Impmodel Proposal

7/30/2019 Impmodel Proposal

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contribute highly to the existing knowledge about social media engagement by providing a

validated measurement scale for customer engagement in online social platforms. However,

the research is still in progress and no results have been published to date. Thus, even

though the new media present a number of significant opportunities and challenges for both

researchers and practitioners (Hennig-Thurau et al., 2010), most of the existing research is

primarily conceptual or qualitative (Cheung et al., 2011).

2.6 Problem statement

Academic literature highlights the importance of approaching the concept of engagement

with consideration to its highly contextual nature, because engagement, separated from its

() context, is a contradiction that ignores deeply embedded understandings about the

purpose and nature of engagement itself (Vibert & Shields, 2003). Moreover, Brodie et al.

(2011a) suggest that under different circumstances the importance of the cognitive,

emotional, and behavioral customer engagement dimensions may vary. Therefore, it is

likely that customer engagement in different contexts, such as online versus offline

environments, would manifest in different expressions.

The context of online social media has become of great interest to marketing

practitioners as the new social media platforms quickly emerged as valuable tools central totheir effort of customer engagement (WARC, 2012a). Despite the vast popularity of the

concept among businesses, the push of engagement still misses the mark and fails to

explain what it ultimately means to the brand. The behavioral measures of engagement

currently available on online social media platforms such as number of fans, repeated visits

or interactions with the brand page provide little information about the returns to be

expected (Nelson-Field & Taylor, 2012). Hence, the lack of theory-guided empirical studies

in order to better understand customer engagement with brands in the context of online

social media points to a fault line between the practitioners who increasingly pursue the

quest for their Holy Grail, and the scholars who yet mostly choose to focus their

empirical research elsewhere.
http://www.pdfxviewer.com/http://www.pdfxviewer.com/


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Hence, the main objective of this study is to bridge this gap by conceptualizing

customer brand engagement on online social media platforms and answering two important

research questions:

1. What drives the customer to engage with brands on online social mediaplatforms?

2. What are the outcomes of such engagement?Identifying and validating the antecedents and consequences of customer brand

engagement in this particular context is crucial in order to further advance the knowledge in

the area. According to Hollebeek (2011b), the rising practitioner interest in the concept of

customer brand engagement is mostly driven by the expected benefits and its explanatory

and predictive power in customer relationship outcomes, such as loyalty in particular. Since

it is more cost-effective to retain the existing as opposed to winning new customers,

insights into customer brand engagement on online social media platforms may help

businesses to capitalize on enhancing customer relationships, retention and loyalty through

the use of social media.

2.7 A conceptual model of customer brand engagement on online social

media platforms

The five fundamental propositions underlying the general concept of customer engagement

suggested by Brodie et al. (2011a) provide suitable guidelines for framing the investigation

of the nature and role of customer brand engagement on online social media platforms.

These five themes were therefore applied in developing the working definition and building

the conceptual model. The proposed working definition in this study is the following:

The concept of customer brand engagement on online social media platforms is

characterized by interactive customer experiences with the brand. It is a process of

dynamic and iterative nature, which stems from the domains of S-D logic, relationship

marketing and social exchange theory. Customer brand engagement on online social

media platforms is the central element embedded in a broader network of other

relational constructs serving as the antecedents and the consequences. The concept of


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engagement is multidimensional and comprises the expressions of emotional,

behavioral and cognitive engagement specific to this particular context.

Based on this definition and the findings from the literature review, a conceptual model

of customer brand engagement on online social media platforms was developed (see Figure

2). The framework portrays customer brand engagement on online social media platforms

as the central element embedded in the network of other constructs, which are divided into

two groups of potential antecedents and consequences. In principle, the structure of the

framework relates to van Doorns et al. (2010) conceptual model of customer engagement

behavior. However, instead of considering three types of factors that can affect

engagement, the current model is focused on customer-based antecedents and consequences

only. The customer-based perspective has been chosen, since not only it represents the

inevitable focus of the business, but the consequences of engagement to the customer are

also suggested to have an inherent effect on the ultimate business performance (Kumar et

al., 2010). Furthermore, as suggested in the working definition, the conceptual framework

does not only comprise the behavioral aspect of engagement, but addresses the concept in a

broader sense by including the cognitive and emotional aspects as well.

