2.1. Methodology of the Qualitative Research
After reviewing the literature, we decided to use a qualitative research method to explore the research topic from the perspective of a defined scientific gap.
The aim of the study was to analyze current customs and opinions regarding payment methods, as well as to identify threats and opportunities for new biometric solutions in this area. Based on the process of studying literature, as well as the author’s own observations regarding the biometric market and its participants, we were able to formulate research questions:
As a method of qualitative studies, we chose the FGI (focus group interview)—a well-known technique for collecting data in social sciences, which consists of conducting collective in-depth (semi-structured) intelligence in groups of 4–9 people (depending on the research area and organizational capabilities). We decided to focus on the newest form of biometric usage, which is iris-based biometrics (for now only available in Poland as a pilot project). We decided to choose this particular case because of its innovative nature and the effect of fresh opinions. A total of 4 focus groups meetings were conducted (November−December 2019), the shortest of which lasted 2.5 h and the longest almost 4 h. The participants were of different age groups, from different localities (both residents of small towns and big cities), and of different ages (the youngest was 17 and the oldest 74).
Focus I—4 women and 5 men predominate in focus groups;
Focus II—3 women and 3 men;
Focus III—5 women;
Focus IV—4 women and 3 men.
In conclusion, the gender differences in the focus studies conducted were as follows: 16 women and 11 men, for a total of 27 people. They were from different professions and lifestyles—high school students, housewives, secretarial managers, accountants, office workers (4 participants), sales, lawyers, entrepreneurs (3 participants were from businesses). All groups were surveyed without showing any type of biometric devices (no biometric payment tools).
According to the focus group participants, there were no apparent flaws in the current payment system (notably, this generation uses a card and a smartphone). There was enthusiasm about using smartphones as a payment option, especially among the younger generation. All participants stressed that biometric solutions are associated with risks of data leakage, health risks, “data hacking”, etc. The visualization of the most frequent word used in relation to eye biometrics during the focus research, marked by emotion, was definitely the word “fear”.
After the focus study, without the demonstration of a biometric device (iris-based), two focus studies with the demonstration of an identification device were conducted. After observing the first set of focus groups, we decided to divide the subsequent groups according to gender categories, as we noticed that due to the stereotype of a wider knowledge of technological issues in the male group, women kept their opinions to themselves and were not very open to sharing their thoughts. Due to this, the first meeting was a women-only meeting. These women represented different ages and professional categories:
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Economics student—master’s degree;
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Employee of a creative agency;
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So-called housewife, however, conducting business;
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Accountant;
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Cashier;
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Management student;
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Bachelor’s degree/at the same time waitress;
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Administrative employee of a small company (staff).
The age gap of the participants of the study (focus group) was 21–56 years old.
The first phase of the study looked similar to previous audio meetings: the issues of making payments, stressors, annoying and unpleasant payments were discussed (mainly queue times, breathing on the back of other customers, and lack of hygiene, whether using cash or card, “system jams”, “internet crashes”, and similar problems).
Participants declared that they mostly paid by card (plastic or smartphone) or cash. Another element of discussion was biometrics and their approaches to the use of biometric solutions in payments. In this area, there was a fairly strong element of doubt about biometric solutions, with survey participants associating them with gaining access to their accounts, and therefore lack of security surveillance, the possibility of copying fingerprints, and more than half of the survey participants stated (which was also important in this part) that they did not use biometric features at all and usually paid by card or cash, and used a code to identify themselves on their laptop or smartphone.
In the next part of the study, biometric equipment was presented. After a brief presentation, participants were encouraged to “encode” their eye on the device, which they were rather reluctant to do and even stressed about whether something could happen to their eyes.
In the next round, participants were able to check how the equipment recognized their iris. This step was welcomed more positively, although it must be said it was not met with great enthusiasm.
The final element was a discussion of other possible uses of the equipment. It is worth noting that participants strongly emphasized the health aspect—concerns were raised about the impact of eye scanning on health.
After the study, which took place with a female group, only male participants were intentionally invited to the second meeting. The format of the second focus group (except for different participants) was identical to the format of the stages (including the presentation of the device) in the female group. A total of eight participants, aged 21–54, representing different professions and industries took part in the second study:
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Aviation/own business;
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Film production;
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Economics student;
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Management student/bank employee;
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Management representative;
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Marketing director in a large international production and trading company;
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Construction worker;
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Rock musician.
