1. Introduction
E-commerce or electronic commerce is defined as the development of buying and selling processes supported by electronic means and the internet [
1]. In the last twenty years, e-commerce has emerged as one of the most important markets for goods and services [
2].
According to Kemp [
3], a website with reports designed to help people and organisations find data, insights and trends resulting in more informed decision-making, 3.78 billion people made online purchases, an increase of 10% relative to the analysis carried out in the previous year. Still, in the same study, it was possible to identify that the total annual expenditure on online purchases was 3.85 billion, +18% more than last year. Despite the positive values presented previously at a global level, De Marco [
4] indicates that the expected levels for the prevalence of this type of practice in the Western world still need to be reached.
In the case of Portugal, it was found that, in 2020, sales of goods or services carried out through e-commerce represented 17% of business volume, a value that decreased by 2.8 percentage points (p.p.) compared to 2019 [
5]. Regarding 2021, we verified that 25.2% of internet users in Portugal made online purchases, showing an improvement of 8.2%, although it is still considered a small value [
6]. We also found that only 14.1% of companies with websites in Portugal place orders or reservations for products online, which makes it difficult for users to adhere [
5]. According to Veybitha [
7], e-commerce is becoming popular among younger generations, such as Generation Z. Generation Z, known as the Net-Generation, E-Generation or iGen, refers to individuals born between 1995 and 2010 [
8]. This is a more technological generation, as these individuals were born during the advent of new technologies, and it is therefore quicker and easier for them to move online [
9]. The research by Costa [
10] states that this generation will manage and direct the world in the coming years.
As previously mentioned, despite positive results overall, De Marco [
5] states that the expected levels for the prevalence of this type of practice in the Western world, a world in which Portugal is included, still need to be reached. We chose to carry out this research on Generation Z, as it is a generation going through the transition period from adolescence to young adulthood, becoming an important group in the job market [
7]. Thus, with great potential for purchasing power, they are becoming essential to guarantee the success of a company’s communication and marketing [
11]. Corroborating the above information, Vieira [
8] indicates that this generation will represent the most relevant group of consumers in e-commerce in the coming years. The behaviour of younger generations tends to be quite different from previous generations due to political, cultural, and socioeconomic changes, which makes understanding this group more critical [
12]. Through this study, we intend to contribute to this topic with recent data, aiding the increase in knowledge at a national level and allowing us to understand whether Generation Z users accept this type of technology in Portugal.
Therefore, the following research question was created: How does Generation Z accept e-commerce in Portugal? Given the research question, the general objective was defined, which consists of understanding the acceptance of e-commerce by Generation Z in Portugal. The following specific objectives were also defined:
Define the digital consumer profile of Generation Z;
Check the impact of security and privacy concerning perceived risk;
Verify the impact of perceived risk, privacy and security on the trust factor;
Investigate whether the perceived ease of use and attitude can influence purchase intention;
Determine technological acceptance by Generation Z in Portugal.
In this way, we intend to understand the level of acceptance of Generation Z concerning the acceptance of e-commerce and technology in Portugal, proposing a conceptual model that can explain the acceptance of this technology and testing this model through the analysis of the factors, dimensions, variables, and respective causal relationships defined therein.
This study is different from other existing studies addressing e-commerce and Generation Z, as it is a study applied to the Portuguese population. In this way, it is hoped that this study will contribute to understanding the types of consumers that Generation Z in Portugal are, while providing recent data on this subject and increasing knowledge at a national level, which would allow this information to be used at an academic and business level.
5. Research Model
The proposed model (
Figure 4), presented below, is an adaptation of the model created by Lestari (
Figure A1) [
23]. The author believes that Generation Z consumers could represent many opportunities for companies. Therefore, future studies should consider other variables to examine regarding the direct or indirect effects of adopting technology. The TAM model was also used as a basis to develop this model proposal. It is considered essential to have this model (TAM) as a base because it is one of the most pop1ular models used to research the acceptance and use of technology [
24], and the model in this paper is based on it.
In this way, the following hypotheses were defined, which are also shown in
Figure 4:
H1:
Perceived risk has a negative impact on digital consumer confidence.
H2:
Perceived ease of use has a positive impact on attitude when adopting an e-commerce platform.
