Technological Acceptance of E-Commerce by Generation Z in Portugal
Abstract
:1. Introduction
- 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.
2. E-Commerce
3. Generation Z
4. Technology Acceptance Model (TAM)
5. Research Model
- Self-efficacy Factor
- Perceived Usefulness Factor
- Perceived Ease of Use Factor
- Perceived Risk Factor
- Trust Factor
- Security Factor
- Privacy Factor
- Attitude Factor
6. Methodology
- 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.
7. Results
7.1. Sample Characterization
7.2. Constructing Reliability and Validity
7.3. Hypothesis
8. Discussion
- H1: PR−>TRU—Hypothesis 1, which indicates that perceived risk has a negative impact on digital consumer confidence, is not supported. This hypothesis was not supported by the analysis of p- and t-values, with the p-value being greater than 0.050 and the t-value being less than 1.96, which demonstrates that this relationship is not significant. Although this relationship is not significant, it can be seen, through the beta value, that there is a negative relationship between the variables; that is, a consumer who has a perception of risk may not experience a decrease in their confidence when carrying out online shopping.
- H2: PEOU−>ATT—Hypothesis 2 was rejected; therefore, it is concluded that in Portugal, for Generation Z, the perceived ease of use does not have a positive impact on attitude when utilising an e-commerce platform. This conclusion was reached because the t-value was less than 1.96, and the p-value was greater than 0.050. The same results for this hypothesis were also obtained in the study carried out by [68].
- H3: PEOU−>UP—Perceived ease of use has a positive impact on the perceived usefulness related to the use of e-commerce platforms. This is due to the analysis carried out using the values obtained in Table 3, whose t-value is 9.662 (higher than 1.96) and the p-value is 0.000 (lower than 0.050), which demonstrates that it is a positive relationship. From the beta value, it can be verified that this is a positive relationship. The same result for this hypothesis is also obtained in the study carried out by Kanchanatanee [69].
- H4: PEOU−>PI—When analysing the significance of the t- and p-values, it can be concluded that Hypothesis 4 is not supported, as it is not a significant relationship. The same results for this hypothesis were also obtained in the study carried out by Figueiredo [62]. Although it is not significant, it can be verified, through the analysis of the beta value, that there is a positive relationship between the variables.
- H5: ATT−> PI—Through Table 3, it can be seen that there is a t-value of 18.374 and a p-value of 0.000. Since 18.374 is greater than 1.96 and 0.000 is less than 0.050, this relationship is significant. Through the beta value, this is a positive relationship; therefore, it can be concluded that attitude has a positive impact on the intention to utilise an e-commerce platform. A customer’s attitude is often associated with emotion and is considered the main predictor of their intention to adopt a technology [34]. The same hypothesis result was also obtained in the study carried out by Ramadania and Aldhmour [70,71].
- H7: TRU−>PR—Through the analysis of the p- and t-values, it can be concluded that this hypothesis is rejected at the significance level, with the t-value being lower than 1.96 and the p-value being higher than 0.050. When analysing the beta value, it can be verified that these variables present a positive relationship; therefore, it can be stated that online privacy has a positive impact on the risk perceived by the consumer.
- H8: PRIV−>TRU—It can be concluded that online privacy has a positive impact on consumer trust based on the beta value analysis. Despite this value, the t-value is less than 1.96, and the p-value is greater than 0.050; therefore, it is not a significant variable, and therefore this hypothesis is rejected.
- H9: SEC−>TRU—It can be concluded that online privacy has a positive impact on consumer trust based on the beta value analysis. Despite this value, the t-value is less than 1.96, and the p-value is greater than 0.050; therefore, it is not a significant variable, and therefore this hypothesis is rejected.
- H10: SEC−>PT—Based on the analysis of the t (1.307)- and p (0.191)- values, it is considered that the hypothesis is not supported, as it appears that the t-value is lower than 1.96 and the p-value is higher than 0.050. With the analysis of the beta value, it is verified that these variables present a negative relationship. Thus, it is considered that for Generation Z consumers in Portugal, security has a negative impact on perceived risk; that is, the safer the consumer feels, the lower the perception of risk.
