Wearables technology or wearable devices are a type of miniaturised electronic components, sensors or computers inserted into clothing or other wearable accessories (Wright & Keith, 2014). Examples of such devices on the market include smart watches, smart wristbands, smart jewellery, smart clothing, smart clips, smart contact lenses, smart specialised sensors, smart tattoos (Piątek, 2018) or even smart chips that are subcutaneous (The Economist, 2018) or implanted in the brain (Reuters, 2022). These devices are used to measure physical or physiological parameters and to make calls, read messages, record audio, video or even pay, among other things (The Economist, 2022; The Times of India, 2020).

According to estimates by Activate Consulting, the market for wearables and connected fitness equipment will reach US$28.6 billion in the United States in 2026 (Activate, 2022), while IDC predicts that there will be more than 637.1 million such devices worldwide in 2024 (Brown, 2020).

Considering the above market potential, the objective of this study was formulated, which is to identify the level of consumer trust towards wearables technology. The authors additionally assessed the relationship and its nature for selected factors, such as techno-paranoia, techno-fear and narcissism, which may determine this level of trust and examined that gender can moderate that effect.

Theoretical Context

The literature review was prepared on the basis of the SCOPUS database, for the phrases 'paranoia’, 'fear’, 'narcissism’, 'determinity’, 'wearables’ and 'trust’. Due to the different number of indications for the different configurations of the mentioned words, the authors decided to use a nested search and the expression finally had the form (TITLE-ABSKEY ((((„paranoia”) OR („fear”) OR („narcissism”) OR („determinants”)) AND („wearables”) AND („trust”)))) OR (TITLE-ABS-KEY(((„determinants”) AND („wearables”) AND („trust”)))) OR (TITLE-ABS-KEY((((„paranoia”) OR („fear”) OR („narcissism”) OR („determinants”)) AND („wearables”)))) OR (TITLE-ABS-KEY((((„paranoia”) OR („fear”) OR („narcissism”)) AND („wearables”)))). The search algorithm returned 78 results. The subsequent search narrowed the results to the following subject areas: Computer Science, Business, management and Accounting, Social Sciences, Economics, Econometrics and Finance and Psychology, and to papers in English, and 37 records were finally obtained.

The first paper was published in 2011 (Graph 1). The next one was published in 2016 (five papers), with subsequent papers published annually. Looking at the chart below, there are some fluctuations in the number of these publications from year to year, with a slight upward trend.

Analysing the works searched for keywords, it can be seen that the most recurring phrase was 'electronic wearables’ (Figure 1).

Other occurring keywords were 'health data’, 'fear’, 'stress’, 'tracking position’, 'technology acceptance’, 'self-concept’ or even 'technology assessment’. By categorising the keywords presented, the following groups of words can be distinguished: those relating to technology, health and sport, psychology and marketing and fashion.

In founded papers, wearables technology has been described from the perspective of determinants such as wearability, ease of use, compelling design (aesthetics as well as attractiveness), functionality, price (Karahanoglu & Erbug, 2011), technology adaptation (Al.-Emran et al., 2022; Askari et al., 2018; Nascimento et al., 2018; Pancar & Ozkan Yildirim, 2021; Schamberger & Nieroda, 2017; Sulkowski & KaczorowskaSpychalska, 2021; Wild et al., 2017), trust in technology (Gao et al., 2016), safety of use, fear, phobia or paranoia related to technology (Aksoy et al., 2020; Catherwood et al., 2015) and stress (Clusiault et al., 2022; Viegas et al., 2018).

The technology has also been described as a medium of integrity for blind and visually impaired people due to its ability to identify emotions such as fear, joy, surprise, anger, sadness and disgust based on facial expressions, and the possibility of haptic communication with users to facilitate daily life (Buimer et al., 2016). Other areas mentioned for the use of wearables were healthcare (Gao et al., 2016; Lim et al., 2019), sports (Saliba et al., 2021), in particular cycling (Kräuter et al., 2016) and climbing (Mencarini et al., 2016), psychology and psychiatry (Ortiz et al., 2017), and the technology component of the Internet of Things ecosystem (Albesher & Alhomoud, 2020).

Techno-Fear, Techno-Paranoia and Narcissism vs. Technology

Techno-fear is 'an unpleasant feeling of fear that an individual experiences in the presence of technology when it may be perceived as a threat to their existing norm’ (Khasawneh, 2018). Techno-paranoia, on the other hand, is explained as 'the unwarranted fear and distrust an individual has of technology that leads them to avoid that technology, their fear and avoidance of technology may not be supported by evidence or facts’ (Khasawneh, 2018) and 'people with paranoid behavior are suspicious’ (Von Gemmingen et al., 2003) in this case the suspicion may be about the intention of the technology and its safety. Narcissism, on the other hand, is 'a personality trait reflecting a grandiose and inflated self-image’ and is characterised by an 'unrealistic positive self-image’ (Buffardi & Campbell, 2008). Techno-fear or techno-paranoia are treated as critical determinants of modern technology acceptance and trust (Lee et al., 2018). In terms of the relationship between narcissism and technology, this relationship was addressed in the work of Rosen et al. (2013), where a team of researchers suggested that the rise of narcissism is due to advanced technology and easy access to it. Pearson and Hussain (2015), on the other hand, showed that there was a significant positive relationship between narcissism and technology addiction (using smartphones as an example), which meant that the higher the level of narcissism, the higher the propensity to become addicted to it. Based on the aforementioned, the following research questions were formulated:

• RQ1 – What differences in trust in wearables technology exist for the different types of wearables in the study group?
• RQ2 – Which of the studied predictors (techno-paranoia, techno-fear, narcissism) determine trust in particular types of wearables?

Methods

For the purposes of the study, wearables were divided into three categories: non-invasive technologies, that is, technologies that are worn on the body without interfering with it, for example, a smart watch or a smart band; indirect/emergent technologies – these are devices that interfere with the human body in some part, but are mostly on the outside, for example, a glucose sensor that is glued to the skin with a special patch while a needle is placed in the skin; invasive technologies, which are placed under the skin entirely or on internal organs.

Procedure

The survey was conducted using an online survey technique supported by an online version of the questionnaire prepared in the MS Forms software environment. The process of data acquisition lasted from November 2022 to January 2023. Individuals for the study were selected purposively, the criterion for selection being the age of the respondent. The authors focused mainly on young people, due to their possession of relatively higher technological competence in contrast to representatives of other age groups (GUS, 2020). A total of 218 respondents took part in the survey. Six questionnaires were rejected due to deficiencies and errors in the responses. Therefore, 212 questionnaires were analysed.

Research Sample

In the sample – 212 individuals – the majority were female (66%). The average age of respondents was M = 21.38 years (SD = 2.77 years); 85.9% of respondents declared their material situation to be good or average (43.9% and 42%, respectively). Only 3.3% of respondents considered their material status as very good. The rest – 10.8% considered the conditions in which they live as bad or very bad (9% and 1.9%, respectively). Slightly more than half of the respondents – 50.9% combine their studies with work, with the remainder (49.1%) declaring only studying.

Measures

Trust in wearables

Trust in wearables technology in terms of non-invasive, indirect and body-invasive was measured using a trust scale adapted from Shao et al. (2020) and Pavlou and Gefen’s (2004) work. The construct consisted of three statements – items to which respondents had to respond according to a scale from 1 to 7, where 1 meant – 'strongly disagree’ and 7 meant – 'strongly agree’. The construct was measured separately to each of the three subgroups of wearable devices.

Techno-paranoia

The scale measuring the level of techno-paranoia was borrowed from the work of Khasawneh (2018). It consisted of five items/statements (such as 'It scares me that technologies will change the way we live, communicate, love and even judge others’ or 'I am afraid of new technologies because one day it will make us (people) obsolete’), to which respondents were asked to relate on a 7-point scale, where 1 meant – 'strongly disagree’ and 7 meant – 'strongly agree’.

Techno-fear

Fear of technology was measured using a borrowed scale from the work of Khasawneh (2018). The construct consisted of five items/statements (such as 'I am afraid of new technologies because if something goes wrong with them (if they stop working for some reason), we will go back to the 'Stone Age’ or 'I am terrified of being connected to the Internet, someone might follow me.’), to which respondents referred on a proposed scale from 1 to 7, where 1 meant – 'strongly disagree’ and 7 meant – 'strongly agree’.

Narcissism

The narcissism scale (Narcissistic Personality Inventory [NPI]-13) was borrowed in a shortened version (13 items) from the work of LachowiczTabaczek and Kozłowska (2021). Respondents had to address 13 statements on a 7-item scale, where 1 meant – 'strongly disagree’ and 7 meant – 'strongly agree’.

Results

In the first part of the survey questionnaire, respondents were asked about their knowledge of both the wearable device phenomenon and the different types of wearable devices (Table 1).

According to Table 1, 91.5% of respondents claim to be familiar with wearables. However, when it comes to the specific types of such devices, the most familiar among respondents are the smart watch (97.6%), smart wristband (76%) and smart glasses (56.7%), while the least familiar are smart earrings (embedded in the skin) (8.2%), smart contact lenses (10.1%) and smart tattoos (11.5%).

Respondents were then asked to refer to the use or declaration of future use of these devices (Table 2).

It was found that in the case of non-intrusive technologies, as many as 62.3% of respondents declared using them, while 29.7% declared a desire to use them. The remainder – 8% of respondents, neither used nor expressed a desire to use non-invasive wearables technologies.

For indirect technologies, only 4.7% of respondents declared use, 42.5% expressed willingness to use while the rest of the respondents (52.8%) did not use and declared no willingness to use. None of the respondents used invasive technologies, but more than one in five respondents (28.8%) declared a desire to use such wearables. In contrast, the remainder (more than 71%) had not used and were not willing to use such devices. It is therefore clear that the lack of willingness to use a particular type of technology is greater, as the technology’s intrusion into the body increases.

The next part of the survey asked respondents about their level of trust in different types of wearable technology. Due to the borrowing and adaptation of the trust scale for the survey, the authors performed an exploratory factor analysis (EFA) using the (PCA) method to verify its dimensionality and analysed its reliability based on Cronbach’s a coefficient. These analyses were performed for each group of wearable devices (non-invasive, indirect, invasive). The results of these analyses are presented in Table 3.

