IDEAS home Printed from https://ideas.repec.org/a/icb/wpaper/v5y2019i189-94.html

The Future of Jobs in the Digital World

Author

Listed:
  • Luminita IONESCU

    (Spiru Haret University, Faculty of Economic Sciences, 46 G Fabricii Str., District 6 Bucharest, Romania)

  • Maria ANDRONIE

    (Spiru Haret University, Faculty of Economic Sciences, 46 G Fabricii Str., District 6 Bucharest, Romania)

Abstract

The current trends in the global economy depend on the accelerated technology, the trends in robotization, a new human-machine frontier, the changing geography of production, distribution and value chains, a net positive outlook for jobs and a re-skilling imperative in a context of growing skills instability all over the world. Current strategies for business development in the digital word seek to automate work tasks and increase the profits. The new accelerated technology determines significant changes in the employment types, leading to cost control and reduction of expenses. Most of the companies are prepared to find opportunities to use new technologies and to upgrade job quality. However, the job market is perceived differently due to mobile Internet, artificial intelligence and cloud technology. The employers are seeking workers with new skills and talents for adoption of user and entity big data analytics, cloud computing and artificial intelligence. The future workforce must develop their skills or retrain to acquire new skills and to invest heavily in the development of new agile learners in order to perform more flexible jobs and to accept new roles due to business transformation and digital technology in the global economy.

Suggested Citation

  • Luminita IONESCU & Maria ANDRONIE, 2019. "The Future of Jobs in the Digital World," International Conference on Economic Sciences and Business Administration, Spiru Haret University, vol. 5(1), pages 89-94, November.
    • Handle: RePEc:icb:wpaper:v:5:y:2019:i:1:89-94
    as

    Download full text from publisher

    File URL: http://icesba.eu/RePEc/icb/wpaper/ICESBA2019_9IONESCU_P89-94.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Zhang, Pengqing, 2019. "Automation, wage inequality and implications of a robot tax," International Review of Economics & Finance, Elsevier, vol. 59(C), pages 500-509.
    2. Francesco Caselli & Alan Manning, 2019. "Robot Arithmetic: New Technology and Wages," American Economic Review: Insights, American Economic Association, vol. 1(1), pages 1-12, June.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Maria ANDRONIE & Luminita Ionescu, 2019. "The Influence Of Cloud Technology In Transforming Accounting Practices," Annals of Spiru Haret University, Economic Series, Universitatea Spiru Haret, vol. 19(4), pages 27-34.

