Impact of corporate social responsibility on customer loyalty behaviors: evidence from Vietnam

Bạn đang xem bản rút gọn của tài liệu. Xem và tải ngay bản đầy đủ của tài liệu tại đây (1.26 MB, 102 trang )

(1)<div class='page_container' data-page=1>

VIETNAM NATIONAL UNIVERSITY, HANOI 
VIETNAM JAPAN UNIVERSITY

---

NGO THANH THANH HUYEN

IMPACT OF CORPORATE SOCIAL

RESPONSIBILITY ON CUSTOMER

LOYALTY BEHAVIORS: EVIDENCE

FROM VIETNAM

MASTER'S THESIS

BUSINESS ADMINISTRATION

</div>
(2)<div class='page_container' data-page=2>

VIETNAM NATIONAL UNIVERSITY, HANOI 
VIETNAM JAPAN UNIVERSITY

---

NGO THANH THANH HUYEN

IMPACT OF CORPORATE SOCIAL

RESPONSIBILITY ON CUSTOMER

LOYALTY BEHAVIORS: EVIDENCE

FROM VIETNAM

MAJOR: BUSINESS ADMINISTRATION

CODE: 8340101.1

RESEARCH SUPERVISORS: 
Prof. TOHRU INOUE 
Dr. TRAN THI BICH HANH

</div>
(3)<div class='page_container' data-page=3>

ACKNOWLEDGEMENT

To finish the process of researching and complete this graduation project, there are no
words to express my gratitude to Professor. Tohru Inoue and Dr. Tran Thi Bich Hanh
who accompanied me and guided me directly during this time. Thank you for not
hesitating to help me a lot, from topic suggestions to how to do the topic even though
you are very busy with your task. Without your help, I could not to get very useful advice
and could not go in the right direction. I would like to choose this moment in order to
acknowledge their contribution gratefully.

On this occasion, I am very impatient for showing my appreciation to all staffs at
Vietnam Japan University- Vietnam National University in particular for creating
conditions and time for me during the course. Especially, I am extremely grateful to Mrs.
Nguyen Thi Huong for giving me needed information and answered all my questions
during the period of working on this project.

Besides, my family, relatives and friends are very worthy to receive thanks from the
bottom of my heart for always stood by and encouraged me to finish the graduation thesis
and all participants who help me complete my survey.

Lastly, I am so grateful for great learning environment and opportunities that Vietnam
Japan University and Yokohama National University have brought for me. Thanks to
these, I have improved myself a lot.

Sincerely,

</div>
(4)<div class='page_container' data-page=4>

ABSTRACT

</div>
(5)<div class='page_container' data-page=5>

TABLE OF CONTENTS

CHAPTER 1: INTRODUCTION ... 1

1.1. Background and necessary of the research ... 1

1.2. The research objectives ... 3

1.3. Research questions ... 3

1.4. Research scope ... 3

1.5. Research structure ... 4

CHAPTER 2: LITERATURE REVIEW AND HYPOTHESIS DEVELOPMENT 5 
2.1 Corporate social responsibility (CSR) ... 5

2.2 Customer loyalty behaviors ... 11

2.3 CSR performance and brand likeability. ... 12

2.4 CSR performance and relational switching cost ... 16

2.5 Brand likeability on Word-of-mouth and Repurchase intention. ... 19

2.6 Relational switching cost on Word-of-mouth and Repurchase intention. 20

CHAPTER 3: RESEARCH METHODOLOGY ... 23

3.1 Research design ... 23

3.2 Sampling ... 24

3.3 Data collection process ... 25

3.4 Questionnaire design ... 25

3.5 Data analysis ... 28

CHAPTER 4: DATA PRESENTATION AND FINDINGS ... 31

4.1 Data description ... 31

4.2 Reliability analysis ... 35

4.3 Exploratory factor analysis (EFA) ... 36

4.3.1 EFA of CSR scale ... 36

4.3.2 EFA of Brand Likeability scale ... 39

</div>
(6)<div class='page_container' data-page=6>

4.3.4 EFA of WOM scale ... 42

4.3.5 EFA of Repurchase Intention scale ... 43

4.4 Regression analysis results ... 44

CHAPTER 5: RESULT DISCUSSION ... 49

5.1 Result discussion ... 49

5.2 Contributions of the research ... 52

5.2.1 Theoretical contribution ... 52

5.2.2 Practical contribution ... 53

5.3 Limitations and future research direction ... 55

</div>
(7)<div class='page_container' data-page=7>

LIST OF TABLES

Table 3.1: Measurement items ... 26

Table 3.2: Likert scale for Agreement extent ... 28

Table 4.1: Descriptive Statistics of 212 respondents ... 31

Table 4.2: Samples’ demographic data ... 32

Table 4.3: Summary of retailing companies ... 34

Table 4.4: Reliability statistic of all scales ... 36

Table 4.5: EFA for CSR scale – 1st test ... 36

Table 4.6: Rotated components matrix for CSR scale - 1st test ... 37

Table 4.7: EFA for CSR scale – 2nd test ... 38

Table 4.8: Rotated components matrix for CSR scale - 2nd test ... 38

Table 4.9: EFA for Brand Likeability scale ... 39

Table 4.10: Component matrix for Brand Likeability scale ... 40

Table 4.11: EFA for Relational Switching cost scale ... 41

Table 4.12: Component matrix for Relational Switching Cost scale ... 41

Table 4.13: EFA for WOM scale ... 42

Table 4.14: Component matrix for WOM scale ... 42

Table 4.15: EFA for Repurchase Intention scale ... 43

Table 4.16: Component matrix for Repurchase Intention ... 43

Table 4.17: Correlations ... 45

Table 4.18: Collinearity Statistics ... 45

</div>
(8)<div class='page_container' data-page=8>

LIST OF FIGURES

</div>
(9)<div class='page_container' data-page=9>

1
CHAPTER 1: INTRODUCTION

1.1. Background and necessary of the research

Retailing alluded to direct sale of goods to the ultimate consumers who do not
commercialize or reselling. In the other words, these products or services are just for
their own use. There are many different types of retailing organizations such as
independent stores, conjoint retailers, hypermarkets, chain stores or shopping malls.
Retailing activities could be directly related many environmental issues such as “energy
and water consumption, waste, the volume of packaging, land use, and transportation,
the use of chemicals by suppliers and offering genetically modified food” (Martinuzzi,
et al., 2011). Additionally, retailing is an intensely competitive market. Therefore,
maintaining repurchase behavior of customers is very important to retailing companies.
Especially in the case that costs of attracting and getting new customer are estimated to
6 times as big as retaining the existing ones (Huddleston, et al., 2004). Moreover,
customer loyalty can benefit firms by an increase in loyal customers’ spending and
appealing potential customers through oral communication among people (Curasi &
Kennedy, 2002). At the same time, customers are believed to be unlikely to purchase
products or service which has low or unacceptable corporate social performance
(Castaldo & Perrini, 2004) and they expect the brand they are going to buy product or
service to meet some certain minimum level of social performance as well (Meijer &
Schuyt, 2005). In this case, CSR is considered as integral value when customers make
purchase decision. In other words, retailing companies are supposed to implement their
social responsibilities as a corporate citizen so that they can create their positive public
image and opinion (Jones, et al., 2007) besides their purpose of economic gain.

</div>
(10)<div class='page_container' data-page=10>

General Statistics Office, in 2019, retailing sales of goods reached nearly USD $ 162
billion, accounting for 75.9% of the total and increasing by 12.7% compared to 2018. In
2018, retailing sales Vietnam's goods were estimated at nearly 143 billion USD which
increased by 12.4% over the previous year. In 2017, it was nearly 130 billion USD which
increased by 10.9%. In 2016, retailing sales reached about USD 118 billion, increasing

by 10.2% compared to USD 110 billion of 2015. Along with the impressive growth rate,
the fact that the Vietnamese retailing market fully opened to allow foreign enterprises to
invest 100% capital since January 11, 2015 and the signing of a series of new generation
of Free Trade Agreements have led to fierce competition between retail supermarket
systems in Vietnam market with the arrival of many large enterprises from abroad such
as Lotte, K Mart , Central Group, Aeon, , Auchan, Family Mart or Circle K. Therefore,
maintaining repurchase behavior of customers and efforts to differentiate itself from
others are very important to retailing companies in Vietnam now. In the current context
of Vietnam, many businesses are not paying attention to their social responsibility, which
includes frauds in business, production of poor quality goods or intentionally causing
environmental pollution have made many customers annoyed (Hoang, 2019). Whereas,
customers are believed to be unlikely to purchase products or service which has low
corporate social performance (Meijer & Schuyt, 2005). Therefore, executing social
responsibilities is an effective marketing tool and an indispensable condition for retailing
companies in Vietnam in term of creating positive opinion (Jones, et al., 2007) and
meeting customers’ certain minimum level of social engagement (Meijer & Schuyt,
2005) which in turn can help them increase loyal customers’ spending, appeal potential
consumers through WOM communication (Curasi & Kennedy, 2002) and make
themselves become more outstanding relative to their competitors (Porter & Kramer,
2007) through enhancing customer loyalty (Martínez & Bosque, 2013).

</div>
(11)<div class='page_container' data-page=11>

explained the direct influence of CSR on customer behaviors, many researchers made
their effort to explain the effect of CSR initiatives on customer behaviors through many
different routes such as the enhancement of satisfaction, valuation of service,
identification, trust, corporate image, reputation, commitment, perceived value or social
media engagement. However, the impact of CSR on “brand likeability” and “relational
switching cost” and ultimately on customer loyalty behaviors are underexplored.
Therefore, exploring these relationships is essential and is going to be conducted in this

research.

1.2. The research objectives

The research aims at exploring the chain effect of CSR on brand likeability as well as
relational switching cost and ultimately on customer loyalty behaviors. Also, the study
provides the Vietnamese companies with managerial implication.

1.3. Research questions

The thesis is answering the questions as follows:

1. How significant do CSR dimensions (environment, society, stakeholders) affects
brand likeability which in turn impacts on customer loyalty behaviors (word of
mouth and repurchase intention) ?

2. How significant do CSR dimensions (environment, society, stakeholders) impact
on relational switching cost which in turn impacts on customer loyalty behaviors
(word of mouth and repurchase intention) ?

1.4. Research scope

</div>
(12)<div class='page_container' data-page=12>

1.5. Research structure

This study will be split into five parts as follows:
- Chapter 1: Introduction

 The general overview of research including necessity, objectives, questions

and scope are briefly presented.

- Chapter 2: Literature review and hypothesis development

 The theoretical framework will be presented in detail by displaying the
fundamental concept and explaining the relationship of key variables. From
that, the hypothesis will be developed.

- Chapter 3: Research methodology

 Data collection and analysis plan as well as questionnaire designing is about
to be shown.

- Chapter 4: Data presentation and findings

 Data description will be shown. Also, the results of data analysis and
hypothesis test that are taken from SPSS software will be presented.

- Chapter 5: Discussions and conclusion

</div>
(13)<div class='page_container' data-page=13>

5
CHAPTER 2: LITERATURE REVIEW AND HYPOTHESIS

DEVELOPMENT

2.1 Corporate social responsibility (CSR)

Corporate social responsibility is not really a new concept but it is still an academic and
management subject that receives a lot of growing attention (Maon, et al., 2010; Peloza
& Shang, 2011) since it was first mentioned by Sheodon (1923) in his work and first

formally defined by (Howard Bowen, 1953). CSR is defined as “the commitment of
business to contribute to sustainable economic development working with employees,
their families, the local community and society to improve their quality of life in ways
that are good for both business and good for development.” Moreover, there have been
37 definitions of CSR published (Dahlsrud, 2008) and a lot of research have been done
to bring a better understanding of CSR concept.

</div>
(14)<div class='page_container' data-page=14>

supposed ethical dimension of CSR to be responsibilities including acknowledged
standards, norms or expectations in society. Most of the previous studies indicated that
the companies behaving ethically can improve the customers’ satisfaction and retention
(Galbreath, 2010; Hassan & Nareeman, 2013). According to Carroll & Shabana’s work
(2010), philanthropic dimension of CSR contains all activities of the companies in effort
to improve that the companies are good corporate citizen, which is society’s expectation.
Contributing to better community would make business become their preference (Jamali
& Mirshak, 2007). Lev, et al., (2010) revealed that firms involving in charitable
contribution would increase their customer retention.

Similarly, Maignan, et al., (1999) also considered CSR as multidimensional concept with
“economic, legal, ethical and discretionary” responsibilities of businesses toward their
stakeholders. Pinney (2001) simply regarded CSR as set of management practices which
organizations choose to minimize their negative impact on society. Among the many
different definitions of CSR, Mohr et al. (2001) grouped them into two major sorts
including CSR towards stakeholders which is based on multidimensional definitions and
CSR towards society relied on societal marketing principle. Specially, multidimensional
definitions describe most duties of companies towards their diversified stakeholders such
as owners, customers, employees or the community. Societal marketing concept was
defined as companies’ decision making that improves the well-being of both customers
and society (Kotler, 1991). Mohr et al. (2001) used this to define CSR at more abstract

level.

</div>
(15)<div class='page_container' data-page=15>

CSR from Mohr et al.’s work (2001) which are used in various researches (Maignan &
Ferrell, 2004; Maloni & Brown, 2006; Mandhachitara & Poolthong, 2011; Pomering &
Dolnicar, 2009). CSR toward environment is supposed to be visible and feasible in
business operations (Liu, et al., 2014). In the other words, it is easy for CSR toward
environment to be understood and recognized by media and consumers (Rahbar &
Wahid, 2011).

Therefore, this study chose to focus on studying three aspects of CSR including: society,
stakeholders and environment. There exist a number of researches that also have
concentrate on studying these three aspects of CSR environment (Liu, et al., 2014;
Mohammed & Al-Swidi, 2019; Dahlsrud, 2008).

