Full, Partial Mediating and Moderating Play A ...

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, [email protected] 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, [email protected], 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, [email protected]

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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). 1

Proceedings of 9th Annual London Business Research Conference 4 - 5 August 2014, Imperial College, London, UK, ISBN: 978-1-922069-56-6 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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Proceedings of 9th Annual London Business Research Conference 4 - 5 August 2014, Imperial College, London, UK, ISBN: 978-1-922069-56-6 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 3

Proceedings of 9th Annual London Business Research Conference 4 - 5 August 2014, Imperial College, London, UK, ISBN: 978-1-922069-56-6 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 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 (0.05); Goodness of Fit Index (GFI) of >0.95; and root mean square error of approximation (RMSEA) of values less than 0.08 (