2929Copernican Journal of Finance & Accounting e-ISSN 2300-3065 p-ISSN 2300-12402024, volume 13, issue 4 Date of submission: December 1, 2024; date of acceptance: December 20, 2024. * Contact information: mbb@doktorant.umk.pl, Interdisciplinary Doctoral School of Social Sciences, Nicolaus Copernicus University in Toruń, Collegium Humanisticum, Bojarskiego 1, 87-100 Toruń, +48 698 700 010.; ORCID ID: https://orcid.org/0000- 0001-6590-4279. ** Contact information: michal.polasik@umk.pl, Faculty of Economic Sciences and Management, Nicolaus Copernicus University in Toruń, Gagarina 13a, 87-100 Toruń, Po- land, phone: +48 608 335 541; ORCID ID: https://orcid.org/0000-0002-7790-4839. *** Contact information: andrzej.meler@umk.pl, Faculty of Philosophy and Social Sci- ences, Nicolaus Copernicus University in Toruń, Fosa Staromiejska 1a, 87-100 Toruń, Poland, phone: +48 790 897 540; ORCID ID: https://orcid.org/0000-0001-8769-8752. **** Contact information: anna.kiermas@doktorant.umk.pl, Interdisciplinary Doctor- al School of Social Sciences, Nicolaus Copernicus University in Toruń, Collegium Hu- manisticum, Bojarskiego 1, 87-100 Toruń, Poland, phone: +48 533 643 552; ORCID ID: https://orcid.org/0000-0002-6876-9866. Borowski-Beszta, M., Polasik, M., Meler, A., & Borowska-Beszta, A. (2024). NFC, Wearables and QR Code in POS Payments: Determinants of Adoption of the Leading Mobile Payment Technologies in Europe. Copernican Journal of Finance & Accounting, 13(4), 29–59. http://dx.doi.org/10.12775/ CJFA.2024.016 Mikołaj Borowski-Beszta* Nicolaus Copernicus University in Toruń Michał Polasik** Nicolaus Copernicus University in Toruń andrzej Meler*** Nicolaus Copernicus University in Toruń anna Borowska-Beszta**** Nicolaus Copernicus University in Toruń nfc, wearaBles and qr code in Pos PayMents: determinants of adoption of the leading mobile payment technologies in europe http://dx.doi.org/10.12775/CJFA.2024.016 http://dx.doi.org/10.12775/CJFA.2024.016 M. Borowski-Beszta, M. Polasik, A. Meler, A. Borowska-Beszta3030 Keywords: mobile payments, mobile banking, NFC, wearables, QR codes. J E L Classification: D12, E42, O33. Abstract: Digital technologies are increasingly important in the European payment services market. The study examined NFC mobile payments, wearables payments, and QR code payments, to determine the potential for development in the European mar- ket. The paper aims to explain the factors determining consumers’ intention to use or reject these technologies following the TAM methodology. Within the study, a pan-Eu- ropean survey using the CAWI method was conducted on a sample of n = 5,504 respond- ents from 22 countries. Quantitative analysis was performed using logit models. The results confirmed that the most important, positively influencing factors are the Per- ceived Usefulness and Perceived Ease of Use of studied payment methods. Moreover, the preference for anonymity and trust of service providers impact the intention to use mobile payment technologies. It turned out that education level and knowledge of tech- nology play an essential role. The study showed that Europe has the market space for all three mobile payment technologies. However, NFC payments have advantages in the European market due to consumers’ declared interests and widespread acceptance in- frastructure among merchants.  Introduction Introduction With technological progress, service providers and technology companies pro- vide new solutions enabling potential users to gain new experiences. An exam- ple of the impact of technology on society is the digitalization process, which has significantly influenced society’s development and the change of its cur- rent behavior, habits, and expectations towards technology. Access to the In- ternet and technology has meant that part of society carries out everyday ac- tivities continuously online, i.e., has access to communication links all the time, regardless of where they are, time, and circumstances. One of the most inten- sively developed innovations in recent years is mobile payment systems, the development and distribution of which turned out to be more challenging to implement. This work focuses on developing critical mobile payment solutions used in physical points of sale in the European payments market. The technology that has been most successful in recent years is Near Field Communication (NFC) (Borowski-Beszta & Kiermas, 2019). It combines the payment card model with the convenience of using mobile technologies and is available in various distri- bution channels, i.e., via smartphones or wearable devices (Borowski-Beszta & Polasik, 2020). Mobile payments with QR codes, popular in selected European NFC, wEaraBlEs and QR CodE in POS PaymEnts… 3131 Union countries, also play an essential role. However, the implementation and spread of mobile payments are still early, so it is essential to investigate the knowledge about mobile payments in Europe and their position in the overall payment system. This work aims to: 1. Present the main mobile technologies – NFC, wearables, and QR codes – shaping the contemporary mobile payments market in Europe, 2. Identify the factors influencing European consumers’ intensions of use or rejection of mobile payments. 