Buying Intentions for Second-Hand Branded Bags via Facebook

Live-Streaming: E-Servicescape, Consumers' Trust

Virgo Simamora

, Qiven Daud and Khoirunnisa

Universitas 17 Agustus 1945 Jakarta, Indonesia

Keywords: E-Servicescape, Trust, Purchasing Intention, Live-Streaming.

Abstract: The rise of internet penetration has led to increased e-commerce in Indonesia, especially live-streaming

shopping. The purpose of this study is to examine the effect of the e-servicescape on trust and its impact on

purchasing intentions for second-hand branded bags using Facebook live-streaming. The population of this

study consists of an unknown number of people who purchased products through Facebook live-streaming.

Purposive sampling was used in this study to select samples based on the research criteria. The sample should

be a person born between 1980 and 2000 who has made at least one transaction through live-streaming on

Facebook. This study included 100 participants who satisfied the study's requirements as samples. Also, this

study collected data using a questionnaire distributed through social media. The results of this research reveal

that the e-servicescape influences customer trust. In the same way, millennials' intentions to buy second-hand

branded bags through Facebook live-streaming are affected by how much they trust the seller.

1 INTRODUCTION

An increase in people who have access to the internet

has led to a rise in people doing business online.

According to the Bank of Indonesia (2021), the

revenue generated through internet transactions had a

78% growth in 2021 compared to the previous year.

According to Dataindonesia. Id (2020), products

related to fashion and handbags are the most popular

products purchased online. Together, these products

account for 67.2% of all online transactions

conducted in Indonesia. This phenomenon is

evidence of a high level of customers' desire to

purchase products via the internet. According to

Keller and Kotler (2015), the term "buying intention"

refers to the desire of a potential purchaser to

purchase a good or service.

Because there are risks involved in doing business

over the internet, trust is a crucial factor influencing

whether or not a consumer plans to buy a product

online (Pavlou, 2003). According to Kemenkominfo

of Indonesia (2021), 35% of all online transactions in

Indonesia are fraudulent. Financial fraud accounts for

26% of the cases, while non-financial fraud accounts

for 74%. If online transaction fraud occurs often,

https://orcid.org/0000-0001-6452-5090

people may lose trust in doing financial transactions

over the internet. A lack of trust could make it hard to

do business online (Wang et al., 2009).

According to the prior study, e-servicescape is one

factor that influences customer trust (Oebit and Sari,

2018). Furthermore, in an online transaction, e-

servicescape defines as an online environment during

service delivery that affects customers purchasing

intentions (Harris & Goode, 2010). A study

conducted on web-based online buyers by Tankovic

& Benhows2018), shows the impact of servicescape

on how customers view the value offered by vendors.

Additionally, according to Tankovic & Benazic

(2018), the functionality and aesthetics of the e-

servicescape significantly affect the perceptions of

consumers who do business online. Moreover, the

study by (Line and Hanks, 2020) also found the effect

of e-servicescape on consumers' consumption

behaviour in the fast-casual restaurant industry.

The goal of this research is to use Facebook live-

streaming to examine the effect of the e-servicescape

on trust and its impact on the purchase intention of

second-hand and branded bags among millennials.

The findings of this research may provide online

sellers with insight into how to establish a positive

environment via e-servicescape that encourages

Simamora, V., Daud, Q. and Khoirunnisa, .

Buying Intentions for Second-Hand Branded Bags via Facebook Live-Streaming: E-Servicescape, Consumers’ Trust.

DOI: 10.5220/0011979800003582

In Proceedings of the 3rd International Seminar and Call for Paper (ISCP) UTA â

Z45 Jakarta (ISCP UTA’45 Jakarta 2022), pages 275-281

ISBN: 978-989-758-654-5; ISSN: 2828-853X

 2023 by SCITEPRESS – Science and Technology Publications, Lda. Under CC license (CC BY-NC-ND 4.0)

275

millennials' trust, which is critical for online

transactions.

2 LITERATURE REVIEW

2.1 E-Serivescape

Servicescape is a marketing concept that impacts the

visitor's impression of the physical environment in

which a service is provided (Bitner, 1992). As online

transaction volume rises, e-servicescape is increasing

in popularity (Koering, 2003). E- servicescape is a

term used to explain the virtual environment during

delivery service that affects consumers' impressions

(Zeithaml, 2002; Harris and Goode (2010); Lee and

Lee and Jeong, 2012). A study by Tankovic and

Benazic (2018), who ran a web- based survey of

online shoppers, found that consumers' impression of

e-servicescape positively influences perceived e-

shopping value and loyalty.

