The Effects of Shopping Orientations , Online Trust and Prior Online Purchase Experience toward Customers ’ Online Purchase Intention

The advancement of the World Wide Web has resulted in the creation of a new form of retail transactionselectronic retailing (e-tailing) or web-shopping. Thus, customers’ involvements in online purchasing have become an important trend. As such, it is vital to identify the determinants of the customer online purchase intention. The aim of this research is to evaluate the impacts of shopping orientations, online trust and prior online purchase experience to the customer online purchase intention. A total of 242 undergraduate information technology students from a private university in Malaysia participated in this research. The findings revealed that impulse purchase intention, quality orientation, brand orientation, online trust and prior online purchase experience were positively related to the customer online purchase intention.


Introduction
The advancement of the World Wide Web has resulted in the creation of a new form of retail transactionselectronic retailing (e-tailing) or web-shopping.The rapid growth of the Internet technology has enabled Malaysian consumers to purchase products or services from the web-retailers and search product information from the Internet.However, web-retailers can only offer certain ranges of products and services to web-shoppers, including e-banking services, technology gadgets, cosmetics, clothing and the booking of airlines ticket.Wolfinbarger and Gilly (2001) assert that web-shopping presents different shopping experiences even when the same products are purchased.Through web shopping, consumers interact in a virtual environment via the website interface (Alba, Lynch, Weitz and Janiszewski, 1997;Hoffman and Novak, 1996).Therefore, web shopping is perceived to be more risky and therefore trust and risk play prominent roles in online transaction (Forsythe and Shi, 2003;Pavlou, 2003).Web-shopping behaviour does not necessarily follow traditional consumer behaviour in the bricks-or-mortar retailing environment, thus Internet marketers are advised to explore the determinants of customer online purchasing intention among the web shoppers.With a good understanding of the web shopper's online purchase intention, web-retailers will be able to develop effective and efficient web-shopping strategies to attract new and potential web-shopping customers.Some models for examining web-shopper behaviour such as technology acceptance models (TAM) (Davis, Bagozzi and Warshaw, 1989) and online pre-purchase intentions models (Shim, Eastlick, Lotz and Warrington, 2001) have appeared in the extant literature.Forsythe and Shi (2003) argue that web shopping is perceived to be more risky than brick-or-mortar retailing transaction.Since consumer behaviour is cultural-specific, it is unclear whether the reported findings of the consumer online purchase intention in the western countries (which exhibit low uncertainty avoidance in the Hofstede cultural typology) can be directly applied in a cross-cultural context such as in Malaysia (which exhibit high uncertainty avoidance in the Hofstede cultural typology), particularly among Generation Y. Consequently, a gap is created in this research.Therefore, this study aims to examine the impacts of shopping orientations, online trust and prior online purchase intention on the customer online purchase intentions in Malaysia, particularly among Generation Y.

Internet Subscription in Malaysia
Based on the research carried out by Maddox and Gong (2005), the Internet market penetration rate has increased dramatically in Asia region.According to the Malaysia Internet Usage and Telecommunication report (retrieved from http://www.internetworldstats.com/asia/my.htm),the number of Internet subscribers has increased from 2.9 million in year 2004 to close to 5 million in year 2006.Thus, there is a sight of positive growth in the Internet subscription and Internet purchase in Malaysia.Considering that web shopping is still at the development stage in Malaysia, not much information is known about consumer attitude toward web shopping and factors that affect customer online purchase intention in the web-shopping environment.Therefore, it is crucial to identify the determinants of consumer online purchase intention in the web-shopping environment in Malaysia context.

Web-Shopping
Advancement in the Internet technology has facilitated the growth of in-home shopping (Lumpkin & Hawes, 1985).Shim, Quereshi and Siegel (2000) define web shopping as the process consumers go through to purchase products or services over the Internet.The terms online-shop, Internet-shop, web-shop and online-store are used interchangeably in the extant literature.Web shopping is an e-commerce system used by shoppers in the context of business-to-consumer (B2C) or business-to-business (B2B).
From the consumer's viewpoint, web shopping allows web shopper to search and compare various product or service alternatives from different online stores that are located in different parts of the world.The interactive nature of the Internet offers opportunities for consumers to use the web shopping facilities effectively by improving the availability of product information, enabling direct multi attributes comparison, and reducing prospective buyers' information search costs (Alba, et. al., 1997).
The Internet can also provide benefits to companies.As consumers are increasingly using the Internet as a shopping approach in performing their purchasing activities, companies can take this opportunity to use the Internet as a medium to attract and maintain current and potential customers.In this vein, online retailers must understand consumers' perceptions of website characteristics and their online shopping behaviour.Thus, the research will try to explore the concept of customer online purchase intention and the antecedent relationship of shopping orientations, online trust and prior online purchase experience on customer online purchase intention.

