes and experiments with a new model of collecting, storing, and analyzing big data on customer feedback in the tourism industry. The research focused on the Vietnam market. Background: Big Data describes large databases that have been “silently” built by businesses, which include product information, customer information, customer feedback, etc. This information is valuable, and the volume increases rapidly over time, but businesses often pay little attention or store it discretely, not centrally, thereby wasting an extremely large resource and partly causing limitations for business analysis as well as data. Methodology: The study conducted an experiment by collecting customer feedback data in the field of tourism, especially tourism in Vietnam, from 2007 to 2022. After that, the research proceeded to store and mine latent topics based on the data collected using the Topic Model. The study applied cloud computing technology to build a collection and storage model to solve difficulties, including scalability, system stability, and system cost optimization, as well as ease of access to technology. Contribution: The research has four main contributions: (1) Building a model for Big Data collection, storage, and analysis; (2) Experimenting with the solution by collecting customer feedback data from huge platforms such as Booking.com, Agoda.com, and Phuot.vn based on cloud computing, focusing mainly on tourism Vietnam; (3) A Data Lake that stores customer feedback and discussion in the field of tourism was built, supporting researchers in the field of natural language processing; (4) Experimental research on the latent topic mining model from the collected Big Data based on the topic model. Findings: Experimental results show that the Data Lake has helped users easily extract information, thereby supporting administrators in making quick and timely decisions. Next, PySpark big data processing technology and cloud computing help speed up processing, save costs, and make model building easier when moving to SaaS. Finally, the topic model helps identify customer discussion trends and identify latent topics that customers are interested in so business owners have a better picture of their potential customers and business. Recommendations for Practitioners: Empirical results show that facilities are the factor that customers in the Vietnamese market complain about the most in the tourism/hospitality sector. This information also recommends that practitioners reduce their expectations about facilities because the overall level of physical facilities in the Vietnamese market is still weak and cannot be compared with other countries in the world. However, this is also information to support administrators in planning to upgrade facilities in the long term. Recommendation for Researchers: The value of Data Lake has been proven by research. The study also formed a model for big data collection, storage, and analysis. Researchers can use the same model for other fields or use the model and algorithm proposed by this study to collect and store big data in other platforms and areas. Impact on Society: Collecting, storing, and analyzing big data in the tourism sector helps government strategists to identify tourism trends and communication crises. Based on that information, government managers will be able to make decisions and strategies to develop regional tourism, propose price levels, and support innovative programs. That is the great social value that this research brings. Future Research: With each different platform or website, the study had to build a query scenario and choose a different technology approach, which limits the ability of the solution’s scalability to multiple platforms. Research will continue to build and standardize query scenarios and processing technologies to make scalability to other platforms easier.

Aim/Purpose: This study investigated factors influencing the intention to engage in green innovation among small and medium enterprises (SMEs) in the tourism sector, using an integrated approach from the pro-environmental planned behavior (PEPB) and technology organization environment (TOE) models. Background: Green innovation is a long-term strategy aimed at addressing environmental challenges in the Indonesian tourism sector, especially those related to SMEs in culinary, accommodation, transportation, and creative industries. While prior research primarily focused on innovation characteristics and various behavioral intentions towards new technologies, this study pioneered an approach to understanding green innovation practices among SMEs by examining behavioral intention and the influence of internal organizational and external environmental factors. This was achieved through the PEPB model, which extends the theory of planned behavior (TPB) by incorporating perceived authority support and perceived environmental concern and integrating it with the TOE model. This comprehensive approach was crucial for understanding SME motivations, needs, and challenges in adopting green innovation, thereby supporting environmental sustainability. Methodology: Data were collected through offline and online questionnaires and interviews with 405 SMEs that had implemented green innovation as respondents. The theoretical model was tested using partial least squares structural equation modeling (PLS-SEM) with top-level constructs. Contribution: This research contributed to the development and validation of an integrated model for green innovation in SMEs, offering insights and recommendations for all stakeholders in the tourism sector to formulate effective green innovation strategies. Findings: This research revealed that the integrated model of pro-environmental planned behavior and technology organization environment successfully explained 71% of the factors influencing the intention to engage in green innovation for SMEs in the tourism sector. Perceived authority support emerged as the strongest factor, while perceived behavioral control was identified as a weaker factor. Recommendations for Practitioners: The research findings recommended that SMEs in the tourism sector focus on customer satisfaction and operational efficiency and optimize the recruitment and training processes of resources to maximize success in adopting environmentally friendly innovations. Meanwhile, for the government, providing support, incentives, and stringent environmental regulations could encourage sustainable business practices. Recommendation for Researchers: The research findings recommended that SMEs in the tourism sector focus on customer satisfaction and operational efficiency and optimize the recruitment and training processes of resources to maximize success in adopting environmentally friendly innovations. Meanwhile, for the government, providing support, incentives, and stringent environmental regulations could encourage sustainable business practices. Impact on Society: Examining the factors influencing the intention to engage in green innovation among SMEs in the tourism sector carried significant social implications. The findings contributed to recommending strategies for businesses and stakeholders such as the government, investors, and tourists to collectively strive to minimize environmental damage in tourist areas through the implementation of green innovation. Future Research: There are several promising avenues to explore to enhance future research. Expanding the scope to include diverse regions and industries and using additional approaches, such as leadership theory and management commitment theories, can increase the R-squared value. Additionally, broadening the profile of interviewees to obtain a more comprehensive understanding of the intention to engage in green innovation should be considered.

