Pekin Erhan Eren

E-mail

ereren@metu.edu.tr

Department

Graduate School of Informatics

ORCID

0000-0003-4354-3358

Scopus Author ID

6603471003

Web of Science Researcher ID

ABA-4438-2020

Edge Computing Applications in Industrial IoT: A Literature Review Bayar, Alp; Şener, Umut; Kayabay, Kerem; Eren, Pekin Erhan (2023-01-01) The Industrial Internet of Things (IIoT) covers many computing devices and sensors constantly generating and exchanging data in a complicated network. Ongoing research tries to fit decentralized edge computing architecture...
What Drives Success in Data Science Projects: A Taxonomy of Antecedents Gökay, Gonca Tokdemir; Nazlıel, Kerem; Şener, Umut; GÖKALP AYDIN, EBRU; Gökalp, Mert Onuralp; Gençal, Nergiz; Dağdaş, Gizemnur; Eren, Pekin Erhan (2023-01-01) Organizations have been trying to reshape their business processes and transform them into a smart environment to attain sustainable competitive advantage in their markets. Data science enables organizations to define inte...
A Comprehensive Big Data Framework for Energy Markets: Oil and Gas Demand Forecasting Bayar, Alp; Koç, Burcu; Gökalp, Mert Onuralp; Özden, Baran; Yeldan, Yiğit; Koçyiğit, Altan; Eren, Pekin Erhan (2022-12-29) Demand forecasting in the energy sector is essential for both countries and companies to plan their supply and demand. Agents in the highly volatile oil markets have to act fast and data-driven. In the literature, studies ...
Determinative Factors of Cloud Computing Adoption in Government Organizations Koç, Burcu; Şener, Umut; Eren, Pekin Erhan (2022-12-29) Digital transformation in government organizations has led to the spread of e-government applications. Accordingly, government institutions face many challenges, such as the lack of highly skilled IT personnel and resource...
A process assessment model for big data analytics Gökalp, Ebru; Gökalp, Mert Onuralp; Kayabay, Kerem; Gökalp, Selin; Koçyiğit, Altan; Eren, Pekin Erhan (2022-03-01) Big data analytics (BDA) grasp the potential of generating valuable insights and empowering businesses to support their strategic decision-making. However, although organizations are aware of BDAs’ potential opportunities,...
Data science roadmapping: An architectural framework for facilitating transformation towards a data-driven organization Kayabay, Kerem; Gökalp, Mert Onuralp; Eren, Pekin Erhan; Koçyiğit, Altan (2022-01-01) Leveraging data science can enable businesses to exploit data for competitive advantage by generating valuable insights. However, many industries cannot effectively incorporate data science into their business processes, a...
Dijital Olgunluk İndeksi: Organizasyonların Dijital Dönüşüm Yolculuğunda Verimliliği Artırmak İçin Bir Kantitatif Yöntem Şener, Umut; Gokalp, Ebru; Eren, Pekin Erhan (2022-01-01) Amaç: Literatürde dijital dönüşüm için geliştirilmiş olgunluk modellerinin incelenmesi ve yeni bir indeks yapısının temellerinin oluşturulması hedeflenmektedir. Böylece, işletmelerin mevcut dijital dönüşüm düzeylerini anal...
The development of the data science capability maturity model: a survey-based research Gökalp, Mert Onuralp; Kayabay, Kerem; Koçyiğit, Altan; Eren, Pekin Erhan (2021-09-01) Purpose The purpose of this paper is to investigate social and technical drivers of data science practices and develop a standard model for assisting organizations in their digital transformation by providing data science ...
Data-driven manufacturing: An assessment model for data science maturity Gökalp, Mert Onuralp; KAYABAY, KEREM; Koçyiğit, Altan; Eren, Pekin Erhan (2021-07-01) © 2021 The Society of Manufacturing EngineersToday, data science presents immense opportunities by turning raw data into manufacturing intelligence in data-driven manufacturing that aims to improve operational efficiency a...
Assessment of process capabilities in transition to a data-driven organisation: A multidisciplinary approach Gökalp, Mert Onuralp; Gökalp, Ebru; Koçyiğit, Altan; Eren, Pekin Erhan (2021-06-01) The ability to leverage data science can generate valuable insights and actions in organisations by enhancing data-driven decision-making to find optimal solutions based on complex business parameters and data. However, on...

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