3. Examining the differences between factors shaping consumer interest in the three main technologies for mobile payments. The study is based on a pan-European representative survey conducted in August 2020 on a sample of n=5,504 respondents from 22 countries. Such a large and diverse research sample allowed for examining the entire Europe- an market, setting it apart from other studies in this field that focus on a single country or a few. The rich research material enabled the exploration of three key technologies, which are typically investigated separately. The first part of the work presents information on key mobile payment sys- tems used in physical points of sale in European countries, i.e., NFC technology and mobile payments in QR technology. The next part of the work is the pres- entation of the theoretical basis, which is the starting point for the empirical analysis. The main framework used for the work is the Technology Acceptance Model by F. Davis, which has been successfully used for years to study the fac- tors influencing the acceptance or rejection of mobile technologies worldwide. The last part of the work presents empirical research, i.e., the analysis of data obtained as part of a survey using quantitative methods, including logit mode- ling. The work ends with conclusions and recommendations from the conduct- ed research. Mobile Payments DefinitionMobile Payments Definition Mobile payments are a type of cashless payment that can be initiated, author- ized, and completed using mobile devices, such as a smartphone (Humbani & Wiese, 2018) or a wearable device (an advanced technological solution that the user can wear – these include, among others, smartwatches and smart- bands (Borowski-Beszta & Polasik, 2020). Mobile devices play a key role in this M. Borowski-Beszta, M. Polasik, A. Meler, A. Borowska-Beszta3232 type of payment because they are used to initiate, confirm, and finalize trans- actions (Kisiel, 2013; Pal, Khethavath, Chen & Zhang, 2017). This work analyz- es two main categories of mobile payments: NFC mobile payments (made using smartphones and wearable devices) and mobile payments with QR codes. NFC mobile payments originate from contactless payments with payment cards dating back to 1997. NFC mobile payments fall within the definition of mobile payments but have several different features. The leading NFC mobile payment solutions are based on the payment card instrument. The first im- plementation of contactless payments with payment cards took place in Hong Kong in 1997, when the Octopus system was introduced. It was the first large- scale implementation of contactless cards and was used to handle fares in public transport (Kunkowski, 2013). MasterCard, in turn, was the first inter- national payment organization to implement contactless technology in Decem- ber 2002 in the United States. Implementing the MasterCard PayPass pilot pro- gram showed many benefits associated with the contactless payment method, resulting in the spread of contactless cards in major global markets (Polasik & Kunkowski, 2009). The year 2004 turned out to be a breakthrough for the co- operation of three technology giants, i.e., Philips, Sony, and Nokia, because they jointly developed the NFC standard, founded the NFC Forum, and then started promoting NFC applications (McHugh & Yarmey, 2012). To implement NFC contactless payments in Mastercard and Visa solutions, NFC payment systems use procedures and communication channels created for contactless cards. The NFC device exchanges data with the EFT-POS ter- minal, and further information transfer in the payment system occurs only on the terminal side. Payment transactions using NFC can also be made offline, bypassing communication with the bank server issuing a given payment in- strument (Polasik, 2014). In turn, contactless ATMs are almost always online. Thanks to this, “NFC mobile payments constitute a common part of the con- cepts of mobile and contactless payments […], and within each of these terms, there are other solutions with clearly different characteristics” (Polasik, 2014). The combination of many different features makes NFC mobile pay- ments attractive in terms of convenience and speed of transaction execution for individual customers. A mobile device with NFC eliminates the need for a plastic card and wallet. An innovative timing study conducted by M. Polasik in the initial phase of introducing NFC technology to the Polish payment ser- vices market showed that NFC mobile payments are competitive in terms of transaction execution time for cash and contactless payment cards and much NFC, wEaraBlEs and QR CodE in POS PaymEnts… 3333 faster than payment cards authorized via using a PIN code and mobile pay- ments requiring the consumer to enter the codes on the phone. An important conclusion from the research at that time was that it took customers much less time to take out a smartphone and prepare it for a transaction than to take out a payment card from the wallet (Polasik, Górka, Wilczewski, Kunkowski, Przenajkowska & Tetkowska, 2013). NFC technology has created enormous potential for the development of mo- bile payments, which are considered the most revolutionary and future-proof retail payments. Making payments using a mobile device is becoming easier and more accessible, and the level of convenience of use is also increasing (Alal- wan, Baabdullah, Al-Debei, Raman, Alhitmi, Abu-ElSamen & Dwivedi, 2024). Therefore, the natural development of contactless payments will be a gradual transition from card payments to NFC mobile payments using the same exten- sive network of EFT-POS contactless payment terminals (Kunkowski, 2013). Wearable devices are also a promising distribution channel for NFC mobile payments. The Impact of Wearables on PaymentsThe Impact of Wearables on Payments Wearable devices have set a new technological trend that focuses on a solu- tion with a particularly distinctive feature, i.e., the wearability of technology. Thanks to the possibility of equipping clothes with technology, an additional benefit is achieved – always having technology. Additionally, these devices al- low consumers to replace their smartphones with smartwatches or wristbands. The functionalities of wearables include not only sports (Wang, 2015) or health functions (Chang, Xu, Wong & Mendez, 2019; Reeder & David, 2016), but also payments (Borowski-Beszta & Polasik, 2020, 2022). Thanks to the last function, wearable devices are one of the innovative elements of the European