Aim/Purpose: This study aims to develop a solution for personalized tourism recommendations that addresses information overload, data sparsity, and the cold-start problem. It focuses on enabling tourists to choose the most suitable tourism-related facilities, such as restaurants and hotels, that match their individual needs and preferences. Background: The tourism industry is experiencing a significant shift towards digitalization due to the increasing use of online platforms and the abundance of user data. Travelers now heavily rely on online resources to explore destinations and associated options like hotels, restaurants, attractions, transportation, and events. In this dynamic landscape, personalized recommendation systems play a crucial role in enhancing user experience and ensuring customer satisfaction. However, existing recommendation systems encounter major challenges in precisely understanding the complexities of user preferences within the tourism domain. Traditional approaches often rely solely on user ratings, neglecting the complex nature of travel choices. Data sparsity further complicates the issue, as users might have limited interactions with the system or incomplete preference profiles. This sparsity can hinder the effectiveness of these systems, leading to inaccurate or irrelevant recommendations. The cold-start problem presents another challenge, particularly with new users who lack a substantial interaction history within the system, thereby complicating the task of recommending relevant options. These limitations can greatly hinder the performance of recommendation systems and ultimately reduce user satisfaction with the overall experience. Methodology: The proposed User-based Multi-Criteria Trust-aware Collaborative Filtering (UMCTCF) approach exploits two key aspects to enhance both the accuracy and coverage of recommendations within tourism recommender systems: multi-criteria user preferences and implicit trust networks. Multi-criteria ratings capture the various factors that influence user preferences for specific tourism items, such as restaurants or hotels. These factors surpass a simple one-star rating and take into account the complex nature of travel choices. Implicit trust relationships refer to connections between users that are established through shared interests and past interactions without the need for explicit trust declarations. By integrating these elements, UMCTCF aims to provide more accurate and reliable recommendations, especially when data sparsity limits the ability to accurately predict user preferences, particularly for new users. Furthermore, the approach employs a switch hybridization scheme, which combines predictions from different components within UMCTCF. This scheme leads to a more robust recommendation strategy by leveraging diverse sources of information. Extensive experiments were conducted using real-world tourism datasets encompassing restaurants and hotels to evaluate the effectiveness of UMCTCF. The performance of UMCTCF was then compared against baseline methods to assess its prediction accuracy and coverage. Contribution: This study introduces a novel and effective recommendation approach, UMCTCF, which addresses the limitations of existing methods in personalized tourism recommendations by offering several key contributions. First, it transcends simple item preferences by incorporating multi-criteria user preferences. This allows UMCTCF to consider the various factors that users prioritize when making tourism decisions, leading to a more comprehensive understanding of user choices and, ultimately, more accurate recommendations. Second, UMCTCF leverages the collective wisdom of users by incorporating an implicit trust network into the recommendation process. By incorporating these trust relationships into the recommendation process, UMCTCF enhances its effectiveness, particularly in scenarios with data sparsity or new users with limited interaction history. Finally, UMCTCF demonstrates robustness towards data sparsity and the cold-start problem. This resilience in situations with limited data or incomplete user profiles makes UMCTCF particularly suitable for real-world applications in the tourism domain. Findings: The results consistently demonstrated UMCTCF’s superiority in key metrics, effectively addressing the challenges of data sparsity and new users while enhancing both prediction accuracy and coverage. In terms of prediction accuracy, UMCTCF yielded significantly more accurate predictions of user preferences for tourism items compared to baseline methods. Furthermore, UMCTCF achieved superior coverage compared to baseline methods, signifying its ability to recommend a wider range of tourism items, particularly for new users who might have limited interaction history within the system. This increased coverage has the potential to enhance user satisfaction by offering a more diverse and enriching set of recommendations. These findings collectively highlight the effectiveness of UMCTCF in addressing the challenges of personalized tourism recommendations, paving the way for improved user satisfaction and decision-making within the tourism domain. Recommendations for Practitioners: The proposed UMCTCF approach offers a potential opportunity for tourism recommendation systems, enabling practitioners to create solutions that prioritize the needs and preferences of users. By incorporating UMCTCF into online tourism platforms, tourists can utilize its capabilities to make well-informed decisions when selecting tourism-related facilities. Furthermore, UMCTCF’s robust design allows it to function effectively even in scenarios with data sparsity or new users with limited interaction history. This characteristic makes UMCTCF particularly valuable for real-world applications, especially in scenarios where these limitations are common obstacles. Recommendation for Researchers: The success of UMCTCF can open up new avenues in personalized recommendation research. One promising direction lies in exploring the integration of additional contextual information, such as temporal (time-based) or location-based information. By incorporating these elements, the model could be further improved, allowing for even more personalized recommendations. Furthermore, exploring the potential of UMCTCF in domains other than tourism has considerable significance. By exploring its effectiveness in other e-commerce domains, researchers can broaden the impact of UMCTCF and contribute to the advancement of personalized recommendation systems across various industries. Impact on Society: UMCTCF has the potential to make a positive impact on society in various ways. By delivering accurate and diverse recommendations that are tailored to individual user preferences, UMCTCF fosters a more positive and rewarding user experience with tourism recommendation systems. This can lead to increased user engagement with tourism platforms, ultimately enhancing overall satisfaction with travel planning. Furthermore, UMCTCF enables users to make more informed decisions through broader and more accurate recommendations, potentially reducing planning stress and leading to more fulfilling travel experiences. Future Research: Expanding upon the success of UMCTCF, future research activities can explore several promising paths. Enriching UMCTCF with various contextual data, such as spatial or location-based data, to enhance recommendation accuracy and relevance. Leveraging user-generated content, like reviews and social media posts, could provide deeper insights into user preferences and sentiments, improving personalization. Additionally, applying UMCTCF in various e-commerce domains beyond tourism, such as online shopping, entertainment, and healthcare, could yield valuable insights and enhance recommendation systems. Finally, exploring the integration of optimization algorithms could improve both recommendation accuracy and efficiency.

