Proceedings of 9th Annual London Business Research Conference
4 - 5 August 2014, Imperial College, London, UK, ISBN: 978-1-922069-56-6
Full, Partial Mediating and Moderating Play A Significant Role
in Online Purchase Items in Facebook among Facebook Users
Jamal Mohammed Esmail Alekam 1, Nik Kamariah Nik Mat3, Tunku Nur
Atikhah Tunku Abaidah3 Noraini Nasirun4 and Nur Syuhadah Kamaruddin5
The purpose of this study is to examine the factors influencing customer purchasing behaviour
towards online shopping via Facebook . The power of social media nowadays influenced
customers buying behaviour either via website or Facebook . The use of TPB has been proven
in many research, therefore again the TPB is used and the additional of variables were added.
Each variable is measured using 7-point interval scale: Facebook Intensity (7 items), perceived
behavioural control (4 items), subjective norm (5 items), attitude (5 items) and mediators
purchase orientation (8 items) and intention (5 items), moderator habit (11 items) and online
purchase (5 items). Using primary data collection method, 300 questionnaires were distributed
to target respondents of students in UUM, UniMap and KPTM. The responses were in terms of
offline and online whereby 161 responded in offline survey and 139 completed and return the
questionnaires. This representing 16.1% offline and 4.2% online response rate. The data were
analyzed using Structural equation modelling (SEM) using AMOS 7. Confirmatory factor
analysis of measurement models indicate adequate goodness of fit after a few items was
eliminated through modification indices verifications. Goodness of fit for the revised structural
model shows adequate fit. This study has established nine direct impacts: (1) purchase
intention and attitude; (2) purchase intention and subjective norm and (3) purchase intention
and facebook intensity; (4) purchase orientation and attitude (5) purchase orientation and
subjective norm; (6) purchase orientation and facebook intensity; (7) online purchase and
habit; (8) online purchase and purchase intention; (9) online purchase and purchase
orientation. The findings will be discussed further in this report.
Keywords: Online purchase, Theory of planned behaviour, Facebook intensity, purchase
orientation, intention, subjective norm, perceived behavioural control
1. Introduction
Social media play increasingly important roles as a marketing platform. More and more
retailers use social media to target teens and young adults, and social networking sites
are a central venue in that trend (Marketwatch.com 2008). Online shopping nowadays
become a trend and brings a lot of impact to customers and sellers. With the increasing
role of the Internet in daily life extends the re-search towards this emerging market and
changing customer behaviors. Companies facing the challenge of customer acquisition
are searching for ways to predict the factors that lead to actual purchases on the Internet
(AlJabari, Othman and Nik Mat, 2012).
_______________________________________________________________________
1
Dr. Jamal Alekam, Doctor in Marketing, College of Business, School of Business Management, Universiti
Utara Malaysia, gamal_mohammed2003@yahoo.com
2,
OYA-Graduate School of Business, Universiti Utara Malaysia
2
Dr Nik Kamariah Nik Mat, Professor in Marketing, OYA-Graduate School of Business, Universiti Utara
Malaysia, drnikuum@gmail.com,
3, 4, 5
Tunku Nur Atikhah Tunku Abaidah Noraini Nasirun and Nur Syuhadah Kamaruddin, OYA-Graduate
School of Business,Universiti Utara Malaysia
Correspondence to: Dr Jamal Mohammed Esmail Alekam, College of Business Sintok, 06010 Kedah Darul
Aman, Malaysia.Telephone: 00604-9287554, 0060175778276
Fax No.: 00604-9287422, gamal_mohammed2003@yahoo.com
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Proceedings of 9th Annual London Business Research Conference
4 - 5 August 2014, Imperial College, London, UK, ISBN: 978-1-922069-56-6
Electronic commerce has become one of the essential characteristics in the Internet era. According
to UCLA Center for Communication Policy (2001), online shopping has become the third most
popular Internet activity, immediately following e-mail using/instant messaging and web browsing
(Li and Zhang, 2002). According to the internet search, about 40% of social media users have
purchased an item after sharing or “favoriting” it on these sites. (The company uses “Shared or
Favorited” to mean pinned/repinned/liked on Pinterest; shared/liked/commented on Facebook;
tweeted/retweeted or favourite on Twitter.) Facebook is the network most likely to drive
customers to purchase. Social media drives not just online purchasing, but in-store purchasing as
well – and at about equal rates.
Thus, the objective of this study is to analyze the online purchase behaviour of facebook users.
This paper is structured as follows. First, we review the marketing literature on the theory of
planned behaviour, including mediators of intention and purchase orientation and habit as the
moderator. Next, we present the research framework, methods, measures and findings. Finally, the
results were discussed in terms of its contribution to the upgrading of banking services and
recommendations for future research.
2.
LITERATURE REVIEW
Online purchases are still considered to be risky compared to offline retail purchases (Laroche et
al., 2005). In an online shopping environment, prior online purchase experience leads to the
reduction of uncertainties and eventually leads to an increase in the customer purchase intention
(Shim and Drake, 1990). Online shoppers who have bought products online are more open and
inclined to shop online than others (Lee and Tan, 2003). Pavlou (2003) observed online purchase
intention to be a more appropriate measure of intention to use a web site when assessing online
consumer behavior. Since online transaction involves information sharing and purchase action,
purchase intention will depend on many factors (Pavlou,2003).
Theory of Planned Behavior
The theory of planned behaviour (TPB) was developed by Ajzen 1988. The theory proposes a
model which can measure how human actions are guided. It predicts the occurrence of a particular
behaviour, provided that behaviour is intentional.
The theory of planned behavior, introduced by Ajzen (1991), is an extension of the theory of
reasoned action made necessary by the original model‟s limitation in dealing with behaviors over
which people have incomplete volitional control (Ajzen, 1991). The theory of reasoned action