payment system because they can be used to make NFC contactless mobile payments. Due to the dynamics of the development of wearable devices, which are char- acterized by introducing a high level of innovation in a relatively short period, this technology is a new and promising research area. Payments using wearable devices are currently offered by many payment institutions around the world, including Apple (Apple Pay) (www1), Google (Google Pay) (www2), Xiaomi (Xi- aomi Pay) (www3), Garmin (Garmin Pay) (www4), as well as Fitbit, which until 2022 offered the Fitbit Pay system, currently working with Google Pay (www5). M. Borowski-Beszta, M. Polasik, A. Meler, A. Borowska-Beszta3434 QR Code Payments as an AlternativeQR Code Payments as an Alternative An essential solution for making mobile payments is mobile payment systems based on QR codes. This is another cashless form of payment using dot matrix codes developed by Denso Wave (HARA, 2019), which can be displayed both on the smartphone screen and, for example, printed. QR codes contain transaction data and enable quick mobile payments (Ramos de Luna, Liébana-Cabanillas, Sánchez-Fernández & Muñoz-Leiva, 2019). QR code payments have been most popular in Asian countries, with systems such as WeChat and AliPay (Polasik, Widawski, Keler & Butor-Keler, 2021). However, their popularity is growing in some European countries, e.g., in Belgium, where one of the most popular mo- bile payment systems is Bancontact by Payconiq (www6). These codes have many uses and also work very well for city payments (Di Pietro, Guglielmetti Mugion, Mattia, Renzi & Toni, 2015), as a quick form of purchasing tickets for consumers. Mobile Payments in EuropeMobile Payments in Europe In our study, we asked respondents in individual European countries whether they already use NFC, wearables, and QR payments, and whether they intend to use them in the future. In Table 1, we have compiled statistics for the use and interest in individual types of mobile payments. Paying with NFC technol- ogy is already quite common in the EU, with a reach exceeding 25%, twice as much as wearables, and nearly three times more than QR payments. We can say that the success of NFC is significant, and one of the reasons is a well-de- veloped network of contactless payment systems that both NFC and wearables (EBC SPACE) can leverage. However, these systems do not support payments via QR codes. NFC, wEaraBlEs and QR CodE in POS PaymEnts… 3535 Table 1. Use and Intention to Use the Three Main Mobile Payment Technologies in Europe Country NFC Wearables QR code Use Willingness Use Willingness Use Willingness % % of agree and strongly agree answers % % of agree and strongly agree answers % % of agree and strongly agree answers Austria 20 39 7 19 7 19 Belgium 17 52 8 24 35 40 Bulgaria 12 46 4 36 2 28 Czechia 29 30 16 12 15 17 Denmark 21 40 11 19 13 26 Finland 23 42 6 24 6 18 France 20 53 20 34 6 32 Germany 20 35 9 21 7 23 Greece 15 48 9 28 8 22 Hungary 19 41 8 31 9 24 Ireland 32 63 18 31 4 21 Italy 20 42 12 27 7 30 Lithuania 18 64 10 48 11 48 Netherlands 29 47 11 29 34 34 Norway 24 42 9 24 6 19 Poland 37 65 15 46 5 41 Portugal 12 61 8 41 9 46 Romania 25 53 9 32 5 32 Slovakia 29 35 15 18 9 18 Spain 24 47 11 30 6 31 Sweden 31 49 8 24 21 34 United Kingdom 37 56 20 41 3 27 Total 25 50 12 31 9 30 S o u r c e : PayTchImpact.EU research, weighted data based on gender, age, and location. M. Borowski-Beszta, M. Polasik, A. Meler, A. Borowska-Beszta3636 However, considering the differences between countries, the highest percent- age of use of NFC mobile payments is reported in Poland, the United Kingdom (37%), Ireland (32%), and Sweden (31%). NFC mobile payments are most rare- ly indicated by consumers from Bulgaria, Portugal (12%), and Greece (15%). However, regarding the willingness to use NFC mobile payments, in all the countries surveyed, the share of respondents interested in using NFC in the near future is 30%. The highest interest was shown by consumers from Poland (65%), Ireland (63%), and Lithuania (66%). When it comes to wearable devices, this is a less frequently used product. On average, only 12% of consumers use it for payments, and this level of pop- ularity is similar across Europe. However, significant differences were found when it comes to interest in using wearable devices in the future. Consumers from 4 of the 22 surveyed countries showed a willingness to use wearable de- vices at a level higher than 40%, and the most significant interest was shown by consumers from Lithuania (48%), Poland (46%), Portugal (41%), and the Unit- ed Kingdom (41%). It is worth paying attention to Bulgaria, which takes fifth place (35%). Despite the low popularity of wearable devices and NFC mobile payments among Bulgarians, they are willing to use such solutions. Analyzing mobile payments with QR codes brings a radically different pic- ture than the above-described technologies. Consumers from Belgium (35%) and the Netherlands (34%) are undoubtedly at the forefront, which may be be- cause there are already two well-functioning QR mobile payment systems in these countries – i.e., Payconiq by Bancontact in Belgium, as well as iDEAL in the Netherlands. In other countries, the percentage of users who use QR mobile payments is much lower, and the average for the entire sector is lower – 9%. It should be noted, however, that again, as in the case of wearable devices, the most significant potential for using QR mobile payments is perceived by consumers from Lithuania (47%), Portugal (46%), Poland (41%), and Belgium (40%). Research ModelResearch Model We used the Technology Acceptance Model framework as a starting point for developing the research model. The Technology Acceptance Model (TAM), de- veloped based on the Theory of Reasoned Action, was presented by F. Davis in 1986. The TAM model makes it possible to examine and explain