IDEAS home Printed from https://ideas.repec.org/a/ana/journl/v10y2024i2p43-54.html
   My bibliography  Save this article

Drivers of Advanced Digital Technologies

Author

Listed:
  • Ozlem Fikirli

    (Bartin University, Department of Economics)

  • Hasan Sahin

    (Ankara University, Department of Economics)

Abstract

Advancements in digital technologies, especially computer and information systems, force firms to adopt them in their production processes. Artificial intelligence, cloud computing, big data analytics, robotics, smart devices, and blockchain are the leading advanced technologies. This study explores the drivers of firms’ adoption of these technologies by estimating a multivariate probit model utilizing a Eurobarometer dataset. A statistically significant and positive correlation between the error terms of all models indicates that investigating the adoption of all advanced digital technologies together is more appropriate than independent analyses. Drivers of advanced digital technologies appear similar with decisive factors in using new technologies, and implementation of any type of innovation significantly increases the probability of adoption. The other determinants are the firm size, interaction with international markets, and the network structure of the market in which firms operate. Furthermore, location positively impacts the adoption of cloud computing and big data analytics, while it exerts no significant influence on the adoption of other types of advanced digital technologies.

Suggested Citation

  • Ozlem Fikirli & Hasan Sahin, 2024. "Drivers of Advanced Digital Technologies," World Journal of Applied Economics, WERI-World Economic Research Institute, vol. 10(2), pages 43-54, December.
    • Handle: RePEc:ana:journl:v:10:y:2024:i:2:p:43-54
    DOI: 10.22440/wjae.10.2.1
    as

