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Contactless service encounters among Millennials and Generation Z: the effects of Millennials and Gen Z characteristics on technology self-efficacy and preference for contactless service

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Purpose “Contactless service” refers to the use of technology in providing products or services without a salesperson. This study explores the mechanism underlying Millennial and Generation Z (M/Z generations) consumers' preference for contactless service over salespersons in retail stores. In addition, this study tests differences between the M/Z generations. Design/methodology/approach The researchers predict characteristics to be antecedents of young consumer's preference for contactless service over salespersons and that the effects are mediated by technology self-efficacy. Next, a moderating variable (perceived consumer conformity) is added in the path between technology self-efficacy and the preference for contactless service. The hypotheses are tested among 142 Gen Z and 137 Millennial respondents. Findings The results show that M/Z generations’ characteristics significantly influence the preference for contactless service, except for security seeking. Also, interests in new technology and safety seeking are perceived higher by M/Z generations. The influence of technology self-efficacy on the preference for contactless service is moderated by social conformity. Originality/value As retail technology rapidly develops, the service industry is expected to change from the past, where salespersons played an important role, to contactless services. This study has academic and practical values, for the authors clarify the underlying psychological mechanisms of why young consumers prefer retail technology rather than communication with salespersons.
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Contactless service encounters
among Millennials and
Generation Z: the effects
of Millennials and Gen Z
characteristics on technology
self-efficacy and preference
for contactless service
Songmee Kim, Seyoon Jang and Woojin Choi
Department of Textiles, Merchandising, and Fashion Design,
Seoul National University, Seoul, Republic of Korea
Chorong Youn
Department of Clothing and Textiles, Pusan National University,
Pusan, Republic of Korea, and
Yuri Lee
Department of Textiles, Merchandising and Fashion Design, The Research Institute
of Human Ecology, Seoul National University, Seoul, Republic of Korea
Abstract
Purpose Contactless servicerefers to the use of technology in providing products or services without a
salesperson. This study explores the mechanism underlying Millennial and Generation Z (M/Z generations)
consumerspreference for contactless service over salespersons in retail stores. In addition, this study tests
differences between the M/Z generations.
Design/methodology/approach The researchers predict characteristics to be antecedents of young
consumers preference for contactless service over salespersons and that the effects are mediated by
technology self-efficacy. Next, a moderating variable (perceived consumer conformity) is added in the path
between technology self-efficacy and the preference for contactless service. The hypotheses are tested among
142 Gen Z and 137 Millennial respondents.
Findings The results show that M/Z generationscharacteristics significantly influence the preference for
contactless service, except for security seeking. Also, interests in new technology and safety seeking are
perceived higher by M/Z generations. The influence of technology self-efficacy on the preference for contactless
service is moderated by social conformity.
Originality/value As retail technology rapidly develops, the service industry is expected to change from the
past, where salespersons played an important role, to contactless services. This study has academic and
practical values, for the authors clarify the underlying psychological mechanisms of why young consumers
prefer retail technology rather than communication with salespersons.
Keywords Contactless service, Technology self-efficacy, Consumer conformity, Generation Z, Millennials
Paper type Research paper
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This paper forms part of a special section Pandemic Aftershock - The challenges of rapid technology
adoption and social distancing for interactive marketing practice, guest edited by Paul Baines, Mairead
Brady and Shailendra Pratap Jain.
The current issue and full text archive of this journal is available on Emerald Insight at:
https://www.emerald.com/insight/2040-7122.htm
Received 18 January 2021
Revised 21 July 2021
23 September 2021
Accepted 7 October 2021
Journal of Research in Interactive
Marketing
Vol. 16 No. 1, 2022
pp. 82-100
© Emerald Publishing Limited
2040-7122
DOI 10.1108/JRIM-01-2021-0020
1. Introduction
As technology rapidly develops, how people use it to communicate, connect, and discover is
changing. Many consumers are migrating from offline retail stores to online channels, and
offline retailers are struggling with the resulting declines in consumer spending. Companies
have introduced contactless service to increase productivity and efficiency (Walkr et al.,
2002), to lower or avoid high labor cost (Lin and Hsieh, 2007), and/or to offer customers access
to services via new and convenient channels (Meuter et al., 2003) aimed at better meeting
customer demand and increasing customer satisfaction (Bitner et al., 2002). Offline retail
stores still play a pivotal role in consumer experience, and retailers are trying to bring
technology to offline retail stores to make consumersretail experiences more convenient and
effective. In addition, many young consumers feel uncomfortable with interpersonal services
that require communication with others, generally preferring non-face-to-face interaction. As
a result, demand has increased for contactless service, which refers to non-face-to-face forms
of service that use technology to minimize human contact. Contactless service enables
consumers to avoid interacting with sales staff directly and to acquire products or services in
an unmanned condition or with minimal human contact.
Retail services using contactless technology include virtual reality (VR) technology,
interactive mirrors, socially interactive dressing room and in-store mobile applications that
enable consumers to indirectly touch and feel products. It also includes a self-checkout and
cashless payment system, where consumers can automatically make transactions without
queuing, and live streaming commerce that provides an immersive shopping experience.
Nordstrom Department Store in the USA introduced non-face-to-face styling services via
video-conferencing apps (WGSN, 2020). The sports retailer Decathlon in Germany introduced
ScanPayLeaveservice using a mobile self-checkout technology (WGSN, 2020). Moreover,
LAB101 in Korea has introduced an unmanned store specializing in jeans, which can only be
accessed by presenting a credit card.
A survey by Whistl (2018) found that 57% of British consumers use non-face-to-face
payment services to avoid human interaction in their shopping experience. Furthermore,
according to HMG Journal (2020), younger consumers enjoy these contactless technologies
more comfortably. As they share an enormous amount of information online, they prefer to use
contactless service, allowing them to have their own time, rather than having a connection
with others. Millennials and Gen Z (M/Z generations) are called digital natives, and the need for
contactless service is expected to be higher as people become accustomed to interacting with
machines or technologies rather than with humans. In the hyperconnected society, where
technology develops and connects people anytime and anywhere, they may feel tired of
contacting people and having too much interaction (Whelan et al.,2020).
This study uncovers the mechanism of M/Z generation consumerspreference for
contactless retail service over salespersons. First, this study expects that the characteristics
of M/Z generations are antecedents of the preference for contactless service over
salespersons and that the effects were mediated by technology self-efficacy. Next, we
extended the model, adding moderating variables related to the intentional avoidance of
salespersons in the path between technology self-efficacy and the preference for contactless
service over salespersons.
This study has an academic and practical significance when services are expected to change
from the past, where salespersons used to play an important role, to contactless services.
Although many previous studies have examined contactless retail services such as VR and
interactive mirrors (Kim et al.,2017;Roy et al., 2018), technology acceptance studies focusing on
the perceived value of technology predominate, and research regarding generational
characteristics remains scarce. In addition, this study is meaningful because it measured the
preference for contactless service rather than attitudes toward or intentions to use contactless
service. While customers who use contactless services in retail stores choose contactless
Contactless
service:
Millennials
versus Gen Z
83
services instead of services provided by salespersons, their intentions or attitudes cannot fully
explain the mechanism of the choice between contactless service and salespersons. Given that
even smart stores offer face-to-face services through salespersons, examining consumer
choices will presumably generate greater practical insights.