EFA, exploratory factor analysis

Based on the above results, it can be seen that the KMO measure of sampling adequacy indicates values above 0.7 da for each of the three constructs studied. A level of 0.6 is usually taken as the critical threshold from which values are considered as acceptable (Sagan, 2004). The next step, according to the Kaiser criterion, was to check the eigenvalues for the examined factors that exceed one. For each of the three examined constructs, there was only one such property – for construct one (Trust in wearables – non-invasive technology subgroup) – it explained 85.56% of the variance, for construct two (Trust in wearables – indirect technology subgroup) – it explained 88.29% of the variance and for construct three (Trust in wearables – invasive technology subgroup) – it explained 93.81% of the variance. Thus, on the basis of the EFA conducted, the unidimensionality of the scales studied was confirmed. The reliability of the tested constructs takes values above the threshold of 0.6, which is characteristic of scales with high reliability (Sagan, 2004).

In the case of the other scales, the authors borrowed them without any adaptation, so that only an analysis of their reliability was carried out. The techno-paranoia scale had a reliability of Cronbach’s α = 0.705, the techofear scale had a reliability of Cronbach’s α = 0.670 and the narcissism scale had a reliability of Cronbach’s α = 0.855.

The next step of the analysis was to identify and compare the average trust in the different types of wearable devices in the study group. The results are presented in the Graph 2.

In order to determine the significance of differences between the different types of wearables technology, a one-way ANOVA with repeated measures was performed. The analysis was preceded by verification of assumptions such as analysis of the normality of the distribution of the dependent variable in the subgroups studied (skewness and kurtosis were between 2 and –2, which are characteristic of normal distributions (George, 2011)) and sphericity as measured by the Mauchly test (the sphericity test turned out to be significant for values of p < 0.001, so the values of the F statistic were corrected based on the Greenhouse-Geisser correction). Confidence values were found to be significantly different in the subgroups studied and the effect was strong F(1,873; 395,171) = 216.295; p < 0.001, eta2 = 0.506 (main effect). Post hoc tests showed that the mean confidence in non-invasive technologies (M = 5.44; SD = 1.24) was significantly different compared with the mean confidence in indirect technologies (M = 3.99; SD = 1.42; p < 0.001) and invasive technologies (M = 3.34; SD = 1.63; p < 0.001) and between indirect and invasive technologies (p < 0.001). Thus, we found that for technologies that are more intrusive to the body, the mean confidence values are significantly lower than for non-invasive technologies.

To assess which factor (techno-paranoia, techno-fear or narcissism) determines trust in each type of technology, the authors conducted a linear regression analysis. The regression analysis was preceded by verification of the normality of the distribution of the predictors based on the values of the skewness and kurtosis statistics. All values fell within the range of –2 to 2, which is characteristic of variables characterised by a distribution close to a normal distribution (George, 2011).

The first regression model was a model with a dependent variable – trust in non-invasive technologies. The result of the analysis is presented in Table 4.

The model tested proved to be significant and a good fit to the data F(3, 208) = 14.915; p < 0.001. It turned out that in the case of trust in noninvasive technologies, the higher the trust the lower both the level of techno-paranoia (beta = –0.170; t(208) = –2.091; p = 0.038) and technofear (beta = –0.303; t(208) = –3.682; p < 0.001). Narcissism proved to be a statistically insignificant determinant t(208) = 1.579; p = 0.116.

In the next model, the dependent variable was confidence in indirect technologies (Table 5).

The model tested proved to be significant and a good fit to the data F(3, 208) = 9.207; p < 0.001. It was found that for trust in indirect technologies, the higher the trust the lower the level of techno-paranoia (beta = –0.334; t(208) = –3.964; p < 0.001). Techno-fear (t(208) = –0.238; p = 0.812) and Narcissism (t(208) = 0.665; p = 0.507) proved to be statistically insignificant determinants.

The model tested (see Table 6.) proved to be significant and well fitted to the data F(3, 208) = 8.108; p < 0.001. It was found that for trust in invasive technology, the higher the trust the lower the level of technoparanoia (beta = –0.294; t(208) = –3.964; p < 0.001). Techno-fear (t(208) = = –0.543; p = 0.588) and Narcissism (t(208) = 1.571; p = 0.118) proved to be statistically insignificant determinants.

Concentrating on the identified significant relationships between the studied determinants and trust in each of the presented forms of wearable devices, it was examined what might moderate these relationships. Most often, technology-related research examines gender differences in the context of, for example, online shopping (Awad & Ragowsky, 2008; Gefen et al., 2003; Pengnate & Sarathy, 2017), e-commerce (Fang et al., 2014; Riedl et al., 2010), virtual communities (Ridings et al., 2002; Wu et al., 2010) or mobile social networking service (Gong et al., 2015).

Moderated linear regression analysis was used to test for differences in the relationships studied. The PROCESS macro (version 4.1; model 1; Hayes, 2022) was used. A significant interaction effect between gender and techno-paranoia on trust in non-invasive devices was observed (b = 0.295, SE = 0.1421, t = 2.078, p < 0.05, LLCI = 0.015, ULCI = 0.576).

Post hoc tests indicated that (see Graph 3) for men, low levels of technoparanoia were associated with greater trust in non-invasive technologies (b = –0.557, SE = 0.119, t = –4.693, p < 0.001, LLCI = –0.791, ULCI = –0.323). Thus, men with low levels of techno-paranoia indicated greater trust in non-invasive technologies than men with mid- and high levels of technoparanoia. A similar effect was seen in women (b = –0.262, SE = 0.078, t = –3.347, p = 0.001, LLCI = –0.416, ULCI = –0.108). Women with low techno-paranoia had higher levels of trust in non-invasive technologies than women with mid- and high techno-paranoia. It was additionally noted that the decrease in trust when the level of techno-paranoia increased was more dynamic in men than in women. At low levels of techno-paranoia,men have higher levels of trust in technology than women. This situation changes as the level of techno-paranoia increases; at mid-level, trust in technology in men is lower than in women, and the same situation is observed in those with high levels of techno-paranoia. For indirect technologies, no interaction effect was observed between gender and techno-paranoia. Focusing on invasive technologies such as subcutaneous chips, a significant interaction effect was noted between gender and technoparanoia and trust in this type of technology (b = 0.480, SE = 0.188, t = 2.546, p < 0.05, LLCI = 0.108, ULCI = 0.851).

Conducted post hoc tests indicated a similar nature of the relationship that existed for non-invasive technologies. As techno-paranoia increases, the trust in invasive technologies decreases for both men (b = –0.744, SE = 0.157, t = –4.728, p < 0.001, LLCI = –1.054, ULCI = –0.434) and women (b = –0.264, SE = 0.104, t = –2.550, p < 0.05, LLCI = –0.468, ULCI = –0.060). In addition, it can be seen that at low techno-paranoia, men have more trust in invasive technologies than women. However, this situation changes as techno-paranoia increases, and at mid- and high levels, trust in this type of technology is higher in women than in men (see Graph 4).

Discussion and Conclusion

Regarding the formulated research questions for the first one – the level of trust differs significantly for the different types of this technology. The respondents have the highest average trust values, that is, the highest trust, in relation to non-invasive technologies, and the lowest in relation to technologies that invade the human body.

Referring to RQ2, it was found that narcissism did not statistically determine trust in each type of wearables technology. Techno-fear proved to be a significant determinant only for non-invasive technologies (the higher the trust, the lower the techno-fear value). Techno-paranoia, on the other hand, proved to be a statistically significant determinant for trust in each of the technology types tested. The higher the level of trust, the lower the level of techno-paranoia.

The results of the conducted study show that techno-fear and technoparanoia significantly (negatively) determine the level of trust. The reason for this may be that respondents may be afraid of the device itself interfering with the body, losing data security, possible damage to the device inside the body or simply never having used the device. Such a fear effect can be reduced by, for example, providing opportunities for more frequent contact with the technology in question or better education on its use (Agha & Saeed, 2015; Aksoy et al., 2020; Sherrill et al., 2022).

Considering the significant interaction effect of gender and technoparanoia in relation to trust in wearables technology, it can be seen that as concern about technology (techno-paranoia) increases, trust in technology (both invasive and non-invasive) decreases, and this effect is stronger for men than for women. It can also be noted that men and women differ in terms of trust in technology at different levels of techno-paranoia. Higher levels of trust at low levels of techno-paranoia may be explained by the fact that men are generally more technologically advanced than women (Goswami & Dutta, 2015). This situation was the case for both non-invasive and invasive technologies. With regard to the trust variation in the case of increased techno-paranoia, it appears that men are more prone to paranoia and paranoid behavior than women (Millon & Davis, 1996; Sperry, 1996; Von Gemmingen et al., 2003), which may cause men to be more suspicious (Von Gemmingen et al., 2003) of wearables technology, for instance, which in this case may be related to a much greater decrease in trust in this type of technology than in women.

The limitations of the present study are certainly the purposive nature of the sampling and its size, which makes it impossible to generalise the results to the entire general population. It is also worth noting that the group is of similar age. Future research should pay attention to what the trust issue is for the other age groups and whether there are similar relationships in terms of the dependent variables studied. It is also worth investigating whether the moderating effect of gender also occurs in other age groups and considering other demographic and psychographic variables.

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Social media is a phenomenon that has modified the ways people around the world interact and communicate (Edosomwan et al., 2011). More than half of the world’s population (59.4%) use social media, making a total of 4.76 billion users, while in Poland it is 66,3% of the total — 27.5 million residents (DataReportal, 2023).

What has made social media so popular among users is convenience, enjoyment and access to information (Chai & Kim, 2012). Social networking sites (SNS), such as Facebook, Instagram, YouTube, etc., are an integral part of social media and one of the fastest-growing uses of the Internet today (Omar et al., 2014). Society uses social networks for entertainment, to create and maintain relationships, to connect with others with similar interests or hobbies, or to fill free time (Marino et al., 2016; Ryan et al., 2016). Nowadays, in many cases, social media are replacing traditional forms of communication such as calling or e-mailing (Sigurdsson et al., 2021). The data also show that social media are engaging users around the world, who spend an average of 2 hr and 31 min a day, while for Polish residents, it is 2 hr and 2 min (DataReportal, 2023). Social media users use their favourite platforms because they want to stay in touch with relatives and friends, fill their free time, read news, find interesting content and be up to date. Alongside these reasons, they indicate a desire to find shopping inspiration or just to make purchases (DataReportal, 2023). One of the tools used to respond to users’ purchasing needs is influencer marketing-an extremely popular type of advertising that uses an opinion leader-an influencer. It was chosen to concentrate on this form because 66% of consumers say they trust shopping recommendations from family, friends or influencers. At the same time, only 33% trust brand recommendations (Celestino, 2023).

Moreover, it is decided to focus on the beauty industry, because beautyrelated content is one of the biggest and fast-growing industries across all social media platforms (Van Kessel et al., 2019). Also, an analysis was performed on two-of the most relevant-social media platforms for the beauty field:

• YouTube, because according to the data, beauty-related videos (about makeup and cosmetics) are the most popular content category for females on YouTube (Petrov, 2023).
• Instagram, because there is the second largest number of beauty influencers on this platform (after those addressing lifestyle topics; Statista, 2021). Moreover, Instagram is one of the fastest-growing platforms with the highest engagement from social media users (Phua et al., 2017).