Aim/Purpose: This article takes ‘tourism decision-making behavior’ as an entry point, and deeply analyzes the factors influencing the travel decision-making of Chinese ‘American Travel’ tourists and their degree of influence, so as to provide a reference for the development of Chinese outbound tourism. Background: With the development of China’s economy and the improvement in people’s level, the outbound tourism market of Chinese residents has developed rapidly. The United States has become an important tourism destination country for Chinese residents’ outbound tourism, and China has also become one of the important tourist source countries of American tourism. However, the rapid development of ‘American tourism’ has also caused competition problems in China’s tourism industry. For example, prices and tourism products have become a means of competition among tourism enterprises. As the main body of consumption, tourists’ decision-making behavior will be affected by various factors. Methodology: Drawing lessons from previous scholars’ research results on tourism decision-making behavior, the influencing factors of tourism decision-making behavior are summarized. A theoretical model and index system of factors influencing tourism decision-making behavior of Chinese residents ‘Travel in the United States’ are established, research hypotheses are put forward, questionnaire data are collected, and SPSS and Amos are used to analyze and verify the theoretical model. Contribution: This research expands the literature on topics related to tourism decision-making in research and practice. It establishes a theoretical model and index system for the factors that influence the decision-making behavior of Chinese residents’ ‘American Travel’ tourism. In addition, we propose countermeasures for tourism products, enterprises, and the government. Findings: Prior knowledge and external information have a positive influence on tourism perception and value perception, and a negative influence on risk perception. Risk perception value perception has a positive and negative influence on tourism decision-making and tourism motivation, respectively. Tourism motivation has a positive influence on tourism decision-making and has a positive impact. Recommendation for Researchers: According to the research conclusions of this article, the following counter-measures and suggestions are put forward from three aspects of tourism: products, enterprises, and governments. On the basis of existing tourism products, relevant operating companies should pay more attention to the upgrading and transformation of tourism, leisure and entertainment products in scenic spots to increase the willingness of tourists to travel. When considering corporate marketing and promotion plans, tourism companies operating related businesses should increase the weight of their marketing budgets in online marketing, increase investment in online marketing, and develop mobile applications that meet the preferences of Chinese residents in the United States. Do a good job in the timely publication of safety reminders and local information. Safety is an important foundation for tourism development and the core concern of many tourists. Future Research: Due to the important research on the impact of tourism activities, the influencing factors are many and complex, and the psychological process of tourism decision-making is carried out directly. There are still unconsidered factors that need to be studied in depth. In the future, it is possible to compare multiple resource-featured themes, and increase the characteristics of potential tourists, and the factors affecting the selection behavior of regional cultural tourists, and so forth, in order to make the research more applicable and practical instructive significance.