proposed that behavioral intention (BI) leads to behavior (B), and that BI is determined by the
consumer‟s attitudes toward purchasing or using a brand (Aact) and by a normative value or
subjective norm (SN) (Fishbein and Ajzen, 1975). Attitude toward behavior is defined as “an
individual‟s positive or negative feeling about performing the target behavior” (Fishbein and
Ajzen, 1975, p. 216). Subjective norm refers to “a person‟s perception that most people who are
important to him or her think he or she should or should not perform the behavior in question”
(Fishbein and Ajzen, 1975, p. 302).
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Proceedings of 9th Annual London Business Research Conference
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The theory of planned behavior adds one more variable, perceived behavioral control (PBC), to the
two existing determinants of intention, attitude toward the behavior and subjective norm. The
degree of PBC refers to an individual‟s perceptions of the presence or absence of the requisite
resources or opportunities necessary for performing a behavior (Ajzen and Madden, 1986; Chau
and Hu, 2001). PBC has two dimensions: an internal factor and an external factor. The internal
factor refers to the extent of confidence that a person has in his/her ability to perform a certain
behavior, which is grounded in one‟s self-efficacy (Bandura, 1997). The external factor refers to
resource constraints. These constraints are facilitating conditions available to an individual – such
as money, time, or technology – that are required to perform a behavior (Taylor and Todd, 1995).
The theory of planned behaviour is a theory which predicts deliberate behaviour, because
behaviour can be deliberative and planned.
Attitudes
Subjective norms
Behavioural intentions
Behavior
Perceived
behavioural control
The Theory of Planned Behavior (Azjen, 1991)
Purchase Intention
PBC was found to be the second most significant factor influencing respondents‟ purchase
intention in the proposed model by Junghwa, Byoungho and George (2013). This finding supports
many previous studies‟ result the significant impact of PBC on purchase intention (Kang et al.,
2006; Lim and Dubinsky, 2005; Shim et al., 2001).
Getting brands visible on blogs is an increasingly interesting way not only to improve attitudes, but
also to better reach potential buyers (Wyld (2008).
Online purchase intention refers to the strength of a consumer's intention to perform a specified
purchasing behaviour over the Internet (Salisbury et.al. 2001).
Online purchase
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Online purchasing is like a phenomenology among customers and sellers are now become more
creative in order to gain attraction from the buyers. Fourteen studies discuss online purchasing,
which refers to consumers actions of placing orders and paying. This is the most substantial step in
online shopping activities, with most empirical research using measures of frequency (or number)
of purchases and value of online purchases as measures of online purchasing; other less commonly
used measures are unplanned purchases (Koufaris et al. 2002) and Internet store sales (Lohse and
Spiller 1999). Online purchasing is reported to be strongly associated with the factors of personal
characteristics, vendor/service/product characteristics, website quality, attitudes toward online
shopping, intention to shop online, and decision making (Andrade 2000; Bellman et al. 1999;
Bhatnagar et al. 2000; Cho et al. 2001; Grandon and Ranganathan 2001; Jarvenpaa et al. 2000; Lee
et al. 2000; Sukpanich and Chen 1999).
Facebook intensity
Today, Facebook is the world‟s most successful social networking company. Facebook receives its
income from companies that want to access members through marketing and advertising activities
on the web site (Lilley et al., 2012, p. 83). Marketing via Facebook is a well-functioning concept.
Through this channel, it is possible for companies of all sizes to achieve marketing and branding
goals at a relatively low cost. A previous study from 2009 shows that more than half of Facebook
users have clicked on a company‟s Facebook page, and that 16 percent of them had sent a message
to a company (Palmer and Koenig-Lewis, 2009). Customers help promote the brand through their
commitment to Facebook and the brand‟s page. Companies / sellers also want to build a Facebook
page to encourage their customers to return and use it for online shopping (Jin, 2012).
Habit
In the online shopping context, a repetitive satisfactory shopping experience may not only increase
trust but also develop habit and reduce the impact of trust gradually. Habit has been used to predict
behavioral intention in the traditional retail context. However, the relationship between trust,
intention and habit has not been explored by researchers to date (Chiu, Hsu, Lai and Chang, 2012).
Researchers have found that habit moderates the relationship between satisfaction and online
repurchase intention. Unfortunately, none of them have investigated the moderating effect of habit
on the relationship between trust and repeat purchase intention.
However, one of the aims of this paper is to examine does habit able to be moderator for intention
to online purchase?
3.
RESEARCH METHODOLOGY
4.
This study formulates the online purchase towards the items offered in facebook. In the
research framework, it shows that intention and purchase orientation become a mediators for
attitude, subjective norms, perceived behavioural control and facebook intensity. Whereby, habit
becomes moderator between intention and online purchase.
Sampling and instrument
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Proceedings of 9th Annual London Business Research Conference
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This study focused on offline and online survey which for offline method the questionnaire has
been distributed to students in three universities as follows:
 Universiti Teknologi MARA (UiTM) – Operation Management (500)
 Universiti Malaysia Perlis (UniMAP) – final year student from business school (300)
 Kolej Poly-tech MARA – (200)
The sample for this method was about 1000 students by using the stratified sampling techniques.
Whereas, the Offline method consist of questionnaire that has been posted in Facebook of each
group members. Therefore the friends‟ list will answers the survey through online and click
submission button. The total population was 3306 friends which each member has different
number of friends as follow:



