Unit VII Ess

Received: 10 January 2022 | Accepted: 25 July 2022

DOI: 10.1002/mar.21715

R E S E A R CH AR T I C L E

It's all part of the customer journey: The impact of augmented reality, chatbots, and social media on the body image and self‐esteem of Generation Z female consumers

Nisreen Ameen1 | Jun‐Hwa Cheah2 | Satish Kumar3,4

1School of Business and Management, Royal

Holloway, University of London, London, UK

2School of Business and Economics, Universiti

Putra Malaysia, Serdang, Selangor, Malaysia

3Department of Management Studies,

Malaviya National Institute of Technology

Jaipur, Jaipur, Rajasthan, India

4Faculty of Business, Design and Arts,

Swinburne University of Technology, Kuching,

Sarawak, Malaysia

Correspondence

Nisreen Ameen, School of Business and

Management, Royal Holloway, University of

London, Egham, TW20 0EX London, UK.

Email: [email protected]

Abstract

Research is needed to identify novel ways to influence Generation Z female

consumers' behavior when they interact with various technologies. This study

investigates how experiences of using augmented reality, artificial intelligence‐

enabled chatbots, and social media when interacting with beauty brands affect body

image, self‐esteem, and purchase behavior among female consumers in Generation

Z. Through three studies, we propose and test a model drawing on social comparison

theory. In Study 1, a survey was completed by Generation Z women (n = 1118). In

Study 2 and Study 3, two laboratory experiments were conducted with Generation Z

women in Malaysia (n = 250 and n = 200). We show that (1) Generation Z women's

perceived augmentation positively affects their body image, self‐esteem, and actual

purchase behavior; (2) although trust in social media celebrities positively affects

Generation Z women's body image and self‐esteem, the addictive use of social media

does not have significant effects; (3) the chatbot support type (assistant vs. friend)

has a significant impact on these women's experience; and (4) brand attachment,

reputation, and awareness do not have significant effects. This article provides

important implications for theory and practice on the behavior of Generation Z

females when interacting with various technologies.

K E YWORD S

artificial intelligence, augmented reality, chatbot, Generation Z, self‐esteem, social media

1 | INTRODUCTION

Generation Z refers to individuals who were born from 1997 onwards

(Dimock, 2019). This generation comprises 40% of all the world's

consumers (Chamberlain, 2018). As a “tech native” generation,

Generation Z is highly active on social media and open to interacting

with technologies such as chatbots and augmented reality (Ameen

et al., 2021; Yu et al., 2019). This generation had a spending power of

$143 billion in 2020, and retailers are competing to appeal to

consumers who belong to it (Davis, 2020). In addition, Generation Z

consumers have been named the biggest cohort of beauty spenders,

with female Generation Z consumers spending approximately $368

annually on beauty products (In‐Cosmetics, 2020).

Previous research has indicated that Generation Z has certain

characteristics that differentiate it from other generations; for

example, its expectations for purchasing behavior are different from

Psychol Mark. 2022;39:2110–2129.2110 | wileyonlinelibrary.com/journal/mar

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© 2022 The Authors. Psychology & Marketing published by Wiley Periodicals LLC.

those of previous generations because its members' digitally literate

consumption makes them highly informed, more pragmatic, and more

capable of making analytical decisions than representatives of

previous generations are (Grigoreva et al., 2021). In addition,

Generation Z has been associated with low confidence and low

self‐esteem (Writer, 2017). Low self‐esteem is a particular issue for

young women: it affects their risk of developing depression, anxiety,

self‐harming behaviors, and other mental health problems

(Kramer, 2021).

Of all the generations alive today, Generation Z is one of the

most concerned with physical and mental well‐being, and its

members like to monitor their health via a variety of methods

(Egolf, 2018). Accordingly, this generation is more willing to spend on

health‐related products and cosmetics than previous generations are

(Moussavi & Mander, 2019). Prior studies have identified a link

between women's use of cosmetics and beauty products and their

self‐esteem (Dickman, 2010). In the context of Generation Z, women

in this section of the population are active customers of beauty

brands; they consider these brands to be part of their self‐identity

and link beauty products to their self‐esteem (In‐Cosmetics, 2020).

Beauty brands such as Mac, Sephora, and L'Oréal have

developed software applications that allow consumers to try on

make‐up virtually; these are referred to as virtual make‐up try‐on

applications. A virtual make‐up try‐on application provides consum-

ers with integrated, augmented reality‐enabled, virtual make‐up try‐

on services. Many beauty brands have started to invest in and

use artificial intelligence‐enabled chatbots to reach consumers

more efficiently and effectively. The customer journey offered by

these brands no longer relies on a single technology but integrates

multiple cutting‐edge technologies to ease consumers' decision

making (i.e., purchase behavior) (Ameen et al., 2021). Hence, it is

important to study Generation Z's interactions with beauty brands

and the services offered by these brands through various technol-

ogies and to determine how these interactions affect body image,

purchase behavior, and self‐esteem among this consumer group.

The creative use of advanced technologies and high engagement

with sharing on social media are the norm for digital natives (Ameen

et al., 2021). However, despite their importance, there is a lack of

research focusing on digital natives' interaction with new‐age

technologies and the developmental psychology aspects of this

process (Kesharwani, 2020). Specifically, there is a gap in research on

how services that are offered by beauty brands and enabled through

the integration of artificial intelligence, augmented reality, and social

media influence Generation Z women's body image, self‐esteem, and

purchase behavior.

Building on previous studies on Generation Z's interactions with

technologies as part of the shopping journey (e.g., Ameen et al., 2021;

Ng et al., 2019), we advance the knowledge of female Generation Z

consumers' buying behavior and self‐esteem by exploring how these

factors are influenced by a range of technologies that are integrated

into the customer journey. Specifically, we argue that the augmenta-

tion enabled by augmented reality, the type of chatbot (friend vs.

assistant), and social media (specifically trust in social media

celebrities and addictive use of social media) can affect these

women's body image, purchase behavior, and self‐esteem. Further-

more, we analyze the influence of brand‐related factors in this

context. The research develops a theoretical model that draws on

social comparison theory (Festinger, 1954). This theory has been

used to investigate how consumers compare themselves to others

(Hendrickse et al., 2017).

We focus on services offered by beauty brands because beauty

products are often linked with body image and self‐esteem (de Lenne

et al., 2021). In addition, beauty brands are more innovative than

other brands in terms of integrating the latest technologies into the

services that they offer to customers, and Generation Z women often

relate to beauty and cosmetics products and are these brands'

biggest buyers (Knit, 2022). Furthermore, more than 66% of

Generation Z consumers are spending more on beauty since the

COVID‐19 pandemic (Knit, 2022).

In addition to the practical implications of employing various

technologies in the customer journey for the purchase behavior and

self‐esteem of women in Generation Z, this study provides three

theoretical contributions. First, our research contributes to the

literature on body image, buying behavior, and self‐esteem (e.g.,

Djafarova & Rushworth, 2017; Gulas & McKeage, 2000; Kurt, 2022;

Townsend & Sood, 2012; Yim & Park, 2019) by considering how

these can be enhanced during interactions with cutting‐edge

technologies as part of the customer journey. In particular, although

past research has explored the effects of different types of

technologies on Generation Z consumers (e.g., Ameen & Anand, 2020;

Ameen et al., 2021), it remains unclear how the integration of

augmented reality, chatbots, and social media into the customer

journey can affect the buying behavior and psychological well‐being

of female Generation Z consumers.

Second, we contribute to the literature on the use of chatbots in

marketing services to facilitate various processes related to customer

service (e.g., Ciechanowski et al., 2019; Mariani et al., 2022; Roy &

Naidoo, 2021) by exploring the impact of the chatbot support type

on female Generation Z consumers' perception of the augmentation

of services, their body image, their purchase behavior, and their self‐

esteem.

Third, we address the gap in the existing literature on how brand‐

related factors affect the impact of the various technologies with

which Generation Z women interact as part of their shopping

journey. We contribute to the literature on the impact of brand‐

related factors on the customer journey (e.g., Thomson et al., 2005;

Veloutsou & Moutinho, 2009; Yoo & Donthu, 2001; Yoo et al., 2000)

by exploring the impact of brand attachment, reputation, and

awareness as control variables in the context of our research.

The article is organized as follows. First, the relevant literature on

social comparison among Generation Z consumers, the influence of

social media, augmented reality, and chatbots in the customer journey is

discussed to develop a theoretical backbone for the proposed model

and hypotheses. Then, the results from the three studies conducted to

test the research hypotheses are presented. In the final section, the

theoretical and practical implications are discussed.

AMEEN ET AL. | 2111

2 | LITERATURE REVIEW

2.1 | Social comparison and Generation Z women

Social comparison theory is the most extensively used theory in the

existing studies. This theory was first developed by Festinger (1954),

and it has been used in later research to examine the relationship

between media and body image (e.g., Hendrickse et al., 2017).

According to the theory, individuals compare themselves with others

around them (e.g., on social media), and this comparison can be either

an upward social comparison or a downward social comparison

(Hendrickse et al., 2017). Individuals have a drive to compare their

own attributes and abilities with those of others (Festinger, 1954).

For example, when women compare themselves with a better look

(i.e., thinner) or an ideal look, the difference between their body size

and the target's body size becomes salient, which leads to an

undesirable evaluation of their own body image (Hendrickse

et al., 2017). Generation Z has been classified as the least confident

generation in comparison with previous generations, causing its

members anxiety and leading them to experience increasing pressure

due to the rise of social media, which can make problems like bullying

or body image issues more intense than they were in the past

(Chappet, 2019). For younger and older women alike, body image is

strongly linked to self‐esteem, self‐concept, and mental health

(Cameron et al., 2019). However, Generation Z women have less

self‐confidence and are more risk averse in their attitude and

behavior than earlier generations (Khamis & Zaatarti, 2019). Further-

more, low self‐esteem in young women has been linked to the use of

social media in ways that do not reflect a true social life and may

reduce their confidence further (NYU Dispatch, 2019).

