IDEAS home Printed from https://ideas.repec.org/a/aes/jetimm/v1y2022i1p126-132.html
   My bibliography  Save this article

Impact of Digitization and Big Data on Romanian Companies - a Qualitative Research

Author

Listed:
  • Horia Mihalcescu

    (The Bucharest University of Economic Studies)

  • Ana-Maria Dumitrache (Bajan)

    (The Bucharest University of Economic Studies)

  • Gheorghe Orzan

    (The Bucharest University of Economic Studies)

Abstract

Our general investigation is about the degree of understanding of the new economy, "digital economy", in Romanian companies, with a narrow focus on understanding the needs and uses of Big Data technology. We used a structured interview with 30 owners, CEO, IT managers, and Marketing Managers from Romanian companies and applied descriptive statistics on all data collected and content analysis on the open answers. The key findings are that Romanian managers are half aware that the digital economy will dramatically reshape business models and increase the competition. However, around one-third of them don't understand the basic concept of digitalization, digital transformation, and the need for digitalization. The most important department the Romanian managers think they should digitalize is marketing, but some big businesses don't think and want digitalization. One of the main obstacles to the digitalization of Romanian companies is the lack of human resources with proven expertise in the field. In order of Industry 4.0 components, only a few implements and use CRM, ERP, or another form of integration with customers or suppliers. Big Data is poorly known and used, but where it is used, it is a strong competitive advantage. Romanian managers do not understand how public institutions are digitalized to help the private initiative. They expect the public institutions to take the initiative to start digitalization in all society, including companies. The implications of our findings are extremely different from other public studies that suggest Romanian companies are strong in digital transformation. Our study shows the need for further investigation, if not measures to increase support for the digitalization of Romanian companies to remain/become competitive. Our findings are that only a few managers/companies are aware of the new digital economy with increased competition, and the initiative of digitalization, even in the private sector, should be from public institutions.

Suggested Citation

  • Horia Mihalcescu & Ana-Maria Dumitrache (Bajan) & Gheorghe Orzan, 2022. "Impact of Digitization and Big Data on Romanian Companies - a Qualitative Research," Journal of Emerging Trends in Marketing and Management, The Bucharest University of Economic Studies, vol. 1(1), pages 126-132, November.
    • Handle: RePEc:aes:jetimm:v:1:y:2022:i:1:p:126-132
    as