Furthermore, on both Instagram and YouTube, 'makeup’ is the most used hashtag, which also indicates a huge interest in beauty topics (Geyser, 2022). Also, Instagram and YouTube are the most common combination of platforms for beauty influencers. The majority of beauty influencers are active on both platforms (Industry Report — Beauty Brands, n.d.). Taking into consideration, the aforementioned information and the literature review, the objective of the article was formulated, which is to compare consumers’ preferences towards activities and content, published by beauty influencers on Instagram and YouTube platforms.

To achieve the objective, the paper was based on primary and secondary sources. The former was obtained through an empirical study, using a survey method, of a sample of 146 individuals. The latter included a review of scientific articles from the SCOPUS database, industry reports and articles.

Literature Review

Influencer marketing is a form of marketing that allows brands to have commercial partnerships with selected social media influencers, thereby addressing the influencer’s community and the collaborating brand’s content (Lou & Yuan, 2019). Influencer marketing has become an indispensable part of digital marketing strategy that enables reaching out to target customers (Kim & Kim, 2021). According to the Influencer Marketing Hub report, the market of influencer marketing reached $16.4 billion in 2022, an increase of $2.6 billion (so 19%) compared with the previous year.

Influencers are individuals who are active on social media and influence their audience, fans, etc. through the content they add on social media platforms (Vodák et al., 2019). Beauty influencers focus specifically on creating beauty content and promoting beauty products or brands. Tran, Rosales and Copes define a beauty influencer as an aesthetic expert who provides teaching on topics of enhancement (life, health, style, etc.) and beautification practices (Tran et al., 2020).

Beauty influencers are eager to use social media platforms to share the content they create and to promote many of their own products as well as brands that collaborate with them. The beauty industry itself is worth a lot of money, and it is expected to increase from $420 billion in 2018 to $716.3 billion by 2025 (Roberts, 2022). The beauty industry on YouTube has grown, thanks to interesting personalities who engage their audiences. In 2019, there was an important event for the beauty industry when two popular beauty influencers, Jeffree Star and Shane Dawson, created a documentary series of beauty videos titled 'The Beautiful World of Jeffree Star’, which achieved 152 million views on YouTube. The series resulted as the most significant customer engagement and the largest product launch in e-commerce history (Cowburn, 2022) with 2 million users queuing on the website to purchase the products promoted in the series (Weinlich & Semerádová, 2022). Another example is Instagram beauty influencer Kylie Jenner, who released her first product-lipsticks-called 'LipKits’-and sold them out in minutes after announcing the launch on Instagram (Duboff, 2015). Kylie Jenner, who is the biggest beauty influencer in the world, is also in the second place (after Christiano Ronaldo) in terms of the number of followers on Instagram with 378 million (Instagram, January 2023).

Based on the mentioned examples, beauty topics are particularly popular and engaging for social media users. Researchers are also paying a lot of attention to the topic of social media (265,987 publications can be found in the SCOPUS database alone). However, considering the purpose of the article and the research gap, it was decided to narrow down the search results.

Table 1 presents a literature review based on the SCOPUS database. In order to search for relevant results, it was decided to use the following keywords: ((’beauty influencer’ OR 'beauty content’) AND 'social media’). Initially, 18 results appeared. Then the results were reduced by branch criteria. Articles belonging to the categories of Business, Management and Accounting or Social Sciences were filtered out. Eventually, 14 articles were included for further analysis.

In the available literature, it is noticeable that the authors address the topic of influencer marketing in the beauty industry on social media in different contexts. Some researchers have concentrated on word-of-mouth marketing as a strategy for promoting brands (Fitriati et al., 2022; Yones & Muthaiyah, 2022), others as a potential determinant of SME resilience and competitiveness (Konstantopoulou et al., 2019). Some researchers concentrated on the influence of electronic word-of-mouth and perceived quality on purchase intention of beauty products (Rosara & Luthfia, 2020). Other papers focused on aspects of gender, such as exploring the topic of beauty in the context of plastic surgery for trans women (Zhang, 2022) or the level to which influencers show themselves in a sexualized manner in various roles (Devos et al., 2022). Previous studies have also examined the impact of beauty content on purchase intentions (Pangaribuan et al., 2019). Others have examined the level of consumer engagement with products (Rutter et al., 2021) or the reasons why users follow influencers (Tran et al., 2022). There was also a concentration on how the attitudes of beauty influencers influence repeat purchase decisions (Ayuaspharalinda & Tanuwidjaja, 2021). The authors also focused on ethical topics, examining transparency while influencers disclose information about advertised products and brands (Lee et al., 2022).

Several articles did not concentrate on a specific platform at all. The studies were conducted in the context of social media in general (Ayuaspharalinda & Tanuwidjaja, 2021; Tran et al., 2022; Zhang, 2022). One article focused its considerations on TikTok platform (Yones & Muthaiyah, 2022). Others approached the research only in the context of Instagram (Devos et al., 2022; Fitriati et al., 2022; Konstantopoulou et al., 2019; Pangaribuan et al., 2019; Rutter et al., 2021) or only on YouTube (Bishop, 2019; Dekavalla, 2022; Lee et al., 2022; Rosara & Luthfia, 2020). However, they did not put both platforms in one study. The exception was the research of Sokolova and Kefi’s (2020) who focused on those two, previously mentioned platforms; however, the paper concentrates on examining the para-social interaction (PSI) that the audience creates with an influencer online and how this influences purchase decisions. To do this, the authors based their study on four beauty influencers who are popular in France. The survey considered not only beauty but also fashion influencers. Also, all the studies have been conducted in foreign markets, mostly in Indonesia (Ayuaspharalinda & Tanuwidjaja, 2021; Fitriati et al., 2022; Indrawati et al., 2022; Pangaribuan et al., 2019; Rosara & Luthfia, 2020).

The literature review helped to reveal that the Instagram and YouTube platforms have not been studied in terms of consumer preferences for the preferred beauty content shared by influencers and the product categories that they are most interested in. Moreover, neither the study focused on the Polish market and addressed the topic of the behaviour nor preferences of Polish consumers in terms of the beauty industry. This lack of information indicates a research gap, which prompted the authors, to conduct the following study.

Research

Methodology

To fulfil the objective of this paper, a research design was prepared according to the following research questions:

RQ1: What are consumers’ preferences for content, published by beauty influencers on Instagram and YouTube?
RQ2: What are the respondents’ preferences for beauty products recommended by beauty influencers on Instagram and YouTube?
RQ3: How do respondents perceive beauty influencers on Instagram and YouTube and how does it affect followers’ purchasing decisions?

Procedure

The study was conducted using a diagnostic survey method, with a questionnaire as the research tool, hosted on Microsoft Forms and distributed via the Internet. The process of collecting responses lasted from December 2022 to January 2023. The selection of individuals for the survey sample was based on a purposive selection scheme, in which the categories were the use of social media, particularly the Instagram and YouTube platforms. A total of 151 questionnaires were collected; however, due to not meeting the criteria, 5 questionnaires were rejected. Thus, a total of 146 questionnaires were taken into further consideration. Responses were given anonymously.

The questionnaires were divided into three parts. The first part is general questions directed at active social media users. The second part involved questions related to the Instagram platform for respondents who declared that they use it, and a sub-category of this part-question related to beauty influencers on Instagram. Analogous to the previous one was the last part, concerning the YouTube platform and then the perception of beauty influencers.

Sample characteristics

Most of the participants in the survey were women (73.5%). The largest group are the respondents who were aged between 19 years old and 27 years old (76.8%), followed by young people between 12 years old and 18 years old (13.2%), then people who were aged between 28 years old and 42 years old (6.6%). The smallest group are the respondents who were aged between 43 years old and 57 years old (33%). In terms of occupational status, the survey mainly involved those declaring themselves to be university or school students — 91.4% and the rest were people who work. The sample was dominated by respondents who lived in large cities, with over 500,000 residents (536%). The others lived mainly in villages (172%) and mediumsized towns with a population between 50,001 and 200,000 (126%). The fewest number of respondents lived in small towns with a population of up to 50,000 residents (93%) and those who lived in large towns with a population between 150,001 and 500,000 residents (73%).

Results

The first question, in the general part of the questionnaire, required to identify the one social media platform that respondents use most frequently. The largest group chose Instagram (36.4%), followed by TikTok (19.9%) and Facebook Messenger (19.2%). The others indicated YouTube (14.4%), Facebook (5.5%) and WhatsApp (1.4%) as their favourite platform. The rest chose the answer 'other’, indicating Twitter, Telegram and Snapchat here (0.7% each of additional responses).

The second question asked respondents to estimate how much time they spend on average on social media per day. The average was 3 hr and 38 min (SD = 1.96).

The next question allowed respondents to indicate their three favourite social media topic categories. The study found that it was mainly lifestyle (39%), entertainment (38%) and beauty (32%).

The next question referred to the Instagram platform. Thus, only people who use it participated in this part (n = 136). Instagram users declare that they use Instagram an average of 12.8 times per day (SD = 17.77) and spend on average 1 hr and 42 min on the app each day (SD = 1.22).

About 87% said they follow influencers on Instagram. Those who do were asked if they follow beauty influencers. A total of 100 respondents declared that they follow beauty influencers on Instagram.

Respondents, who are active on YouTube, were asked the same questions as with Instagram. Only those who use YouTube answered questions about this app (n = 131). YouTube users say, they use the platform 4.6 times a day (SD = 5.33) and spend an average of 2 hr and 10 min on it daily (SD = 3.36). About 91.6% of respondents said they follow influencers on YouTube. Those 120 people who gave a positive answer were asked if they also follow beauty influencers on YouTube. About 84.1% answered affirmatively. Therefore, 102 people answered further questions about the YouTube platform.

Table 2 presents the preferred types of content published by beauty influencers on Instagram and YouTube. Respondents were asked to rank this content in the order from 1 (most favourite) to 10 (least favourite). They had the following types of content to choose from when ranking:

A – Tutorial videos
B – Product reviews
C – Shopping haul
D – Unboxing
E – Testing products of various brands
F – Comparison of the same products from different brands
G – Videos with invited guests
H – Review of the latest products
I – Promotional videos of own-brand products
J – Promotional videos about the products of the brands the influencer works with

Then a weighted mean value was calculated showing the degree of importance of each quantity, according to the respondents’ preferences.
The lower the value of the measure, the more the respondent prefers a particular type of content. The results are presented in Table 2.