Atikah 1321,
Syuhadah – 1051
Noraini – 934
The used of theory of planned behavior allowed us to adopt the questionnaire design from as
article „Online purchase intentions model by Shim, S., Eastlick, M. A., Lotz, S. L., & Warrington,
P. (2001). Each variable is measured using previously developed instrument as follows: attitude
measure was adopted from Shim, S., Eastlick, M. A., Lotz, S. L., & Warrington, P. (2001). – (5
items measured by 7-point interval-scale of (1)- strongly disagree to (7)- strongly agree);
subjective norm was adopted from Shim, S., Eastlick, M. A., Lotz, S. L., & Warrington, P. (2001).
- (5 items measured by 7-point interval-scale of (1)- strongly disagree to (7)-strongly agree);
facebook intensity was adopted from Andreassen, C. S., & Brunborg, G. S. (2012) -(7 items
measured by 7-point interval-scale of (1)- strongly disagree to (7)- strongly agree); habit was
adopted from Chiu, C., Hsu, M., Lai, H., & Chang, C. (2012); -(11 items measured by 7-point
interval-scale of (1)- completely uncertain to (7)-completely certain) and online purchase was
adopted from Negra, A., & Mzoughi, M. N. (2012) - (5 items measured by 7-point interval-scale
of (1)- strongly disagree to (7)- strongly agree).
There are also eleven demographic questions included in the instrument which use ordinal and
nominal scale such as gender, age, education, program, institution, nationality, internet experiences
and online purchase frequency per year.
Data Screening and Analysis
The 300 dataset were coded and saved into SPSS version 16 and analyzed using AMOS version
7.0. During the process of data screening for outliers, three dataset were deleted due to
Mahalanobis (D2) values more than the χ2 value (χ2 =78.75; n=44, p<.001) leaving a final 257
dataset to be analyzed. We also conducted univariate normality computations using z-scores of
skewness statistics and standard error of skewness as well as kurtosis statistics. Z-score skewness
of more than 2 needs to be transformed since it is considered as non-normal data (Hair et al.,
2006). Thus, the z-score skewness values highlighted in grey were transformed using reflect
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Proceedings of 9th Annual London Business Research Conference
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function for negative values followed by square root function and ending in reflect function. For
positive z-values, reflect function was omitted (Tabachnik & Fidell, 2001). The transformed
variables were then used in subsequent CFA and structural models (Appendix 1).
Several statistical validity tests and analysis were further conducted such as reliability (Cronbach
alpha) and composite reliability tests, validity tests using confirmatory factor analysis (CFA) for
construct convergent, discriminant, and nomological validities.
Subsequently, the data was subjected to descriptive analysis, correlation and structural equation
modeling analysis. The steps in SEM analysis are CFA analysis, measurement analysis,
discriminant analysis (average variance extracted), composite reliability analysis, and direct
indirect impact analysis (mediating effects), testing the fit for the hypothesized structural model,
revised model, competing model, and comparison of nested model analysis.
4.
Results
Demographic Profile of the Respondents
The respondents‟ ages ranged from twenty to twenty four years old. There are more female
(62.6%) than male respondents (37.4%). The offline respondents are mostly full-time students
(49.8%) from UiTM, Unimap and Kolej Poly-Tech Mara, whereby the online respondents (50.2%)
were from various organizations. Their qualification varies from diploma and bachelor degree.
About (40.9%) respondents experienced more than ten years using the internet. And about (23.7%)
respondents had more than nine times of purchased things online and about 42% had one to two
frequent purchased per year.
Descriptive Analysis of Variables
The research framework consists of two exogenous and four endogenous variables (Table 3). Each
construct shows Cronbach alpha readings of acceptable values of above 0.8, well above Nunnally,
(1970) recommendation of 0.60 limits. The highest was 0.970 and the lowest was Facebook
intensity 0.903.
However, this variable is included in subsequent analysis because it is anticipated
that the spurious items will be self-deleted during confirmatory factor analysis (CFA) process.
Convergent Validity (Confirmatory Factor Analysis -CFA)
From the confirmatory factor analysis (CFA) result in (Table 6), we observed that the regression
estimates or factor loadings of all manifesting observed variables or items are adequate ranging
from 0.664 to 0.997. The factor loadings of latent to observed variable should be above 0.50 (Hair
et al., 2006).This indicates that all the constructs conform to the construct convergent validity test.
After deletions were made using modification indices suggestions, the remaining numbers of items
for each construct are as follows: attitude (from 5 to 4 items), subjective norm (5 items to 3),
perceived behavioural control (no deletion- 4 items remain), facebook intensity (7 items to 5),
habit (4 items of 11), purchase intention (no deletion remain 5 items), purchase orientation (4 item
of 8 items) and online purchase (4 items of 5).
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Composite Reliability
The calculations of composite reliability based on the standardized factor loadings obtained from
the final revised structural model. The equation for composite reliability is as follows:
( standardized loading)2
Composite reliability =
 standardized loading)2 +  j
The readings of composite reliability of all exogenous latent constructs are well above 0.60 except
for customer satisfaction (below 0.60) – (Teschan, Nunnally, Bourne, Hamel et. al 1979).
(Appendix 1)
Discriminant Validity
To substantiate discriminant validity, average variance extracted (AVE) is compared to correlation
squared of the interrelated variables of concerned (Fornell and Larcker, 1981) (see table 4 and
table 5). The AVE is derived from the calculation of variance extracted using the following
equation:
Variance Extracted (VE) =
 (standardized SMC)
 (Standardized SMC) +  j
The variance extracted is calculated and presented in (Appendix 2). From the variance extracted,
AVE is than calculated by averaging the two variances extracted of the variables. The finding is
presented in a matrix as in Table 4. For discriminant validity to be upheld, the value of AVE must
be more than correlation squared (Table 5). For example, between the variables online purchase
and purchase orientation, the AVE=0.91 (Table 4), while correlation squared=0.74 (Table 5).
Hence, AVE > correlation squared, or online purchase discriminates from purchase orientation.
Thus, discriminant validity is supported. All constructs used for this study support discriminant
validity.
Goodness of Fit of Structural Model
To arrive to the structural model, confirmatory factor analysis (CFA) was conducted on every
construct and measurement models (Table 6). The goodness of fit is the decision to see the model
fits into the variance-covariance matrix of the dataset. The CFA, measurement and structural
model has a good fit with the data based on assessment criteria such as GFI, CFI, TLI, RMSEA
(Bagozzi & Yi, 1988). All CFAs of constructs produced a relatively good fit as indicated by the