the factors in- fluencing the use or rejection of selected technological innovations. This model, NFC, wEaraBlEs and QR CodE in POS PaymEnts… 3737 presented in Figure 1, is the basis for determining factors influencing the be- liefs, behaviors, and intentions of potential users, which simultaneously trans- lates into the actual use of the selected innovation. The two key factors that form the basis of the discussed model are (Davis, Bagozzi & Warshaw, 1989): ■ Perceived Usefulness – PU; ■ Perceived Ease of Use – PEoU. Perceived Usefulness (PU) is the level to which an individual believes that a selected technological innovation will help increase his or her performance when completing tasks. However, the second primary factor – perceived ease of use (PEoU), refers to the degree to which the user believes that using a given innovation will take place without effort (Davis et al., 1989). Figure 1. The Classic Form of F. Davis’ Technology Acceptance Model users who use QR mobile payments is much lower, and the average for the entire sector is lower – 9%. It should be noted, however, that again, as in the case of wearable devices, the most significant potential for using QR mobile payments is perceived by consumers from Lithuania (47%), Portugal (46%), Poland (41%), and Belgium (40%). Research Model We used the Technology Acceptance Model framework as a starting point for developing the research model. The Technology Acceptance Model (TAM), developed based on the Theory of Reasoned Action, was presented by F. Davis in 1986. The TAM model makes it possible to examine and explain the factors influencing the use or rejection of selected technological innovations. This model, presented in figure 1, is the basis for determining factors influencing the beliefs, behaviors, and intentions of potential users, which simultaneously translates into the actual use of the selected innovation. The two key factors that form the basis of the discussed model are (Davis, Bagozzi & Warshaw, 1989):  Perceived Usefulness – PU;  Perceived Ease of Use – PEoU. Perceived Usefulness (PU) is the level to which an individual believes that a selected technological innovation will help increase his or her performance when completing tasks. However, the second primary factor – perceived ease of use (PEoU), refers to the degree to which the user believes that using a given innovation will take place without effort (Davis et al., 1989). Figure 1. The Classic Form of F. Davis’ Technology Acceptance Model Source: own study based on: Davis, Bagozzi and Warshaw (1989). External variables Usefulness (PU) Ease of Use (PEoU) Attitude Toward Using Behavioral Intention to Use Actual System Usage S o u r c e : own study based on: Davis, Bagozzi and Warshaw (1989). The classic version of the TAM model assumes that perceived usefulness (PU) and perceived ease of use (PEoU) are directly influenced by external factors (External Variables – EV). In turn, the intention to use (Behavioral Intention – BI) of a selected system or technological innovation is influenced by the overall attitude of users towards a given system (Attitude) and Perceived Usefulness (PU). The factors mentioned above may ultimately translate into the actual use of technology among consumers (Polasik & Kumkowska, 2015). The Technology Acceptance Model is successfully used among researchers of technology acceptance by users worldwide. It has been used in a wide range M. Borowski-Beszta, M. Polasik, A. Meler, A. Borowska-Beszta3838 of research, including financial innovations such as mobile banking (Jeong & Yoon, 2013; Muñoz-Leiva, Climent-Climent & Liébana-Cabanillas, 2017; Po- lasik, Wisniewski & Lightfoot, 2012), NFC mobile payments (Pal, Vanijja & Pa- pasratorn, 2015; Ramos-de-Luna, Montoro-Ríos & Liébana-Cabanillas, 2016), as well as QR code payments (Yan, Tan, Loh, Hew & Ooi, 2021). This model is also a research tool used by authors examining wearable devices, including smartwatches and smartbands (Borowski-Beszta & Polasik, 2020; Chang, Lee & Ji, 2016). Research conducted using the TAM model concerned both non-fi- nancial contexts (Morosan, 2011), as well as financial (Leong, Hew, Tan & Ooi, 2013; Mun, Khalid & Nadarajah, 2017; Patil, Tamilmani, Rana & Raghavan, 2020; Polasik & Kumkowska, 2015; Ramos-de-Luna et al., 2016). With tech- nological progress, an increasing number of wearable devices enabling con- tactless payments have appeared on the market. Therefore, the attention of researchers has also been directed to contactless payments with wearable de- vices (Borowski-Beszta & Polasik, 2020; Chang et al., 2016; Chuah, Rauschna- bel, Krey, Nguyen, Ramayah & Lade, 2016; Kim & Shin, 2015). The widespread use of the TAM model and its derivatives in research on payment innovations suggests the application of its assumptions and main constructs for this work. Methodology and dataMethodology and data The study is based on a pan-European representative survey conducted using the CAWI method on a sample of n=5,504 respondents from 22 countries in Au- gust 2020. The pan-European research was carried out under a grant from the National Science Center, entitled “The impact of FinTech development and legal regulations on innovations in the payment services market in the European Un- ion: financial sector strategies and consumer needs” No. 2017/26/E/HS4/00858. The research agency collected the survey responses using the Dynata research panel. The study is representative of the characteristics of European Internet us- ers and included, among others, age, gender, and place of residence. The analysis considered three payment methods separately: NFC (under- stood as digital card, Google Pay, or Apple Pay payments via a smartphone), wearables, and QR. NFC and wearables can be treated as the same solution in the technology dimension of data exchange with payment terminals. Still, in the dimension