Most respondents mainly prefer to view product reviews on Instagram (2.82%) and then tutorials (4.13%). On the other hand, the fewest number of respondents are interested in promotional videos of the influencer’s own products (7.47%) or a collaborative brand (8.66%) as their favourite type of content. In terms of respondents’ favourite content viewed on the YouTube platform, similar to Instagram, were product reviews (2.95%) and next tutorial videos (3.54%). Again, most consumers were least likely to indicate promotional videos about the products of the brands the influencer works with (8.23%) and videos about influencers’ brands (7.56%).

In the next section, respondents again ranked, but in this case, they decided which beauty products were their most (1) and least (7) favourite in content posted by beauty influencers on Instagram and YouTube. Respondents had the following types of content to choose from when ranking:

A – Makeup products
B – Facial care cosmetics
C – Body care cosmetics
D – Hair care cosmetics
E – Hair styling cosmetics
F – Nail products
G – Beauty accessories

Then, similarly to the previous question, a weighted average value was calculated showing the degree of importance of each quantity according to the respondents’ preferences. The lower the value of the measure, the more the respondent prefers a particular type of content. The results are presented in Table 3.

Favourite beauty products in consumers’ feeds on Instagram are primarily facial care products (2.17%). Slightly fewer respondents indicated makeup products (2.44%). The last choice for consumers on Instagram were beauty accessories (5.43%) and nail products (5.43%). For the YouTube platform, respondents primarily pointed to makeup products (1.93%). The second most popular product category was facial care products (2.50%). As with Instagram, beauty accessories were the least popular.

The final part of the survey attempted to explore how respondents perceive beauty influencers on Instagram and YouTube. For this purpose, a 5-point Likert scale has been applied, with which consumers could assess the extent to which they agree with the given statement. Table 4 compares the two platforms: Instagram (IG) and YouTube (YT). Only Instagram users responded to the statements (n = 100), and the same is the case of YouTube (n = 102).

Over half of Instagram users say they trust their favourite beauty influencers on Instagram (55.2% trust and 5.7% definitely trust). By contrast, on YouTube, 42.6% say they trust influencers and 18.5% say they definitely trust them. On Instagram, 9.2% do not trust their favourite beauty influencers, and 5.6% simply do not trust them. Overall, slightly more than one-fifth of respondents do not trust influencers on YouTube (14.8% of viewers disagreed with the statement in Table 4, and 5.6% strongly disagreed).

In the second affirmative given in Table 4, the audience was asked if they agreed with the statement that beauty influencers are the first source of information when they want to purchase a product. About 43.7% of Instagram users agreed with the statement, while 5.7% strongly agreed. In contrast, Instagram users answered rather positive (42.6%) and strongly positive (18.5%). Very similar results were noted in the case of negative attitudes to the given statement, for 9.2% of Instagram users and 9.3% of YouTube beauty influencers are definitely not the first source of product information, and for 29.9% Instagram and 25.9% YouTube consumers are rather not.

Another statement focused on purchasing issues, specifically whether beauty influencers influence followers’ purchasing decisions. The study found that for both platforms they do. About 46% of Instagram viewers declare that beauty influencers rather influence their purchasing decisions, and for 11.5% they definitely do. In the case of YouTube audiences, 35.2% of respondents are rather under the influence and 16.7% definitely are affected by influencers when it comes to purchasing from beauty influencers’ recommendations.

Responses to the last statement were quite divided. About 34.5% of Instagram users tend to agree with the statement: 'beauty influencers on Instagram are credible’. In contrast, 25.3% think quite the opposite, while 28.7% have a neutral opinion on the issue. Meanwhile, in the context of trusting beauty influencers on YouTube, 29.6% rather trust them, 24.1% rather do not, and 27.8% do not particularly have an opinion.

Discussion

The objective of the paper is to compare consumers’ preferences towards activities and content, published by beauty influencers on Instagram and YouTube platforms. The study showed similarities between consumer preferences for content. On both Instagram and YouTube, consumers are most likely to watch product reviews, and secondly tutorials. On the other hand, they least prefer advertising content, such as product promotional videos of brands the influencer works with and promotional content of his own products. This may be because promotional content is increasingly associated with advertisements, and consumers realize that such videos are aimed at profit and selling specific products. Reviews, on the other hand, respond to the needs of consumers, who see value in these videos for themselves, they might get an opinion on a product they are interested in, e.g., some particular cosmetics.

Meanwhile, taking into consideration the product preferences of respondents, some differences were noted between the platforms discussed. Favourite products in the beauty category for Instagram users are primarily facial care products and secondarily makeup products. These two categories are also the most popular on YouTube, with the difference being that makeup products were the primary choice and facial care the secondary choice. Given the high popularity of tutorials and makeup products, it can be assumed that Internet users are learning how to apply makeup from beauty influencers.

The survey also showed that both Instagram and YouTube users perceive beauty influencers rather positively. In both cases, most of the consumers trust their favourite influencers, but they do not always feel the same way about beauty influencers in general. In this case, opinions were mainly spread between rather negative, neutral and rather positive. Respondents also mostly declared that influencers on both Instagram and YouTube are the first source of information when they want to purchase a beauty product, and most often the mentioned influencers later affect their purchasing decisions. Such results show that influencers are opinion leaders and have a real impact on consumers’ purchasing decisions.

Conclusions

The study fulfilled the purpose of the article and answered the research questions. However, the conducted survey had some limitations, such as non-random nature of respondent’s selection and a relatively small sample size. Therefore, it is difficult to generalize the results of this research. Nonetheless, it is hoped that the presented article can expand the knowledge of buyers’ perception towards influencers. In the future, it would certainly be worthwhile to overcome these limitations. Moreover, future research could focus on other social media platforms, such as TikTok, which has recently become incredibly popular, especially among teens and young adults.

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Homogenisation of customer experiences across channels has been implemented for a while and aims to adopt the available technologies for the needs and requirements of customers, especially in real and virtual channels (Lazaris & Vrechopoulos, 2014; Santalova, Lesnikova, Kustov, Balahanova, & Nechaeva, 2019). Research related to omnichannel is positioned in a stream of customer and offer behaviours (Li et al., 2018; Lafkihi, Pan, & Ballot, 2019), similar to that of offerers only (Rigby, 2011; Brynjolfsson, Hu, & Rahman, 2013; Grewal, Roggeveen, & Nordfält, 2016; Lim, Rabinovich, Rogers, & Lester, 2016; Wiener, Hoßbach, & Saunders, 2018).

Omnichannel solutions were initially used in commerce to extend previously implemented multichannel options. It is pointed out that omnichannel experiences have been developed for over a decade. In this concept, offerors guarantee the customer’s ability to order and take the commodity in all the channels (Taylor, Brockhaus, Knemeyer, & Murphy, 2019). Sometimes, it is also said that based on the preferences in terms of all channel usage, the typologies of customers are built, and they show the omnichannel customers separately (Lazaris & Vrechopoulos, 2014; Gregor & Gotwald-Feja, 2018). Omnichannel is sometimes also treated as a path to deliver customer value, which became crucial during the Coronavirus Disease-19 (COVID-19) pandemic. On average, one in three American citizens used omnichannel solutions (such as shopping online and stationary collection) during the pandemic, and two in three-plan to continue this form of transaction fulfilment (Briedis, Gregg, Heidenreich, & Liu, 2021). The research, published in the 'Voice of the Retail Industry Survey’ conducted in July 2020, shows that the pandemic forced sellers to treat entering the omnichannel as their top priority (Bourlier, 2020). At the same time, it is challenging to state to what extent omnichannel solutions will be implemented and what factors can influence their further functioning.

Identifying processes and phenomena happening in an omnichannel environment in the past 3 years (2020-2022) is difficult due to the COVID-19 pandemic, which appeared at the beginning of 2020. On a global scale, until Sep. 13, 2022, around 610 million people got ill due to the coronavirus, and over 6.5 million died (WorldoMeter, 2022). Apart from the health condition of humankind, the results of the pandemic were reflected in the worsening economic situation of specific countries, the massive growth of unemployment (in 2020 alone, over 225 million regular posts vanished), further increase in the number of people struggling with extreme poverty, increase in public debt, decrease in investments (in Europe and North America for 42%), and a significant growth in the prices of commodities and services (United Nations, 2020). The other type of consequences is visible in the popularity of remote work, the decrease in working hours (Committee for the Coordination of Statistical Activities, 2020) and the popularisation of online tools in building the employees’ brand (Sobocińska, 2022). At the same time, the worsening of the current and future economic situation perception of households (Biga et al., 2020) will significantly influence the fulfilment of customer needs. Research shows that entrepreneurs were not prepared to implement omnichannel and multichannel solutions forced by the pandemic (Acquila-Natale, ChaparroPelaez, Del-Rio-Carazo, & Cuenca-Enrique, 2022; Gerea & Herskovic, 2022; Gutierrez-Leefmans, 2022).

The COVID-19 pandemic also influenced customer attitudes and market behaviours (Kucharska & Malinowska, 2021; Liu, Fang, Cai, Su, & Wang, 2022; Mącik & Mącik, 2022). The forced implementation of solutions decreased the probability of being infected by the virus. It was reflected in the changes in needs satisfaction (social distance, purchases in the real world with many limitations, and the necessity to purchase certain goods online). The ways to make orders also changed. Significant changes in offerors’ suppliers accompanied all these behaviours, mainly in the tools used by companies in relations with customers (Peppers & Rogers 2022). These processes relate to virtualisation and the need to unify customer experiences in different channels (or guarantee their equivalence and substitutional character), which was mentioned earlier. Customer behaviours seem to gravitate towards omnichannel or (which is surprising in terms of the earlier research results; Gotwald-Feja, 2016)-toward the domination of online channels (Naragon, 2022).

In this paper, we have analysed texts published in the professional online journals, Total Retail and Multichannel Merchant. We selected papers which appeared in search results related to the 'omnichannel’ keyword, published between March and September 2020 and in 2022 (until June). There were 134 papers from Total Retail and 172 documents from Multichannel Merchant. The literature review method was used, and it aimed to identify the phenomena and processes related to the omnichannel environment and their evaluation. As a consequence of the research goal, detailed questions were stated regarding customers’ needs and experiences, changes in terms of product delivery and usage of technologies by enterprises. The papers mainly reflect the pandemic challenges, covering the challenges regarding satisfaction of customers’ needs in the virtual and real world in parallel (Stabler, 2020). The changes and tendencies which were noticed are described below more in the issue order, not necessarily chronologically.