    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. Kudoh, Noritaka & Miyamoto, Hiroaki, 2025. "Robots, AI, and unemployment," Journal of Economic Dynamics and Control, Elsevier, vol. 174(C).
    2. Venturini, Francesco, 2022. "Intelligent technologies and productivity spillovers: Evidence from the Fourth Industrial Revolution," Journal of Economic Behavior & Organization, Elsevier, vol. 194(C), pages 220-243.
    3. Caselli, Mauro & Fracasso, Andrea & Scicchitano, Sergio & Traverso, Silvio & Tundis, Enrico, 2025. "What workers and robots do: An activity-based analysis of the impact of robotization on changes in local employment," Research Policy, Elsevier, vol. 54(1).
    4. Jacob, Tinu Iype & Paul, Sunil, 2024. "Labour income share, market power and automation: Evidence from an emerging economy," Structural Change and Economic Dynamics, Elsevier, vol. 69(C), pages 37-45.
    5. Philippe Aghion & Céline Antonin & Simon Bunel & Xavier Jaravel, 2020. "What Are the Labor and Product Market Effects of Automation? New Evidence from France," Post-Print hal-03384668, HAL.
    6. Kaltenberg, Mary & Foster-McGregor, Neil, 2020. "The impact of automation on inequality across Europe," MERIT Working Papers 2020-009, United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT).
    7. Li, Rui & Xu, Shoufu & Zhang, Yun, 2023. "Can digital transformation reduce within-firm pay inequality? Evidence from China," Economic Modelling, Elsevier, vol. 129(C).
    8. Azio Barani, 2021. "Innovazione tecnologica e lavoro: automazione, occupazione e impatti socio-economici," QUADERNI DI ECONOMIA DEL LAVORO, FrancoAngeli Editore, vol. 0(114), pages 51-79.
    9. Philippe Aghion & Céline Antonin & Simon Bunel, 2019. "Artificial Intelligence, Growth and Employment: The Role of Policy," Economie et Statistique / Economics and Statistics, Institut National de la Statistique et des Etudes Economiques (INSEE), issue 510-511-5, pages 149-164.
    10. Maciej Cieślukowski & Przemysław Garsztka & Beata Zyznarska-Dworczak, 2022. "The Impact of Robotification on the Financial Situation of Microenterprises: Evidence from the Financial Services Sector in Poland," Risks, MDPI, vol. 10(2), pages 1-20, February.
    11. Cao, Qiang & Xu, Aiyan & Wang, Jiawen & Yu, Wenmei, 2024. "Influence of financial inclusion and industrial robots on the efficiency of China's OFDI: A heterogeneous spatial stochastic frontier analysis," Economic Analysis and Policy, Elsevier, vol. 84(C), pages 996-1009.
    12. Ross, Andrew G. & McGregor, Peter G. & Swales, J Kim, 2024. "Labour market dynamics in the era of technological advancements: The system-wide impacts of labour augmenting technological change," Technology in Society, Elsevier, vol. 77(C).
    13. Rachel Ngai & Orhun Sevinc, 2025. "A Multisector Perspective on Wage Stagnation," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 56, April.
    14. Genz, Sabrina & Schnabel, Claus, 2021. "Digging into the digital divide: Workers' exposure to digitalization and its consequences for individual employment," Discussion Papers 118, Friedrich-Alexander University Erlangen-Nuremberg, Chair of Labour and Regional Economics.
    15. Uwe Thuemmel, 2023. "Optimal Taxation of Robots," Journal of the European Economic Association, European Economic Association, vol. 21(3), pages 1154-1190.
    16. Alonso, Cristian & Berg, Andrew & Kothari, Siddharth & Papageorgiou, Chris & Rehman, Sidra, 2022. "Will the AI revolution cause a great divergence?," Journal of Monetary Economics, Elsevier, vol. 127(C), pages 18-37.
    17. Nakatani, Ryota, 2022. "Optimal fiscal policy in the automated economy," MPRA Paper 115003, University Library of Munich, Germany.
    18. Caselli, Mauro & Fracasso, Andrea & Scicchitano, Sergio & Traverso, Silvio & Tundis, Enrico, 2021. "Stop worrying and love the robot: An activity-based approach to assess the impact of robotization on employment dynamics," GLO Discussion Paper Series 802, Global Labor Organization (GLO).
    19. Growiec, Jakub, . "Gospodarka 4.0? Nowe ujęcie teoretyczne rewolucji cyfrowej i jej konsekwencji dla długookresowego wzrostu," Gospodarka Narodowa-The Polish Journal of Economics, Szkoła Główna Handlowa w Warszawie / SGH Warsaw School of Economics, vol. 2023(4).
    20. Peralta, Catarina & Gil, Pedro Mazeda, 2025. "Automation, education, and population: Dynamic effects in an OLG growth and fertility model," Journal of Economic Behavior & Organization, Elsevier, vol. 234(C).

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    JEL classification:

    • E02 - Macroeconomics and Monetary Economics - - General - - - Institutions and the Macroeconomy
    • E24 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Employment; Unemployment; Wages; Intergenerational Income Distribution; Aggregate Human Capital; Aggregate Labor Productivity
    • M40 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Accounting - - - General
    • L20 - Industrial Organization - - Firm Objectives, Organization, and Behavior - - - General

    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:icb:wpaper:v:5:y:2019:i:1:89-94. 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: Rocsana Bucea-Manea-Tonis (email available below). General contact details of provider: http://icesba.eu .

    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.