of consumer experiences, they have somewhat different char- acteristics. For instance, smartphones are a more widespread technology used NFC, wEaraBlEs and QR CodE in POS PaymEnts… 3939 for various purposes, while wearables are a relatively newer solution. In the study, respondents were asked about their intention to use the tested payment technologies in the near future (12 months). In the analysis, three models were constructed for each payment method. The variable testing intention is an or- dinal variable, so an ordered logit was used to explain it. Different combina- tions of independent variables were adopted for each model from a set compris- ing three groups of variables. Table 2. Variables Description Group Short name of variable Description Scale use Declaration of ac- tual use of mobile payment Dependent variable (explained) 1 – separate for each of the three methods: NFC / QR / wearables. ordered 1–5 1 – strongly none 2 – rather none 3 – neither none or yes 4 – rather yes 5 – strongly yes willingness Declaration of intent to the use mobile payment in the near future Dependent variable (explained) 2 – separate for each of the three methods: NFC / QR / wearables. ordered 1–5 1 – strongly none 2 – rather none 3 – neither none or yes 4 – rather yes 5 – strongly yes TAM (Group A) Usefulness Perceived usefulness contruct. Construct of variables related to safety, supporting household budgets, and perceived accessibility of given methods. continuous 1 – the least usefulness 5 – the most usefulness orthogonalized to avoid corellation with other variables in the model Ease of Use Perceived ease of use. Construct of variables related to the convenience of paying with a given method. continuous 1–5 1 – the least ease of use 5 – the most ease of use social attitudes (Group B) opinion_leader Construct of variables defining the consumer’s self-perception as a per- son who provides advice to others regarding new solutions. ordered 1–5 1 – strongly disagree 2 – rather disagree 3 – neither agree or disagree 4 – rather agree 5 – strongly agree trustful Most people can be trusted. ordered 1–5 1 – strongly disagree 2 – rather disagree 3 – neither agree or disagree 4 – rather agree 5 – strongly agree M. Borowski-Beszta, M. Polasik, A. Meler, A. Borowska-Beszta4040 Group Short name of variable Description Scale anonimity I prefer payments for shopping to be anonymous, so that no one can see what I bought and when (e.g., paying by cash is anonymous, contrary to payment cards and smartphones). ordered 1–5 1 – strongly disagree 2 – rather disagree 3 – neither agree or disagree 4 – rather agree 5 – strongly agree reliable It is better to use tried and tested solutions. ordered 1–5 1 – strongly disagree 2 – rather disagree 3 – neither agree or disagree 4 – rather agree 5 – strongly agree peer_fraud_victim Someone close to me was a victim of fraud which involved using a card or a payment mobile application. ordered 1–5 1 – strongly disagree 2 – rather disagree 3 – neither agree or disagree 4 – rather agree 5 – strongly agree tech inclusion (Group B) apps no Number of aplications from fol- lowing: – �Fitness/healthcare�applications� (e.g., MyFitnessPal, Garmin, En- domondo, Huawei Health, Sam- sung Health, Polar, Apple Health) – �Transport�applications�(e.g.,�Uber,� Bolt, Freenow) – �Food�delivery�applications�(e.g.,� Uber Eats, TakeAway) – �Anti-virus�software�installed�on� a mobile device – �Applications�for�buying�tickets�in� public transport – �Applications�for�buying�parking� tickets continuous number data_sharer Sharing my personal data is not a problem for me. ordered 1–5 1 – strongly disagree 2 – rather disagree 3 – neither agree or disagree 4 – rather agree 5 – strongly agree cloud_user My personal data stored by com- panies such as Google, Amazon, Facebook, and Apple are adequately protected. ordered 1–5 1 – strongly disagree 2 – rather disagree 3 – neither agree or disagree 4 – rather agree 5 – strongly agree Table 2. Variables… NFC, wEaraBlEs and QR CodE in POS PaymEnts… 4141 Group Short name of variable Description Scale bank_storage When it comes to payments, I only trust banks. ordered 1–5 1 – strongly disagree 2 – rather disagree 3 – neither agree or disagree 4 – rather agree 5 – strongly agree solution availability coefficient in a given country (Group B) share_contactless An indicator assigned to a country reflecting the availability of contact- less payments. continuous percent cvm_limit An indicator assigned to a country reflecting the limit for contactless payments without the need to enter a PIN code. continuous EURO socio- demographic (Group C) gender gender Nominal 1 – woman 2 – man age age continuous years location place of residence Ordered 1 – Rural area 2 – Town with less than 50 thousand inhabitants 3 – Town between 50 thousand and 100 thousand inhabitants 4 – City between 100 thousand and 500 thousand inhabitants 5 – City between 500 thousand and 1 million inhabitants 6 – City with over 1 million inhabit- ants education education level divided to higher and less than higher ordered 1–2 1 – less than higher 2 – higher income personal income ordered 1–11 standardized 11 ranges with control points at the poverty line, the national minimum and the national average for each country S o u r c e : own study based on: PayTchImpact.EU research. Table 2. Variables… M. Borowski-Beszta, M. Polasik, A. Meler, A. Borowska-Beszta4242 A description of the variables is presented in Table 2. The first group (Group A) includes variables related to Usefulness and Ease of use, derived from the theo- retical assumptions of the TAM model. This allowed testing to what extent fac- tors related to usability and ease of use impact the intention to use NFC, wear- ables, and QR payment technologies. Results of the reliability analysis of two constructs, Usefulness and Ease of Use, for all three payment methods