Lal Bahadur Shastri Institute of Management, Delhi

LBSIM Working Paper Series

LBSIM/WP/2020/07

Brand Community Commitment

through Brand Loyalty

Samant Shant Priya

August,2020

LBSIM Working Papers indicate research in progress by the author(s) and are brought out to elicit ideas,

comments, insights and to encourage debate. The views expressed in LBSIM Working Papers are those of the

author(s) and do not necessarily represent the views of the LBSIM nor its Board of Governors.

WP/August2020/07

LBSIM Working Paper

Research Cell

Brand Community Commitment through Brand Loyalty

Samant Shant Priya

Faculty, LBSIM, Delhi

samantsp@lbsim.ac.in

+919923190752

The research involves validating a proposed theory that revolves around brand community

commitment and the proposition suggests, it is led by brand loyalty and the brand loyalty has

further been derived from brand satisfaction, brand trust and brand affect. The brand community

of a famous Indian Two- wheeler brand is considered for this work. It is a cult brand and has one

of the oldest and largest brand communities in India. A structured questionnaire was used to collect

data via online medium from total 390 respondents who are currently the part of this community.

The analysis techniques used is structural equation modeling (SEM) with the help of AMOS, the

results indicate that there exists a positive relation between brand loyalty and brand community

commitment.

Keywords: Brand Community, Brand Community Commitment, Brand Loyalty, Brand

Satisfaction, Brand Affect and Brand Trust

Brand Community Commitment through Brand Loyalty

Introduction: A non-geographically bound and a specialized community which is based on a social relationship

among the people who appreciates a brand (Muniz and O’guinn, 2001). It usually represents a

human association among the members of the community for some consumption purposes. Over

the time the concept of bend community has considerably evolved. It as a group of people who

have longtime interactions with rich individual affection (Rheingold, 1994). Though context of

this work of based on online community. Cova & Pace (2006) define a brand community “as any

group of people that possess a common interest in a specific brand and create a parallel social

universe rife with its own myths, values, rituals, vocabulary and hierarchy”. Despite of the

differences between definitions, it is assumed that there exists a stable relationship among the

participants of a brand community. Earlier works on brand relationships suggest that there is only

customer-based brand relationship, but the relationship among the brand community members is

much beyond consumption. To get more closer to consumers numerous organizations now a days

are getting closer to the idea of brand network, this brand network or the brand community may

help organizations communicate with buyer in a straightforward manner and purchaser can

cooperate with brand as well as with different buyers. Few famous brand communities across the

world are The SAP community, PlayStation Community, Being Girl Figment, H&R Block,

Harley Owners Group, My Starbucks Idea, Oracle Community, r/Nordstrom 1991 and Lugnet.

These community operate globally and help organizations not only communicate but to innovate

the product design and troubleshoot problems of the other community members. Some marquee

brand community that operates in India are Gangs of Dusters and Royal Enfield forum. This work

is an attempt on understanding how the commitment can be built across the brand community

members. While the reviewed literature could not trace the impact of brand loyalty on brand

commitment, but it is implied that a loyal customer may be a committed customer and may like

to participate in the community. Under this premise, the work will further explore the

relationship between brand loyalty and brand community commitment.

Theoretical framework and hypotheses development Brand loyalty is Antecedents of brand community commitment, means once any consumer is loyal

to the brand then it drives the consumer towards the brand community and brand community

commitment which brings brand and consumer closer to each other.

“Brand loyalty is defined as positive feelings towards a brand and dedication to purchase the same

product or service repeatedly now and in the future from the same brand, regardless of a

competitor's actions or changes in the environment” ("future of brand loyalty," 2019).

It is individual’s feeling or attachment towards a brand (Kotler, 2003). Companies with more loyal

customers have competitive advantage in marketing. Aaker (2010) defines brand loyalty as the

degree of consumer’s emotional attachment towards brand. For the present work, brand trust,

brand affect, and brand satisfaction are considered as the driving force to brand loyalty.

A sound relationship is built between company and consumer and is based on brand affect. As per

Kapoor (2011) the brand reflects the self -identity or it acts like a very important symbol that is

meaningful to consumer and that’s why consumers’ get themselves involved emotionally towards

a brand. This emotional involvement is referred to as brand affect. This attachment is developed

for the consumers trust those brands and feel that they are very close to their lifestyle and values.

