https://rfos.fon.bg.ac.rs/handle/123456789/1 Fri, 11 Sep 2026 10:46:09 GMT 2026-09-11T10:46:09Z https://rfos.fon.bg.ac.rs/handle/123456789/3290 Title: Innovation Portfolio Under Constraints: Strategic Bucket Design In A Process Industry Authors: Borozan, Tea; Stošić, Biljana; Milutinović, Radul; Mihić, Marko Abstract: In capital-intensive process industries, where innovation is strongly linked to operational continuity, regulatory requirements, and long-term asset investments, managing innovation projects portfolios can be especially difficult. The design and adaptation of strategic buckets to specific industrial contexts have received little attention in prior research, despite their widespread recognition as a helpful tool for project portfolio management. This study fills this gap by investigating how strategic buckets are created to manage innovation projects portfolio in the paper industry. This study employs a qualitative case study methodology, utilizing semistructured interviews and document analysis. It draws on innovation portfolio management theory and an established conceptual framework for strategic bucket design. Key dimensions and related factors are identified within the proposed framework. Furthermore, the study demonstrates the application of strategic buckets in the case company. The findings contribute to a more context-sensitive understanding of strategic bucket design and provide practical insights for managing innovation project portfolios in capital-intensive process industries. Wed, 03 Jun 2026 00:00:00 GMT https://rfos.fon.bg.ac.rs/handle/123456789/3290 2026-06-03T00:00:00Z https://rfos.fon.bg.ac.rs/handle/123456789/3289 Title: The Impact of Low-Code/No-Code Platforms on Organizational Innovativeness: A Generation Z Perspective Authors: Raković, Lazar; Đorđević-Milutinović, Lena; Milutinović, Radul; Lula, Pawel Abstract: Low Code/No Code (LCNC) platforms enable end users without formal software development knowledge to independently create applications and automate business processes. This approach, known as end-user development and citizen development, contributes to the democratization of software development and creates opportunities for decentralized innovation within organizations. The ongoing development and increasing adoption of artificial intelligence-based tools further expand the functionality of LCNC platforms, making them more accessible, intuitive, and efficient for developing digital solutions. Given that Generation Z represents future drivers of digital transformation and potential citizen developers, it is important to understand their perceptions of the innovation potential of these platforms. The aim of this paper is to examine the perceptions of Generation Z regarding the impact of LCNC platforms on organizational innovativeness. The study is based on empirical research conducted through a survey administered to a sample of Generation Z respondents. The analysis focuses on their views regarding the contribution of LCNC platforms to business process improvement, the development of new products and services, and the enhancement of organizational innovation capabilities. The findings contribute to understanding the readiness of the future workforce to adopt LCNC technologies as tools for innovation and may serve as a basis for shaping strategies related to digital skills development and the implementation of these platforms in organizational contexts. Fri, 12 Jun 2026 00:00:00 GMT https://rfos.fon.bg.ac.rs/handle/123456789/3289 2026-06-12T00:00:00Z https://rfos.fon.bg.ac.rs/handle/123456789/3288 Title: Mapping Innovation Domains Using Topic Modeling Authors: Dziura, Marek; Lula, Paweł; Milutinović, Radul; Rojek, Tomasz; Vuković, Vuk Abstract: Innovation plays a crucial role in driving economic growth and development, improving competitiveness, and creating new opportunities for individuals and businesses. It can lead to higher living standards and improved quality of life by addressing some of the world's most pressing challenges, such as climate change, health crises, and poverty. In recent years, artificial intelligence (AI) has emerged as one of the most influential forces shaping everyday life. It is also revolutionizing the innovation process by supporting R&D activities, automating complex tasks and enabling data analysis at speeds far exceeding human capabilities. The adoption of AI technologies accelerates the development of new products and business models while fundamentally transforming decision-making processes. Consequently, companies are required to restructure their innovation processes in response to rapid technological advancement and evolving workforce roles. AI is widely perceived as a source of unlimited possibilities, and its increasing adoption is strongly reflected in the expanding body of scholarly work. The number of papers addressing innovation and AI has grown significantly in recent years. To illustrate, assess and map research at the intersection of AI and innovation, this study analyzes published work indexed in the Elsevier Scopus databases. The research examines thousands of publications related to innovation by analyzing titles, abstracts, and keywords, employing BERTopic modeling and bipartite graph analysis to identify emerging patterns. The findings reveal five distinct innovation technology domains and systematically map their relationships with various AI methods. The results indicate that AI-related innovations are not isolated phenomena but are widely integrated across multiple domains, highlighting the importance of crossdepartmental collaboration to maximize system-wide benefits. Mon, 18 May 2026 00:00:00 GMT https://rfos.fon.bg.ac.rs/handle/123456789/3288 2026-05-18T00:00:00Z https://rfos.fon.bg.ac.rs/handle/123456789/3287 Title: THE USE OF GENERATIVE AI TOOLS BY LOGISTICS PROFESSIONALS IN GERMANY, CROATIA, AND SERBIA Authors: Cvetić, Biljana; Bernhard Axmann; Vanina Macowski Durski Silva; Maja Trstenjak Abstract: Тhe aim of this study is to examine the use of general generative artificial intelligence (AI) tools and generative AI office tools among logistics professionals in Germany, Croatia, and Serbia. To that end, an exploratory analysis about available generative AI tools and their use in logistics is conducted. Then, an empirical study is performed to investigate generative AI tool utilization among German, Croatian, and Serbian logistics professionals. This study provides new insights into the profiles of logistics professionals from these three countries, as well as their utilization and satisfaction with general generative AI tools and generative AI office tools. Thu, 01 Jan 2026 00:00:00 GMT https://rfos.fon.bg.ac.rs/handle/123456789/3287 2026-01-01T00:00:00Z