2. Literature review
2.1 Characteristics of M/Z generations
Although the definitions for generation vary, Mannheim (1952) suggested dividing groups
born in the same period based on the year of birth. By sharing historical and cultural
experiences simultaneously, each generation has a common notion or value, and they show
similar consciousness and consumption behavior (Rhodes, 1983). Prior studies have shown
that things people experience as they grow up, such as information and communication
technologies, affect individual values (Bakewell and Mitchell, 2003;Berkup, 2014;Francis and
Hoefel, 2018) and thus changes consumption values or beliefs (Bakewell and Mitchell, 2003;
Barber et al., 2011), and even the purchase decision-making process.
Emerging as leading forces in modern social culture, the M/Z generations also have many
similar characteristics, particularly when it comes to attitudes toward new technologies.
Members of the M/Z generations grew up in an increasingly digital environment; they are
proficient in new technologies, prioritize individual personality and taste, actively use social
media, and have been described as prioritizing economic value. Of course, the M/Z generations
have a common propensity to pursue convenience (Shin, 2020) in addition to proficiency in
digital technology, which can be seen in their general lifestyles. According to Wood (2013),
Gen Z is interested in new technology, insists on ease of use and wants a sense of safety. The
characteristics that Wood (2013) ascribes to Gen Z resemble those of Millennials. Taking these
factors into consideration, this study divided M/Z generationsattitudes toward technology
into (1) interest in new technology, (2) convenience seeking and (3) security seeking.
Members of the M/Z generations are generally interested in new technology. Unlike other
generations, they have shown a high interest in and preference for new technologies (Berkup,
2014;Priporas et al., 2017;Wood, 2013). Millennials and members of Gen Z use new
technologies not only because the technologies are fast and easy but also because they are
curious about them. Curiosity stimulates exploratory behavior and leads to an acceptance of
innovative new products.
In addition, the M/Z generations value convenience when they use products and services,
giving it top priority in the shopping process. In the context of services, convenience is
defined as consumersperception of the required time and effort associated with purchasing
or using services, which may affect customer satisfaction and behavior (Keh and Pang, 2010).
It is also defined as the ability to perform tasks in a short time with the minimum cost of
human energy (Morganosky, 1986). Convenience can be regarded as a means of adding value
for consumers by reducing the amount of time and effort required to receive paid services
(Colwell et al., 2008). Indeed, prior research has shown that one of the reasons Millennials use
self-checkout technology in shopping situations is its convenience (Lee and Leonas, 2020).
Also, Gen Z consumers have been shown to have short attention spans (Berkup, 2014), which
makes them value economic value and thus seek technology-driven convenience, efficiency
and practicality (Berkup, 2014;Francis and Hoefel, 2018;Wood, 2013). Simultaneously
preferring new technologies, their concerns about security in transactions based on these new
technologies arise. In particular, both Millennials and Gen Z expressed concern about security
issues and the negative consequences that arise during smart retailing transactions (Berkup,
2014;Priporaset al., 2017). Problems such as stealing credit card information and personal
information leakage in stores can lead to privacy security concerns among the young
consumers and a decline in trust in service personnel. This study predicts that three
characteristics (i.e. interest in new technology, convenience seeking and safety seeking) of M/
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Z generations derived from prior research will have significant effects on the preference for
contactless service. Therefore, the following hypotheses are presented:
H1a. Interest in new technology has a positive influence on preference for contactless
service over salespersons.
H1b. Convenience seeking has a positive influence on preference for contactless service
over salespersons.
H1c. Safety seeking has a positive influence on preference for contactless service over
salespersons.
2.2 Technology self-efficacy
Self-efficacy is critical when conducting new work or innovative actions. Self-efficacy refers to an
individuals belief in his or her capacity to execute the necessary behaviors to produce specific
performance attainments (Bandura, 1986). This belief is an individuals self-awareness of the
level of competence he or she possesses, rather than his or her ability to perform. In other words,
self-efficacy is ones trait rather than an intrinsic value (Davis, 1989;Lee and Lyu, 2016;Yang,
2010) Self-efficacy has been found to indirectly influence behavior intentions (Bandura, 1994).
And the predictive ability of self-efficacy with respect to behavior thus translates into people
likely engaging in behaviors about which they are motivated (Nystrand and Olsen, 2020).
In the meantime, many researches have examined various technology acceptance models.
However, it does not explicitly consider how individualsexpectations of their capabilities
influence their behavior (Zheng and Zheng, 2017). On the other hand, social cognitive theory
claims that beliefs about outcomes may be insufficient to influence behavior if individuals
doubt their capabilities to successfully undertake behaviors (Bandura, 1996). Self-efficacy,
the belief that one has the ability to perform a particular action is an important construct of
the social cognitive theory (Artino, 2012). Consumersbeliefs about their self-efficacy are
essential to how they perceive the context in which they purchase (Li et al., 2018). Therefore,
technology self-efficacy, which is defined as an individuals ability to use technology-
equipped devices, is important when an individual accepts a new technology.
In addition, concerning innovative behavior, previous research (e.g. Albion, 2001;Balapour
et al., 2019;Igbaria and Iivari, 1995;Redmond et al., 1993) has validated the mediated effect of
perceived self-efficacy. Environments that individuals find interesting can encourage them to
engage in innovative behavior, increasing their willingness to actively develop and believe in
new ideas. Furthermore, a prior study examining the relationship between online news portal
usage motivation and self-efficacy revealed that the higher the tendency to seek new and
interesting news, the higher th e Internet self-efficacy (Park, 2009). Therefore, consumers who are
interested in new technology may have a higher sense of technological self-efficacy.
The characteristics of M/Z generations, which are interest in new technology, convenience
seeking and safety seeking, can also be important antecedents for technology self-efficacy.
People who are highly interested in new technology have high curiosity and an internal
motivation to perform tasks; they are also involved in exploratory acceptance of innovative new
products (Albion, 2001;Balapour et al., 2019). For those who have abundant knowledge of a
specific area and a strong internal motivation for creativity, there is a greater sense of self-
efficacy that they will be able to solve the problem in that area (Amabile, 1989). Furthermore, the
more one seeks convenience, the more likely they are to have a sense of technology self-efficacy.
Consumers who seek convenience when using online news portals feel higher Internet self-
efficacy (Park, 2009). Accordingly, the tendency to pursue convenience and the feeling of
technology self-efficacy have a positiverelationship. Additionally, intrinsic value, which refers to
what individuals believe is important, has a significant impact on a sense of technology self-
efficacy (Lee and Lyu, 2016). Intrinsic value has a significant impact on technology self-efficacy.
Contactless
service:
Millennials
versus Gen Z
85
Awareness of security can be on e intrinsic value. The information security awareness was found
to have a significant effect on computer self-efficacy (Cuganesan et al., 2018).