Fedorikhin, Park, & Thomson, (2008) suggest that this attachment can help develop long term

relationships. And a positive consumer affection towards the brand may lead to more repurchases

(Morgan & Hunt, 1994), so the first hypothesis for the work

H1: Brand affect has positive impact towards brand loyalty.

Spekman (1988) suggests that the brand affect and brand trust are the cornerstone to strategic

partnership. It is also proven to be correct in the case of services marketing literature that effective

marketing depends on brand effect and brand trust (Berry and Parasuraman, 2004). Brand trust is

defined as the willingness of consumers to rely on the power of the brand to realize its stated

purpose. Brand trust can be defined as “a consumer’s willingness to rely on the brand in the face

of risk because of expectations that the brand will cause positive outcomes” (Lau & Lee, 1999).

Assael (2001) suggests attributes and benefits of a brand can help build trust. It is believed start

underlying loyalty is always trust (Lau & Lee, 1999). Because it creates relationships that are

highly valued brand trust leads too loyalty. So, the researcher maintains the next hypothesis for

the work as:

H2: Brand trust has positive impact brand loyalty.

Brand satisfaction is defined as performance of the actual products or services from the brand as

compared to the expectation from the brand. As per Lin & Sun (2009), satisfaction will surface

when a consumer’s hope is met with the purchase decision. It is a result of subjective evaluation

of a chosen brand and it is meeting or exceeding their expectations (Lau & Lee 2000).

Satisfaction is a type a behavior that results in repurchasing more often the same brand. In the

hospitality industry it is suggested by Tepeci (1999) that there exists a direct positive relationship

between brand satisfaction and brand loyalty. Brand satisfaction is evaluative summary of

customers’ after consumption of product or service (Nam, Ekinci, & Whyatt, 2011). Their

evaluation helps in building the brand loyalty, thus the next hypothesis for the work is

H3: Brand satisfaction has positive impact towards brand loyalty.

Hans Ouwersloot &Gaby Odekerken‐Schröder (2008) write about the different motivation to the

customer to join brand communities and investigates the question can we treat the people of one

brand community as one segment or not? The finding of study suggests that Community

members share a reasonably strong commitment to the brand, but the brand concept is so complex

that members can and do differ in many respects. The brand affect and brand trust lead to consumer

loyalty and in turn it leads to brand community and their commitment (Morandin & Bergami,

2013). Another work by Won-Moo Hur, Kwang-Ho Ahn & Minsung Kim, (2011) talks about the

direct effect of brand trust and satisfaction on the community towards the brand community

which lead to change in consumers’ actions like repurchase intention, word of mouth and

constructive complaints. In the light of the above the researcher proposes the next hypothesis for

the work as

H4: Brand loyalty has positive impact on brand community commitment.

Proposed Conceptual Framework:

Proposed conceptual model for the research

Research Methodology: The data used here for the study was collected from 379 brand enthusiasts/community members

of famous 2-Wheeler automobile brand of India. The community members were all scattered

across India, so the snowballing approach of sampling was used for the study. The questionnaire

contained 27 items at the beginning apart from the demographic details of the respondents. These

questions in the measurement scale were drawn from earlier proven studies and taken from a book

on marketing scale handbook by Gordon C. Bruner II and other relevant literature cited earlier.

Validity and Reliability of measurement scale

Face Validity of the Questionnaire

As the name itself suggests the face validity of a measurement scale is its appearance about its

purpose. This in a sense clarifies whether at face value; the questions appear to be measuring the

construct. It is subjective but systematic assessment of the content to which a scale measures a

construct (Malhotra, 2015). The face validity of the questionnaire was performed with the help of

Delphi method. In the Delphi method, experts are identified and asked to respond to scale and

based on their suggestions the scale was further modified. The following modifications were made

and the version 2 of the questionnaire was prepared.

1. The order of questions has been changes.

2. One statement from brand satisfaction, one satisfaction from brand affect and three

statements from brand loyalty has been removed due to low content validity ratio.