2.2 | The influence of social media on the customer journey

Previous research has studied interactions on social media and the

impact of these interactions on their users (e.g., Hawi &

Samaha, 2017; Pozharliev et al., 2022). For example, social media

celebrities have been found to influence these platform users'

behavior (e.g., Lo & Peng, 2022). The relationship between celebrity

endorsements and self‐esteem has also been studied, with the

findings showing that, when consumers believe in a product

endorsed by a celebrity, they feel better about buying it and doing

so increases their self‐esteem (Djafarova & Rushworth, 2017). These

consumers seek the opinions of others before making the decision to

buy as they are less confident in their own decision‐making

capabilities. Previous studies in this area have focused on the effect

of social media on individuals' self‐esteem or on the role of self‐

esteem in individuals' perceptions of social media interactions and

celebrity recommendations (e.g., Djafarova & Trofimenko, 2019).

Furthermore, the addictive use of social media has been found to

have a negative effect on young people's self‐esteem but a positive

association with life satisfaction (Hawi & Samaha, 2017).

Interestingly, there is more addiction to social media among young

women than among young men (Hawi & Samaha, 2017). Young

women are active on social media platforms; for example, female

users constitute 51% of Instagram users worldwide (Statista, 2020)

and 61% of users of Tik Tok, which is mainly a platform for young

individuals (Cyca, 2022).

2.3 | Augmented reality and chatbots in the customer journey

Augmented reality is defined as a “medium in which digital

information is overlaid on the physical world that is in both spatial

and temporal registration with the physical world and that is

interactive in time” (Craig, 2013; p. 20). From a marketing perspec-

tive, two of the main benefits of chatbots enabled by artificial

intelligence are powerful personalization and the option to automate

services offered to customers (Ameen et al., 2022; Chandra

et al., 2022; Liu‐Thompkins et al., 2022; Mariani et al., 2022).

Chatbots have been defined as “an e‐service agent that represents a

technological evolution of the traditional service agent involved in

direct firm–customer exchanges” (Murtarelli et al., 2020; p. 2).

Previous studies have tended to focus on customers' experience

of using one single type of technology as part of their shopping

experience, for example by investigating either artificial intelligence

or augmented reality as a sole technology used in retail (e.g., Flavián

et al., 2019; Gatter et al., 2022). However, in reality, the customer

journey no longer relies on one technology alone but instead involves

a combination of smart technologies. Specifically, beauty brands have

integrated artificial intelligence and augmented reality technologies

into their applications to provide a more efficient customer

experience. Both chatbots and augmented reality have recently

become more widely used in a range of industries, including

cosmetics and beauty, to offer services enabled by these technolo-

gies. They have been integrated into mobile applications or made

accessible through social media platforms, such as Facebook,

Instagram, or WeChat, which include Virtual Artist Apps, Modiface,

Virtual Catwalks, and digital mirrors.

Augmented reality has been described as digital and real‐time

content that is superimposed on users' actual surroundings (Flavián

et al., 2019). Consumers' evaluations of products available through

augmented reality (AR)‐based virtual try‐on product applications

have been found to be linked to perceptions of their body image,

whether those perceptions are either positive or negative (Yim &

Park, 2019). An AR‐enriched user experience can be more entertain-

ing, and it enables potential customers to have limitless interactions

with virtual information. Augmented reality allows customers to

become more familiar with a product, and this makes them feel more

comfortable about making a decision to purchase (Hilken et al., 2017).

Although augmentation is a core aspect of AR‐enabled experiences,

the impact of augmentation on Generation Z women's body image,

self‐esteem, and actual purchase behavior and the impact of the type

of chatbot support and brand‐related factors are notions that have

2112 | AMEEN ET AL.

not been fully investigated in the marketing context and theory (i.e.,

social comparison theory) (Javornik, 2016).

3 | RESEARCH OVERVIEW

Since the customer journey often entails interactions with different

technologies that can affect the customer experience, we opt for a

multistudy approach based on three studies using multiple methods

to understand the impact of each of these technologies. Study 1

analyses the impact of the perceived augmentation of reality on

Generation Z women's body image, which, in turn, affects the actual

purchase behavior and self‐esteem of this generation of consumers.

In addition, Study 1 analyses the moderating effects of external

factors related to Generation Z women's use of social media, namely

trust in social media celebrities and addictive use of social media. In

Study 2, we extend the model further by analyzing the moderating

effects of the type of chatbot support (friend vs. assistant) on the

relationships in the model proposed in Study 1. In Study 3, we re‐

examine the proposed hypotheses of Study 1 and Study 2 with the

inclusion of control variables, namely brand attachment, brand

reputation, and brand awareness. Figure 1 depicts the overall model.

4 | STUDY 1

Study 1 sets the basis of this study by analyzing the impact of

perceived augmentation on Generation Z women's body image, which,

in turn, affects their actual purchase behavior and self‐esteem

(Figure 1). In addition, this study analyses the moderating effects of

external factors related to Generation Z women's use of social media,

namely trust in social media celebrities and addictive use of social

media. As AR‐enabled try‐on virtual make‐up applications tend to be

built around self‐service technologies (Ameen et al., 2021), the quality

of the service offered by these applications is likely to differ

significantly from that provided by conventional interpersonal services.

However, to the best of our knowledge, there is a lack of research on

how these services can affect body image, self‐esteem, and purchase

behavior among Generation Z women. Furthermore, no research exists

on the role of external factors related to social media in this process.

4.1 | Theoretical model and hypothesis development

Social comparison theory (Festinger, 1954) has increasingly been

used to understand the processes through which societal messages

about appearance influence body image among adolescents (Krayer

et al., 2008). Previous research on body image has shown that they

emerge most prominently among women whose traits rank higher in

social comparisons (Betz et al., 2019). Self‐esteem and body image

have been identified in previous research on individuals' behavior as

important components of this theory (e.g. Tylka & Sabik, 2010).

Rosenberg (1965a, p. 15) defined self‐esteem as “a favorable or

unfavorable attitude toward the self.” For young women, self‐esteem

is an important factor that influences their well‐being, learning, and

employability (Potgieter, 2012). From a marketing perspective, recent

studies have identified the role of self‐esteem in shaping consumer

behavior toward brands and when buying products and services. Tan

et al. (2017) found that self‐esteem strongly influences customer

citizenship behavior towards brands through its effects on four main

mediators: attachment, commitment, involvement, and beliefs.

F IGURE 1 Overall research model (Study 1 to Study 3)

AMEEN ET AL. | 2113

Body image is defined as an individual's subjectively perceived

physical self, embedded in a mental construct (P. N. Myers &

Biocca, 1992). As women are very frequently judged on their

appearance, they often compare their bodies with those of other

women (Stice et al., 2001). Previous research has found that even

women with high self‐esteem may engage in social comparison

processes at the individual level (i.e., with daughters or peers) as well

as at the group level (with other women in society) because both

types of comparison should enable them to redefine and improve

their feminine image (Gentina et al., 2018).

Previous studies have adopted social comparison theory

(Festinger, 1954) to focus on the relationship between women's

self‐esteem, their body image, and the use of various technologies

(such as social media and virtual reality [VR]). The authors found that

women are more likely than men to engage in appearance

comparisons, body image concerns, and a drive for thinness on social

media. Hendrickse et al. (2017) investigated the role of appearance‐

related comparisons and intrasexual comparisons among male and

female consumers using social comparison theory. They classified

social comparison as follows: upward comparison (i.e., when

individuals compare themselves with those whom they consider to

be superior to them) and downward comparison (i.e., when

individuals compare themselves with those whom they consider to

have attributes and abilities that are inferior to their own). Women

who are exposed and connected to more women on Instagram are

more likely to engage in downward comparison (Hendrickse

et al., 2017). Some studies have focused on the relationships

between VR‐enabled experiences that examine body image and

enable social comparison.

Based on these aforementioned issues, the model proposed in

this study draws on social comparison theory (Festinger, 1954), which

focuses on body image and self‐esteem. It offers a novel approach to

understanding how the integration of AR‐enabled services into

virtual make‐up try‐on applications can improve Generation Z

women's body image, self‐esteem, and purchase behavior. The

model integrates factors that are relevant to the phenomenon of

Generation Z women's interaction with AR‐enabled services. It

hypothesizes the effects of perceived augmentation on Generation

Z women's body image, which, in turn, is hypothesized to affect self‐

esteem and purchase behavior (see Figure 1, Study 1).

4.1.1 | Perceived augmentation

Figure 2 Previous research in the area of human–computer

interaction has explained that AR's capability of enhancing physical

reality is referred to as augmentation (Preece et al., 2015). It can

overlay virtual elements onto people, products, or the surrounding

space. Augmentation refers to an enrichment of the environment in

which the virtual elements are not separated from the physical ones

and computer‐generated elements coexist with the physical environ-

ment due to the technological ability to augment real objects with

virtual annotations (Javornik, 2016). Augmentation is the main

characteristic that differentiates augmented reality from other

technologies (Javornik, 2016). There has been a significant increase

in the integration of augmented reality into the beauty industry in

recent years; for example, in the use of magic mirrors and smart

virtual applications (Javornik, Rogers, et al., 2016). Despite this,

previous studies have highlighted that research is needed to aid our

understanding of customers' perceived augmentation when using

beauty services (Javornik, 2016; Javornik, Rogers, et al., 2016).

