Addressing productivity paradox with big data: implications to policy making

Informazioni relative al progetto

BIGPROD

ID dell’accordo di sovvenzione: 870822

DOI

10.3030/870822

Progetto chiuso

Data della firma CE 8 Novembre 2019

Data di avvio 1 Dicembre 2019

Data di completamento 30 Aprile 2022

Finanziato da

• SOCIETAL CHALLENGES - Europe In A Changing World - Inclusive, Innovative And Reflective Societies

Costo totale

€ 993 726,25

Contributo UE

€ 993 726,25

Coordinato da

TEKNOLOGIAN TUTKIMUSKESKUS VTT OY
Finland

CORDIS fornisce collegamenti ai risultati finali pubblici e alle pubblicazioni dei progetti ORIZZONTE.

I link ai risultati e alle pubblicazioni dei progetti del 7° PQ, così come i link ad alcuni tipi di risultati specifici come dataset e software, sono recuperati dinamicamente da .OpenAIRE .

Risultati finali

Documents, reports (11)

Dissemination of workshop results, scientific paper and policy brief

Dissemination of workshop results scientific paper and policy brief

Final platform operation report

Final platform operation report the deliverable reports on the data sources mining algorithms and numbers relative to the operation of the platform PPMI

Interim platform operation report:

Interim platform operation report the deliverable reports on the data sources mining algorithms and numbers relative to the operation of the platform PPMI

Interim Reports D2.1 and D3.2

Interim Reports D21 and D32 dissemination on social media

Policy Brief_1

Policy brief aiming to introduce project objectives and spark discussions

Final report on the including updated literature

Final report on the including updated literature the estimations of the econometric model and a discussion of the policy implications

Work in progress scientific publication

Work in progress publication addressing each pilot with a concrete list of variables data needed and measures created

Interim report including the literature review

Interim report including the literature review, an outline of the econometric model plus data description to be used.

Scientific publication

Scientific publication submitted on published in the repository evaluating the productivity in each pilot

Policy Brief_2

Policy brief aiming to introduce project objectives and spark discussions also introducing the preliminary achievements and ongoing actions

Scientific paper

Scientific paper on the extended CDM model

Websites, patent fillings, videos etc. (4)

Interim Report D3.3

Interim Report D33 and Update on Pilots dissemination on social media

Social Media launch

Social Media launch including website and other media presence Twitter Facebook etc

Final reports D2.2, D3.4, D3.5 and D4.4 dissemination (on social media)

Final reports D22 D34 D35 and D44 dissemination on social media

Policy Brief_3

Policy brief encompassing all three pilots describing in detail the potential of Big data approached in all three pilots

Demonstrators, pilots, prototypes (3)

3rd consultation_Experts on D3.3

3rd consultation with experts (data science focus) on Interim Report “Platform Operation” D3.3

Validation Workshop
Interactive learning workshop

Other (2)

Programme code

Dashboard-like visualization of the measures and a GitHub repository of programme code (Jupyter Notebooks)

Personal Data Protection Strategy and Measures - Final report

Open Research Data Pilot (1)

Personal Data Protection Strategy and Measures - Interim report

Personal Data Protection Strategy and Measures Interim report

Pubblicazioni

Other (9)

Addressing the productivity paradox with big data: A literature review and adaptation of the CDM econometric model

Autori: Torben Schubert, Angela Jäger, Serdar Turkeli & Fabiana Visentin
Pubblicato in: MERIT Working Papers, Numero 2020-050, 2020
Editore: United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT)

BIGPROD: Write-up of three pilot cases

Autori: Suominen Arho, Hajikani Arash, Ashouri Sajad, Cunningham Scott
Pubblicato in: dataverse, 2022
Editore: dataverse
DOI: 10.34894/r99trk

Indicators on firm level innovation activities from web scraped data

Autori: Sajad Ashouri, Arho Suominen, Arash Hajikhani, Lukas Pukelis, Torben Schubert, Serdar Türkeli, Cees Van Beers, Scott Cunninghum
Pubblicato in: 2021
Editore: Elsevier
DOI: 10.2139/ssrn.3938767

Addressing the productivity paradox with big data: A literature review and adaptation of the CDM econometric model

Autori: Torben Schubert, Angela Jäger, Serdar Türkeli, Fabiana Visentin
Pubblicato in: UNU-MERIT Working Paper Series, 2020
Editore: Maastricht Economic and social Research institute on Innovation and Technology (UNU‐MERIT)

BIGPROD Data & Information

Autori: Ashouri Sajad, Suominen Arho, Hajikhani Arash, Cunningham Scott, Schubert Torben, Türkeli Serdar, Jäger Angela, Van Beers Cees, Pukelis Lukas, Deschryvere Mathias
Pubblicato in: dataverse, 2022
Editore: dataverse

Connecting firm's web scraped textual content to body of science: Utilizing microsoft academic graph hierarchical topic modeling

Autori: Arash Hajikhani, Lukas Pukelis, Arho Suominen, Sajad Ashouri, Torben Schubert, Ad Nottend, Scott W.Cunninghame
Pubblicato in: MethodsX, Numero 22150161, 2022, ISSN 2215-0161
Editore: Elsevier
DOI: 10.1016/j.mex.2022.101650

Return of the Solow-paradox in AI? AI-adoption and firm productivity

Autori: Asta Bäck, Arash Hajikhani, Angela Jäger, Torben Schubert, Arho Suominen
Pubblicato in: Papers in Innovation Studies, Lund University, CIRCLE - Centre for Innovation Research, 2022
Editore: Scandinavian Working Papers in Economics

Policy Brief: Introducing BIGPROD

Autori: Arho Suominen, Ad Notten
Pubblicato in: 2020
Editore: United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT)

Policy Brief: Data Analytics in Policy-Making: The BIGPROD approach

Autori: Arho Suominen, Arash Hajikhani
Pubblicato in: 2020
Editore: United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT)

Peer reviewed articles (1)

Research themes in big data analytics for policymaking: Insights from a mixed‐methods systematic literature review

Autori: Arho Suominen, Arash Hajikhani
Pubblicato in: Policy & Internet, Numero 19442866, 2021, ISSN 1944-2866
Editore: Wiley
DOI: 10.1002/poi3.258