Content Validity

S.No. Parameters CVR

1 Brand Satisfaction

BS1 Overall I am very satisfied with this brand. 1

BS2 The experiences with this brand meet my expectations of an ideal brand. 0.591

BS3 The performance of this brand has fulfilled my expectations. 0.227

2 Brand Affect

BA1 This brand makes me happy. 0.591

BA2 This brand gives me pleasure 0.682

BA3 I feel good when I purchase this brand. 0.091

3 Brand Trust

BT1 I trust this brand. 0.591

BT2 I rely on this brand. 0.682

BT3 This is an honest brand. 0.636

BT4 I can always trust on this brand if I want a product of high quality 0.5

BT5 I feel that this brand’s claims are general y trustworthy. 0.5

4 Brand Loyalty

BL1 I intend to buy this brand in the near future. 0.818

BL2 I would actively search for this brand in order to buy it. 0.818

BL3 I intend to buy other products of this brand. 0.546

BL4

I will hardly miss an opportunity to tell others positive things about the

brand. -0.136

BL5 I will actively encourage friends and relatives to buy this brand. 0.546

BL6

If friends or relatives were to search, I would recommend them to buy this

brand. -0.046

BL7 I will repurchase this brand in the year to come 0.182

BL8 I would love to use this brand continuously 0.818

BL9 Even though this brand is sold out, I won’t purchase other brands. 0.818

5 Brand Community Commitment

BCC1 I feel a sense of belonging in this brand community 0.864

BCC2 I will visit this brand community continuously 0.864

BCC3

I will exchange information and opinions with the members of this brand

community 0.864

BCC4 I will collect information through this brand Community 0.909

Sum of all CRVs 13.96

Content Validity Index (Includes all parameters) 0.581

Content Validity Index (Includes only accepted parameters) 0.718

Reliability

Alpha (Cronbach): This model’s internal consistency based on average correlation among items.

Cronbach's alpha is the most common form of internal consistency reliability coefficient. Alpha

equals zero when the true score is not measured at all and there is only an error component. Alpha

equals 1.0 when all items measure only the true score and there is no error component. Cut-off

Criteria, by convention, a lenient cut-off of .60 is common in exploratory research; alpha should

be at least .70 or higher to retain an item in an "adequate" scale; and many researchers require a

cut-off of .80 for a "good scale. Since the Cronbach’s alpha for the present scale is 0.965, it is

considered the scale is reliable

Reliability of Individual scale

The Composite Scale Reliability Test It is mandatory to check the reliability of the scale because this scale has not been previously

explored by any researcher in context of Indian Automobile industry specifically 2-wheeler and

internal consistency or reliability is particularly important in connection with multiple item scales.

Cronbach’s alpha has been used to check the internal consistency. Ideally, the Cronbach’s alpha

scale for internal consistency (Nunnally, 1978) should be above 0.7 (Pallant, 2020). Items that rate

below the recommended alpha level of 0.7 may be removed in order to improve the scale’s

reliability.

Reliability Statistics

Cronbach's Alpha N of Items

.867 19

In the present research, the value of Cronbach’s alpha computed using SPSS 20.0 software for the

19 items was found as 0.867, which is reasonably on a higher side to be accepted. According to

Sekaran, (2003) higher the value of Cronbach’s alpha (closer to one), the higher is the internal

consistency or reliability.

Construction of Measurement Model To verify whether the 19 measurement variables are truly represented by 5 unobserved constructs,

it is mandatory to define a measurement model. The fit of measurement model is extremely

important in that all possible latent-variable structural models are nested within it. Obtaining a

poor fit at this precludes moving on to investigate latent variable structural models (Gerbing &

Anderson, 1988).The CFA was carried out to determine the degree of model fit, the adequacy of

the factor loadings, and the standardized residuals and explained variances for the measurement

variables. In this initially constructed measurement model, the 19 measured variables (EFA) were

drawn using rectangle, while 5 latent constructs were made using ellipse and all the error terms

using circle. The single headed arrows indicate linear dependencies, these arrow-head points

toward observed variables from their respective dependent variable or latent construct. The path

coefficient of all the error terms from e1 to e19 was fixed to unity, while the path coefficients for

one of the observed variables for each construct were also fixed.

Measurement Model

Confirmatory Factor Analysis Confirmatory factor analysis (CFA) is a special form of factor analysis, most commonly used in

social research. It is used to test whether measures of a construct are consistent with a researcher's

understanding of the nature of that construct (or factor). CFA allows the researcher to test the

hypothesis that a relationship between observed variables and their underlying latent constructs

exists.

Confirmatory factor analysis is done in two part one is convergent factor analysis and another is

discriminant factor analysis. Convergent Validity is a sub-type of construct validity. Construct

validity means that a test designed to measure a construct is measuring that construct. Convergent

validity takes two measures that are supposed to be measuring the same construct and shows that

they are related. Conversely, discriminant validity shows that two measures that are not supposed

to be related are in fact, unrelated. Both types of validity are a requirement for excellent construct

validity.