In addition, augmented reality applications allow the augmentation

of a product—usually by scanning an item with a smart device that can

then create an enhanced view. Such applications help female customers

to see how products fit them personally, or how they look in their own

environment, while maintaining the convenience of online purchasing.

AR‐based service augmentation improves not only the product offering

but also the interaction between customers and the business frontline.

From the perspective of customers (Hilken et al., 2017), augmented

reality can offer a more context‐sensitive interface with richer

information (Yaoyuneyong et al., 2016) and a more distinct process

of interaction than other smart technologies (Javornik, 2016). Previous

studies have also suggested that the use of augmented reality enhances

customers' perceptions of interface, information, and interaction in the

holistic shopping experience in a retail context (e.g., Hilken et al., 2017).

Augmentation has a more significant effect on female consumers than

male ones because socially and culturally driven body ideals have led to

women generally developing a more negative attitude towards their

bodies than men (Yim & Park, 2019). Thus, this study proposes that

perceived augmentation may have a significant positive effect on body

image among Generation Z women. Hence, the following hypothesis is

proposed:

H1: Perceived augmentation has a significant positive effect on body

image.

4.1.2 | Body image

Body image is commonly defined as an individual's subjectively

perceived physical self, embedded in a mental construct (P. N. Myers

F IGURE 2 Differences between the virtual assistant and the virtual friend for Study 2

2114 | AMEEN ET AL.

& Biocca, 1992; Yim & Park, 2019). In addition, social comparisons

with idealized body images can have a negative impact on self‐

esteem and individuals' evaluations of their body image (Gulas &

McKeage, 2000). Body image has been found to have a stronger

effect on the use of augmented reality than traditional web‐based

media (Yim & Park, 2019). In addition, a relationship has been

identified between body image and cosmetics consumption among

young women, who tend to use cosmetics for compensation and

concealing when they felt dissatisfied with areas of their face

(Dickman, 2010). However, women are interested in improving or

maintaining their looks even when they have a positive body image,

and this affects the depth and breadth of the beauty products that

they purchase. Thus, the following hypothesis is proposed:

H2: Body image has a significant positive effect on purchase behavior.

In addition, previous studies have identified the significant direct

effects of body image on self‐esteem among women (e.g., Yim &

Park, 2019). The concepts of both “body image” and “self‐esteem”

come from social comparison theory (Krayer et al., 2008). As stated

by T. A. Myers et al. (2012, p. 342), “Social comparison theory

(Festinger, 1954) provides a foundation for understanding women's

body image disturbance. This theory proposes that people have a

drive to determine their progress and standing in life, and they often

do so by searching out standards to which they can compare

themselves.” Scholars have explained that people with a negative

body image tend to worry about how others view them and tend to

avoid public places where their bodies are exposed, which negatively

affects their self‐esteem (Thompson & Chad, 2002). Previous

research on advanced technologies (such as virtual reality) has

explained their significance in improving body image and self‐esteem

(Yim & Park, 2019). This suggests that artificial intelligence and

augmented reality‐enabled services can improve body image, which

may have a significant positive impact on self‐esteem among women.

Thus, the following hypothesis is proposed:

H3: Body image has a significant positive effect on self‐esteem.

4.1.3 | Purchase behavior

In their qualitative study, Djafarova and Rushworth (2017) found that

consumers believe that buying products online boosts their self‐

esteem and that they make purchases as a way of rewarding

themselves. The authors also found that women's self‐esteem is

enhanced when buying a product or service that has been

recommended by a celebrity on social media. In addition, women

with low self‐esteem can develop a beauty obsession in an attempt to

increase their self‐esteem (Britton, 2012). Existing studies in the area

of retail therapy have shown that consumers are keen to buy new

products when they feel less confident and less powerful than others;

hence, they anticipate that buying these products will boost their

positive mood, confidence, and power (e.g., Townsend & Sood, 2012).

Similarly, buying beauty products can make young women feel good

about themselves and boost their self‐esteem: a pertinent finding

given that low self‐esteem is an issue for Generation Z women

(Gillan, 2019). Hence, the following hypothesis is proposed.

H4: Purchase behavior has a significant positive effect on self‐esteem.

4.1.4 | The moderating effects of trust in social media celebrities and addictive use of social media

Individuals who are part of Generation Z do not simply use smartphones;

they live their lives on them. This behavior is one step ahead of tech

savviness, a skill possessed by many millennials. However, for women,

exposure to idealized images of the human body, which their own bodies

differ from, creates pressure to achieve what can sometimes be classified

as “unrealistic ideals of attractiveness” (West, 2018). The rise of influencer

marketing, particularly targeting younger demographics, proves that word

of mouth on social media plays a significant part in shaping the

preferences of these young consumers.

Social media celebrities and influencers are perceived to be more

genuine than brand advertisers because they have built up loyal

audiences and the content that they produce tends to outperform the

content that most brands create internally (Patel, 2017). They are role

models, movement leaders, and even educators. It is common for

people in Generation Z to turn to YouTube when they want to learn

something or when faced with a decision about whether to buy a

product (Patel, 2017). However, recent research has highlighted that

building trust in content generated by social media celebrities remains

a challenge (Lou & Yuan, 2019). Buying a product or service that has

been recommended by a trusted celebrity on social media can enhance

self‐esteem among women (Djafarova & Rushworth, 2017), and when

women trust a celebrity to recommend products that will improve the

way they look, they tend to buy these products more often. It follows

that a high level of trust in social media celebrities can strengthen the

relationship between body image and self‐esteem.

The majority of the existing studies on self‐esteem and celebrity

endorsement on social media have focused on the effect of self‐esteem

on interactions between individuals and with celebrities on social media

and the role of social comparison in this process (e.g., Djafarova &

Rushworth, 2017). Consumers perceive celebrity advertisements or

endorsements as trustworthy when parasocial relationships are formed.

Individuals who follow digital celebrities are more likely to experience

feelings of friendship for them than for traditional celebrities owing to

similarities and familiarity with parasocial relationships (Hwang &

Zhang, 2018). When women trust the recommendations made by

social media celebrities, in spite of the effects of social comparison, they

start to believe in the improvement that the recommended products

would make to their facial appearance, which increases their self‐

esteem. Hence, the following hypothesis is proposed:

H5a, b: Trust in social media celebrities moderates the relationships

between (a) purchase behavior and (b) Generation Z women's

AMEEN ET AL. | 2115

self‐esteem and body image such that these relationships are

stronger among women with a higher level of trust.

Social media addiction occurs more often among women than

among men (Boyle et al., 2016). In addition, some studies have linked

Generation Z's addiction to social media to some of the main

problems associated with this generation—low self‐esteem and

anxiety—due to the negative stories and views that individuals

express and share on these platforms (Chappet, 2019). A young

woman with a positive body image can still have low self‐esteem if

she is addicted to social media because these can have a negative

impact on her perception of herself. In addition, high levels of social

media addiction can interrupt the relationship between body image

and purchase behavior. Social media use has been found to predict

stronger baseline dissatisfaction with one's body and to be associated

with a higher risk of eating disorders (Cohen & Blaszczynski, 2015).

Women who are highly addicted to social media may be more

influenced by the opinions of individuals on these platforms than by

their own perceptions of their body. Hence, the addictive use of

social media may moderate the effect of body image on purchase

behavior. Thus, the following hypothesis is proposed:

H6a, b: Addictive use of social media moderates the relationships

between (a) purchase behavior and (b) Generation Z women's

self‐esteem and body image such that these relationships are

stronger among women with a lower level of addiction.

4.2 | Method

4.2.1 | Sampling and data collection

The target participants for this study were young female customers

who had used a virtual make‐up try‐on application that integrated

augmented reality and was offered by a leading European beauty

brand. The brand specialized in personal care and beauty products,

and the target participants for this study were already its customers.

Beauty brands are increasingly using AR‐enabled virtual artist

applications to enhance the customer experience. A virtual artist

application includes a color (shade)‐matching tool that analyses an

image of the user's face to estimate the shade of any product and

then shows a picture of how the product will look on the user's skin.

In addition, the beauty application used for this study offered an AR‐

enabled customer experience by integrating a virtual make‐up try‐on

facility, a color (shade)‐matching tool, and a chatbot service. The

augmented reality virtual make‐up try‐on feature helps shoppers to

see how they would look when wearing different types of make‐up,

and the color (shade)‐matching tool helps them to identify the most

suitable foundation for their skin tone. These tools allowed a

reasonable level of customer interaction with AR, and using this

application provided greater access to the target participants.

A purposive sampling strategy was used in the data collection. This

sampling method has been used in previous studies on specific issues

related to consumers (e.g., Cuny & Opaswongkarn, 2017). Purposive

sampling allows researchers to target individuals who may hold various

and important views and therefore to answer the research question. In

addition, the main objective of a purposive strategy is to produce a

sample that can logically be assumed to represent the population,

which was the case in this study. Following Malhotra and Galletta

(1999), the criteria for sampling were that participants: (1) must be

female consumers; (2) must be between 18 and 23 years old; and (3)

must have used the AR‐enabled application selected for this study. The

average time taken to complete the survey was 10min. The

participants were recruited through social media platforms (i.e.,

Facebook and Instagram). In particular, we collected data through

various beauty groups on these two platforms, on which young

women who are interested in beauty products are often active.

