The New Retail Business Model and Customer Experience: A Case

Study on a Coffee Shop Retail

Dera Thorfiani

and Noneng Nurjanah

D4 Manajemen Perusahaan, Politeknik Pos Indonesia, Jl. Sariasih No. 54, Bandung, Indonesia

D3 Administrasi Logistik, Politeknik Pos Indonesia, Jl. Sariasih No. 54, Bandung, Indonesia

Keywords: New Retail, Customer Experience, Online-offline channel.

Abstract: Business model innovation is becoming substantial to survive in a dynamic environment. However, the

innovation can not stand alone. Customer behaviour is one of the variables that a company should consider

when creates a business model innovation. A new business model called new retail (NRBM) is invented to

adapt to the digital transformation. The study aims to measures the new retail business model factors: customer,

Convenience, cost, communication, and context or distribution channels that could affect consumer

experience: sensory experience, emotional experience, and social experience. The quantitative approach: The

structural Equation Model (SEM) and the Smart PLS application are used to obtain the data and measure the

impact of the independent variable on the dependent variable. The population in this study is Starbucks

consumers who have used all online-offline channels and are domiciled in Bandung. Based on data analysis,

NRBM and customer experience variables are in the excellent category. It can be proven that NRBM has a

positive impact on customer experience when shopping at a coffee shop. Future research can expand the area,

involve other retail sectors, and add additional variables that could contribute different results, such as

environmental factors and other consumer behaviour variables.

1 INTRODUCTION

The traditional retail industry is one of the industries

most affected by the growth of e-commerce. It

changes customer behaviour from conventional

transactions to online shopping (Laudon & Traver,

2016). The development of e-commerce in Indonesia,

which is projected to reach 75.3% of the total

population of the selected market in 2023 (Katadata,

2019), impacts decreasing the use of conventional

mall space. For example, in Jakarta, the decline

reached 10% to 20% in 2018 (Ekarina, 2018). There

are some benefits of online shopping causing a

decrease in traditional shopping; a wider variety of

products, ease of making product comparisons, lower

prices than in stores or physical malls, and regular

shopping easiness(Helm et al., 2020). Technological

developments, starting from industry 1.0 to industry

4.0, where Information and Communication

Technology (ICT) is the key in e-commerce

innovation and growth, are among the main factors

causing significant changes in human life, including

buying and selling transactions (Amiri & Woodside,

2017).

Based on the trends, the retail business needs to

change the concept to survive by changing the

business model. Several new concepts have been

successfully applied in some countries such as

Thailand, combining retail stores with tourists or

Singapore; opening a retail store between offices and

settlements (Ekarina, 2018). The same thing is also

crucial for the coffee shop retail industry, one of

which is Starbucks, the largest retail coffee shop

globally. Starbucks itself has been able to predict this.

Therefore in 2019, it has started the concept of a new

business model that will support its business growth.

This business model is called “new retail.” This retail

coffee shop has more than 3000 outlets worldwide

and is experimenting with different types of stores,

whether it’s a physical store with a new concept such

as the Starbucks Roasteries Premium outlet and other

smaller outlets. In addition, there is also application

development and the improvement of payment

methods that have existed since 2011. Starbucks

continues to improve the appearance of its digital

store to provide a better experience for consumers

(Bhattacharyya, 2019).

Thorﬁani, D. and Nurjanah, N.

The New Retail Business Model and Customer Experience: A Case Study on a Coffee Shop Retail.

DOI: 10.5220/0010860100003255

In Proceedings of the 3rd International Conference on Applied Economics and Social Science (ICAESS 2021), pages 227-235

ISBN: 978-989-758-605-7

227

Starbucks merchants are also available in online

motorcycle taxi service providers in Indonesia, both

GoFood and GrabFood. Due to the dynamic

environment, the company must be able to innovate.

For the retail industry, especially coffee shops, this is

crucial because the changes in this industry are

speedy (Ferreira & Ferreira, 2018). The “new retail”

business model itself is defined as a business model

that aims to combine online and offline shopping

channels to reduce the weaknesses in both

distribution channels and improve the consumer

experience in shopping (Starbucks, 2018). New retail

is a consumer-oriented pattern and pays more

attention to consumers by reconstructing the

relationship between customers, goods, and

marketing contexts and focusing on four primary

indicators: Customer, Convenience, Cost, and

Communication plus Context or distribution

channels, types of goods, and technology support

(Zhang et al., 2018). Meanwhile, indicators on

customer experience consist of sensory experience,

emotional experience, and social experience

(Nasermoadeli et al., 2013).

