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    Comparison of Artificial Intelligence Techniques for The UK Air Passenger Short-Term Demand Forecasting: A Destination Insight Study
    (2023) Koçak, Bahri Baran
    Web search queries become essential drivers to forecast air passenger demand for operational benefits. Scholars and marketing experts. Forecasting passenger demand is one of the most important marketing problems that experts frequently encounter, but there are very few studies in the literature using search queries. The main novelty of this study is to show that Destination Insight (DI) can be useful as an air passenger demand proxy in the UK. To prove this primary objective, this work uses several machine and deep learning multi-layer perceptron (MLP) methods based on a big-data framework. The findings indicate that DI is a crucial predictor of the UK air passenger demand. Besides, popular error metrics (RMSE, MAPE, MAD and AIC) were compared to find the best model in this study. Specifically, results indicate that MLP following feed forward neural networks works better for the UK air passenger market.
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    Deep learning models for airport demand forecasting with google trends: A case study of Madrid International Airports
    (IGI Global, 2023) Koçak, Bahri Baran
    Managers gain new insights into how operational benefits can be achieved. Forecasting problems for passenger flow in airports are gaining interest among marketing researchers, but comparison of stochastic optimisation methods via deep learning forecasts with search query data is not yet available in the aviation field. To fill this gap, the current study predicts the demand of Madrid airport demand with Google search query data using H2O deep learning method. The findings indicate that there is a long-term relationship between search queries and actual passenger demand. Besides, search queries “fly to madrid,” and “flights to madrid spain” were found to be the cause of the actual domestic air passenger demand in Madrid. Also, to determine the best forecasting accuracy, stochastic gradient descent (SGD) optimisers were used. Specifically, findings indicate that Adam is a better optimiser increasing forecasting accuracy for Madrid airports.
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    EXPLORING AND IDENTIFICATION OF PASSENGERS’ WEB SEARCH GOALS USING “TICKET” RELATED QUERIES IN THE AIRLINE MARKET: A GOOGLE TRENDS STUDY
    (2020) Koçak, Bahri Baran
    The implications of information search behavior on the web have become clearer nowthat internet search engines data are publicly available. In this respect, understanding andexploring web search goals of users can lead search engines to provide better-personalizedresults, while enabling marketers to choose the right advertising objectives. It is of greatimportance that people’s time-dependent web search goals of the purchasing of air ticketsare revealed from a collective perspective in the airline market. Thus, this study aims todetermine time-dependent web search goals of passengers for the airline market by examining different word variations in flight ticket queries. Thus, global search query datafrom different periods were obtained using Google Trends (GT). Independent samplest-test, One-Way ANOVA and MANOVA were performed to answer the research questions.According to the results of the research, passengers were mostly interested in using Google for transactional goals. This was followed by “locating” physical evidence in airlineservices. Besides, navigational searches of passengers appeared to differ significantly byhourly periods.
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    Fly “With us”! Impact of Consumer-Brand Relationship on Consumer Engagement: An Empirical Investigation on Turkish Airline Instagram Pages
    (2021) Koçak, Bahri Baran
    Leading consumers to engage with brand posts in social media has become one of essential branding strategies for airline industry. Linguistic characteristics of a social media message can also play an important role to increase consumer engagement (CE) level. This study investigates the effects of the uses of pronouns and “we” as a consumer-brand (cb) relationship on CE with Turkish airline Instagram posts considering Social Presence Theory. Multiple Linear Regression (MLR) analysis using least squares model are conducted to analyze 817 Instagram data. The findings indicate that the use of first-person singular, first-person plural, third-person singular, and second-person pronouns in Instagram posts increase CE. Also, the use of “we-biz” as c-b relationship affect both liking and commenting behavior of consumers.