goodness of fit indices such as CMIN/df ratio (<2); p-value (>0.05); Goodness of Fit Index (GFI)
of >0.95; and root mean square error of approximation (RMSEA) of values less than 0.08 (<0.08)
(Hair et al., 2006).
Table 6 shows that the goodness of fit of generated or revised model is better compared to the
hypothesized model. This is expected as hypothesized model is usually strictly confirmatory
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(Byrne, 2001). GFI of revised model is 0.950 compared to GFI of hypothesized model of 0.664.
Root mean square Error Approximation (RMSEA) also shows a better readings of 0.027 for
revised model compared to 0.082 for hypothesized model (<0.08).
Hypotheses Results
Since the results of hypothesized model (Appendix 3) did not achieve model fit (p<0.000), hence,
the explanation of hypotheses result will be based on generated or revised model (Table 7 and
Appendix 4). The result demonstrates that purchase orientation, purchase intention and habit gave
a significant positive impact towards online purchase. Hence, Habit has a direct significant impact
on online purchase (CR=6.282; P<0.005) or H10 is asserted. Purchase intention has a positive and
direct impact on online purchase (CR=3.04; p<0.002), i.e H11 is asserted. Similarly, purchase
orientation has a positive and direct impact on online purchase. (CR=3.035; P<0.002), i.e H12 is
also asserted. On the other hand, attitude, subjective norm and Facebook intensity are also has
direct impact toward purchase intention. Attitude gave significant impact to purchase intention
(CR=3.734), subjective norm also shows significant impact towards purchase intention
(CR=2.106; p<0.035). Facebook intensity has significant impact to purchase intention (CR=5.33).
Purchase orientation also has significant impact from attitude, subjective norm and facebook
intensity. Alternatively, hypotheses H4 and H8 are not asserted. Thus these hypotheses are
rejected.
Mediating Effect Analysis of Revised Model
Table 9a and 9b shows the indirect effect estimates to test the mediating effects of attitude,
purchase orientation, purchase intention, Facebook intensity, subjective norms and online shopping
as hypothesized in hypotheses H13a to H14d. From the result, only H13b is supported, where:
Purchase intention mediates the relationship between subjective norm and online purchase. This
means that purchase orientation mediate the relationship between subjective norm and online
purchase.
Moderating Effect Analysis Using Multi Group Analysis (MGA) Method
Table 10a and 10b demonstrates the results to test the moderating effects of gender on the
relationships specified in hypotheses H15a ,H15b Gender moderates the relationship between habit
and purchase intention; (H15a) Gender moderates the relationship between habit and purchase
orientation; (H15b), Type of respondents moderates the relationship between habit and purchase
intention H16a and Type of respondents moderates the relationship between habit purchase
orientation H16b. also Habit moderates the relationship between intention and online purchase
H17. From the results, moderation hypotheses H15a accepted, H15b are rejected, H16a, H16b are
accepted and moderation hypotheses H17 accepted
Overall Comparison between structural models
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Table 11 indicates the overall comparison between two structural models (hypothesized and
revised) derived from the study. It shows that hypothesized model produces nine significant direct
impacts while revised model produces four significant direct impacts. Even though there are more
significant direct impacts in hypothesized model, the results could not be generalized due to nonachievement of p-value (p<0.05). It seems that four significant direct impacts of purchase
orientation to online purchase (H12) and purchase intention to online purchase (H11) are
consistently significant across the two structural models.
For mediating effects of purchase intention on each hypothesized paths, we found four full
mediating effects of: purchase intention mediates the relationship between subjective norm and
online purchase (H13b); purchase intention mediates the relationship between facebook intensity
and online purchase (H13c); purchase orientation partially mediates the relationship between
attitude and online purchase (H14a); and purchase orientation partially mediates the relationship
between subjective norm and online purchase (H14b) , purchase orientation also partially mediates
the relationship between habit and online purchase (H14d).
Among the two structural models, revised model achieved the higher squared multiple correlation
(SMC) or (R2 ), in which the revised model explains 44% variance in purchase orientation; 67.8%
variance in purchase intention and 68.6% variance in online purchase, (Table 8).
In the context of moderating effects (Table 10b) this study has found that gender and type of
responses either online or offline moderates the variables. (H15a) Gender moderates the
relationship between habit and purchase intention. Type of respondents moderates the relationship
between habit and purchase intention (H16a) and type of respondents moderates the relationship
between habit and purchase orientation (H16b). In the beginning, the hypothesized model was
habit moderates the relationship between purchase intention and online purchase (H17) but after
the revised model, the result was not significant and habit was non moderator between purchase
intention and online purchase.
5. Discussion
This study attempts to examine the online purchase among facebook users by using the TPB and
the additional variables of facebook intensity, purchase orientation and habit as moderator. The
Theory of Planned Behaviour is used as the conceptual underpinning (Ajzen, 1991). The
hypothesized model do not achieve model fit (p value=0.000, p <0.001). After the elimination has
been done the revised model came out to be p value = 0.073. This implies that hypothesized model
could not be generalized to the population as the sample was only concentrated on the students,
maybe it should be focused more on those who have income.
6. Suggestion for Future Research
The findings can be generalized for Malaysia because it was conducted in the universities that
representing online shoppers especially those who used facebook. This model has shown some
interesting findings which could be applied for utilization in research on a bigger scale to include
the whole of Malaysia especially those who actively involved in online business.
7. Conclusion
About the topic of ‘Online Purchase Items Offered in Facebook among
Facebook Users’, the model that has been developed slightly gave the new contribution in terms of
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moderating factor which is the gender and types of responses. These two factors gave impact on
moderating the Habit to Purchase Intention as well as Habit to Purchase orientation. This research
faced not significant impact towards the mediators. Maybe in the future the combination of theory
might be given more significant impact or extended research method would be contributing to new
findings.
This study has established nine direct impacts: (1) purchase intention and attitude; (2) purchase
intention and subjective norm and (3) purchase intention and facebook intensity; (4) purchase
