Data driven decisions in enterprises - implications for business education and cases

ISBN-13: 9783631878712 / Angielski / Miękka / 2023 / 230 str.

Haldun Akpinar; Riza Öztürk

Opis

The topic "Big Data" represents a major challenge for companies and there is an enormous need for "data intelligence" in order to use this information specifically for the competitiveness. This volume contains contributions on challenges, hurdles and examples in intelligent data structuring both in corporate practice and in teaching.

Spis treści

Data driven decisions in enterprises - implications for business cases, Data Driven Business at Miele - An implementation case in the manufacturing industry, Process Mining as a tool for corporate value production, A cross-sector comparative analysis of a multidimensional framework of value creation through big data, Data-driven security, AI enabled "Just walkout technlology" in shopping malls: empirical evidence to predict consumer purchase intention with moderating role of shopping convenience, Business Valuation Methods in Europe - Similarities and Differences. Applying situated visualization for supporting consumer decision making, Resource based theory: insights in a managerial point of view, Data reports with dynamic documents: using R, Makdown, RStudio, Shiny, , Analysis of an SME company using the Altman Z-Score model, A constructive learning model for digital skills in treasury, Using researched-based learning on barriers to digital transformation to impact student engagement during a pandemic, Teaching Business students to code - thoughts on Why and How

O autorze

Riza Öztürk is a Professor of Statistical and Mathematical Methods in Economics and Business Administration at Bielefeld University of Applied Sciences and since 2020 Dean of the Faculty of Business.

Haldun Akpinar is a Professor of Business Informatics at Marmara University and has been Department Head of the German Department of Business Informatics since 2003. He also lectured on Quantitative Decision Making Systems, Data Mining & Knowledge Discovery and Artificial Intelligence.