    Download full text from publisher

    File URL: https://journal.econworld.org/index.php/econworld/article/view/246/94
    Download Restriction: no
    File URL: https://libkey.io/10.22440/wjae.10.2.1?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Euripidis Loukis & Spyros Arvanitis & Niki Kyriakou, 2017. "An empirical investigation of the effects of firm characteristics on the propensity to adopt cloud computing," Information Systems and e-Business Management, Springer, vol. 15(4), pages 963-988, November.
    2. Nicoletti, Giuseppe & von Rueden, Christina & Andrews, Dan, 2020. "Digital technology diffusion: A matter of capabilities, incentives or both?," European Economic Review, Elsevier, vol. 128(C).
    3. Da Xu & Ye Guo & Mengqi Huang, 2021. "Can Artificial Intelligence Improve Firms’ Competitiveness during the COVID-19 Pandemic: International Evidence," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 57(10), pages 2812-2825, August.
    4. Lene Kromann & Nikolaj Malchow-Møller & Jan Rose Skaksen & Anders Sørensen, 2020. "Automation and productivity—a cross-country, cross-industry comparison," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 29(2), pages 265-287.
    5. DeStefano, Timothy & Timmis, Jonathan, 2024. "Robots and export quality," Journal of Development Economics, Elsevier, vol. 168(C).
    6. Giotopoulos, Ioannis & Kontolaimou, Alexandra & Korra, Efthymia & Tsakanikas, Aggelos, 2017. "What drives ICT adoption by SMEs? Evidence from a large-scale survey in Greece," Journal of Business Research, Elsevier, vol. 81(C), pages 60-69.
    7. Mohamed Kossaï & Maria Luiza Lapa Souza & Younes Ben Zaied & Pascal Nguyen, 2020. "Determinants of the Adoption of Information and Communication Technologies (ICTs): the Case of Tunisian Electrical and Electronics Sector," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 11(3), pages 845-864, September.
    8. Lorenzo Cappellari & Stephen P. Jenkins, 2003. "Multivariate probit regression using simulated maximum likelihood," Stata Journal, StataCorp LLC, vol. 3(3), pages 278-294, September.
    9. Nir Kshetri, 2011. "Cloud Computing in the Global South: drivers, effects and policy measures," Third World Quarterly, Taylor & Francis Journals, vol. 32(6), pages 997-1014.
    10. Ballestar, María Teresa & Díaz-Chao, Ángel & Sainz, Jorge & Torrent-Sellens, Joan, 2020. "Knowledge, robots and productivity in SMEs: Explaining the second digital wave," Journal of Business Research, Elsevier, vol. 108(C), pages 119-131.
    11. H. Peyton Young, 2009. "Innovation Diffusion in Heterogeneous Populations: Contagion, Social Influence, and Social Learning," American Economic Review, American Economic Association, vol. 99(5), pages 1899-1924, December.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Yin, Zi Hui & Zeng, Wei Ping, 2023. "The effects of industrial intelligence on China's energy intensity: The role of technology absorptive capacity," Technological Forecasting and Social Change, Elsevier, vol. 191(C).
    2. Delera, Michele & Pietrobelli, Carlo & Calza, Elisa & Lavopa, Alejandro, 2022. "Does value chain participation facilitate the adoption of Industry 4.0 technologies in developing countries?," World Development, Elsevier, vol. 152(C).
    3. Parteka, Aleksandra & Kordalska, Aleksandra, 2023. "Artificial intelligence and productivity: global evidence from AI patent and bibliometric data," Technovation, Elsevier, vol. 125(C).
    4. Zhao, Yantong & Said, Rusmawati & Ismail, Normaz Wana & Hamzah, Hanny Zurina, 2024. "Impact of industrial robot on labour productivity: Empirical study based on industry panel data," Innovation and Green Development, Elsevier, vol. 3(2).
    5. Cui, Huijie & Liang, Shangkun & Xu, Canyu & Junli, Yu, 2024. "Robots and analyst forecast precision: Evidence from Chinese manufacturing," International Review of Financial Analysis, Elsevier, vol. 94(C).
    6. Wang, En-Ze & Lee, Chien-Chiang & Li, Yaya, 2022. "Assessing the impact of industrial robots on manufacturing energy intensity in 38 countries," Energy Economics, Elsevier, vol. 105(C).
    7. Cho, Jaehan & DeStefano, Timothy & Kim, Hanhin & Kim, Inchul & Paik, Jin Hyun, 2023. "What's driving the diffusion of next-generation digital technologies?," Technovation, Elsevier, vol. 119(C).
    8. Cao, Yuanyuan & Chen, Shaojian & Tang, Heyan, 2025. "Robot adoption and firm export: Evidence from China," Technological Forecasting and Social Change, Elsevier, vol. 210(C).
    9. Liu, Liang & Yang, Kun & Fujii, Hidemichi & Liu, Jun, 2021. "Artificial intelligence and energy intensity in China’s industrial sector: Effect and transmission channel," Economic Analysis and Policy, Elsevier, vol. 70(C), pages 276-293.
    10. Wang, Ting & Zhang, Yi & Liu, Chun, 2024. "Robot adoption and employment adjustment: Firm-level evidence from China," China Economic Review, Elsevier, vol. 84(C).
    11. Schneider, Florian, 2024. "Do robots boost productivity? A quantitative meta-study," MPRA Paper 123392, University Library of Munich, Germany.
    12. Adelheid Holl & Ruth Rama, 2024. "Spatial Patterns and Drivers of SME Digitalisation," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 15(2), pages 5625-5649, June.
    13. Zhang, Yi & Wang, Ting & Liu, Chun, 2024. "Beyond the modern productivity paradox: The effect of robotics technology on firm-level total factor productivity in China," Journal of Asian Economics, Elsevier, vol. 90(C).
    14. Kren, Janez & O'Toole, Conor, 2024. "What drives SME investment in digitalisation? Micro-data evidence for Ireland," Papers WP777, Economic and Social Research Institute (ESRI).
    15. Andre Jungmittag, 2021. "Robotisation of the manufacturing industries in the EU: Convergence or divergence?," The Journal of Technology Transfer, Springer, vol. 46(5), pages 1269-1290, October.
    16. Kanit Sangsubhan & Kumpon Pornpattanapaisankul & Pisacha Kambuya, 2023. "Automation and Productivity: Evidence from Thai Manufacturing Firms," PIER Discussion Papers 199, Puey Ungphakorn Institute for Economic Research.
    17. Filippi, Emilia & Bannò, Mariasole & Trento, Sandro, 2023. "Automation technologies and their impact on employment: A review, synthesis and future research agenda," Technological Forecasting and Social Change, Elsevier, vol. 191(C).
    18. H Peyton Young, 2014. "The Evolution of Social Norms," Economics Series Working Papers 726, University of Oxford, Department of Economics.
    19. Ke Liu & Zhenhong Qi & Li Tan & Caiyan Yang & Canwei Hu, 2023. "Mixed Use of Chemical Pesticides and Biopesticides among Rice–Crayfish Integrated System Farmers in China: A Multivariate Probit Approach," Agriculture, MDPI, vol. 13(8), pages 1-17, August.
    20. Marina Rybalka, 2015. "The innovative input mix. Assessing the importance of R&D and ICT investments for firm performance in manufacturing and services," Discussion Papers 801, Statistics Norway, Research Department.

    More about this item

    Keywords

    ;
    ;
    ;

    JEL classification:

    • D22 - Microeconomics - - Production and Organizations - - - Firm Behavior: Empirical Analysis
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ana:journl:v:10:y:2024:i:2:p:43-54. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Unal Tongur The email address of this maintainer does not seem to be valid anymore. Please ask Unal Tongur to update the entry or send us the correct address (email available below). General contact details of provider: https://edirc.repec.org/data/ewanatr.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.