Turker (2009) defined CSR toward society as activities contributing to well-being of
society. These activities contains “philanthropy, public welfare contributions, culture
promotion and sustainable development” (Liu, et al., 2014). Environmental CSR is
viewed as the companies’ contribution in balancing and improving environmental effects
without damaging economic performance in order to sustain their development
(Williamson, et al., 2006). It is supposed to include environmental pollution prevention,
energy conservation as well as green production or service provision. From stakeholders
viewpoint, Turker (2009) viewed CSR towards stakeholders as businesses’
responsibility which go beyond economic interest and have a positive influence over
their stakeholders including “owners, customers, employees or the community”.
Stakeholders activities comprise returns to investors, employee treatment, community
development, monitoring and inﬂuencing supplier behaviors (Liu, et al., 2014; Dahlsrud,
2008).

</div>
(16)<div class='page_container' data-page=16>

companies (Bhattacharya & Sen, 2004). In other words, social and environmental
standards are increasingly being considered by customers when making purchasing
decision (Knox & Maklan, 2004). Customers, nowadays, expect organizations to offer
superior products or services and contribute to improving societal issues in addition to
the task of economy development (Polychronidou, et al., 2014). Therefore, many
organizations have been increasingly conscious of CSR’s magnitude (Hemingway &
Maclagan, 2004) and thus enhance its CSR initiatives. Also, CSR has gotten lots of
attention from researchers and become a main topic in customer behavior literature
(Amatulli, et al., 2018).

</div>
(17)<div class='page_container' data-page=17>

</div>
(18)<div class='page_container' data-page=18>

Based on the literature of CSR and its relationship with customer behavior, it is very
obvious that it has gotten a lot of attention from the researchers with many different
explanation about the route that CSR activities affect customer behavior. However, there
is still theoretical gap that need to be filled. It is the fact that the effect of CSR on
branding has gotten great attention recently with research of “brand love” (Ho, 2017) or
“brand preference” (Liu, et al., 2014). Nevertheless, those researches just focused on
understanding the effect from affect-based perspective, namely, emotion, rather than
examining the customers’ perceptions. “Brand likeability” which is perception-oriented
has not been fully examined in the relationship with CSR initiatives in order to bring
more various view of CSR-branding relationship. Besides, likeability is suggested to
appear in all phase of transaction and to be a precursor of brand love, brand preference
and other important outcomes such as satisfaction or favorable attitudes toward brand as
well (Nguyen, et al., 2013); so “how to increase the likelihood that firms are perceived
to be likeable” is very important question for firm’s managers. Therefore, exploring the

connection of CSR activities with “brand likeability” and the clout of “brand likeability”
on customer loyalty behaviors including word of mouth as well as repurchase intention
is extremely necessary because they are underexplored.

</div>
(19)<div class='page_container' data-page=19>

be said that a study of effect of CSR activities on relational switching cost which then
affects customer loyalty behaviors is essential.

2.2 Customer loyalty behaviors

Oliver (1997) defined loyalty as “ a deeply held commitment to rebuy or repatronize a
preferred product/service consistently in the future, thereby causing repetitive same
brand or same brandset purchasing, despite marketing efforts to cause ‘switching
behavior”. In addition, Dick and Basu (1994) defined customer loyalty as the link
between relative attitude and repeated purchase. However, the concept of customer
loyalty hasn’t got much consensus in spite of its popularity (Zhang and Bloemer, 2008).
For instance, some researches conceptualized customer loyalty by “behavioral,
attitudinal and integrated perspectives” (Dick and Basu, 1994; Homburg and Giering,
2001; Hur et al., 2012). Important to the this study, Fullerton (2003) and Zhang and
Bloemer (2009) constructed customer loyalty as essentially “behavioral intention” and
named “customer loyalty behaviors” which includes willing to pay, word of mouth
communication and repurchase intention. The study is going to focus on the two later
dimensions.

An actual customer behavior of buying the same brand more than one time can define
repurchase (Ibzan, et al., 2016). Intention is defined as a motivation of someone when
they wants to perform their behavior (Rezvani, et al., 2012). While repeated purchase is
considered as actual action, repurchase intention is explained as consumers’ decision of
continuing to purchase a product or service when it comes in handy (Keller, 2001).

Dodds, et al., (1991) insisted repurchase intention is representatives for consumers’
possibility of keeping on purchasing a product or service. Therefore, intention to
repurchase can be considered as customer loyalty.

</div>
(20)<div class='page_container' data-page=20>

colleagues consumption experience. Put another way, WOM is verbal communication
related to a product, service, organization or brand. There are 2 types of word-of-mouth
including positive and negative. The research focused on positive WOM which is
defined as “a desire to help the company, altruism, a desire to signal expertise to others
and product involvement” (Angelis, et al., 2012). WOM is widely accepted by customers
and they consider them as an important communication source. People enjoy talking
about their possibilities and experiences (Kelly, 2007). Also, when making purchase
decision, customers have more confidence in WOM communication rather than radio,
television, and publications (Cakim, 2010). There are between 50-70% of buying
decisions are affected by WOM (Sweeney, et al., 2008). Therefore, firms’ effort in
enhancing positive WOM is very vital not only since it can bring them more new
customers but only because it is like an express of their success in increasing the
customer loyalty.

2.3 CSR performance and brand likeability.

</div>
(21)<div class='page_container' data-page=21>

divers of likeability so that they can raise the likelihood that customers would perceive
them as more likeable ones (Nguyen, et al., 2013).

Likeability is described to be “a persuasion tactic and a scheme of self-presentation”
(Cialdini, 1993; Reysen, 2005) and is considered as multidimensional concept including
cognitive and affective elements (Alwitt, 1987). Attribution theory, “the study of the

causal interpretations that persons give to events in their environment” (Crittenden,
1983) is very helpful in defining “likeability”. That means it was supposed that when
people face or cope with an surprising or negative event, they tend to look for causal
interpretation for that event. The way people interpret that event can imply their thinking
and behavior. As the attribution concept’s suggestions, the likeability is expected to
occur when consumers have positive inference from firm’s activities (Nguyen, et al.,
2013). Once a positive assessment attaches to a firm, that firm will be found likeable and
vice versa. In order to make any inference about any firms, customers usually assess
firm’s profit and motives, past behavior and reputation (Cox, 2001; Campbell, 2007). 
Therefore, building and maintaining good reputation can affect more positively inference
of customers towards firms, which increases brand likeability.

Besides, attractiveness model (McGuire, 1985) also provides insight in defining
likeability. The connection of customers’ negative or positive awareness of
attractiveness with likeable firm are found (Nguyen, et al., 2013) . This finding suggests
that firms improving their offerings’ attractiveness which may comprise “building
relationships with fair trade organizations, delivering green products, and supporting
charities” are well regarded by their customers. In addition, good reputation can be also
a kind of attractiveness (Nguyen, et al., 2013).

</div>
(22)<div class='page_container' data-page=22>

environmental practices. Brown & Dacin (1997) believed that what customers know
about the companies would determine their belief and attitude toward the products of the
company. They suggested that when the customers consider CSR performance of the
companies as positive, they make positive inference of the companies’ business. Mohr
& Webb (2005) showed that customers’ positive company evaluation and strong
purchase intention was impacted by the manufacturers who implement CSR towards
environment. Reputation could be one of criteria for customer to determine their
perception toward a company and its attractiveness (Nguyen, et al., 2013). A bank ’s

reputation for CSR activities, for example, environmental efforts, therefore, positively
affects customer’s liking towards it. (Rives, et al., 2009). A green brand image is
supposed to have a positive link with consumers’ satisfaction (Chen, 2010). It is very
obvious that consumers tend to like the companies which make donation for
environmental organizations (Nguyen, et al., 2013) because when firms support to these
activities, they can develop goodwill among customers which would generate likeability
effect. While Kucukusta, et al., (2013) found the CSR factors related to environment,
mission and vision could be predictor the visitors’ stay preference, Liu, et al. (2014)
contended that environmental CSR would yield more brand preference by customers. In
sum, with the support and evidence from the literature for the environmental CSR’s
positive association with brand likeability, the first hypothesis is defined as:

H1: CSR towards environment positively impacts brand likeability.

</div>
(23)<div class='page_container' data-page=23>

intended to enhance social interests increase and enhance brand image (Singh, et al.,
2008) and brand association (Ricks, 2005). In support, there are various researchers
including Hassan & Nareeman (2013), Galbreath (2010) and Lee, et al., (2013) provided
the evidence proving that the businesses’ philanthropic activities which contribute to
community’s well-being could generate higher level of customer satisfaction. The
contribution to community’s well-being which are regarded as meeting community
expectation would drive the firm be its favor (Jamali & Mirshak, 2007; Wood, 2010). In
support, (Nguyen, et al., 2013) contended that customer is likely to like the companies
which involve in social activities such as supporting charity. With supportive evidence
from the literature, engaging in CSR towards society can make the firms become more
likeable. As a result, the hypothesis is:

H2: CSR towards society positively impacts brand likeability.

</div>
(24)<div class='page_container' data-page=24>

H3: CSR towards stakeholders positively impacts brand likeability. 
2.4 CSR performance and relational switching cost

Due to the increasingly high competition and the decline in market growth rate,
protecting market share towards companies has become more important than ever.
Switching costs can be one of the effective strategy to create customer loyalty which
helps companies to maintain their market share against their competitors. In (1998),
Poster defined switching cost as the costs consumers incur once they migrate to another
products or service provider. Chen & Wang (2009) contended that switching costs could
be “the form of termination costs from the current service provider to joining costs with
the alternative service provider”.

Klemperer (1987) supposed that there were 3 kinds of switching cost including
“transaction, learning and contractual costs”. Transaction cost arises when customers
stop buying products or using services from a provider and find a new one. Learning cost
refers the cost of immigrating to a new brand after learning to use another brand.
Contractual cost is supposed to be the expense of losing programs for loyal customers
that they got from current brand such as “repeat-purchase coupons or frequent-flyer
program” (Klemperer, 1987).

</div>
(25)<div class='page_container' data-page=25>

to experience or incur emotional discomfort because of the loss of identity, the breaking
of bonds, the risk and the uncertainty that the termination of the current relationship
could bring.

</div>
(26)<div class='page_container' data-page=26>

to another provider or brand of customers. With supportive evidence from the literature,
the following is hypothesized:

H4: CSR towards environment positively impacts relational switching cost.

The characters that are contributed to organizations by CSR actions, for example, fair
employment policies, supports for society and environment are much more distinctive
than other facets of the company-schema (Bhattacharya & Sen, 2004), which becomes
attractive point for customers to identify themselves with. Besides, all CSR efforts
towards society, for example, funding to community programs, create both added-value
for community and for business on account of their reflection about company
identification matching with beneficent values. Those values can create the company’s
association as well as identification with its purchasers (Sen, et al., 2006). Consumers
always desire a better society and that is also the reason why they are likely to feel the
overlap between their value and company which involves in CSR for the welfare of
society (Abbas, et al., 2018). In support, Pérez & Rodríguez-del-Bosque (2015) ,in a
survey with saving bank customer, found that CSR oriented to society can enhance C-C
identification. Mostafa & Elsahn (2016) also revealed consumer-bank identification was
positively affected by philanthropic CSR initiatives. Those bonds of identification that
are enhanced by CSR towards society strengthen the discomfort that customers incur if
they switch to another provider. With supportive evidence from the literature, engaging
in CSR towards society can increase psychological barriers called relational switching
cost. As a result, the hypothesis is:

H5: CSR towards society positively impacts relational switching cost

</div>
(27)<div class='page_container' data-page=27>

customer-19

centric CSR activities. In support, Saleem & Gopinath (2015) indicated that consumer
CSR was found to affect positively customers’ trust towards firms. Also, Marquina &

Vasquez-Parraga (2013) indicated that CSR image related to employee affairs has
positive impact on customer behavior. Moreover, CSR effort toward stakeholders can 
decrease customers’ skepticism and increase customers’ trust towards firms (Vlachos, et
al., 2008). Consumers are supposed to found an association with their favorable firms or
show consumers’ personality through those (Fournier, 1998); while Liu, et al., (2014)
showed CSR endeavor towards stakeholders can make the brands become customers’
preference. As a consequence, the sixth hypothesis is defined as:

H6: CSR towards stakeholders positively impacts relational switching cost. 
2.5 Brand likeability on Word-of-mouth and Repurchase intention.

</div>
(28)<div class='page_container' data-page=28>

and Taghizadeh, et al., (2013). With supportive evidence from the literature, the
hypothesis is:

H7: Brand likeability positively impacts word of mouth.

Suetrong, et al. (2018) revealed that in short-term, customers like a brand if they are
contented with its characteristics or benefits. In case of customers’ keeping this feeling
relative to alternatives, it is conceivable that they would keep on repurchase that brand
(Suetrong, et al., 2018). Also, a favorable attitude towards a firm can lead to repeat
purchase (Buil, et al., 2013) based on theory of reasoned action related to explanation
for relationships between “attitudes, intentions and behavior” (Fishbein & Ajzen, 1975).
Theoretically, consumer preference is a direct premise of intention (Bagozzi, 1983).
Consistent with this perspective, there are some researchers’ empirical evidences support
positive link between customers’ favor toward a brand and their willingness to buy it
again. In other words, they supported the role of brand preference in motivating
customers’ intention to repurchase (Hellier, et al., 2003; Ebrahim, et al., 2016; Roest &
Pieters, 1997; Hellier, et al., 2003; Andreassen & Lindestad, 1998). Besides, feeling of

attachment such as brand love is considered a great predictor of repurchase intention
(Suetrong, et al., 2018). Moreover, a satisfied customers are also supposed to be more
likely to be interested in repurchasing intention. In support, there are some researchers
found that customer satisfaction is the precedent of customer repurchase intention such
asBearden & Teel (1983), Anderson & Sullivan (1993), Innis (1991) , Roest & Pieters
(1997) or Olive (1980). With supportive evidence from the literature, a likeable brand
can positively affect repurchase intention. As a result, the hypothesis is:

H8: Brand likeability positively impacts repurchase intention.