In addition, prior studies have shown that consumer characteristics such as self-efficacy
are critical antecedents in the acceptance of non-interpersonal service technologies
(Dabholkar and Bagozzi, 2002). More confidence in the ability to use technology has a
strong positive impact on attitudes and usage habits. In addition, the more self-effective
consumers are, the more detailed they are to discover the products that fit their purpose of
purchase and use various channels (Lim and Kim, 2018). By contrast, people with low self-
efficacy for Internet technology are less likely to accept and use the Internet than those with
high self-efficacy (Bandura, 1986). Based on prior research, this study predicts that the
relationship between the characteristics of M/Z generations and preference for contactless
service over salespersons will be mediated by technology self-efficacy. Therefore, the
following hypotheses are presented:
H2a. Interest in new technology has a positive influence on preference for contactless
service mediated by technology self-efficacy.
H2b. Convenience seeking has a positive influence on preference for contactless service
mediated by technology self-efficacy.
H2c. Safety seeking has a positive influence on preference for contactless service
mediated by technology self-efficacy.
2.3 Moderating effect of consumer conformity
Preference for contactless service can be interpreted as avoidance of salespersons. Research
has shown that the M/Z generations dislike interacting with salespersons in retail stores, and
that young consumers perceive being served by salespersons as stressful (Netsuite, 2019;
Novarica, 2016). These studies indentify consumer conformity as a psychological factor
related to avoiding interactions with salespersons. However, prior salespersonconsumer
communication studies have used consumer conformity a psychological factor to explain
consumerspositive responses to salespersons. In other words, this study seeks to examine
the effect of consumer conformity on interactions with salespersons from a perspective
opposite of that taken by previous studies.
Conformity is defined by changes in behavior or belief due to collective pressure or by
individuals changing their behavior in response to other peoples reactions (Bond and Smith,
1996). Although an individual can judge or perceive objective facts, they cannot act according
to their judgment or perception when collective pressure is applied to them (Asch, 1952).
Consumer conformity refers to a change in consumption behavior due to the product
evaluation, purchase intention or purchase behavior of the reference group (Lascu and
Zinkhan, 1999). Also, Deutsch and Gerard (1955) classified such social influence as normative
and informational. This study focused on informational conformity, which is formed by
othersinformational influence. Consumers often face situations where they make decisions
about what they should choose based on other peoples opinions. For example, one might ask
for the opinions of friends, family, other consumers or salespersons, which means they can
play an important role in the purchasing process of consumers. The salespersons provide
accurate information about the products, and consumers accept recommended products and
exchange opinions about their purchase.
However, as the roles of salespersons and consumers have changed, consumers have come
to rely more on social media, online and mobile platforms as sources of information than on
salespersons. In other words, as digital platforms have replaced reliable information providers,
members of the M/Z generations have come to perceive salespersonsopinions as unnecessary
external stimuli rather than information from professional information providers (Netsuite,
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2019;Novarica, 2016). When consumers want to focus on their shopping experiences, they
want to make decisions with full independence (Li et al., 2021). For example, if a consumer who
went shopping to buy a basicjacket is persuaded by a salesperson and changeshis/her mind to
buy an oversized jacket, the consumer might regret the decision. Such regret stems from the
fact that the consumer did not entirely control the shopping process.
Perceiving lack of control weakens the relationship between expected emotions and
behaviors (Lunardo and Mbengue, 2009). If purchases were made to be impulsively influenced
by other social presence, not by individual choices and beliefs, that purchase will highly
likely cause regret afterward. Post-purchase regret can occur when consumers do not think
about or pay attention when purchasing (Zeelenberg and Pieters, 2007). After following others or
salespersons in making a purchase decision, consumers may experience post-purchase regret
due to the sudden change of attitude (Novliadi et al., 2018). Dissatisfaction with purchased
products will further strengthen consumersavoidance of salespersons. In other words, the more
people are influenced by others in the shopping context (high consumer conformity), the more
they will view their interactions with salespersons as burdensome. The M/Z generations have a
strong tendency to be self-centered in their consuming behaviors, and they also have a
propensity to be highly influenced by reference groups (Purani et al., 2019). Consumers who have
high consumer conformity will prefer to use technology to be influenced by an accurate source,
and they will use contactless services to make purchasing decisions at their discretion. Moreover,
they will try to have a shopping experience consistent with their purposes and motivations.
Therefore, consumer conformity is expected to moderate preference for contactless service.
H3. Consumer conformity among moderates the relationship between technology self-
efficacy and preference for contactless service. In other words, when ones consumer
conformity is high, the effect of technology self-efficacy, from M/Z generation
characteristics (a: interest in new technology, b: convenience seeking, c: safety
seeking) on preference for contactless service is stronger.
From a cohort perspective, differences in generation tendencies occur because of birth timing
variations and the different environments encountered during growth processes. Millennials
and Gen Z differin their consumption-related propensities and in how they express themselves
(Francis and Hoefel, 2018;Bakewell and Mitchell, 2003). Research has shown that members of
Gen Z have a highdegree of autonomy whenit comes to using new technology (Dadvari and Do,
2019). Also, technological advancements have exposed this generation to diverse information,
enabling them to make more rational decisions than any other generation (Kardes et al.,2010).
Meanwhile, perceived social influence is one of the main antecedents that leads to acceptance of
new technology for Millennial consumers (Mun et al.,2017). Moreover, Millennials have been
shown to place greater emphasis on turning to friends or family members for suggestions
before making purchase decisions. Therefore, this study tested the hypotheses independently
for each group (Millennials and Gen Z) and explored the differences between them.
3. Method
This study explored the effects of the three characteristics of M/Z generations on preference
for contactless service over salespersons mediated by technology self-efficacy. The
conceptual framework of the study is shown in Figure 1.
3.1 Procedure and participants
The data were collected using an online survey to test our research hypotheses. A total of 288
respondents answered the survey, of which 144 are Millennials (2639 years old, born 1981
1993), and 144 are Gen Z (1925 years old, born 19942001). Respondents were asked to watch
a video and respond to the survey using Amazon Mechanical Turk (MTurk). The stimuli were
Contactless
service:
Millennials
versus Gen Z
87
a one-minute video, including various situations using contactless services, such as a woman
searching for information about fashion products at the kiosk instead of asking a salesperson
and using a contactless payment system rather than checking out with a human cashier in a
fashion retail store. All respondents were asked to answer questions to check if they fully
understood the description of the contactless service and the video stimuli. Those who did not
accurately understand the stimuli were excluded from the analysis; seven respondents and
two respondents were excluded from Millennials and Gen Z, respectively. According to the
demographic information responses, 66.9% of the respondents were men and 33.1% women;
moreover, 73.9% of the respondents have experienced contactless service.