tested, are shown in Table 3. Cronbach’s Alpha parameters are consistently above the threshold of 0.60, deemed acceptable by Churchill (1979). Therefore, both con- structs can be treated as representing the hidden phenomena of “usefulness” and “ease of use.” The constructs Usefulness and Ease of use were related (Pear- son r > 0.55), so to eliminate the redundancy of information brought by them to the model; orthogonalization was applied, in which one variable is transformed so that it becomes independent (orthogonal) with respect to the other variable. This means that their correlation coefficient is equal to zero. In the second group (Group B), variables testing the level of technological involvement in areas other than payments are introduced. Technological in- volvement in various life areas may significantly correlate with the adoption of modern payment methods. In this block, variables such as the number of used transportation apps (apps_no), attitude toward cloud solutions (cloud_user), and willingness to share personal data with service providers (data_sharer) are included. It is also assumed that social factors may influence the higher- level adoption of payment methods, such as the general level of trust in others (trustful), perception of anonymity (anonymity), seeing oneself as a person who influences the purchasing decisions of others (opinion_leader), and the experi- ence of encountering a fraudster personally or in the immediate surroundings using new technologies (peer_fraud_victim). Additionally, variables indicating the level of contactless payment acceptance in the respondent’s country (share_ contactless) and the contactless payment limit without requiring a PIN code (cvm _limit) are introduced. These two variables are considered at the country level, not for individual respondents. Group C comprises socio-demographic variables: gender, age, location (size of the residential area), education, and income. The detailed assignment of vari- ables to blocks and a description of the scales on which they were measured are provided in Table 2. NFC, wEaraBlEs and QR CodE in POS PaymEnts… 4343 Table 3. Reliability Analysis of the Constructs Payment method Construct Observed variable Scale Mean if Item Deleted Scale Variance if Item Deleted Corrected Item-Total Correla- tion Cronbach’s Alpha if Item Deleted Cronbach’s Alpha n NFC Usefulness wide- spread 17.5548 15.145 0.546 0.780 0.807 4829 control over personal finance 17.4157 14.511 0.606 0.767 conveni- ent 17.5419 13.895 0.629 0.760 safe 17.3371 13.696 0.622 0.762 useful mobile 17.0345 15.903 0.486 0.792 mobile finance 17.3988 14.649 0.504 0.791 Ease of Use easy to use 20.2684 17.238 0.311 0.735 0.735 conveni- ent 19.9428 17.132 0.388 0.716 methods overflow 19.7188 16.927 0.425 0.709 easy app 20.4923 16.115 0.434 0.707 online hardship 20.3179 15.313 0.564 0.675 mobile- hardship 20.1680 14.751 0.595 0.665 forced 20.3237 16.263 0.421 0.710 M. Borowski-Beszta, M. Polasik, A. Meler, A. Borowska-Beszta4444 Payment method Construct Observed variable Scale Mean if Item Deleted Scale Variance if Item Deleted Corrected Item-Total Correla- tion Cronbach’s Alpha if Item Deleted Cronbach’s Alpha n wearables Usefulness wide- spread 17.2626 17.614 0.597 0.792 0.822 control over personal finance 17.1130 17.288 0.625 0.785 conveni- ent 17.2330 16.174 0.649 0.780 safe 17.1977 16.398 0.727 0.762 useful mobile 16.6777 20.128 0.451 0.819 mobile finance 17.0000 18.846 0.483 0.815 Ease of Use easy to use 20.3107 17.600 0.319 0.724 0.722 conveni- ent 19.9969 17.615 0.389 0.701 methods overflow 19.7425 18.642 0.406 0.697 easy app 20.4720 17.815 0.422 0.692 online hardship 20.3135 16.952 0.552 0.662 mobile hardship 20.1905 16.479 0.573 0.655 forced 20.3614 17.939 0.411 0.695 Table 3. Reliability… NFC, wEaraBlEs and QR CodE in POS PaymEnts… 4545 Payment method Construct Observed variable Scale Mean if Item Deleted Scale Variance if Item Deleted Corrected Item-Total Correla- tion Cronbach’s Alpha if Item Deleted Cronbach’s Alpha n QR Usefulness wide- spread 17.0075 16.619 0.535 0.784 0.807 control over personal finance 16.7110 15.792 0.626 0.763 conveni- ent 17.0311 15.227 0.624 0.763 safe 16.7632 15.177 0.704 0.744 useful mobile 16.2564 18.521 0.437 0.803 mobile finance 16.5902 17.258 0.470 0.798 Ease of Use easy to use 20.1504 16.597 0.264 0.701 0.693 conveni- ent 19.7433 16.529 0.319 0.682 methods overflow 19.3459 16.969 0.391 0.663 easy app 20.0934 16.146 0.407 0.657 online hardship 19.9336 15.442 0.530 0.625 mobile hardship 19.7991 14.972 0.553 0.617 forced 19.9786 16.330 0.392 0.661 opinion_leader following trends 3.0222 1.171 0.536 – 0.697 advising others 3.4808 1.072 0.536 – S o u r c e : own study based on PayTchImpact.EU research. Table 3. Reliability… M. Borowski-Beszta, M. Polasik, A. Meler, A. Borowska-Beszta4646  Results Results Three ordered logit models were estimated for Intention to Use Payment Meth- ods dependent variables, each of the analyzed payment methods: NFC, weara- bles, and QR mobile payments. The results of the estimations are presented in Table 4. Model 1 for each method includes all the variables mentioned above in Table 2. Model 2 excludes variables from Group B, while Model 3 excludes vari- ables from Group B. The results confirm the role of traditional TAM model constructs – useful- ness and ease of use – as factors shaping the willingness to adopt new payment technologies. In each model variant for all three payment methods, Usefulness and Ease of Use are statistically significant and impact the Intention to Use these payment methods in the future within 12 months. These constructs determine the willingness to use of both NFC, as well as wearables and QR payments. In the case of all three tested payment methods, the Intention to Use them in the future positively correlates with the consumer’s self-perception as a per- son at the