</div>
(29)<div class='page_container' data-page=29>

by an increase in loyal customers’ spending and appealing more consumers through
WOM communication (Curasi & Kennedy, 2002). Besides, Vasudevan, et al., (2006)
and Patterson, et al., (2001) contended that relational switching cost are positively
associated with commitment; whereas commitment was found to be likely to enhance
positive WOM (Bougie, et al., 2003; Derbaix & Vanhamme, 2003; Fazal-e-Hasan, et al.,
2017). With supportive evidence from the literature, relational switching cost can
positively affect WOM . As a consequence, the hypothesis is:

H9: Relational switching cost positively impacts word-of-mouth.

</div>
(30)<div class='page_container' data-page=30>

H10: Relational switching cost positively impacts repurchase intention.

</div>
(31)<div class='page_container' data-page=31>

23
CHAPTER 3: RESEARCH METHODOLOGY

3.1 Research design

The research was conducted as follows:

Figure 3.1: Research process proposed by the author

Identify research interest and motivation

Review the literature

Identify theoretical
and practical gaps

Develop conceptual
framework and propose
research model

Determine research methods:
questionnaire/survey

Determine research sample

Develop questionnaire

Pilot test

Correct and finalize questionnaire

Distribute questionnaire online

Analyze data by SPSS

</div>
(32)<div class='page_container' data-page=32>

3.2 Sampling

According to the study of Hair, et al., (1998) about the expected sample size for
Exploratory Factor Analysis, the minimum number of sample is determined by the total
measurement item in questionnaire multiple by 5. This research’s questionnaire includes
30 measurement items. Therefore, the number of respondents, or in other words, the
minimum sample size needed to conduct this should be: 30*5=150.

Besides, Tabachnick & Fidell (2007) suggested that the minimum sample size for
multivariate regression models must be calculated by 50 plus (8*the number of
independent variable). The maximum amount of independents is 3 for this study.
Therefore, the minimum sample size needed to conduct this should be: 50+8*3=74.
Normally, if a paper incorporates multiple analysis methods, the sample size would be
the largest required one of all the methods. In this study, the author intends to use two
methods including EFA and multivariate regression analysis. Therefore, the minimum
sample size shall be 150 which is minimum sample size needed to conduct EFA.
However, in case there is invalid responses that need eliminating and to boost reliability
and validity of the research, the author decided to distribute 225 questionnaires.

</div>
(33)<div class='page_container' data-page=33>

3.3 Data collection process

To ensure that the final questionnaire that was officially distributed to the respondents
was understandable and error-free, 30 questionnaires were sent to 30 people who are
highly educated and have high perception of CSR initiatives of companies with
expectation of getting useful comments about the content and wording of the

questionnaire. In general, the questionnaire received good feedback from these people.
Some errors in word usage have been corrected and modified before being formally
contributes to main respondents.

After finalizing the questionnaires, these were distributed online via google doc file in
order to collect the primary data. The data then was used to be analyzed and found out
the results for the research.

3.4 Questionnaire design

The measurement items for all variables in this study was obtained from the similar
previous literature. Also, each item is evaluated on 5-point Likert-type scale ranging
from 1 (strongly disagree) to 5 (strongly agree). Measurement items of 3 different CSR
dimensions was taken from different studies. In detail, CSR towards Society and
Environment are measured using 6-item scale which are proposed by Herrera (2017) and
CSR toward Stakeholders are measured by 8-item scale introduced by (Liu, et al., 2014).
Besides, the measurement of Brand Likeability was adopted from Nguyen, et al., (2013)
while Relational Switching Cost are measured with 3-item scale from Özer, et al.,
(2009). In addition, the study measures Word of Mouth by 3-item scale taken obtained
from (Abbas, et al., (2018). Also, Repurchase Intention is measured 3-item scale
developed by Fang, et al., (2011).

</div>
(34)<div class='page_container' data-page=34>

- Part 1: contains 4 demographic questions.

- Part 2: comprises of 30 measurement items for measuring: CSR towards Society,
CSR towards Environment, CSR towards Stakeholders, Brand Likeability,
Relational Switching Cost, Word of Mouth and Repurchase Intention. However,
those measurement items is mixed randomly and not arranged in order

corresponding with the variables it measures. Thanks to that, responders cannot
come up exactly with the purpose of the research. Therefore, the research can
limit the potential biases and increase its reliability.

Table 3.1: Measurement items

Construct Items Label Sources

CSR 
towards 
Society

This brand is trying to sponsor educational

programmes SCSR1

Herrera
(2017)
This brand is trying to sponsor public health

programmes SCSR2

This brand is trying to sponsor cultural

programmes SCSR3

This brand is trying to make financial

donations to social causes SCSR4

This brand is trying to help to improve quality

of life in the local community SCSR5

CSR 
towards 
Environm
ent

This brand is trying to sponsor

pro-environmental programmes ECSR1

Herrera
(2017)
This brand is trying to allocate resources to

offer services compatible with the environment ECSR2
This brand is trying to carry out programmes to

reduce pollution ECSR3

This brand is trying to protect the environment ECSR4
This brand is trying to recycle its waste

materials properly ECSR5

This brand is trying to use only the necessary

</div>
(35)<div class='page_container' data-page=35>

CSR towards 
Stakeholders

This brand respects consumer rights beyond

the legal requirements StCSR1

Liu, et
al.,
(2014)
This brand provides full and accurate

information about its products/services to
customers

StCSR2
Customers’ satisfaction is highly important

for this brand StCSR3

This brand provides a healthy and safe

working environment for employees StCSR4

This brand complies with legal regulations

completely and promptly StCSR5

Pornography, gambling and drug abuse are

prohibited in this brand StCSR6

Brand 
Likeability

I believe that this brand continues to get

better and better. BL1 Nguyen,

et al.,
(2013)

I feel attached to this brand. BL2

I would say that the brand is approachable. BL3

Overall, I approve of this brand. BL4

Relational 
Switching 
Cost

It is important for me that this brand is a
trusted corporation (when I bethink of factors
like pricing, service quality etc.)

RSC1 Özer, et 
al.,
(2009)

I am thinking positive about this brand RSC2

The name of this brand is important for me RSC3

Positive 
Word of 
Mouth

I say positive things about this brand to

others. WOM1

Abbas,
et al.,
(2018)
I recommend the services or products of this

brand to friends, relatives and other people. WOM2
I mention favorable things of this brand to

friends, relatives and other people. WOM3

Repurchase 
Intention

If I could, I would like to continue purchase

products of this brand RI1

Fang, et

al.,
(2011)
It is likely that I will continue purchasing

products from this brand in the future RI2
I intend to continue purchasing products from

</div>
(36)<div class='page_container' data-page=36>

5-point Likert-type scale for agreement extent is presented as follows: 
Table 3.2: Likert scale for Agreement extent

3.5 Data analysis

The research uses SPSS to analyze data and test hypothesis. The process is presented as
follows:

a. Reliability analysis

Before analyzing data, checking the reliability of scale is very necessary, especially
towards questionnaires using multiple Likert questions. Campbell & Fiske (1959)
contended that a valid measurement has to accurately measure what needs to be
measured. Cronbach’s alpha is proposed to facilitate checking the reliability of scale.
However, Cronbach’s alpha can be only used for a scale whose the number of
measurement items are 3 or more. This coefficient is understood and used as follows:

- Cronbach’s alpha varies from 0 to 1.

- Theoretically, this value is understood as the higher, the better. It is supposed to
be great as it is higher than 0.9 and poor when it is lower than 0.5 (George &

Mallery, 2010). However, that α is higher than 0.95 is believed to lead to
duplication in scale.

Besides, when doing reliability analysis by Cronbach’s alpha in SPSS software, there
are some indicators needing to be paid much attention as follows:

1 2 3 4 5

Strongly
disagree

Disagree Neutral Agree Strongly

</div>
(37)<div class='page_container' data-page=37>

- “Corrected Item – Total Correlation” of each measurement item: should be equal
or more than 3 in order not to be removed.

- If “Cronbach's Alpha if Item Deleted” of a measurement item is more than
Cronbach’s alpha, that item will be removed.

b. Exploratory factor analysis (EFA)

Besides assessing the reliability of scale, assessing the value of the scale is also essential.
EFA is used to shorten a set of k variables into a smaller set of variables, namely, F (F<k),
which makes them more meaningful. When doing EFA by SPSS software, there are
something needing to be paid much attention as follows:

- “Kaiser-Meyer-Olkin” (KMO) which is used to consider whether factor analysis
is suitable or not, must be equal or more than 0.5. (0.5 ≤ KMO ≤ 1). If KMO is

less than 0.5, factor analysis is likely to be inappropriate for the data set.

- “Bartlett's test of sphericity” is used to consider correlation of the observed
variables in a factor. “Sig Bartlett's Test” must be less than 0.5 in order to
demonstrate that they are correlated with each other.

- The “Eigenvalue value” is to figure out the amount of factors for EFA. Those
whose Eigenvalue is equal or more than 1 are retained and vice versa.

c. Pearson correlation analysis

After finishing reliability analysis and exploratory factor analysis, “Pearson correlation
analysis” is conducted to explore linear relationship among the variables in the model.
Based on Pearson correlation coefficient which is abbreviated as R, the author could
determine strict degree of linear relationship between two quantitative variables:

</div>
(38)<div class='page_container' data-page=38>

- The more R approaches to 0, the weaker the linear correlation is.
- If R equal 0, there is no linear correlation.

However, when doing this analysis by SPSS, it is necessary to notice “Sig” indicator
which shows whether the correlation between 2 variables is meaningful. The correlation
is supposed to be meaningful when “Sig” is less than 0.5.

d. Regression analysis

Regression analysis is used to analyze the relationship between a dependent variable and
one or more than one independent variables. When doing this by SPSS, there are some
indicators needing to be paid attention as follows:

- “R Square and Adjusted R Square”: which indicate magnitude of interpretation
of dependent variable of independent variables in regression model range from 0
to 1. It is believed that the higher this indicator, the better model.

- “Durbin – Watson”: should be from 1.5 to 2.5 in order not to lead to first-order
correlation with each other.

</div>
(39)<div class='page_container' data-page=39>

31
CHAPTER 4: DATA PRESENTATION AND FINDINGS

4.1 Data description

A summary of data description including the minimum, maximum, mean and standard
deviation are shown as follow.

Table 4.1: Descriptive Statistics of 212 respondents

(Source: Data analysis by SPSS)

Descriptive Statistics

N Minimum Maximum Mean Std. Deviation

SCSR1 212 1 5 3.37 1.020

SCSR2 212 1 5 3.43 .979

SCSR3 212 1 5 3.30 .940

SCSR4 212 1 5 3.49 1.014

SCSR5 212 1 5 3.57 1.035

ECSR1 212 1 5 3.23 .973

ECSR2 212 1 5 3.42 .988

ECSR3 212 1 5 3.39 1.022

ECSR4 212 1 5 3.46 1.055

ECSR5 212 1 5 3.24 1.004

ECSR6 212 1 5 3.20 1.006

StCSR1 212 1 5 3.72 .787

StCSR2 212 1 5 4.00 .803

StCSR3 212 1 5 3.90 .941

StCSR4 212 1 5 3.86 .747

StCSR5 212 1 5 3.74 .783

StCSR6 212 1 5 4.13 .825

BL1 212 1 5 4.00 .763

BL2 212 1 5 3.70 .867

BL3 212 1 5 3.99 .815

BL4 212 1 5 3.99 .840

RSC1 212 1 5 3.76 .915

RSC2 212 1 5 3.72 .846

RSC3 212 1 5 3.43 .913

WOM1 212 1 5 3.67 .874

WOM2 212 1 5 3.65 .871

WOM3 212 1 5 3.66 .918

RI1 212 1 5 3.81 .904

RI2 212 1 5 3.83 .885

RI3 212 1 5 3.89 .896

</div>
(40)<div class='page_container' data-page=40>

The author distributed 225 questionnaires via google doc file. However, after screening
all received responses, the author eliminated 13 disqualified samples and retained the set
of 212 valid samples as presented in table above. The reason that those 13 samples were
removed is the respondents of them chose the same option for all questions in

questionnaires.

Table 4.2: Samples’ demographic data

(Source: Data analysis by SPSS)

Taking a look at the table 4.2 about samples’ demographic data, it is obvious that the
amount of male and female respondents are not equal. Among all 212 subjects, there are

Demographics Frequencies Percentage

Total 212 100

1. Gender

Female 137 64.6

Male 75 35.4

2. Age

18 - 24 years old 38 18.1

25 - 30 years old 102 48.3

31 - 40 years old 37 17.2

> 41 years old 35 16.4

3. Education level

Vocational training 15 7.1

College 9 4.2

University 146 68.9

Postgraduate 38 17.9

Others 4 1.9

4. Income

< 5M 46 21.7

5M - 10M 55 25.9

10M - 15M 66 31.1

15M - 30M 31 14.6

</div>
(41)<div class='page_container' data-page=41>

137 female respondents accounting for 64.6 per cent and 75 male responders accounting
for 35.4 per cent.

Additionally, it is obviously seen that among 212 participants, 38 people accounting for
18.1 per cent are from 18 to 24 years old, 102 people making up for 48.3 percent are
from 25 to 30 years old, 37 people constituting 17.2 percent are from 31 to 40 years old
and more than 41 year-old respondents make up for 16.4 percent. In a nutshell, the

majority of respondents are young people in the age from 25 to 30.

