The paper aims to improve the methodology of measuring efficiency of Latvian banks. Efficiency scores were calculated with application of non-parametric frontier technique Data Envelopment Analysis (DEA). Input-oriented DEA model under Variable Returns to Scale (VRS) assumption was used. Potential model variables were selected based on the intermediation and profitability approach. Fourteen alternative models with different inputs-outputs combinations were developed for the research purposes. To substantiate the variables selection for DEA model the received data was processed, using such methods, as correlation analysis, linear regression analysis, analysis of mean values, and two-samples Kolmogorov-Smirnov test. The research results assisted the authors in providing general recommendations about the variables selection for DEA application in the Latvian banking sector. The present research contributes to the existing analytical data on bank performance in Latvia. The empirical findings provide a background for further studies, in particular, the efficiency of Latvian banks could be analysed in the extended time period.

Industry 4.0 describes a phenomenon which augments business models and also communication channels in commercial enterprises. This paper analyses scientific publications related to the business model changes driven by Industry 4.0, and also digital internal communication channels used to reduce risks in the process. The paper is based upon a systematic review of scientific publications and evaluation by experts. The research revealed a gap between internal communication through digital channels and the change process in Industry 4.0-driven business models. Each channel has its mission and contributes to reducing risk during the change process. Since there is no universal digital channel for internal communication, different digital communication channels are efficient at different stages of change. The paper makes recommendations for enterprises, related to the effectiveness of digital communication channels during the business model transformation. It further contributes to existing knowledge by expanding the change process model and aligning the change process with features of digital communication channels. The research focused on the manufacturing sector, exploring digital communication channels used to reduce risk during the change process, which is a limitation of this study, along with assumption of a basic level of digital competences in the enterprise.

The financial services sector, perhaps more than any other, is being disrupted by advances in technology. The purpose of this study is to provide comprehensive data and evidence on value of the FinTech innovation event. First, a text-based filtering method for identifying FinTech patent applications is provided. Using machine learning applications, innovations are classified into major technology groups. The methodology for valuation of FinTech innovation is based on data of stock price changes. To assess the value impact, Poisson flow rates and stock price movements were combined. Further, to evaluate the effect of FinTech patents on the company’s value, a combination of CAR of patent application and Poisson intensities were used. Research findings provide evidence that FinTech innovations bring significant value for innovators and Blockchain being especially valuable. Such innovations as blockchain, robo-advising and mobile transactions are the most valuable for the financial sector. On one side of the spectrum, the financial industry can be affected more negatively by the innovation of nonfinancial startups that carry disruptive technology at their core. However, on the other side of the spectrum, market leaders who make significant investments in their innovations can evade most of these negative effects. This helped to form an overall view of FinTech innovations.

Aim/purpose – This study aims to identify the role of Artificial Intelligence (AI) in achieving the Sustainable Development Goals (SDGs), with specific reference to their targets, and to present good practices in this regard. Design/methodology/approach – This study adopts qualitative research based on an integrative literature review encompassing five stages: problem identification, literature search, data evaluation, data analysis, and presentation of findings. Findings – This study presents a framework for leveraging AI to achieve SDGs. It de- tails the role of AI in achieving each SDG, identifies the best practices for using AI to achieve these goals, and recommends the main steps for systematically deploying AI to achieve SDGs. Research implications/limitations – The presented findings reflect the authors’ per- spective on the role of AI in achieving SDGs based on an integrative literature review, which may have overlooked some literature on AI’s impact on individual SDGs or lacked published evidence on such interlinkages. Originality/value/contribution – This study contributes to the existing body of knowledge by providing a comprehensive framework for leveraging AI to achieve the SDGs. It systematically identifies and details the role of AI in advancing each SDG, highlights best practices for deploying AI effectively, and recommends steps for integrating AI into SDG initiatives. The study’s value lies in its ability to guide policymakers, researchers, and practitioners in harnessing AI’s potential to address critical global challenges while highlighting the need for careful consideration of potential limitations and gaps in the existing literature. Keywords: sustainable development, SDGs, Agenda 2030, Artificial Intelligence, AI. JEL Classification: 033, M15; Q01.

The paper presents an attempt to adopt a muticriteria decision making approach, particularly the Analytical Hierarchy Process (AHP) model, and to evaluate the performance of banks. The model is based on a system of various qualitative and quantitative criteria and their mutual relations. A system of indicators is created and described and each indicator is assigned a different degree of significance taking into account the needs and priorities of both internal and external evaluators. Model adaptation to Lithuanian market and an empirical test enabled to compare banks between each other, reveal their ranking and identify the banks taking leading positions in the market. The conducted research has concluded that the Analytical Hierarchy Process (AHP) model is appropriate for using it in the process valuating bank performance.

Circular economy (CE) is based on environmental, economic and social dimensions which aim to ensure sustainable development on each step of product creation, transformation and conversion by creating a closed-loop economy. The purpose of the article is to propose a concept of measurement the development of eco-innovations in the context of circular economy, apply and provide empirical evidence based on the data of Baltic Sea Region countries. The study augmented for the models that include the analysis of the circular economy concept, the importance of eco-innovation in the context of circular economy including the accent on recycling, circular material usage, material efficiency and waste management. The multi-criteria decision methods MULTIMOORA and TOPSIS were used to assess the eco-innovation as a pillar of circular economy. Results are useful to add to theoretical building and also evaluate the socio-economic aspect in the concept of circular economy.