Yazar "Habiboglu, Ozge" seçeneğine göre listele

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    A Literature Review on the Emerging Trends of AI Applications in E-Retailing: Insights from the Journal of Retailing and Consumer Services
    (Bolu Abant Izzet Baysal University, 2025) Habiboglu, Ozge
    The use of artificial intelligence (AI) in the retail sector is steadily increasing. This study aims to reveal the usage of AI in retailing over the years. For thisKoh purpose, 137 studies published in the Journal of Retailing and Consumer Services were analyzed according to SPAR-4-SLR protocol. The reviewed studies were analyzed across four domains: publication year, consumer approach, AI technology applied, and theoretical framework. Findings indicate that most studies were published in 2024, primarily focusing on consumer purchasing behavior, extensive use of chatbots, and frequent application of the Technology Acceptance Model (TAM) in theoretical grounding. This research distinguishes itself by examining the retailer-consumer behavior relationship, mainly contributing to current knowledge in this area. Keywords: AI, artificial ıntelligence, retailing, consumer behaviour
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    Research on the Effect of Social Media Implementations for Improved Customer Relations and Services
    (2024) Habiboglu, Ozge; Turkyilmaz, Ceyda Aysuna; Yüksel, Cenk Arsun; Pirtini, Serdar
    The primary motivation of this study is to examine the increase in social media usage and the primary reasons behind it. The effects of social media implementations (SMI) on customer relations and services have been investigated in this context. Data were collected from 195 firms operating in Turkey and analyzed using regression analysis. The findings revealed that Social Media Usage (SMU) is essential to customer relations and services. Additionally, it was found that SMIs have a positive impact on improving customer relationships and that the customer engagement initiatives (CEI) and social media strategies (SMS) implemented by firms are strongly associated with improved customer relations and services (ICRS). This research is expected to contribute to the literature by analyzing the effects of social media usage at the firm level.
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    The analysis of brand reputation and willingness to pay price premium with regression analysis and classification algorithms
    (Emerald Group Publishing Ltd, 2023) Ozhan, Seniz; Ozhan, Erkan; Habiboglu, Ozge
    Purpose - Brand reputation (BR) is one of the most important factors that affect the consumer-brand relationship and give businesses a competitive advantage. Businesses with a strong BR can increase their market shares and product market prices, in addition to gaining a competitive advantage. In order for businesses to have these advantages, they need to know and analyze their consumers. This study aimed to develop an alternative analysis method by using classification algorithms and regression analysis to measure and evaluate the effect of consumers' BR perceptions on their willingness to pay premium prices (WPP). Design/methodology/approach - The research data were collected from 483 participants by the online survey method due to the COVID-19 pandemic. The data were first analyzed with regression analysis, and the effect of BR on WPP was found to be significant. Then, using artificial intelligence (AI) methods that were not used in previous studies, consumers' perceptions of BR and WPP were clustered and classified. Findings - The results revealed the highest and lowest customer groups with BR and WPP and empirically demonstrated that highly accurate practical classification models can be applied to determine strategies in line with these findings. Originality/value - The model proposed in this study offers an integrated approach by using AI and regression analysis together and tries to fill the gap in the literature in this field. Therefore, the novelty of this study is to quantitatively reveal and evaluate the relationship between BR and WPP by using AI classification algorithms and regression analysis together.