Besides, most of participants are highly educated people in which group of people whose
educational levels are university are largest with ratio of 68.9 per cent. The second largest
group is postgraduate people accounting for 17.9 per cent. Besides, the group of people
whose educational levels are vocational training and college making up for 7.1 percent
and 4.2 per cent respectively. The group of people who just graduated from high school
or lower, namely, others accounts for 1.9 per cent and it also constitutes the lowest per
cent among all subjects.

</div>
(42)<div class='page_container' data-page=42>

Figure 4.1: Retailing companies distribution

Figure 4.3 indicates that The Gioi Di Dong, Vinmart, Big C, Lotte Mart, Sai Gon Co.op,
Media Mart, Aeon Mall, TH true Mart, FPT shop, Circle K, Fivi Mart , Pico and Dien
May Xanh are retailing companies mentioned in respondents’ answers. In which,
Vinmart is shown up the most in respondents’ answers, which accounts for 30.3%.
Besides, Big C, The Gioi di Dong or AeonMall significantly take up proportion, which
are respectively 14.7 %, 9.8 % and 8.6%.

General information about these retail companies is shown in the table below:
Table 4.3: Summary of retailing companies

No.

Retailing

companies Products Distribution Origin

1 The Gioi Di Dong

Mobile phones, digital devices,

and consumer electronics 1890 stores Vietnam

2 Dien May Xanh

Electronics refrigeration,
appliances, technology

products 750 stores Vietnam

3 FPT shop

Mobile digital products include
mobile phones, tablets, laptops,
accessories and technology

services 635 stores Vietnam

4 Media Mart Consumer electronics products 190 stores Vietnam

9.8
30.3

14.7

</div>
(43)<div class='page_container' data-page=43>

5 Pico

Consumer electronics products

and refrigeration. 23 stores Vietnam

6 Vinmart

Fresh food, foodstuffs and

groceries 111 stores Vietnam

7 Big C

Fresh food, foodstuffs and

groceries 35 stores Thailand

8 Lotte Mart Grocery, clothes, toys 14 stores Korea

9 Sai Gon Co.op

Fresh food, foodstuffs and

groceries 110 stores Vietnam

10 Aeon Mall

Fresh food, semi-processed
food grocery and consumer

electronics 4 stores Japan

11 TH true Mart Fresh food from nature 250 stores Vietnam

12 Circle K Groceries 393 stores US

Table 4.4 shows that although the companies mentioned in the respondents' responses
are only a part of the Vietnamese retail market, they also illustrate this market’s fierce
competition well. In detail, in addition to some Vietnamese retailing companies such as
The gioi di dong or FPT shop, the market also welcomed the arrival of a huge number
of foreign players such as Lotte mart, Aeon Mall or Circle K. Also, the retailing
companies mentioned mainly operate in 3 areas including sales of refrigeration and
electronics; technology; food products and groceries. Moreover, although the scale is
different now, most retailers are trying to increase coverage and brand recognition by
opening more stores across the country.

4.2 Reliability analysis

</div>
(44)<div class='page_container' data-page=44>

number of items of five, six, six, four, three, three and three respectively are checked by
Cronbach’s Alpha and summarized as the following table:

Table 4.4: Reliability statistic of all scales

(Source: Data analysis by SPSS)

Looking at table 4.4, it can be seen that Cronbach’s Alpha value of all variables’ scales
are greater than 0.5 and less than 0.95. This proves that all variables’ scales are very

reliable. In the other words, all measurement items are acceptable for next analysis step
and none of them are removed to increase the reliability of scales.

4.3 Exploratory factor analysis (EFA)

4.3.1 EFA of CSR scale

Table 4.5: EFA for CSR scale – 1st test

(Source: Data analysis by SPSS)

Scale Cronbach's Alpha N of Items

CSR towards Society - (SCSR) 0.878 5

CSR towards Environment - (ECSR) 0.915 6

CSR towards Stakeholder - (StCSR) 0.912 6

Brand Likeability - (BL) 0.923 4

Relational Switching cost - (RSC) 0.855 3

Word of Mouth - (WOM) 0.900 3

Repurchase Intention - (RI) 0.929 3

Condition

Value

KMO index

0.931 Sig. (Bartlett's Test)

0.000 Total Variance Explained

69.987

</div>
(45)<div class='page_container' data-page=45>

Table 4.6: Rotated components matrix for CSR scale - 1st test

Component

1 2 3

ECSR3 0.836

ECSR4 0.829

ECSR6 0.813

ECSR1 0.801

ECSR2 0.716

ECSR5 0.692

StCSR4 0.793

StCSR2 0.790

StCSR3 0.787

StCSR6 0.763

StCSR1 0.745

StCSR5 0.640 0.453

SCSR4 0.761

SCSR2 0.756

SCSR3 0.737

SCSR1 0.715

SCSR5 0.709

(Source: Data analysis by SPSS)

CSR scale initially contains 17 measurement items. After doing reliability analysis, none
of them are removed. Therefore, the EFA is conducted with these 17 measurement items
in order to examine convergence of items along with components.

Looking at table 4.5, it is obvious that KMO value is 0.931 (greater than 0.5 and less
than 1) and Sig. is 0.000 ( less than 0.05). Therefore, it can be concluded that the set of
data is valid for EFA. Additionally, there are three components extracted with greater
than 1 Eigenvalue. Besides, the cumulative variance is 69.987 %. Therefore, it can be
contended that there are 3 components explaining 69.987 % of variance of CSR.

</div>
(46)<div class='page_container' data-page=46>

distinction in rotated component matrix. Moreover, the factor loading difference
between them which is 0.187 is less than 0.3. Therefore, “StCSR5” is removed.

After removing “StCSR5”, Exploratory Factor Analysis of CSR scale is conducted again
as the following tables:

Table 4.7: EFA for CSR scale – 2nd test

(Source: Data analysis by SPSS)

Table 4.8: Rotated components matrix for CSR scale - 2nd test

Component

1 2 3

ECSR3 0.838

ECSR4 0.830

ECSR6 0.817

ECSR1 0.803

ECSR2 0.715

ECSR5 0.689

StCSR3 0.798

StCSR4 0.789

StCSR2 0.787

StCSR6 0.769

StCSR1 0.734

SCSR4 0.769

SCSR2 0.760

SCSR3 0.737

SCSR1 0.719

SCSR5 0.711

(Source: Data analysis by SPSS)

Condition

Value

KMO index

0.926 Sig. (Bartlett's Test)

0.000 Total Variance Explained

70.336

</div>
(47)<div class='page_container' data-page=47>

Taking a look at table 4.7, it can be seen that after eliminating “StCSR5” item, KMO
index is 0.926 (greater than 0.5 as well as less than 1) and Sig. is 0.000 ( less than 0.05),
which proves that the set of data is valid for EFA. Additionally, there are three
components extracted with greater than 1 Eigenvalue. Besides, the cumulative variance
is 70.336 %. Therefore, it can be contended that there are 3 components explaining
70.336 % of variance of CSR.

When looking at table 4.8, every items’ factor loading is higher than 0.5 and they are
loaded to each corresponding component. In other words, the first component is formed
by 6 items of CSR towards Environment, the second is defined by 5 items of CSR
towards Stakeholders and the last is defined by 5 items of CSR towards Society.

In conclusion, after doing Exploratory Factor Analysis, CSR scale has 16 items which
are grouped into CSR towards Environment, CSR towards Stakeholders and CSR
towards Society.

4.3.2 EFA of Brand Likeability scale

Table 4.9: EFA for Brand Likeability scale

(Source: Data analysis by SPSS)

Condition

Value

KMO index

0.847 Sig. (Bartlett's Test)

0.000 Total Variance Explained

81.344

</div>
(48)<div class='page_container' data-page=48>

Table 4.10: Component matrix for Brand Likeability scale

(Source: Data analysis by SPSS)

Brand likeability initially contains 4 measurement items. After doing reliability analysis,
none of them are removed. Therefore, EFA is conducted with these 4 measurement items
in order to examine convergence of items along with components, which is presented in
table 4.13.

Table 4.9 shows that KMO value is 0.847 (greater than 0.5 and less than 1) and Sig. is
0.000 ( less than 0.05). Therefore, it can be concluded that the set of data is valid for
EFA. Additionally, there is a component extracted with greater than 1 Eigenvalue.
Besides, the cumulative variance is 81.344 %. Therefore, it can be contended that there
is a component explaining 81.344 % of variance of Brand Likeability.

When looking at table 4.10, all items’ factor loading are higher than 0.5 and they are
loaded to a component, namely, Brand Likeability.

In a nutshell, Brand Likeability has 4 items that extracted to 1 component, namely, Brand
Likeability.

Component

BL4 .919

BL1 .901

BL2 .896

</div>
(49)<div class='page_container' data-page=49>

41
4.3.3 EFA of Relational Switching cost scale

Table 4.11: EFA for Relational Switching cost scale

(Source: Data analysis by SPSS)

Table 4.12: Component matrix for Relational Switching Cost scale

(Source: Data analysis by SPSS)

Relational Switching cost initially contains three measurement items. After doing
reliability analysis, none of them are removed. Therefore, the EFA is conducted with
these 3 measurement items in order to examine convergence of items along with
components, which is presented in table 4.14.

Table 4.11 indicates that KMO value is 0.708 (greater than 0.5 and less than 1) and Sig.
is 0.000 ( less than 0.05). Therefore, it can be concluded that the set of data is valid for
Exploratory Factor Analysis. Additionally, there is a component extracted with greater
than 1 Eigenvalue. Besides, the cumulative variance is 77.777 %. Therefore, it can be

Condition Value

KMO index 0.708

Sig. (Bartlett's Test) 0.000
Total Variance Explained 77.777

Eigenvalue 2.333

Component

RSC2 .916

RSC1 .871

</div>
(50)<div class='page_container' data-page=50>

contended that there is a component explaining 77.777 % of variance of Relational
Switching Cost.

When looking at table 4.12, every items’ factor loading is higher than 0.5 and they are
loaded to a component, namely, Relational Switching Cost.

In a nutshell, Relational Switching Cost has 3 items that extracted to 1 component,
namely, Relational Switching Cost.

4.3.4 EFA of WOM scale

Table 4.13: EFA for WOM scale

(Source: Data analysis by SPSS)

Table 4.14: Component matrix for WOM scale

(Source: Data analysis by SPSS)

WOM initially contains three measurement items. After doing reliability analysis, none
of them are removed. Therefore, the EFA is conducted with these three measurement

Condition Value

KMO index 0.749

Sig. (Bartlett's Test) 0.000
Total Variance Explained 83.404

Eigenvalue 2.502

Component

WOM1 .923

WOM2 .917

</div>
(51)<div class='page_container' data-page=51>

items in order to examine convergence of items along with components, which is
presented in table 4.15.

Table 4.13 shows that KMO value is 0.749 (greater than 0.5 and less than 1) and Sig. is
0.000 ( less than 0.05). Therefore, it can be concluded that the set of data is valid for
Exploratory Factor Analysis. Additionally, there is a component extracted with greater
than 1 Eigenvalue. Besides, the cumulative variance is 83.404 %. Therefore, it can be

contended that there is 1 component explaining 83.404 % of variance of Word of Mouth.
When looking at table 4.14, every items’ factor loading is higher than 0.5 and they are
loaded to a component, namely, WOM.

In conclusion, WOM has 3 items that extracted to a component.

4.3.5 EFA of Repurchase Intention scale

Table 4.15: EFA for Repurchase Intention scale

(Source: Data analysis by SPSS)

Table 4.16: Component matrix for Repurchase Intention

(Source: Data analysis by SPSS)

Condition Value

KMO index 0.755

Sig. (Bartlett's Test) 0.000
Total Variance Explained 87.507

Eigenvalue 2.625

Component

RI3 .948

RI1 .938

</div>
(52)<div class='page_container' data-page=52>

Repurchase Intention initially contains three measurement items. After doing reliability
analysis, none of them are removed. Therefore, the EFA is conducted with these three
measurement items in order to examine convergence of items along with components,
which is presented in table 4.16.

Table 4.15 shows that KMO value is 0.755 (greater than 0.5 and less than 1) and Sig. is
0.000 ( less than 0.05). Therefore, it can be concluded that the set of data is valid for
Exploratory Factor Analysis. Additionally, there is a component extracted with greater
than 1 Eigenvalue. Besides, the cumulative variance is 87.507 %. Therefore, it can be
contended that there is 1 component explaining 87.507 % of variance of Repurchase
Intention.

When looking at table 4.16, every items’ factor loading is higher than 0.5 and they are
loaded to a component, namely, Repurchase Intention.

In conclusion, Repurchase Intention has 3 items that extracted to a component.

To sum up, after doing Exploratory Factor Analysis, there is one item called “StCSR” is
removed from the model. Therefore, the model retains 29 measurement items instead of
30 items.

4.4 Regression analysis results

</div>
(53)<div class='page_container' data-page=53>

Table 4.17: Correlations

**. Correlation is significant at the 0.01 level (2-tailed).

(Source: Data analysis by SPSS)

Looking at table 4.17, it can be concluded that all dimensions of CSR have significant
relationship with BL and RSC. Additionally, it can be seen that WOM and RI
respectively have significant link with both BL and RSC. However, the correlations
among independent variables in the relationship of CSR dimensions with BL and RSC
as well as ones in the relationship of customer loyalty behaviors (WOM and RI) with BL
and RSC are really high (higher than 0.3). Therefore, it is necessary to check whether
there exists Multi-collinear problem or not by looking at Variance Inflation Factor (VIF)
value.

