The topic of this doctoral dissertation is based on the research of the determinants that influence the successful adoption of business intelligence systems in the tertiary sector small and medium sized enterprises in the Republic of Croatia. The Technology – Organization – Environment theoretical framework was applied to select the determinants that would be considered in the research. The chosen theoretical framework is used for observing the process of embracing technological innovation in the enterprise business through three dimensions: the technological dimension, the organizational dimension, and the environmental dimension. Set to cover all aspects of the company, the above mentioned theoretical framework was chosen to identify the determinants in the context of business intelligence systems acceptance in small and medium sized Croatian enterprises of the tertiary sector. The dissertation consists of two parts: theoretical and empirical part of the research, both of which contributed to: (1) selecting relevant determinants of impact through reviews of the relevant scientific literature presented in the theoretical part and (2) identifying determinants of impact through analyzing the results of the qualitative and quantitative research presented in the theoretical and empirical part of the dissertation. The quantitative survey was conducted with the help of a questionnaire on a sample of small and medium sized enterprises of the tertiary sector in the Republic of Croatia. The sample was selected due to the lack of research in the field of business intelligence systems application in tertiary sector small and medium sized enterprises and the fact that such research had not yet been conducted on the above-mentioned companies in the Republic of Croatia. In addition to the mentioned quantitative research, a qualitative form of research was presented through a case study analysis of a medium-sized enterprise, which carries out its activity within the tertiary sector in the Republic of Croatia.The results of the research show that determinants within the organizational dimension (significant positive influence) have the greatest impact on the business intelligence system acceptance in the tertiary small and medium sized enterprises in the Republic of Croatia. This is followed by the determinants within the environmental dimension (significant positive impact) and, finally, the determinants of the technological dimension (partially significant positive impact) with the least impact on business intelligence systems acceptance in small and medium sized-enterprises in the Republic of Croatia. Given the research results, for small and medium sized enterprises that base their business largely on information and therefore want to embrace business intelligence systems in their business, the most important determinant is competitive pressure in the market that will encourage them to make faster decisions and take timely action to adopt a business intelligence system. Also, organizational readiness plays an important role, according to which small and medium sized enterprises must have sufficient resources within the enterprise beforehand, and that is needed to successfully adopt a business intelligence system. In addition to the two above-mentioned most important determinants, the third determinant belongs to the technological dimension and concerns the compatibility of a business intelligence system establishment with existing business values, practices, and technological infrastructure of small and medium sized enterprises in the Republic of Croatia. There are several limitations of the dissertation, concerning the defined sample, the conducted qualitative research, and the research model. Recommendations for further research are based on the previously mentioned limitations, thus proposing: (1) conducting the same survey on a larger number of enterprises in the Republic of Croatia, (2) conducting the same survey on a sample of large enterprises in the Republic of Croatia, (3) conducting the research on a sample of primary, secondary and quaternary sectors in the Republic of Croatia, (4) conducting longitudinal research, (5) conducting qualitative research with a larger number of enterprises, (6) upgrading the research model by adding the new dependent variable to investigate the potential impact of the successful business intelligence system adoption on achieving better business performance. The importance of the doctoral thesis is manifested through several scientific and practical contributions in which guidelines for a simpler and more successful implementation of the business intelligence system acceptance in business are given, especially for small and medium sized enterprises, as well as for managers, business intelligence system software providers and information technology consultants in the Republic of Croatia. This is very important for small and medium sized enterprises, which are often unfairly neglected when it comes to adopting business intelligence systems, precisely because great attention is paid to large enterprises that are assumed to have greater needs for and interest in implementation and adoption of technological innovations such as a business intelligence system regarding their characteristics and resources (Gudfinnsson and Strand, 2017; Ayoubi and Aljawarneh, 2018; Bhatiasevi and Naglis, 2018). However, small and medium sized enterprises today represent the major drivers of markets development in many national economies (Gudfinnsson and Strand, 2017 according to Airaksinen and et al., 2015; Eurostat, 2020) and as such, they need to embrace technologies such as business intelligence systems whose application is of particular importance in the business of many enterprises (Gudfinnsson and Strand, 2017; Gonzales and Wareham, 2018; Ayoubi and Aljawarneh, 2018). Specifically, technology such as business intelligence systems is of particular importance in the present day since it enables key companies to make better decisions at all levels of governance and respond promptly to turbulent market changes, characterized by an increasing amount of data, more complex technological changes and stronger competition (Bhatiasevi and Naglis, 2018; Gonzales and Wareham, 2018 according to Chugh and Grandhi, 2018).