H3:
Perceived ease of use has a positive impact on the perceived usefulness related to the use of e-commerce platforms.
H4:
Perceived ease of use has a positive impact on the intention to adopt an e-commerce platform.
H5:
Attitude has a positive impact on the intention to adopt an e-commerce platform.
H6:
Purchase intention has a positive impact on the current use of e-commerce platforms.
H7:
Online privacy has a negative impact on consumer perceived risk.
H8:
Online privacy has a positive impact on consumer trust.
H9:
Online security has a positive impact on consumer trust.
H10:
Online security has a positive impact on consumer perceived risk.
Although it was possible to study several relationships between variables using this model, considering time constraints, only ten were analysed. Making this decision resulted in a high number of relationships being studied within a short period. In this way, the remaining relationships were analysed by inference (i.e., that which is deduced from something else; illation; deduction; conclusion [
25]). For example, Hypothesis 5 (i.e., attitude has a positive impact on the intention to adopt an e-commerce platform) is considered valid since the variables PIIT, AE, CONF, and RP would also have a positive impact on the intention to adopt technology since this attitude is related to all the variables mentioned above.
For the insertion of external variables, reference was made to the analysis carried out in the literature review, which is in line with the proposed study objectives:
The concept of self-efficacy is defined as an individual’s perception of their ability to control and influence an action or change behaviour [
26].
Self-efficacy is a construct that affects the selection of human action, regardless of the existing alternatives, the amount of effort that will be required to carry out the action and the resistance to face obstacles and the opportunities to act; that is, self-efficacy is an essential factor in influencing behaviour through a process, where it is necessary to establish the goals to be achieved, outcome expectations and challenges that may be encountered [
27]. There is also the concept of computer self-efficacy (CSE), which is defined as the self-assessment of the ability to use a computer, associated with the belief that users have about their ability to deal with existing challenges associated with this [
28].
According to Eraslan Yalcin and Kutlu [
28], CSE has a high influence on the acceptance of a technology, as users are more likely to use a technology when they need less effort to use it. Individuals with high self-efficacy tend to believe that they can perform well in the future, even in situations with high difficulty. Consequently, they tend to view difficult tasks as something to be mastered, rather than something to avoid [
29].
In addition, people with high self-efficacy associated with information technology find it less difficult to use and have more a positive attitude towards it [
29].
Perceived usefulness is defined as a user’s subjective belief that using a technology will increase their performance when performing a task [
30]. In the context of e-commerce, perceived usefulness will make it possible to improve the following activities for the user [
31]: improving performance when shopping online; increasing their effectiveness when shopping online; increasing productivity; and faster online shopping.
Perceived usefulness is made up of the benefits that customers can obtain by saving time and money and making decisions between a wide variety of products and services [
32]. In addition to the benefits mentioned above, there are now more and more ways to reward customers, such as promotions and free delivery. In this way, perceived usefulness is considered to influence consumer intentions and attitudes towards e-commerce [
33].
The perception of ease of use is a subjective judgement on the part of users regarding the degree to which they feel that using a technology can make their process easier and free of psychological and physical effort [
34]. In other words, if a person feels that a new technology is easy to use in the process of carrying out a task, they may pass on positive feedback to those closest to them and will be more inclined to use the technology [
35].
A consumer making an online purchase expects to find specific information or products without having to make a great effort and also expects this action to take as little time as possible. They also expect to find products and services online as easily as possible, with the benefit of comparative analyses of prices, availability, payment terms, delivery terms and privacy policies [
33].
Perceived ease of use has been recognised as one of the main elements influencing attitude and intention to use, as in the TAM model [
36]. It is therefore considered a necessary factor in establishing the acceptance of the use of technology in relation to online shopping [
33].
Perceived risk is considered a form of lack of confidence and refers to general assessments of uncertainty, which may be reflected in adverse consequences in the future [
37]. The consumer’s perception of risk is a major obstacle and is considered by most scholars to be the main factor affecting the adoption of a technology [
38]. Regarding online shopping, there are four types of perceived risk that can be considered [
39]: psychosocial risk—the anticipated harm affects the consumer’s identity or self-esteem; financial risk—this is a monetary harm, as there may be a loss of money; time risk—this harm causes the consumer to lose time, such as when there is a delay in the delivery of the product; product or performance risk—this damage occurs when expectations about the product are not met after it has been used.