Numerous studies of e-servicescape led us to

learn that each researcher employs unique indicators

to characterize e-servicescape. For example,

Tankovic and Benazic (2018) describe four indicators

in measuring e-servicescape, including layout and

functionality and financial security, to explain e-

servicescape. In their research, Harris and Goode

(2010) describe the indicators of e-servicescape as

visual appeal, layout, functionality, and financial

stability of the online environment. Furthermore, Lee

and Jeong (2012) employed atmosphere, design, and

social components as indicators to define the e-

servicescape. In this research, indicators used to

measure e-servicescape are atmosphere, design, and

social components developed by Lee & Jeong (2012)

2.2 Trust

Trust is a crucial factor in online transactions.

Conversely, a lack of trust may influence a person's

willingness to buy a product online (Wang et al.,

2009). Trust defines constancy, honesty, fairness,

accountability, helpfulness, and altruism. (Morgan

and Hunt, 1994). According to (Gustianto et al.,

2022), trust explains consumers' understanding and

conclusions about products, qualities, and benefits.

According to Sing and Sirdeshmukh (2000), trust

has two distinct components: credibility and

benevolence. Credibility relates to the idea that the

other party can carry out their responsibilities, while

benevolence refers to the other party's sincerity in

keeping out the terms of the agreement. When one

partner trusts the reliability, stability, and honesty of

the other and when that person's activities are in the

best interests of the other, the relationship is one of

trust. According to Sing and Sirdeshmukh (2000),

trust consists of credibility and benevolence.

Credibility is the belief that the other party can fulfil

their responsibilities, while benevolence refers to the

other party's sincerity in keeping the terms of the

agreement. When one partner believes the other to be

dependable, stable, and honest or when that person's

decision benefits the other, the connection is one of

trust, according to Lewicki and Wiethoff (2000).

Trust is an individual's belief in and willingness to act

based on the words, actions, and decisions of another.

In their research, Lewicki and Wiethoff (2000) used

three indicators of trust, including personality, norms,

and experiences.

Based on the previous discussions, this study

defines trust as the expectation of consumers that

service providers can be relied upon to fulfil their

promises. This research uses the buyer's belief in the

information (Lewicki and Wiethoff, 2000) and the

seller's credibility and benevolence (Sing and

Sirdesmukh, 2000.) as trust indicators.

2.3 Purchasing Intention

Keller and Kotler, 2015) define purchasing intention

as customer behaviour demonstrating the buyer's

desire to buy a product or service. It is a type of

consumer behaviour that develops before purchasing

decisions (Kotler and Armstrong. 2016). For

example, the intention to buy a product develops

based on customers' Evaluation of a product

(Angelita et al., 2021). From a different perspective,

Wulandari & Wijaksana (2021) noted that purchasing

interest starts with a feeling of pleasure toward the

products or services, followed by the belief that the

products or services provide benefits, which

motivates customers to want to pay for these things.

Moreover, Nulufi and Murwartiningsih (2018)

stated that purchasing intention arises when

customers have a favourable view of a product

because they perceive it to be valuable. Roozy et al.

(2014) define consumer purchasing intention as a

consumer's positive perception of a product and their

desire and willingness to recommend it to others.

Many factors influence consumer purchasing

intention, such as product features, brand name, social

influence and cost to buy a product (Rahim et al.,

2016). As each customer has different tastes and

preferences, the factors that impact consumer

purchasing intentions also differ.

There are multiple indicators used to describe

purchasing intention. (Kotler and Amstrong (2016)

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developed three purchasing intention indicators:

seeking further product information, the intent to

purchase, and the intent to repurchase. Abzari et al.

(2014) employ three indicators to describe purchasing

interest: transactional interest, referential interest,

preferential interest, and exploratory interest. Finally,

Roozy et al. (2014) use two indicators to describe

purchasing intention: the consumer's positive

perception of the product and the desire to acquire it

and the possibility of recommending it to others.

Based on the discussion above, in this research,

purchasing intention describes consumer behaviour

that emerges following product evaluation and

eventually results in a desire to purchase the product.

Indicators of buying intent include eagerness to learn

more about the product, seeking further information,

the desire to purchase the product, and the possibility

of recommending it to others.

2.4 Hypothesis

The effect of service escape on trust

A prior study by Kurniawati and Yaakop (2020)

showed that e-servicescape positively and

significantly affects customers' trust to buy products

through Tokopedia. Similarly, Oebit and Sari (2018)

found that the e-servicescape influences trust to use

the GO-FOOD delivery service. Lastly, a study by

Aprianti and Rachmawati (2020) revealed that e-

servicescape influences customers' trust to buy

products through Grab Food Delivery Service.

Based on the prior research discussed above, this

study proposes the following hypothesis:

H1: E-servicescape affects millennials' purchasing

intentions to buy second-hand branded bags through

live-streaming on Facebook among millennials.