Customer Online Purchase Intention
Customer online purchase intention was one of the intensive research areas in the extant literature.Customer online purchase intention in the web-shopping environment will determine the strength of a consumer's intention to carry out a specified purchasing behaviour via the Internet (Salisbury, Pearson, Pearson and Miller, 2001).Furthermore, the theory of reasoned action suggested that consumer behaviour can be predicted from intentions that correspond directly in terms of action, target and context to that consumer behaviour (Ajzen and Fishbein, 1980).According to Day (1969), the intentional measures can be more effective than behavioural measures to capture customer's mind as customer may make purchases due to constraints instead of real preference when purchase is considered.
Purchase intention can be classified as one of the components of consumer cognitive behaviour on how an individual intends to buy a specific brand.Laroche, Kim and Zhou (1996) assert that variables such as consideration in buying a brand and expection to buy a brand can be used to measure consumer purchase intention.Based on the argument of Pavlou (2003), online purchase intention is the situation when a customer is willing and intends to become involved in online transaction.Online transactions can be considered as an activity in which the process of information retrieval, information transfer, and product purchase are taken place (Pavlou, 2003).The information retrieval and exchange steps are regarded as intentions to use a web site; however, product purchase is more applicable to an intention to handle a web-site (Pavlou, 2003).Therefore, it is crucial to evaluate the concept of online purchase intention in this study.In order to trigger customer online purchase intention, web retailers have to explore the impact of shopping orientations on the customer online purchase intention.

Shopping Orientations
Brown, Pope and Voges (2001) define shopping orientations as related to general predisposition toward the acts of shopping.This predisposition may be demonstrated in different forms such as information search, alternative evaluation, and product selection.Li, Kuo and Russell (1999) conceptualise the concept of shopping orientations as a specific portion of lifestyle and operationalised by a range of activities, interests and opinion statements that are relevant to the acts of shopping.
With the emergence of online shopping activities, customers' online shopping behaviour may be different in terms of their shopping orientations.Swaminathan, Lepkowska-White and Rao (1999) suggest that shopping orientations is one of the important indicators of making online purchase.Based on the relationship study between shopping orientations and online shopping orientation, Vijayasarathy and Jones (2000) identify seven types of shopping orientations, such as in-home shoppers who liked to shop from home; economic shoppers who shopped around before making purchase decisions; mall shoppers who preferred to shop at malls; personalized shoppers who liked to shop where they knew the salespeople; ethical shoppers who liked to shop in local stores to promote the community; convenience shoppers who placed a premium on convenience when shopping; and enthusiastic shoppers who enjoyed shopping.As the result of the study, it was found that customers who prefer traditional in-home shopping, such as by mail order via catalogs, tended to show high intentions toward online shopping, whereas individuals with a preference for mall shopping tended to have low online shopping intentions.
In the emergence of diverse retail outlets and increasing competition in the marketplace, online retailers must understand customers' shopping orientations in order to maximize customers' online purchase intention that leads to the increase in online sales.Several researchers have demonstrated that shopping orientations have significant impact on customer online purchase intention (Vijayasarathy & Jones, 2000;Park, 2002;Brown, et. al., 2001;Seock, 2003;Gehrt, Onzo, Fujita and Rajan, 2007).Shopping orientations is regarded as a multi-dimensional construct.According to Gehrt, et. al. (2007), there are 7 types of shopping orientations which include recreation, novelty, impulse purchase, quality, brand, price, and convenience.However, the present research will only explore three types of shopping orientation that includes impulse purchase orientation, quality orientation, and brand orientation.Thus, impulse purchase orientation, quality orientation, and brand orientation will be grouped under the category of shopping orientations.This together with online trust and prior online purchase experience will be tested as the independent variables for customer online purchase intention.Piron (1991) defines impulse purchase as an unplanned action that result from a specific stimulus.Rook (1987) argues that impulse purchase takes place whenever customers experience a sudden urge to purchase something immediately, lack substantive additional evaluation, and act based on the urge.Several researchers have concluded that customers do not view impulse purchase as wrong; rather, customers retrospectively convey a favourable evaluation of their behaviour (Dittmar, Beattie, and Friese, 1996;Hausman, 2000;Rook, 1987).Therefore, Ko (1993) reports that impulse purchase behaviour is a reasonable unplanned behaviour when it is related to objective evaluation and emotional preferences in shopping.Wolman (1973) frames impulsiveness as a psychological trait that result in response to a stimulus.Weinberg and Gottwald (1982) state that impulse purchase is generally emanated from purchase scenarios that feature higher emotional activation, less cognitive control, and largely reactive behaviour.Impulse purchasers also tend to be more emotional than non-purchasers.Consequently, some researchers have treated impulse purchase as an individual difference variable with the anticipation that it is likely to affect decision making across situations (Beatty and Ferrell, 1998;Rook and Fisher, 1995).

