Projects / Programmes source: ARIS

Decision Support Systems in Digital Business

Research activity

Code Science Field Subfield
5.04.00  Social sciences  Administrative and organisational sciences   
2.06.00  Engineering sciences and technologies  Systems and cybernetics   

Code Science Field
S000  Social sciences   

Code Science Field
5.06  Social Sciences  Political science 
2.02  Engineering and Technology  Electrical engineering, Electronic engineering, Information engineering 
organizational system, management, feedback information, decision-making, decision support, system simulation, sistem dynamics, information systems, sustainable development, digital transformation, digitalization, information technology, business model, innovation
Evaluation (rules)
source: COBISS
Data for the last 5 years (citations for the last 10 years) on April 19, 2024; A3 for period 2018-2022
Data for ARIS tenders ( 04.04.2019 – Programme tender , archive )
Database Linked records Citations Pure citations Average pure citations
WoS  302  3,547  3,231  10.7 
Scopus  402  5,491  4,918  12.23 
Researchers (17)
no. Code Name and surname Research area Role Period No. of publicationsNo. of publications
1.  54752  Blaž Gašperlin  Administrative and organisational sciences  Junior researcher  2020 - 2023  17 
2.  12476  PhD Tomaž Kern  Computer science and informatics  Researcher  2019 - 2024  504 
3.  22598  PhD Mirjana Kljajić Borštnar  Administrative and organisational sciences  Researcher  2019 - 2024  389 
4.  23452  PhD Davorin Kofjač  Computer science and informatics  Researcher  2019 - 2021  351 
5.  07112  PhD Robert Leskovar  Computer science and informatics  Researcher  2019 - 2024  692 
6.  29804  PhD Damjan Maletič  Administrative and organisational sciences  Researcher  2019 - 2024  214 
7.  29803  PhD Matjaž Maletič  Administrative and organisational sciences  Researcher  2019 - 2024  334 
8.  34167  PhD Maja Meško  Administrative and organisational sciences  Researcher  2023 - 2024  584 
9.  16437  PhD Andreja Pucihar  Administrative and organisational sciences  Head  2019 - 2024  430 
10.  23262  PhD Uroš Rajkovič  Computer science and informatics  Researcher  2019 - 2024  485 
11.  01074  PhD Vladislav Rajkovič  Computer science and informatics  Retired researcher  2019 - 2024  2,207 
12.  05488  PhD France Sevšek  Medical sciences  Retired researcher  2019 - 2024  221 
13.  28219  PhD Andrej Starc  Public health (occupational safety)  Researcher  2019 - 2024  201 
14.  15694  PhD Andrej Škraba  Administrative and organisational sciences  Researcher  2019 - 2024  411 
15.  22299  PhD Polona Šprajc  Administrative and organisational sciences  Researcher  2020 - 2024  449 
16.  50633  PhD Doroteja Vidmar  Administrative and organisational sciences  Researcher  2019 - 2023  39 
17.  29915  PhD Anja Žnidaršič  Administrative and organisational sciences  Researcher  2019 - 2024  288 
Organisations (2)
no. Code Research organisation City Registration number No. of publicationsNo. of publications
1.  0586  University of Maribor, Faculty of Organizational Sciences  Kranj  5089638018  10,515 
2.  0382  University of Ljubljana, Faculty of Health Sciences  LJUBLJANA  1627155  14,405 
The research program "Decision Support Systems in Digital Business" is focused to comprehensive study of complex organizational systems management be it manufacturing, service, social, ecological or virtual. The organizational system inevitably incorporates groups of people working together to achieve common goals. These systems are managed by feedback information, real time and anticipative information, which is provided by decision support systems and other information systems (IS). Organizations are confronted with the challenges of digital transformation imposed by modern ICT and rapid changes in the environment. Digital transformation enforces the complete transformation of organizations, its management, business processes, competencies and business models, being in organization or in larger systems. Transformation is also reflected in the digitization of the decision-making process, with a special emphasis on the use of leading edge methods of artificial intelligence. Our assumption is that the organization is capable to use modern technologies and establish quality data sets, which are collected within organization and from external environment, social media and publicly available data sources (e.g. open data). These data are used to achieve higher efficiency, effectiveness, competitiveness, innovativeness, and to follow sustainable development and social responsibility practices. In the business environment, it can be observed that many organizations, especially small and medium-sized enterprises, have significant difficulties with adoption of new technologies, usage of data for decision-making and integration into the digital economy. These challenges are addressed by the continuation of the research program. The foundation of the program is based on the assumption that use of systems and simulation methodologies that support cause-and-effect analysis, are transparent and user-friendly, contribute to significant improvement of the management of complex organizational systems. The research program has strong foundations in our previous research results and include new contexts brought by digitalization and new ICTs. The program focuses on the development of methodologies, tools and models to provide holistic solutions for complex organizational problems. For that purpose, we will use contextually relevant methodologies with emphasis on system approach: soft system methodology, system dynamics, simulation methods, artificial intelligence methods, multi-criteria decision methods, machine learning methods, process management methods, innovation frameworks, total quality management, software engineering and sustainable development.
Significance for science