    Download full text from publisher

    File URL: http://www.etimm.ase.ro/RePEc/aes/jetimm/2022/ETIMM_V01_2022_30.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Luigi M. De Luca & Dennis Herhausen & Gabriele Troilo & Andrea Rossi, 2021. "How and when do big data investments pay off? The role of marketing affordances and service innovation," Journal of the Academy of Marketing Science, Springer, vol. 49(4), pages 790-810, July.
    2. David-Florin Ciocodeică & Raluca-Giorgiana (Popa) Chivu & Ionuț-Claudiu Popa & Horia Mihălcescu & Gheorghe Orzan & Ana-Maria (Dumitrache) Băjan, 2022. "The Degree of Adoption of Business Intelligence in Romanian Companies—The Case of Sentiment Analysis as a Marketing Analytical Tool," Sustainability, MDPI, vol. 14(12), pages 1-20, June.
    3. Mikalef, Patrick & Boura, Maria & Lekakos, George & Krogstie, John, 2019. "Big data analytics and firm performance: Findings from a mixed-method approach," Journal of Business Research, Elsevier, vol. 98(C), pages 261-276.
    4. Amado, Alexandra & Cortez, Paulo & Rita, Paulo & Moro, Sérgio, 2018. "Research Trends On Big Data In Marketing: A Text Mining And Topic Modeling Based Literature Analysis," European Research on Management and Business Economics (ERMBE), Academia Europea de Dirección y Economía de la Empresa (AEDEM), vol. 24(1), pages 1-7.
    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. Mariani, Marcello M. & Fosso Wamba, Samuel, 2020. "Exploring how consumer goods companies innovate in the digital age: The role of big data analytics companies," Journal of Business Research, Elsevier, vol. 121(C), pages 338-352.
    2. Huynh, Minh-Tay & Nippa, Michael & Aichner, Thomas, 2023. "Big data analytics capabilities: Patchwork or progress? A systematic review of the status quo and implications for future research," Technological Forecasting and Social Change, Elsevier, vol. 197(C).
    3. Ahmad Ibrahim Aljumah & Mohammed T. Nuseir & Md. Mahmudul Alam, 2021. "Traditional marketing analytics, big data analytics and big data system quality and the success of new product development," Post-Print hal-03538161, HAL.
    4. Shet, Sateesh.V. & Poddar, Tanuj & Wamba Samuel, Fosso & Dwivedi, Yogesh K., 2021. "Examining the determinants of successful adoption of data analytics in human resource management – A framework for implications," Journal of Business Research, Elsevier, vol. 131(C), pages 311-326.
    5. Herhausen, Dennis & Bernritter, Stefan F. & Ngai, Eric W.T. & Kumar, Ajay & Delen, Dursun, 2024. "Machine learning in marketing: Recent progress and future research directions," Journal of Business Research, Elsevier, vol. 170(C).
    6. Lutfi, Abdalwali & Alrawad, Mahmaod & Alsyouf, Adi & Almaiah, Mohammed Amin & Al-Khasawneh, Ahmad & Al-Khasawneh, Akif Lutfi & Alshira'h, Ahmad Farhan & Alshirah, Malek Hamed & Saad, Mohamed & Ibrahim, 2023. "Drivers and impact of big data analytic adoption in the retail industry: A quantitative investigation applying structural equation modeling," Journal of Retailing and Consumer Services, Elsevier, vol. 70(C).
    7. Keeheon Lee, 2021. "A Systematic Review on Social Sustainability of Artificial Intelligence in Product Design," Sustainability, MDPI, vol. 13(5), pages 1-29, March.
    8. Luther Yuong Qai Chong & Thien Sang Lim, 2022. "Pull and Push Factors of Data Analytics Adoption and Its Mediating Role on Operational Performance," Sustainability, MDPI, vol. 14(12), pages 1-19, June.
    9. Junlan Tan & Yasir Ahmed Solangi, 2024. "Assessing impact investing for green infrastructure development in low-carbon transition and sustainable development in China," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 26(10), pages 25257-25280, October.
    10. Pan, Qiaohong & Luo, Wenping & Fu, Yi, 2022. "A csQCA study of value creation in logistics collaboration by big data: A perspective from companies in China," Technology in Society, Elsevier, vol. 71(C).
    11. Meadows, Maureen & Merendino, Alessandro & Dibb, Sally & Garcia-Perez, Alexeis & Hinton, Matthew & Papagiannidis, Savvas & Pappas, Ilias & Wang, Huamao, 2022. "Tension in the data environment: How organisations can meet the challenge," Technological Forecasting and Social Change, Elsevier, vol. 175(C).
    12. Raed A.I. Abueed & Mehmet Aga, 2019. "Sustainable Knowledge Creation and Corporate Outcomes: Does Corporate Data Governance Matter?," Sustainability, MDPI, vol. 11(20), pages 1-15, October.
    13. Russell Tatenda Munodawafa & Satirenjit Kaur Johl, 2019. "Big Data Analytics Capabilities and Eco-Innovation: A Study of Energy Companies," Sustainability, MDPI, vol. 11(15), pages 1-21, August.
    14. Md Ahsan Uddin Murad & Dilek Cetindamar & Subrata Chakraborty, 2022. "Identifying the Key Big Data Analytics Capabilities in Bangladesh’s Healthcare Sector," Sustainability, MDPI, vol. 14(12), pages 1-21, June.
    15. Kim, Jaemin & Dibrell, Clay & Kraft, Ellen & Marshall, David, 2021. "Data analytics and performance: The moderating role of intuition-based HR management in major league baseball," Journal of Business Research, Elsevier, vol. 122(C), pages 204-216.
    16. G. Tomas M. Hult & Forrest V. Morgeson III & Udit Sharma & Claes Fornell, 2022. "Customer satisfaction and international business: A multidisciplinary review and avenues for research," Journal of International Business Studies, Palgrave Macmillan;Academy of International Business, vol. 53(8), pages 1695-1733, October.
    17. Imran Bashir Dar & Muhammad Bashir Khan & Abdul Zahid Khan & Bahaudin G. Mujtaba, 2021. "A qualitative analysis of the marketing analytics literature: where would ethical issues and legality rank?," Journal of Marketing Analytics, Palgrave Macmillan, vol. 9(3), pages 242-261, September.
    18. Philp, Matthew & Jacobson, Jenna & Pancer, Ethan, 2022. "Predicting social media engagement with computer vision: An examination of food marketing on Instagram," Journal of Business Research, Elsevier, vol. 149(C), pages 736-747.
    19. Moro, Sérgio & Lopes, Rui J. & Esmerado, Joaquim & Botelho, Miguel, 2020. "Service quality in airport hotel chains through the lens of online reviewers," Journal of Retailing and Consumer Services, Elsevier, vol. 56(C).
    20. Cabrera-Sánchez, Juan-Pedro & Villarejo-Ramos, Ángel F., 2019. "Fatores que afetam a adoção de análises de Big Data em empresas," RAE - Revista de Administração de Empresas, FGV-EAESP Escola de Administração de Empresas de São Paulo (Brazil), vol. 59(6), December.

    More about this item

    Keywords

    Digitalization; digital transformation; Big Data; Romanian companies; Public Sector.;
    All these keywords.

    JEL classification:

    • M31 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Marketing and Advertising - - - Marketing

    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:aes:jetimm:v:1:y:2022:i:1:p:126-132. 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: Lucian Onisor (email available below). General contact details of provider: https://edirc.repec.org/data/aseeero.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.