Table 4.18: Collinearity Statistics

Components VIF

SCSR 1.924

ECSR 1.634

STCSR 1.796

BL 1.625

RSC 1.625

(Source: Data analysis by SPSS)

SCSR ECSR StCSR BL RSC WOM RI

SCSR 1

ECSR .582** 1

StCSR .631** .540** 1

BL .658** .571** .789** 1

RSC .592** .530** .511** .620** 1

WOM .686** .568** .741** .800** .646** 1

</div>
(54)<div class='page_container' data-page=54>

Table 4.18 indicates that the VIF value of independent variables are less than 2. Hence,
there is no Multi-collinear issue and Regression Analysis is appropriate for independent
variables.

Regression analyses are used to examine the relationships in model and the results are
shown as following table:

Table 4.19: Regression analysis coefficients

(Source: Data analysis by SPSS)

Looking at table 4.19, the results of the relationship between CSR dimensions and Brand
Likeability can be seen. Adjusted R2 is 0.672, which means 67.2 % in variance of BL are

explained by three independent variables including SCSR, ECSR and STCSR. Moreover,
Sig. F is 0 < 0.05, so linear regression model is suitable for the set of data and can be
used.

More importantly, Sig. value of all three independent variables are less than 0.05.
Therefore, it can be said that all three independent variables including SCSR, ECSR and
STCSR explain dependent variable, namely, BL. In which, CSR towards stakeholders is
found to have more significant impact on BL (β = 0.584, p<0.001). The other domains
are CSR towards Society (β = 0.212, p<0.001) and CSR towards Environment(β = 0.132,

Independent variable Dependent variable

Standardized 
Coefficients

Adjusted

R2 T-value

Sig.level

(1-tailed) Resulted

H1 CSR towards Society Brand Likeability 0.212 0.672 3.872 0.000 Supported

H2 CSR towards Environment 0.132 2.620 0.0045 Supported

H3 CSR towards Stakeholders 0.584 11.052 0.000 Supported

H4 CSR towards Society Relational Switching Cost 0.352 0.408 4.794 0.000 Supported

H5 CSR towards Environment 0.239 3.537 0.000 Supported

H6 CSR towards Stakeholders 0.159 2.246 0.013 Supported

H7 Brand Likeability WOM 0.649 0.673 12.927 0.000 Supported

H9 Relational Switching Cost 0.243 4.841 0.000 Supported

H8 Brand Likeability Repurchase Intention 0.434 0.685 8.821 0.000 Supported

</div>
(55)<div class='page_container' data-page=55>

p<0.01) having lower significant effective level. Hence, hypotheses H1, H2, H3 are all
supported.

In addition, the results of the relationship between CSR dimensions and Relational
Switching can be shown in table 4.19. Adjusted R2 is 0.408, which means 40.8 % in

variance of RSC are explained by three independent variables including SCSR, ECSR
and STCSR. Moreover, Sig. F is 0 < 0.05, so linear regression model is suitable for the
set of data and can be used.

All above, Sig. value of all three independent variables are less than 0.05. Therefore, it
can be said that all three independent variables including SCSR, ECSR and STCSR
explain dependent variable, namely, RSC. Among CSR dimensions, CSR towards
Society (β = 0.352, p<0.001) and Environment (β = 0.239, p<0.001) have more
significant impact on Relational Switching Cost rather than CSR towards Stakeholders
(β = 0.159, p<0.05). Hence, hypotheses H4, H5, H6 are all supported.

Besides, table 4.19 also indicates the link of WOM with BL and RSC. Adjusted R2 is
0.673, which means 67.3 % in variance of WOM are explained by three independent
variables including BL and RSC. Moreover, Sig. F is 0 < 0.05, so linear regression model
is suitable for the set of data and can be used.

Importantly, Sig. value of all three independent variables are less than 0.05. Therefore,
it can be said that all two independent variables including BL and RSC explain dependent
variable, namely, WOM. Also, it is obvious that BL (β = 0.649, p<0.001) has more
significant on WOM rather than RSC(β = 0.243, p<0.001). Hence, hypotheses H7 and
H9 are all supported.

Last but not least, the results of the relationship of RI with BL and RSC are revealed in
table 4.19. Adjusted R2 is 0.685, which means 68.5 % in variance of WOM are explained

</div>
(56)<div class='page_container' data-page=56>

</div>
(57)<div class='page_container' data-page=57>

49
CHAPTER 5: RESULT DISCUSSION

5.1 Result discussion

This research examined the impact of 3 domains of CSR on Brand Likeability in context
of Vietnamese retailing industry. After collecting and analyzing data by SPSS software,
the obtained results shows that retail companies can increase brand likeability by
enhancing their various CSR initiatives. This finding is consistent with the previous
literature which suggested that company’s CSR effort is a predictor of branding
consequences(Sen & Bhattacharya, 2001; Hoeffler & Keller, 2002). Besides, the result
can also reveal that Vietnamese purchasers are aware of CSR initiatives of the companies
and based on that to evaluate the brands. However, impact of each domain of CSR
initiatives on Brand Likeability is not the same degree. In detail, the research indicates

that CSR towards Stakeholders has the most significant impact on Brand Likeability in
comparison with the other domains of CSR including Environment and Society. One of
possible reasons for this effective inequality among those CSR dimensions is that in
Vietnam, doing business for just profit without caring the ethical standards of companies
is very common. This is reflected in poor quality products, violating the law by tax
evasion or import of unidentified inputs..etc.., which directly affects health and benefits
of customers. Therefore, it is understandable when Stakeholders CSR which is likely to
provide direct beneﬁts to customers affects more a customer’s likeable company
evaluation.

</div>
(58)<div class='page_container' data-page=58>

Society have stronger impact on Relational Switching Cost. In other words, the study
suggests that company’s environmental and social CSR activities can much increase the
barrier which prevents Vietnamese customers from moving to another brand. It can be
understood that Vietnamese customers are aware of environmental social CSR activities
and more identify them with the companies which invested in those activities. This result
can be understandable because recently harmful activities of companies towards
environment detected have been very common in Vietnam, which has annoyed a lot of
Vietnamese people and led to their really serious responses. Besides, the Vietnamese
themselves seem to care much about charitable activities which was probably originated
from the Vietnamese’s solidarity spirit. This is clearly expressed in the popularity of
charity organization established by individual or small group of people. Hence, it might
be said that the Vietnamese in general and Vietnamese customers in particular
appreciate activities towards community and would like to show their ethical and social
image by involving in these activities or through connection with the companies
participating in these activities. It can be said that, in other words, CSR towards
environment and society which can bring the feeling of caring for others rather than just
own benefits might be supposed to able to create more favorable self-definition for
customers rather than CSR stakeholders. Therefore, investing in environmental social

CSR activities can make customers more be willing to stay with current brand in order
to avoid psychological discomfort that they can suffer in case of breaking their
identification with the company to switch to another brand.

</div>
(59)<div class='page_container' data-page=59>

Karjaluoto (2016). Besides, it is revealed that the higher likeable the companies are, the
higher level of repurchase intention they can get. The result is consistent with the
previous study that supposed that the persistence of likeability relative to other offerings
can drive customers to repurchase the products (Carroll and Ahuvia, 2006). Similarly,
Relational Switching Cost can lead to higher Repurchase Intention. The finding
consolidates the long-standing belief that makes customers stay with the companies and
is also consistent the previous researches of Burnham, et al. (2003) or Blut, et al. (2015).
Moreover, Relational Switching Cost is also found to be linked with WOM.

</div>
(60)<div class='page_container' data-page=60>

To sum up, empirical results from the study can help the company understand and learn
more about customer responses towards CSR initiatives. According to the findings from
the research, it is obvious that Vietnamese customers are increasingly aware of various
CSR practices and take into account CSR activities when evaluating the brand and
considering moving to another brand. In other words, CSR activities can increase Brand
Likeability and Relational Switching Cost which can enhance customer loyalty.
Therefore, investing in CSR practices is necessary for Vietnamese companies. However,
in reality, not all companies can integrate various CSR into their business because of
limited resource. It is the fact that of the more than 500,000 businesses currently, 97%
are small and medium enterprises (SME) according to data from the Vietnam Chamber
of Commerce and Industry (VCCI). Therefore, the study’s findings of differently
effective level of various CSR practices can provide evidence to suggest small and
medium Vietnamese retail companies electing to relatively more concentrate on the

stakeholders CSR activities.

5.2 Contributions of the research

5.2.1 Theoretical contribution

</div>
(61)<div class='page_container' data-page=61>

perspective. In detail, this study reveals the positive relationship between CSR activities
and Brand Likeability. Besides, the study also reveals the effect of various CSR on
Relational Switching Cost which has not been gotten much attention in previous
literature.

Another contribution to the literature of this study is providing effect of each domain of
CSR on Brand Likeability and Relational Switching Cost. The finding indicates that CSR
towards stakeholders has the most significant impact on CSR activities’ relationship with
Brand Likeability while CSR towards Environment and Society are more significant
predictors in CSR activities’ relationship with Relational Switching Cost. Moreover, the
study also provides the relationship between Brand Likeability and Relational Switching
Cost and customer loyalty behaviors including WOM and Repurchase Intention. Word
of Mouth is found to be impacted more significantly by Brand Likeability than
Repurchase Intention. Whereas, the relatively equal effective degree of Brand
Likeability and Repurchase Intention on Repurchase Intention is also revealed.

5.2.2 Practical contribution

</div>
(62)<div class='page_container' data-page=62>

Although benefits and advantages that investing in various CSR activities brings for
companies cannot be denied, not many Vietnamese companies have enough resources

for all of them at once. It is the fact that there are up to 97 % of SME in Vietnam.
Therefore, the study provides an evidence of the different effective level of CSR
dimensions on Brand Likeability and Relational Switching Cost. Therefore, depending
on their different purpose and strategy, the companies can choose to integrate suitable
CSR activities into their business to enhance positive customer responses which leads to
an increase in customer loyalty. In detail, if a company would like to make it more
likeable by their customers and spread that love to more potential customers through
word of mouth communication, it should focus much on satisfying stakeholders by
creating “fair trade relationships with suppliers or safe workplace conditions” (Vermeir
and Verbeke, 2006) or “a law-abiding image” McWilliams and Siegel (2001); because
CSR towards Stakeholder is found to have the most significant influence on customers’
liking for brands. Besides, if a company would like to positively prevent customers from
moving to other brands or increase repurchase intention, it ought to invest more in CSR
activities related to Society and Environment, for instance, by showing their
environment-friendly image or donating for projects related to community’s well-being;
because they are factors affecting more significantly Relational Switching Cost.

While increasing brand likeability and relational switching costs can have different
benefits and can positively affect customer loyalty in general, brand likeability is a little
bit better than relational switching cost because While the effect of these two factors on
both repurchase intention is almost the same, brand likeability is found to have a much
stronger effect on word of mouth. Therefore, for those companies that are too limited in
resources, investing in CSR activities for stakeholders, the one that affects the Brand
Likeability most strongly seems to be the most economical and optimal option.

</div>
(63)<div class='page_container' data-page=63>

really necessary. Companies should integrate their CSR activities into advertisements
for their products to increase customer awareness about CSR. Moreover, nowadays, with
the popularity of the internet, companies should also take advantage to communicate

their CSR activities on online sites. For example, the company can create its fan page on
some social networking sites such as facebook or instagram. In addition to promoting
the company's main activities and products, the company can also post its CSR activities
there. Moreover, the company can also launch environmental or charitable activities that
encourage customer contribution and cooperation. These activities not only promote the
company's CSR image but can also create cohesion between the company and its
customers.

5.3 Limitations and future research direction

This study analyzed how CSR performance affects Brand Likeability and Relational
Switching Cost in Vietnamese retail industry. Because each industry has different
property and characteristics, the findings cannot be generalized and applied for all
industry. Therefore, it is impossible for other authors to explore these relationship in
other industries. In turn, the comparison among industries is highly recommended.
Besides, the study is conducted in only Hanoi and the respondents are mostly highly
educated. Therefore, it is difficult for it to be representative for all throughout countries.
It can be suggested for other authors to conduct this research with more various sample
in term of location and education level as well.

</div>
(64)<div class='page_container' data-page=64>

future may need to consider data collection by interviewing to get more insight about
this phenomenon.

Additionally, although word of mouth is still one of the effective ways to attract more
customers, it has changed to new form before the popularity of the internet today. In
particular, instead of face-to-face sharing experiences of buying or using products or
services, customers have become accustomed to sharing them on various media channels
such as social networking sites or review sites, which is called electronic word of mouth

(eWOM). eWOM has been becoming increasingly so prominent that “77 percent of
online consumers check online reviews and ratings of products before deciding to make
a purchase” ( Mc Guigan, 2008). Therefore, that just focusing on general word of mouth
can be considered as the study’s limitation. Hence, eWOM can be suggested for other
authors in the future.

</div>
(65)<div class='page_container' data-page=65>

REFERENCE

Abbas, M., Gao, Y. & Shah, S. R. A., 2018. CSR and Customer Outcomes: The
Mediating Role of Customer Engagement. Multidisciplinary Digital Publishing Institute, 
Volume 10, p. 4243.

Akroush, M. N., 2012. An empirical model of marketing strategy and shareholders value:
A value based marketing perspective. Competiveness Review: An International Business

Journal, 22(1), pp. 48-89.

Albert, N. & Merunka, D., 2013. The role of brand love in consumer-brand relationships.

Journal of Consumer Marketing, 30(3), pp. 258-266.

Anderson, E. W. & Sullivan, M. W., 1993. The antecedents and consequences of
customer satisfaction for firms. Marketing Science, 12(2), pp. 125-143.

Andreassen, T. W. & Lindestad, B., 1998. Customer loyalty and complex services.

International Journal of Service Industry Management, 9(1), pp. 7-23.

Angelis, M. D. et al., 2012. On Braggarts and Gossips: A Self-Enhancement Account of
Word-of-Mouth Generation and Transmission. Journal Of Marketing Research, 49(4), 
p. 552.