Furthermore, The study will examine the key

variables imperative for the success of innovative

business models, specifically, the impact of the new

retail business model and e-commerce ecosystem on

customer experience with the case study Starbuck

Coffee Outlets in Bandung. The research findings

will broaden the understanding of new retail business

models and customer experience.

1.1 Significances of the Study

The study of the new retail business model is still

rarely found in Indonesia. This research initial the

study of the new retail business model in Indonesia,

especially in Bandung. This research is expected to

contribute to the innovation and utilisation of

information and communication technology, where

integrated online-offline has become necessary to

survive and adapt to digital transformation nationally

and globally. Furthermore, it could support

enterprises to formulate the best strategies and

business models related to digital transformation and

online-offline channels to maintain customer

satisfaction, which can also indirectly affect

economic growth in Indonesia.

2 LITERATURE REVIEW

2.1 The New Retail Business Model

(NRBM)

Business model issues have been widely associated

with the environment. Safar et al. (2018) examine

enterprises applying business models suitable to the

Industry 4.0 environment and should be designed and

executed in a specific dynamic environment

(Osterwalder et al., 2011). The former research finds

how the environment affects an enterprise’s business

model. Thus, it has not been discovered how business

models impact customer experience. Clauss et al.

(2019) find an association between business model

innovation and customer satisfaction. Yet, it does not

examine customer experience in the study.

Technology acts as a determinant, stimulating the

e-commerce emergence, business model innovation,

and industry ecosystem (Maria & Widayati, 2020;

Safar et al., 2020). Technology development is

changing business and shifting traditional commerce

into e-commerce (Bhat et al., 2016; Laudon & Traver,

2016). Alibaba has implemented a business model

innovation named a new retail business model

(NRBM) in response to those issues. New retail is a

concept first proposed by Jack Ma, founder of

Alibaba Group, in 2016; it is an innovative business

model that combines online and offline (O2O)

shopping experiences (Alibaba Group, 2018), which

will help retail stores adapt to the digital era.

However, another opinion states that the new retail

concept is not 100% unique because the British

Department Store has already implemented

omnichannel innovation. Nike has also opened a

flagship store, using data-driven hybrid

digital/physical technology and connected to the Nike

App to improve customer satisfaction (Bird, 2018).

Although it is not 100% new, the widespread and

concurrent use of the concept in the Alibaba Group is

an essential part of the return to traditional retail

business with the support of digitalisation. This

opinion aligns with Zhang, Liang, and Yin (2018),

which states that “new retail” requires technological

assistance. Although a theoretical definition of “new

retail” does not yet exist, it can be defined as “Modes

of retail that is centred on consumers by relying on

advanced technology; Big Data and Artificial

Intelligence to improve production, circulation and

sales processes in the retail ecosystem.” Zhang,

Liang, and Yin also state that there are four main

components in the new retail business model, which

includes the 4Cs theory: Customer, Cost,

Convenience, and Communication plus Context

ICAESS 2021 - The International Conference on Applied Economics and Social Science

228

(distribution channels), types of goods, where New

retail is a pattern that is more consumer-oriented and

pays attention to and reconstructs the relationship

between customers, interests, and the marketing

context.

2.1.1 Customer

Customer is the core of marketing. The company

must understand and be able to create value that suits

the customers’ needs. The needs recognition is highly

dependent on Big Data and AI technologies, helping

identify consumer needs based on experiences from

various physical and digital interaction channels. It

makes marketing strategies more specific and

personalised because they are tailored to the character

and customers’ needs.

2.1.2 Cost

The cost consists of the production costs and includes

other sacrifices: time, effort, and other expenses. A

reasonable psychological price is more important

than making high profits. One of the advantages of

online shopping that physical retail stores do not have

is the lower prices and the ability to compare various

prices offered by sellers (Alwafi & Magnadi, 2016).