With the evolution of the internet and the possibility of making online purchases, consumer uncertainty has increased significantly due to the types of risks mentioned above [
40]. Therefore, individuals with a higher perception of risk are not likely to buy products or services online, as their intentions are suppressed when they discover that the transaction may be risky [
41].
In order to corroborate the previous information, Fortes and Rita [
42], by analysing various studies, indicate that perceived risk has a negative effect on the intention to buy online. The same authors add that this factor also has a negative effect on consumer attitudes towards online purchases.
Trust is defined as a subjective disposition to believe in the occurrence of an action consistent with positive assumptions [
43]. Thus, trust is considered a multidimensional factor, consisting of [
44]: benevolence—interest in creating a relationship and avoiding opportunistic situations; honesty—belief that third parties will behave honestly, keep their promises and can be counted on to do the right thing; competence—in the online environment this involves, for example, a website having the technical and commercial infrastructure to carry out its activities successfully.
In e-commerce, trust plays an important role because customers cannot touch, see in person or check the quality of a product. In addition, they also have concerns associated with making online payments [
45]. The same author states that trust is an important predictor of attitude towards online purchases and online purchase intention [
42], adding that this factor also negatively influences perceived risk.
Information security is an important asset of any organisation and must be highly protected, as the loss or disclosure of this asset can damage the company [
46].
Security, in the context of e-commerce, is a necessity and is defined as the implementation of rules and/or protocols that carry out all transactions in a secure manner [
47].
According to [
48], consumer perception of this factor is associated with both online transactions and financial information to ensure that there is no unauthorised access. The factor that can increase online transactions in e-commerce is the guarantee of security [
49]. Thus, security is important in online shopping, as it is a direct and significant factor in consumer intention [
50].
In addition to the aforementioned influence, this factor also affects perceived risk, as it influences the buyer’s mindset and purchasing behaviour [
51]. Another factor that influences security is trust, since the higher the level of security, the greater the possibility of securing customers and the more customers will make purchases [
36].
Privacy is recognised as a fundamental human right by the United Nations [
52] and is defined as an individual’s right to control the collection and use of personal digital data and non-digital information, as well as its unapproved disclosure [
43]. Due to many widely publicised news stories through the media over the past few years about personal data breaches, consumers have become unsure about how and where their personal information is used [
36].
The increased use of e-commerce over the years has led to privacy becoming a more relevant issue in e-commerce, as it has resulted in a huge amount of personal information about consumers being collected and used [
52].
The impacts of privacy concerns lead to less trust and consequently a perception of greater risk when sharing information online [
52]. Due to this concern, data protection laws have been implemented in most countries, such as the GDPR [
43]. According to Fortes and Rita [
42], after they analysed various studies, in addition to this factor influencing the intention to buy online, it also has an influence on perceived risk, trust and attitude when making an online purchase.
Attitude is defined as an individual’s positive or negative view of a behaviour. This individual is concerned with the possible consequences of carrying out that action, which may lead to different decisions based on different evaluations [
35].
Associated with online shopping, a customer’s attitude is often associated with emotion and is considered the main predictor of the intention to adopt a technology [
34]. This construct has been used in various theories of IT adoption, such as TRA, TAM and DTPB [
53]. According to Ariff et al. [
54], based on studies carried out, attitude can be expected to have a significant and direct impact on online purchase intention.
Therefore, it is considered that when consumers have positive perceptions of a certain technology, their adoption intentions will also increase [
34]. The same is true in reverse, i.e., if a user has negative perceptions of a particular technology, their adoption intention will decrease.
6. Methodology
The present investigation is a quantitative and descriptive study, with theoretical research being initially carried out, and subsequently, an online questionnaire was carried out as the main data collection method.
To carry out this study, we adapted the model created by Lestari [
23], which is an adaptation of the TAM (technology acceptance model). The author considers that the segmentation of Generation Z consumers could offer many opportunities for companies. Therefore, future studies should consider other variables to examine direct or indirect effects on technology adoption.