The group of potential antecedents portrayed in the model includes factors related to

customer brand relationship quality and online social media platforms. The customer brand

relationship quality related factors are further specified as involvement, satisfaction,

commitment and trust. Brodie et al. (2011a) suggest involvement to be a required

antecedent of customer engagement, whereas customer satisfaction, commitment and trust

in relation to the brand represent the potential attitudinal antecedents also proposed by

Bowden (2009) and Hollebeek (2011b). Because of the iterative nature of customer

engagement, all three attitudinal factors have been found to have the potential of acting as

both antecedents and consequences. The role of the factor will vary depending on whether

the customer is new or existing (L. D. Hollebeek, 2011b). The structure of the conceptual

model given in Figure 2, however, implies that it was chosen and built on the premise of

existing customers in particular.


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Another sub-group of antecedents comprises online social media platform related

factors, such as involvement, participation, telepresence and ease of use. Even though

involvement has already been included to the relationship quality related factors, the latter

case addresses the concept in terms of personal interest and relevance towards online social

media platforms. Participation, according to Brodie et al. (2011a), is another prerequisite

for customer engagement, as it determines customers propensity to participate on online

social media platforms. Furthermore, the concept of telepresence is included in the model,

since Mollen and Wilson (2010) suggest it to be a direct antecedent of online engagement.

Hollebeek (2011b) and Brodie et al. (2011a) also suggested the concept of flow, which is

related to telepresence and could also be considered relevant in this specific context.

However, as no commonly accepted conceptualization or consensus regarding the

operationalization of flow exists in the academic literature (Mollen & Wilson, 2010), it has

been decided to leave the concept out of the model. Finally, ease of use has also been added

BEHAVIORAL

EMOTIONAL

COGNITIVE

CUSTOMER BRAND

RELATIONSHIP RELATED

ONLINE SOCIAL MEDIA

PLATFORM RELATED

INVOLVEMENT

SATISFACTION

COMMITMENT

TRUST

INVOLVEMENT

PARTICIPATION

TELEPRESENCE

EASE OF USE

CUSTOMER BRAND

ENGAGEMENT ON

ONLINE SOCIAL

MEDIA PLATFORMS

BRAND LOYALTY

WORD-OF-MOUTH

CONSEQUENCES

ANTECEDENTS

Figure 2. Conceptual model of customer brand engagement on online social

media latforms


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to the model as a potential contextual antecedent referring to the degree to which a

customer perceives using online social media platforms to be free of effort (Davis, 1989).

As for the consequences, two customer-based items were selectedbrand loyalty and

word-of-mouth, which here refers to the intention to recommend the brand. Bowden (2009)

addresses customer engagement as the superior predictor of customer loyalty as compared

to other more traditional marketing constructs. On the other hand, Cheung et al. (2011)

suggest that a customer willing to invest physical, cognitive and emotional effort into an

online platform will also have a higher propensity to spread word-of-mouth communication

about it. A customer valuation framework introduced by Kumar et al. (2010) suggests that

the value of customer engagement is comprised of four dimensions: customer purchasing

behavior, customer referral behavior, customer influencer behavior through customers

influence on other existing or prospect customers, and finally, customer knowledge

behavior via feedback provided to the firm. Thus, both customer loyalty and word-of-

mouth have established grounds as potential engagement consequences in the literature.