With the integration of O2O, production costs are

expected to be cheaper and reduce consumer concerns

about price differences between online and offline

channels. In this situation, technology allows

companies to obtain buyer response data for a price,

adjusts the price to the consumer’s character, and

plays a role in the logistics process.

2.1.3 Convenience

Convenience includes improving the consumer

experience from pre-sales, sales, and after-sales

service on every O2O channel. The transaction

process is adjusted to the consumer’s lifestyle to

make consumers feel the company’s added value,

such as selection of marketing channels, delivery of

goods, and payment types. Technologies such as Big

Data, cloud computing, and AI help companies

formulate the most appropriate types of products and

services so that consumers can experience more

valuable experiences.

2.2.4 Communication

Effective two-way communication and focus on

consumers are crucial in the new retail business

model. In the internet era, communication can be

carried out in two directions, delivered personally,

and reaches an extensive range of consumers.

2.2.5 Context

The new retail business model involves various sales

channels, physical stores and digital channels such as

website applications and even other distribution

channels outside the company to reach a wider

consumer group.

2.2.6 Product

In the new retail business model, products and

services are made based on consumer demand.

Therefore, the types of products sold will be more

varied because they are tailored to the needs and

desires of consumers personally.

2.2.5 Technology

In the new retail business model, technology is used

to support business processes and determine

strategies. There are some crucial technologies in the

new retail business model: Big Data, including data

collection, processing, storage, application, and

analysis; cloud computing, processing, and managing

data (SIS Binus, 2016); Artificial Intelligence,

supporting in product personalisation, recognition of

consumer needs; Internet of Things (IoT), logistics

processes, supply chain management, and inventory;

and mobile payments, including NFC, biometrics,

and e-wallet that make it easier for consumers to

make payments.

2.2 Customer Experience

Positive consumer experiences when consuming the

product can build a positive image for the company

and increase the chances of consumers becoming

loyal customers. Previous research stated that to

generate, strengthen and maintain customer loyalty,

companies must understand the concept of customer

experience and apply it systematically (Mascarenhas

et al., 2006).

Nasermoadeli et al. (2013) examine that consumer

experience can be measured through three

dimensions: sensory experience, aesthetic and

sensory perception of the shopping environment,

atmosphere, products and services that involve the

human senses; emotional experience, the moods, and

emotions that develop during the shopping process

and social experience, relationships with other

people, have a social impact and can influence the

thoughts, feelings, and activities of consumers. Based

The New Retail Business Model and Customer Experience: A Case Study on a Coffee Shop Retail

229

on the study of Bilgihan et al. (2016), several factors

that could affect consumer experience when shopping

online include ease of accessing and using the web,

Hedonic and Utilitarian Features, Convenience,

personalisation, social interaction, and compatibility

on various devices. Thorfiani et al. (2021) also find

that e-commerce technology and platform could

affect the customer experience as well.

This study aims to determine how NRBM affects

customer experience when shopping at Starbucks

coffee shop sales channels. The explanation can be

described in the following framework:

Figure 1: Research Model

The objective of the study is to identify business

model innovation: the new retail business model

(NRBM) and how it affects the customer experience.

There will be research questions as follows:

What is the impact of the NRBM on customer

experience?

This study focuses on the relationship between the

new retail business model (x) and customer

experience (y) variables. In former research, the

NRBM variable was only analysed descriptively. It

had not been linked to other variables (Zhang et al.,

2018), while the customer experience variable in

previous studies was associated with the shopping

interest variable (Nasermoadeli et al., 2013). This

study examines how the relationship and the effect of

new retail variables on customer experience with the

following research hypotheses:

a. H

: The NRBM has a positive and significant

effect on customer experience

b. H

: The NRBM does not have a positive and

significant effect on customer experience

3 RESEARCH METHODOLOGY

The quantitative method is used to obtain the data and

measure the impact of the independent variable on the

dependent variable. The research population in this

study is Starbucks consumers who have used all sales

channels (online-offline) and domiciled in Bandung

(unknown population). The data analysis method uses

PLS-SEM, the 10 (ten) Times Rule is referred to as a

guide in determining the research sample size

(Astuty, 2018; Hair Jr. et al., 2014, 2016), where there

is one arrow that points to the latent variable in the

PLS pathway model. Based on the structural path in

the research model, the minimum sample obtains ten

times the largest number of formative indicators used

to measure one construct (10 x 1), so it can be

determined that the minimum sample size is ten

samples. Because it uses the student version of smart

PLS, the maximum number of samples that can be

done is 100 respondents.