We started the survey with qualifying questions based on the

criteria set for our purposive sampling, and only those who met all three

criteria completed the survey. An online survey was distributed in 2020,

and a total of 1118 unique responses were collected. An ethics review

application was submitted to the author's university and approved

before the data collection stage. All ethical approval procedures and

guidelines set by the university were followed with regard to the data

collection. Accordingly, each questionnaire was accompanied by a

participant information sheet that explained the purpose of the research

and how participants' data would be used and informed participants

that no personal information would be collected or used at any time and

that they could withdraw from the study at any time without giving a

reason. In addition, the questionnaire was accompanied by a participant

consent form, which each participant had to complete before answering

the questionnaire. All the participants were aged 18 or over, and no

sensitive data were collected.

Supporting Information: Table D (Supporting Information Appen-

dix) shows the profile of the respondents. All the participants had

used the brand's artificial intelligence‐ and augmented reality‐enabled

virtual artist application, and they all followed the brand on social

media. All the participants indicated that they had used the virtual

artist application for less than 5 years, and they had all shopped with

the brand for less than 5 years. With regard to relationships, 74% of

the participants were single and 26% were married. In terms of

professional status, 51% of them were employed, 21% were

unemployed, and 28% were studying.

4.2.2 | Measurement items

The measurement items for perceived augmentation were adopted

from Javornik, Rogers, et al.'s (2016) study, those for self‐esteem

were from Rosenberg's (1965b) study, and those for purchase

behavior were from Adjei et al.'s (2010) study (in which it was

measured based on the depth of purchase and breadth of purchase).

A 7‐point Likert scale with anchors ranging from “strongly disagree”

to “strongly agree” was used. For body image, two questions were

adopted from Chan and Grossman's (1988) study, with answers given

on a 7‐point scale ranging from “not at all satisfied” to “extremely

2116 | AMEEN ET AL.

satisfied” for the first question and from “nothing” to “as much as

possible” for the second question. Regarding purchase behavior, the

7‐point scale for depth of purchase was based on the total number of

products purchased (1 to more than 20); in relation to the breadth of

purchase, the scale was related to the number of product categories

purchased by the participant, following the study conducted by Adjei

et al. (2010). The measurement scale for addictive use of social media

was adopted from Andreassen et al. (2012) study, with answers on a

7‐point scale ranging from “never” to “always.” The measurement

items for trust in social media celebrities were adopted from

Ohanian's (1990) study. To ensure the validity and reliability of the

measurement items included in this study, the items were adopted

from existing scales that had been used and empirically tested in

relevant previous studies. The inclusion of a 7‐point Likert scale was

justified given that it had been used extensively in previous related

studies (e.g., Javornik, Rogers, et al., 2016). Supporting Information:

Table E (Supporting Information Appendix) shows the measurement

items for all the factors that were integrated into the model proposed

in this study.

4.3 | Analysis and results

The collected data were first analyzed using the Statistical Package

for the Social Sciences software for the descriptive statistics.

Subsequently, partial least squares structural equation modeling

(PLS‐SEM) analysis (Hair et al., 2017)—using SmartPLS3 software—

was used to assessed both the measurement model and the

structural model. In addition, multigroup analysis was also adopted

to test the moderating effects of trust in social media celebrities and

addictive use of social media in the proposed model.

To minimize the potential for common method variance (CMV)

bias, the survey design and administration adhered to the guidelines

created by Podsakoff et al. (2003). Harman's single‐factor test was

used to assess CMV, in which the factor analysis result showed that

the first factor accounted for 8% of the variance in the sample.

Subsequently, CMV was assessed and the values of the inner

variance inflation factor were below the threshold value of 3.3

(Petter et al., 2007). Hence, no issues were identified.

4.3.1 | Measurement model

When assessing the measurement model, the criteria of loading,

convergent validity, reliability, and discriminant validity were eval-

uated. Most of the measurement items had loadings that were higher

than 0.7 (Hair et al., 2017), and those with low loadings were deleted.

In addition, as shown in the Supporting Information: Table E

(Supporting Information Appendix), all the factors had an average

variance extracted of 0.5 or higher (Hair et al., 2017). Hence,

convergent validity was established. In addition, all the Cronbach's

alpha (CA) and composite reliability (CR) values were higher than the

threshold value of 0.7 (Hair et al., 2017). Supporting Information:

Table A (Supporting Information Appendix) shows the results of the

assessment of loading, reliability, convergent validity, and discrimi-

nant validity. Hence, the measurement model met the reliability

requirements. Finally, discriminant validity was examined using the

heterotrait–monotrait (HTMT) values. The result showed that each

value was below 0.85 (Henseler et al., 2015); thus, no issues were

identified.

4.3.2 | Structural model

The structural model was evaluated using the standardized path

coefficients (β‐value), significance level (t value), and R2 estimates.

The result showed that all the hypothesized relationships were

supported (see Table 1; H1 to H4).

4.3.3 | Structural model based on multigroup analysis

H6a and H6b predicted the moderating effects of trust in social

media celebrities and addictive use of social media on the relation-

ships between body image and each of the purchase behavior and

self‐esteem factors. Before conducting the multigroup analysis, the

sample was first separated into two subgroups according to the

median score for each of the factors trust in social media celebrities

and addictive use of social media.1 For trust in social media

celebrities, the first group contained 425 women with a low trust

level (below or equal to the median) and the second group contained

693 women with a high trust level (above the median). For addictive

use of social media, the first group contained 474 women with a low

level of addictive use (below or equal to the median) and the second

group contained 644 women with a high level of addictive use (above

the median). Next, the measurement invariance of composite models

(MICOM) procedure was employed to assess the configural and

compositional invariance and the equality of the values and variances

across the two groups for each factor (Henseler et al., 2016). The

results of the MICOM procedure supported full measurement

invariance (see Supporting Information: Table F, Supporting Informa-

tion Appendix); see Study 2(i) and Study 2(ii)). Subsequently, we

compared the path coefficients between the two groups in each

factor using Henseler's PLS‐MGA approach (Hair et al., 2017). This

approach assesses the observed distribution of the bootstrap

outcomes instead of making any distributional assumptions

(Henseler, 2012). As shown in Table 2, H5a and H5b were supported

as trust in recommendations made by social media celebrities

moderated the relationship between body image and purchase

behavior (t value = 1.997**) as well as the relationship between body

1Cheah et al. (2021) and Sarstedt et al. (2020) highlighted that the use of PROCESS is not

advisable because it does not account for the measurement error inherent in multi‐item

measurements as well preventing researchers from simultaneously analyzing complex

inter‐relationships between observed and latent variables.

AMEEN ET AL. | 2117

image and self‐esteem (t value = 5.141***). However, H6a was only

partially supported as the addictive use of social media moderated

the relationship between body image and purchase behavior (t

value = 4.167***) but did not moderate the relationship between

body image and self‐esteem (t value = 1.145). Nevertheless, the

effect of body image on self‐esteem was significant among both the

high‐addiction and the low‐addiction group.

4.4 | Discussion

The research findings supported the proposed model, which drew on

social comparison theory (Festinger, 1954). They revealed that

augmented reality can affect body image, self‐esteem, and purchase

behavior positively. This study found that perceived augmentation

had a significant effect on body image. In other words, the quality of

the virtual make‐up try‐on application and the way in which the

virtual make‐up is placed on the face in real‐time affect Generation Z

women's satisfaction with how they look. This finding bridges the gap

in research by improving our understanding of the effects of

customers' perceived augmentation (Javornik, 2016; Javornik,

Rogers, et al., 2016). The findings of this study show that body

image has a significant effect on both self‐esteem and purchase

behavior. Furthermore, they show how body image is affected by

factors related to the use of augmented reality and how the body

image created by AR‐enabled experiences can build self‐esteem

among Generation Z women. In addition, the findings reveal that the

depth and breadth of the purchase of cosmetics products has a

significant impact on Generation Z women's self‐esteem.

Moreover, this study examined the role of social media‐related

factors in the relationship between Generation Z women's body image

and their self‐esteem as well as the relationship between their body

image and their actual purchase behavior. The findings indicate that

trust in social media celebrities moderates the effects of body image on

purchase behavior as well as self‐esteem. In particular, the more trust

recommendations made by celebrities that Generation Z women see on

social media, the more confident they are about the products that they

are buying and the higher their self‐esteem becomes. However, trust in

content generated by social media celebrities is difficult to achieve, as

has been highlighted in recent studies (Lou & Yuan, 2019).

A surprising finding was the absence of the moderating effects of

addictive use of social media on self‐esteem among young women.

This may indicate that, although addiction to social media leads to

Generation Z individuals becoming less sociable or more withdrawn

(Chappet, 2019), it does not necessarily result in a weaker

relationship between body image and self‐esteem. In other words,

whether or not Generation Z women are highly addicted to social

media has no effect on the significance of the relationship between

body image and self‐esteem. The findings also reveal that the effect

of body image on self‐esteem is significant among Generation Z

women, regardless of how addicted they are to social media. A

possible explanation for this lack of the moderating effects of

addictive use of social media in our study is the type of social media

content that these young women have been exposed to while using

TABLE 1 Assessment of the structural model

Hypothesis Standard β t value Supported? R2

H1 Perceived augmentation ≥ body image 0.06 2.095** Yes 0.1

H2 Body image ≥purchase behavior 0.41 12.364*** Yes 0.2

H3 Body image ≥ self‐esteem 0.68 34.577*** Yes 0.6

H4 Purchase behavior ≥ self‐esteem 0.15 4.887** Yes

Note: ***p < 0.001; **p < 0.01; *p < 0.05.

TABLE 2 Multigroup analysis

Hypothesis Moderator Relationship t Value (group differences)

Standard β (group one: lower level)

Standard β (group two: higher level) Results

H5a Trust in social media celebrities

Body image ≥ purchase behavior

1.997** −0.060 0.463*** Supported

H5b Trust in social media celebrities

Body image ≥ self‐esteem

5.141*** 0.201*** 0.321*** Supported

H6a Addictive use of social media

Body image ≥ purchase

behavior

4.167*** 0.201*** 0.413*** Supported

H6b Addictive use of social media

Body image ≥ self‐esteem

1.145 0.331*** 0.332*** Not supported

Note: ***p < 0.001; **p < 0.01; *p < 0.05.