3. Methodology

3.1 Data collection

In order to collect the data and test the proposed model of customer brand engagement

on online social media platforms an online survey was conducted using a convenience

sample of Facebook2

account holders. With 901 million active monthly users Facebook is

currently worlds largest online social network (Facebook, 2012) and a highly relevant

platform for this study. Among many various online services offered by Facebook, there is

also something called Facebook Pages. Facebook Pages are public profiles meant to

promote brands, products, artists, web sites or organizations. Once registered Facebook

users visit a Page, they are able to 'become fans' by clicking on the 'Like' button. The

owners of the Page can then post informational content, which consequently will appear in

the news feed of their fans. The fans can choose to react to the posts in few different ways

such as liking, commenting or sharing it with their own networks. In other words,

2 www.facebook.com


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Table 1: Characteristics of the respondents (N1=112, N2=307)

Fans(N1) %

Non-fans(N2) %

Age X2(7) = 4.43, = 0.729Younger than 20

20242529

303435394044

454950 and older

7

3733

1144

23

4

3338

1542

13

Gender X2(1) = 0.70, = 0.401

Male

Female

58

42

53

47Use of other online social media platforms X

2(4) = 10.51, = 0.033

No other1-2 others3-5 others

6-9 others10 and more others

83235

232

94335

121

Time spent on online social media platforms per day X2(4) = 15.92, = 0.003Less than 30 mins

30 mins1 hour1 hour2 hours2 hours3 hours

More than 3 hours

12

223316

17

26

252614

8

Time spent on Facebook per day X2(4) = 13.97, = 0.007

Less than 30 mins30 mins1 hour

1 hour2 hours2 hours3 hours

More than 3 hours

1929

2714

11

3627

239

6

3.2 Measurement of constructs

The survey instrument comprised of 62 items measuring the constructs mentioned in the

modelthe antecedents, the consequences, and the customer brand engagement on online

social media platforms itself.

There were two groups of constructs representing the potential antecedents customer

brand relationship quality related and online social media platform related. The customer


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brand relationship quality related constructs (involvement, satisfaction, commitment and

trust) have been widely discussed in academic marketing literature and the choice of scales

for these constructs has therefore been based on the findings of previously published

research. Brand involvement has been operationalized via five items measuring an

individuals level of interest, importance and personal relevance in relation to the brand

(Beatty & Talpade, 1994). Commitment has been measured with a six item scale valuing an

ongoing relationship between the customer and the brand as well as willingness to make

efforts in order to maintain it (Aaker, Fournier, & Brasel, 2008). The satisfaction scale

included three items focusing on the general performance of the brand (Gustafsson,

Johnson, & Roos, 2005). Finally, the construct of trust has been measured with four items

relating to an individuals perceptions and beliefs regarding the safety and security of

interacting with the brand (Chaudhuri & Holbrook, 2001).

The suggested antecedents related to online social media platform were involvement,

participation, ease of use and telepresence. Involvement in online social media platform has

been measured with the same five item scale adapted from the paper by Beatty & Talpade

(1994). The construct of participation in an online social media platform has been

approached as the frequency and the intensity of participation as suggested by van Doorn et

al. (2010), and measured with three self-constructed items. The ease of use scale has been

adapted from a research paper by Davis (1989) and included six items. Even though

telepresence has been discussed in the literature and defined as the psychological state of

being there in the computed-mediated environment (Mollen & Wilson, 2010), there is no

actual measuring instrument developed for telepresence in the online social media platform

context yet. Therefore, a set of four relevant items from an originally eight item scale by

Kim & Biocca (1997) meant to measure telepresence in the context of television has been

adapted and used in this survey.

