"Scientific research" Almanac

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  PRODUCT INNOVATION AND SUSTAINABLE DEVELOPMENT OF EUROPEAN SMALL AND MEDIUM-SIZED ENTERPRISES IN THE INDUSTRY SECTOR

  Product innovations of European small and medium-sized enterprises (SMEs) in the industrial sector are one of the key instruments of sustainable economic development. The aim of the study is, based on the interpretation of theoretical views, to develop and validate a model for studying the relationship between product innovations and the ... Product innovations of European small and medium-sized enterprises (SMEs) in the industrial sector are one of the key instruments of sustainable economic development. The aim of the study is, based on the interpretation of theoretical views, to develop and validate a model for studying the relationship between product innovations and the sustainable development of the business activity of SMEs in the industrial sector of the European Union countries and on this basis to formulate conclusions and generalizations. To achieve the goal, research tasks have been defined: study of the nature of product innovations and their contribution to the sustainable development of SMEs; development of a Model for studying the relationship between product innovations and the sustainable development of the business activity of European SMEs in the industrial sector; validation of the proposed model; formulation of more significant conclusions and generalizations. The research thesis defended in the paper is that there is a natural relationship between the introduced product innovations and the sustainable development of the business activities of European SMEs in the industrial sector, explaining to a certain extent part of the emerging similarities and differences between the highlighted enterprises. The proposed study is based on collected data, published by Eurostat for the period 2012-2022. The processing of empirical data is carried out using the IBM SPSS Statistics software product and the Excel program. The methods of descriptive and comparative analysis, linear regression and correlation methods, as well as synthesis and generalization are used. The research utility of the obtained results is in deriving more important regularities in the product innovation and sustainable development of the business activity of European industrial enterprises of small and medium size.

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  APPROACHES AND MECHANISMS FOR IMPLEMENTING OPEN INNOVATION IN THE PUBLIC SECTOR IN BULGARIA

  The application of the concept of open innovation in the public sector is a relatively new but rapidly developing field of research and practice. The public sector in Bulgaria continues to exhibit low innovation activity and limited adaptability to change, despite the growing importance of open innovation. In this regard, the main goal of the ... The application of the concept of open innovation in the public sector is a relatively new but rapidly developing field of research and practice. The public sector in Bulgaria continues to exhibit low innovation activity and limited adaptability to change, despite the growing importance of open innovation. In this regard, the main goal of the study is to explore the approaches and mechanisms for implementing open innovation in the public sector in Bulgaria based on theoretical analysis and empirical research on public sector attitudes toward interaction with stakeholders. The following tasks have been set: 1. Analysis of the theoretical framework for open innovation and models for its implementation in the public sector; 2. Examination of interactions between the public sector, citizens, businesses, and among public sector entities; 3. Development of a model for implementing open innovation in the public sector in Bulgaria. The research thesis is based on the assertion that the implementation of open innovation, with a focus on users of public services in public sector organisations, would have a beneficial impact on their performance, especially in cases where additional expertise, knowledge, and skills are needed beyond the capacity of the organisation. The results of the study are: 1. the factors for the emergence of open innovation are analysed; 2. different models for the implementation of open innovation in the public sector are examined; 3. the external and internal interactions of the public sector in the creation of open innovation are explored, and appropriate steps for their adoption and expansion are proposed; 4. a model for the implementation of open innovation in the public sector in Bulgaria is developed.

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  FRAMEWORK FOR PREDICTIVE AND CAUSAL MODELING OF MULTI-TOUCH ATTRIBUTION IN A DIGITAL ENVIRONMENT

  In the increasingly complex ecosystem of digital marketing, determining the incremental contribution of different marketing channels to consumer conversion remains a fundamentally unresolved challenge. The subject of this study is the process of multi-touch attribution in a digital environment, and its object is the predictive and causal approach ... In the increasingly complex ecosystem of digital marketing, determining the incremental contribution of different marketing channels to consumer conversion remains a fundamentally unresolved challenge. The subject of this study is the process of multi-touch attribution in a digital environment, and its object is the predictive and causal approach to assessing the contribution of channels. The main goal is to develop a comprehensive framework for multi-touch attribution that integrates probabilistic modeling (Markov chains), machine learning (XGBoost), and causal methods (Shapley values, counterfactual analysis) to provide a more accurate and interpretable assessment of channel influence. As part of the study, a hybrid model system was built and tested on real user journey data, and its effectiveness was compared to that of traditional heuristic models. The results show significant differences from heuristic approaches and highlight the superior predictive accuracy of machine learning-based methods (overall accuracy = 0.984; AUC = 0.846), while the application of explainable AI techniques increases the transparency of attribution. Theoretically, the study combines causal models, reinforcement learning, and interpretability in attribution modeling, linking econometric theory with data analysis, and in management terms, it offers a reproducible framework for resource optimization and data-driven decision-making.