2118 | AMEEN ET AL.

social media. It is possible that they have mainly been exposed to

positive posts on beauty‐related topics due to their interest in this

area. Therefore, the level of addiction to social media use has not

affected the impact of body image on their self‐esteem.

5 | STUDY 2

In Study 2, we extend the model from Study 1 by analyzing the

moderating effects of the type of chatbot support (friend vs. assistant)

(see Figure 1). Chatbots can simulate human language with the aid of a

text‐based dialog system (Youn & Jin, 2021). Previous studies have

examined the impact of the two types of chatbot support (friend vs.

assistant) (e.g., Dautenhahn, 2007; Youn & Jin, 2021). This study

extends the findings of these studies by showing the impact of the

chatbot support type on Generation Z female consumers' perceived

augmentation, body image, self‐esteem, and purchase behavior.

5.1 | The moderating effects of the chatbot support type

Chatbot systems not only mimic human conversation but also utilize

well‐trained chatbots widely to interact with users in business,

education, or information retrieval (Ciechanowski et al., 2019). In

addition, chatbots' language style and name can influence perceptions

of their social presence as well as mindful and mindless anthropo-

morphism (Mariani et al., 2022). Chatbots are increasingly used in

marketing services to facilitate various processes related to customer

service and personalization. Recent research has shown that anthro-

pomorphic assistants and the increasing perceived humanness of

chatbots result in more effective conversations (Roy & Naidoo, 2021).

Sundar et al. (2017, p. 89) reported that “the label of assistant and the

label of companion can both trigger heuristics (or mental shortcuts)

that elicit positive evaluations from the user,” such that the label of

“assistant” triggers the “helper” heuristic while the label of “compan-

ion” triggers the “social presence” or “copresence” heuristic. Thus, a

chatbot's assistantship and friendship could be both (1) the intrinsic

properties of the chatbot and (2) the mental representations ascribed

to each consumer's approach (Youn & Jin, 2021).

The “assistant” type of interactive technology identifies and

responds to humans' needs primarily in the sense of assisting in

certain tasks, thus making the “competence” dimension more relevant

and salient (Dautenhahn, 2007). However, the role of a “companion”

type of interactive technology is to provide users with emotional

support, thus making the “sincerity” dimension more relevant and

salient (Dautenhahn, 2007). Youn and Jin (2021) found that the type

of customer–chatbot relationship affects customers' perception of

the brand personality and parasocial interactions. Consumers who

interact with a friendlier chatbot will experience stronger parasocial

interactions with it. However, when chatbots are used in the context

of digital beauty experiences, the customer–chatbot relationship may

affect customers' perception of the experience, body image, self‐

esteem, and actual purchase behavior. Previous studies have found

that digital devices with friend‐like characteristics encourage

stronger feelings of warmth than those with engineer‐like character-

istics that can relate to brand attachment (Schweitzer et al., 2019).

For Generation Z consumers, it is possible that a chatbot has the

anthropomorphic attribution with friend‐like characteristics, that is,

“female, tall, sassy, perky, humorous, abrupt, shy, helpful, nice,

friendly, unassertive, intelligent, factual, organized, and serious”

(Schweitzer et al., 2019; p. 702). It is possible that a chatbot with

friend‐like characteristics can improve young women's perceptions of

their bodies and increase their self‐esteem and actual purchase

behavior since previous research has highlighted that positive social

interactions and social influence improve young women's perceptions

of their beauty and self‐esteem (Coughlin, 2009). We propose that

Generation Z women who receive chatbot support in friend‐like

conversations would have a more positive perception of their body

image, self‐esteem, and actual purchase behavior than women who

receive chatbot support in assistant like conversations that are aimed

at improving functionality. Hence, we propose:

H7: The type of chatbot support (assistant vs. friend) moderates the

effects of Generation Z customers' (7a) perceived augmentation on

body image; (7b) body image on self‐esteem; and (7c) body image on

actual purchase behavior such that those who interact with a chatbot

as a virtual friend will perceive these relationships to be stronger.

5.2 | Method, sampling, data collection, and manipulation check

In Study 2, the authors employed a one‐way experimental design in

which female participants from Generation Z in Malaysia were asked to

evaluate chatbot support via a virtual assistant versus virtual friend

condition. Following the between‐subject design method, participants

were first assigned randomly to one of the conditions. In particular,

respondents were instructed to read a chatbot scenario regarding

seeking information about a make‐up product. In this manipulation

procedure, respondents were randomly exposed to one of two

conditions: (1) a chatbot as a virtual assistant, in which participants

were exposed to communication that was intelligent, factual, organized,

and serious; or (2) a chatbot as a virtual friend, in which respondents

were exposed to communication that was helpful, nice, and friendly (see

Supporting Information: Table G, Supporting Information Appendix, C,

Panel A and Panel B). In addition, the communications in the two

chatbot scenarios were identical (i.e., chatbot communications from two

different well‐known international beauty brands), that is, seeking

information on a make‐up product (i.e., lipstick).

Consent agreement (e.g., assurance of anonymity) was given to the

participants before their participation. First, the participants were

instructed to imagine that they were looking for information on lipstick

and presented with the paragraph that introduced a chatbot given by

each of the two beauty brands. They were also informed that they

would encounter a mobile phone screen depicting a conversation

AMEEN ET AL. | 2119

between the brand's chatbot and a consumer. Second, the participants

were presented with an explanation that described the chatbot as either

a virtual assistant or a virtual friend. We employed forced exposure by

displaying the paragraph for 30 s to ensure that the participants were

able to read the message completely. They were then asked to answer a

number of questions about perceived augmentation, body image, actual

purchase behavior, and self‐esteem (see Study 1 for the measurement

items' details). The scenario was adapted fromYoun and Jin (2021) and

ensured that no one realized the specific research hypotheses during

the study, demonstrating that the concern about demand characteristics

was nonexistent.

In 2021, a sample of 300 consumers, among attendees at a

research lab in Malaysia, was invited to participate by the researcher

via email. They volunteered to participate in the study after we

discussed the goal of our investigation during a meeting at the

research lab. Following that, the instructions for the online experi-

ment at the lab were presented to the participants. Fifteen

participants were excluded because they did not answer correctly

the following attention check question: What does the virtual

chatbot communication look like? The respondents had to choose a

binary answer: either the communication was an assistant or it was

friendly. In addition, 35 responses were discarded due to being

incomplete, leaving 250 usable responses (n = 118 for the assistant

data set; n = 132 for the friend data set) from Generation Z female

participants (mean age = 22 and standard deviation = 0.597) with

student status. Importantly, these participants have used the brand's

virtual artist application for more than a year (between 1 and 5 years).

In addition, they have shopped with the cosmetic brand before

through mobile commerce and social commerce (many times a week)

with the help of the chatbot service. Supporting Information: Table H

(Supporting Information Appendix) (see Study 2) contains the

demographic information of the participants in this study.

For the appraisal of manipulation success, the participants were

asked about the extent to which they perceived the chatbot to be an

assistant or a friend. The two specific statements were: (1) This

chatbot is an assistant to me; and (2) This chatbot is a friend to me. A

7‐point Likert scale, ranging from 1 “strongly disagree” to 7 “strongly

agree,” was used. An independent sample t test analysis reported a

statistically significant difference between assistant and friend

chatbot conditions (t = 5.432, df = 248, p < 0.001, the mean values

of the assistant chatbot condition versus the friend chatbot condition

for the first question being 6.14 and 5.29, respectively; while

t = −4.230, df = 248, p < 0.001, the mean values of the assistant

chatbot condition versus the friend chatbot condition for the second

question being 2.74 and 4.01, respectively). Thus, these findings

showed that the participants were more likely to identify the

relationship type assigned to them correctly.

5.3 | Analysis and results

In Study 2, we continued to use the PLS‐SEM technique to assess the

measurement model and structural model.

5.3.1 | Measurement model

Following the standard evaluation of the measurement model, this

study first examined the result of the loading, convergent validity,

internal reliability, and discriminant validity (see Supporting Informa-

tion: Table B, Supporting Information Appendix). After cleaning

the low loading values, all the items for the subgroup data sets (i.e.,

the assistant data set and friend data set) achieved outer loadings

above the threshold value of 0.70. In addition, convergent validity

was established because all the factors across the data sets had an

average variance extracted (AVE) of 0.5 or higher. In addition, both

CA and CR values for both subgroup data sets were above the

threshold value of 0.7 (Hair et al., 2017); hence, the measurement

model met the reliability requirements. Finally, there were no

discriminant validity issues in the HTMT assessment because both

data sets showed that all the values were below 0.85 (Henseler

et al., 2015).

5.3.2 | Structural model based on multigroup analysis

H7a to H7c predicted the moderating effects of chatbot support

(assistant vs. friend) on the relationships between perceived

augmentation and body image as well as body image and both

factors of purchase behavior and self‐esteem. Similar to Study 1, our

study first assessed the measurement invariance using MICOM.

Partial measurement invariance was thus established for the assistant

and friend groups (see Supporting Information: Appendix B, Study 2)

because not all factors have significant differences in terms of the

composite mean values and variance ratio (i.e., not all the results of

both composite mean and variance ratio values fall outside the upper

and lower bounds of the 95% confidence interval). Subsequently, we

compared the path coefficients between the two groups in each

factor using Henseler's PLS‐MGA approach (Hair et al., 2017). As

shown in Table 3, H7a, H7b, and H7c were supported as the chatbot

support type moderated the relationships between perceived

augmentation and body image (t value = 4.155**) and between body

image and purchase behavior (t value = 3.065**) as well as the

relationship between body image and self‐esteem (t value =

3.993***). Nevertheless, the virtual friend type of chatbot support

showed a stronger path coefficient effect than the virtual assist-

ant type.

