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Author Guidelines

Authors are required to use their institutional e-mail addresses (whenever possible) while submitting the paper and for all related communication with journal editors.

 

Receiving papers

The editorial office of the journal "Economic Research-Ekonomska istraživanja" accepts only unpublished papers. Papers are submitted in digital form in English in a word document (doc or docx), pages of A4 format. The editorial board reserves the right to editorially adapt the work to the magazine's propositions and English language standards.

Font

Paper should be written in Times New Roman, size 12, spacing 1 to 1,5. The text should be justified.

Page numbering

Pages of articles should be numbered with Arabic numbers. The first page of the paper is numbered, but the page number is not displayed.

Language

All articles should be written in English, and papers should be proofread before submission.

The first page of the work

The first page of the paper must contain:

1. Title of the paper

2. Name and surname of the author(s), institutional address, and e-mail for at least the corresponding author.

3. Abstract

4. Keywords

5. JEL classification

In the anonymous version of the paper, all authors' information should be excluded

 

Change of address

If one of the paper's authors changes his address, the journal's editorial office must be informed.

Scope of work

A typical article should include up to 8.000 words (including tables, references, figures, endnotes, and abstracts)

Abstract

The abstract of the work should be on the first page under the title of the work. The abstract of the work should contain up to 300 words. The abstract should include the purpose and goals of the work, methods, structure of the work, basic results, and a conclusion on the possible application of the results.

Keywords

Keywords are listed on the first page of the paper, below the abstract. They should include no more than six (6) words.

Titles and subtitles

All titles and subtitles must be numbered with Arabic numerals. The introduction is the first title, and the conclusion is the last title.

Tables and figures

Tables and figures representations are entered in the intended place in the work, and pictures must be made in black and white on separate sheets. If tables and graphics are submitted on separate sheets, then it is necessary to mark the place in the paper where they appear.

Tables and figures must be numbered with Arabic numerals and have a short title and source. All tables and figures need to be referenced in paper text.

Mathematical expressions

Equations must be written in italics. In addition, they must be numbered with Arabic numerals in brackets pr. (1), which should be on the right side of the page in line with Eq.

Footnotes

Use footnotes only to clarify the text while the citation is given in the text.

References

The APA 7 Style should be used for citations and references.

Notes

Notes are marked with Arabic numerals in the text, and are attached at the end of the text under the heading "Notes" on a separate sheet with the name and surname of the author and the title of the paper.

Third-party material

If third-party material is used in the article, permission to use it should be submitted.

Disclosure Statement

Include this section if there is some conflict of interest significant for submission.

Change of authorship

If the authorship of a paper changes during the review process, the authorship change form should be submitted with the revised paper.

The paper templete is avaialble here.

 

Submission Preparation Checklist

All submissions must meet the following requirements.

  • All author(s) of the text have been included.
  • The submission has not been previously published, nor is in another journal for consideration (or an explanation has been provided in Comments to the Editor).
  • The anonymous version of the text has been submitted and it does not contain any author(s) details.
  • The submission file is in Microsoft Word.
  • Where available, URLs for the references have been provided.
  • The text adheres to the requirements outlined in the Author Guidelines.

Articles for regulat issue

Section default policy

From Automation to Augmentation: Strategic Gaps in Managing AI and Economic Growth

From Automation to Augmentation:  Strategic Gaps in Managing AI and Economic Growth

 

Guest Editors:

Samuel Ribeiro-Navarrete (Ph.D), VIZJA University (Poland) and Lithuanian Centre for Social Sciences (Lithuania). Email: samuelribeironavarrete@gmail.com

Klaus Ulrich, ESIC Business & Marketing School (Spain) and ESIC University (Spain). Email: Klaus.u.b@gmail.com

 

Background and Motivation

Artificial Intelligence (AI) is changing the global economic environment. AI has emerged as one of the most disruptive and transformative technologies of recent times, revolutionising entire industries, organisations and economies across the globe (Climent et al., 2024; Malik, 2024;  Mensikovs, 2024). This technology enables companies, for example, to increase efficiency, optimise costs and provide management tools with great potential to reconfigure competitive environments, catalyse innovation and redefine the relationship and collaboration between machines and humans (Dissanayake et al., 2024; Dhaheri et al., 2024; Faruqui et al., 2025). AI is an unprecedented opportunity for business transformation, entrepreneurial innovation and sustainable economic growth (Al Halbusi, 2025; Fang et al., 2024; Gurjar et al., 2024; Lanzalonga, 2024). However, its integration into business strategy, entrepreneurial ventures and innovative ecosystems reveals significant gaps in understanding strategic management, economic impact and social implications (Razaei, 2025; Vesely & Amaris, 2025). In this sense, potential improvements in efficiency, fostering innovation and the democratisation of entrepreneurship are being adopted in a heterogeneous and uneven manner, with their potential remaining subordinate to business culture, ethics and the challenges of measuring them (Kleinrichert, 2024; Reis et al., 2025; Tlili, 2024).

