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- ItemAssessing competition in the Turkish cement industry: insights from the boone indicator(Emerald Publishing Limited, 2024-08) Yıldız, Hakan; Köprücü, Yılmaz; Şengül, Serkan; 355807Purpose – This paper investigates the degree of competitiveness within the Turkish cement industry, employing firm-level quarterly data spanning from 2008 to 2016. Design/methodology/approach – To assess the level and trajectory of competition among Turkish cement firms, we employ the Boone indicator (β) as formulated by Boone (2008). This indicator, rooted in the concept of relative profit differences (RPD), serves as a robust metric for gauging competitive dynamics. According to the ß indicator, firms exhibiting higher relative efficiency are expected to secure greater profits and market shares in a fiercely competitive market. Additionally, we utilize concentration indices for the purpose of revealing comparable findings. Findings – Empirical findings reveal that an enhancement in firms’ efficiency corresponds to a proportionally modest increase in either market share or profits, implying a lower degree of competition within the Turkish cement industry. Although the specific magnitudes of ß estimates exhibit temporal fluctuations, we may conclude that the Turkish cement industry does not conform to the ideals of perfect competition. The concentration indices calculated on the sample also support this result. Research limitations/implications – This research is limited to the Turkish cement companies over the period 2008–2016. Originality/value – The studies measuring the level of competition in the Turkish cement sector are generally based on concentration ratios. In this study, we assess the competition level by using a different methodology based on parametric procedures.
- ItemFashioning the self in Jean Rhys’s voyage in the dark and good morning, midnight(Çankaya Üniversitesi, 2024-04) Koç, Nesrin; 13778Jean Rhys held a deep passion for fashion and stylish attire. Her perspective on fashion, as an instrument of adopting “a second skin” finds expression in her focus on fashioning the self, a recurring motif in Rhys’s oeuvre. The physical difficulty Rhys’s female characters, whose lives bear strong similarities to her own, have in obtaining fashionable clothes represents the broader struggles they go through as the objects of the patriarchal and colonial gaze, in their voyages through the physical and metaphorical darkness of urban spaces like Paris and London in the early 1900s. Focusing on two of these women, Anna of Voyage in the Dark and Sasha in Good Morning, Midnight, for whom fashionable clothing appears to be the only way of navigating the modern society which marginalizes them, this study explores Rhys’s multilayered portrayal of fashion as a reflection of the near impossibility of attaining a cohesive sense of self, mirroring the characters’ struggles in fashioning their inner and outer selves.
- ItemImpact of contemporary technology on art and design(IGI Global, 2024-10) 36080; Dölkeleş, GülceHow does art and design intersect with digitalization? What does this mean for the future of design and art? In order to better understand digital transformation in art, it is necessary to reveal the predictions of experts in these fields. This book examines the relationship between art, design and digitalization and the impact of contemporary technology on these dynamics. Within the confines of this carefully researched book lies a comprehensive analysis of how art and design processes adapt and respond to the rise of technologies. This book covers extensive topics such as contemporary art, digital art, computer art, software art, virtual art, interactive art, video art, animation, digital advertising. The book draws a vivid portrait of the emergence of digital art by linking these developments from traditional to digital in its historical trajectory.
- ItemProblems and opportunities of artificial intelligence(İnönü Üniversitesi, 2022) Gürsakal, Necmi; Çelik, Sadullah; Batmaz, Bülent; 16040This article reviews Artificial Intelligence (AI)’s challenges and opportunities and discusses where AI might be headed. In the first part, it was tried to reveal the differences between Symbolic AI and Deep Learning approaches, then long promises but short deliveries of AI were mentioned. The problems of AI are that the media has high expectations about artificial intelligence and keeps the problems and restrictions it creates low. Today, while AI is stuck with issues such as deepfake applications and carbon footprints that create moral and climatologic problems; on the other hand, it is struggling with problems such as deep learning models requiring huge amounts of data. Another problem with deep learning is that deep learning models are a blackbox and not open to improvements because it is not known where mistakes were made. Among the new paths ahead of AI are Hierarchical Temporal Memory (HTM) models and hybrid models that generally try to bridge the gap between Symbolic AI and Connectionist AI. If we consider that the most important leaps in AI have been made with the features of the brain that AI can imitate, then the developed HTM models may also be a new opportunity for AI.
- ItemSynthetic data for deep learning: generate synthetic data for decision making and applications with Python and R(Apress, 2022) Gürsakal, Necmi; Çelik, Sadullah; Birişçi, Esma; 16040
- ItemUtilizing large language models for EFL essay grading: an examination of reliability and validity in rubric-based assessments(Wiley, 2024-05) Yavuz, Fatih; Çelik, Özgür; Yavaş Çelik, Gamze; 131069This study investigates the validity and reliability of generative large language models (LLMs), specifically ChatGPT and Google's Bard, in grading student essays in higher education based on an analytical grading rubric. A total of 15 experienced English as a foreign language (EFL) instructors and two LLMs were asked to evaluate three student essays of varying quality. The grading scale comprised five domains: grammar, content, organization, style & expression and mechanics. The results revealed that fine-tuned ChatGPT model demonstrated a very high level of reliability with an intraclass correlation (ICC) score of 0.972, Default ChatGPT model exhibited an ICC score of 0.947 and Bard showed a substantial level of reliability with an ICC score of 0.919. Additionally, a significant overlap was observed in certain domains when comparing the grades assigned by LLMs and human raters. In conclusion, the findings suggest that while LLMs demonstrated a notable consistency and potential for grading competency, further fine-tuning and adjustment are needed for a more nuanced understanding of non-objective essay criteria. The study not only offers insights into the potential use of LLMs in grading student essays but also highlights the need for continued development and research.