In the past, the research program was focused to combining of classical simulation models, based on the differential equations, with qualitative methods of expert systems for validation of scenarios aimed at use of e-business technologies. The results showed how the structure and quantity of feedback information, assured by a simulation model, facilitate organizational learning support (on an individual and group level). Furthermore, we provided proof that the system approach with the use of hybrid decision support methods, efficiently supports the decision processes in the business environment.   Fast development of digital technologies and constant changes of the business environment impact organizations and their broader ecosystems, which are no longer merely global, but are migrating more and more into virtual space. The changed dynamic conditions require organizations to respond quickly and with innovative approaches in order to become and remain competitive. There is a need for a comprehensive digital transformation of enterprises, which will enable the creation of new value, changed customer relationships and design of innovative business models. Most organizations are facing problems of providing quality data for decision-making and use of technologies for successful, efficient and sustainable business.   In the new context of digital transformation, we will focus our research on all aspects of business that are related to decision-making support and use of modern digital technologies. These aspects are: data capture, use of appropriate technologies for capturing, storing, managing and organizing data throughout the organization's ecosystem (related organizations, customers, users, public administration), knowledge discovery in data and visualizations, development of appropriate contextual methodologies for solving decision-making problems and management, supporting the learning of the organization and thus the ability to adapt to continuous changes in the environment (business models, customer relationships).   For this purpose we will test the usefulness of new technologies, which also promise new opportunities in decision support, such as big data and data lakes, machine learning methods, blockchain technologies and digital twins. Special attention will be devoted to support of human in the decision-making process to understand the complex processes. This includes visualization and "what-if" analysis of high-performing, so called »black box« machine learning models (i.e. random forests, support vector machines, neural networks). In this way, we will address the problem of conveying misassumptions and beliefs in predictive models and the ability to perceive changes in the environment and to correct the predictive models, and mental models of organization.   There are similar dilemmas regarding the optimization of production and service processes, and the management of multi-project environments. Individual methods and algorithms are well known in scientific literature, however, there is a huge gap in implementation in practice, which requires the integration of partial solutions into a comprehensive methodology.   System approach is particularly important in dealing with large systems, such as agriculture, healthcare, ecology, education, etc. For the design of development policies of such systems, we increasingly use hybrid approaches such as system dynamics, agent modeling and evolutionary computation for modeling the system and scenarios development. These approaches will enable more precise analysis of different policies effects on efficiency of the system.   New technologies and principles of the Internet of Things allow us to run simulations on high-performance computers in almost real time with high-quality visualization on the Internet. Feedback information is thus user friendly, more accurate, and accessible in close-to-real-time. Principles of Internet of Things and machine learning methods will be used to d
Significance for the country
The research program is characterized by the fact that research is focused on solving real complex problems for which solutions do not yet exist. In the process of research we actively involve users (companies, public administration organizations and end users) in order to validate solutions, and accelerate the implementation of the technologies, methods and tools that we are developing.   We expect that the methods and tools that we develop as part of the research on business model innovation will be useful for enterprises and other organizations that must adapt to the constant changes in the environment. The tools will be freely available on the web portal, however, it is unlikely that the SMEs will use them independently, therefore we plan to collaborate with the business support environment, and conduct workshops for enterprises and students. The aim is primarily to reach SMEs that are lagging behind in implementation of new technologies and business model innovation.   We will also continue with researching the opportunities for the introduction of new technologies and contribute to the development of recommendations, appropriate policies and supportive environment for the transition to the digital economy and society. In this regard, we will carry out series of workshops for raising awareness about the opportunities of using cloud based high-performance computing technology, big data, and business model innovation in cooperation with the horizontal ICT network, SRIP Smart cities and communities.   The results of group learning with the introduction of continuous feedback information, assured by different models, will be implemented in other areas and business ecosystems, thus contributing to concrete problem solving in practice and a better understanding and development of an effective information system to support learning and decision-making. Methods and optimization algorithms, validated on test data and on real business problems, will be used for solving new business problems, for example in production, steel industry, and agriculture. We expect that validated methods will contribute to greater prevalence and acceptance of these technologies and solutions in practice. Use cases will be prepared on the basis of implementation analysis to inform other organizations about the possibilities offered by the proposed solutions.   The significance in the aspects of socio-economic development is also in the exploration of the opportunities offered by cyber-physical systems and the Internet of Things (voice recognition in the cloud, for example, management of wheelchairs) aimed at solving problems and innovating processes in various fields (healthcare, education, agriculture, production and service organizations). Implementation of novel technologies are usually delayed in the large social systems. It is therefore important that we test and showcase the opportunities for the introduction of new technologies within secure experimental environments.   An important field of research is focused on innovating and sustainable development of business models, and managing all the resources of the organization, while taking care of the quality, efficiency and effectiveness of organizations. Findings in the field solve important economic issues, and in a broader context, they also contribute to the sustainable development of society.   We expect the software, developed in the framework of the program, can be used in partner enterprises as well as in the public administration for management, control and reorganization of business processes.  In the framework of the research we also plan international collaboration. Research results will be useful for practice and we believe that this will contribute to a more efficient transition to the digital economy.
Most important scientific results Interim report
Most important socioeconomically and culturally relevant results Interim report
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