Advancements in Decision Making and Data Analytics Case Applications — Ayşegül Tuş Esra Aytaç Adalı Tayfun Öztaş Furkan Şükrü Kütük Mahmut Baydaş Abdullah Hulusi Kökçam Abdullah Özçil Gülin Zeynep Öztaş

Decision making processes have become increasingly critical in the face of complex global dynamics and the era of big data Advanced analytical methods and multi criteria decision making MCDM approaches facilitate more informed and optimized decisions across various domains In this context the scientific book titled Advancements in Decision Making and Data Analytics Case Applications brings together significant studies that explore innovations in decision making and data analytics By focusing on the applied aspects of decision and data analytics this book serves as a comprehensive resource for academics and professionals The chapters encompass both theoretical approaches and real world applications presenting original research contributions The first chapter examines the LOPCOW method and a novel RAM based MCDM methodology in the context of university rankings The evaluation of university performance plays a crucial role in shaping educational policies and this study contributes to the literature by proposing a new integrated model The second chapter analyzes the assessment of logistics performance in emerging markets using the CILOS and MOORA methods Logistics is a fundamental pillar of global trade and effective decision support mechanisms are essential for gaining a competitive advantage The third chapter focuses on enhancing decision making processes through machine learning and data analytics techniques By conducting sentiment analysis on user reviews this study highlights the role of big data analytics in decision making

Abdullah Özçil tarafından kaleme alınan Advancements in Decision Making and Data Analytics Case Applications Eğitim Yayınevi Bilimsel Eserler eseri olarak okurlarla buluşuyor Advancements in Decision Making and Data Analytics Case Applications Abdullah Özçil Kitap Özeti Decision making processes have become increasingly critical in the face of complex global dynamics and the era of big data Advanced analytical methods and multi criteria decision making MCDM approaches facilitate more informed and optimized decisions across various domains In this context the scientific book titled Advancements in Decision Making and Data Analytics Case Applications brings together significant studies that explore innovations in decision making and data analytics By focusing on the applied aspects of decision and data analytics this book serves as a comprehensive resource for academics and professionals The chapters encompass both theoretical approaches and real world applications presenting original research contributions The first chapter examines the LOPCOW method and a novel RAM based MCDM methodology in the context of university rankings The evaluation of university performance plays a crucial role in shaping educational policies and this study contributes to the literature by proposing a new integrated model The second chapter analyzes the assessment of logistics performance in emerging markets using the CILOS and MOORA methods Logistics is a fundamental pillar of global trade and effective decision support mechanisms are essential for gaining a competitive advantage The third chapter focuses on enhancing decision making processes through machine learning and data analytics techniques By conducting sentiment analysis on user reviews this study highlights the role of big data analytics in decision making Yayınevi Eğitim Yayınevi Bilimsel Eserler Yazar Abdullah Özçil Sayfa 120 Sayfa Kağıt 1 Hamur Boyut 16 00x24 00 cm Basım Yılı Mart 2025 Barkod 9786253850890 Kategori Yönetim

Decision making processes have become increasingly critical in the face of complex global dynamics and the era of big data Advanced analytical methods and multi criteria decision making MCDM approaches facilitate more informed and optimized decisions across various domains In this context the scientific book titled Advancements in Decision Making and Data Analytics Case Applications brings together significant studies that explore innovations in decision making and data analytics By focusing on the applied aspects of decision and data analytics this book serves as a comprehensive resource for academics and professionals The chapters encompass both theoretical approaches and real world applications presenting original research contributions The first chapter examines the LOPCOW method and a novel RAM based MCDM methodology in the context of university rankings The evaluation of university performance plays a crucial role in shaping educational policies and this study contributes to the literature by proposing a new integrated model The second chapter analyzes the assessment of logistics performance in emerging markets using the CILOS and MOORA methods Logistics is a fundamental pillar of global trade and effective decision support mechanisms are essential for gaining a competitive advantage The third chapter focuses on enhancing decision making processes through machine learning and data analytics techniques By conducting sentiment analysis on user reviews this study highlights the role of big data analytics in decision making

Decision making processes have become increasingly critical in the face of complex global dynamics and the era of big data Advanced analytical methods and multi criteria decision making MCDM approaches facilitate more informed and optimized decisions across various domains In this context the scientific book titled Advancements in Decision Making and Data Analytics Case Applications brings together significant studies that explore innovations in decision making and data analytics By focusing on the applied aspects of decision and data analytics this book serves as a comprehensive resource for academics and professionals The chapters encompass both theoretical approaches and real world applications presenting original research contributions The first chapter examines the LOPCOW method and a novel RAM based MCDM methodology in the context of university rankings The evaluation of university performance plays a crucial role in shaping educational policies and this study contributes to the literature by proposing a new integrated model The second chapter analyzes the assessment of logistics performance in emerging markets using the CILOS and MOORA methods Logistics is a fundamental pillar of global trade and effective decision support mechanisms are essential for gaining a competitive advantage The third chapter focuses on enhancing decision making processes through machine learning and data analytics techniques By conducting sentiment analysis on user reviews this study highlights the role of big data analytics in decision making

Decision making processes have become increasingly critical in the face of complex global dynamics and the era of big data Advanced analytical methods and multi criteria decision making MCDM approaches facilitate more informed and optimized decisions across various domains In this context the scientific book titled Advancements in Decision Making and Data Analytics Case Applications brings together significant studies that explore innovations in decision making and data analytics By focusing on the applied aspects of decision and data analytics this book serves as a comprehensive resource for academics and professionals The chapters encompass both theoretical approaches and real world applications presenting original research contributions The first chapter examines the LOPCOW method and a novel RAM based MCDM methodology in the context of university rankings The evaluation of university performance plays a crucial role in shaping educational policies and this study contributes to the literature by proposing a new integrated model The second chapter analyzes the assessment of logistics performance in emerging markets using the CILOS and MOORA methods Logistics is a fundamental pillar of global trade and effective decision support mechanisms are essential for gaining a competitive advantage The third chapter focuses on enhancing decision making processes through machine learning and data analytics techniques By conducting sentiment analysis on user reviews this study highlights the role of big data analytics in decision making