3.2 Measures
The characteristics of M/Z generations, which include interest in new technology, convenience
seeking and safety seeking, were set as independent variables. Technology self-efficacy was
suggested asthe mediating variableand preference for contactless service over salespersons as
dependent variables. The suggested Gen Z characteristics from the qualitative study of Wood
(2013) allowed us to adapt and modify the scales from the prior studies that are relevant to each
concept. In particular, thefollowing items were adapted and modified: six items ininterest in the
new technology from Liaw and Huang (2003) and Stell and Paden (1999);fouritemsin
convenience seeking fromSheth (1983), and four items in safety seeking from Ranganathan and
Ganapathy (2002). The technology self-efficacy was used by adapting the five items used by
Compeau and Higgings (1995), and social overload was measured using four items from
Ayyagari et al. (2011). Moreover, four items in informational conformity were adapted from
Grimm et al. (1999) to measure consumer conformity. Finally, the preference for contactless
service oversalespersons was measured by adapting scales from Kattara and El-Said(2013).All
items except demographic characteristics were scored on a seven-point Likert scale (ranging
from 1 5strongly disagree to 7 5strongly agree).
3.3 Validity and reliability of the measures
The reliability and validity of the measures of the characteristics of M/Z generations were
examined through SPSS 23.0 and Amos 18.0. Confirmatory factor analysis of the five
variables was conducted. Two items were excluded from convenience seeking and safety
seeking, and one item from technology self-efficacy was excluded. Even though the chi-
square was significant, the GFI, AFGI, CFI, and TLI were above 0.80, and RMSEA was lower
than 0.080. As a result, the measurement model showed satisfactory fit (x
2
5305.987,
H1a
H1b
H2a
H2b
Interests in
new technology
(INT)
Convenience
seeking
(CS)
Security
seeking
(SS)
Technology
self-efficacy
(TSE)
Preference for
contactless service
over salespersons
(PCS)
Consumer
conformity
(CC)
H2c
H2a/b/c
H1c H3
Figure 1.
Conceptual framework
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p50.000, normal x
2
52.000, GFI 50.89, AFGI 50.85, CFI 50.95, TLI 50.93 and
RMSEA 50.063). Composite reliability was found to be 0.94 or higher, and average variance
extracted (AVE) was also found to be satisfactory, confirming the reliability and convergence
validity of the measurement tool. In addition, as shown in Table 1, the AVE values of all
constituent concepts exceeded the squared correlation between the constructs and met the
discrimination validity criteria presented by Fornell and Larcker (1981). The data were
processed through SPSS 23.0 and PROCESS Macro to test the hypothesis.
4. Results
4.1 Millennials
4.1.1 Difference between the perception of Millennials and Generation Z on M/Z generation
characteristics, consumer conformity and preference for contactless service over salespersons.
Before testing the hypotheses, we compared M/Z generation characteristics to check how
shopping behavior of Millennials and Gen Z differs as shown in Table 2. Independent sample
t-tests were conducted to see the differences in perceptions between the two generations. Gen
Z perceived interest in new technologies (M
z
55.83, M
mil
55.49, t52.70, p< 0.01) and
security seeking (M
z
55.75, M
mil
55.44, t52.52, p< 0.01) significantly higher than
Millennials. In other words, interest in new technology and safety seeking can be deemed key
features of Gen Z. By contrast, the difference in average of convenience seeking was not
significant between two groups. That is, convenience seeking is a trait that both generations
share, and it is a fundamental factor in the context of using technology. In terms of consumer
conformity (M
z
55.05, M
mill
55.35, t52.19, p< 0.01), Millennials showed higher
perception at a significant level compared with Gen Z.
4.1.2 Effects of M/Z generationscharacteristics on preference for contactless service over
salespersons. H1 posited that three characteristics of M/Z generations will have a significant
influence on preference for contactless service over salespersons. To examine our hypothesis,
we used 137 Millennialsresponses to empirically test the influence of three characteristics
(H1a: interest in new technology, H1b: convenience seeking, H1c: security seeking). A multiple
regression analysis was then conducted to reveal the effects of the consumer characteristics
on contactless service over salespersons. The effect of interest in new technology (β50.28,
t(137) 53.18, p< 0.05), convenience seeking (β50.36, t(137) 53.93, p< 0.000) and safety
seeking (β50.23, t(137) 52.79, p< 0.05) on contactless service were statistically significant.
Thus, H1a,b,care supported. The results are as shown in Table 3.
4.1.3 Moderated mediation effects of technology self-efficacy. Furthermore, to examine
H2aH3c among Millennials, moderated mediation was conducted with consumer conformity
as a moderator between the three characteristics of the M/Z generations and preference for
technology over salespersons. The analysis was performed using Model 14 of the PROCESS
Macro (Hayes, 2013) with a reliability interval specified at 95% and the number of bootstrap
samples 5,000, as shown in Table 4.
The results demonstrated that interest in new technologies did not have a significant
direct effect on preference for technology (b50.11, SE 50.07, 95% CI 5[0.0224 0.2494],
INT CS TSE PCS
INT 0.60a
CS 0.46 0.51a
TSE 0.46 0.47 0.50a
PCS 0.31 0.32 0.35 0.55a
Note(s): (a) Numbers on the diagonal are average variance extracted (AVE)
(b) Numbers off the diagonal are the squared correlation between the constructs
Table 1.
The squared
correlations and
AVE of variables
Contactless
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Millennials
versus Gen Z
89
p> 0.05) because 0 was included in the confidence interval. However, the indirect effect was
significant (b50.23, SE 50.08, 95% CI 5[0.06650.3835]), confirming the full mediation
effect. Next, while convenience seeking also did not have a significant direct effect on
preferences for technology (b50.06, SE 50.06, 95% CI 50.0700 0.1817], p> 0.05, the
indirect effect was significant (b50.24, SE 50.08, 95% CI 5[0.08590.3918]), confirming a
full mediation effect. Finally, the direct effect of safety seeking on preferences for technology
(b50.12, SE 50.07, 95% CI 5[0.0228 0.2595], p> 0.05) was not significant, whereas its
indirect effect (b50.24, SE 50.09, 95% CI 5[0.06090.4036]) was significant, confirming a
full mediation effect. In conclusion, H2a,H2b and H2c were all supported, verifying the full
mediation effects of technology self-efficacy on the relationships between the M/Z generation
characteristics and preferences for contactless service over salespersons.
In addition, the analyses revealed that consumer conformity plays a significant
moderating role in the relationships between preference for technology over salespersons
via technology self-efficacy and interest in new technology (b50.10, SE 50.04, 95%
CI 5[0.01820.1806], p< 0.05), convenience seeking (b50.09, SE 50.04, 95% CI 5[0.0129
0.1764], p< 0.05), and security seeking (b50.09, SE 50.04, 95% CI 5[0.01090.1719],
p< 0.05). The conditional indirect effect of interest in new technology, convenience seeking
and security seeking on preference for technology over salespersons through technology self-
efficacy at three levels namely, the mean(M), one standard deviation above the mean (þ1
SD), and one standard deviation below the mean (1 SD) were also assessed. Bootstrap CIs
revealed that interest in new technology and security seeking had significant conditional
indirect effects on preference for technology over salespersons (via technology self-efficacy)
at high/moderate levels of interest in new technology and insignificant effects at low levels. In
terms of convenience seeking, Bootstrap CIs revealed significant conditional indirect effects
on all three levels. However, as the levels of each variable became high, the effects grew
stronger. Therefore, H2a,b,cand H3a,b,cwere confirmed in Millennials.