Singer takes you on a three-and-a-half hour journey spanning over 18 years of music

CM Mahmood Khan orders early opening of provincial tourism authority

WETHEPEOPLE X kunstform BMX Shop - Get in the Van Tour 2015

The WETHEPEOPLE crew which consisted of Ed Zunda, Dillon Llody, Pete Sawyer, Moritz Nussbaumer and Dima Pyrkhodko did a huge roadtrip trough Germany and visited every day a BMX Shop. At 9th of July the team stopped at kunstform BMX Shop in Stuttgart. First we did a little session in our warehouse. After that we all went to BOOST Skatehalle and spend some great ridin till deep in the night! It was a very awesome time to hang up with Pros of WETHEPEOPLE and we're very happy about that good session. Our friend Sebi Nitsche did a little videoclip just to share some impression. Thanks for WETHEPEOPLE, SPORT IMPORT to make this stop in our BMX Shop possibil and of course a very special thanks to all local riders and customers!

Cheers Daniel !!

In Hard am Bodensee, almost directly on the German-Austrian border, one of the largest and best bowls of Europe is located. This is the location of the Ride Further Tour 2017 from the 2nd - 3rd September with a big stint in the fifth round.

From England have already announced Kriss Kyle, Bas Keep, Matt Priest, Chaz Mailey and Lima Eltham, but that's not all. A total of 16 international pros will go to Hard in the start and then there would be the winners of the four wildcards. Chris Halbritter and Mätti Hilber have already qualified at the BMX Männle Turnier in Tuttlingen, two other wildcards can be won on the 2nd September at the Pre-Quali directly on site. But be careful: the number of participants is limited, so register quickly (register@wayfurther.com)

For more information on the Ride Further Tour 2017 in Hard, visit Facebook.

The Vans BMX Pro Cup Series, the world’s leading platform for elite BMX park terrain competition, announces the official 2018 World Tour dates and locations for the upcoming season. The celebrated BMX competition series will take place in Australia, California, Mexico and Spain, welcoming a top-ranking competitive field of invited pro BMX riders and Wildcards for their chance to compete on the world stage for a piece of the grand $155,000USD prize.



The Vans BMX Pro Cup Series is also proud to expand the 2018 World Tour with the addition of two new Regional Qualifier events in the United States and Chile, encouraging more talented BMX riders from around the world to earn their way to the Vans BMX Pro Cup World Championships. The five confirmed Regional Qualifier events are open to registration by all professional men and women BMX riders beginning in Santiago, Chile on March 23. The top three podium winners from each Regional Qualifier will advance to the Vans BMX Pro Cup Pro Tour, and secure their invite to the Vans BMX Pro Cup World Championships.