orientation and attitude (5) purchase orientation and subjective norm; (6) purchase orientation and
facebook intensity; (7) online purchase and habit; (8) online purchase and purchase intention; (9)
online purchase and purchase orientation.
8.
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APPENDIX
SURVEY
PURCHASE ITEMS OFFERED IN FACEBOOK AMONG
FACEBOOK USERS
Dear respondents,
We are conducting research on PURCHASE ITEMS OFFERED IN FACEBOOK AMONG
FACEBOOK USERS The aim of the study is to investigate factors influencing purchase items offered in
facebook.
This survey consists of 58 statements regarding various aspects of users perceived quality followed by a
series of demographic questions about the students‟ portal website. It should take between 20 minutes to
complete.
Please be informed that taking part of this survey is voluntarily, and all information gathered will be kept
confidential. It will be used for academic purposes only.
If you have any difficulties answering the survey, kindly please contact the following researchers.
Your cooperation and participation in this survey is highly appreciated.
Yours Sincerely,
NORAINI NASIRUN @ HIRUN
TUNKU ATIKHAH TUNKU ABAIDAH
NUR SYUHADA KAMARUDDIN
Postgraduate Students
OYAGSB, UUM
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S ECTION A: DEMOGRAPHIC
1.
Gender
:
FEM ALE
M ALE
2.
Age
3.
Program : ____________________
4.
Institution
5.
Please indicate if you are local or international students
: ____________________
: ____________________
Local
International
6.
State your origin country: ___________________________
Internet Experience
< 6 years
8 – 10 years
7.
6 – 8 years
> 10 years
Online purchase frequency per year
1 – 2 times
7 – 8 times
3- 6 times
> 9 times
S ECTION B: ATTITUDE
B
Strongly
agree
Strongly
disagree
The following questions require respondents to evaluate attitude towards purchase items offered in facebook . Please circle the
appropriate answer. All items using a 7-point Likert scales anchored by “1” as strongly disagree to “7” being “strongly agree”.
ATTITUDE
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1
Purchase items offered in facebook is a good idea.
1
2
3
4
5
6
7
2
I like the idea of purchasing items offered in facebook.
1
2
3
4
5
6
7
3
Purchase items offered in facebook is a pleasant idea.
1
2
3
4
5
6
7
4
Purchase items offered in facebook is an appealing idea.
1
2
3
4
5
6
7
5
Purchase items offered in facebook is an exciting idea.
1
2
3
4
5
6
7
S ECTION C: S UBJECTIVE NORM
Strongly
agree
Strongly
disagree
The following questions require respondents to evaluate subjective norm towards purchase items offered in facebook . Please circle
the appropriate answer. All items using a 7-point Likert scales anchored by “1” as strongly disagree to “7” being “strongly agree”.
C
S UBJECTIVE NORM
1
People who influence my behaviour think that I should purchase
items offered in facebook.
1
2
3
4
5
6
7
2
People who are important to me think that I should purchase items
offered in facebook.
1
2
3
4
5
6
7
3
People whose opinion I value think that I should purchase items
offered in facebook.
1
2
3
4
5
6
7
4
People who are close to me think that I should purchase items
offered in facebook.
1
2
3
4
5
6
7
5
People who influence my decisions think that I should purchase
items offered in facebook.
1
2
3
4
5
6
7
S ECTION D: FACEBOOK INTENS ITY
Strongly
agree
Strongly
disagree
The following questions require respondents to evaluate facebook intensity towards purchase items offered in facebook . Pleas e
circle the appropriate answer. All items using a 7-point Likert scales anchored by “1” as strongly disagree to “7” being “strongly
agree”. For item no. 8, please refer to the scale provided.
D
FACEBOOK INTENS ITY
1
Facebook is part of my daily activity
1
2
3
4
5
6
7
2
I am proud to tell people I‟m on Facebook
1
2
3
4
5
6
7
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3
Facebook has become part of my daily routine
1
2
3
4
5
6
7
1
2
3
4
5
6
7
I feel out of touch when I haven‟t logged onto
4
Facebook for a while
5
I think I am part of the Facebook community
1
2
3
4
5
6
7
6
I would be sorry if Facebook shut down
1
2
3
4
5
6
7
In the past week, on average, approximately how many minutes/hours per day have you spent on Facebook?
0 = less than 10, 1 = 10–30, 2 = 31–60, 3 = 1–2 hours, 4 = 2–3 hours, 5 = 3-4 hours
7
6 = 4-5 hours, 7 = more than 5 hours
1
2
3
4
5
6
7
S ECTION E: PERCEIVED BEHAVIORAL CONTROL
Strongly
agree
Strongly
disagree
The following questions require respondents to evaluate perceived behavioral control towards purchase items offered in facebook .
Please circle the appropriate answer. All items using a 7-point Likert scales anchored by “1” as strongly disagree to “7” being
“strongly agree”.
E
PERCEIVED BEHAVIORAL CONTROL
1
I would be able to purchase items offered in facebook.
1
2
3
4
5
6
7
2
I have the resources to purchase items offered in facebook.
1
2
3
4
5
6
7
3
I have the knowledge to purchase items offered in facebook.
1
2
3
4
5
6
7
4
I have the ability to purchase items offered in facebook.
1
2
3
4
5
6
7
S ECTION F: BEHAVIORAL INTENTION
F
BEHAVIORAL INTENTION
1
I intend to purchase items offered in facebook in the future.
1
Strongly
agree
Strongly
disagree
The following questions require respondents to evaluate behavioral intention towards purchase items offered in facebook . Please
circle the appropriate answer. All items using a 7-point Likert scales anchored by “1” as strongly disagree to “7” being “strongly
agree”.
2
3
4
5
6
7
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2
I will purchase items offered in facebook in the future.
1
2
3
4
5
6
7
3
Given the chance, I predict I will purchase items offered in
facebook in the future.
1
2
3
4
5
6
7
4
It is likely that I will purchase items offered in facebook in the
future.
1
2
3
4
5
6
7
5
I expect to purchase items offered in facebook in the future.
1
2
3
4
5
6
7
S ECTION G: PURCHAS E ORIENTATION
Strongly
agree
Strongly
disagree
The following questions require respondents to evaluate purchase orientation towards purchase items offered in facebook . Please
circle the appropriate answer. All items using a 7-point Likert scales anchored by “1” as strongly disagree to “7” being “strongly
agree”.
G
PURCHAS E ORIENTATION
1
When I have the intention to purchase items offered in facebook, I
voluntarily delay the purchase.
1
2
3
4
5
6
7
2
I sometimes delay a purchase I have planned to perform over
facebook to maximize the likelihood of having the best deal.
1
2
3
4
5
6
7
3
Sometimes, I delay the purchase items offered in order to get
more information.
1
2
3
4
5
6
7
4
When I have the intention to purchase items offered in facebook ,
I spend a lot of time comparing web sites and shops.
1
2
3
4
5
6
7
5
I spend a lot of time searching for additional information to make
an online purchase decision
1
2
3
4
5
6
7
6
When my intention is to merely browse through facebook, I
sometimes make a purchase
1
2
3
4
5
6
7
7
I am impulsive when purchasing products/services items offered
in the facebook
1
2
3
4
5
6
7
8
When I purchase products/services spontaneously from the
facebook, I think released
1
2
3
4
5
6
7
S ECTION H: HABIT
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Completely
certain
Completely
uncertain
The following questions require respondents to evaluate habit towards purchase items offered in facebook . Please circle the