Group Independent variable βtR
2
F
Millennial H1a Interest in new technology 0.28 3.18* 0.73 94.20***
H1b Convenience seeking 0.36 3.93***
H1c Security seeking 0.23 2.79*
Gen Z H1a Interest in new technology 0.30 2.51* 0.27 17.32***
H1b Convenience seeking 0.25 2.65**
H1c Security seeking 0.15 1.76 (n.s.)
Note(s): DV: preference for contactless service over salesperson; *p< 0.05, **p< 0.01, ***p< 0.001
Factor
Generation Z
(N5142)
Millennials
(N5137) tvalue Significance
Interest in new technology M55.83
SD 51.01
M55.49
SD 50.98
2.698 0.007
Convenience seeking M55.43
SD 51.00
M55.39
SD 51.05
0.305 0.761
Security seeking M55.75
SD 50.94
M55.44
SD 50.96
2.522 0.012
Social conformity M55.05
SD 51.16
M55.35
SD 50.95
2.185 0.030
Preference for contactless service over
salespersons
M55.26
SD 51.13
M55.36
SD 50.94
0.759 0.448
Table 3.
Multiple regression
results of M/Z
characteristics on
preference for
contactless service
over salespersons
Table 2.
t-test results
comparing Generation
Z and Millennials
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Furthermore, to illustrate the interaction effects, high/low technical self-efficacy 3high/
low consumer conformity (2 32) groups were extracted, and the mean scores of each
group were computed. As shown in Figure 2, the higher an individual consumers
technology self-efficacy was, the more strongly the consumer preferred technology over
salespersons. However, when an individuals consumer conformity was high, the effect of
technology self-efficacy on preference for technology over salespersons was greater. In
other words, when an individual feels insecure about his/her decisions or wants to make
more accurate decisions, he/she tends to be strongly influenced by others surrounding
him/her, especially salespersons. However, salespersons might be a strong reference
source for them, and if they wish to not be disturbed by salespersons when making
purchase decisions, they might tend to avoid salespersons and instead choose to use
contactless services.
4.2 Generation Z
4.2.1 Effects of M/Z generationscharacteristics on preference for contactless service over
salespersons. A multiple regression analysis was then conducted to reveal the effects of the
three characteristics on contactless service over salespersons. The effect of interest in new
technology (β50.30, t(142) 52.51, p< 0.05) and convenience seeking (β50.25, t(142) 52.65,
and p< 0.001) on contactless service was statistically significant. However, safety seeking
(β50.15, t(142) 51.76, p> 0.05) did not have a significant effect on preference for contactless
service. Thus, H1a and H1b are supported, whereas H1c is rejected. Although prior studies
Predictor
Technology self-efficacy Preference for technology over salespersons
Effect SE LLCI ULCI Effect SE LLCI ULCI
INT 0.68*** 0.06 0.5696 0.7902 0.11 0.07 0.0224 0.2494
CS 0.60*** 0.06 0.4750 0.7302 0.06 0.06 0.0700 0.1817
SS 0.70*** 0.06 0.5875 0.8093 0.11 0.07 0.0228 0.2595
Conditional indirect effects at various levels of the moderator
Levels of the moderator Effect on PT SE LLCI ULCI
INT 1 SD 0.21 0.09 0.0295 0.4044
M0.34 0.09 0.1568 0.5257
þ1 SD 0.44 0.11 0.2217 0.6597
CS 1 SD 0.28 0.08 0.1132 0.4462
M0.40 0.08 0.2304 0.5655
þ1 SD 0.49 0.11 0.2843 0.7008
SS 1 SD 0.23 0.09 0.0460 0.4075
M0.34 0.09 0.1566 0.5254
þ1 SD 0.43 0.11 0.2095 0.6552
Index of moderated mediation predictor
Predictor Effect on PT SE LLCI ULCI
INT 0.10* 0.04 0.0182 0.1806
SC 0.09* 0.04 0.0129 0.1764
CC 0.09* 0.04 0.0109 0.1719
Note(s): *p< 0.05, **p< 0.01, ***p< 0.001
INT: interest in new technology, CS: convenience seeking, SS: security seeking, TSE: technology self-efficacy,
CC: consumer conformity; PT: preference for technology over salespersons
1 SD: standard deviation below the mean; M: mean; þ1 SD: standard deviation above the mean
Table 4.
Moderating effect of
consumer conformity
in Millennials
Contactless
service:
Millennials
versus Gen Z
91
suggested that Gen Z is concerned about security issues and the negative consequences that
arise during smart retailing transactions (Berkup, 2014;Priporas et al., 2017;Wood, 2013), this
may not be true when it comes to the context of shopping fashion products. As fashion
products are high-involvement products and fashion consumers are greatly influenced by
hedonic motivation, the hedonic experience in the shopping process might have been more
important than concerns about privacy and transaction risks. The results are as shown in
Table 3.
4.2.2 Mediation effects of technology self-efficacy. Furthermore, we examined H2, which
tested the mediation effect of technology self-efficacy through Model 4 of Process Macro
(Hayes, 2013). The reliability interval was specified at 95%, and the number of bootstrap
samples was 5,000. The direct effect of the interest in new technologies to preference for
technology was significant (b50.36, SE 50.11, 95% CI 5[0.13320.5806], p< 0.001) because
0 is not included between the confidence intervals. The indirect effect was also significant
(b50.23, SE 50.10, 95% CI 5[0.02430.4123]); thus, a partial mediating effect was
identified. Next, convenience seeking also had a significant direct effect on preferences for
technology (b50.26, SE 50.09, 95% CI 50.09120.4336], p< 0.01, and the indirect effect was
significant (b50.19, SE 50.07, 95% CI 5[0.07160.3332]). Therefore, a partial mediating
effect was confirmed. Finally, both the direct effect (b50.22, SE 50.10, 95% CI 5[0.0185
0.4268], p< 0.05) and indirect effect (b50.25, SE 50.08, 95% CI 5[0.07930.3936]) of safety
seeking on preferences for technology are significant, and partial mediation was identified.
Thus, H2a,H2b, and H2c were all supported, verifying the mediation effects of technology
self-efficacy between Gen Z characteristics and preference for contactless service over
salespersons.
4.2.3 Moderated mediation effects of technology self-efficacy. Furthermore, to examine
H2aH3c among Gen Z, moderated mediation was again conducted with consumer
conformity as a moderator between the three characteristics of M/Z generations and
preference for technology over salespersons, as shown in Table 5.
Figure 2.