5.4 | Discussion

This study examined the role of the chatbot support type (friend vs.

assistant) in the body image, self‐esteem, and purchase behavior of

Generation Z female customers who use beauty brands' virtual

applications. Our findings show that, for Generation Z women,

receiving support from a chatbot in a form of a virtual friend, with the

characteristics of being helpful, nice, and friendly, can have a more

2120 | AMEEN ET AL.

positive outcome for perceptions in terms of body image and self‐

esteem and improved purchase buying behavior when using beauty

brands' virtual applications (which integrate augmented reality).

Hence, our findings show that, when the chatbot support is in the

form of friendship, it can have a positive effect on how female

customers perceive themselves and how they evaluate the impact of

services enabled by other technologies (i.e., services enabled by

augmented reality) on their body image. This is particularly important

for young women who tend to use cosmetics for compensation and

concealing purposes when they feel dissatisfied with areas of their

face (Dickman, 2010). This extends the findings of previous studies

on chatbots, which have found that assistant versus friendship

chatbot support can influence customers' perception of brands (Youn

& Jin, 2021) and feeling of warmth (Schweitzer et al., 2019). While

the “assistant” type of chatbot support (i.e., intelligent, factual, and

organized) can offer responses to different customer enquiries, it can

be extended to offer benefits to both the customer and the brand.

6 | STUDY 3

Study 3 re‐examines the overall proposed hypotheses of Study 1 and

Study 2 with the inclusion of control variables, namely brand

attachment, brand reputation, and brand awareness (see Figure 1).

These three brand concepts have long been regarded as important

factors in influencing product evaluations, preferences, and purchase

intentions (Thomson et al., 2005; Veloutsou & Moutinho, 2009; Yoo

& Donthu, 2001; Yoo et al., 2000). However, there is a gap in

research concerning how brand‐related factors affect Generation Z

female customers when using various technologies in their shopping

journey. Hence, this study enriches our understanding of the impact

of such factors in the context of this study by building on the findings

of Study 1 and Study 2.

6.1 | The impact of brand attachment, reputation, and awareness

Previous studies have emphasized the impact of various brand‐

related factors on consumers' preferences and choices (Yoo &

Donthu, 2001; Yoo et al., 2000). In particular, brand attachment,

reputation, and awareness have been found to be significant factors

in shopping contexts (Shahid et al., 2022; Thomson et al., 2005; Yoo

et al., 2000). Brand attachment is conceptualized as “an emotion‐

laden target‐specific bond between a person and a specific object”

(Thomson et al., 2005; p. 77). This factor is related to consumers'

emotions regarding a brand, and it comprises affection for, connec-

tion to, and passion about a brand (Thomson et al., 2005). Brand

reputation occurs primarily through the signals that producers send

to the market and the degree to which the organizational tactics

support the marketing signals to establish it (Veloutsou &

Moutinho, 2009). It refers to whether consumers find the brand to

be trustworthy, to be reliable, and to make honest claims (McLean

et al., 2022). Brand awareness is the “ability for a buyer to recognize

or recall that a brand is a member of a certain product category”

(Aaker, 1991; p. 61).

In the context of the involvement of chatbots in brand

management, previous studies have examined the attributes of

chatbots facilitating positive beliefs about and behavior towards a

brand (e.g., Roy & Naidoo, 2021). Brand‐related factors have mainly

been examined as outcome variables in previous studies (e.g., Cheng

& Jiang, 2020; Trivedi, 2019). Despite the existing literature agreeing

that brand‐related factors affect consumers' choices, there is a lack of

research on how such factors affect consumers' preference for the

type of chatbot to interact with during their shopping experience. In

addition, consumers' preferences for a chatbot type (friend vs.

assistant) can be influenced by brand attachment, reputation, and

awareness. For example, when consumers are emotionally attached

to a brand, they develop strong feelings and become more

emotionally engaged in their experience. Therefore, it is possible

that they prefer the chatbot to act as a friend that they can bond with

and become more emotionally attached to as it encourages stronger

feelings of warmth than one with engineer‐like characteristics linked

to brand attachment (Schweitzer et al., 2019). As brand reputation

covers functional aspects related to the brand, including being

trustworthy, being reliable, and making honest claims (McLean

et al., 2022), it is possible that consumers who interact with a brand

that they perceive to have a positive reputation may prefer a chatbot

to act as an assistant that is functional and reliable. Similarly, brand

awareness may change consumers' preferences.

TABLE 3 Multigroup analysis for Study 2

Hypothesis Moderator Relationship t Value (group differences)

Standard β (group one: assistant)

Standard β (group two: friend) Results

H7a Chatbot support Perceived augmentation ≥

body image

4.155*** 0.166*** 0.509*** Supported

H7b Chatbot support Body image ≥ purchase behavior

3.065*** 0.331*** 0.564*** Supported

H7c Chatbot support Body image ≥ self‐esteem

3.993*** 0.263*** 0.568*** Supported

Note: ***p < 0.001; **p < 0.01; *p < 0.05.

AMEEN ET AL. | 2121

In addition, when empirically examining purchase intention and

self‐esteem effects, it is desirable to control for potential exogenous

influences of the brand attachment, reputation, and awareness

concepts to ensure that a causal explanation can be achieved from

our inferential test (Nguyen et al., 2018). Furthermore, Generation Z

customers' perceptions of a brand may affect the extent to which

they are influenced by social media interactions (Mahmoud

et al., 2021). Therefore, we empirically analyzed the impact of these

brand‐related factors of the relationships in our proposed model as

control variables.

6.2 | Method, sampling, data collection, and manipulation check

Study 3 (in 2022) employed a similar experimental design to the one

that we used in Study 2, in which female participants from

Generation Z in Malaysia were randomly asked to evaluate the type

of chatbot support (virtual assistant vs. virtual friend) in the scenario

(a make‐up cosmetic product) that we employed. In addition, the

participants responded to questions related to the moderating effect

of the external influences of social media (i.e., trust in social media

celebrities and addictive use of social media).

A new sample of 200 female volunteers from Generation Z, from

attendees at our research lab, were invited randomly via email by the

researcher. Specifically, 100 participants were exposed to the

scenario of a virtual assistant and the remaining 100 participants

were exposed to the scenario of a virtual friend. A paragraph was

displayed for 30 s to both groups of participants to ensure that they

were able to read the complete message. Subsequently, the

participants were asked to respond to similar measurements to

those used in Study 1 and Study 2. In addition, new control variables

were included for which the measurement items were adapted from

previous studies: brand attachment (Thomson et al., 2005), brand

reputation (Veloutsou & Moutinho), and brand awareness (Yoo

et al., 2000).

From the data collection, the majority of the participants—

regardless of the type of chatbot support—were students aged 22

with standard deviation of 0.773. Importantly, these participants

have used the brand's virtual artist application for more than a year

(between 1 and 5 years). In addition, they have shopped with the

cosmetic brand before through mobile commerce and social

commerce (many times a week) with the help of the chatbot service.

In terms of the attention check, the respondents were able to choose

the right answer regarding whether the communication was being an

assistant or a friend.

To ensure the effectiveness of the manipulation check, similar

manipulation questions to those in Study 2 were used. The

independent‐sample test results showed significant differences

between the assistant and the friend chatbot conditions (t = 4.451,

df = 98, p < 0.001, the mean values of the assistant chatbot condition

vs. the friend chatbot condition for the first question being 5.85 and

4.51, respectively; while t = −3.545, df = 98, p < 0.001, the mean

values of the assistant chatbot condition vs. the friend chatbot

condition for the second question being 3.24 and 5.41, respectively).

Thus, these findings also showed a similar outcome to Study 2 in that

the participants were able to identify the relationship type assigned

to them correctly Figure 3.

6.3 | Analysis and result

Subsequently, we continued to use the PLS‐SEM technique to assess

the measurement model and structural model in Study 3.

6.3.1 | Measurement model

All the items for the subgroup data sets (i.e., the assistant data set and

friend data set) achieved outer loadings above the threshold value of

0.70, especially after removing indicators that have low loading

values. Consequently, the CA, CR, AVE, and HTMT values for both

subgroup data sets met the satisfactory threshold values suggested

by Hair et al. (2017) (see Supporting Information: Table C in

Supporting Information Appendix).

6.3.2 | Structural model based on multigroup analysis

The results are generally consistent with the findings of Study 1

(Table 4), in which all the proposed hypothesized relationships were

supported (H1 to H4), after controlling for the effects of brand

attachment, brand reputation, and band awareness. However, the

findings also show that the control variables of both brand awareness

and brand reputation have significant effects on Generation Z

women's purchase behavior.

Study 3 used a similar assessment procedure to Study 1 and

Study 2 when assessing the proposed moderating effect of H5a to

H7c while controlling for the three brand‐related factors. Partial

measurement invariance was established for factors such as trust in

F IGURE 3 Differences between the virtual assistant and the virtual friend in Study 3

2122 | AMEEN ET AL.

social media celebrities and addictive use of social media. The

invariance also occurred for both assistant and friend groups (see

Supporting Information: Appendix B, Study 3i to Study 3iii).