appropriate answer. All items using a 7-point Likert scales anchored by “1” as strongly disagree to “7” being “strongly agree”.
H
HABIT
1
Purchase items offered in facebook is something I do frequently
1
2
3
4
5
6
7
2
Purchase items offered in facebook is something I do
automatically.
1
2
3
4
5
6
7
3
Purchase items offered in facebook is something I do without
having to remember.
1
2
3
4
5
6
7
4
Purchase items offered in facebook is something that makes me
feel weird if I do not do it.
1
2
3
4
5
6
7
5
Purchase items offered in facebook is something that would
require effort not to do it.
1
2
3
4
5
6
7
6
Purchase items offered in facebook is something I do without
thinking.
1
2
3
4
5
6
7
7
Purchase items offered in facebook is something that has become
a routine for me.
1
2
3
4
5
6
7
8
Purchase items offered in facebook is something I have been
doing for a long time.
1
2
3
4
5
6
7
9
Purchase items offered in facebook is something I would find hard
not to do.
1
2
3
4
5
6
7
10
Purchase items offered in facebook is something I have no need to
think about doing.
1
2
3
4
5
6
7
11
Purchase items offered in facebook is something that's typically
“me”.
1
2
3
4
5
6
7
S ECTION I: ONLINE PURCHAS E
I
Strongly
agree
Strongly
disagree
The following questions require respondents to evaluate purchase items offered in facebook . Please circle the appropriate answer.
All items using a 7-point Likert scales anchored by “1” as strongly disagree to “7” being “strongly agree”.
PURCHAS E ITEMS OFFERED IN FACEBOOK
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1
I was happy with my purchase items offered in facebook
1
2
3
4
5
6
7
2
I was pleased with my purchase items offered in facebook
1
2
3
4
5
6
7
3
I was satisfied with my purchase items offered in facebook
1
2
3
4
5
6
7
4
I like to purchase items offered in facebook
1
2
3
4
5
6
7
5
Purchase items offered in facebook fit means to buy products
1
2
3
4
5
6
7
THANK YOU
Table 1
Operational Definition of Variables
Variable
Definition
Source
Attitude
Subjective Norm
Perceived
Behavioral
Control
Facebook
Intensity
Habit
Purchase
Intention
Purchase
Orientation
Online Purchase
Table 2
Hypotheses Formulation
H1
Attitude is related positively with purchase intention
H2
Subjective norm is related positively with purchase intention
H3
Perceived behavioral control is related positively with purchase intention
H4
Facebook intensity is related positively with purchase intention
H5
Habit is related positively with purchase intention
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H6
Attitude is related positively with purchase orientation
H7
Subjective norm is related positively with purchase orientation
H8
Perceived behavioral control is related positively with purchase orientation
H9
Facebook intensity is related positively with purchase orientation
H10
Habit is related positively with purchase orientation
H11
Purchase intention is related positively with online purchase
H12
Purchase orientation is related positively with online purchase
H13a
Purchase intention mediates the relationship between attitude and online purchase
H13b
Purchase intention mediates the relationship between subjective norm and online purchase
H13c
Purchase intention mediates the relationship between Facebook intensity and online
purchase
H13d
Purchase intention mediates the relationship between habit and online purchase
H14a
Purchase orientation mediates the relationship between attitude and online purchase
H14b
Purchase orientation mediates the relationship between subjective norm and online
purchase
H14c
Purchase orientation mediates the relationship between Facebook intensity and online
purchase
H14d
Purchase orientation mediates the relationship between habit and online purchase
H15a
Gender moderates the relationship between habit and purchase intention
H15b
Gender moderates the relationship between habit and purchase orientation
H16a
Type of respondents moderates the relationship between habit and purchase intention
H16b
Type of respondents moderates the relationship between habit and purchase orientation
H17
Habit moderates the relationship between purchase intention and online purchase
Table 3
Descriptive Statistic of Variables
Variable
Total
Mean
Items
Standard
Cronbarch
Deviation
Alpha
Composite
Reliability
Facebook Intensity
7
4.1017
1.190
0.903
0.982
Attitude
5
4.4708
1.120
0.955
0.989
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Subjective Norm
5
3.9502
1.188
0.939
0.987
Perceived Behavioral Control
4
4.1556
1.105
0.946
0.987
Habit
11
3.4163
1.166
0.972
0.993
Intent to Purchase
5
4.1588
1.167
0.970
0.993
Purchase Orientation
8
4.1931
1.087
0.930
0.977
Purchase
5
3.9307
1.351
0.956
0.990
Total Items
50
Table 4
Average Variance Extracted (AVE) Matrix of Exogenous Variables
Variable
1
2
3
4
5
6
7
1
Facebook Intensity
1
2
Attitude
0.92
1
3
Subjective Norm
0.92
0.94
1
4
Perceived Behavioral
Control
0.93
0.95
0.94
1
5
Habit
0.92
0.94
0.93
0.94
1
6
Intent to Purchase
0.94
0.96
0.95
0.96
0.95
1
7
Purchase Orientation
0.89
0.90
0.90
0.91
0.90
0.92
1
8
Purchase
0.93
0.95
0.94
0.95
0.94
0.96
0.91
8
1
Table 5
Correlation & Correlation square Matrix among Exogenous Variables
Variable
1
2
3
4
5
6
7
8
1
0.22
0.21
0.44
0.24
0.44
0.37
0.35
1
Facebook
Intensity
2
Attitude
0.47***
1
0.40
0.49
0.21
0.44
0.44
0.48
3
Subjective Norm
0.46***
0.63***
1
0.30
0.27
0.38
0.38
0.38
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4
Perceived
Behavioral
Control
0.67***
0.70***
0.55***
1
0.24
0.78
0.55
0.52
5
Habit
0.49***
0.46***
0.52***
0.49***
1
0.24
0.30
0.42
6
Intent to Purchase
0.67***
0.66***
0.62***
0.88***
0.49***
1
0.59
0.56
7
Purchase
Orientation
0.61***
0.66***
0.62***
0.74***
0.55***
0.77***
1
0.55
8
Purchase
0.59***
0.69***
0.61***
0.72***
0.65***
0.75***
0.74***
1
Significance Level: * = .05, ** = .01, *** = .001
Note: Values below the diagonal are correlation estimates among constructs, diagonal elements are
construct variances, and values above the diagonal are squared correlation. Since all correlations are
significant, mediation is plausible.
Table 6
Goodness of Fit Analysis-Confirmatory Factor Analysis (CFA) of Models (N=257)
Final Model
Attitude
Subjective
Norm
Perceived
Behavioral
Control
Facebook
Intensity
Habit
Purchase
Intention
Original Items
5
5
4
7
11
5
Items remain
4
3
4
5
4
5
1.340
13.187
66.069
9.761
4.673
4.455
2
2
2
5
2
5
CMIN/df
.670
6.593
33.034
1.952
2.336
.891
p-value
.512
.001
.000
.082
.097
.486
GFI
.997
.974
.877
.985
.991
.993
CFI
1.000
.986
.939
.995
.997
1.000
TLI
1.002
.959
.818
.991
.992
1.001
PNFI
.333
.328
.313
.495
.332
.499
CMIN
Df
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RMSEA
.000
.148
.354
.061
.072
.000
Table 6 (continued)
Goodness of Fit Analysis-Confirmatory Factor Analysis (CFA) of Models (N=257)
Final Model
Purchase
Orientation
Online
Purchase
Endogenous
Exogenous
Hypothesis
Model
Generated
Model
Original Items
8
5
18
32
50
-
Items remain
4
4
10
10
-
17
9.815
21.080
50.019
35.154
3113.688
116.284
2
2
32
29
1153
98
CMIN/df
4.908
10.540
1.563
1.212
2.700
1.817
p-value
.007
.000
0.022
0.2
0.000
0.100
GFI
.980
.959
0.963
0.973
0.664
0.950
CFI
.990
.984
0.995
0.997
0.877
0.995
TLI
.970
.952
0.992
0.995
0.870
0.994
PNFI
.329
.328
0.701
0.632
0.77
0.700
RMSEA
.124
.193
0.047
0.029
0.082
0.027
CMIN
Df
Table 7
Direct Impact of Generated Model: Standardized Regression Weights
Std. Est.
S.E.
C.R.
P-value
Status
Hypothesis
Endogenous
H1
Purchase Intention