This special issue seeks to address these gaps, calling on researchers to conduct rigorous, interdisciplinary research that explores how AI can be strategically managed to drive sustainable economic growth and social value (Alessandro et al., 2024; Carayannis et al., 2025). Furthermore, it seeks to advance both theoretically and empirically in the interrelation of technology and organisational dynamics, entrepreneurial ecosystems, and macroeconomic outcomes (Roundy et al., 2024; Roy et al., 2025; Tabata et al., 2025). The special issue seeks to address and understand these issues by contributing to the understanding of how AI can be applied beyond automation to enhance human skills, the capacity to innovate, and reshape economic systems.

Topics and Research Questions

This special issue aims to contribute to the theoretical and empirical advancement of the role of AI in strategic business management, entrepreneurship, innovation, and economic growth. In this regard, three research objectives are sought to guide the studies within the framework of this call for papers. First, an analysis of the impact of AI on organisational transformation and the construction of competitive advantages, analysing the integration of technology-derived systems and the transformation of business structures, cultures and processes, and how these can be transformed into new sources of sustainable competitive advantages adapted to the emerging new economy. Secondly, research on the role of AI in identifying new business opportunities and business innovation in mature companies and start-ups, emphasising the tools offered by this technology when it comes to detecting business opportunities, predicting trends, developing new innovative business models, managing data in accordance with regulations and addressing privacy challenges. Finally, measuring the impact of AI on innovation and economic growth, addressing potential barriers to adoption and productivity gains, while also considering its impact on the labour market and the challenges arising from its transformation and the development of novel metrics to measure its value in the industrial and services sectors.

We invite researchers to contribute to the following subtopics, including but not limited to:

  1. The Strategic Management of AI
  • Organizational transformation: How does AI adoption require changes to structures, culture, and processes?
  • Human-AI collaboration in strategic decision-making: Best practices, cognitive biases, and evolving managerial roles.
  • AI and competitive advantage: Beyond efficiency—new sources of sustained value creation.
  • Leadership in the age of AI: Skills, roles, and the challenges of guiding AI-driven change.
  1. Entrepreneurship and the AI-Driven Startup
  • AI for opportunity recognition: Using predictive analytics and generative models to discover unmet needs.
  • AI-driven business model innovation: Redefining value creation, delivery, and capture.
  • Challenges for AI-centric startups: Talent acquisition, data governance, and regulation.
  • Democratization of entrepreneurship: Lowering barriers to entry through accessible AI tools.
  1. Innovation and AI
  • AI as a catalyst for innovation: Accelerating ideation, R&D, and commercialization.
  • The future of R&D: AI in drug discovery, materials science, and scientific breakthroughs.
  • Ethical and social implications of AI-driven innovation: Inclusivity, equity, and responsible design.
  • Intellectual property and creativity in the AI era: Legal and managerial challenges.
  1. The Productivity Paradox of AI: Measuring Economic Impact
  • Measurement gaps: Capturing AI’s impact on services, customization, and welfare beyond GDP.
  • Diffusion lag: Why adoption is uneven and how this shapes aggregate productivity.
  • Capital-labor substitution: Modeling trade-offs between efficiency gains and job displacement.
  • AI as a general-purpose technology: Complementary investments and new economic models.

We therefore expect researchers to produce work that provides novel insights, rigorous academic methodologies, and valuable academic, managerial, and regulatory applications that enable the advancement of technology and its democratised implementation in order to achieve greater economic and social well-being.

Submission dates:

Submissions Open: October 1st 2025.

Submission Deadline: September 30th 2026.

 

References

Alessandro, G., Federica, D., Cristina, B., & Luca, A. (2024). Artificial Intelligence in the Eyes of Society: Assessing Social Risk and Social Value Perception in a Novel Classification. Human Behavior and Emerging Technologies, 2024, 7008056.

