Biometrics Innovation and Payment Sector Perception

Mróz-Gorgoń, Barbara; Wodo, Wojciech; Andrych, Anna; Caban-Piaskowska, Katarzyna; Kozyra, Cyprian

doi:10.3390/su14159424

Cited by 8 publications

(4 citation statements)

References 34 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The results of Miltgen et al (2013) shows that consumers who have greater privacy concerns will perceive acceptance of a biometric system as riskier. The results of other studies confirm that perceived risk negatively impacts consumer attitudes towards using biometric payments (Dang et al, 2022), while perceived security (Morosan, 2011;Mróz-Gorgoń et al, 2022) significantly affects attitudes towards using biometric systems. In the case of research on the acceptance of biometric technologies in payment services security is analysed in comparison to existing authentication methods.…”

Section: Acceptance Factors Of Biometric Technologiesmentioning

confidence: 56%

Determinants of consumer adoption of biometric technologies in mobile financial applications

Anna Iwona Piotrowska

2024

EBR

View full text Add to dashboard Cite

This study aims to identify what determines the use of biometric technologies in the financial applications of banks and FinTechs. The analysis uses data from a survey of 1,000 adult Polish residents. The estimated logit model indicates that the probability of using biometric solutions decreases with age and increases with the level of education and technological sophistication relating to personal innovativeness, experience with biometric technology, and the use of digital technology in both financial and non-financial areas. The work identifies the COVID-19 pandemic as a factor accelerating the adoption of biometric solutions and fostering awareness of the threat of digital technologies invading respondents’ privacy. The study demonstrates the positive impact of trust that phone manufacturers ensure the security of stored funds and data processing on the acceptance of biometric solutions in financial services. This relationship underpins the recommendation to financial institutions in the field of promoting biometric technologies.

show abstract

Section: Acceptance Factors Of Biometric Technologiesmentioning

confidence: 56%

Determinants of consumer adoption of biometric technologies in mobile financial applications

Anna Iwona Piotrowska

2024

EBR

View full text Add to dashboard Cite

show abstract

“…The assumption is that the green economy is about conducting all economic activities with respect for nature’s assets and in such a way as to prevent irreversible changes to the environment [ 7 ]. Therefore, there are changes taking place in all business processes and decision-making aiming at a low-carbon, and a resource-efficient economy based on green technologies [ 8 , 9 ]. The examples of the changes towards SD are visible in all economic sectors and there is a gradual green transformation of the whole economy taking place [ 10 , 11 ].…”

Section: Introductionmentioning

confidence: 99%

Green Jobs: Bibliometric Review

Kozar

Sulich

2023

IJERPH

View full text Add to dashboard Cite

Among the visible effects as Sustainable Development (SD) transitions from theory into practice, there are Green Jobs (GJs). There are multiple variants in naming this phenomenon in the labor market. Among them are green collars, green employment, and sustainable employment, all indicating a profound inconsistency in the GJ definition. This article aims to identify keyword-specified areas around which the topic of GJs revolves in the scientific literature indexed in the Scopus database. The usage of two methods has achieved this goal. First is the Structured Literature Review (SLR) variation with queries, and it is used to explore the scientific database to determine GJ’s definition consistency by the queries syntax. The second method is the search results analysis performed in the Scopus database online to identify the most cited publications and most contributing authors. Then the bibliometric analysis was performed to create bibliometric maps of the most critical keywords in VOSviewer software. The combination of those two approaches allowed this research to indicate the most influential research directions on GJs. The results are presented in graphical forms, and tables with main co-occurring keyword clusters were identified. GJs are a key part of green economy development, where green self-employment and green entrepreneurship play a pivotal role. The presented results can inspire other researchers who are looking for a research gap or describing the state of the art. Politicians and decision-makers can be influenced by the presented contextualization of green job’s meaning in the labor market.

show abstract

“…Currently, the development and application of biometric technologies are considered in a number of scientific papers. In particular, the design of multicomponent food products depending on human needs [9,10], the use of biometrics to solve the problems of migration and border management [11], the development of biometric applications for making payments [12,13], early detection of signs of diseases based on pattern recognition [14], etc. However, at present, the use of biometric technologies, in particular, face recognition technology in PACS, has not been studied enough.…”

Section: Introductionmentioning

confidence: 99%

Development of software and hardware complex for control and access management based on face recognition algorithms and neural networks

Rada

Тимофеев

Kon’kov

et al. 2023

International Conference on Digital Transformation: Informatics, Economics, and Education (DTIEE2023)

View full text Add to dashboard Cite

The purpose of the study is to develop and test a software and hardware complex for access control and management using face recognition algorithms and neural network technology. A software and hardware complex was used, including turnstiles with swing doors, single-board mini-computers on each turnstile, webcams, sensors, an integrated graphics processor, as well as a software development kit for developers. Siamese neural network “FaceNet” was used for face recognition. When training a neural network, each face image is associated with a feature vector lying on the N-dimensional hyposphere. The study developed and tested photo pre-processing algorithms (to exclude irrelevant images), as well as the biometric PACS algorithm. Approbation of the developed hardware and software system on the campus of the Kemerovo State University (Kemerovo, Kemerovo region – Kuzbass, Russia) showed that the average frame processing speed is high (0.076 seconds per frame), which ensures a fairly fast pass of people. This result is achieved on the basis of the image pre-processing algorithm. During the first test of the software and hardware complex, it was found that 60% of the frames are excluded from the analysis by the neural network. Errors of the first kind (passing people who do not have the right to pass) were observed in 4% of cases. After setting up and calibrating the software and hardware complex, the proportion of such errors decreased to 0.4% of the total number of frames processed by the neural network.

show abstract

Biometrics Innovation and Payment Sector Perception

Cited by 8 publications

References 34 publications

Determinants of consumer adoption of biometric technologies in mobile financial applications

Determinants of consumer adoption of biometric technologies in mobile financial applications

Green Jobs: Bibliometric Review

Development of software and hardware complex for control and access management based on face recognition algorithms and neural networks

Contact Info

Product

Resources

About