tourism management
Ghazaleh Soltani; ameneh khadivar; neda paravian
Abstract
With the expansion of the internet and the emergence of social media, airlines are increasingly using these platforms to engage with customers. Twitter, as one of the most popular microblogging platforms, plays a key role in communication between airlines and passengers. This study aims to analyze sentiments ...
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With the expansion of the internet and the emergence of social media, airlines are increasingly using these platforms to engage with customers. Twitter, as one of the most popular microblogging platforms, plays a key role in communication between airlines and passengers. This study aims to analyze sentiments and topics related to Iranian airlines on Twitter, based on 2,876 English tweets collected between April 2008 and March 2024 using Playwright. After preprocessing and interpreting 230 emojis with artificial intelligence, sentiment labeling was performed using both lexicon-based and machine learning approaches (RoBERTa model). Among the five evaluated algorithms, logistic regression with the lexicon-based method achieved the best performance, with an F-score of 0/81. Incorporating emoji information significantly improved model accuracy. Topic modeling with LDA revealed that “safety” was the primary concern of users. These findings can contribute to optimizing the communication and service strategies of Iranian airlines.
Sociology of tourism
Ameneh Khadivar; Zeinab Hashemi baghi
Abstract
This research is a part of qualitative and quantitative research in terms of practical purpose and terms of method. The analyses of the bibliometric section are related to the qualitative section and the neural network analyses are related to the quantitative section. The method of systematic bibliometric ...
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This research is a part of qualitative and quantitative research in terms of practical purpose and terms of method. The analyses of the bibliometric section are related to the qualitative section and the neural network analyses are related to the quantitative section. The method of systematic bibliometric review was carried out with VOSviewer software and R programming language. Three main clusters were identified in the vocabulary co-occurrence analysis section, which include: (1) innovation in event tourism attractions (2) mental engagement towards event tourism destination attachment (3) event tourism experiences in social media. In the quantitative section, following the results of the TCM-ADO framework, neural network analyses were performed on the clusters to predict event tourism revisit intention. The results indicate that the variables of social media, experience, and tourist attractions, satisfaction, loyalty, attitudes, mental involvement and dependence on the place effect revisiting.
Marketing economics
Ameneh Khadivar; Maryam Golestani; Fahimeh Golshani
Abstract
The main goal of the current research is to predict the ethical purchase intention of sustainable products in the circular business model through the behavior of customers/tourists using artificial neural network (ANN). The statistical population of the present study are customers/tourists who have used ...
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The main goal of the current research is to predict the ethical purchase intention of sustainable products in the circular business model through the behavior of customers/tourists using artificial neural network (ANN). The statistical population of the present study are customers/tourists who have used the products/services of Gargop restaurant. Sampling was done based on Morgan's table and 384 people were examined through a questionnaire. The results indicate that as much as the input variables include attitude (willingness to pay more money, attitude towards circular business models), perceived value (social value, functional value and value) and awareness (awareness of ethical product/service and brand awareness) have a higher value; it is expected that the ethical purchase intention will be stronger. The present study by examining the behavioral factors of customers to the collection of literature related to circular business models and also sustainable development helps.IntroductionTourism has many positive and negative economic, social, cultural, and environmental effects. These dimensions have always been and will be discussed in most sources as essential areas of destination sustainability in sustainable development issues. In the world, the tourism industry is known as a smoke-free industry. According to those mentioned above, the expectation from this industry without smoke is that all these active businesses will operate in line with sustainable development goals. On the other hand, the rapid growth of the world's population and urbanization increases consumption significantly, while natural resources are limited and scarce (De Angelis, 2018). The world's population is estimated to reach about nine billion people by 2050, and it consumes resources more than three times the current rate (Planning, 2015). The current linear economy, characterized by "take-produce-do things in order," accelerates the depletion of resources and energy (Boken et al., 2017).The concept of circular or circular economy, inspired by nature in the late 1970s, means that nothing is wasted and all outputs are inputs to other processes (Ellen McArthur, 2018). The circular economy is a strategy to oppose the traditional market system, aiming to deal with the challenge of lack of resources and waste disposal in a win-win approach with an economic and value perspective (Homrich et al., 2018). The ethical purchase intention of customers/tourists is essential for the successful implementation of circular business models and sustainable development. However, few researchers have focused on the role of customers/tourists in activating circular business models and sustainable development.The current