Interaction effects in
Millennials
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The results demonstrated that interest in new technologies had a significant direct effect on
preference for technology (b50.36, SE 50.10, 95% CI 5[0.16960.5510], p< 0.000) because
0 was not included in the confidence interval. The indirect effect was also significant (b50.21,
SE 50.09, 95% CI 5[0.02440.3602]), confirming a partial mediation effect. Next, while
convenience seeking did not have a significant direct effect on preferences for technology
(b50.16, SE 50.10, 95% CI 50.0334 0.3505], p> 0.05, the indirect effect was significant
(b50.25, SE 50.07, 95% CI 5[0.12180.3953]), confirming a full mediation effect. Finally,
both the direct (b50.36, SE 50.09, 95% CI 5[0.18590.5345], p< 0.000) and indirect effects
(b50.19, SE 50.06, 95% CI 5[0.05910.2973]) of safety seeking on preferences for
technology were significant, confirming a partial mediation effect. Thus, H2a,H2b, and H2c
were all supported, verifying the mediation effects of technology self-efficacy between M/Z
generation characteristics and preference for contactless service over salespersons.
In addition, the analysis revealed that consumer conformity plays a significant
moderating role in the relationships between preference for technology over salespersons
via technology self-efficacy and interest in new technology (b50.15, SE 50.06, 95%
CI 5[0.02870.2805], p< 0.05), convenience seeking (b50.13, SE 50.07, 95% CI 5[0.0000
0.2599], p< 0.05) and security seeking (b50.21, SE 50.07, 95% CI 5[0.07810.3383],
p< 0.01). The conditional indirect effect of interest in new technology, convenience seeking
and security seeking were again assessed in three levels. Bootstrap CIs revealed the interest
in new technology and security seeking had significant conditional indirect effects on
preference for technology over salespersons (via technology self-efficacy) at high/moderate
Predictor
Technology self-efficacy Preference for technology over salespersons
Effect SE LLCI ULCI Effect SE LLCI ULCI
INT 0.55*** 0.06 0.4175 0.6742 0.36*** 0.10 0.1696 0.5510
CS 0.49*** 0.07 0.3542 0.6257 0.16 0.10 0.0334 0.3505
SS 0.43*** 0.07 0.3038 0.5637 0.36*** 0.09 0.1859 0.5345
Conditional indirect effects at various levels of the moderator
Levels of the moderator Effect on PT SE LLCI ULCI
INT 1 SD 0.11 0.08 0.0649 0.2622
M0.21 0.09 0.0244 0.3602
þ1 SD 0.28 0.10 0.0480 0.4490
CS 1 SD 0.17 0.07 0.0382 0.3224
M0.25 0.07 0.1218 0.3953
þ1 SD 0.30 0.08 0.1393 0.4622
SS 1 SD 0.08 0.07 0.0647 0.2027
M0.19 0.06 0.0591 0.2973
þ1 SD 0.26 0.07 0.1049 0.3773
Index of moderated mediation predictor
Predictor Effect on PT SE LLCI ULCI
INT 0.13* 0.07 0.0287 0.2805
SC 0.13* 0.07 0.0000 0.2599
CC 0.21** 0.07 0.0781 0.3382
Note(s): *p< 0.05, **p< 0.01, ***p< 0.001
INT: interest in new technology, CS: convenience seeking, SS: security seeking, TSE: technology self-efficacy,
CC: consumer conformity; PT: preference for technology over salespersons
1 SD: standard deviation below the mean; M: mean; þ1 SD: standard deviation above the mean
Table 5.
Moderating effect of
consumer conformity
in Generation Z
Contactless
service:
Millennials
versus Gen Z
93
levels of interest in new technology and insignificant effects at low levels. Likewise, Bootstrap
CIs revealed that interest in new technology, convenience seeking and security seeking had
significant conditional indirect effects on preference for technology over salespersons (via
technology self-efficacy) at high/moderate levels of interest in new technology and
insignificant effects at low levels, thus supporting H2a,b,cand H3a,b,cin Gen Z.
Furthermore, to illustrate the interaction effect, high/low technical self-efficacy 3high/
low consumer conformity (2 32) groups were extracted, and the mean scores of each group
were computed. The same as Millennials, the analysis revealed a positive relationship
between technology self-efficacy and preference for technology over salespersons in Gen Z, as
shown in Figure 3. However, when an individuals consumer conformity was high, the effect
of technology self-efficacy on preference for technology over salespersons was greater. To
compare the moderating effect of consumer conformity between Gen Z and Millennials, two-
way ANOVA was conducted for each group. The moderating effect of consumer conformity
was higher in Gen Z (
ƞ
2
50.081) consumers than in Millennials (
ƞ
2
50.021). In other words,
the effect of technology self-efficacy on preference for technology over salespersons became
stronger in the group with high consumer conformity than in the group with low consumer
conformity, and this phenomenon even manifested in Gen Z. That is, although Millennials
and Gen Z exhibit similar characteristics such as consumer conformity, the two groups differ
in the extent to which the features of their surroundings (i.e. salespersons) affect them.
5. Discussion and conclusion
This study discussed contactless service, for which demand is increasing rapidly in the
context of fashion retail, and empirically verified the mechanism of choosing contactless
service in retail store. In particular, this study has important theoretical and practical
implications because we clarified why consumers avoid communication with salespersons,
who used to play an important role in the past. Also, discovering the preference mechanism of
Figure 3.
Interaction effects
in Gen Z
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94
contactless services has a significance when the importance of face-to-face services shifts to
non-face-to-face services.
This research validated the path from M/Z generationscharacteristics to preference for
contactless service over salespersons mediated by technology self-efficacy. Results reveal
that the effect of the interest in new technology and convenience seeking on preference for
contactless service was significant, whereas safety seeking did not have a significant impact.
Furthermore, technology self-efficacy had a partial mediation effect in the relationship
between the three variables and preference for contactless service. Therefore, when designing
contactless services, retailers should emphasize interesting features of the new service to
arouse curiosity among the young consumers. Also, retailers should effectively suggest the
convenience of the service that could be achieved during the transaction when targeting M/Z
generations. Furthermore, since technology self-efficacy mediated the relationship between
the three characteristics of M/Z generations and preference for technology over salespersons,
retailers should persuade consumers that they have the capabilities to produce a satisfactory
outcome when they use the new service. Although safety seeking did not have a significant
effect on preference for technology over salespersons, the relationship was mediated by
technology self-efficacy. Therefore, retailers should especially assure consumers who seek
safety so that technology self-efficacy of consumers can be strengthened.
Besides, similarity and differences in shopping behavior between Millennials and Gen Z
were identified in this study. In particular, we compared the average perception of the
variables to see if any difference exists between the groups. The results showed that Gen Z
perceives higher interest in new technologies and safety seeking than Millennials, but no
significant difference exists in convenience seeking. That is, convenience seeking could be
seen as a factor sought by both generations. Therefore, retailers targeting Gen Z might have
to provide new services to meet their needs and target consumers who are highly interested in
new technologies; they will have to provide a benefit of safety so that consumers can trust
them. In addition, convenience is a benefit commonly sought by Gen Z and will be the most
fundamental element in designing contactless services.
Furthermore, the moderating effects of consumer conformity on the relationship between
technology self-efficacy and preference for contactless service over salespersons were
explored. Consumer conformity had a significant moderating effect among M/Z generations.