Aquino, K. & Reed, A. I., 2002. The self-importance of moral identity.. Journal of

Personality and Social Psychology, 83(6), pp. 1423-1440.

Arndt, J., 1967. Role of Product-Related Conversations in the Diffusion of a New
Product. Journal of Marketing Research, 4(3), pp. 291-295.

</div>
(66)<div class='page_container' data-page=66>

Bansal, H. S. & Taylor, S. F., 19999. "The Service Provider Switching Model (SPSM).

Journal of Service Research , 2(2), pp. 200-218.

Banyte, J., Brazioniene, L. & Gadeikiene, A., 2010. Expression of Green Marketing
Developing the Conception of Corporate Social Responsibility. Engineering Economics , 
21(5), pp. 550-560.

Barroso, C. & Picón, A., 2012. Multi-dimensional analysis of perceived switching costs.

Industrial Marketing Management, 41(3), pp. 531-543.

Batra, R., Ahuvia, A. C. & Bagozzi, R., 2012. Brand love. Journal of Marketing , 76(2), 
pp. 1-16.

Bearden, W. O. & Teel, J. E., 1983. Selected determinants of consumer satisfaction and
complaint reports. Journal of Marketing Research, 20(1), pp. 21-28.

Bitner, M. J., 1990. Evaluating Service Encounters: The Effects of Physical
Surroundings and Employee Responses. Journal of Marketing, 54(2), pp. 69-82.

Bloch, P. H., 1986. the product enthusiast: implications for marketing strategy. Journal of

Consumer Marketing, 3(3), pp. 51-62.

Blut, M. et al., 2016. Securing Business-to-Business Relationships: The Impact of
Switching Costs. Industrial Marketing Management, Volume 52, pp. 82-90.

</div>
(67)<div class='page_container' data-page=67>

Burnham, T., Frels, J. & Mahajan, V., 2003. Consumer Switching Costs: A Typology,
Antecedents, and Consequences. Journal of the Academy of Marketing Science, 31(2), 
p. 109.

Cakim, I. M., 2010. Implementing word of mouth marketing: online strategies toidentify

influencers, craft stories, and draw customers. s.l.:John Wiley & Sons..

Campbell, D. T. & Fiske, D. W., 1959. Convergent and discriminant validation by the
multitrait-multimethod matrix. Psychological Bulletin, 56(2), p. 81–105.

Carroll, A. B., 1991. The pyramid of corporate social responsibility: Toward the moral
management of organizational stakeholders. Business Horizons, 34(4), pp. 39-48. 
Carroll, A. B. & Shabana, K., 2010. The business case for corporate social responsibility:
A review of concepts, research, and practice. International Journal of Management

Reviews, 12(1), pp. 85-105.

Carroll, B. A. & Ahuvia, A. C., 2006. Some Antecedents and Outcomes of Brand Love.

Marketing Letters, 17(2), pp. 79-89.

Castaldo, S., Perrini, F., Misani, N. & Tencati, A., 2009. The Missing Link Between
Corporate Social Responsibility and Consumer Trust: The Case of Fair Trade Products.

Journal of Business Ethics, 84(1), pp. 1-15.

Castro-Gonzalez, S., Bande, B., Fernandez-Ferrín, P. & Kimura, T., 2019. Corporate
social responsibility and consumer advocacy behaviors: The importance of emotions and
moral virtues. Journal of Cleaner Production, Volume 231, pp. 846-855.

</div>
(68)<div class='page_container' data-page=68>

Chen, Y.-S., 2010. The Drivers of Green Brand Equity: Green Brand Image, Green
Satisfaction, and Green Trus. Journal of Business Ethics, 93(2), pp. 307-319.

Choi, B. & La, S., 2013. The impact of corporate social responsibility (CSR) and
customer trust on the restoration of loyalty after service failure and recovery. Journal of

Services Marketing, 27(3), pp. 223-233.

Cialdini, R. B., 1993. Influence: Science and Practice. 3 ed. s.l.:New York: 
HarperCollins .

Clarkson, M. B. E., 1995. A stakeholder framework for analyzing and evaluating
corporate social performance. The Academy of Management Review, 20(1), pp. 92-117. 
Cox, J., 2001. Can differential price be far?. Journal of product and brand managment,

10(5), pp. 264-275.

Creyer, E. H., 1997. The inﬂuence of ﬁrm behavior on purchase intention: do consumers
really care about business ethics. Journal of Consumer Marketing,, 14(6), pp. 421-432. 
Crittenden, K. S., 1983. Sociological aspect of attribution. Annual Reviews of sociology, 
Volume 9, pp. 425-446.

Dahlsrud, A., 2008. How corporate social responsibility is deﬁned: an analysis of 37
deﬁnitions. Corporate Social Responsibility and Environmental Management , 15(1), 
pp. 1-13.

Derbaix, C. & Vanhamme, J., 2003. Inducing word-of-mouth by eliciting suprise-a pilot
investigation. Journal of Economic Psychology , 24(1), pp. 99-116.

</div>
(69)<div class='page_container' data-page=69>

Ebrahim, R., Ghoneim, A., Irani, Z. & Fan, Y., 2016. A brand preference and repurchase
intention model: the role of consumer experience. Journal of Marketing Management, 
32(13/14), pp. 1230-1259.

Fang, Y.-H., Chiu, C.-M. & Wang, E. T. G., 2011. Understanding Customers'
Satisfaction and Repurchase Intentions: An Integration of IS Success Model, Trust, and
Justice. Internet Research, 21(4), pp. 479-503.

Fazal-e-Hasan, S. M., Lings, I. N., Mortimer, G. & Neale, L., 2017. How Gratitude
Influences Customer Word-OfMouth Intentions and Involvement: The Mediating.

Journal of Marketing Theory and Practice, 25(2), pp. 200-211.

Fishbein, M. A. & Ajzen, I., 1975. Belief, attitude, intention and behavior: An

introduction to theory and research. Addison-Wesley ed. s.l.:MA.

Fournier, S., 1998. Consumers and Their Brands: Developing Relationship Theory in
Consumer Research. Journal of Consumer Research, 24(4), pp. 343-353.

Galbreath, J., 2010. How does corporate social responsibility benefit firms? Evidence
from Australia. European Business Review, 22(4), pp. 411-431.

George, D. & Mallery, P., 2010. SPSS for Windows Step-by-Step: A Simple Guide and

Reference, 14.0 update. 7th ed. Boston: Pearson.

Gürlek, M., Duzgun, E. & Uygur, S. M., 2017. How does corporate social responsibility
create customer loyalty? The role of corporate image. Social Responsibility Journal, 
13(3), pp. 409-427.

</div>
(70)<div class='page_container' data-page=70>

Hassan, Z. & Nareeman, A., 2013. Impact of CSR Practices on Customer Satisfaction
and Retention: An Empirical Study on Foreign MNCs in Malaysia. International Journal

of Accounting and Business Management, 1(1), pp. 63-81.

Heikki Karjaluoto, J. M. K. K., 2016. Brand love and positive word of mouth: the
moderating effects. Journal of Product & Brand Management, 25(6), pp. 527-537. 
Hellier, P. K., Geursen, G. M., Carr, R. & Rickard, J. A., 2003. Customer repurchase
intention: A general structural equation model. European Journal of Marketing, 
37(11/12), p. 1762–1800.

Hemingway, C. A. & Maclagan, P. W., 2004. Managers' Personal Values as Drivers of
Corporate Social Responsibility. Journal of Business Ethics, 50(1), pp. 33-44.

Ho, C.-W., 2017. Does Practicing CSR Makes Consumers Like Your Shop More?
Consumer-Retailer Love Mediates CSR and Behavioral Intentions. International

Journal of Environmental Research and Public Health, 14(12), p. 1558.

Hoeffler, S. & Keller, K. L., 2002. Building Brand Equity Through Corporate Societal
Marketing. Journal of Public Policy & Marketing , 21(1), pp. 78-89.

Howard Bowen, 1953. Social Responsibilities of the Businessman. s.l.:Harper and Row: 
New York.

Huddleston, P., Whipple, J. M. & VanAuken, A., 2004. Food store loyalty: Application
of a consumer loyalty framework. Journal of Targeting Measurement and Analysis for

Marketing , 12(3), pp. 213-230.

Hunt, H. K., 1977. CS/D : overview and future research directions. In: H. K. Hunt, ed.

Conceptualization and measurement of consumer satisfaction and dissatisfaction.

</div>
(71)<div class='page_container' data-page=71>

Ibzan, E., Balarabe, F. & Jakada, B., 2016. Consumer Satisfaction and Repurchase
Intentions. Developing Country Studies , 6(2), pp. 96-100.

Innis, D. E., 1991. Customer service, repurchase intentions, market orientation and firm
performance in the channel. Ohio State University.

Jones, P., Comfort, D. & Hillier, D., 2007. What's in store? Retail marketing and
corporate social responsibility. Marketing Intelligence & Planning, 25(1), pp. 17-30. 
Kasliwal, N., Khan, I. & Joshi, M. C., 2017. Corporate Social Responsibility and
Consumer Behavior: A Review to Establish a Conceptual Model. International Journal

of Emerging Research in Management &Technology, 6(9), pp. 2278-9359.

Keller, K. L., 2001. Building customer-based brand equity: creating brand resonance
requires carefully sequenced brand-building efforts. Marketing Management, 10(2), pp. 
15-19.

Kelly, L., 2007. Beyond buzz: The next generation of word-of-mouth marketing. 
s.l.:Amacom Books.

Kennedy, M. S., Ferrell, L. & LeClair, D. T., 2001. Consumers' trust of salesperson and
manufacturer: an empirical study. Journal of Business Research,. Journal of Business

Research , 51(1), pp. 73-86.

Kenrick, D. T., Neuberg, S. L. & Cialdini, R. B., 2002. Social Psychology: Unraveling

the Mystery. 2 ed. Boston: MA: Allyn & Bacon.

</div>
(72)<div class='page_container' data-page=72>

Kiziltas, O. & Çalıyurt, K. T., 2018. Corporate Social Responsibility in the Retail Sector:
A Case from Turkey. In: Sustainability and Social Responsibility of Accountability

Reporting Systems. s.l.:s.n., pp. 95-124.

Klemperer, P. D., 1987. Markets With Consumer Switching Costs. Quarterly Journal of

Economics, 102(2), pp. 375-394.

Knox, S. & Maklan, S., 2004. Corporate social responsibility: moving beyond
investment towards measuring outcomes. European Management Journal, 22(5), pp. 
508-516.

Kotler, P., 1991. Marketing Management: Analysis, Planning, Implementation, and

Control. 7th ed. Englewood Cliffs: NJ:Prentice Hall.

Kucukusta, D., Mak, A. & Chan, X., 2013. Corporate social responsibility practices in
four and five-star hotels: Perspectives from Hong Kong visitors. International Journal

of Hospitality Management, Volume 34, pp. 19-30.

Kudeshia, C., Sikdar, P. & Mittal, A., 2016. Spreading love through fan page liking: a
perspective on small scale entrepreneurs. Computers in Human Behavior, Volume 54, 
pp. 257-270.

Kukar-Kinney, M., Xia, L. & Monroe, K. B., 2007. Consumers' perceptions of the
fairness of price-matching refund policies. Journal of Retailing, 83(3), pp. 325-337. 
Laroche, M., Bergeron, J. & Barbaro‐Forleo, G., 2001. Targeting consumers who are
willing to pay more for environmentally friendly products. Journal of Consumer

Marketing, 18(6), pp. 503-520.

Lee, S., Seo, K. & Sharma, A., 2013. Corporate social responsibility and ﬁrm

performance in the airline industry: The moderating role of oil prices. Tourism

</div>
(73)<div class='page_container' data-page=73>

Lee, Y.-K., Kim, S. Y., Lee, K. H. & Li, D.-x., 2012. The impact of CSR on relationship
quality and relationship outcomes: A perspective of service employees. International

Journal of Hospitality Management , 31(3), pp. 745-756.

Lev, B., Petrovits, C. & Radhakrishnan, S., 2010. Is doing good good for you? how
corporate charitable contributions enhance revenue growth. Strategic Managment

Journal, 31(2), pp. 182-200.

Liu, M. T. et al., 2014. The impact of corporate social responsibility (CSR) performance
and perceived brand quality on customer-based brand preference. Journal of Services

Marketing, 28(3), pp. 181-194.

Luo, X. & Bhattacharya, C., 2006. Corporate social responsibility, customer satisfaction,
and market value.. Journal of Marketing, 70(4), pp. 1-18.

Maignan, I. & Ferrell, O., 2001. Corporate citizenship as a marketing instrument ‐
Concepts, evidence and research directions. European Journal of Marketing, 35(3/4), pp. 
457-484.

Maignan, I. & Ferrell, O. C., 2004. Corporate social responsibility and marketing: an
integrative framework. Journal of the Academy of Marketing Science, 32(1), pp. 3-19. 
Maignan, I., Ferrell, O. C. & Hult, G. T. M., 1999. Corporate Citizenship: Cultural
Antecedents and Business Benefits. Journal of the Academy of Marketing Science, 27(4),

pp. 455-469.

Maloni, M. J. & Brown, M. E., 2006. Corporate social responsibility in the supply chain:
an application in the food industry. Journal of Business Ethics, 68(1), pp. 35-52.

</div>
(74)<div class='page_container' data-page=74>

Maon, F., Lindgreen, A. & Swaen, V., 2010. Organizational Stages and Cultural Phases:
A Critical Review and a Consolidative Model of Corporate Social Responsibility
Development. International Journal of Management Reviews, 12(1), pp. 20-38.

Marcos, A., 2018. The Role of the Positive Switching Costs in the Insurance Industry.

International Journal of Marketing, Communication and New Media , 10(6), pp. 7-31.

Marcos, A. & Coelho, A., 2017. Antecedents and consequences of perceived value in
the insurance industry. European Journal of Applied Business Management, 3(2), pp. 
29-51.