Impulse Purchase Orientation
Given the ongoing development of the digital economy and the shopping convenience being delivered through digitalized exchanges, one might reason that more impulse individuals may be more prone to online shopping.Donthu and Garcia (1999) assert that online shoppers were more likely to be impulse oriented.The study from Zhang, Prybutok and Strutton (2007) conclude that impulse purchase is positively related to the customer online purchase intention.

Quality Orientation
Quality is regarded as a key strategic component of competitive advantage and therefore the enhancement of product or service quality has been a matter of main concern to firms (Daniel, Reitsperger, and Gregson, 1995;Foster and Sjoblom, 1996).Garvin (1987) identifies five approaches to define quality: transcendent, product-based, user-based, manufacturing-based, and value-based.Transcendent definition of quality is synonymous with innate excellence.The assumption of transcendent approach is that quality is both absolute and universally recognizable.The product-based approach has its roots in economics.Garvin (1984) argues that differences in the quantity of some ingredients or attributes possessed by the product are considered to reflect differences in quality.Whereas in the user-based definition, quality is the extent to which a product or service meets or exceeds customers' expectations.The manufacturing-based approach has its roots in operation and production management.Its quality is defined as conformance to specifications (Crosby, 1979).Quality of conformance relates to the degree to which a product meets certain design standards.Besides, the value-based definition equates quality with performance at an acceptable price, or alternatively conformance at an acceptable cost.
The impact of quality orientation on online purchase intention is well documented in the extant literature.Bellenger and Korgaonkar (1980) state that recreational shoppers tended to consider quality, variety of product types and pleasant store atmosphere as important factors when choosing stores.In the context of web-shopping environment, Gehrt, et al. (2007) discovered that customers from the shopping enjoyment segment are positively inclined toward recreation, quality, and impulse orientations when making online purchase.

Brand Orientation
A brand is defined as a name or symbol, trademark and package design that uniquely identifies the products or services of a retailer, and differentiates them from those of its competitors (Aaker, 1991).In the cyber marketplace, a corporate brand identity is a cognitive anchor and a point of recognition where customers perceive a great deal of uncertainty (Rajshekhar, Radulovich, Pendleton and Scherer, 2005).For many online retailers, the brand name is the company name.In the e-commerce environment, trusted corporate and brand names are used by customers as substitutes for product information when they intent to make online purchase (Ward and Lee, 2000).
Several studies have found that brand loyalty exhibits strong impact on purchase intention in the traditional offline retailing world (Hawes and Lumpkin, 1984;Sproles and Kendall, 1986).A strong brand name not only attracts new customers, but also has the lock-in ability to make customers feel comfortable with their purchase decisions.A study carried out by Jayawardhena, Wright and Dennis (2007) conclude that brand orientation is positively related to the customer online purchase intention.

