Purpose The purpose of this study is to determine the satisfaction of the guests who stay at hotels offering technology-supported products and services related to the services and products they receive by using the opinion mining technique. Design/methodology/approach In this research, 12,396 customer reviews on booking.com related to ten hotels belonging to a hotel chain using technology-supported products were evaluated with aspect-based sentiment analysis techniques. Findings As a result of this study, it has been determined that using technology in hotel businesses creates a positive impression on customer satisfaction. It has been determined that the enrichment of standard hotel business products such as beds and room lighting with technology, in a way that will not be very costly, affects the guests. In addition, it is interesting that technological features such as robots and room service robots, which are called “High & Technology” in this study, are evaluated by customers in the service process. Practical implications The hotel managements have the opportunity to evaluate the services we offer by analyzing their online comments and to see their own image from the eyes of the guests. Hotel businesses must learn about customer expectations for technologies with high investment costs. This study, which analyzes online customer reviews, enables tourism businesses that offer technology-supported products and services and invest in technology in service delivery, to understand how customers evaluate the service. Originality/value In this study, customer reviews of a hotel group operating in many countries belonging to a hotel group that enriches its standard products with technology and provides service with the concept of a “smart hotel” were examined. This study contributes to the understanding of customers' experience of using technological products in hotel businesses. This study contributes to the literature on customers' satisfaction with technological hotel products and services and the decision of hotels to invest in technology.

In the tourism sector, online tourist reviews analysis is one of the methods to evaluate the products and services offered by businesses and understand the needs of tourists. These reviews take place in social networks and e-commerce sites in parallel with the developments in information and communication technologies. Tourists generate these reviews during or after their use of the products or services. In the literature, these reviews are referred to as UGC (User Generated Content) or eWOM (electronic word-of-mouth). The scientific evaluation of the textual contents in tourist reviews is done by text mining, which is a sub-area of data mining. This chapter discusses the methods and techniques of opinion mining or sentiment analysis. In addition, aspect-based sentiment analysis and techniques to be used in the application are discussed. A case study was carried out using aspect-based sentiment analysis method. In the application “Cappadocia home cooking” restaurant used tourist reviews.

With the revolution of Industry 4.0, the technologies that enter our daily lives are based on smart devices, applications, and platforms with internet connection. A wide range of these technologies collected under one umbrella is known as IoT (internet of things). This chapter evaluates the stages of a touristic travel in smart tourism destinations by considering IoT architecture. The technologies used in these phases and their contributions to the tourism sector and tourists are examined. In the implementation section, an IoT-based information system is proposed for Cappadocia hot air balloon tours. The main purpose of the system is to determine whether the appropriate weather conditions are formed before the hot air balloon flights. The proposed system allows for the automation and evaluation of data already collected using traditional methods. With the implementation of the system; work and time savings can be achieved, and more accurate measurements will make safe flights.

Kapadokya UNESCO dünya miras listesinde yer alan peri bacaları, doğal kayaların oyulmasıyla oluşturulan yerleşim yerleri ve otantik atmosferiyle lüks turizm faaliyetleri için önemli bir destinasyondur. Araştırmada, Kapadokya Bölgesi'nde dünya miras alanları içeresinde yer alan lüks mağara otelleri ziyaret eden yabancı turistlerin oteller hakkındaki algılarının belirlenmesi amaçlanmıştır. Araştırmanın örneklemini, 2021 yılında TripAdvisor sitesi tarafından belirlenen ve Kapadokya'da faaliyet gösteren en iyi 14 lüks mağara otellere ait 3430 adet İngilizce yorum oluşturmaktadır. Araştırma verisi metin madenciliği yöntemlerinden konu çıkarımı tekniği kullanılarak analiz edilmiştir. Araştırma bulgularına göre; turistler, mağara otellerde yaşadıkları eşsiz deneyimlerini tanımlarken fiziksel çevre açısından önem sırasına göre vadiden, sıcak hava balonu seyirlerinden ve peri bacalarından bahsetmişlerdir. Otellerde sunulan ürün hizmetler açısından otellerdeki şömineleri, modern olanakları (banyo, yataklar, kaya odalar), yardımsever personelleri, şarap mahzenleri ve akşam yemeği konularından bahsetmişlerdir. Ayrıca otel deneyimlerini başkalarına tavsiye etme niyetlerini ve otellerde kendilerini evlerinde gibi hissettiklerini belirtmişlerdir.

In the tourism sector, online tourist reviews analysis is one of the methods to evaluate the products and services offered by businesses and understand the needs of tourists. These reviews take place in social networks and e-commerce sites in parallel with the developments in information and communication technologies. Tourists generate these reviews during or after their use of the products or services. In the literature, these reviews are referred to as UGC (User Generated Content) or eWOM (electronic word-of-mouth). The scientific evaluation of the textual contents in tourist reviews is done by text mining, which is a sub-area of data mining. This chapter discusses the methods and techniques of opinion mining or sentiment analysis. In addition, aspect-based sentiment analysis and techniques to be used in the application are discussed. A case study was carried out using aspect-based sentiment analysis method. In the application “Cappadocia home cooking” restaurant used tourist reviews.