The effect of trust on purchasing intention

The study of Ling et al. (2010) on online

transactions among undergraduate information

technology students in Malaysia explains that online

trust positively affects purchase intentions when other

variables are considered. Furthermore, Ha et al.

(2019) study reveals that trust impacts online

shopping intention among online buyers in

Vietnamese. Furthermore, Li et al. (2007) also found

the effect of trust on purchasing intention among

internet shoppers in China.

Based on the prior research discussed above, this

study proposes the following hypothesis:

H1: Trust affects millennials' intentions to buy

second-hand branded bag products through live-

streaming on Facebook.

3 METHODS

This study aims to examine the effect of e-

servicescape on trust and its impact on millennials'

purchasing intentions for second-hand branded bags.

The population of this study consists of an unknown

number of millennials who have ever made a

transaction using Facebook live-streaming. This

study employs purposive sampling to select samples

based on the criteria used in this study. The sample

should be a person born between 1980 and 2000 who

has made at least one transaction through live-

streaming on Facebook. Using the formula of

Lemeshow, the number of samples used in this

research is 100, higher than 96, the minimum number

according to Lemeshow. All the samples were

millennials and fulfilled the criteria applied in this

research. The data collection technique used is a

questionnaire distributed through social media. The

Likert scale, which assigns each answer a value

between 1 and 5 (five), is used to evaluate the

opinions of respondents.

4 RESULTS AND DISCUSSION

4.1 The Respondent Profile

A hundred millennials have participated in this

research. Based on this research, most respondents

are male (70%), followed by females (30%).

Furthermore, based on their education, most of them

hold a diploma certificate (46%), followed by high

school graduates (45%), and university graduates

(9%), with a certificate diploma (23.8%). (See table

1.)

Based on their profile, all the respondents are

millennials who are eligible to be a primary data

source, which is collected using a questionnaire (See

table 1.)

4.2 The Evaluation of the

Measurement Model

The validity and reliability tests are employed to

assess the measurement model in this research. As all

of the indicators in this research are reflective

indicators, convergent validity and discriminant

validity are used to evaluate the validity. At the same

time, Conbrach's alpha and composite reliability are

employed to assess the reliability.

Buying Intentions for Second-Hand Branded Bags via Facebook Live-Streaming: E-Servicescape, Consumers’ Trust

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Table 1: Respondents' Profile.

Indicators Number Percentage

Gender

- Male 70 70%

- Female

30 30%

Pendidikan

- High School

45 45%

- Diploma 46 46%

- Bachelor of

higher

9 9%

Professions

- Student

9 9%

- Entrepreneur

11 11%

- Employee 65 65%

- Housewives 15 15%

Source: Processed Data (2022)

The convergent validity is examined by testing the

loading factor and the extracted average variance

(AVE). If the loading factor is greater than 0.70 and

the average variance extracted (AVE) is higher than

0.50, then the convergent validity test is considered to

have been successfully satisfied. (Ghozali and Laten,

2015). This study founds that all the value of loading

factors is greater than 0.70 (See figure 1), and all the

AVE value is greater than 0.5. (See table 2). This

result indicates that this research has fulfilled the

convergent validity requriment.

Figure 1. Path Analysis Model.

Table 2: The Value of AVE.

AVE

PI 0,770

SE 0,897

T 0,959

Source: Processed Data (2022).

The validity test continued by using the value of

cross-loading, the square root of AVE, and the

Fornell-Larcker criterion as parameters for a

discriminant validity test (Chin, 2010). Ghozali and

Laten (2015) state that to fulfil the discriminant

validity requirements, the value of each item on the

construct is higher than cross-loading, and the square

root of the AVE of each construct is greater than the

correlation of the latent construct (Fornell-Larcker

criteria).

Table 3. Cross Loading.

PI SE T

P11

0,887 0,745 0,737

P12

0,865 0,685 0,710

PI3

0,881 0,751 0,829

SE1

0,728 0,940 0,793

SE2

0,795 0,963 0,835

SE3

0,831 0,938 0,856

0,823

0,848 0,970

0,848 0,858 0,970

0,879

0,875 0,998

Source: Processed Data (2022).

Table 3 shows that the loading value of each item on

the construct is greater than the value of cross-

Additionally, the square root of AVE for each

construct exceeds the correlation between latent

constructs (See table 4), meaning that discriminant

validity in this research has been fulfilled. As the

convergent and discriminant validity has been

fulfilled, it suggests that the measuring model

employed in this study is valid.

Evaluating the measurement model continued to

test the reliability of the measurement instrument by

using CConbrach'salpha and composite reliability.