Marquina, P. & Vasquez-Parraga, A. Z., 2013. Consumer social responses to CSR
initiatives versus corporate abilities. Journal of Consumer Marketing, 30(2), pp. 
100-111.

Martínez, P. & Bosque, I. R. d., 2013. CSR and customer loyalty: The roles of trust,
customer identification with the company and satisfaction. International Journal of

Hospitality Management, Volume 35, pp. 89-99.

Martinuzzi, A., Kudlak, R., Faber, C. & Wiman, A., 2011. CSR Activities and Impacts
of the Retail Sector. RIMAS Working Papers, Volume 4.

McGuire, W., 1985. Attitudes and attitude change. 2 ed. New York: In: Lindzey, G. and 
Aronson, E., Eds., Handbook of Social Psychology.

Meijer, M.-M. & Schuyt, T., 2005. Corporate Social Performance as a Bottom Line for
Consumers. Business and Society, 44(4), pp. 442-461.

</div>
(75)<div class='page_container' data-page=75>

Mohr, L. A. & Webb, D. J., 2005. The effects of corporate social responsibility and price
on consumer responses. Journal of Consumer Affairs, 39(1), pp. 121-147.

Mohr, L. A., Webb, D. J. & Harris, K. E., 2001. Do Consumers Expect Companies to be
Socially Responsible? The Impact of Corporate Social Responsibility on Buying
Behavior. The Journal of Consumer Affairs, 39(1), pp. 45-72.

Morgan, R. M. & Hunt, S., 1994. The commitment-trust theory of relationship marketing.

Journal of Marketing, 58(3), pp. 20-38.

Mostafa, R. B. & ElSahn, F., 2016. Exploring the mechanism of consumer responses to
CSR activities of Islamic banks The mediating role of Islamic ethics fit. International

Journal of Bank Marketing, 34(6), pp. 940 - 962 .

Murray, K. & Vogel, C. M., 1997. Using a hierarchy-of-effects approach to gauge the
effectiveness of corporate social responsibility to generate goodwill toward the firm:
Financial versus nonfinancial impacts. Journal of Business Research, 38(2), pp. 141-159. 
Nareeman, A. & Hassan, Z., 2013. Customer perceived practice of CSR on improving
customer satisfaction and loyalty. International Joural of Accounting and Business

Management, 1(1), pp. 30-49.

Nguyen, B., Melewar, T. & Chen, J., 2013. A framework of brand likeability: an
exploratory study of likeability in firmlevel brands. Journal of Strategic Marketing, 
21(4), pp. 369-390.

Nguyen, B., T.C.Melewar & Chen, J., 2013. The brand likeability effect: can firms make
themselves more likeable?. Journal of general management, 38(3), pp. 25-50.

</div>
(76)<div class='page_container' data-page=76>

Oliver, R. L., 1980. A Cognitive Model of the Antecedents and Consequences of
Satisfaction Decisions. Journal of Marketing Research, 17(4), pp. 460-469.

Özer, G., Kazan, H. & Cüneyd, M., 2009. The Measurement of Switching Costs as a
Perception of Customer in the Turkish Credit Card Market. Journal of Electrical and

Electronics Engineering, 9(2), pp. 1015-1028.

Patterson, P. G., “A”, R. M. & Smith, T., 2001. Switching Costs as a Moderator of
Service Satisfaction Processes in Thailand. Journal of International Consumer

Marketing, 14(1), pp. 1-21.

Pedersen, E. R., 2010. Modeling CSR: how managers understand the responsibilities of
business towards society. Journal of Business Ethics , 91(2), pp. 155-166.

Peloza, J. & Shang, J., 2011. How can corporate social responsibility activities create
value for stakeholders? A systematic review. Journal of the Academy of Marketing

Science, 39(1), pp. 117-135.

Pérez, A. & Bosque, I., 2015. An Integrative Framework to Understand How CSR
Affects Customer Loyalty through Identification, Emotions and Satisfaction. Journal of

Business Ethics, 129(3), pp. 571-584.

Pérez, A. & Rodríguez-del-Bosque, I., 2015. Corporate social responsibility and
customer loyalty: Exploring the role of identification, Satisfaction and type of company.

Journal of Services Marketing, 29(1), pp. 15-25.

Pérez, A., Salmones, M. d. M. G. d. l. & Bosque, I. R. d., 2013. The effect of corporate
associations on consumer behaviour. European Journal of Marketing, 47(1/2), pp. 
218-238.

</div>
(77)<div class='page_container' data-page=77>

Polychronidou, P., Ioannidou, E. & Kipouros, A., 2014. Corporate
socialresponsibilityinGreekbankingsector – anempiricalresearch. Procedia Economics

and Finance, Volume 9, p. 193–199.

Porter, M. E., 1998. Competitive Advantage: Creating and Sustaining Superior

Performance. New York: The Press.

Porter, M. E. & Kramer, M. R., 2007. Strategy & society: The link between competitive
advantage and corporate social responsibility. Harvard business review , 84(12), pp.

78-92.

Rahbar, E. & Wahid, N. A., 2011. Investigation of green marketing tools’ effect on
consumers’ purchase behavior. Business Strategy Series, 12(2), pp. 73-83.

Rashid, N. R. N. A., Khalid, S. A. & rahman, N. i. a., 2015. Environmental Corporate
Social Responsibility (ECSR): Exploring its Influence on Customer Loyalty. Procedia

Economics and Finance, Volume 31, pp. 705-713.

Reichheld, F. F. & W. Earl Sasser, J., 1990. Zero Defections: Quality Comes to Services.

Harvard Business Review 68, Volume 5, pp. 105-111.

Reysen, S., 2005. Construction of a new scale: The Reysen Likability Scale. Social

Behavior and Personality An International Journa, 33(2), pp. 201-208.

Rezvani, S., Dehkordi, G. J., Rahman, M. S. & Fouladivanda, F., 2012. A Conceptual
Study on the Country of Origin Effect on Consumer Purchase Intention. Canadian

Center of Science and Education, 8(12), pp. 205-215.

</div>
(78)<div class='page_container' data-page=78>

Rives, L. M., Maya, S. R. d. & Bón, A. R., 2009. The Role of Identity Salience in the
Effects of Corporate Social Responsibility on Consumer Behavior. Journal of Business

Ethics, 84(1), pp. 65-78.

Roest, H. & Pieters, R., 1997. The nomological net of perceived service quality. The

nomological net of perceived service quality, 8(4), pp. 336-351.

Rowley, T. & Berman, S., 2000. A Brand New Brand of Corporate Social Performance.

Business & Society, 39(4), pp. 397-418.

Saleem, F. & Gopinath, C., 2015. Corporate Social Responsibility and Customer
Behavior: A. The Lahore Journal of Business, 4(1), pp. 1-22.

Schlesinger, L. A. & Heskett, J., 1991. The Service Driven Service Company. Harvard

Business Review 69, Volume 5, pp. 71-81.

Sen, S. & Bhattacharya, C., 2001. Does Doing Good Always Lead to Doing Better?
Consumer Reactions to Corporate Social Responsibility. Journal of Marketing Research, 
38(2), pp. 225-243.

Sen, S., Bhattacharya, C. & Korschun, D., 2006. The role of corporate social
responsibility in strengthening multiple stakeholder relationships: a ﬁeld experiment.

Journal of the Academy of Marketing Science, 34(2), pp. 158-166.

Sheodon, O., 1923. The philosophy of management. Sir Issac Pitman & Sons, Bath,

England.

</div>
(79)<div class='page_container' data-page=79>

Suetrong, P., Pires, G. D. & Chen, T., 2018. Conceptualising the effect of brand love on
consumers’ repurchase intentions for consumer products. Global Business and

Economics Review, 20(2), pp. 213-230.

Taghizadeh, H., Taghipourian, M. J. & Khazaei, A., 2013. The Effect of Customer
Satisfaction on Word of Mouth Communication. Research Journal of Applied Sciences,

Engineering and Technology, 5(8), pp. 2569-2575.

Turker, D., 2009. Measuring corporate social responsibility: a scale development study.

Journal of Business Ethics, 85(4), pp. 411-427.

Vasudevan, H., Gaur, S. S. & Shinde, R. K., 2006. Relational switching costs,
satisfaction and commitment A study in the Indian manufacturing context. Asia Pacific

Journal of Marketing and Logistics, 18(4), pp. 342 - 353 .

Vlachos, P. A., Tsamakos, A., Vrechopoulos, A. P. & Avramidis, P., 2008. Corporate
social responsibility: attributions, loyalty, and the mediating role of trust. Journal of the

Academy of Marketing Science, 37(2), pp. 170-180.

Wallace, E., Buil, I. & Chernatony, L. d., 2014. Consumer engagement with
self-expressive brands: Brand love and WOM outcomes. Journal of Product & Brand

Managemen, 23(1), pp. 33-42.

Wang, J. & WU, L., 2016. The impact of emotions on the intention of sustainable

consumption choices: evidence from a big city in an emerging country. Journal of

Cleaner Production, Volume 126, pp. 325-336.

</div>
(80)<div class='page_container' data-page=80>

APPENDIX 1. QUESTIONNAIRE

Introduction 
Welcome to my survey!

I am studying Master of Business Administration program at Vietnam Japan University
- Vietnam National University, Hanoi. Currently, I am doing a research related to
customer behaviors. My research cannot be completed without your helps. Therefore, I
hope that you can feel comfortable to share your opinion by answering some following
questions. I guarantee that your answers will be kept strictly confidential and used for
scientific research purpose only. Thank you once again for spending your time answering
these questions.

Survey 
Section 1: Personal background

1. Gender: ________________
2. Age:___________________
3. Educational level:_________
4. Monthly income:__________
Section 2: Measuring the constructs

- Please name the supermarket you have purchased recently:

- Please answer the following questions about the supermarket you mentioned
above:

Statement Agreement extent

This brand is trying to sponsor educational
program

</div>
(81)<div class='page_container' data-page=81>

This brand is trying to carry out program to
reduce pollution

1 2 3 4 5

It is likely that I will continue purchasing
products from this brand in the future

1 2 3 4 5

This brand is trying to make financial
donations to social causes

1 2 3 4 5

This brand is trying to protect the
environment

1 2 3 4 5

I would say that the brand is approachable. 1 2 3 4 5

Customers’ satisfaction is highly important
for this brand

1 2 3 4 5

I say positive things about this brand to
others.

1 2 3 4 5

This brand is trying to carry out program to
reduce pollution

1 2 3 4 5

This brand is trying to recycle its waste
materials properly

1 2 3 4 5

This brand is trying to use only the necessary
natural resources

1 2 3 4 5

This brand respects consumer rights
beyond the legal requirements

1 2 3 4 5

It is important for me that this brand is a
trusted corporation (when I bethink of
factors like pricing, service quality etc.)

1 2 3 4 5

If I could, I would like to continue purchase
products of this brand

</div>
(82)<div class='page_container' data-page=82>

This brand is trying to help to improve
quality of life in the local community

1 2 3 4 5

This brand complies with legal regulations
completely and promptly

1 2 3 4 5

I intend to continue purchasing products
from this brands in the future

1 2 3 4 5

This brand is trying to sponsor
pro-environmental program

1 2 3 4 5

I feel attached to this brand. 1 2 3 4 5

I am thinking positive about this brand 1 2 3 4 5

Pornography, gambling and drug abuse are
prohibited in this brand

1 2 3 4 5

This brand is trying to allocate resources to
offer services compatible with the
environment

1 2 3 4 5

I mention favorable things of this brand to
friends, relatives and other people.

1 2 3 4 5

The name (brand) of this brand is important
for me

1 2 3 4 5

This brand provides full and accurate
information about its products/services to

customers

1 2 3 4 5

I recommend the services or products of this
brand to friends, relatives and other people.

1 2 3 4 5

This brand provides a healthy and safe
working environment for employees

</div>
(83)<div class='page_container' data-page=83>

This brand is trying to sponsor public health
program

1 2 3 4 5

I believe that this brand continues to get
better and better.