Al Halbusi, Popa, S., Sota-Acosta, P., & Alshallaqi, M. (2025). The nexus of managerial and technical AI knowledge, disruptive innovation and the circular economy: The role of organizational change capability and financial resilience. Technology in Society, 82, 102937.

Carayannis, E.G., Dumitrescu, R., Falkowski, T., Papamichail, G., & Zota, N.R. (2025). Enhancing SME resilience through artificial intelligence and strategic foresight: A framework for sustainable competitiveness. Technology in Society, 81, 102835.

Climent, R.C., Haftor, D.M., & Staniewski, M.W. (2024). AI-enabled business models for competitive advantage. Journal of Innovation Knowledge, 9(3), 100532.

Dissanayake, H., Manta, O., Iddagoda, A., & Palazzo, M. (2024). AI applications in business: Trends and insights using bibliometric analysis. International Journal Of Management Education, 22(3), 101075.

Dhaheri, M.H.A., Ahmad, S.Z., & Papastathopoulos, A. (2024). Do environmental turbulence, dynamic capabilities, and artificial intelligence force SMEs to be innovative? Journal of Innovation Knowledge, 9(3), 100528.

Fang, C.Y., Li, H.Y., & Wang, Y.T. (2024). Unleashing the potential: the impact of AI on corporate entrepreneurship with top management involvement. International Journal of Organizational Analysis, https://doi.org/10.1108/IJOA-03-2024-4364.

Faruqi, N., Raju, N.V.D.S.S.V.P., Sivakumar, S., Patel, N., Bhaskaran, S.V., Khanam, S., & Bhuiyan, T. (2025). Gen-Optimizer: A Generative AI Framework for Strategic Business Cost Optimization. Computers, 14(2), 59.

Gurjar, K., Jangra, A., Baber, H., Islam, M., & Sheikh, S.A. (2024). An Analytical Review on the Impact of Artificial Intelligence on the Business Industry: Applications, Trends, and Challenges. IEEE Engineering Management Review, 52(2), 84-102.

Kleinrichert, D. (2024). Empathy: an ethical consideration of AI & others in the workplace. AI & Society, 39(6), 2743-2757.

Lanzalonga, F. Marseglia, R., Irace, A., & Biancone, P.P. (2024). The application of artificial intelligence in waste management: understanding the potential of data-driven approaches for the circular economy paradigm. Management Decision, https://doi.org/10.1108/MD-10-2023-1733.

Malik, S., Muhammad, K., & Waheed, Y. (2024). Artificial intelligence and industrial applications-A revolution in modern industries. Ain Shams Engineering Journal, 15(9), 102886.

Mensikovs, V., Simakhova, A., & Sipilova, V. (2024). Harnessing Artificial Intelligence for Socio-Economic Development. European Journal of Sustainable Development, 13(3), 569-590.

Rzaei, M. (2025). Artificial intelligence in knowledge management: Identifying and addressing the key implementation challenges. Technological Forecasting and Social Change, 217, 124183.

Reis, M.I., Goncalves, J.N.C., Cortez, P., Carvalho, M.S., & Fernandes, J.M. (2025). A context-aware decision support system for selecting explainable artificial intelligence methods in business organizations. Computers in Industry, 165, 104233.

Roundy, P.T., & Asllani, A. (2024). Understanding AI innovation contexts: a review and content analysis of artificial intelligence and entrepreneurial ecosystems research. Industrial Management & Data Systems, 124(7), 2333-2363.

Roy, S.K., Dey, B.L., Brown, D.M., Abid, A., Apostolidis, C., Christofi, M., & Tarba, S. (2025). Business Model Innovation through AI Adaptation: The Role of Strategic Human Resources Management. British Journal of Management, 36(2), 546-559.

Tabata, M., Wildermuth, C., Bottomley, K., & Jenkins, D. (2025). Generative AI Integration in Leadership Practice: Foundations, Challenges, and Opportunities. Journal of Leadership Studies, 18(4), 41-54.

Tlili, A., Denden., M., Abed, M, & Huang, R.H. (2024). Artificial intelligence ethics in services: are we paying attention to that?! Service Industries Journal, 44, 15-16, 1093-1116.

Vesely, S. & Amaris, G. (2025). AI-driven income inequality and preferences for redistribution. Economic Analysis and Policy, 87, 642-648.

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