Subsequently, we compared the path coefficients between the

moderating variables using Henseler's PLS‐MGA approach (Hair

et al., 2017). As shown inTable 5, both H5a and H5b were supported

as trust in the recommendations made by social media celebrities

moderated the relationship between body image and purchase

behavior (t value = 2.334**) as well as the relationship between body

image and self‐esteem (t value = 2.615**). In addition, H6a was

supported as the addictive use of social media moderated the

relationship between body image and purchase behavior (t value =

2.412**) but did not moderate the relationship between body image

and self‐esteem (t value = 0.945). Nevertheless, the effect of body

image on self‐esteem was significant in both the low social media

addiction and the high social media addiction group. Furthermore,

H7a, H7b, and H7c were supported (see Table 5). Similar to Study 2,

there were also significant differences between virtual assistant and

virtual friend chatbot support for perceived augmentation and body

image (t value = 5.521**), body image and purchase behavior (t

value = 4.210**), and body image and self‐esteem (t value = 4.523**).

Importantly, the type of virtual friend also showed a stronger path

coefficient effect than the virtual assistant type. Overall, when

examining the impact of brand attachment, reputation, and image,

the results remained consistent with those of Study 2.

6.4 | Discussion

Overall, the findings of Study 3 supported the robustness of our

earlier findings in Study 1 and Study 2 when controlling for brand

attachment, brand reputation, and brand awareness. While the

existing literature has highlighted the significance of brand‐related

factors for various aspects of the customer journey (Shahid

et al., 2022; Thomson et al., 2005; Yoo et al., 2000), our findings

show that the inclusion of these factors does not influence

Generation Z women's perceptions of the technologies that they

interact with as part of their journey. This is possibly due to the

nature of Generation Z consumers' perceptions of brands as they

were found to be less attached and loyal to brands than other

consumer cohorts and they trust user‐generated content on social

media more than the brands themselves (Djafarova & Bowes, 2021).

In addition, Generation Z consumers are mostly well educated about

brands and the realities behind them (Francis & Hoefel, 2018).

Furthermore, it is conceivable that Generation Z women are tech

natives; hence, they are less influenced by brand‐related factors.

However, our findings show that these control variables have

significant effects on Generation Z women's purchase behavior. This

is consistent with previous studies emphasizing the impact of brand‐

related factors on customer purchase behavior (e.g., Shahid

et al., 2022; Thomson et al., 2005).

7 | GENERAL DISCUSSION

Prior research has emphasized that low self‐esteem, confidence, and

body image are major issues for young female consumers

(Chappet, 2019; Khamis & Zaatarti, 2019). In addition, previous

studies on consumers' interactions with technologies have demon-

strated the potential of these technologies to improve their shopping

experience (e.g., Ameen et al., 2021; Ng et al., 2019). In this study, we

study the integration of multiple technologies as part of Generation Z

women's customer journey. We argue that the augmentation enabled

by augmented reality, the type of chatbot (friend vs. assistant), and

social media (specifically trust in social media celebrities and addictive

use of social media) can affect Generation Z female consumers' body

image, purchase behavior, and self‐esteem. Evidence for our

hypotheses was provided by a survey and two experimental studies

TABLE 4 Assessment of the structural model

Hypothesis Standard β t Value Supported? R2

H1 Perceived augmentation ≥ body image 0.804 43.314** Yes 0.6

H2 Body image ≥ purchase behavior 0.174 3.276*** Yes 0.7

H3 Body image ≥ self‐esteem 0.107 2.831*** Yes 0.6

H4 Purchase behavior ≥ self‐esteem 0.140 2.967** Yes

Control variables

Brand attachment ≥ purchase behavior 0.067 1.212

Brand attachment ≥ self‐esteem 0.076 1.583

Brand awareness ≥ purchase behavior 0.135 1.766*

Brand awareness ≥ self‐esteem 0.056 1.139

Brand reputation ≥ purchase behavior 0.119 1.698

Brand reputation ≥ self‐esteem 0.014 0.602

Note: *p < 0.05; **p < 0.01; ***p < 0.001.

AMEEN ET AL. | 2123

T A B L E

5 M ul ti gr o up

an al ys is

fo r St ud

y 3

H yp

o th es is

M o d er at o r

R el at io ns

hi p

t V al ue

(g ro up

d if fe re nc

es )

St an

d ar d β (g ro up

o ne

: lo w er

le ve

l) St an

d ar d β (g ro up

tw o :

hi gh

er le ve

l) R es ul ts

H 5 a

T ru st

in so ci al

m ed

ia ce

le b ri ti es

B o d y im

ag e ≥ p ur ch

as e b eh

av io r

2 .3 3 4 **

0 .1 7 8 **

0 .2 6 8 ** *

Su p p o rt ed

H 5 b

T ru st

in so ci al

m ed

ia ce

le b ri ti es

B o d y im

ag e ≥ se lf ‐e st ee

m 2 .6 1 5 **

0 .2 0 1 ** *

0 .3 2 1 ** *

Su p p o rt ed

H 6 a

A d d ic ti ve

us e o f so ci al

m ed

ia B o d y im

ag e ≥ p ur ch

as e b eh

av io r

2 .4 1 2 **

0 .2 2 2 ** *

0 .3 3 4 ** *

Su p p o rt ed

H 6 b

A d d ic ti ve

us e o f so ci al

m ed

ia B o d y im

ag e ≥ se lf ‐e st ee

m 0 .9 4 5

0 .1 8 1 **

0 .1 9 5 **

N o t su p p o rt ed

C o nt ro l va

ri ab

le s

B ra nd

at ta ch

m en

≥ p ur ch

as e b eh

av io r

0 .0 5 4

0 .0 6 8

0 .0 6 0

N o t si gn

if ic an

t

B ra nd

at ta ch

m en

t ≥

se lf ‐e st ee

m 0 .5 3 4

0 .0 7 6

0 .0 6 4

N o t si gn

if ic an

t

B ra nd

aw ar en

es s ≥ p ur ch

as e b eh

av io r

0 .5 8 4

0 .1 6 8 *

0 .1 5 8 *

N o t si gn

if ic an

t

B ra nd

aw ar en

es s ≥

se lf ‐e st ee

m 0 .8 7 3

0 .0 6 7

0 .0 7 3

N o t si gn

if ic an

t

B ra nd

re p ut at io n ≥ p ur ch

as e b eh

av io r

1 .4 8 6

0 .1 2 1 *

0 .1 4 3 *

N o t si gn

if ic an

t

B ra nd

re p ut at io n ≥ se lf ‐e st ee

m 1 .3 2 4

0 .0 6 2

0 .0 6 9

N o t si gn

if ic an

t

H yp

o th es is

M o d er at o r

R el at io ns

hi p

t V al ue

(g ro up

d if fe re nc

es )

St an

d ar d β (g ro up

o ne

: as si st an

t) St an

d ar d β (g ro up

tw o :

fr ie nd

) R es ul ts

H 7 a

C ha

tb o t su p p o rt

P er ce

iv ed

au gm

en ta ti o n ≥ b o d y im

ag e

5 .5 2 1 ** *

0 .3 7 6 ** *

0 .6 1 2 ** *

Su p p o rt ed

H 7 b

C ha

tb o t su p p o rt

B o d y im

ag e ≥ p ur ch

as e b eh

av io r

4 .2 1 0 ** *

0 .1 3 7 ** *

0 .3 1 6 ** *

Su p p o rt ed

H 7 c

C ha

tb o t su p p o rt

B o d y im

ag e ≥ se lf ‐e st ee

m 4 .5 2 3 ** *

0 .1 6 3 ** *

0 .3 6 8 ** *

Su p p o rt ed

C o nt ro l va

ri ab

le s

B ra nd

at ta ch

m en

t≥ p ur ch

as e b eh

av io r

0 .0 5 4

0 .0 6 0

0 .0 5 8

N o t si gn

if ic an

t

B ra nd

at ta ch

m en

t≥ se lf ‐e st ee

m 0 .5 3 4

0 .0 8 1

0 .0 7 4

N o t si gn

if ic an

t

B ra nd

aw ar en

es s ≥ p ur ch

as e b eh

av io r

0 .5 8 4

0 .1 7 8 *

0 .1 7 2 *

N o t si gn

if ic an

t

B ra nd

aw ar en

es s ≥ se lf ‐e st ee

m 0 .8 7 3

0 .0 5 7

0 .0 1 1

N o t si gn

if ic an

t

B ra nd

re p ut at io n ≥ p ur ch

as e b eh

av io r

1 .4 8 6

0 .1 5 3 *

0 .1 9 3 *

N o t si gn

if ic an

t

B ra nd

re p ut at io n ≥ se lf ‐e st ee

m 1 .3 2 4

0 .0 4 7

0 .0 6 5

N o t si gn

if ic an

t

N ot e:

*p < 0 .0 5 ; ** p < 0 .0 1 ; ** *p

< 0 .0 0 1 .

2124 | AMEEN ET AL.

showing that the integration of augmented reality and a “friend” type

of chatbot support in services offered by beauty brands and

promotion through trusted social media celebrities can improve

Generation Z female customers' body image, self‐esteem, and

purchase behavior. Overall, the findings show that Genertaion Z

women are less influenced by brand‐related factors when interacting

with various technologies as part of their shopping journey.

7.1 | Theoretical contributions

Our research makes important contributions to the literature on

Generation Z consumers' behavior by highlighting the conditions

under which their self‐esteem and purchase behavior can be

enhanced with technology‐enabled solutions. The literature in this

study stream has shown that body image and low self‐esteem are

major issues among Generation Z consumers, specifically female

consumers, and has called for further research to identify ways to

enhance their body image and self‐esteem (Khamis & Zaatarti, 2019;

Rosenbaum, 2018; Thompson & Chad, 2002). While there has been

substantial interest in understanding the impact of technology on

young consumers (e.g., Ameen & Anand, 2020; Ameen et al., 2021;

Yu et al., 2019), no research has investigated how the integration of

multiple technologies into the customer journey can influence

Generation Z female consumers' body image, self‐esteem, and

purchase behavior. To the best of our knowledge, our research is

the first to consider how the use of various technologies in the

services offered to Generation Z female consumers can be beneficial

beyond enhancing their purchase behavior, drawing on social

comparison theory (Festinger, 1954). This is significant given the

central role that self‐esteem and body image play in Generation Z

female consumers' decision making (Hendrickse et al., 2017).