1 2 3 4 5

This brand is trying to sponsor cultural
program

1 2 3 4 5

</div>
(84)<div class='page_container' data-page=84>

APPENDIX 2. CRONBACH’S ALPHA

CSR towards Society-SCSR scale

Reliability Statistics 
Cronbach's

Alpha

N of
Items

.878 5

Item-Total Statistics 
Scale Mean

if Item
Deleted

Scale
Variance if
Item Deleted

Corrected
Item-Total
Correlation

Cronbach's

Alpha if
Item Deleted

SCSR1 13.79 10.860 .720 .850

SCSR2 13.73 11.034 .731 .847

SCSR3 13.86 11.863 .617 .873

SCSR4 13.67 10.753 .746 .843

SCSR5 13.59 10.697 .734 .846

CSR towards Environment-ECSR scale

Reliability Statistics 
Cronbach's

Alpha

N of
Items

</div>
(85)<div class='page_container' data-page=85>

77
Item-Total Statistics 
Scale Mean
if Item
Deleted
Scale
Variance if

Item
Deleted
Corrected
Item-Total
Correlation
Cronbach's
Alpha if
Item
Deleted

ECSR1 16.71 18.282 .776 .898

ECSR2 16.52 18.810 .689 .910

ECSR3 16.56 17.689 .809 .893

ECSR4 16.48 17.521 .799 .894

ECSR5 16.70 18.684 .690 .909

ECSR6 16.75 17.850 .802 .894

CSR towards Stakeholder-StCSR scale

Reliability Statistics 
Cronbach's

Alpha

N of

Items

.912 6

Item-Total Statistics 
Scale Mean
if Item
Deleted
Scale
Variance if
Item
Deleted
Corrected
Item-Total
Correlation
Cronbach's
Alpha if
Item
Deleted

StCSR1 19.62 11.847 .775 .893

</div>
(86)<div class='page_container' data-page=86>

StCSR3 19.44 10.807 .803 .890

StCSR4 19.49 12.194 .750 .897

StCSR5 19.61 12.078 .730 .899

StCSR6 19.22 12.133 .670 .908

Brand Likeability – BL scale

Reliability Statistics 
Cronbach's

Alpha

N of
Items

.923 4

Item-Total Statistics 
Scale Mean

if Item
Deleted

Scale
Variance if

Item
Deleted

Corrected
Item-Total
Correlation

Cronbach's
Alpha if

Item
Deleted

BL1 11.67 5.311 .821 .901

BL2 11.97 4.909 .812 .903

BL3 11.68 5.138 .807 .904

</div>
(87)<div class='page_container' data-page=87>

79
Relational Switching cost-RSC scale

Reliability Statistics 
Cronbach's

Alpha

N of
Items

.855 3

Item-Total Statistics 
Scale Mean

if Item
Deleted

Scale
Variance if

Item
Deleted

Corrected
Item-Total
Correlation

Cronbach's
Alpha if

Item
Deleted

RSC1 7.15 2.622 .706 .817

RSC2 7.19 2.650 .794 .738

RSC3 7.48 2.668 .687 .835

Word of Mouth-WOM scale

Reliability Statistics 
Cronbach's

Alpha

N of
Items

</div>
(88)<div class='page_container' data-page=88>

80
Item-Total Statistics 
Scale Mean
if Item
Deleted
Scale
Variance if
Item
Deleted
Corrected
Item-Total
Correlation
Cronbach's
Alpha if
Item
Deleted

WOM1 7.31 2.763 .821 .841

WOM2 7.32 2.797 .809 .851

WOM3 7.32 2.720 .777 .880

Repurchase Intention-RI scale

Reliability Statistics 
Cronbach's

Alpha

N of
Items

.929 3

Item-Total Statistics 
Scale Mean
if Item
Deleted
Scale
Variance if
Item
Deleted
Corrected
Item-Total
Correlation
Cronbach's
Alpha if
Item
Deleted

RI1 7.72 2.865 .857 .893

RI2 7.70 2.998 .824 .920

</div>
(89)<div class='page_container' data-page=89>

APPENDIX 3. EFA

CSR scale-1st test

KMO and Bartlett's Test 
Kaiser-Meyer-Olkin Measure of

Sampling Adequacy. .931

Bartlett's Test of
Sphericity

Approx.
Chi-Square

2512.4
91

df 136

Sig. .000

Total Variance Explained 
Compon

ent

Initial Eigenvalues Extraction Sums of
Squared Loadings

Rotation Sums of
Squared Loadings
Total % of

Variance
Cumul
ative
%
Tota
l
% of
Varia
nce
Cumul
ative
%
Tota
l
% of
Varia
nce
Cumul
ative
%

1 8.645 50.855 50.855 8.64

50.85

5 50.855
4.29
5
25.26
7
25.26
7

2 1.943 11.428 62.283 1.94

11.42

8 62.283
4.05
1
23.83
1
49.09
9

3 1.310 7.704 69.987 1.31

0 7.704 69.987
3.55
1
20.88
8

69.98
7

4 .730 4.293 74.279

5 .557 3.275 77.554

</div>
(90)<div class='page_container' data-page=90>

Rotated Component Matrixa

Component

1 2 3

ECSR3 .836

ECSR4 .829

ECSR6 .813

ECSR1 .801

ECSR2 .716

ECSR5 .692

StCSR4 .793

StCSR2 .790

StCSR3 .787

StCSR6 .763

7 .449 2.644 83.399

8 .406 2.391 85.790

9 .381 2.239 88.029

10 .376 2.210 90.239

11 .307 1.806 92.045

12 .298 1.754 93.798

13 .263 1.546 95.344

14 .217 1.274 96.618

15 .205 1.208 97.826

16 .198 1.165 98.991

17 .172 1.009 100.00

</div>
(91)<div class='page_container' data-page=91>

StCSR1 .745

StCSR5 .640 .453

SCSR4 .761

SCSR2 .756

SCSR3 .737

SCSR1 .715

SCSR5 .709

CSR scale-2nd test

KMO and Bartlett's Test 
Kaiser-Meyer-Olkin Measure of Sampling

Adequacy. .926

Bartlett's Test of
Sphericity

Approx. Chi-Square 2290.75
8

df 120

Sig. .000

Total Variance Explained

Comp
onent

Initial Eigenvalues Extraction Sums of
Squared Loadings

Rotation Sums of
Squared Loadings
Tota
l
% of
Varianc
e
Cumula
tive %

Total % of
Varianc

Cumula
tive %

Total % of
Varianc

Cumula
tive %

1 8.06

6 50.413 50.413 8.066 50.413 50.413 4.241 26.505 26.505

2 1.88

</div>
(92)<div class='page_container' data-page=92>

3 1.30

7 8.171 70.336 1.307 8.171 70.336 3.409 21.304 70.336
4 .693 4.328 74.665

5 .556 3.478 78.143
6 .526 3.288 81.431
7 .436 2.724 84.155
8 .406 2.535 86.690
9 .380 2.377 89.067
10 .344 2.152 91.219
11 .300 1.873 93.092
12 .271 1.691 94.783
13 .249 1.559 96.342
14 .207 1.292 97.634
15 .199 1.245 98.879

16 .179 1.121 100.000

Extraction Method: Principal Component Analysis.

Rotated Component Matrixa
Component

1 2 3

ECSR3 .838

ECSR4 .830

ECSR6 .817

ECSR1 .803

ECSR2 .715

ECSR5 .689

StCSR3 .798

</div>
(93)<div class='page_container' data-page=93>

StCSR2 .787

StCSR6 .769

StCSR1 .734

SCSR4 .769

SCSR2 .760

SCSR3 .737

SCSR1 .719

SCSR5 .711

Brand Likeability and Relational Switching Cost

KMO and Bartlett's Test 
Kaiser-Meyer-Olkin Measure of

Sampling Adequacy. .880

Bartlett's Test of
Sphericity

Approx.
Chi-Square

1041.06
0

df 21

Sig. .000

Total Variance Explained 
Comp

onent

Initial Eigenvalues Extraction Sums of
Squared Loadings

Rotation Sums of
Squared Loadings
Tota
l
% of
Varianc
e
Cumula
tive %

Total % of
Varianc

Cumula
tive %

Total % of
Varianc

Cumula
tive %

1 4.57

2 65.314 65.314 4.572 65.314 65.314 3.179 45.409 45.409

2 1.02

2 14.606 79.920 1.022 14.606 79.920 2.416 34.511 79.920

3 .419 5.988 85.907

4 .308 4.404 90.312

</div>
(94)<div class='page_container' data-page=94>

6 .228 3.264 97.454

7 .178 2.546 100.000

Extraction Method: Principal Component Analysis.

Rotated Component 
Matrixa

Component

1 2

BL4 0.866

BL3 0.849

BL1 0.848

BL2 0.847

RSC3 0.84

RSC2 0.834

RSC1 0.819

Word of Mouth-WOM scale

KMO and Bartlett's Test 
Kaiser-Meyer-Olkin Measure of Sampling

Adequacy. .749

Bartlett's Test of
Sphericity

Approx. Chi-Square 394.194

df 3

</div>
(95)<div class='page_container' data-page=95>

Total Variance Explained 
Compone

Initial Eigenvalues Extraction Sums of Squared

Loadings

Total % of

Variance

Cumulative
%

Total % of

Variance

Cumulative
%

1 2.502 83.404 83.404 2.502 83.404 83.404

2 .285 9.483 92.888

3 .213 7.112 100.000

Extraction Method: Principal Component Analysis.

Component Matrixa
Component

WOM1 .923

WOM2 .917

WOM3 .899

Repurchase Intention scale

KMO and Bartlett's Test 
Kaiser-Meyer-Olkin Measure of Sampling

Adequacy. .755

Bartlett's Test of
Sphericity

Approx. Chi-Square 509.62
1

df 3

</div>
(96)<div class='page_container' data-page=96>

Total Variance Explained 
Compone

Initial Eigenvalues Extraction Sums of Squared

Loadings

Total % of

Variance

Cumulative
%

Total % of

Variance

Cumulative
%

1 2.625 87.507 87.507 2.625 87.507 87.507

2 .230 7.658 95.166

3 .145 4.834 100.000

Extraction Method: Principal Component Analysis.

Component Matrixa
Component

RI3 .948

RI1 .938

</div>
(97)<div class='page_container' data-page=97>

APPENDIX 4: REGRESSION ANALYSIS

CSR dimensions and Brand Likeability

Model Summaryb
Mode

R R

Square

Adjusted R
Square

Std. Error of

the Estimate

Durbin-Watson

1 .822a .676 .672 .42461 1.839

a. Predictors: (Constant), STCSR, ECSR, SCSR
b. Dependent Variable: BL

ANOVAa

Model Sum of

Squares

df Mean

Square

F Sig.

Regressio

n 78.305 3 26.102 144.774 .000

Residual 37.501 208 .180

Total 115.805 211

a. Dependent Variable: BL

b. Predictors: (Constant), STCSR, ECSR, SCSR

Coefficientsa

Model Unstandardized

Coefficients

Standardiz
ed

Coefficien
ts

t Sig. Collinearity
Statistics

B Std. Error Beta Toleran

</div>
(98)<div class='page_container' data-page=98>

(Consta

nt) .431 .171 2.523 .012

SCSR .192 .050 .212 3.872 .000 .520 1.924

ECSR .116 .044 .132 2.620 .009 .612 1.634

STCSR .623 .056 .584 11.052 .000 .557 1.796

a. Dependent Variable: BL

CSR dimensions and Relational Switching Cost

Model Summaryb

Mode
l

R R

Square

Adjusted R
Square

Std. Error of
the Estimate

Durbin-Watson

1 .646a .417 .408 .60408 1.984

a. Predictors: (Constant), STCSR, ECSR, SCSR
b. Dependent Variable: RSC

ANOVAa

Model Sum of

Squares

df Mean

Square

F Sig.

Regressio

n 54.241 3 18.080 49.547 .000

Residual 75.903 208 .365

Total 130.144 211

a. Dependent Variable: RSC

</div>
(99)<div class='page_container' data-page=99>

Coefficientsa

Model Unstandardized

Coefficients

Standardiz
ed
Coefficien

t Sig. Collinearity

Statistics

B Std.

Error

Beta Toleran

VIF

(Consta

nt) 1.031 .243 4.241 .000

SCSR .338 .070 .352 4.794 .000 .520 1.924

ECSR .223 .063 .239 3.537 .000 .612 1.634

STCSR .180 .080 .159 2.246 .026 .557 1.796

Brand Likeability, Relational Switching Cost and Word of Mouth

Model Summaryb

Model R R Square Adjusted R

Square

Std. Error of
the Estimate

Durbin-Watson

1 .822a .676 .673 .46368 1.873

</div>
(100)<div class='page_container' data-page=100>

ANOVAa

Model Sum of

Squares

df Mean Square F Sig.

Regression 93.712 2 46.856 217.932 .000b

Residual 44.936 209 .215

Total 138.648 211

a. Dependent Variable: WOM
b. Predictors: (Constant), RSC, BL

Coefficientsa

Model Unstandardized

Coefficients

Standardi
zed
Coefficien

t Sig. Collinearity
Statistics

B Std.

Error

Beta Toleran

VIF

(Consta

nt) -.037 .180 -.204 .838

BL .710 .055 .649 12.927 .000 .615 1.625

RSC .251 .052 .243 4.841 .000 .615 1.625

</div>
(101)<div class='page_container' data-page=101>

93
Brand Likeability, Relational Switching Cost and Repurchase Intention

Model Summaryb

Model R R Square Adjusted R

Square

Std. Error of
the Estimate

Durbin-Watson

1 .829a .688 .685 .46981 2.218

a. Predictors: (Constant), RSC, BL
b. Dependent Variable: RI

ANOVAa

Model Sum of

Squares

df Mean Square F Sig.

Regression 101.733 2 50.866 230.456 .000b

Residual 46.131 209 .221

Total 147.863 211

a. Dependent Variable: RI

</div>
(102)<div class='page_container' data-page=102>

Coefficientsa

Model Unstandardized

Coefficients

Standardize
d

Coefficient
s

t Sig. Collinearity

Statistics

B Std. Error Beta Toleranc

VIF

(Constan

t) .034 .183 .187 .852

BL .491 .056 .434 8.821 .000 .615 1.625

RSC .519 .053 .487 9.882 .000 .615 1.625

</div>

Impact of corporate social responsibility on customer loyalty behaviors: evidence from Vietnam

<b>IMPACT OF CORPORATE SOCIAL </b>

<b>RESPONSIBILITY ON CUSTOMER </b>

<b>LOYALTY BEHAVIORS: EVIDENCE </b>

<b>FROM VIETNAM </b>

<b>MASTER'S THESIS </b>

<b>BUSINESS ADMINISTRATION </b>

<b>IMPACT OF CORPORATE SOCIAL </b>

<b>RESPONSIBILITY ON CUSTOMER </b>

<b>LOYALTY BEHAVIORS: EVIDENCE </b>

<b>FROM VIETNAM </b>

<b>Condition </b>

<b>Value </b>

KMO index

0.931

Sig. (Bartlett's Test)

0.000

Total Variance Explained

69.987

<b>Condition </b>

<b>Value </b>

KMO index

0.926

Sig. (Bartlett's Test)

0.000

Total Variance Explained

70.336

<b>Condition </b>

<b>Value </b>

KMO index

0.847

Sig. (Bartlett's Test)

0.000

Total Variance Explained

81.344

Tài liệu liên quan

Tài liệu bạn tìm kiếm đã sẵn sàng tải về