The Method

In this paper, the qualitative attitude was used. Regarding social sciences, the literature review is usually based on scientific sources (Czakon, 2011; Lenart-Gansiniec, 2021). In terms of omnichannel, the implementation of new solutions and theoretical analysis is made faster in professional journals, and not scientific journals; therefore we have focused on the former, applying the rigours of a systematic literature review. We selected the journals devoted to multichannel and commerce because, in this case, the implementation of omnichannel solutions was advised at the earliest. The journals were one of those that were the first ones to describe omnichannel. All the texts presented in the search results after typing the keyword 'omnichannel’ in Total Retail and Multichannel Merchant were analysed. There were two periods for analysis: at the beginning of the pandemic (58 and 23 papers) and during the pandemic (76 and 149 articles). If the issue discussed in a paper was previously described in an earlier publication, quoted and analysed, we desisted from presenting the same content again. Based on the research results, we made an overview of the phenomena and processes related to the omnichannel environment. Then the results were combined with the scientific research results published in peer-reviewed journals, indexed in SCOPUS database.

Results

The importance of consumer experience personalisation is growing steadily. It is, therefore, vital to enable users to build an experience almost a’la carte, which is difficult for sizeable online commerce chains. For this reason, the importance of small and flexible players is crucial to adapt to clients’ needs and preferences (Stabler, 2020). At the same time, it is noted that customer contact should be meaningful. This excludes short and brief business relationships and emphasises (mainly through CRM (Customer Relationship Management) and Artificial Intelligence [AI] systems) a more profound experience through a better understanding of each customer. The dynamic approach to the customer is also a factor that significantly affects the total satisfaction and perception of the brand and the marketing materials it provides (Estas, 2020; Garber, 2020).

Stein Mart implemented (in March) the solutions to enrich customer experience in online purchases and collection in a standard shop, Buy Online, Pick-Up In-Store (BOPIS). It aimed at the personalisation of customer experience in every brand touchpoint. BOPIS is often equated with the technology of implementing a 'button’, which calls for assistance and alarming the employee that a customer wants to collect the package. In this way, the carrier can invite the customer with their first name, offer promotional goods (finally enhancing the total value of the client’s cart) and deliver it in the shortest possible time (Schebella, 2020; Sackos, 2022). During the pandemic, new models of delivery (services) appeared, and they are still available. Among others, they are Research online, purchase instore (ROPIS) and Buy online, return in-store (BORIS) (Balytsky, 2022). Even if the first one was known in the literature as Research online, purchase offline (ROPO) (Gregor & Gotwald-Feja, 2017), the concept was popularised during the pandemic for apparent reasons. Additionally, the customer is not switching the offeror, which might be a significant change compared with the ROPO effect. The purchase is finished in-store to shorten the waiting time for a product. New products were used in the model (e.g. the groceries offered by supermarkets). It resonates with Neslin’s (2022) model, which presents various strategies and stages of the customer’s decision-making process.

Feng, Zhang, Feng and Zhu (2022) propose a model which relates to the cost of visiting the store in omnichannel, using the BOPS effect. The authors state that allowing customers to complete online shopping with the traditional visit to the store is one of the strategies for the omnichannel presence of the company. However, they point out that the strategy implies many challenges related to price management and store visiting cost relationships.

Feeney (2022) states that the attitude towards POS (Point of Sales) must change (Nguyen & Borusiak, 2021). Currently, it is impossible to implement a single technology for 5–10 years. It is inevitable to adapt it to the needs of customers and their preferences, including using new technologies like AI, personalised advertising or acceptance of various payment methods (Pero 2022). It is essential to guarantee the maximum comfort for the user. Implementation of the 'additional brain’ in store, which will interpret inventory, scan shelves and all the data from the point of sales, and forecast the demand, becomes necessary if one wants to keep a competitive advantage in the omnichannel environment. 'Data is retail’s secret weapon to reduce costs, improve labour reliability and consistency, and access operational insights’ (Baylin, 2022). Inventory automation frees the labour, which can focus on customer service (Thielens, 2022).

However, the changes happening in brick-and-mortar stores are not only related to inventory management (Haggerty 2020) or the shop’s 'interface’. Due to the changes in customer expectations regarding technology usage, it is crucial to implement the so-called 'experiential retail’. It is essential for omnichannel customers who need stretching of fluent, sage and exciting user experience from the virtual to the real world (Barnes, 2022). An example of such a solution can be an ACI Smart Engage. This mobile platform offers the sellers a chance to present their offer directly on a customer’s smartphone, using geolocation, voice commerce and the technology of picture recognition (ACI Worldwide, 2022).

Technological changes are related to the possibilities granted by socalled 'headless e-commerce’. Implementation of solutions which divide the front-end and back-end of shopping portals allows the potential for easy and fast reaction to changes in customer surrounding and lets the seller become independent from one technology provider for the whole store. It results in smoother interactions with the website for customers and helps in easier adaptation to the sellers’ and clients’ expectations. Headless e-commerce is often joined with the term 'MACH’ (meaning: Microservices, API-First, Cloud-Native and Headless). So the attitude is stretching and covering the implementation of small and independent solutions in one full service. To be successful in online commerce, employees who adapt fast and are open to change are crucial (Broke, 2022). A total of 8 in 10 US citizens agree that during the COVID-19 pandemic, unnecessary movement must be reduced, and 6 in 10 support telephone contact with physicians, banks and pharmacies. At the same time, research proves that two-thirds of clients, regardless of age group, prefer online shopping and pick-up in-store (Wethered, 2020). Clients require adjusting their preferences regarding the product and delivery (Panzer, 2020; Cocco & De Juan-Vigaray, 2022 ). Some brands also develop the concept of adaptation to customer needs through returns collection (to reduce the purchasing risks) (Freedman, 2022). It is, however, challenging for target groups of different ages to differ significantly in terms of the products in the cart and the application’s interface (Bergman, 2020). For example, many suppliers do not use the offered changes by providing voice shopping. Only 15% of contact centre leaders plan to implement that solution (Abeysena, 2022).

It is inevitable to extend and change the customer experience towards using the shop’s floors (especially in terms of big retail chains) instead as a place for meetings rather than pure commerce. Concerning the need for personalisation, a transition towards direct to customer (D2C), like in the local stores (Stabler, 2020), can be implemented, especially since customers support the solution. Almost half of the customers (55%) more eagerly buy directly from brands which result in a reduction of the distribution network costs and allow financial optimisation (Panzer, 2020). Implementation of these solutions supports omnichannel customers who, 30% more often than other customer groups, buy coffee in the shop’s café or pick up medicine in the shop’s pharmacy during regular shopping. The role of minimally distractor factors is important not only to implement omnichannel solutions but to be an omnichannel (Birnbaum, 2020).

Extension of customer experience is in line with its optimisation, and AI can be of assistance with implementing real-time data analytics (RTDA) or Application Performance Monitoring (APM) analysing the most important application’s parameters (Long, 2020). Enterprises must, however, cope with not only gathering or sorting the data but with efficient usage of the information derived from the data (Seify, 2022).

In relation to customer experience, the growth of augmented reality (AR) and virtual (VR) reality’s role is noticeable in terms of testing the product before purchasing and-using it instead of purchasing (Maddimsetty 2022). The development of 5G networks and usage of their abilities (faster Internet connection, more devices, etc.) will accelerate the process (Stabler, 2020). Openness for AR/VR can raise the conviction that enterprises should get involved in the Metaverse (announced by Mark Zuckerberg) because those entities which 20 years ago did not decide to enter the online world had lost the market opportunity (Ryan, 2022). The potential to enter the hybrid world is related to all the organisations, and it was initially tested during Metaverse Fashion Week. It was proved that there is a possibility to find a balance between the usage of the virtual world and immersion comparable to that in the real world. Among others, this is the reason why organisations should prepare strategies for entering Metaverse (even if only in a scenario model) (Moreti, 2022). As an example of engagement in hybrid environments, we can present the cooperation of Mattel and Forever21 brands, thanks to which Metaverse users can buy clothing, accessories and equipment inspired by the Barbie world (Albiges, 2022). The quality of the Internet connection is still a challenge and, in many cases, will be a barrier to entering the full usage of the hybrid world (Norton, 2022).

The role of the speed of page loading (Pilarczyk & Rogala, 2018) and the development of Progressive Web Applications (PWAs) is growing to shorten the customer journey (Cardarella, 2020). The processes of omnichannel development involve all the enterprises which take attempt to implement seamless commerce. They face the challenges of implementing changes in an evolutionary, not revolutionary, way to compete successfully with others. Jaszczyk (2022) recommends them a few priorities:

• The clients have to be positioned in the first place, and technological plans should be adjusted to their needs, regardless of the plans for the solution’s implementation and its timing;
• The companies should invest only in good technologies because their implementation can improve the financial results of the company (savings from customer service), but additionally, it creates the potential to implement a higher level of customer purchasing experience personalisation;
• Implementation of innovations related to the online ecosystem of customer experience should be considered;
• The technological plans have to be related to complex business strategies.

Customer preferences towards delivery have also changed. Clients using the service, for example, the delivery on the day of order offered by UPS (O’Brien, 2022) or Amazon, in the majority of cases, accept a 2- or 3-day period to wait for the delivery of an ordered product. For that reason, companies are forced to use the newest technologies for order completion or use historical data to accurately forecast the demand. It is also challenging to guarantee the resilience of supply chains in terms of the unpredictable business environment (Dagan, 2022). The character of the relationship with suppliers, directed at the agility of the organisation, seems to be inevitable (Garber, 2020). The problem’s role grew due to the pandemic. The necessity to maintain close and positive relations with suppliers (also the local ones) becomes crucial for maintaining the quality and scope of services, implementing new solutions, improving enterprise performance and improving its flexibility (Agile, Lean) (Barnes, 2020).

Acquisition of a good supplier becomes challenging and new solutions are there to help. For example, Extensiv offers the brands the possibility to use the suppliers’ search (Extensiv, 2022).

Implementation of omnichannel solutions can require additional resources, so the limitation of costs with unaffected product quality is crucial, especially during COVID-19. During that period, curbside delivery develops. The package is delivered in front of the house, but the client is responsible for further logistics (e.g. collecting and taking it to his or her flat). Such delivery limits the time for delivery, allows serving more customers and can be contactless (Barnes, 2020) and, for that reason-safer.