Attitude
0.227
0.061
3.734
***
Sig.
H2
Purchase Intention

Subjective Norm
0.126
0.06
2.106
0.035
Sig.
H3
Purchase Intention
Facebook
Intensity
0.282
0.053
5.33
***
H4
Purchase Intention

Habit
0.081
0.05
1.642
0.101
Not Sig.
H5
Purchase Orientation

Attitude
0.353
0.093
3.806
***
Sig.
Exogenous

Sig.
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H6
Purchase Orientation

Purchase Orientation

H7
Subjective Norm
0.252
0.094
2.679
0.007
Facebook
Intensity
0.315
0.079
3.986
***
Sig.
Sig.
H8
Purchase Orientation

Habit
0.061
0.08
0.759
0.448
Not Sig.
H10
Online Purchase

Habit
0.39
0.062
6.282
***
Sig.
Online Purchase

Purchase
Intention
0.266
0.088
3.04
0.002
Purchase
Orientation
0.207
0.068
3.035
0.002
H11
Online Purchase
H12

Sig.
Sig.
Table 8
Squared Multiple Correlation Results
Endogenous Variable
Squared Multiple Correlation (SMC) =
R2
Purchase Indentation
0.678
Purchase Orientation
0.440
Online Purchase
0.686
H13a
Purchase intention mediates the relationship between attitude and online purchase
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Purchase Intention (INT)
a
b
.22***/.22***
.21(NS)/.33***
Attitude
Online Purchase
c
.29***/.000
Revised Model
Variables
Before
After
Remarks
(with ATT  Pur)
(w/o ATT  Pur)
ATT  INT
.22 ( ***)
.22 ( ***)
No change
INT  Pur
.21 (NS)
.33 ( ***)
ATT  Pur
.29 ( ***)
.000
Increased
0)
Before (Sig)
Indirect effects
0.067 (NS)
0.190 (Sig)
Direct effects
0.29 (Sig)
0.000
Total effects
0.357 (NS)
0.190 (Sig)
Std estimates (Correlation)
Verdict
Purchase Intention (INT) is not a mediator between attitude (ATT) and online purchase (Pur)
H13b
Purchase intention mediates the relationship between subjective norm and online purchase
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Purchase Intention (INT)
a
b
.12*/.12*
.21**/.20**
Subjective Norm (SN)
Online Purchase (Pur)
c
.000/.06(NS)
Revised Model
Variables
Before
After
(w/o SN  Pur)
(with SN  Pur)
SN  INT
.12 ( *)
.12 ( *)
INT  Pur
.21 ( **)
.20 ( **)
SN  Pur
.000
.06 (NS)
0.025 (Sig)
0.04 (Sig)
Direct effects
.000
0.06 (NS)
Total effects
0.025 (Sig)
0.084 (NS)
Remarks
Std estimates (Correlation)
Indirect effects
No change
0)
Reduce
Verdict
Purchase Intention (INT) is full mediator between subjective norm (SN) and online purchase (Pur)
H13c
Purchase intention mediates the relationship between Facebook intensity and online
purchase
25
Proceedings of 9th Annual London Business Research Conference
4 - 5 August 2014, Imperial College, London, UK, ISBN: 978-1-922069-56-6
Purchase Intention (INT)
a
b
.30***/.30***
.21**/.15(NS)
Facebook Intensity (FI)
Online Purchase (Pur)
c
.000/.12(NS)
Revised Model
Variables
Before
After
(w/o FI  Pur)
(with FI  Pur)
FI  INT
.30 ( ***)
.30 ( ***)
INT  Pur
.21 ( **)
.15 (NS)
.000
.12 (NS)
Indirect effects
0.063 (Sig)
0.054 (NS)
Direct effects
.000
.12 (NS)
Total effects
0.063 (Sig)
0.174 (NS)
Remarks
Std estimates (Correlation)
FI  Pur
No change
0)
Reduce
Verdict
Purchase Intention (INT) is a mediator between Facebook intensity (FI) and online purchase (Pur)
H13d
Purchase intention mediates the relationship between habit and online purchase
26
Proceedings of 9th Annual London Business Research Conference
4 - 5 August 2014, Imperial College, London, UK, ISBN: 978-1-922069-56-6
Purchase Intention (INT)
a
b
.09(NS)/.08(NS)
.21**/.32(NS)
Habit (HABIT)
Online Purchase (Pur)
c
.32(***)/.000
Revised Model
Variables
Before
After
(with HABIT 
Pur)
(w/o HABIT 
Pur)
HABIT  INT
.09 (NS)
.08 ( NS)
INT  Pur
.21 (.002)
.32 ( ***)
HABIT  Pur
.32 ( ***)
.000
Indirect effects
0.0189 (NS)
0.026 (NS)
Direct effects
.32
.000
Total effects
0.340 ( NS)
0.174 (NS)
Remarks
Std estimates (Correlation)
0)
Verdict
Purchase Intention (INT) is not a mediator between habit (HABIT) and online purchase (Pur)
H14a
Purchase orientation mediates the relationship between attitude and online purchase
27
Proceedings of 9th Annual London Business Research Conference
4 - 5 August 2014, Imperial College, London, UK, ISBN: 978-1-922069-56-6
a
Purchase Orientation (PO)
b
.29(***)/.30(***)
.29(.002)/.27(***)
Attitude (Att)
Online Purchase (Pur)
c
.20(***)/.000
Revised Model
Variables
Before
After
(with Att  Pur)
(w/o Att  Pur)
Att  PO
.29 ( ***)
.30 (***)
PO  Pur
.29 (.002)
.27(***)
Att  Pur
.20 ( ***)
.000
Indirect effects
.084 (Sig)
.081 (Sig)
Direct effects
.20
.000
Total effects
.284 (Sig)
.081 (Sig)
Remarks
Std estimates (Correlation)
0)
Verdict
Purchase orientation (PO) is a partial mediator between Attitude (Att) and online purchase (Pur)
H14b
Purchase orientation mediates the relationship between subjective norm and online
purchase
28
Proceedings of 9th Annual London Business Research Conference
4 - 5 August 2014, Imperial College, London, UK, ISBN: 978-1-922069-56-6
a
Purchase Orientation (PO)
b
.21(**)/.20(**)
.20(**)/.19(**)
Subjective Norm (SN)
Online Purchase (Pur)
c
.000/.06(**)
Revised Model
Variables
Before
After
(w/o SN  Pur)
(with SN  Pur)
SN  INT
.21 (.007)
.20 (.008)
INT  Pur
.20 (.002)
.19 (.004)
SN  Pur
.000
.06 (.003)
0.042 (Sig)
0.038 (Sig)
Direct effects
.000
.06 (Sig)
Total effects
0.042 (Sig)
0.098 (Sig)
Remarks
Std estimates (Correlation)
Indirect effects
0)
Verdict
Purchase orientation (PO) is a partial mediator between subjective norm (SN) and online purchase
(Pur)
H14c
Purchase orientation mediates the relationship between Facebook intensity and online
purchase
29
Proceedings of 9th Annual London Business Research Conference
4 - 5 August 2014, Imperial College, London, UK, ISBN: 978-1-922069-56-6
a
Purchase Orientation (PO)
b
.28(***)/.27(**)
.19(**)/.18(**)
Facebook Intensity (FI)
Online Purchase (Pur)
c
.000/.12(*)
Revised Model
Variables
Before
After
(w/o FI  Pur)
(with FI  Pur)
FI  PO
.28 ( ***)
.27 (.008)
PO  Pur
.19 (.004)
.18 (.006)
FI  Pur
.000
.12 (.042)
.053 (Sig)
0.05 (Sig)
Direct effects
.000
.12 (.042)
Total effects
.053 (Sig)
0.086 (Sig)
Remarks
Std estimates (Correlation)
Indirect effects
0)
Verdict
Purchase orientation (PO) is a partial mediator between Facebook intensity (FI)and online purchase
(Pur)
H14d
Purchase orientation mediates the relationship between habit and online purchase
30
Proceedings of 9th Annual London Business Research Conference
4 - 5 August 2014, Imperial College, London, UK, ISBN: 978-1-922069-56-6
a
Purchase Orientation (PO)
b
.05(NS)/.06(NS)
.18**/.18**
Habit (HABIT)
Online Purchase (Pur)
c
.010(NS)/.000
Revised Model
Variables
Before
After
(with HABIT 
Pur)
(w/o HABIT 
Pur)
HABIT  PO
.05 (NS)
.06 (NS)
PO  Pur
.18 (.006)
.18 (.010)
HABIT  Pur
.29 ( ***)
.000
Indirect effects
.010 (NS)
.010 (NS)
Direct effects
.29 (Sig)
.000
Total effects
.299 (NS)
.010 (NS)
Remarks
Std estimates (Correlation)
0)
Verdict
Purchase orientation (PO)is not a mediator between habit (HABIT) and online purchase (Pur)
Table 9a
Hypotheses Formulation (Mediating Effects)
H13a
Purchase intention mediates the relationship between attitude and online purchase
H13b
Purchase intention mediates the relationship between subjective norm and online purchase
H13c
Purchase intention mediates the relationship between Facebook intensity and online
purchase
H13d
Purchase intention mediates the relationship between habit and online purchase
H14a
Purchase orientation mediates the relationship between attitude and online purchase
31
Proceedings of 9th Annual London Business Research Conference
4 - 5 August 2014, Imperial College, London, UK, ISBN: 978-1-922069-56-6
H14b
Purchase orientation mediates the relationship between subjective norm and online
purchase
H14c
Purchase orientation mediates the relationship between Facebook intensity and online
purchase
H14d
Purchase orientation mediates the relationship between habit and online purchase
Table 9b
Indirect Effect of Variables Interaction (Mediating Effect)
H
H13a
H13b
H13c
H13d
H14a
H14b
H14c
H14d
Exogenous
Attitude
Mediated