The analysis carried out in the literature review was used as a reference to insert new external variables, evaluating the following studies: [
16,
17,
18,
19,
20,
21,
22,
23,
24,
25,
26,
27,
28,
29,
30,
31,
32,
33,
34,
35,
36,
37,
38,
39,
40,
41,
42,
43,
44,
45,
46,
47,
48,
49,
50,
51,
52,
53,
54,
55,
56,
57,
58,
59,
60,
61,
62,
63,
64,
65].
Five objectives were defined, with four of the five objectives being associated with the ten defined hypotheses, as shown in
Table 1. Therefore, to answer the hypotheses, a structural equation modelling analysis was carried out using the SmartPLS 4 tool. Unfortunately, it was not possible to analyse Hypothesis 6 (i.e., purchase intention has a positive impact on the current use of e-commerce platforms) using this tool since it does not support relationships between ordinal qualitative variables and ordinal qualitative variables. Therefore, the analysis of this hypothesis was carried out with the help of the IBM SPSS Statistics tool.
The data relating to the study were collected through a survey carried out using an online questionnaire, which was anonymous. Through the analysis of this investigation, the aim was to obtain an understanding of the technological acceptance of e-commerce by members of Generation Z in Portugal, as well as to define their digital consumer profile.
The questionnaire developed was composed of four groups of questions, based on the model explained above. The questionnaire was divided as follows:
First group—demographic characterisation: The first group deals with the demographic characteristics of the respondent. The information collected includes gender, year of birth, complete educational qualifications, region (NUT) where respondents live, monthly income and, finally, professional occupation.
Second group—online shopping: The second group seeks to understand the relationship between the factors of online shopping and the consumer and thus answer the proposed hypotheses. The aim is to better understand the relationships associated with the factors of personal innovation, self-efficacy, perceived use, perceived ease of use, trust, perceived risk, security, privacy, attitude and purchase intention, using a Likert scale of agreement (1–5), where 1 represents “Totally Disagree” and 5 represents “Totally Agree”. It was decided to standardise the scale because, according to Queiroz et al. [
55], it is easier to construct and administer and has the great benefit of being easier for respondents to understand. Finally, we sought to understand the current use of e-commerce in Portugal, through the yes/no question “Do you shop online”?
Third Group—characterisation of the Generation Z digital consumer: The third group portrays the characterisation of the Generation Z digital consumer, and the respondent only had access to this group of questions if the answer given in the question “Do you shop online?” in
Section 2 was Yes. The aim of this section is to understand the reasons for liking to shop online, the frequency with which they do so, the amount they spend on these purchases every six months, as well as the number of purchases made online per year. This section also includes categories of products bought online and also aims to understand whether or not these respondents only use this channel to buy products or not.
Fourth group—reasons for not using e-commerce: Finally, the fourth group examined the main reasons why respondents had never used e-commerce. As in the previous section, a respondent only had access to this group if the answer given to the question “Do you shop online?” in
Section 2 was No.
After designing the questionnaire, the consistency test was carried out through Cronbach’s alpha analysis using the IBM SPSS Statistics tool. By analysing the result, it was concluded that its consistency was good (
Table 2).
To define the necessary sample that can represent the number of individuals present in Generation Z in Portugal, and consequently, this is the sample essential to completing the study, the Krejcie and Morgan formula was used [
66]. After the calculations were carried out, it was concluded that the required number of valid responses to the questionnaire would be 385.
The initial sample consisted of 404 responses, resulting from data collection through a questionnaire carried out between 10 May 2023 and 15 July 2023. As this is a study related to Generation Z, only responses from individuals born between 1997 and 2010 were accepted.
As the questionnaire was online, it was shared in order to obtain the required number of responses required and was distributed digitally, using platforms such as Instagram, Facebook and WhatsApp, as well as by email.
Of the 404 responses to the initial sample, only 401 were used. The exclusion of these three responses was due to the fact that these users did not give their consent to be included in the study and so did not fill in the questionnaire, which only resulted in the information associated with the denial of consent being recorded.
9. Conclusions
In recent years, e-commerce has grown exponentially, emerging as one of the most important markets for goods/services. However, despite this growth, the necessary value for the prevalence of this practice in the Western world has yet to be reached. Generation Z is a more technological generation, covering an age group that includes teenagers and young adults. They have more purchasing power as they go through this transition, and some of them are joining the job market.