The pick-up window, fast packages (having the basic groceries, prepared to pick them up in-store and have no contact with others) or 'dock and load’ (putting the order which was previously bought and paid for directly to customers car parked in front of the store) are other examples of the delivery innovations (Osburn, 2020). The usage of drones for product delivery is another issue. Walmart can serve as an example, as it covers 4 million households with drone delivery (Keenan, 2022), experiencing an increase of online sales of 99% compared between March 2019 and 2020 (Rosenstrauch, 2020). Some companies noticed the change in the usage of robots or autonomic cars in delivery, especially at the last stage of order fulfilment (Sackos, 2022). Some of those and the other solutions would not have even been considered before COVID-19. Metzker (2022) believes that brick-and-mortar shops can have a significant competitive advantage due to the broad network of selling points and their distributed retail chains. This way, the concept of instant delivery can become real. Black (2022) states that in that situation, omnichannel from the customer’s perspective is the chance to fulfil the shopping in an optimal way, and for that reason, traditional retail chains with a broad potential for delivery become efficient in the omnichannel world. In this way, the shops can easily manage returns which are far more challenging for virtual entities. This is why the latter need to consider reverse delivery or building partnerships with specialised organisations which handle not only complaints and returns but also will use the economy of scale (Huddle, 2022).

Limitations and avoidance of contact (Akers, 2020) are in line with the trends of self-service purchasing or product scanning and putting products to the cart at the same time as payment in the cashier, optimal, self-service ones (Barnes, 2020). The solution, which was not that long ago developed only to shorten the service time for customers, becomes an element in improving the safety of people. The role of robots and cobots (collaborative robots) (Barnes, 2020) is similar since they were designed for order processing and direct interaction with humans. Lack of contact limits the chance for infection, and the humanoid shape of cobots allows for building a good relationship with the customer. In terms of delivery, the acceleration of processes aimed at financial optimisation (decrease in employment, automation and robotisation) is noticed, but it is motivated not only due to financial issues but mainly by the requirements of customers and the current situation. The expectations of customers relate to something far more significant than just virtualisation. They cover the need of the possibility to fulfil purchasing processes on entertainment and social platforms. It is especially related to Generation Z, which is far more familiarised with technologies than the Y Generation and the chance for smooth service and fast delivery is a basic condition, not a 'premium’
feature (Hook, 2022). Shopping on social networks gets more popular, and the value of transactions in 2021 in the so-called social commerce was US$958 billion (Morris, 2022). Social media are not enough for solving conversions known from shops (although some platforms are working in that direction). For that reason, a part of brands prefer, for example, the organisation of live events on their websites instead of on social networking sites (Holland, 2022). It can be caused by the fact that brands treat social media rather as a tool for promotion, reaching customers and building loyalty, and not conversion itself (Champion, 2022).

The role of inventory management grows due to the necessity to focus on one channel during COVID-19 frees some resources and allows the job of ordering the systems for multiple locations. Hogue (2020) states that such actions will be crucial when customers come back from lockdown to their natural omnichannel preferences. In that context, the popularisation of electronic payments is essential (Eichinger, 2020) since they do not require a presence of a seller and they allow full self-service automation. The functioning of shops can also change. Enterprises need to choose whether to focus their attention on delivering customers a complex service (at the expense of the back-office processes) or allow instant delivery due to shrinking the shop area (and extension of the warehouse facility) (Kroner, 2022).

At the same time, the problems with the labour force became a challenge (Feeney, 2022). The solution to this problem can be greater involvement of technologies. The need to virtualise the job influenced not only the development of employees’ competencies in e-commerce but also forced the absorption of new behavioural patterns of customers. For that reason, the presence of a seller in the shop is not required to make customers feel satisfied. However, online services in the form of video conversations started to be required by clients (Hordagoda, 2022). The reason could be to balance the previous absence of the seller.

The need for clients’ online safety (Ronhaar, Zehner, & Langhorne, 2021) is essential due to the growth of intensity of criminal behaviours aimed at capturing transactions, payments or private data (Benge, 2020). An increase in the number and value of online transactions can determine the growth of interest in this field by criminal groups. Not only the data stealing and its usage not in accordance with the intended purpose, it might also be dangerous. Inappropriate usage of data by enterprises themselves is punishable, and for that reason, it is suggested to hire experts in private data protection or network safety (Joshi, 2022). Suppliers are forced to ensure certificates of safety for websites and their identities online because such investments can be translated into customer trust (Palanisamy, 2022). Similarly, it is important to provide similar safety measures to the company, especially while the popularity of online payment grows (Laudenbach, 2022). It is also visible in the model buy now, pay later (BNPL), where the customer finalises purchasing at the point of sales, but the payment is postponed or divided into instalments without the need to use a debit card or classical procedure for consumer credit (Ryan, 2022, Martin 2022). It is forecasted that the value of the market shall grow from US$ 15.91 billion in 2021 (globally) to US$ 22.86 billion in 2022 and US$ 90.51 billion in 2029 (Fortune Business Insights, 2022).

The change in the efficiency of action evaluation is also visible. Initially, marketers measured the efficiency of mailing with the number of opened and read e-mails. Currently, the attention is transferred to qualitative factors related to customer engagement (Sargeant, 2022).

The element which allows further virtualisation is the implementation of solutions of AI (Mcglynn, 2020). It is a crucial trend from the perspective of AI operational efficiency. Research suggests that 35% of customer purchases on Amazon come from recommendations stimulated by AI, and by the end of 2023, the commerce plans to invest in this area US$ 12 billion, which is a growth of 230% while comparing with the year 2019 (Mcglynn, 2020).

Sustainable commerce becomes very important, especially in relation to the declarations of the retail chains to implement sustainable fabrics (ZARAvir), zero carbon footprint (H&M), and growth of the value of the second-hand clothing market (from US$ 24 billion currently, the value can reach US$ 51 billion in 2023) (Stabler, 2020). Although the issue was not much visible due to urgent challenges related to the COVID-19 pandemic, it appears again due to the periodical ease of the health problems. It seems that sustainable commerce, from a classical perception of the issue, covering the balance between technological, social, economic and environmental issues becomes visible in a different manner. It can be seen in ’empathising commerce’ (Akers, 2020) and customer and employee voluntary service (e.g. free product delivery for elderly people during pandemics) or virtualisation of some goods (like offering access to online events for easing social distancing while still participating in culture). Wilson (2022) noticed that the sustainable attitude of business should be derived directly from the mission of the organisation. 'Purpose-driven marketing becomes a buzzword like the omnichannel itself’. Almost all the customers (94% of respondents) declare that they value purpose-driven companies, regardless of their ambitions to create a metaverse or to meet sustainability goals. For this reason, the communication of goals by companies should be clear at the levels of strategy, key values and brand message (Wilson, 2022).

McGovern (2020) writes about the 'new normality’ caused by the coronavirus. The 'commerce apocalypse’, which was experienced by the economies of all countries, can be described by the virtualisation and transition from omnichannel to single-channel (online). The structure of employment in marketing and logistics has changed, similarly as automation of advertising material creation is noticed, and the institutions teaching marketers try to adjust to the new reality by adapting the teaching programmes. The relations with other humans in a shopping situation in shops are pushed to the background (especially for Z Generation), but the usage of fast online service becomes crucial (even within 8 s, with the usage of a chatbot to answer customer queries). The author also states that the 'new normality’ does not wait till the COVID-19 pandemic ends.

Sularia (2020) additionally noticed that COVID-19 has caused many changes related to not only the new consumption models or the say in how retail chains operate. Among others, distant work is stimulating online shopping. Other changes in terms of organisation actions are the attitude 'digital first’, efficient inventory management as a key for achieving profitability, and 'cost-less customers’ online appearance (who buy online because they have no other option). In Sularia’s (2020) perception, logistics will be the element of competitive advantage building, which is stimulated by the growing popularity of distributed production. It is symptomatic that the ready-made solutions to be implemented in e-commerce appear (in a model 'plug and play’), and online shopping will naturally become a vital part of the customer journey (Rosenstrauch, 2020). Implementation of the solutions which support better functioning of the applications (Birnboim 2022) (or websites) and delivering customers the best product possible is caused by the necessity to transfer the majority of customers online. It is hard to say what we can say about the disappearance of omnichannel towards single-channel, because multi-screening still gains popularity. Customers prefer solutions of that sort because they give more possibilities (Stotz, 2020). Assuming usage of a television set, personal computer and smartphone (or tablet)-three channels are already used. Even if the content is not complementary and related to different brands, it is opposed to a single-channel idea.¹

On the other hand, Smythe (2022) noticed that the implementation of a customer-centric approach is significant, and the level of omnichannel integration needs to be determined by the needs of customers. In his opinion, such attitudes allow companies to increase ROI (Retur on Investment). So if customers prefer online channels, maybe optimisation should be applied here (reducing the usage and the role of the other ones).

Discussion

The phenomena described above seem to be the background for omnichannel environment development. Although the matters presented are related mainly to the issues caused by the pandemic, some of them were visible earlier (although their role was smaller). An example might be the necessity of paying attention to customer experience (Schmitt, 2015). Headless e-commerce, PWA, changes in relations with suppliers and employee or service optimisation are problems which touch business in general, not only in terms of an omnichannel environment. However, we must agree that the implementation of omnichannel in the enterprise makes those issues more important than in multichannel or single-channel reality (especially while considering the entities operating in e-commerce only). Some novelty might be the need for less direct contact with the other person (seller); however, while we compare it with earlier research results (Kowalczyk, 2006), the issue appeared far earlier than the pandemic. The need for social distancing implementation just made those challenges more visible than ever before.

We can also agree that the ability to complete the purchasing process in social networks and the change in their role is significantly determined by the pandemic. Although social commerce was analysed earlier (Turnbaum & Strauss & Lai), the necessity for transferring social and emotional activity to social networking sites and the appearance of the digital natives’ generation (or the Alfa Generation) caused the acceleration in the changes.

It can also be said that the most significant challenge is an attempt to diagnose the future directions for omnichannel environment development. One of the key factors influencing the potential forecast is the further development of the Metaverse. Mark Zuckerberg’s proposition is highly interesting for offerors and clients, among others, for the deep immersion offered by AR. Yet, it is hard to predict whether Metaverse will replace omnichannel or, rather, will become a part of it. Maybe in the future, we will speak about the single channel in terms of AR application. It is also hard to state whether and which actions taken by organisations were caused by COVID-19. Initiation of works on the implementation of virtual solutions was visible far earlier, and it can be rather related to technological advancement and the digital economy (Gregor & Gotwald-Feja, 2017; Kucharska, 2020). It is also difficult to answer which phenomena have the potential to become trends and a constant element of the economic landscape. Determinants for this can be high dynamics of technological advancement, social trends or the natural tendency of humans to gain comfort (at the expense of development or change) (Young, 2022).