When an individuals consumer conformity is high, the effect of technology self-efficacy on
preference for technology over salespersons was greater. That is, when consumers feel high
levels of pressure to make decisions based on other peoples opinions, technology self-efficacy
plays a stronger role in the choice of contactless service. The moderating effect of consumer
conformity was higher among Gen Z consumers than among Millennial consumers. Also,
members of Gen Z showed low perceptions of social conformity. This may stem from their
high degree of autonomy in technology usage and the extensive information they can access
through diverse technology and social media, as previous research has suggested (Dadvari
and Do, 2019). Meanwhile, Millennials tend to rely on the opinions of salespeople when
making purchase decisions (Mun et al., 2017), which often leads them to regret the purchases
they make. Therefore, when retailers provide contactless services to members of the M/Z
generations with high consumer conformity, they need to persuade the young consumers by
providing reliable information such as recommendations based on sales data from relevant
professionals and easy-to-use contactless services with intuitively comprehensible interfaces
to increase technology self-efficacy.
From a theoretical perspective, this study identified the psychological mechanism of
preference for contactless services over salespersons to explain the interaction effects
between technology self-efficacy and consumer conformity. In particular, unlike the prior
research, this study showed that consumer conformity is a factor that explains avoidance of
salespersons. Perceived self-determination is very important for the M/Z generations, and
Contactless
service:
Millennials
versus Gen Z
95
rather than encouraging them to listen to salespersons, consumer conformity leads them to
prefer contactless services.
From a practical perspective, this study found that the three characteristics of M/Z
generations are important drivers that lead to technology self-efficacy and preference for
contactless service. Hence, stores may need to use appropriate appeal in their communication
when employing contactless service in physical retail stores. However, Millennials and Gen Z
showed difference in perception of three characteristics. For example, importance of security
among Gen Z was found to be nonsignificant. Therefore, marketers should focus on
communicating convenience of the service and stimulating consumersinterest in new
technology to increase footfalls. Also, members of the M/Z generation perceive themselves as
having both high technical self-efficacy and high consumer conformity. According to our
results, high technical self-efficacy and high consumer conformity result in a preference for
contactless service. Although this study showed that Millennials have higher technological
self-efficacy than members of Gen Z, Gen Zs technological self-efficacy is expected to rise
given Gen Zs higher interest in new technologies. In other words, the characteristics and
psychological variables of the M/Z generations lead them to prefer contactless service.
Therefore, retailers targeting members of the M/Z generations need to operate their stores so
that contactless services play a main role and salespersons play a secondary role for
customers with low technology self-efficacy.
This study had several limitations. The first issue is stimuli. The respondents were
required to self-report their perceptions of contactless services that they experienced through
the stimuli video, not what they experienced in reality. Future studies could use the mall
intercept method to more accurately measure the perceptions of consumers who actually
have contactless service shopping experience. The second issue is the sample size. If the
sample sizes were larger for both the Millennial and Gen Z groups, higher research validity
could be obtained. Additionally, future research could focus on the interesting moderating
effect of consumer conformity by applying psychological theories (i.e. self-determination
theory). Moreover, future research could strengthen this studys theoretical foundations and
produce more robust empirical evidence by manipulating conditions of consumer conformity
instead of measuring consumersperceptions by scenarios.
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Corresponding author
Chorong Youn can be contacted at: chorong.youn@pusan.ac.kr
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... However, the primary focus is on Generations Y and Z in line with the study by Gizycki, Pöhlmann [38], which found that they have the highest interest in and willingness to use digital technologies. The age categories are defined in Sect. 4. In addition, the differences in technology application and uptake between Generations Y and Z are considerable [39]. Gender is classified as male or female. ...
... Figure 1 illustrates the TAUSS model with both the paths and effect directions of all variables and moderators as well as the corresponding hypotheses. [15,24] H1a The influence is moderated by age and is strongest among Generation Z [14,24] H2 Effort Expectancy (EE) positively influences Behavioural Intention (BI) to use smart stores [15,24] H2a The influence is moderated by age and is strongest among Generation Y [24,41] H2b The influence is moderated by gender and is strongest among women [24,42] H3 Social Influence (SI) positively influences Behavioural Intention (BI) to use smart stores [15,24] H3a The influence is moderated by age and is strongest among Generation Z [24,43] H3b The influence is moderated by gender and is strongest among women [24,41] H4 Facilitating Conditions (FC) positively influence Behavioural Intention (BI) to use smart stores [15,24] H4a The influence is moderated by age and is strongest among Generation Z [15,24] H4b The influence is moderated by gender and is strongest among men [37,43] H5 Hedonic Motivation (HM) positively influences Behavioural Intention (BI) to use smart stores [15] H5a The influence is moderated by age and is strongest among Generation Y [44] H5b The influence is moderated by gender and is strongest among men [45,46] H6 Price Value (PV) positively influences Behavioural Intention (BI) to use smart stores [15] H6a The influence is moderated by age and is strongest among Generation Y [15] H6b The influence is moderated by gender and is strongest among women [15] H7 Technology Anxiety (TA) negatively influences Behavioural Intention (BI) to use smart stores [29,30] H7a The influence is moderated by age and is strongest among Generation Y [47][48][49] H7b The influence is moderated by gender and is strongest among women [50] H8 Perceived Safety (PS) positively influences Behavioural Intention (BI) to use smart stores [12,31,32] H8a The influence is moderated by age and is strongest among Generation Y [37,39] H8b The influence is moderated by gender and is strongest among women [43] H9 Generation Z customers have a higher Behavioural Intention (BI) to use smart stores than customers from the Baby Boomer, X, and Y generations, with acceptance decreasing with age [39,43,51] H10 Men have a higher Behavioural Intention (BI) to use smart stores than women [50,52] 316 M. Netscher et al. ...
... Figure 1 illustrates the TAUSS model with both the paths and effect directions of all variables and moderators as well as the corresponding hypotheses. [15,24] H1a The influence is moderated by age and is strongest among Generation Z [14,24] H2 Effort Expectancy (EE) positively influences Behavioural Intention (BI) to use smart stores [15,24] H2a The influence is moderated by age and is strongest among Generation Y [24,41] H2b The influence is moderated by gender and is strongest among women [24,42] H3 Social Influence (SI) positively influences Behavioural Intention (BI) to use smart stores [15,24] H3a The influence is moderated by age and is strongest among Generation Z [24,43] H3b The influence is moderated by gender and is strongest among women [24,41] H4 Facilitating Conditions (FC) positively influence Behavioural Intention (BI) to use smart stores [15,24] H4a The influence is moderated by age and is strongest among Generation Z [15,24] H4b The influence is moderated by gender and is strongest among men [37,43] H5 Hedonic Motivation (HM) positively influences Behavioural Intention (BI) to use smart stores [15] H5a The influence is moderated by age and is strongest among Generation Y [44] H5b The influence is moderated by gender and is strongest among men [45,46] H6 Price Value (PV) positively influences Behavioural Intention (BI) to use smart stores [15] H6a The influence is moderated by age and is strongest among Generation Y [15] H6b The influence is moderated by gender and is strongest among women [15] H7 Technology Anxiety (TA) negatively influences Behavioural Intention (BI) to use smart stores [29,30] H7a The influence is moderated by age and is strongest among Generation Y [47][48][49] H7b The influence is moderated by gender and is strongest among women [50] H8 Perceived Safety (PS) positively influences Behavioural Intention (BI) to use smart stores [12,31,32] H8a The influence is moderated by age and is strongest among Generation Y [37,39] H8b The influence is moderated by gender and is strongest among women [43] H9 Generation Z customers have a higher Behavioural Intention (BI) to use smart stores than customers from the Baby Boomer, X, and Y generations, with acceptance decreasing with age [39,43,51] H10 Men have a higher Behavioural Intention (BI) to use smart stores than women [50,52] 316 M. Netscher et al. ...