The data collection obtains the e-questionnaire

method to make it easy and fast (Sekaran & Bougie,

2016) with a semantic differential scale and simple

random sampling method; to measure feelings about

something (Sugiyono, 2018), and literature study.

The relationship and influence between each

variable are analysed by the Structural Equation

Model (SEM) and the Smart PLS application (Hair Jr.

et al., 2014). SEM can be considered a unique

combination because SEM’s foundation lies in two

standard multivariate methods: factor analysis and

multiple regression analysis(Hair Jr. et al., 2014). Six

stages of SEM are: 1) Defining individual construct,

2) Develop and specify measurement model, 3)

Designing a study to produce an empirical result, 4)

Assessing measurement model validity, 5) Specify

structural model, and 6) Assess structural model

validity. Initial validity is tested by counting the t

value, valid if t value > t table. Based on the data

calculation, t value > 0.361 (t table), . The reliability

is tested using the method of consistency between

questionnaire items. Cronbach’s alpha value is

reliable if r > 0.6, and it is obtained that rx=0.837 and

ry=0.885 which means r>0.6. The initial validity and

reliability are calculated using SPSS 20 (Sugiyono,

2018). Hypothesis testing and the causal relationship

analysis between variables are carried out by

analysing the full model structural test. The results of

the measurement model are analysed by taking into

account the following rule of thumb:

ICAESS 2021 - The International Conference on Applied Economics and Social Science

230

Table 1: The rule of thumb of the reflective measurement

model evaluations

Validity &

Reliabilit

Parameters Rule of Thumb

Convergent

Validity

Indicator’

s Outer

Loadin

>0.78

Average

Variance

Extracte

>0.50

Discriminan

Validity

Cross

Outer loading indicator

on a construct > all

cross-loading values

with other constructs

Akar

Kuadrat

AVE and

correlations

between

constructs

latent

Square of correlation

between latent

constructs < AVE of

each related construct,

or the square root of

AVE > correlation

between latent

constructs

Internal

Consistency

Realibility

Cronbrach's

Alpha

> 0,70 for

confirmatory research,

and > 0,60 still

acceptable for

lorator

research

Composite

Reliability

> 0,708 for

confirmatory

research, and 0,60-

0,70 still acceptable

lorator

research

Table 2: The rule of thumb of structural models

evaluations

4 RESULT AND ANALYSIS

Based on the results of the e-questionnaire, out of 107

respondents, only 71 met the respondents’ criteria: 1)

Customer has an experience of transaction in

Strabucks’s online and offline sales channels, and

domiciled in Bandung. The other 36 did not meet one

or more of the respondents’ criteria. The following is

the profile of the respondents based on the results of

the questionnaire:

Table 3: Profil of Respondents

Profile Persentase

Occupation

Teacher/Lecturer 38.03%

Privat Employee 16.90%

Student 25.35%

Freelancer 2.82%

Public Servant 1.41%

Entepreneur 8.45%

Unemployee 1.41%

Others 5.63%

Age

< 20 y.o 7.04%

20-30 y.o 36.62%

30-40 y.o 43.66%

40-50 y.o 4.23%

>50 y.o 8.45%

Domicili

Bandung 67.61%

West Bandung 4.23%

Cimahi 7.04%

Bekasi 2.82%

Jakarta 2.82%

Others 15.49%

Gender

Women 50.7%

Men 49.3%

Monthly Income

<Rp 3.000.000,- 29.58%

Rp 3.000.000,- sd Rp 5.000.000,- 14.08%

Rp 5.000.000,- sd Rp 10.000.000,- 40.85%

>Rp 10.000.000,- 15.49%

Buying Frecuency/month

< 3 83.10%

3 -5 14.08%

> 5 2.82%

Offline Channel

Coffee Houses 39.4%

Stores 71.8%

Outlets 38%

Online Channel

Starbuck Mobile App 19.7%

Criterion Rule of Thumb

R-Square

0,67, 0,33, and 0,19

(

substantial, moderate, weak

)