Summary

The analysed issue seems to complete the requirements of novelty, especially in relation to the intensity of the changes (compared with earlier years). Although it is a serious limitation that the attention was focused only on two professional online journals, the number of over 300 analysed papers concerning omnichannel addressed mainly to enterprises which implement them can be of a certain value. The development of omnichannel activities can be related to a significant development of customer experience (in relation to the customer journey and available channels, including VR, AR and voice commerce) and its personalisation. It is also noticeable that the spectre of delivery methods has developed significantly, including dock and load or instant delivery. Changes in the intensity of omnichannel solutions usage by customers force a more frequent update of solutions implemented in brick-and-mortar stores (POS technology), used to manage inventory or concepts like Metaverse, headless e-commerce and PWA. The pandemic forced the development of contactless shopping, and Żabka or Amazon kept the solutions. It is worth noticing that sustainable commerce and transparency are important regardless of the pandemic stage.

Some pay attention to the fact that we are facing the 'new normality’ (McGovern, 2020), where people have adjusted to the surrounding threats caused by the deadly virus and have implemented new patterns of behaviours which can be a standard in the future. The source of these challenges is the COVID-19 pandemic. However, we need to ask ourselves if the so-called 'new normality’ is really caused by the appearance of the virus, lockdowns and their consequences or, rather, regardless of it. This question can be an inspiration for further research in terms of the meaning of factors stimulating technology implementation, omnichannel commerce and the omnichannel environment. The research that we conducted allows showing a few problem areas related to omnichannel (which stands in line with the results of Salvietti, Ziliani, Teller, Ieva, and Ranfagni’s research [2022]). The first group of problems is the customer behaviours of clients, including the fulfilment of customer journeys and preferences towards specific channels or omnichannel customer experience (Omnichannel-CX). Furthermore, the supply side of the market requires attention, including usage of new technologies (such as real-time research solutions, AR and the Internet of Things), human resources management or the risk of channel cannibalisation. The omnichannel strategies (in terms of creation and implementation) of companies require in-depth studies, especially after the pandemic eases and also require research attention.

Endnotes

1 The problem with introducing that issue is related to the fact that different authors treat the internet as one channel, eliminating the mobile channel as a separate one. On the basis of this, multi- or omnichannel appeared more rarely. See B. Gotwald-Feja, Konsument w realiach omnichannel, SIZ, Łódź 2015.

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XXI wiek nazywany jest okresem transformacji cyfrowej zachodzącej w gospodarce. Klaus Schwab, twórca i prezes Światowego Forum Ekonomicznego w Davos, określił ten okres mianem czwartej rewolucji przemysłowej. Scharakteryzował go jako epokę inteligentnej, współdziałającej w jednym ekosystemie, technologii i sensorów, która wpływa nie tylko na obszar biznesowy, ale również na życie codzienne społeczności (Schwab, 2018). Według prognoz IDTechEx rynek sensorów i urządzeń wearables (dalej UW) do 2023 r. ma osiągnąć wartość 100 mld dolarów, do 2026 r. natomiast 150 mld dolarów (Mazurek, 2019). Duży wpływ na transformację miał również dostęp do internetu szerokopasmowego, w tym w szczególności na urządzeniach mobilnych. Liczba abonentów tego rodzaju połączenia z siecią globalną przekroczyła w 2018 r. wartość 60 na 100 mieszkańców w skali świata (Frąckiewicz, 2019). Z kolei według raportów Best Computer Science do 2020 r. liczba urządzeń inteligentnych (w tym UW) podłączonych do internetu wyniesie około 200 mld (Tarabasz, 2018).

Celem artykułu jest próba identyfikacji stopnia znajomości i wykorzystywania wspominanych UW przez młodych konsumentów oraz postaw w stosunku do nich. Jego realizacja została oparta na badaniu empirycznym przeprowadzonym na próbie 173 jednostek.

Przegląd literatury

Przegląd literatury wykonano w oparciu o cztery bazy naukowe: Science Direct, Scopus, Springer oraz Web of Science (por. tabela 1).

Proces przeglądu baz naukowych składał się z kilku etapów. W pierwszym dokonano filtrowania na podstawie wyszukiwania fraz „wearables technologies” oraz „wearable technology” w tytułach prac, abstraktach oraz słowach kluczowych. W następnym etapie wyniki zawężono o kolejną kategorię — opublikowany artykuł w języku angielskim, w journalach jako artykuły badawcze oraz jako przeglądy literatury. W dalszej kolejności dodano kryterium obszaru tematycznego — biznes, zarządzanie, marketing lub nauki społeczne. Kolejny poziom selekcji polegał na wybraniu tylko tych prac, które zostały opublikowane w ramach otwartego dostępu lub dofinansowania MNiSW. Na samym końcu usunięto artykuły, które występowały jednocześnie w kilku wskazanych bazach. Finalnie otrzymano 25 opracowań. Najstarsze z nich — a są to dwie prace — pochodzą z 2015 r. Pierwsza opisuje zjawisko UW dość pobieżnie i autorzy skupiają się w nim na zastosowaniu tej technologii w turystyce i e-turystyce (Gretzel i in., 2015). Natomiast drugi artykuł opisuje UW jako bliską przyszłość. Urządzenia te pomagają zacierać granicę pomiędzy człowiekiem a komputerem, którą autorzy nazywają cyborgiem. Charakteryzują je jako pewne rozszerzenie możliwości ciała. Opisują możliwości zastosowania takie jak analiza składu potu w czasie rzeczywistym na podstawie tymczasowego inteligentnego tatuażu, mierzenia poziomu wody oraz elektrolitów, monitorowanie stanu zdrowia jamy ustnej oraz tłumaczenie ludzkiego języka ciała (Yeoman i McMahon-Beattie, 2015).

W kolejnym roku pisano o erze UW. Skupiono się na ich zastosowaniu jako sensory i punkty pomiarowe, które umożliwiają monitorowanie stanów aktywności czy fizjologii, jednakże określono również pewien kierunek związany z medycyną. Zaczęto opisywać zastosowanie tego rodzaju urządzenia jako protezy kończyn. Ten kierunek dał potencjał rozwoju ideom transgresyjnym takim jak trans- czy post-humanizm (Matos i in., 2016; Vinay i in., 2016).

W roku 2017 UW opisywano jako potencjalne narzędzia komunikacji pomiędzy marką a konsumentem (Wu i in., 2017; Tanti i Buhalis, 2017).

Urządzenia te, ze względu na stałe połączenie z internetem, pozyskują duże ilości danych, dzięki temu marka ma możliwość analizowania zachowań konsumenckich w czasie rzeczywistym, np. poprzez rozwiązania oparte na udostępnianiu lokalizacji klienta czy skutecznym kanale płatności, zapewniając wysokiej jakości obsługę marketingową oraz specjalne usługi sprzedażowe na życzenie klienta (Wu i in., 2017). Z drugiej strony, poruszony został temat ochrony danych osobowych, prywatności oraz zagrożeń i konsekwencji ciągłego podłączenia do internetu. Specjaliści wskazali takie zagrożenia jak monitoring i przechwytywanie danych, między innymi w postaci prywatnych zdjęć z pamięci urządzenia czy robienia zdjęć otoczenia bez wiedzy użytkownika. Opisano również istotę świadomości rodzaju prywatnych danych narażonych na udostępnienie oraz ich zabezpieczenie (Ghazinour i in., 2017).

Rok 2018 ukazał zupełnie nowe podejście do UW. Zaczęto bardziej ingerować w życie konsumentów, projektując rzeczy będące częścią ich codzienności, z dodatkową funkcjonalnością i sensorami, np. inteligentna biżuteria, kołdra albo śpiwór (Wissinger, 2018; Biswas i in., 2018). Pojawiła się również klasyfikacja tych urządzeń jako elementów składowych ekosystemu Internet of Things (Maglogiannis i in., 2018; Srinivasa i in., 2018; Koo i Fallon, 2018; Tussyadiah, Jung i Dieck, 2018). Rozwój tej technologii dodatkowo umożliwił stworzenie sieci WBSN, która automatycznie monitoruje rytm bicia serca użytkownika i wskazuje nieprawidłowości, które mogą świadczyć o chorobie (Soudani i Almusallam, 2018).

W 2019 r. publikacje obejmowały również tematykę zastosowania UW w medycynie, między innymi jako detektor IR, z którym komunikacja odbywa się za pomocą mrugnięć oczu oraz prostych ruchów głowy osób sparaliżowanych (Malik i Mazhar, 2019). Poruszano również tematykę bezpieczeństwa publicznego (Alsamhi i in., 2019) oraz komunikacji z klientem (Cena, Likavec i Rapp, 2019; Alt i in., 2019; Berkemeier i in., 2019).

Metodyka badania empirycznego

Celem badania empirycznego była próba znalezienia odpowiedzi na następujące pytania:

• Czy UW są znane wśród przedstawicieli młodego pokolenia?
• W jakim stopniu młodzi konsumenci deklarują wykorzystanie tych urządzeń?
• Jakie są postawy młodego pokolenia w stosunku do UW i od czego są one zależne?

Badanie empiryczne oparto na dwóch technikach ankietowych: audytoryjnej oraz internetowej z wykorzystaniem kwestionariusza. Instrument badawczy składał się z dwóch części. Pierwsza dotyczyła rozpoznania, czy uczestnicy badania znają i czy korzystają z UW. Następnie zapytano o preferowane formy płatności oraz poproszono o ustosunkowanie się w podanej skali (od 3 do –3 z antonimami na biegunach skali, gdzie 0 jest wartością neutralną) do określeń charakteryzujących płacenie smartfonem oraz inteligentnym zegarkiem. Ostatnie pytanie z pierwszej części dotyczyło identyfikacji postaw konsumentów na bazie pytania ze skalą Likerta (od 1 do 5, gdzie 1 oznaczało odpowiedź „zdecydowanie się nie zgadzam”, natomiast 5 — „zdecydowanie się zgadzam”), odnoszących się między innymi do wszczepienia pod skórę UW, zastąpienia smartfonów przez UW w przyszłości czy traktowania tych urządzeń jako nowego kanału komunikacji pomiędzy marką a konsumentem. Druga część kwestionariusza obejmowała pytania metryczkowe dotyczące cech demograficzno-społecznych respondentów.

Respondentów do badania dobrano w sposób celowy. Kategorią przynależności do próby był wiek. Uwzględniono wyłącznie ludzi młodych — do 30. roku życia, ze względu na to, że są to konsumenci posiadający szczególnie wysokie kompetencje technologiczne (Linkiewicz i Bartosik-Purgat, 2017; Gregor, Gotwald-Feja i Łaszkiewicz, 2017; Tkaczyk, 2018; Stopczyńska, 2018; Gregor i Kaczorowska-Spychalska, 2018), które sprzyjają skłonności do korzystania z nowych technologii, bez których nie wyobrażają sobie życia (Twenge, 2019). Szczegółowe dane na temat respondentów prezentuje tabela 2.

