Pretražite po imenu i prezimenu autora, mentora, urednika, prevoditelja

Napredna pretraga

Pregled bibliografske jedinice broj: 982700

From analytic to predictive digital performance measurement - Big Data challenge for controlling


Vitezić, Neda; Petrlić, Antonija; Lebefromm, Uwe
From analytic to predictive digital performance measurement - Big Data challenge for controlling // Book of Abstracts of the International Scientific Conference Economics of Digital Transformation (EDT) DIGITOMICS 2018 / Drezgić, Saša (ur.).
Rijeka: Ekonomski fakultet Sveučilišta u Rijeci, 2018. str. 29-29 (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)


CROSBI ID: 982700 Za ispravke kontaktirajte CROSBI podršku putem web obrasca

Naslov
From analytic to predictive digital performance measurement - Big Data challenge for controlling

Autori
Vitezić, Neda ; Petrlić, Antonija ; Lebefromm, Uwe

Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni

Izvornik
Book of Abstracts of the International Scientific Conference Economics of Digital Transformation (EDT) DIGITOMICS 2018 / Drezgić, Saša - Rijeka : Ekonomski fakultet Sveučilišta u Rijeci, 2018, 29-29

Skup
International Scientific Conference Economics of Digital Transformation DIGITOMIC (EDT 2018)

Mjesto i datum
Opatija, Hrvatska, 02.05.2018. - 04.05.2018

Vrsta sudjelovanja
Predavanje

Vrsta recenzije
Međunarodna recenzija

Ključne riječi
controlling ; Big Data ; digitalization ; performance measurement ; prediction

Sažetak
The aim of this research is to present possibilities for controlling regarding digitally oriented performance measurement and a proactive role in decision making. The goal is to develop a conceptual model of “digital proactive/prospective controlling” useful for predictive analysis in private and public- oriented organisations using a range of “information literacy ”. Due to digital technology, data, and information explosion, we need to develop analytical methods and models that will satisfy efficient business decision making. Controlling as one of the important functions in an organisation that provides analytical processing and creation of information for decision making purposes is now deeply affected by the challenges of digital technologies. Analytic or retrospective view of performance measurement is changing to predictive or proactive. Big Data enables controllers to use more accurate data and develop advanced measures. The emphasis is on the prediction of future problems or identification of potential opportunities which will lead to the growth of added value. As a result, the role of controllers as business partners needs to be further strengthened through its holistic analytical prospective thinking that will contribute to more efficient decision making. To find out the current state of controllers' digital development, a desk research of the existing scientific literature has been conduceted followed by interviews with controllers and responsible management in key positions of the selected organisations. Although the research was limited to a small group, primary findings show that the controller’s role will partially change in the future. Based on theoretical background and empirical research, we proposed the conceptual DPC model for the new era of controlling.

Izvorni jezik
Engleski

Znanstvena područja
Ekonomija

Napomena
Cjeloviti rad objavljen u 2019. godini u Zborniku
radova konferencije (Pogledati rad CROSBI ID:
937326)



POVEZANOST RADA


Projekti:
IP-2014-09-8235 - Model mjerenja efikasnosti javno zdravstvenih usluga (MEPHS) (Vitezić, Neda, HRZZ - 2014-09) ( CroRIS)

Ustanove:
Ekonomski fakultet, Rijeka

Profili:

Avatar Url Antonija Petrlić (autor)

Avatar Url Neda Vitezić (autor)


Citiraj ovu publikaciju:

Vitezić, Neda; Petrlić, Antonija; Lebefromm, Uwe
From analytic to predictive digital performance measurement - Big Data challenge for controlling // Book of Abstracts of the International Scientific Conference Economics of Digital Transformation (EDT) DIGITOMICS 2018 / Drezgić, Saša (ur.).
Rijeka: Ekonomski fakultet Sveučilišta u Rijeci, 2018. str. 29-29 (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)
Vitezić, N., Petrlić, A. & Lebefromm, U. (2018) From analytic to predictive digital performance measurement - Big Data challenge for controlling. U: Drezgić, S. (ur.)Book of Abstracts of the International Scientific Conference Economics of Digital Transformation (EDT) DIGITOMICS 2018.
@article{article, author = {Vitezi\'{c}, Neda and Petrli\'{c}, Antonija and Lebefromm, Uwe}, editor = {Drezgi\'{c}, S.}, year = {2018}, pages = {29-29}, keywords = {controlling, Big Data, digitalization, performance measurement, prediction}, title = {From analytic to predictive digital performance measurement - Big Data challenge for controlling}, keyword = {controlling, Big Data, digitalization, performance measurement, prediction}, publisher = {Ekonomski fakultet Sveu\v{c}ili\v{s}ta u Rijeci}, publisherplace = {Opatija, Hrvatska} }
@article{article, author = {Vitezi\'{c}, Neda and Petrli\'{c}, Antonija and Lebefromm, Uwe}, editor = {Drezgi\'{c}, S.}, year = {2018}, pages = {29-29}, keywords = {controlling, Big Data, digitalization, performance measurement, prediction}, title = {From analytic to predictive digital performance measurement - Big Data challenge for controlling}, keyword = {controlling, Big Data, digitalization, performance measurement, prediction}, publisher = {Ekonomski fakultet Sveu\v{c}ili\v{s}ta u Rijeci}, publisherplace = {Opatija, Hrvatska} }




Contrast
Increase Font
Decrease Font
Dyslexic Font