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Nation branding efforts are carried out by means of communication. The element, which is the object of communication tools, must have an analogical connection with nation branding. The object of analogy should have attractive features that will strengthen the nation brand. Online tourism content, which has the quality to add value to nation branding, can produce a strong analogy. Online tourism content can easily be internalized in a positive way, as it creates attractive connotations such as memories, entertainment, holidays, etc. in the mind of the audience. In this direction, the research aims to reveal that the online tourism brand is a strategic transmission tool of nation branding.

The research study was carried out with the semiotics method. Content analysis has been made for the videos of GoTürkiye, Turkey's tourism brand, on YouTube.

Research findings show that content covering a large part of Turkey has been created. Messages to be given in the content; it is that Turkey has authentic and attractive elements and hosts international events. The content on GoTürkiye's YouTube has reached a significant number of views.

The research aims to reveal how to build an online nation brand through online tourism brands. In this respect, it is thought that the results can guide the politicians or marketers responsible for nation branding.

The idea of how to build an online nation branding through online tourism brands remains unclear. In this respect, the research demonstrates its original value in proposing a model that will contribute to online nation branding.

Although it is assumed that migration and tourism directly affect each other, neither has received enough attention in the literature. Moreover, the relationship between them remains unclear. The UNWTO interprets said relationship in two ways: tourism-led migration (TLM) and migration-led tourism (MLT). The latter is crucial for the marketing of tourism. This study aims to clarify the migration-tourism relationship in ways the relevant literature has inadequately addressed and to evaluate the significance of MLT for Turkey's tourism marketing.

The study was carried out with a qualitative research design. Document scanning was used to collect data. A time series analysis was performed based on secondary data. Vector autoregressive models (VARs), which test the relationship between two or more variables, were preferred in the analysis selection. The empirical evidence depends on annual data of German tourists visiting Turkey and persons admitted to Germany from 2006 to 2019.

The findings of the study revealed a significant short-term relationship between those immigrating to Germany and tourists visiting Turkey.

The research shows that migration is a factor in the purchasing behavior of touristic products. In this respect, the practical conclusion of the study reveals that it may be beneficial for national tourism marketers in these countries to promote touristic products through citizens who have migrated abroad.

In the relevant literature, the relationship between tourism and migration (RTM) has been limitedly examined from an MLT perspective. In this respect, the subject has not been examined in detail in many respects (distribution by years, various sampling and data collection technique, etc.). The present research helps fill this literature gap by addressing the subject directly.

This study aims to explore a novel framework for housing price bubbles in the Turkish economy during the pandemic. It examines the probability of housing bubble formation relative to the pre-pandemic period and identifies possible determinants of housing bubbles in the Turkish economy.

In this study, a two-stage novel estimation method is applied. In the first stage, bubble periods are identified through the right-tailed supremum augmented Dickey–Fuller test. In the second stage, the determinants of these bubbles are identified, and the housing bubble determinants during the COVID-19 pandemic are compared to the pre-pandemic period.

The findings indicate that there is an asset price bubble in the housing market during the pandemic period. Furthermore, mortgage credit expansion, mortgage credit rates and the depreciation of the Turkish Lira against the USD could increase housing bubble formation. However, housing sector sales to foreign investors do not contribute to housing bubble formation during the pandemic in the Turkish housing market.

To the best of the author’s knowledge, this is the first study to address the relative determinants of housing bubbles in an emerging market context during the pandemic.

In today's globalising conditions, tourism is marketed as a combined product because the demand for tourism increases as the product differs. It is very difficult for tourism destinations, which emerge as a result of the combination of attractiveness, accessibility, tourism businesses, activity and image elements, to survive because tourism destination stakeholders have different goals and objectives. Therefore, there is a need for an effective destination management in which management functions (planning, organising, coordination, commanding (leading) and control) will be employed. Together with the destination management, stakeholders with different goals and objectives are expected to operate in line with a common goal. The clustering of tourism businesses, one of the stakeholders of the tourism destination, plays a very important role in the emergence of destination management. In addition, this situation causes businesses to act not only in line with their own interests but also in the interests of the destination. While avoiding activities that would endanger the existence of the destination with the unions they establish, they cause local administrations and fund managers to act in line with the infrastructure, superstructure and development opportunities needed. In addition to this, while ensuring the use and protection of social capital in that region, it also enables the development of intellectual capital. On the other hand, it causes the opening of new main and auxiliary enterprises and plays an active role in increasing the welfare level of the region. Therefore, clustering is very important in successful destination management.