0,75, 0,50, and 0,25

(substantial, moderate, weak)

Effect Size f

0,02, 0,15, dan 0,35

(

small, medium, and lar

)

predictive

relevance

> 0, a value greater than zer

indicates that models have

redictive relevance

< 0, a value smaller than

zero indicates that models

have less predictive

relevance

predictive

relevance

0,02, 0,15, dan 0,35

(

small, medium, and lar

)

Significance

(two-tailed)

t-value 1.65 (significance

level = 10%)

t-value 1.96 (significance

level = 5 %

)

t-value 2.58 (significance

level = 1 %

)

The New Retail Business Model and Customer Experience: A Case Study on a Coffee Shop Retail

231

Profile Persentase

GoFood 64.8%

GrabFood 53.5%

The following questions are related to the NRBM

variable indicators.

Table 4: Profil of Respondents

Questions Persentase

There is a price difference

between online and offline

channels

Agree 78.87%

Disagree 21.13%

Delivery cost is affordable

Agree 84.51%

Disagree 15.49%

Purchasing Decession 8.45%

Anytime 32.39%

Based on the needs 67.61%

Various payment methods

Agree 100.00%

Disagree 0.00%

Based on the displayed information, 78.87% of

respondents agree that there is a price difference

between online and offline channels. According to the

observation in various Starbucks sales channels, the

author finds that the online price is higher than the

actual price. This finding does not suit Alawi &

Magnadi (2016), who states that the products usually

have a lower price while being sold online. This

phenomenon does not only happened in Starbucks but

also in other food and beverage businesses. The

NRBM itself purposes to uniform the price both in the

online and offline channels. Therefore, in this case,

the enterprise should design new strategies to address

this issue.

Moreover, most respondents agree that the

shipping cost is affordable (84.51%). This result

aligns with Zhang et al. (2018) study, which finds that

production costs are expected to be cheaper and

reduce consumer concerns about price differences

between online and offline channels with the

integration of O2O. Furthermore, the data presents

that 67.61% of customers purchase the product based

on their customer needs. With the support of AI and

Big Data technology in the NRBM, the products will

be made more specific and personalised because they

are tailored to the character and customers’ needs

(Zhang et al., 2018).

Last, 100% of respondents agree that Starbucks

has various payment methods. Mobile payments,

including NFC, biometrics, and e-wallet, make

customers easier in payments transactions.

Smart PLS student version is applied to analyse

the impact of The NRBM on customer experience.

Based on the calculation, the AVE value is above

0.500 in the first calculation. The following is an

image of the model:

Figure 2: Full model construct

Based on the calculation results obtained AVE>0,500

and Cronbach's alpha value>0,700 which can be seen

in the following table:

Table 5: Average Variance Extracted Full Model

ronbach'

Alpha

Rho_A

Composite

Realibility

Average

Variance

Extracted

(AVE)

Customer

Experience

0,928 0,930 0,938 0,505

NRBM 0,831 0,834 0,876 0,541

Based on the result, the data can be used to

calculate the relationship and influence of each

variable in this study: The NRBM and customer

experience variables because they are valid and

reliable. So, all indicators can be declared to meet

convergent validity. Then, based on the results of data

processing, the results of the structural model analysis

are as follows:

Figure 3: Model substructure

ICAESS 2021 - The International Conference on Applied Economics and Social Science

232

Table 6: Mean, Standard Deviation, T Statistics, and P

Values

Original

Sample

(O)

Sampl

Mean

(M)

tandar

eviatio

(

STDEV

)

Statistics

(O/STD

Valu

he NRBM

Customer

erience

0.753 0.766 0.069 10.958

0.00

Table 7: Total effect between variables

Customer

erience

The NRBM

ustomer Ex

erience

he NRBM 0.753

The test results on the full structural model show

that:

a. The NRBM variable has a positive and significant

effect on the customer experience variable, as

evidenced by the Tstat value of 10.958 (> 1.650)

and the significance of the p-value of 0.000

(<0.05), meaning that the NRBM variable can

raise the customer experience variable of 75.3%.

b. The total effect of the NRBM on customer

experience is 0.753, meaning that the NRBM

variable has a total impact of 75.3% on the

customer experience variables.