Chapter
Stationary food retailers face the pressures of evolving with technological advancements and heightened competition. Smart stores, driven by intelligent technologies, offer efficient and personalised shopping experiences. However, in Germany, the acceptance of smart stores is uncharted territory. To address this research gap, this study adapts the UTAUT2 model to develop the Theory of Acceptance and Use of Smart Stores (TAUSS), which is specifically tailored to the unique context. Data are collected from n = 412 respondents in Germany through an educational online survey. The structure and consistency of TAUSS are evaluated using confirmatory factor analysis. A total of 25 hypotheses are tested through multiple linear regression, moderation analyses, and mean comparisons. The findings reveal significant acceptance factors, including performance expectancy, social influence, hedonic motivation, technology anxiety, and age. Generation Z exhibits the highest level of acceptance, with gender influencing the impact of social influence, particularly among Generation Y women. Overall, the results advocate for the acceptance of smart stores, offering valuable insights for practical implementation. Sales strategies should prioritise aligning with customer expectations, fostering a positive brand image, enhancing the customer experience, and addressing technology-related uncertainties. This research not only enriches the understanding of customer acceptance but also contributes to the expansion of technology acceptance theory. The study’s insights provide practical and theoretical guidance for navigating the evolving retail landscape in the digital age.
... Besides, tourist nowaday prioritize pleasure and safety, they believe travel is essential to people's lives (Sheivachman, 2017). According to Kim et al. (2022), tourists increasingly prefer contactless service and new technology, particularly virtual reality (VR), for their transformative experiences (S. Kim et al., 2022). ...
... Besides, tourist nowaday prioritize pleasure and safety, they believe travel is essential to people's lives (Sheivachman, 2017). According to Kim et al. (2022), tourists increasingly prefer contactless service and new technology, particularly virtual reality (VR), for their transformative experiences (S. Kim et al., 2022). 84% of customers worldwide are interested in using VR or augmented reality (AR) for travel experiences, and 42% believe these technologies will shape tourism in the future (Han et al., 2018). ...
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This study developed a theoretical framework to fill the gap in research on the relationship between VR and experiential marketing. Based on a stimulus-organismresponse (SOR) theory combined with the quantitative research method, the research process surveyed 296 international and domestic tourists in Vietnam. The results revealed significant impacts of telepresence and authentic experience on cognitive and affective responses, indicating that those variables are essential factors in VR tourism. The study also gave managerial implications to help tourism enterprises plan appropriate experiential marketing strategies to attract young travelers and propose solutions for companies to boost the tourists’ intention of visiting the destination shown in the VR travel advertisements.
... Catching health problems at an early stage can stop them from getting worse. devices like smartwatches and fitness bands can detect real-time heart rate, blood oxygen, and sleep patterns (Kim et al., 2022). If there are unusual changes, users can go to get medical help before things get serious. ...
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... Sin embargo, nosotros no hemos distinguido entre diferentes rangos de edad, limitándonos a una muestra de personas adultas. Sin embargo, es posible que estemos ante un cambio de paradigma, principalmente en las nuevas generaciones, en las que se tiende a preferir un encuentro de servicio contactless, es decir, sin intervención de ningún empleado (Kim et al., 2022). ...
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¿Puede una simple acción no verbal cambiar las percepciones que el cliente tiene acerca del vendedor en un encuentro de servicio? En esta tesis hemos examinado, por primera vez en una muestra española y a través de tres estudios, cómo un leve toque del vendedor en el hombro o en el brazo del cliente y/o una sonrisa “Duchenne” del vendedor al cliente influyen en las evaluaciones que el cliente hace de la calidez y de la competencia del vendedor, utilizando para ello el Modelo de Contenido de Estereotipos (Fiske et al., 2002). En el primer estudio (con datos de 2018), estudiamos el efecto del leve toque y de la sonrisa del vendedor sobre las evaluaciones que el cliente hace de su calidez y su competencia, así como la interacción de la sonrisa sobre los efectos del leve toque del vendedor en las evaluaciones del cliente (estudiada por primera vez en un encuentro de servicio). En el segundo estudio, replicamos el primero, pero con datos tomados en 2022, para analizar el efecto pandemia. Y en el tercer estudio, con datos de 2023, estudiamos si el sexo del vendedor y del comprador modula el efecto del leve toque del vendedor en las evaluaciones que el cliente hace de su competencia y su calidez. Además, introducimos la extraversión de cliente (estudios 1 y 2) y el Confort con el Tacto Interpersonal del cliente (estudio 3) como variables moduladoras. Los resultados encontrados muestran que, tanto la sonrisa como el leve toque del vendedor tienen un efecto positivo sobre la evaluación que el cliente hace de su calidez, a lo largo de los 3 estudios. Cuando el vendedor, además, de tocar al cliente, le sonríe, el efecto positivo del tacto sobre la evaluación de la calidez del vendedor es menos intenso, tanto antes como después de la pandemia. En cuanto a la percepción de la competencia, la sonrisa “Duchenne” del vendedor también provoca un efecto positivo sobre el efecto que el tacto del vendedor en las percepciones del cliente, sin efecto pandemia. Sin embargo, el leve toque del vendedor sufre una evolución a lo largo de nuestros tres estudios en cuanto a su efecto sobre la evaluación de su competencia, pasando de ser positivo en 2018, a no ser significativo en 2022 y a tener un efecto negativo en 2023. Así mismo, la interacción de la sonrisa sobre el efecto que el tacto del vendedor tiene sobre la evaluación que el cliente hace de su calidez no es significativa, ni antes ni después de la pandemia. En cuanto a la modulación del sexo del vendedor y del comprador sobre el efecto del leve toque del vendedor en las evaluaciones de los clientes, encontramos que las evaluaciones de los clientes no están influidas por el sexo de los vendedores, sean hombres o mujeres; mientras que el sexo del comprador sí influye, siendo los compradores hombres los que mejor evalúan a los vendedores, en comparación con las clientes mujeres. Se discuten los resultados encontrados y se exponen las implicaciones gerenciales.
... They want more appropriate m-banking services as a solution to their needs. M-banking is expected to have an attractive and friendly user interface (Kim et al., 2022). Gen Z, who have deeper and broader knowledge related to digital technology, will be more confident so they can increase their use of mbanking along with the development of digitalization (Priporas et al., 2017). ...
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