2018 VANS BMX PRO CUP SERIES WORLD TOUR ZEITPLAN



Regional Qualifiers

Santiago, Chile
March 23 & 25

Sydney, Australia
April 27

Woodward East, Pennsylvania
June 28

Guadalajara, Mexico
August 24

Málaga, Spain
September 21



*registration information is available on vansbmxprocup.com



Pro Tour

Sydney, Australia
April 29

Huntington Beach, CA
August 3 & 5

Guadalajara, Mexico
August 25 - 26



World Championship

Málaga, Spain
September 22 - 23



@vansbmxprocup on Instagram
#vansbmxprocup



All the best

Your kunstform BMX Shop Team

The first stop of the Ride Hard Session Tour 2018 will taking place at the 5th of May, at the Trendsport hall in Basel. For the first stop they will host a chilled BMX jam with vouchers and goodies for tricks. If the weather will be nice, you can ride the Half-pipe, flatrails and curbs outside. Sounds good right?

All the best, your kunstform BMX Shop Team!

What:
Ride Hard Session Tour #1 Basel

When:
05 May 2018

Where:
Trendsport Basel
Uferstrasse 80
4057 Basel


More infos on Facebook.

On the 25.07.2018, the Kink Bikes Pro Team will visit our Shop in Stuttgart, Germany. Come over and hang up with the Kink pros, like Nathan Williams, Travis Hughes, Dan Coller and more. Supported by Kink Bikes and Traffic Distribution.

All the best, your kunstform BMX Shop Team!

What:
Kink New Wave Germany Tour 2018

When:
25th July

Where:
kunstform BMX Shop
Rothebühlstr.63
70178 Stuttgart


More infos on Facebook.

On the 25.07.2018, the Kink Bikes Pro Team visited our Shop in Stuttgart, Germany. Travis Hughes, Dan Coller and Ben Basford killed it at our stockroom and on the streets of Stuttgart! Check out the whole video now!

Enjoy the video, your kunstform BMX Shop Team!



Video: Robin Kachfi



Subscribe our youtube channel: https://www.youtube.com/kunstformbmxshop

Yeah, we can't wait for it: After 3 years, it is happening again on September 12th, 2019! As part of the Shadow/Subrosa World Tour 2019, the Shadow/Subrosa team will visit us again in our shop in Stuttgart on the way to #bmxstreetstation 2019 in Lyon. We are sooooo looking forward to it, because the first visit in 2016 was also the trigger for various projects, which we did together with The Shadow Conspiracy. Get ready, as this time the following riders will be present: Mo Nussbaumer (GER), Miguel Smajli (GER), Matt Ray (USA), Jabe Jones (USA), Jiri Blabol (CZE) and Bjarki Hardarson (ISL). You can check what went down in 2016 right here:



There will be a Meet-and-Greet at our shop in Stuttgart at 3pm. After that, we'll all go and ride street with the crew. At the end of the evening, a jam will take place in the Stuttpark Hall in Bad Cannstatt.

We look forward to seeing you, your kunstform BMX Shop Team!

Related links:

• all products of The Shadow Conspiracy
• all products of Subrosa

It was a pleasure having the Shadow / Subrosa team in our Shop in Stuttgart! The visit in 2019 is now history and for those who could not be there: no worries, the video is here! Mo Nussbaumer (GER), Miguel Smajli (GER), Matt Ray (USA), Jabe Jones (USA), Jiri Blabol (CZE) and Bjarki Hardarson (ISL) and guests (known from radio and television ;-)) were ready to give it all!

After sessioning our stock to warm up, the crew takes over the streets of Stuttgart. Unfortunately, the security density this time was quite high, which is why it goes on quite quickly. On the way to Bad Cannstatt, the homies visit Stuttgart's longest (grindable) rail, before all the pros, locals and homies meet up in the Stuttpark for the final jam of the night.

Have fun with the video, your kunstform BMX Shop Team!

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• all products of The Shadow Conspiracy
• all products of Subrosa

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