forefront of market changes (opinion leader). On the other hand, the social capital indicator, i.e., the level of trust in other people (trustful), is irrele- vant in the choice of any of the methods. It can be presumed that the motives for choosing such solutions do not arise from trust in other individuals because, in the social perception, they are based on technology rather than human factors. The lower emphasis an individual places on anonymity (anonymity), the greater the chance of using NFC in the future. However, the attitude towards anonymity does not play a role in the choice of wearables and QR codes pay- ments. This may be related to the fact that in the case of NFC, the connection between the payment method and cards, for which anonymity concerns also exist, is more visible (Borgonovo, Caselli, Cillo, Masciandaro & Rabitti, 2021; Wisniewski, Polasik, Kotkowski & Moro, 2024). Preference for reliable solu- tions (reliable) is positively associated with the choice of each method. Consum- ers who already use cloud solutions (cloud_user) and have no problem sharing their data with digital service providers (data_sharer) and use a greater num- ber of transportation and service mobile applications (apps_no) are more in- clined to use NFC, wearables, or QR codes in the future. NFC, wEaraBlEs and QR CodE in POS PaymEnts… 4747 Ta bl e 4. M od el s E xp la in in g th e In te nt io n to U se P ay m en t M et ho ds W ith in 1 2 M on th s N FC w ea ra bl es Q R M od el 1 M od el 2 M od el 3 M od el 1 M od el 2 M od el 3 M od el 1 M od el 2 M od el 3 Co of . Si g. Co of . Si g. Co of . Si g. Co of . Si g. Co of . Si g. Co of . Si g. Co of . Si g. Co of . Si g. Co of . Si g. U se fu ln es s 2. 01 ** * 2. 21 ** * 2. 00 ** * 0. 78 ** * 1. 02 ** * 0. 77 ** * 0. 71 ** * 0. 94 ** * 0. 70 ** * Ea se o f u se 2. 21 ** * 2. 45 ** * 2. 20 ** * 0. 65 ** * 0. 87 ** * 0. 64 ** * 0. 81 ** * 0. 97 ** * 0. 80 ** * op in io n_ le ad er 0. 20 ** * 0. 21 ** * 0. 50 ** * 0. 50 ** * 0. 49 ** * 0. 49 ** * tr us tf ul 0. 00 0. 00 0. 01 0. 02 0. 05 0. 05 an on ym ity 0. 08 ** * 0. 08 ** * 0. 00 0. 00 0. 03 0. 03 re lia bl e 0. 17 ** * 0. 18 ** * 0. 20 ** * 0. 21 ** * 0. 16 ** * 0. 16 ** * pe er _f ra ud _v ic ~ -0 .1 0 ** * -0 .1 0 ** * -0 .1 3 ** * -0 .1 3 ** * -0 .1 4 ** * -0 .1 3 ** * ap ps 0. 20 ** * 0. 21 ** * 0. 28 ** * 0. 29 ** * 0. 25 ** * 0. 25 ** * da ta _s ha re r 0. 08 ** * 0. 09 ** * 0. 18 ** * 0. 19 ** * 0. 15 ** * 0. 16 ** * cl ou d_ us er 0. 07 ** 0. 07 * 0. 38 ** * 0. 39 ** * 0. 34 ** * 0. 34 ** * ba nk _s to ra ge -0 .1 0 ** * -0 .1 1 ** * -0 .2 0 ** * -0 .2 1 ** * -0 .2 2 ** * -0 .2 2 ** * sh ar e_ co nt ac tle s -0 .4 0 -0 .4 5 0. 56 0. 44 1. 06 ** * 1. 02 ** * cv m _l im it 0. 00 0. 00 0. 00 0. 00 0. 00 0. 00 ge nd er 0. 21 ** * 0. 28 ** * 0. 13 ** 0. 28 ** * 0. 17 ** * 0. 31 ** * ag e 0. 00 -0 .0 1 ** * -0 .0 1 ** * -0 .0 2 ** * 0. 00 -0 .0 2 ** * M. Borowski-Beszta, M. Polasik, A. Meler, A. Borowska-Beszta4848 N FC w ea ra bl es Q R M od el 1 M od el 2 M od el 3 M od el 1 M od el 2 M od el 3 M od el 1 M od el 2 M od el 3 Co of . Si g. Co of . Si g. Co of . Si g. Co of . Si g. Co of . Si g. Co of . Si g. Co of . Si g. Co of . Si g. Co of . Si g. lo ca tio n -0 .0 1 0. 02 -0 .0 3 * 0. 03 * -0 .0 1 0. 05 ** * ed uc at io n 0. 09 0. 18 ** * 0. 03 0. 16 ** * -0 .0 6 0. 07 in co m e -0 .0 1 0. 00 -0 .0 2 * 0. 00 -0 .0 1 0. 01 cu t1 5. 57 ** * 5. 40 ** * 5. 27 ** * 4. 54 ** * 1. 98 ** * 4. 83 ** * 5. 38 ** * 2. 50 ** * 5. 36 ** * cu t2 6. 50 ** * 6. 30 ** * 6. 19 ** * 5. 53 ** * 2. 83 ** * 5. 82 ** * 6. 37 ** * 3. 37 ** * 6. 36 ** * cu t3 8. 27 ** * 7. 99 ** * 7. 96 ** * 6. 91 ** * 4. 00 ** * 7. 18 ** * 7. 84 ** * 4. 65 ** * 7. 82 ** * cu t4 9. 75 ** * 9. 42 ** * 9. 43 ** * 8. 35 ** * 5. 28 ** * 8. 63 ** * 9. 39 ** * 6. 05 ** * 9. 37 ** * M ea n de pe nd en t v ar 3. 43 3. 43 3. 43 2. 79 2. 79 2. 79 2. 77 2. 77 2. 77 Lo g- lik el ih oo d -5 ,9 33 -6 ,0 66 -5 ,9 41 -5 ,6 98 -6 ,1 62 -5 ,7 10 -5 ,7 80 -6 ,1 91 -5 ,7 86 Sc hw ar z c rit er io n 12 ,0 52 12 ,2 25 12 ,0 26 11 ,5 79 12 ,4 17 11 ,5 61 11 ,7 44 12 ,4 74 11 ,7 13 S, D, d ep en de nt v ar 1. 35 1. 35 1. 35 1. 39 1. 39 1. 39 1. 34 1. 34 1. 34 Ak ai ke c rit er io n 11 ,9 10 12 ,1 54 11 ,9 16 11 ,4 40 12 ,3 47 11 ,4 53 11 ,6 04 12 ,4 04 11 ,6 05 H an na n- Q ui nn 11 ,9 60 12 ,1 79 11 ,9 54 11 ,4 89 12 ,3 72 11 ,4 92 11 ,6 53 12 ,4 28 11 ,6 44 Ta bl e 4. M od el s… NFC, wEaraBlEs and QR CodE in POS PaymEnts… 4949 Ta bl e 4. M od el s… N FC w ea ra bl es Q R M od el 1 M od el 2 M od el 3 M od el 1 M od el 2 M od el 3 M od el 1 M od el 2 M od el 3 Co of . Si g. Co of . Si g. Co of . Si g. Co of . Si g. Co of . Si g. Co of . Si g. Co of . Si g. Co of . Si g. Co of . Si g. N um be r o f c as es ‘c or - re ct ly p re di ct ed ’ 2, 36 7 (4 9. 0% ) 2, 35 4 (4 8. 7% ) 2, 35 8 (4 8. 8% ) 1, 70 2 (4 0. 4% ) 1, 49 6 (3 5. 5% ) 1, 70 0 (4 0. 3% ) 1, 71 2 (4 0. 5% ) 1, 45 5 (3 4. 4% ) 1, 72 4 (4 0. 8% ) Li ke lih oo d ra tio te st : Ch i-s qu ar e (1 8) = 3 ,7 73 .0 5 [0 .0 00 0] (7 ) = 3 ,5 06 .8 [0 .0 00 0] (1 3) = 3 ,7 57 .1 1 [0 .0 00 0] (1 8) = 2 ,6 76 .7 1 [0 .0 00 0] (7 ) = 1 ,7 47 .4 4 [0 .0 00 0] (1 3) = 2 ,6 53 .0 1 [0 .0 00 0] (1 8) = 2 ,4 96 .2 8 [0 .0 00 0] (7 ) = 1 ,6 74 .4 3 [0 .0 00 0] (1 3) = 2 ,4 84 .6 9 [0 .0 00 0] n 4, 82 9 4, 21 4 4, 22 5 S o u rc e : o w n st ud y ba se d on : P ay Tc hI m pa ct .E U re se ar ch . M. Borowski-Beszta, M. Polasik, A. Meler, A. Borowska-Beszta5050 Personal experiences with fraud related to the use of modern technologies (peer_fraud_victim) have a significant and statistical negative impact on the willingness to use the tested payment methods in the future. Individuals who feel that their personal data are secure only when banks store them (bank_stor- age) will have less inclination to use new payment methods in the future, and this influence is statistically significant. Trust in banks is thus a factor inhibit- ing the