- If, at most, 20% of the frequencies are less than five and none are less than 1, then the assumption is fulfilled.
9. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
Appendix A
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Objectives | Hypotheses |
---|---|
| N/A |
| H7, H10 |
| H1, H8, H9 |
| H4, H5 |
| H2, H3, H6 |
Cronbach’s Alpha Result | Alpha Coefficient Range | Strength of Association |
---|---|---|
0.701 | <0.6 | Poor |
0.6 to <0.7 | Moderate | |
0.7 to <0.8 | Good | |
0.8 to <0.9 | Very Good | |
0.9> | Excellent |
Construct | Cronbach’s Alpha | Composite Reliability | AVE |
---|---|---|---|
ATT | 0.770 | 0.897 | 0.813 |
PI | 0.791 | 0.905 | 0.827 |
PRIV | 0.569 | 0.759 | 0.529 |
RP | 0.392 | 0.240 | 0.417 |
SEC | 0.392 | 0.672 | 0.440 |
PU | 0.734 | 0.849 | 0.654 |
ATT | TRU | PEOU | PI | PRIV | RP | SEC | PU | |
---|---|---|---|---|---|---|---|---|
ATT | ||||||||
TRU | 0.391 | |||||||
PEOU | 0.329 | 0.201 | ||||||
PI | 0.985 | 0.352 | 0.420 | |||||
PRIV | 0.445 | 0.607 | 0.363 | 0.392 | ||||
RP | 0.531 | 0.524 | 0.524 | 0.695 | 0.417 | |||
SEC | 0.750 | 0.741 | 0.449 | 0.535 | 1.336 | 1.014 | ||
PU | 0.650 | 0.22 | 0.721 | 0.687 | 0.532 | 0.554 | 0.693 |
Hypotheses Tested | t-Value | p-Value | Beta Value |
---|---|---|---|
H1: PR−>TRU | 1.169 | 0.242 | −0.257 |
H2: PEOU−>ATT | 1.331 | 0.183 | −0.084 |
H3: PEOU−>PU | 9.662 | 0.000 | 0.618 |
H4: PEOU−>PI | 1.100 | 0.271 | 0.045 |
H5: ATT−>PI | 18.374 | 0.000 | 0.689 |
H7: PRIV−>TRU | 6.734 | 0.000 | 0.359 |
H8: PRIV−>PR | 1.385 | 0.166 | 0.278 |
H9: SEC−>TRU | 2.889 | 0.004 | 0.198 |
H10: SEC−>PR | 1.307 | 0.191 | −0.603 |
Hypotheses Tested | Result |
---|---|
H1: PR−>TRU | Rejected |
H2: PEOU−>ATT | Rejected |
H3: PEOU−>PU | Supported |
H4: PEOU−>PI | Rejected |
H5: ATT−>PI | Supported |
H6: PI−>CU | Supported |
H7: PRIV−>PR | Supported |
H8: PRIV−>TRU | Rejected |
H9: SEC−>TRU | Supported |
H10: SEC−>PR | Rejected |
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Duarte, C.; Messias, I.; Oliveira, A. Technological Acceptance of E-Commerce by Generation Z in Portugal. Information 2024, 15, 383. https://doi.org/10.3390/info15070383
Duarte C, Messias I, Oliveira A. Technological Acceptance of E-Commerce by Generation Z in Portugal. Information. 2024; 15(7):383. https://doi.org/10.3390/info15070383
Chicago/Turabian StyleDuarte, Carolina, Inês Messias, and Abílio Oliveira. 2024. "Technological Acceptance of E-Commerce by Generation Z in Portugal" Information 15, no. 7: 383. https://doi.org/10.3390/info15070383
APA StyleDuarte, C., Messias, I., & Oliveira, A. (2024). Technological Acceptance of E-Commerce by Generation Z in Portugal. Information, 15(7), 383. https://doi.org/10.3390/info15070383