Convergent validity

. BS BT BA BL BCC

AVE 0.757 0.64 0.591 0.605 0.737

CR 0.851 0.898 0.738 0.901 0.918

Convergent

Validity Established Established Established Established Established

o AVE values should be greater than 0.5.

o CR values should be greater than 0.7.

Discriminant validity:

Factor

Correlation

Squared

Correlation

AVE_1

AVE_2

Discriminant

Validity

BA <--> BL 0.343 0.118 0.591 0.605 Established

BA <--> BCC 0.272 0.074 0.591 0.737 Established

BL <--> BCC 0.478 0.228 0.605 0.737 Established

BS <--> BT 0.039 0.002 0.757 0.64 Established

BS <--> BA 0.002 0.000 0.757 0.591 Established

BS <--> BL 0.056 0.003 0.757 0.605 Established

BS <--> BCC 0.013 0.000 0.757 0.737 Established

BT <--> BA 0.039 0.002 0.64 0.591 Established

BT <--> BL 0.194 0.038 0.64 0.605 Established

BT <--> BCC 0.378 0.143 0.64 0.737 Established

o AVEs should be greater than Squared Correlation.

Results and Discussions for Measurement Model

Unidimensionality

The initial phase in the factual procedure is to test develops in the estimation demonstrate for

unidimensionality. When each develop/scale is evaluated to be unidimensional and solid, assuming

this is the case, the legitimacy can be tried (Gerbing & Anderson, 1988; Steenkamp & Van Trijp,

1991). Every one of the ten builds was exposed to Exploratory Factor Analysis (EFA)

independently. Based on Eigen-esteem more noteworthy than 1 heuristic (Munuera-Aleman,

Delgado-Ballester, & Yague-Guillen, 2003), one chief segment was removed that represented

dominant part of the complete difference on account all things considered. In this way, all scales

were turned out to be unidimensional after the examination.

Test of Reliability When the unidimensionality of the considerable number of scales was built up, scale unwavering

quality appraisals were created. Unwavering quality can mirror the inner consistency of the

markers estimating a given factor. Scales were measurably estimated for marker unwavering

quality and scale dependability. The marker unwavering quality ought to ideally be 0.5 or more

prominent (Schumacker & Lomax, 2004). An estimation of Cronbach's alpha of 0.6 or more is

utilized as a rule for a dependable scale (Hair 1984; Nunnally, 1978). Fornell & Bookstein,

(1982) expressed that Construct Reliability esteem higher than 0.6 infers that there is high

interior consistency. Normal Variance Extracted (AVE) at 0.5 or near it is for the most part

viewed as satisfactory. The Cronbach alpha, CR and AVE values are given in table above.

Test of Validity A scale is legitimate on the off chance that it gauges the idea that it was planned to quantify

(Bagozzi, 1981). Since unidimensionality and unwavering quality have been built up, the

subsequent stage is to survey legitimacy. Different proportions of develop legitimacy named as

Convergent (Bentler-Bonett Coefficient), Discriminant (through Average Variance Extracted)

and Criterion Validity were registered. While Convergent and Discriminant Validity are

estimated utilizing the Measurement Model; the Criterion Validity is estimated through the

Structural Model. The united legitimacy can be estimated utilizing the Bentler-Bonett Coefficient

(Bentler-Bonett, 1980) in AMOS20.0. Ahire, Golhar, and Waller, (1996) prescribed surveying

merged legitimacy utilizing the Bentler-Bonett coefficient with qualities more prominent than

0.9 demonstrating solid focalized legitimacy, even the NFI and NNFI of .8 or more are viewed

as a solid match. In the present case, every one of the scales have a Bentler

Bonett coefficient (for example NFI and NNFI) of more prominent than 0.8 as given in following

table, in this way characteristic of high united legitimacy.

Indicator of Convergent Validity

Sr. No. Scale NFI NNFI

1 BS .944 .923

2 BT .877 .851

3 BA .978 .975

4 BL .929 .889

5 BAA .979 .985

The measurement model has been constructed using 19 items and 5 constructs. The AMOS

results obtained are as follows;

Measurement Model Improvement

AMOS suggests two ways of improving the measurement model which can be helpful in detecting

the model misfit. They are either with the help of modification indices and the standardized

residuals.