Moreover, we contribute to the literature on Generation Z

consumers' interactions with technology (e.g., Ameen & Anand, 2020;

Ameen et al., 2021; Yu et al., 2019) by showing how the integration

of augmented reality, chatbots, and social media can improve

Generation Z female consumers' body image, self‐esteem, and

purchase behavior. This study builds on the findings of previous

studies (e.g., Javornik, 2016; Javornik, Rogers, et al., 2016) and offers

evidence that the perceived augmentation of reality in these

experiences has a strong influence on body image and self‐esteem

and shapes the purchase behavior of Generation Z women. The

present study also contributes to a research stream that examines the

role of social media, body image, self‐esteem, and purchase behavior

(e.g., Hawi & Samaha, 2017; West, 2018). Our findings show that,

while Generation Z female consumers' trust in social media

celebrities' recommendations has a significant moderating effect on

the relationship between body image and self‐esteem, the addictive

use of social media does not have any significant effects in this

context.

Adding to the literature on consumer interactions with chatbots

(Dautenhahn, 2007; Youn & Jin, 2021), our findings offer a more

nuanced understanding of how the chatbot support type, “friend vs

assistant,” can affect Generation Z female consumers' perceived

augmentation, body image, self‐esteem, and purchase behavior and

the impact of brand‐related factors in this context. Previous research

has studied the effects of the friend versus assistant type of chatbot

and the role of factors such as functionality and anthropomorphism in

chatbot support in enhancing purchase behavior or customer–brand

relationships (e.g., Roy & Naidoo, 2021; Sundar et al., 2017). Our

research extends the findings of these studies by establishing that,

when Generation Z female consumers receive support from a chatbot

in the form of a virtual friend, they can have a more positive

perception of beauty brands' virtual applications (which integrate

augmented reality) and their body image and self‐esteem and

improved purchase behavior. Additionally, in the context of chatbot

support, brand‐related factors have mainly been examined as

outcome variables in previous studies (e.g., Cheng & Jiang, 2020;

Trivedi, 2019). However, the majority of previous studies have

highlighted the impact of brand‐related factors, including brand

attachment, brand reputation, and brand awareness, in shopping

contexts (Shahid et al., 2022; Thomson et al., 2005; Yoo et al., 2000).

Our research adds to this line of literature by showing that, for

Generation Z female consumers, brand‐related factors affect neither

their interactions with the technologies offered by brands as part of

their services nor their self‐esteem. However, our findings show that

brand reputation and brand awareness affect these consumers'

purchase behavior. Overall, our research offers a novel way to

enhance body image, self‐esteem, and purchase behavior among

Generation Z female consumers.

7.2 | Managerial implications

Beauty brands are increasingly integrating cutting‐edge technologies

into the services offered to their customers. Until now, the primary

purpose of beauty brands when offering various services enabled by

cutting‐edge technologies had been to offer more convenient

services to customers. Given the significance of the young female

consumer segment for these brands, there is a need to identify new

ways in which their services can be beneficial to young women in

ways that extend beyond influencing their buying decision making.

Beauty brands can play an active role in enhancing young female

consumers' body image, self‐esteem, and purchase behavior through

the careful use of augmented reality, chatbots, and social media.

Despite the excitement surrounding the use of advanced

technologies in retail, there is still much to be learned about how

they can work more effectively. For example, given the significance

of augmentation in enhancing Generation Z women's body image and

self‐esteem, beauty brands should collaborate with IT companies to

find ways to improve the augmentation in the services that they

offer. Further improvements regarding positioning in real time and

precision in showing features are required. In addition to focusing on

cutting‐edge technologies, beauty brands should carefully develop

strategies for integrating social media effectively when communicat-

ing with young female consumers. Social media celebrities or key

AMEEN ET AL. | 2125

opinion leaders play a significant role in encouraging young female

consumers to use technologically advanced services and enhancing

their body image and self‐esteem, but it is crucial to ensure that these

celebrities are trusted by the target consumers. Hence, beauty brands

should collaborate with social media influencers who are considered

trustworthy and are appealing to the young female segment of

consumers to influence them in ways that reach beyond buying

beauty products. Given that social media have a profound impact on

Generation Z women, policy makers should collaborate with beauty

brands and social media celebrities to find ways to use social media to

improve the body image and self‐esteem in this cohort. In addition, to

offset the potential negative impacts of social media on young

women's behavior (e.g., as a result of addictive use of social media),

beauty brands should make such services more available on their

websites.

Finally, while the beauty industry has witnessed a sharp increase in

the use of chatbots since the start of the COVID‐19 pandemic, there is a

need for a more personalized approach to the conversation style of

chatbots when interacting with young female customers (Generation Z) in

a “friend” type of support to provide benefits that extend beyond

increasing sales and improving the customer–brand relationship. Beauty

brands should offer chatbot services in the form of a virtual friend (i.e.,

characterized as being helpful, nice, and friendly) and carefully design the

language style in the text‐based dialog system to enhance young

women's body image and self‐esteem. This is equally important for large

beauty brands as our findings show that brand attachment, reputation,

and awareness do not particularly affect how Generation Z women

interact with cutting‐edge technology‐enabled services. However, given

that brand awareness and brand reputation are important for enhancing

Generation Z female consumers' purchase behavior, beauty brands

should identify ways to enhance their reputation and awareness among

this generation of consumers. This can be achieved in various ways, for

example through collaboration with trusted social media influencers.

8 | LIMITATIONS AND FUTURE RESEARCH

Despite the significant contributions made by this study, it has certain

limitations that can be addressed in future research. Given that

women's perceptions of body image and self‐esteem can vary

according to cultural and national factors, it would be interesting

for future research to collect data from women in two or more

countries and compare the results. This will help in advancing

knowledge by showing the similarities and differences in Generation

Z female consumers behavior in various cultures and settings.

Furthermore, future studies can focus on other aspects, such as

how applications supported by augmented reality and artificial

intelligence can provide the youngest generation of consumers with

retail therapy. This is likely to open new avenues for future research

in this area.

Our study focused on text‐based chatbots. Future studies can

focus on voice‐based systems too and analyze their impact on

Generation Z women's self‐esteem, body image, and purchase

behavior. Additionally, future studies can analyze the impact of

voice‐based systems on Generation Z individuals' loneliness and

engagement at different stages of the customer journey. This is an

important area for future research to investigate due to the growing

use of voice‐based systems.

Our findings show that addiction to social media use does not

moderate the impact of body image on self‐esteem. This area is

worthy of further investigation in future research, which can use

analytics to understand the type of content that Generation Z women

can be addicted to on social media. This will enable a better

understanding of the reasons behind their addiction and how it

changes over time.

In addition, this study has some methodological limitations,

including reliance on self‐reported data from participants, the use of a

controlled lab experiment, and the use of purposive sampling, which

has its own limitations. Future studies can collect data using different

and more robust methods and offer more generalizable findings. In

addition, due to the nature of our study, we collected data from

Generation Z women only. Future studies can also collect data from

individuals from different generations, for example comparing the

model using groups from Generations Z, Y, and X. This will help in

obtaining a better understanding of the behavior of different

generations of consumers.

9 | CONCLUSION

This study aimed to determine how Generation Z women's body

image, self‐esteem, and purchase behavior are influenced by various

technologies that are part of the customer journey, namely

augmented reality, chatbots, and social media, and the impact of

brand‐related factors in this context. Our findings show the role of

augmentation in developing body image and self‐esteem among

Generation Z women and in shaping their purchase behavior. In

addition, the findings show that, when the chatbot support type is

classified as “friend,” it can provide both intrinsic and extrinsic

benefits to young female consumers that extend beyond improving

the customer–brand relationship as it relates to their self‐esteem.

Furthermore, our findings show that brand attachment, awareness,

and reputation have a significant impact on Generation Z women's

interactions with cutting‐edge technologies as part of their shopping

experience. However, the findings indicate that brand awareness and

brand reputation affect Generation Z women's purchase behavior.

The study makes a significant contribution by highlighting the impact

of Generation Z female consumers' interactions with various

technologies as part of their shopping journey with beauty brands

on their shopping behavior and psychological well‐being. Future

research can build on our findings to enhance our understanding of

the impact of various technologies that work together as part of the

customer journey and brand‐related factors on Generation Z

women's psychological well‐being in a step towards marketing for a

better world.

2126 | AMEEN ET AL.

CONFLICT OF INTEREST

The authors declare no conflict of interest.

DATA AVAILABILITY STATEMENT

The research data are not shared.

ORCID

Nisreen Ameen http://orcid.org/0000-0002-1794-9103

Jun‐Hwa Cheah http://orcid.org/0000-0001-8440-9564

Satish Kumar http://orcid.org/0000-0001-5200-1476

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SUPPORTING INFORMATION

Additional supporting information can be found online in the

Supporting Information section at the end of this article.

How to cite this article: Ameen, N., Cheah, J.‐H., & Kumar, S.

(2022). It's all part of the customer journey: The impact of

augmented reality, chatbots, and social media on the body

image and self‐esteem of Generation Z female consumers.

Psychology & Marketing, 39, 2110–2129.

https://doi.org/10.1002/mar.21715

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