W badaniu wzięły udział 173 osoby. 43% z nich to mężczyźni, pozostałe 57% — kobiety. Wiek respondentów, jak już wspominano, był ograniczony w przedziale 19–30 lat. Większość z nich (75%) to osoby w wieku 19–24 lat, pozostali (25–30 lat) stanowili 25%. Ponad połowa respondentów (prawie 57%) to osoby ze średnim wykształceniem, nieco ponad 43% — z wyższym.

Prawie 3/4 badanych to studenci, 18% to osoby pracujące, które nie studiują. Natomiast ponad 8% respondentów zadeklarowało, że łączy pracę zawodową ze studiami. Zdecydowana większość badanych mieszka w miastach (prawie 83%), w tym głównie w miastach powyżej 500 tys. mieszkańców (prawie 54%).

Analiza wyników badania

Jednym ze szczegółowych celów badania empirycznego była identyfikacja znajomości pojęcia UW oraz poznanie, czy przedstawiciele grupy badanej z nich korzystają. Znajomość pojęcia wearables została zadeklarowana w ponad 44% przypadków.

Następnie zbadano, jaki odsetek respondentów zna oraz korzysta z przytoczonych przykładów UW (por. tabela 3).

Urządzeniami najlepiej znanymi respondentom są inteligentny zegarek, wskazany przez ponad 97% badanych, słuchawki — prawie 93% oraz inteligentna opaska, której znajomość określiło ponad 85% badanych. Natomiast najmniej znane są inteligentne ubrania, soczewki oraz tatuaże.

Warto jednak zwrócić szczególną uwagę na wyniki określające znajomość inteligentnych chipów, które są wszczepiane pod skórę, oraz okularów AR — oba przykłady zostały wskazane jako znane przez ponad 60% respondentów.

Inteligentne chipy zostały spopularyzowane między innymi przez test przeprowadzony w Szwecji w 2018 r. na próbie 3000 osób (Ma, 2018). Urządzenia wielkości ziarnka ryżu, wszczepione pod skórę w okolicach nadgarstka umożliwiały między innymi dokonanie opłaty za zakupy, otwarcie drzwi czy odblokowywanie zabezpieczonych pamięci masowych (Gillenson i in., 2019). Natomiast okulary AR zostały rozpowszechnione głownie dzięki Google Glass marki Google, które umożliwiały między innymi szybkie pozyskanie informacji z internetu, dyskretne robienie zdjęć oraz nagrywanie materiału wideo (Kęsy, 2017).

Stopień wykorzystania UW jest jednak niewielki. Prawie 43% badanych deklaruje korzystanie ze słuchawek, 22% z inteligentnych opasek, z zegarków natomiast prawie 18%. W przypadku pozostałych urządzeń badani nie zadeklarowali korzystania lub zrobili to w stopniu nieznacznym.

Należy przy tym zwrócić uwagę na jeden dość istotny szczegół. Porównując stopień znajomości pojęcia UW oraz wyniki z tabeli 3, można zauważyć, że nie są one ze sobą zgodne. Oznacza to, że prawdopodobnie respondenci nie kojarzą tego pojęcia z urządzeniami takimi jak między innymi inteligentny zegarek czy opaska.

W kolejnym etapie zbadano preferowane formy płatności po to, aby zidentyfikować, jaki procent próby badawczej wykorzystuje UW do tego celu (por. tabela 4).

Co ciekawe, płatność w tradycyjnej formie — gotówką — została wskazana tylko przez 64% badanych. Prawie każdy korzysta z kart płatniczych (debetowej i/lub kredytowej). Ponad 60% korzysta z oferowanego w bankach systemu blik. Jest to jeden z przykładów płatności natychmiastowych.

W Polsce został on uruchomiony przez Polski Standard Płatności w 2014 r.

z inicjatywy sześciu głównych banków komercyjnych (Jagodzińska-Komar, 2019). Smartfon, którego wykorzystanie wśród młodych ludzi do 2019 r. ma przekroczyć 90% (Gregor i Gwiaździński, 2019), w badaniu wskazało niecałe 32%. Pozostałe zaproponowane formy płatności, w tym przykłady UW, zadeklarowało mniej niż 15% badanych.

Po zidentyfikowaniu preferencji w zakresie form płatności zbadano postawy względem procesu dokonywania płatności przy użyciu smartfona oraz inteligentnego zegarka (por. rysunek 1).

Stosunek respondentów do płacenia zarówno smartfonem, jak i inteligentnym zegarkiem znajduje się powyżej wartości neutralnej (0), co oznacza, że jest on pozytywny. W kwestii zapewnienia bezpieczeństwa danych osobistych lepiej postrzegane jest płacenie smartfonem, natomiast różnica pomiędzy tymi sposobami zakupu jest niewielka. Respondenci twierdzą, że proces płatności jest bardziej intuicyjny również w przypadku smartfonów. Uważają także, że smartfon zapewnia większe bezpieczeństwo transakcji płatniczych oraz jest bardziej atrakcyjnym rozwiązaniem niż inteligentny zegarek. Z kolei innowacyjność rozwiązań postrzegana jest tak samo.

Zestawiając ze sobą wyniki z tabeli 4 oraz rysunku 1, można zauważyć, że pomimo pozytywnych postaw o niewielkim zróżnicowaniu, respondenci dość rzadko deklarowali takie sposoby płatności. Powinno się w tym przypadku zadać pytanie, dlaczego występuje taka sytuacja.

W przypadku inteligentnego zegarka barierą może być cena urządzenia, natomiast smartfon jest urządzeniem o bardzo wysokim stopniu penetracji wśród młodych konsumentów; cena nie stanowi tutaj problemu. Rynek urządzeń mobilnych jest bardzo nasycony, ponadto taka forma płatności jest dostępna w większości modeli dostępnych na rynku. Możliwe, że konsumenci nie mają wiedzy w tym zakresie, nie wiedzą, że taka funkcja jest dostępna oraz jak z niej korzystać. Zidentyfikowanie powodów takiej sytuacji jest niezwykle istotne i może stanowić odrębny cel badań w tym obszarze.

Ostatnim badanym aspektem były postawy respondentów względem zaproponowanych stwierdzeń na temat UW (por. tabela 5).

W toku prowadzonych analiz zbadano wewnętrzne zależności zachodzące w zbiorze ośmiu zmiennych opisujących odczucia respondentów. Współczynniki na przekątnej macierzy przeciwobrazu korelacji przekraczały wartość progową 0,5. Dla poddanych analizie ośmiu zmiennych test sferyczności Bartletta¹ wyniósł 257,326 (przybliżone χ2) przy 28 stopniach swobody i wartości p = 0,000, natomiast współczynnik KMO wyniósł 2 0,723. Trafność teoretyczna konstruktu została zweryfikowana w kolejnym kroku poprzez zastosowanie eksploracyjnej analizy czynnikowej (EFA). Wykorzystano metodę wyodrębniania czynników uogólnionych najmniejszych kwadratów. W wyniku przeprowadzonej analizy osiem zmiennych wyjściowych zredukowano do trzech czynników wyjaśniających łącznie jedynie 47,356% ogólnej zmienności (co oznacza, że mniej niż połowa zmienności poszczególnych itemów została wyjaśniona przez stworzone konstrukty). Macierz ładunków czynnikowych została poddana rotacji z wykorzystaniem metody Varimax z normalizacją Kaisera. Wyniki analizy wykazały, że w każdym z wymiarów może być uwzględniona tylko jedna zmienna lub dwie zmienne pierwotne, a trzy z nich nie weszły do żadnego z czynników. Nie wykazano jednorodności konstruktu, w związku z czym zdecydowano się na analizę pojedynczych zmiennych.

Respondenci są raczej zgodni, że UW są bezpieczne dla ich danych osobistych takich jak hasła czy kody dostępu. Podobna sytuacja ma miejsce w przypadku stwierdzeń — UW ułatwiają im codzienne życie oraz pozwalają lepiej dbać o zdrowe i kondycję fizyczną. Większość badanych uważa, że UW mogą w przyszłości zastąpić smartfony oraz są nowym kanałem kontaktu pomiędzy marką a konsumentem. Ponad połowa respondentów zdecydowanie nie chciałaby sobie wszczepić pod skórę UW. Większość stwierdziła, że jest im trudno powiedzieć, czy korzystanie z UW powoduje rzadsze korzystanie ze smartfona, natomiast raczej są zgodni, że jest to tylko gadżet.

Analizując odpowiedzi, zauważono również, że:

• zmienna „płeć” różnicuje odpowiedzi dla stwierdzeń 1, 2, 3, 5 i 6;
• zmienna „wiek” różnicuje odpowiedzi dla stwierdzeń 1 i 4;
• zmienna „wykształcenie” różnicuje odpowiedzi dla zdań 1, 4 i 5;
• zmienne: „status zawodowy” i „miejsce zamieszkania” różnicują odpowiedzi dla wszystkich stwierdzeń.

Podsumowanie

Podsumowując, z roku na rok rola oraz potencjał UW rosną. Przedstawione raporty firm badawczych pokazują, że w przyszłości będzie coraz więcej urządzeń podpiętych do internetu. Zaprezentowane wyniki badań ilustrują jednak niski poziom wykorzystania tego typu urządzeń, dwukrotnie niższy niż poziom znajomości. Ciekawy jest również fakt niskiego wykorzystania UW w procesie dokonywania opłat przez badanych, pomimo pozytywnego do nich nastawienia. Praktyka przedsiębiorstw, szczególnie kluczowych graczy z branży technologicznej, dowodzi, że tego typu rozwiązanie staje się powoli nowym standardem płatności.

W przyszłości będzie można dokonywać płatności nie tylko za pomocą inteligentnego zegarka czy chipa, ale również za pomocą inteligentnych tatuaży, inteligentnej biżuterii czy inteligentnych paznokci. Postawy respondentów w tym zakresie są zależne najczęściej od miejsca zamieszkania, płci i wieku. Należy jednak pamiętać, że zaprezentowane wyniki badania opisują tylko ograniczony wycinek rzeczywistości ze względu na dość niewielką liczebność próby, co przekłada się na brak możliwości formułowania wniosków o charakterze uogólniającym. Dają jednak pewien pogląd na omawiane zagadnienia, wytyczając kierunki przyszłych badań, które ze względu na rosnący trend wykorzystywania tego rodzaju technologii będą coraz liczniejsze.

Przypisy

1 Odrzucamy hipotezę zerową o tym, że macierz korelacji jest macierzą jednostkową, na rzecz hipotezy przeciwnej (Malarska, 2005, s. 212).

2 Zaleca się, by wartość współczynnika KMO była większa niż 0,5, co oznacza, że badana próba jest adekwatna do założeń analizy czynnikowej (Malarska, 2005, s. 212).

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