Model Fit Summary

The standardized path coefficients of the Structural Model were estimated by AMOS20. It was

found that the structural model fits the data well. The fit indices values are given in table. The

global fit statistics indicate the structural model represent the data structure well. The significant

value (p=0.000), Bollen-Stine statistic indicated a model fit and so suggested the model could be

accepted i.e. p<0.05. The RMSEA value (.056) falls well below the maximum recommended

value of 0.08 or 0.10 and values for NFI (.933), RFI (.918) and CFI (.962) all exceeded the

recommended 0.90 level, indicating a good fit. The relative chi square/ degree of freedom of

2.218 were less than the recommended maximum of 3.00 Heir et.al (2012).

CMIN

Model NPAR CMIN DF P CMIN/DF

Default model 69 310.508 140 .000 2.218

Saturated model 209 .000 0

Independence model 38 4609.374 171 .000 26.955

Baseline Comparisons

Model NFI

Delta1

RFI

rho1

IFI

Delta2

TLI

rho2 CFI

Default model .933 .918 .962 .953 .962

Saturated model 1.000 1.000 1.000

Independence model .000 .000 .000 .000 .000

RMSEA

Model RMSEA LO 90 HI 90 PCLOSE

Default model .056 .048 .065 .111

Independence model .259 .253 .266 .000

Hypothesis Testing and Model Fit

For hypothesis testing through the path analysis in SEM, following model is developed with the

help of elements confirmed in CFA.

Hypothesis 1: Brand satisfaction towards brand have positive impact brand loyalty.

Brand Trust has direct and positive impact on Brand Loyalty as indicated by the significant

path from BT to BL (β=0.25. Thus hypothesis 1 is accepted.

Hypothesis 2: Brand affect towards brand have positive impact brand loyalty.

Brand Affect has direct and positive impact on Brand Loyalty as indicated by the significant

path from BA to BL (β=0.08). Thus hypothesis 2 is accepted.

Hypothesis 3: Brand trust towards brand have positive impact brand loyalty.

Brand trust has direct and positive impact on brand loyalty as indicated by the significant path

from BT to BL (β=0.24). Thus, the Hypothesis 3 is accepted.

Hypothesis 4: Brand loyalty have positive impact on brand community commitment.

Brand Loyalty has direct and positive impact on Brand Community Commitment as indicated

by the significant path from BL to BCC (β=0.56). Thus hypothesis 4 is accepted.

Final Fit Model with path coefficient

CMIN

Model NPAR CMIN DF P CMIN/DF

Default model 47 230.981 143 .000 1.615

Saturated model 190 .000 0

Independence model 19 4416.351 171 .000 25.827

RMR, GFI

Model RMR GFI AGFI PGFI

Default model .057 .941 .921 .708

Saturated model .000 1.000

Independence model .276 .301 .223 .271

Baseline Comparisons

Model NFI

Delta1

RFI

rho1

IFI

Delta2

TLI

rho2 CFI

Default model .948 .937 .979 .975 .979

Saturated model 1.000 1.000 1.000

Independence model .000 .000 .000 .000 .000

REMSA

Model RMSEA LO 90 HI 90 PCLOSE

Default model .040 .031 .050 .955

Independence model .256 .250 .263 .000

All the indictors have shown the range which is specified like CMIN/Df = 1.615(should be less

than 3). NFI, RFI, IFI, TLI and CFI should be close to one and in the fit model they are reflected

as 0.948, 0.937, 0.979, 0.975 and 0.979. The REMSA for the fit model should be less than 0.05

and the reported fit model has REMSA value as 0.040. The GFI and AGFI also fulfill the condition

of close to one by having the values as 0.941 and 0.921 respectively, thereby it is considered it is

the best fitting model.

The path coefficients of the structural model indicate the magnitude and direction of relationships

and thus are used for testing the hypotheses are given in the above diagram.

Conclusion:

The discoveries in this investigation have useful ramifications for showcasing the way forward.

To begin with, plainly an organization's image network promoting exercises have the ability to

impact the quality of the connections among network members, the brand, and the organization.

In like manner, organizations perceiving the critical job of brand network should bend over

backward to effectively deal with a brand network.

Second, this examination recommends trust, satisfaction and affect influence are indispensable

factors in upgrading clients' loyalty, bringing up the issue with respect to loyalty, how an

organization may expand trust, affect and satisfaction and influence in the psyches of its loyalty.

Continued endeavors to make clients feel delight and satisfaction will upgrade the full of feeling

air of the brand network. Taking into account that trust is more powerful than influence on brand

network loyalty, as distinguished in this examination, the companies must first focus

on blinding trust among its community members to build commitment.

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