Based on the strength test of the structural model,

the following results were obtained:

a. According to (Hair Jr. et al., 2016), the R

values

of 0.567 and 0.560 indicate that the influence of

the model is in the moderate category. The

impact of the NRBM on the customer experience

variable is based on R 56.7%. Thus, variations in

customer experience variables can be explained

by the NRBM variable by 56.7%.

Table 8: R square value

R. Square R Square Adjusted

Customer

Experience

0.567 0.560

b. The effect size value in the structural model f

1.307, meaning that the predictor of the NRBM

variable has a significant effect to predict the

emergence of customer experience. The result

matches with the finding of Hair Jr. et al. (2016),

who states that if the effect size f

value of the

rule of thumb (inner model) is stated:

small=0.02, medium = 0.15, and large = 0.35

Table 9: F

value

Customer

Experience

The

NRBM

Customer Experience

The NRBM 1.307

Based on the results of the full structural model

analysis (inner model), the answers to the hypotheses

proposed in this study has been proved that there is a

positive and significant influence between the

variables of the NRBM on the level of customer

experience, which is 75.3% (path coefficient value).

When viewed from the significance of the effect, it is

still in the significant category because of the P-value

<0.05.

Based on the results, it is concluded that H

accepted and Ho is rejected, meaning that NRBM has

a positive and significant effect on customer

experience.

5 DISCUSSION

The new retail business model (NRBM) is the

innovation of a business model which integrates

online and offline channels and includes technology

to improve customer experience (Zhang et al., 2018).

Based on the data analysis, most respondents agree

that NRBM improves customer experience during the

transaction. NRBM, which integrated online and

offline channels, can reduce the drawbacks of each

channel and escalate the customer experience. The

integration of each channel could not have happened

without the support of the technology. Therefore, the

role of technology is crucial in the business model

innovation. Technology such as big data, artificial

intelligence, and the Internet of Things help the

corporate increase customer experience. With the

help of technology, they can order their product in

various channels based on their needs and do the

transaction easily anytime and anywhere.

Moreover, there is also a positive response of

custoner experience, including sensory experience,

emotional experience, and social experience.

Customer experience in offline channels (Coffee

house, stores, and outlets) helps the customer

minimize the limitation in the online transaction. For

instance, the customer has already tested the product

before they execute the online trades and the

company also provides equal service in both online

and offline channels. Therefore, this situation helps

customer to improve their experience through each

channel.

The New Retail Business Model and Customer Experience: A Case Study on a Coffee Shop Retail

233

6 CONCLUSION

In the new retail business model variable, the results

of the score recapitulation show a positive response

to the NRBM dimensions: Customer, Cost,

Convenience, and Communication plus Context

(distribution channels). The study proves that NRBM

is in line with consumer expectations.

For the customer experience variable, the sensory

experience and emotional experience dimensions

show a positive response. However, for the social

experience dimension, the answers vary. This study

proves that social position is no longer the main

priority for some people.

Based on the research analysis of “The New Retail

Business Model and Customer Experience: A Case

Study of Starbucks Coffee Outlets in Bandung”, it can

be concluded that the NRBM variable has a positive

and significant effect on customer experience.

The business model innovation that has been

carried out, namely NRBM, has proven to be able to

improve the consumer experience. However, there

are several weaknesses, namely the implementation

of NRBM, which requires technology to support the

implementation, which is still a little difficult for

companies that are not yet Seattle and because of the

unevenness of infrastructure. Other variables such as

macro and micro environments can be added to

deepen consumer experience analysis further and

determine customer satisfaction in making

transactions.

Based on the research analysis of “The New Retail

Business Model and Customer Experience: A Case

Study of Starbucks Coffee Outlets in Bandung”, it can

be concluded that the NRBM variable has a positive

and significant effect on customer experience.

ACKNOWLEDGEMENTS

The authors would like to thank The Ministry of

Education, Culture, Research and Technology as the

funder of this research and Pos Indonesia

Polytechnic, which has supported the conduction of

the study.

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