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    Fly “With us”! impact of consumer-brand relationship on consumer engagement: An empirical investigation on Turkish Airline instagram pages
    (Beta Dergi, 2021) Koçak, Bahri Baran
    Leading consumers to engage with brand posts in social media has become one of essential branding strategies for airline industry. Linguistic characteristics of a social media message can also play an important role to increase consumer engagement (CE) level. This study investigates the effects of the uses of pronouns and “we” as a consumer-brand (cb) relationship on CE with Turkish airline Instagram posts considering Social Presence Theory. Multiple Linear Regression (MLR) analysis using least squares model are conducted to analyze 817 Instagram data. The findings indicate that the use of first-person singular, first-person plural, third-person singular, and second-person pronouns in Instagram posts increase CE. Also, the use of “we-biz” as c-b relationship affect both liking and commenting behavior of consumers.
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    Havayolu markalarında tüketici katılımını artırmak: SKYTRAX 100 YouTube sayfaları örneği
    (Pamukkale Üniversitesi, 2022) Koçak, Bahri Baran
    Tüketici Katılımı (TK) YouTube üzerinden ürün/hizmet geliştirme ve sponsorluk gibi birçok pazarlama aktivitelerini gerçekleştiren havayolları için oldukça dikkat çekici bir kavram haline gelmiştir. Bu çalışma YouTube’daki havayolu markaları için TK faktörlerini inceleyerek alanyazındaki araştırmalara katkıda bulunmaktadır. Bu doğrultuda, en küçük kareler yöntemini kullanan çoklu lineer regresyon yöntemi kullanılarak SKYTRAX 100 içerisinde yer alan her bir YouTube sayfasının en popüler 10 videosu analiz edilmiştir. Toplamda 600 video açıklaması dikkate alınarak hipotezler test edilmiş olup sonuçlar interaktif açıklamaların, yüksek çözünürlüklü videoların ve alt yazıların daha fazla izleme sağladığını ortaya koymuştur. Ayrıca, destinasyon sunumu ve animasyon kullanımı da katılımla ilişkilidir. Bulgular canlılık ve interaktivitenin farklı katılım skorları üzerinde etkili belirleyiciler olduğunu ortaya koymakla birlkte araştırma modeli YouTube’da popüer videolar yayınlamak ve başarılı havayolu kanalları kurmak için gerekli ipuçları da vermektedir.
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    More than a thousand words!: Emoji engagement on Turkish airline Instagram pages
    (IGI Global, 2022) Koçak, Bahri Baran
    Consumer engagement (CE) has become one of the marketing problems that many airlines strive to solve. In this sense, emojis implemented to increase CE on social media have gained a stronger popularity as a form of communication among brands. This chapter will provide readers with a deeper understanding of how emoji usage and emoji types affect CE using the highly standardized Unicode classification based on emoji semiotics. Therefore, the author concludes with a case study that investigates the relationship between emoji usage and CE in the official Instagram pages of Turkish airline companies. Also, the author discusses the state of the art in semiotics and concludes by suggesting that the use of emojis by brands may change activism on social media through consumer behavior.
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    THE EFFECT OF FİGURATİVE LANGUAGE ON CONSUMER ENGAGEMENT: CASE OF TURKİSH AİRLİNE INSTAGRAM PAGES
    (Pazarlama ve Pazarlama Araştırmaları Derneği, 2024) Koçak, Cem Burak; Atalık, Özlem; Koçak, Bahri Baran
    Increasing consumer engagement (CE) in social media is one of the most important marketing problems faced by brands in today's competitive markets. Although many studies in the literature prove that brand content types play an important role on CE, the importance and impact of the figurative language elements in the content has not been mentioned so far. The aim of this study is to determine the possible effects of figurative language elements on CE based on encoding/decoding theory. For the study, 1230 airline Instagram posts were examined with the Multiple Linear Regression model. As a result of the research, it was determined that figurative language elements (idioms and personifications) affect CE at various levels. In addition to providing clues about how the figurative language elements to be used in the online environment affect engagement, the findings also give tips for practical benefits such as how to design content in social media marketing communication.