Customer brand engagement on online social media platforms has been split into three

dimensions behavioral, emotional and cognitive. The emotional and cognitive

engagement scales have been used as suggested by Cheung et al. (2011), where both

constructs are measured with six items each. The behavioral dimension, however, only

included two relevant items of those suggested by Cheung et al. (2011) and has been


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supplemented with seven other self-constructed items referring to the frequency of the

different forms of behavioral engagement. Nelson-Field & Taylor (2012) suggest that in

social media, and particularly on Facebook, engagement takes the form of all kinds of

direct interaction with the fan page. The inclusion of seven additional Facebook specific

items was also based on this premise. Thus, the self-constructed items refer to the

frequency of various interactions with a particular fan page, such as visiting the page,

noticing, reading, liking, commenting and sharing its contents as well as creating and

posting contents on the fan page yourself. The response format chosen for these seven

items has been a seven point frequency scale (1=Never, 2=Almost never, 3=Rarely,

4=Sometimes, 5=Often, 6=Almost all the time, 7=All the time). The response

format used for the rest of the items in the questionnaire was a seven point Likert scale

anchored by 1=Strongly disagree, 7=Strongly agree.

The consequences of customer brand engagement on online social media platforms

have been measured in terms of behavioral brand loyalty and word-of-mouth. The scale for

behavioral brand loyalty contained two items relating to future purchase intentions

(Chaudhuri & Holbrook, 2001). Word-of-mouth, which can also be defined as the intention

to recommend the brand to others, has been measured with three items suggested by

Zeithaml, Berry & Parasuraman (1996).

In addition to the 62 mentioned items, there were also three control variables included

in the questionnaire and measured by two self-constructed items each. These were goals,

resources, and the perceived cost/benefit of interacting with the brand pages on Facebook

specifically. These control variables have been included in the survey as the literature

suggests that they can also be expected to influence how customers engage with brands

(van Doorn et al., 2010). The two specific goals accounted for in the questionnaire were: 1)

maximizing the consumption benefits (e.g. interacting with the brand on Facebook out of

interest); 2) maximizing the relational benefits (e.g. becoming a member of a brand

community). The resource items referred to the time available for browsing on Facebook

fan pages and the effort that it takes. Finally, the perceived cost/benefit items were focusing

on the respondents perceived levels of enjoyment while browsing on Facebook fan pages

and its value in comparison to the time and effort spent on it. A summary of all the


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mentioned questionnaire items including the sources of reference and the resulting

Cronbachs alpha for each scales are displayed in Table 2 below.

Table 2: Construct measurement items, sources and scale reliabilities

Measure/Source Items Reliability

Antecedents

Customer brand relationship quality related

Involvement

(Beatty & Talpade,

1994)

1.In general I have a strong interest in [BN]52.[BN] is very important to me

3.[BN] matters a lot to me4.I get bored when other people talk to me about [BN]*

6

5.[BN] is relevant to me

0.80

Satisfaction

(Gustafsson et al.,2005)

6.Overall I am satisfied with [BN]

7.[BN] exceeds my expectations8.The performance of [BN] is very close to the ideal brand

in the product category

0.75

Commitment(Aaker, Fournier,

& Brasel, 2008)

9.I am very loyal to [BN]10.I am willing to make small sacrifices in order to keepusing the products of [BN]11.I would be willing to postpone my purchase if the

products of [BN] were temporarily unavailable12.I would stick with [BN] even if it would let me downonce or twice13.I am so happy with [BN] that I no longer feel the needto watch out for other alternatives

14.I am likely to be using [BN] one year from now

0.84

Trust

(Chaudhuri &Holbrook,2001)

15.I trust [BN]

16.I rely on [BN]17.[BN] is an honest brand18.[BN] is safe to use

0.81

Online social media platform related

Involvement(Beatty & Talpade,

1994)

19.In general, I have a strong interest in Facebook20.Facebook is very important to me

21.Facebook matters a lot to me22.I get bored when other people talk to me aboutFacebook*

23.Facebook is relevant to me

0.83

Participation

(Self-constructed)

24.I consider myself an active user of Facebook

25.I log on to Facebook everyday

26.I spend long periods of time on Facebook

0.82

5 The abbreviation BN stands for brand name, as different respondents have answered the questions with

a different brand name in mind.6The items marked with * were reverse scored.