Subjective
Norm

Facebook
intensity

Habit

Attitude

Subjective
Norm

Facebook
intensity

Habit

Endogenous
Purchase
intention

Purchase
intention

Purchase
intention

Purchase
intention

Purchase
orientation

Purchase
orientation

Purchase
orientation

Purchase
orientation

direct Effects EstimateNo link
direct
Effects
Estimatelink
Online
purchase
AttINT=.22(S)
.357(NS)
INTPur=.33(NS)
.190(S)
Online
purchase
SNINT=.12(S)
.025(S)
INTSN=.21(S)
.084(NS)
Online
purchase
FIINT=.30(S)
.174(NS)
INTFI=.21(S)
.063(S)
Online
purchase
HABINT=.08(NS)
.340(NS)
INTHAB=.32(S)
.086(NS)
Online
purchase
Att PO = .30(S)
.384(S)
PO  Pur = .27(S)
.81(S)
Online
purchase
SN PO =.21(S)
.042 (S)
PO Pur =.20 (S)
.098 (S)
Online
purchase
FIPO =.28 (S)
.053 (S)
PO Pur =.19 (S)
.086 (S)
Online
purchase
HAB PO=.06(NS)
.010 (NS)
PO Pur =.18(NS)
.299 (NS)
Mediating
Hypothesis
Non
mediator
Full
mediator
Full
mediator
Non
mediator
Partial
mediator
Partial
mediator
Non
mediator
Partial
mediator
32
Proceedings of 9th Annual London Business Research Conference
4 - 5 August 2014, Imperial College, London, UK, ISBN: 978-1-922069-56-6
Table 10a
Hypotheses Formulation (Moderating Effects)
H15a
Gender moderates the relationship between habit and purchase intention
H15b
Gender moderates the relationship between habit and purchase orientation
H16a
Type of respondents moderates the relationship between habit and purchase intention
H16b
Type of respondents moderates the relationship between habit and purchase orientation
H17
Habit moderates the relationship between intention and online purchase
Table 10b
Moderating Effects
H
H15a
H15b
H16a
H16b
H17
Exogenous
Habit
Habit
Habit
Habit
Purchase
Intention
Moderate





Gender
Gender
Endogenous


Type of
Response

Type of
Response

Habit

Directs Estimate
Each group
(TF Model)
HAB INT
HAB  PO
Purchase
Intention
Female: .11 (NS)
Purchase
Orientation
Female: .20 (NS)
Purchase
Intention
Purchase
Orientation
Online
Purchase
Combined group
(Constrained)
direct Estimate
HABINT
HAB  PO
Moderating
Hypothesis
.09 (NS)
Moderator
.05 (NS)
Non
Moderator
.09 (NS)
Moderator
.05 (NS)
Moderator
.559 (NS)
Non
Moderator
Male: .20 (S)
Male: .09 (NS)
Online: .23 (S)
Offline .10 (NS)
Online: -.07 (NS)
Offline .26 (S)
.002 (S)
33
Proceedings of 9th Annual London Business Research Conference
4 - 5 August 2014, Imperial College, London, UK, ISBN: 978-1-922069-56-6
HYPOTHESIS MODEL
REVISED MODEL
34
Proceedings of 9th Annual London Business Research Conference
4 - 5 August 2014, Imperial College, London, UK, ISBN: 978-1-922069-56-6
35