The study seeks to understand the experiences and perceptions of the university youth regarding the democratic atmosphere of a public university located in Turkey. To this end, the objective of this research is twofold: (1) to investigate university students’ level of civic engagement regarding student activism, exercising rights, and interest in politics; and (2) to explore students’ perception of their university environment regarding the promotion of tolerance, respect for ideas, and participation in decision-making. This study was carried out at a public university located in the middle of Turkey. A mixed-method approach was employed, including both qualitative and quantitative data. A total of 332 undergraduate students participated in the quantitative part while 14 undergraduate students were interviewed in the qualitative part of the study. In quantitative data collection, two self-developed scales were used: Civic Engagement Scale and Perceptions of Democratic University Environment Scale. The results of the data analysis indicated that students’ overall civic engagement level was below the average level. In particular, the level of students’ activism was significantly lower than that of students’ interest in politics and exercising rights, respectively. In addition, the level of students’ interest in politics was significantly lower than that of students’ exercising rights. With respect to the students’ perception of democratic university environment, the data revealed that students’ overall perception of the university environment was slightly above average level. Specifically, the students’ perception of university environment regarding respect for ideas was significantly higher than that of university environment regarding participation in decision-making.

Hedonic behavior is a well-known phenomenon for tourism activities by the nature of tourism itself. However, there is a possible conflict between the structure of halal tourism and hedonic behavior. This paper aims to investigate the hedonic perception levels of halal-sensitive tourists (HSTs) while questioning their travel motivations.

According to the aim of this study, quantitative approach has been adopted via data gathering within World Halal Summit. A total of 1,123 surveys were gathered face to face from participants. Factor analysis applied to confirm validity of the data set while also running Cronbach alpha test through all dimensions. Also, frequency and mean analyses were applied in addition to t-test for comparing tests.

Results briefly show that HSTs have an average level of perception of hedonism. They also travel once or twice a year for religious, social or environmental reasons which supports the finding about their hedonism perception.

The research is also important in the applied field, especially in terms of decision-makers and supply determinants in destination management. Because if it is determined that the HSTs exhibit a utilitarian consumption, it has a guiding feature for the decision-makers to prefer halal tourism in terms of environmental management in the destination. In terms of the economic sustainability of the research destination or businesses, it also serves as a guide for the supply determinants in their investment activities.

This research is considerably important in terms of putting the HST typology on a conceptual basis in the theoretical field. In the research, it is tested whether the HSTs are hedonic consumers; in other words, whether they comply with the Islamic religious prohibitions. The tendency of HSTs to comply with the prohibitions reveals that they are utilitarian consumers, while halal tourism is a responsible tourism that cares about sustainability.

Central to the entire discipline of construction safety management is the concept of construction accidents. Although distinctive progress has been made in safety management applications over the last decades, construction industry still accounts for a considerable percentage of all workplace fatalities across the world. This study aims to predict occupational accident outcomes based on national data using machine learning (ML) methods coupled with several resampling strategies.

Occupational accident dataset recorded in Turkey was collected. To deal with the class imbalance issue between the number of nonfatal and fatal accidents, the dataset was pre-processed with random under-sampling (RUS), random over-sampling (ROS) and synthetic minority over-sampling technique (SMOTE). In addition, random forest (RF), Naïve Bayes (NB), K-Nearest neighbor (KNN) and artificial neural networks (ANNs) were employed as ML methods to predict accident outcomes.

The results highlighted that the RF outperformed other methods when the dataset was preprocessed with RUS. The permutation importance results obtained through the RF exhibited that the number of past accidents in the company, worker's age, material used, number of workers in the company, accident year, and time of the accident were the most significant attributes.

The proposed framework can be used in construction sites on a monthly-basis to detect workers who have a high probability to experience fatal accidents, which can be a valuable decision-making input for safety professionals to reduce the number of fatal accidents.

Practitioners and occupational health and safety (OHS) departments of construction firms can focus on the most important attributes identified by analysis results to enhance the workers' quality of life and well-being.