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Ease of use(Davis, 1989)

27.Learning to use Facebook is/was easy for me28.It is easy to get Facebook to do what I want it to do

29.It is clear and understandable how to use Facebook30.Facebook is flexible to interact with

31.It is easy to become skillful at using Facebook32.In general, I find Facebook easy to use

0.90

Telepresence(Kim & Biocca,

1997)

While browsing on Facebook..33 I feel like my mind is in a different world created

by Facebook34 I forget about the real world around me35 I feel like my mind is more present in theFacebook world than the real world

36.After I am done browsing on Facebook, I feel like my

mind comes back to the real world

0.89

Customer brand engagement on online social media platforms

Behavioral

(Self-constructed)

(Cheung, Lee, &Jin, 2011)

How often do you...

37.visit the Facebook FP7

of [BN]?38notice the posts by [BN] in your news feed?

39read posts by [BN]?40like posts by [BN]?41comment on posts by [BN]?

42share posts by [BN] with your friends?43post on the Facebook FP of [BN] yourself?

0.89

44.I can continue browsing on the Facebook FP of [BN]for long periods at a time45.I devote a lot of energy to the Facebook FP of [BN]

Emotional

(Cheung, Lee, &Jin, 2011)

46.I am enthusiastic about the Facebook FP of [BN]

47.The Facebook FP of [BN] inspires me48.I find the Facebook FP of [BN] full of meaning and

purpose

49.I am excited when browsing on and interacting withthe Facebook FP of [BN]

50.I am interested in the Facebook FP of [BN]51.I am proud of being a fan of [BN]

0.89

Cognitive(Cheung, Lee, &

Jin, 2011)

52.Time flies when I am browsing on the Facebook FP of[BN]53.Browsing on the Facebook FP of [BN] is so absorbingthat I forget about everything else54.I am rarely distracted when browsing on the Facebook

FP of [BN]55.I am immersed in browsing on and interacting with the

Facebook FP of [BN]

56.My mind is focused when browsing on the FacebookFP of [BN]

57.I pay a lot of attention to the Facebook FP of [BN]

0.90

7 The abbreviation FP stands for fan page.


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Consequences

Behavioral brandloyalty

(Chaudhuri &

Holbrook, 2001)

58.I will buy [BN] the next time I buy food/drinks59.I intend to keep purchasing [BN]

0.61

Word-of-mouth

(Zeithaml, Berry,& Parasuraman,

1996)

60.I say positive things about [BN] to other people

61.I often recommend [BN] to others62.I encourage friends to buy [BN]

0.89

Control variables

Goals(Self-constructed)

63.I browse on Facebook FPs because I am interested inthe brands

64.I browse on Facebook FPs because I am interested inbeing a part of a brand community

0.59

Resources(Self-constructed)

65.I have enough time to browse on Facebook FPs66.Browsing on Facebook FPs does not take too mucheffort

0.53

Perceived

cost/benefit(Self-constructed)

67.I enjoy browsing on Facebook FPs

68.I think that browsing on Facebook FPs is not worth thetime and effort*

0.56

The coefficient reliability analysis revealed that all the scales consisting of more than

two items exceeded the recommended Cronbachs alpha benchmark of 0.70 (Nunnally,

1978). However, the construct of behavioral brand loyalty measured by two items only has

performed an internal consistency of 0.61, which is considered to be questionable (George

& Mallery, 1999). In addition, the same happened to be the case with the three control

variables that were also operationalized by two items each and did not meet the 0.70

benchmark. However, the nature of the Cronbachs alpha dictates that its value is

determined not only by the mean of inter-item correlations, but also depends on the number

of the items in the scale, which implies that the scales with fewer items will generally be

expected to yield lower reliability coefficients. Therefore, the four underperforming two

item scales were not eliminated and used further in the analysis.

3.3 Statistical analysis

The approach applied in the data analysis of this study is called structural equation

modeling, which is a powerful framework for estimating causal models and systems of

simultaneous equations with measurement error. The structural model was established of

seven key constructs: customer brand relationship related antecedents (CBRR), online

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