There were noticeable differences in the observations in this male group compared to the female group, the most important being:
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No strong emphasis on health and hygiene aspects;
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No problem with searching for their wallet, phone, card in their pockets (for objective reasons) as aspects of everyday life.
2.2. Methodology of the Quantitative Research
A survey was conducted in order to verify and extend the main results of the qualitative research and the observed dependencies. A questionnaire was prepared during a brainstorming session based on the results of qualitative research and the authors’ own observations. A pilot survey was used to verify this model. The sample size was planned for a minimum of two hundred respondents, and social platforms were selected as the distribution channel for the questionnaire. For the pilot study, the respondents were not selected randomly, but the aim was to find representatives of working age for the sample. A list of analyzed items in the questionnaire is presented in the
Appendix A of
Table A1.
The statistical analysis was based on measures of dependence between the variables: mainly on the correlation matrix, and also on cross tables, e.g., for binary variables. Exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) were used for the groups of questionnaire items, and for the variables grouped by EFA, a reliability analysis was performed using the Cronbach’s alpha coefficient. Dependencies between constructs based on a linear correlation matrix were analyzed using path analysis within a structural equation model (SEM) to verify the significance of direct and indirect causality.
Due to the indicated research area, on which the research presented in this article focuses (biometric innovations in the payment sector), the model of hypothetical dependencies was based on the analysis of literature studies, including the presented UTAUT model, as well as qualitative research conducted by researchers. Such research procedures made it possible to derive and consequently define a new, proprietary model of hypothetical dependencies, which is presented in
Figure 8. Our own observations and conducted qualitative research on the perception of biometric payments using the iris of the eye (BP) allowed us to prepare a set of hypotheses that lead to the acceptance model of BP verified in this study. The observation about the strong influence of consumer age on BP acceptance is due to the fact that age is the main exogenous variable in the first stages of diffusion of this type of innovation. Thus, age is not only an impact moderator, but also a primary predictor. The main target variable is the behavioral intention to accept and use BP (but not yet recommend BP due to the novelty of the technology), as described in the literature models.
During the process of discussion, we formulated direct causes between variables, marked with arrows in
Figure 8. The directions of the relationships between the variables of the model are presented in
Table 1 together with the content of the hypotheses.
The measurements of variables were constructed from questions presented in the
Appendix A of
Table A1. Predicted behavioral intention to accept and to use BP was measured as the sum of binary items numbered 18 and 19a–19d from
Table A1. Three variables are measured with only one question:
- (1)
Self-reported perceived safety (item 9) was understood as the inverse of perceived risks from the model shown in
Figure 7;
- (2)
Self-reported attitude towards BP (item 8) was understood as one of the main mediators predicting behavioral intention to accept and to use BP, rather shaped by other predictors and not initially trust (component of the model) presented in
Figure 7;
- (3)
Replacement in future (item 20) was a stated belief about payments that may also be shaped by unmeasured science fiction in literature and films.
The three variables from the UTAUT model (perceived ease of use, perceived usefulness, and facilitating conditions) were considered during the preparation of the questionnaire as combining into a single latent variable called perceived use and facilitating conditions, measured as the sum of items 21–26 from
Table A1. Importance of innovative payments was measured by the sum of items 3 and 4; not only biometric payments in their initial use in society (in real shops), but also mobile payments (e.g., codes generated in banking applications used mainly online in online shops), contrasting with traditional cash payments and the very popular card payments. Fear about personal data was measured as the sum of items 10–12 from
Table A1 and is understood as concern about data privacy from
Figure 7. Fear of barriers in life was measured as the sum of items 13–17, understood as social problems (the inverse of social influence from the UTAUT model or social incompatibility used as inverse in the DOI theory shown in
Figure 7). Knowledge and experience was measured as the sum of binary items 5 and 7a–7d and shows respondents’ acquired knowledge of BP. By constructing the model shown in
Figure 8, discussing what is cause and what is effect, the direction of the hypotheses shown in
Table 1 was decided. Comparing
Figure 8 with the model shown in
Figure 7, the only thing missing from the model in
Figure 8 is the perceived innovativeness of biometrics, but this was evident for payments. Statistical software Statistica 13.3 [
48] was used to analyze the collected survey data to assess the measurement of latent variables and to verify the hypotheses.