research fills this gap by identifying the essential factors that affect the ethical purchase intention of customers/tourists for circular business models and sustainable products/services in the tourism industry in restaurants and catering centers. According to the research of researchers of this article, no research has been done on the mentioned subject in this way in Iran, so the value and innovation of the present research are also evident. Therefore, the main problem of the current research is that only some customers or tourists may buy and use sustainable products/services; for example, tourists interested in using luxury restaurants may need to be more attractive to them. In this regard, the main goal of the current research is to identify the behavioral factors that determine customers'/tourists' intention to purchase sustainable products in circular business models ethically.For this purpose, artificial neural network (ANN) has been used as a prediction method, and Python software has been used for analysis. The network's output in this research is ethical purchase intention, and its inputs are the behavioral factors of customers/tourists. The statistical population of this research is the customers/tourists who use the products/services of Gargop restaurant, the first wooden recycled restaurant in Iran, which has all its facilities, products, and services in line with sustainable development near Khorkhoran International Wetland in the coastal city of Bandar Khmeir, Hormozgan province. Sampling was done based on the table of Morgan and Krejcie, and 384 people were examined through a questionnaire. Materials and MethodsThe present research is quantitative; firstly, primary information was collected using a questionnaire, then analyzed using an artificial neural network (ANN) prediction method and Python software. The output of the network in this research is ethical purchase intention. Its inputs are the behavioral factors of customers/tourists, including attitude (willingness to pay more money - attitude towards circular business models), perceived value (social value - functional value - cognitive value) is awareness (biological awareness - environmental awareness - awareness of ethical product/service - brand awareness).The statistical population of this research is the customers/tourists who use the products/services of Gargop restaurant, the first wooden recycled restaurant in Iran, which has all its facilities, products, and services in line with sustainable development near Khorkhoran International Wetland in the coastal city of Bandar Khmeir, Hormozgan province. Sampling was done based on the table of Morgan and Krejcie, and 384 people were examined through a questionnaire.Discussion and ResultsThe specifications of the model are as follows:Due to the lack of balance of the data classes, that were 339 in category one (ethical purchase intention) and only 45 in category zero (no ethical purchase intention) the SMOTE algorithm (Chawla et al., 2002) have used to solve this problem and the increase of the data of the lower class (not intending to buy ethically). Therefore, the neural network was built with an equal number of 339 in class one (ethical purchase intention) and 339 in class zero (no ethical purchase intention). The data were divided into three categories: 70% training, 20% testing, and 10% validation. ConclusionsAccording to the research results, when x variables include attitude (willingness to pay more money (x1), attitude towards circular business models (x2)) - perceived value (social value (x3), functional value (x4) and cognitive value (x5)) and awareness (awareness of ethical product/service (x6) and brand awareness (x7)) get a higher value, variable y means ethical purchase intention also increases, gives that, of course, this relationship is not linear and is formed in the form of a network, and the hidden layer is also essential. By examining the issue from the customers' point of view, the present research contributes to the collection of literature related to ethical purchase intention and circular business models, and consequently to sustainable development, especially in the restaurant and tourism industry, and it provides valuable guidelines for businesses to be more successful in the current market. Considering that businesses have shifted from a linear economy to a circular economy, the vital role of customers/tourists should not be ignored.Therefore, understanding the essential behavioral factors of customers can pave this path, and by predicting their ethical purchase intention through these important behavioral factors, it is possible to predict their behavior and influence their behavior change because the behavior is not formed by itself and is the result of the customer's intention to buy ethically. The current research expands the role of customers and explains how different factors can collectively affect customers' acceptance and purchase intention of the circular business model. Business managers can apply the circular business model in their business and adjust the type of their offers according to the customers they want to target. The present research results help them better understand the behavior of customers who pay more attention to sustainable development goals and are concerned in some way.The intention (intention) and customers' buying behavior are essential to implement the circular business model successfully. Customers' different personal characteristics and changes over time make it difficult for businesses to fully understand their expectations and behavior. This is even more important given the drastic changes from linear to circular economies. Therefore, businesses should do deep market research about their target customers in different time frames and consider many characteristics in a categorized manner. Finally, to successfully brand and protect the brand, as a business that operates with sustainability goals, it should take special measures and stabilize this brand in customers' minds in the long term.
