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Artificial intelligence in influencer marketing: Current researchscape, trends and insights from a bibliometric review
No full textResearch background: Recent years have introduced a tremendous growth in the application of artificial intelligence (AI). Many organizations use this technological development to enhance operations and facilitate daily tasks. Influencer marketing is a field where the use of AI becomes inevitable.
Purpose of the article: The purpose of this paper is to analyze the current state of research on AI in influencer marketing and provide the core guidelines for further exploration of this field.
Research background: Recent years have introduced a tremendous growth in the application of artificial intelligence (AI). Many organizations use this technological development to enhance operations and facilitate daily tasks. Influencer marketing is a field where the use of AI becomes inevitable.
Purpose of the article: The purpose of this paper is to analyze the current state of research on AI in influencer marketing and provide the core guidelines for further exploration of this field.
Methods: Bibliometric analysis of scientific literature is performed based on an article selection procedure encompassing steps indicated in the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology. The Scopus database was chosen, as it has the relatively widest coverage of the Social Sciences. The search using keywords “artificial intelligence” or “AI” and “influencer marketing” found 79 documents.
Findings & value added: The field is rapidly evolving and attracting new researchers. The emerging field of interest has attracted researchers from 28 countries so far, indicating that the domain is still underexplored and requires contributions from scholars. The analysis revealed the need for the clarification of terminology. The terms ‘AI influencer’, ‘AI-generated influencer’, ‘digital influencer’, and ‘virtual influencer’ were used to describe the same phenomenon. Emerging research trends were determined: AI influencer feature determination and analysis; consumer behavioral reactions towards the AI influencers; platforms, media, and networks used by AI influencers; marketing strategies to be used by AI influencers; and suitability and appropriateness of research methods in AI influencer marketing. The main contribution and value-added lie in the determination of underexplored scopes and implications for researchers. The identified research trends would also serve as a checklist for managers choosing to apply an AI influencer in their marketing strategies: the choice of the most suitable platform and determination of the appropriate features of the influencer would set the background for strategy selection and lead to the desired consumer reactions
How is artificial intelligence technology transforming energy security? New evidence from global supply chains
No full textResearch background: Ensuring energy security (ESR) is critical for national stability and sustainable growth. However, the role of artificial intelligence technology (AIT) in enhancing ESR, particularly through global supply chain (GSC) transmission channels, remains underexplored.
Purpose of the article: This study investigates the dynamic relationship between AIT and ESR in the context of the United States, examining whether AIT ensures energy security via GSC optimization and how this interplay evolves over time.
Methods: A time-varying parameter vector autoregressive model with stochastic volatility (TVP-VAR-SV) is developed to analyze the dynamic links between AIT, GSC, and ESR and capture time-varying effects and extreme-period impacts.
Findings & value added: The results indicate that the impact of AIT on ESR is initially modest in the short term, but increases substantially in the medium to long term by optimizing energy production, distribution, and management. GSC stability and efficiency serve as key transmission channels, and post-2010 advancements amplify the influence of AIT. During crises, AIT ensures the continuity of energy security through intelligent GSC adjustments in the US. This study highlights the critical role of AIT-driven supply chain strategies in energy security and offers policy-makers actionable insights to leverage AIT and GSC optimization for sustainable energy systems
FinTech, artificial intelligence, and European Union banks: A double-edged sword for performance?
No full textResearch background: The ongoing digital transformation within the European Union\u27s banking sector, driven by the adoption of financial technologies (FinTech) and artificial intelli-gence (AI), has introduced substantial opportunities for enhancing operational efficiency, customer service personalization, and financial outreach. However, these innovations also generate strategic complexity, intensify competition from non-bank digital entrants, and create disparities in adaptation capacity across financial institutions. Despite a growing body of literature on this topic, empirical investigations remain limited regarding how these technologies differentially affect banks, based on their existing performance levels.
Purpose of the article: This study examines the extent to which FinTech and AI integration influences financial performance across banks in all 27 EU member states. Specifically, it investigates whether these technological drivers yield uniform effects or whether their impact varies across banks depending on their baseline performance. The analysis is grounded in the premise that FinTech and AI are not inherently per-formance-enhancing and that their effects may depend on context, capacity, and strategy.
Methods: Employing a panel quantile regression model, the analysis is based on a balanced panel dataset spanning the 2017–2023 period. To address both short- and long-term dynamics, the study complements its core estimation with a vector error correction model (VECM) and validates the robustness of findings through sys-tem-based regression techniques. The econometric framework incorporates bank-specific instruments and lagged performance metrics, with a particular focus on return on equity (ROE) as the dependent variable.