The literature on accident outcome predictions is limited in terms of dealing with imbalanced dataset through integrated resampling techniques and ML methods in the construction safety domain. A novel utilization plan was proposed and enhanced by the analysis results.

Purpose: Investors and portfolio managers can earn profitably when they correctly predict when stock prices will go up or down. For this reason, it is crucial to know the effect levels of the factors that affect stock prices. In addition to macroeconomic factors, the psychological behavior of investors also affects stock prices. Therefore, the study aims to reveal the different sensitivity levels of the stock index against macroeconomic and psychological factors.

Design/Methodology/Approach: In this study, dollar rate (USD), euro rate (EURO), time deposit interest rate (IR), gold price (GOLD), industrial production index (IPI), and consumer price index (CPI) (inflation (INF)) were used as macroeconomic factors, while Consumer Confidence Index (CCI) and VIX Fear Index (VIX) were used as psychological factors. In addition, the BIST-100 index, which is listed in Borsa Istanbul, was used as the stock index. The sensitivity of the stock index to macroeconomic and psychological factors was investigated using the Multivariate Adaptive Regression Spline (MARS) method using data from January 2012 to October 2020.

Findings: In the analyses performed using the MARS method, the coefficients of INF, USD, EURO, IR, CCI, and VIX Index were found to be statistically significant and effective on the stock index. Among these variables, INF has the highest effect on stocks. It is followed by USD, IR, EURO, CCI, and VIX. GOLD and IPI variables did not show statistical significance in the model. The most important difference of the MARS model from other regressions is that each factor’s effect on the stock index is analyzed by separating it according to the value of the factor. According to the results obtained from the MARS model: (1) it has been determined that USD, EURO, IR, and CPI have both positive and negative effects on the stock market index and (2) CCI and VIX have been found to have negative effects on stocks. These results provide essential information about how investors who plan to invest in the stock index should take into consideration different macroeconomic and psychological values.

Originality/value: This study contributes to the literature as it is one of the first studies to examine the effects of factors affecting the stock index by decomposing it according to the values it takes. Also, this study provides additional information by listing the factors affecting the stock index in order of importance. These results will help investors, portfolio managers, company executives, and policy-makers understand the stock markets.

This chapter addresses the impact of gendered social capital in developing countries to understand the barriers and opportunities to women's entrepreneurship with social capital development and also to examine factors influencing the development of social capital for women and how the identified factors benefit the creation of their entrepreneurial activities. This study follows a systemic literature review to achieve the purpose of the research by examining the selected articles in both English and Turkish, followed by factor comparison between developing, developed countries, and world datasets obtained from Global Entrepreneurship Monitor (GEM) database. The finding shows that social capital strongly impacts the entrepreneurial activities among women entrepreneurs in developing countries, especially in Turkey. Although the academic and practical studies on this field were started about two decades ago in Turkey, it has faced a radical increase in last 5 years and many practitioners and scholars working on these concepts. The clusters in English and Turkish resources are almost the same; however, the density and number of key terms are much lower in Turkish literature which shows a gap for Turkish researchers to publish more in this field to examine variables for better view about women entrepreneurship and social capital related to it.

This study investigates the differences in digitalization tendency levels among young adults (18–30) regarding their living environment, gender, and education.

Digital transformation (DT) refers to digital technologies becoming more prevalent in society. This process transforms lifestyles and business models using information and communication technologies. While digital transformation is on everyone’s agenda worldwide, it is still in its infancy. The data collected from 1,067 young adults show that all three control variables, living environment (CV1), gender (CV2), and education level (CV3), have a significant impact on digitalization tendency. Samples are selected using stratified sampling. Frequency distributions of quantitative data, descriptive statistics, ANOVA analysis, independent sample t-tests, reliability and validity analysis are interpreted in SPSS.

It is concluded from the study that the young adults living in Istanbul are more inclined to use digital technologies and to see the process from the standpoint of its positive results. It is observed that women have a higher digitalization tendency than men. Finally, the tendency to use digital technologies increases with education level, as does the likelihood of perceiving the outputs of these technologies as positive.

The study limited the sample to young adults aged 18–30.

Digitalization tendencies are positively influenced by factors such as living in Istanbul, being a woman, and having a high education level.

The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-01-2023-0020.