development of mobile payments; however, this indicator can be consid- ered an indirect measure of technological conservatism. In countries where the share of contactless transactions (share_contactless) is smaller, there is a statistically significant positive attitude towards using QR technology in the future. This is evident because QR may be perceived as a desirable technology in these markets with underdeveloped payment infra- structure, similar to the case of mobile payments in Kenya (Van Hove & Dubus, 2019). On the other hand, the prevalence of contactless terminals in other coun- tries may render the introduction of QR codes for payments unnecessary. It should be noted that since 2020, all payment terminals in Europe that support Mastercard and Visa cards have been required to support contactless technolo- gy. Consequently, the acceptance network for NFC payments is extensive. These findings confirm the influence of external network effects on the payment ser- vices market. Such effects amplify interest in widely adopted technologies with an established acceptance network in this context. Conversely, for less preva- lent solutions, such as QR codes in Europe, network effects pose a barrier to growth (Johnson, 2019; Van Hove, Polasik & Kotkowski, 2024). In the case of each tested technology, men (gender) are more willing to use them in the next 12 months. This observation aligns with other studies in the area of attitudes toward new technologies for women and men (Chen & Shih, 2014; Venkatesh & Morris, 2000). The age factor achieves statistical signifi- cance only in Model 2, where variables related to attitudes and digital inclusion are not considered. It can be concluded that age is not a factor conducive to the Intention to Use NFC, wearables, and QR codes in the future; rather, it is a vari- able related to digital inclusion associated with age. A similar relationship oc- curs in the case of having a higher education (education), where it is statistically significant in the demographic model but not in the full model because, as we can assume, variables related to digital inclusion are associated with educa- tion. Therefore, the group on which the development of mobile payments will be based in the near future consists of young, better-educated individuals, dig- NFC, wEaraBlEs and QR CodE in POS PaymEnts… 5151 itally engaged in areas such as cloud solutions or service applications, perceiv- ing themselves as opinion leaders.  Conclusions Conclusions Mobile financial technologies undoubtedly already play an essential role in the social lives of European consumers. Within Everett Rogers’s theory of inno- vation diffusion (Rogers, 2003), not only payments via wearables and QR, but also NFC payments, are at the early adopters stage. We can undoubtedly talk about well-prepared ground for the next phase of the early majority. The re- search showed a potential for developing mobile services in the European mar- ket, both for NFC mobile payments and wearable devices, which are currently equipped with NFC antennas and QR code payments with optical interfaces. However, the market space is not equal for the tested payment methods. Ac- cording to the respondents’ declarations, NFC mobile payments have the high- est potential for dynamic growth in the near future. Convincing consumers of their usefulness and ease of use proves to be cru- cial for all three mobile payment methods. However, the popularity of selected payment methods is determined not only by factors from the TAM model, such as Perceived Usefulness and Perceived Ease of Use. The determinants of the interest in mobile payments are complex – consumers with knowledge about mobile payments may be more willing to use them; therefore, educating con- sumers in digital finance is very important. It remains unclear whether mobile payments will contribute to reducing financial exclusion, as observed in Asia and Africa (Senyo & Osabutey, 2020; Zhang, Zhang & Gong, 2022), or if they will primarily cater to the most technologically advanced social groups, limit- ing their positive impact. The choice of a specific payment technology by consumers is strongly in- fluenced by the availability of payment acceptance infrastructure at points of sale. Currently, in Europe, contactless payments and wearables hold a signifi- cant advantage due to the high density of contactless payment terminals in most countries. This generally has a negative impact on the adoption of QR code payments. It should also be noted that this study did not include local mobile payment systems that were not widely used in physical points of sale at the time of the survey. This pertains particularly to alternative systems such as BLIK in Poland, Swish in Sweden, or Bizum in Spain. In the future, their devel- M. Borowski-Beszta, M. Polasik, A. Meler, A. Borowska-Beszta5252 opment holds significant potential to reshape the mobile payments landscape in Europe. Similarly, the growth of the Wero mobile wallet under the European Payments Initiative (EPI) could have a comparable transformative impact (Ja- cob, Burelli, Großkurth, Kasch, Bunge & Büttner, 2024). Therefore, the issue of financial inclusion, the impact of network effects, and the development of alter- native mobile payment systems remain prospective topics for future research. The above research results may have some limitations due to the fact that the survey was conducted in the second half of 2020. However, there are sev- eral factors that make the obtained results still relevant to the situation on the retail payments market. Firstly, from the time of the survey to the pre- sent, no new mobile payment method has appeared in Europe. Therefore, the NFC, wearables, and QR code technologies studied remain the only ones wide- ly available for payments at physical points of sale. 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