Findings & value added: The results indicate that the adoption of FinTech and AI is associated with signif-icant improvements in performance metrics, particularly among well-capitalized or technologically agile banks. However, institutions with weaker fundamentals may experience limited or even adverse effects. These findings suggest that the performance implications of innovation are conditional, not universal. The paper contributes by offering a distribution-sensitive analysis that refines our under-standing of technological transformation in EU banking and provides actionable insights into strategic decision-making and regulatory oversight. Also, the results offer practical implications for bank executives considering strategic technology investments, as well as for regulators aiming to design supportive, risk-sensitive digital finance policies
The Internet of Things in financial services: Real-time data for smarter asset management and insurance underwriting
No full text
Automatic pill dispenser supporting correct medication dosing
No full textThe paper presents an automatic pill dispenser used to support people taking regular doses of medications, as well as people who want to make it easier for themselves to properly dose dietary supplements. This is a system of two devices, which were called: PROGRAMATOR and LEKOMAT. The assumptions of the designed devices were transparency of operation, reliability and ease of use, because they assume that they will be used by people who suffer from various types of pain, disorders (e.g. vision), or lack of full motor coordination. It was assumed that data on how much, what medications and at what time were dispensed will be saved on a medium that the user will enter into the device. Only a person authorized to modify them will have access to this data, and the user will only be able to take medications independently according to a previously established pill dosing schedule
Amplitude and phase shift correction of the signal derivative based on the correction coefficients table
No full textThe article presents a method for correcting the derivative of a measurement signal, where the measurement error results from the signal being processed by the measurement system, altering its amplitude and phase shift. The measured values are modified using a correction coefficient that depends on the increment between successive signal values. The coefficient can be stored in the memory of a microprocessor-based sensor or another DSP system. The correction coefficient values, stored in a lookup table, are determined in advance through laboratory testing by comparing the response of a reference signal with that of the measured signal. Sample correction results are shown for a sinusoidal signal, where the phase shift is −10°, and the amplitude is 1.2 times greater than that of the reference signal. After applying the correction, the median relative error decreased from approximately −18% to negligibly small values
Wpływ ESG na sprawozdawczość finansową – wyzwania i obowiązki
Full text linkCelem niniejszego artykułu jest przedstawienie wyzwań i obowiązków stawianych przed podmiotami prowadzącymi działalność na terenie UE w związku z raportowaniem niefinansowym (raportowaniem ESG). W szczególności zaprezentowano: aspekty ESG, przepisy określające ramy raportowania niefinansowego, harmonogram wdrażania dyrektywy CSRD, wyzwania związane z pozyskiwaniem i opracowaniem informacji niefinansowych oraz występujące praktyki greenwashingu. Została również zaprezentowana analiza realizacji celów zrównoważonego rozwoju przez podmioty działające na polskim rynku. Artykuł został napisany w oparciu o źródła z zakresu raportowania niefinansowego oraz obowiązujące regulacje dotyczące zrównoważonego rozwoju
Precautionary cash holding by consumers making electronic payments and risk-taking behavior
No full textResearch background: The relative inertia in holding cash, despite the increasing importance of electronic payments, is one of the most fascinating puzzles of the current monetary system and a significant issue for central bank policy. In our study, we would like to extend the previous considerations regarding holding cash by consumers who have decided to make electronic payments but keep the cash despite this.
Purpose of the article: Recent literature mainly considers the trade-off between cash and electronic payments. We go beyond this dual framework and instead focus on the precautionary demand for cash. We study the relevance of several psychological factors behind cash holding by consumers who have decided to use electronic payments.
Methods: We employ factor analysis and logistic regression. We use data from a standardized online survey conducted among Polish consumers.
Findings & value added: Our study\u27s key determinants of holding cash include risk-taking behavior, perceived risk of the unavailability of the payment infrastructure and perceived attitudes towards cash (flexibility and cybersecurity related to the lack of exposure to cyberattacks). According to our research, consumers attach great importance to the flexibility that cash gives as an additional option to electronic payments. A better understanding of these motivations is crucial for public policymakers, who should strive to design payment systems that respond to the needs of all social groups. Therefore, in (at least) the short and medium term, cash will remain in circulation, even if it gradually loses its payment function
Twin transformation: The role of digitalization with artificial intelligence, big data and circular supply chain in circular economy performance for sustainability
No full textResearch background: The fourth industrial revolution has significantly changed the operational processes of industries and influenced the industrial structures of multiple countries. These scenarios have resulted in organizations embracing digital technologies in their supply chains. However, the digital supply chain literature is still in its early stages of development.
Purpose of the article: This study primarily aimed to understand whether artificial intelligence (AI) and big data influence circular economy performance (CEP) through the circular supply chain (CSC), along with exploitative and explorative integration.
Methods: Data were collected using a questionnaire survey. The proposed hypotheses were tested using partial least squares structural equation modeling (PLS-SEM) via Smart PLS (4.0). The empirical analysis supported most proposed hypotheses.
Findings & value added: The results indicate that the CSC supports digitalization in improving CEP. Additionally, exploitative integration does not influence the moderating role between big data and the CSC, nor does explorative integration between AI and the CSC. This study enables managers to understand that enabling technologies are suitable for facilitating the accomplishment of a CSC’s goals