Through the analysis of results, carried out with a valid sample of 401 participants, it was possible to analyse the proposed hypotheses, learn more about this generation’s digital consumption, and define their profile as consumers. Regarding the defined proposals (H1 to H10), and with the help of the SmartPLS 4 and IBM SPSS Statistics tools, it was possible to conclude that Hypotheses H3, H5, H6 and H9 were supported. Therefore, we can state that for Generation Z consumers in Portugal, the easier it is to use an e-commerce platform, the greater their perception of its usefulness will be; the more positive their attitude, the greater their intention to use this platform; the safer this consumer feels, the greater their confidence in making online purchases will be; and, finally, the greater their intention to use this technology, the greater the probability of them actually using the e-commerce platforms and engaging in online purchasing activity.
Regarding H5, we found that the attitude variable positively influenced the intention to use. Therefore, we infer that self-efficacy, personal innovation applied to information technology, perceived usefulness, trust and perceived risk also present a positive relationship to the use of technology. This relationship is a result of these variables influencing attitude. Therefore, if attitude positively influences the intention to use a platform, so do the previously mentioned variables. The remaining five hypotheses were rejected for the variables’ lack of significant relationships.
Regarding the Generation Z digital consumer profile in Portugal, there are no differences between specific birth years for this generation. Individuals with educational qualifications and a monthly income make online purchases in all regions (NUT). Most of these consumers are female, representing 58.6% of the sample. Despite this majority, male consumers also make considerable use of e-commerce, with a total of 171 male respondents, approximately 93%, indicating that they make online purchases.
These consumers are more technologically confident and, therefore, believe that they deal well with most digital technologies. They indicate that e-commerce platforms are easy to use, they do not consider making online purchases to be risky, and they also consider purchasing online to be safe.
Despite feeling comfortable in this regard, they are consumers who are aware and concerned about possible online threats, more specifically, security and privacy threats. In general, it is stated that these consumers make online purchases every six months, spending between EUR 21 and EUR 70 during this period. Despite indicating a semi-annual frequency, they also suggest that they make purchases between five and six times per year (31%) or more than eight times per year (40%). Regarding motivation, it was found that consumers of this generation value convenience, availability (24 h) and the variety of products and services that e-commerce platforms provide.
When it comes to the categories of products most purchased online by this type of consumer, it was found that the clothing category stands out the most. Then, with less frequency, consumers make online purchases such as travel, accommodation/hotels, films, books or music, events, and finally, food. Hence, we can see that this generation’s consumer does not only shop digitally, with most respondents making purchases both online and through the more traditional method in a physical store.
This study aims to contribute to a deeper understanding of the acceptance of e-commerce in Portugal by Generation Z, as well as defining the digital consumer profile of this age group. It is also hoped that it will be useful for understanding this type of consumer, contributing recent data on this subject, allowing for an increase in knowledge at a national level, and this information can be used at both an academic and business level, specifically on the themes of e-commerce and technological acceptance, thus allowing companies to see how Generation Z views the market and improve their business strategy.
One of the limitations is that not all the relationships in the proposed model were validated due to the fact that it was quite extensive, and these relationships were affected by inference. The other limitation considered is that some less efficient constructs were kept for this model in the “Constructing Reliability and Validity” section, which could have resulted in a more adjusted and meaningful model.
In future investigations, it would be pertinent to apply this analysis model to the remaining existing generations to compare the results obtained in this study with those obtained in other generations, thus verifying if they present similar behaviour. The same analysis could be carried out in another country to understand whether this generation has the same acceptance and an identical digital consumer profile there. Testing all variables and their relationships in future research is considered pertinent. Finally, future investigations may consider e-commerce in terms of gaming/streaming products. This was one of the categories that was not included in the survey. However, of those types that were not included, it was among the most suggested by respondents. This study could be replicated with a larger sample, with a need for greater attention to be paid to the items that are retained or eliminated in each of the constructs, dimensions or latent variables, thus revising the analysis carried out in the “Constructing Reliability and Validity” section until a more adjusted and meaningful model is achieved.