However, according to Ghozali and Laten (2015), the

minimal value of CConbrach'salpha and composite

reliability to fulfil reliability requirements is greater

than 0.70.

Table 4: The Fornell Larcker Criterion.

PI SE T

0,878

0,830

0,947

0,868 0,879

0,945

Source: Processed Data (2022).

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Table 5: Conbrach's Alpha and Composite Reliability.

CConbrach's

Alpha

Composite Reliability

PI 0,851 0,910

SE 0,943 0,963

T 0,979 0,986

Source: Processed Data (2022).

Based on table 5, the measurement model used in this

study is reliable because each construct has a

CCronbach'salpha value, and the composite

reliability value is greater than 0.70.

4.3 The Evaluation of the Structural

Model

An inner model is a structural model that predicts

causal relationships between variables or factors that

cannot be measured directly. Structural model

evaluations were performed to examine the

relationship between latent constructs. The

parameters used to evaluate the structural models are

R2 and the path coefficient.

Based on the results, the R

found in this study are

as follows:

Table 6: R

and R

Adjusted.

Adjusted

PI 0,754 0,751

T 0,772 0,769

Source: Processed Data (2022).

represents the coefficient of determination for the

endogenous construct. Based on the strength of the

relationship, R

may vary from 0.67 (very strong) to

0.33 (moderate) to 0.19 (weak), as stated by Chin

(2010), According to this research, the R2 value of e-

servicescape on trust is 0.772, and the R2 value of

trust on purchase intent is 0.754. (See table. 7.) Both

R square values are higher than 0.600, indicating a

strong connection between e-servicescape and trust

and between trust and purchase intentions.

Based on the results, the path coefficient between

e-servicescape (SE) and purchasing intention (PI) is

0.879 with p-values of 0.0000 < 0.05 (See table 7.),

meaning there is a significant relationship between e-

servicescape and purchasing intention. Also, the path

coefficient of correlation between trust (T) and

purchasing intention (PI) is 0,868 with a p-value of

0.0000 < 0.05 (See table 6.), meaning there is a

significant relationship between Trust and purchasing

intention.

Table 7: Path Coefficient.

Original

Sample O)

T -

Statistics

P-

Values

SE -> T 0,879 24,234 0,000

T -> PI 0,868 223,881 0,000

Hypothesis Testing

The results of this study support the first hypothesis

as e-servicescape (SE) affects trust (T) in buying

second-hand and branded bags through Facebook

Live-streaming. Likewise, this study supports the

second hypothesis as trust significantly influences

purchase intention (PI) buying second-hand branded

bags through Facebook live-streaming

Discussions

This research reveals the effect of e- servicescape

(SE) on millennials' trust (T) to buy second-hand

branded bags through Facebook live- streaming.

These findings are consistent with those of previous

studies by Oebit and Sari (2018), Kurniawati and

Yaakop (2020), and Aprianti and Rachmawati

(2020), which indicate that consumers feel confident

about purchasing products online when the virtual

environment can create consumers positive

impression. It means that e-servicescape is essential

in increasing consumer confidence to buy second-

hand branded bags online. Also, the results of this

research found that there is an impact of trust on

purchasing intentions. The findings of this study

support the previous studies that found the effect of

trust on customers purchasing intentions ( Ling et al.,

2010; Ha et al., 2019) ; (Li, 2007)

According to this study, e-servicescape is a virtual

environment that increases millennials' trust in

purchasing second-hand branded bags through

Facebook live Streamistreamingdition, and a

consumer-positivity view arose because millennials

were impressed by the virtual atmosphere created by

the seller during the live Streamistreamingimpression

makes consumers perceive that the vendor promotes

valued and high-quality products (GUSTIANTO et

al., 2022)

Trust is crucial as buyers and sellers face a high

risk when transacting online (Pavlou, 2003). In

Indonesia, the high rate of fraud, reaching 35% of

total transactions, explains that online transactions are

Buying Intentions for Second-Hand Branded Bags via Facebook Live-Streaming: E-Servicescape, Consumers’ Trust

279

fraudulent. The frequency with which online

transaction fraud occurs may affect people's trust in

conducting financial transactions over the internet. A

lack of trust may negatively impact online

transactions. A lack of trust could make it hard to do

business online (Wang et al., 2009)

5 CONCLUSION

According to the results of this study, e- servicescape

is a significant determinant of increasing consumers'

trust among millennials in buying online. Likewise,

this study also found the effect of trust on millennials

purchasing intentions. Therefore, based on this study,

online sellers need to build millennials'

trust to increase consumer intention to buy second-

hand branded bags through live-streaming. In this

research, creating an e-servicescape may provide a

solution to increase millennial's trust that impacts

their intention to buy second-hand branded bags

through Facebook live-streaming

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