Online Trust
According to Kramer (1999), trust is a complex statement because individuals do not know what the motives and intentions of others are.Kimery and McCard (2002) define trust as customers' willingness to accept weakness in an online transaction based on their positive expectations regarding future online store behaviour.According to Barber (1983), trust is an expectation about individuals' behaviour within the society where they are living or by which they are ruled.Trust can be bestowed upon a person, an object (product), an organization (a business), an institution (the government) or a role (a professional of some kind).
Trust plays a key role in creating satisfied and expected outcomes in online transaction (Pavlou, 2003;Yousafzai, Pallister, and Foxall, 2003;Gefen and Straub, 2004;Wu and Cheng, 2005;Flavian and Guinaliu, 2006).According to the McCole and Palmer (2001), online purchasing necessitates online customer trust.Egger (2006) argues that sufficient trust needs to exist when placing an order online and when the customer submit his or her financial information and other personal data in undertaking financial transactions.Gefen (2000) asserts that the present of trust will increase the consumers' belief that the e-retailers will not engage in opportunistic behaviour.It has been demonstrated in the extant literature that trust beliefs positively influence customer online purchase intention (Verhagen, Meents, and Tan, 2006;Verhagen, Tan and Meents, 2004;McKnight, Choudhury and Kacmar, 2002;Lim, Sia, Lee and Benbasat, 2001;Jarvenpaa, Tractinsky, and Vitale, 1999).Jarvenpaa and Tractinsky (1999) and Gefen and Straub (2004) conclude that the higher the degrees of consumers' trust, the higher degree of consumers' purchase intentions of consumers.
Dimensions of online trust include security, privacy and reliability (Camp, 2001).Security is defined as the extent to which customers trust that the Internet is secure for them to transmit sensitive information to the business transaction (Kim and Shim, 2002).Security plays a crucial role in affecting the consumer attitudes and purchase intentions (Salisbury, et. al., 2001) because the present of perceived risk in transmitting sensitive information such as credit card numbers across the Internet (Janda, Trocchia, and Gwinner, 2002).Ernst and Young (cited in Lee and Turban, 2001) suggests that consumers may feel uncomfortable to release their personal information such as credit card and social security number through Internet because the consumers cannot physically check the quality of the products or monitor the safety and security of sending sensitive personal and financial information while shopping on the internet.Kim and Shim (2002) emphasize that the personal awareness of security has the significant influence on consumer attitudes and online purchase intentions.Chen and Barnes (2007) define privacy as the consumers' trust about the performance of other party in the environment during the market transaction or consumption behaviour.Lee and Turban (2001) argue that high level of security and privacy in the online shopping experience has a positive effect on consumer trust due to the perceived risk involved in the information exchange.Moreover, company reliability can influence the consumers' online trust and purchase intention (Balasubramanian, Konana, and Menon, 2003;Koufaris and Hampton-Sosa, 2004).In the web-shopping environment, most consumers assume that the large companies have better ability to increase their online trust (Koufaris and Hampton-Sosa, 2004).It is also proposed that a company with positive reputation does increase the consumers' trust (Doney and Cannon, 1997;Figueiredo, 2000).
2.9 Prior Online Purchase Experience Helson (1964) argued that an individual's response to a judgmental task is based on three aspects, which are sum of the individual's past experiences, context or background, and stimulus.Web shopping is a relatively new activity for a wide range of consumers, online purchases are still perceived as riskier than terrestrial ones (Laroche, Yang, McDougall and Bergeron, 2005).Therefore, web-shopping consumers will depend heavily on experience quality in which the experience quality can be obtained only through prior purchase experience.
Prior experiences will strongly affect future behaviour.In the web-shopping context, customers evaluate their online purchase experiences in terms of perceptions regarding product information, form of payment, delivery terms, service offered, risk involved, privacy, security, personalization, visual appeal, navigation, entertainment and enjoyment (Burke, 2002;Parasuraman and Zinkhan, 2002;Mathwick, Malhotra, and Rigdon, 2001).
According to Elliot and Fowell (2000), customer experience with the Internet drives the growth of Internet shopping.Shim and Drake (1990) argue that customers with strong online purchase intention in web shopping usually have prior purchase experiences that assist in reducing their uncertainties.Therefore, customers will only purchase product from the Internet after they have already experienced them.In additional, customers who have prior online purchase experience will be more likely to purchase through online than those who lack such experience.Seckler (2000) explains this phenomenon that as individual gain experience with web-shopping, perhaps with small purchases at first, they will be more likely to develop confidence and skills that facilitate more ambitious buying through the Internet.Dabholkar (1994) asserts that when an individual has less prior knowledge of the problems encountered, behavioural choice is mostly depended on expectancy-value model.Therefore, shoppers who have never done an online purchase before are more risk-averse than who have bought products through online means (Lee and Tan, 2003).If prior online purchase experiences resulted in satisfactory outcomes, this will lead customers to continue to shop on the Internet in the future (Shim, et. al., 2001).Unfortunately, if these past experiences are evaluated negatively, customers will be reluctant to engage in online shopping in the future.This explains the importance of turning existing Internet shoppers into repeat shoppers by providing them with satisfying online shopping experiences (Weber and Roehl, 1999).
Based on the vast extant literature, it can be concluded that customer's online purchase experience will have a significant effect on his or her future purchase intention for online shopping (Shim et al., 2001;So et al., 2005;Brown, et. al., 2001;Lynch and Ariely, 2000).

Hypotheses
Prior discussion has led to a brief examination of the existing literature and the development of the hypotheses in this research.The five hypotheses are: H1: Impulse purchase orientation is positively related to customer online purchase intention.H2: Quality orientation is positively related to customer online purchase intention.H3: Brand orientation is positively related to customer online purchase intention.H4: Online trust is positively related to the customer online purchase intention.H5: Prior online purchase experience is positively related to customer online purchase intention.

Research Design
Positivism approach was adopted in this research because this method allowed the researcher to search for truths of the observation by empirical evidence via the hypothetico-deductive method (Jankowicz, 2005).Furthermore, descriptive research design was adopted as the study has clear problem statements, specific hypotheses and detailed body of knowledge (Malhotra, 2004).

Questionnaire Design
The first part (Part A) of the questionnaire provides general information about the online purchasing behaviour of the potential respondents.The second part of the questionnaire elaborates the independent variables and dependent variable that would be tested in the survey.Questions in the form of scaled-response questions were adopted in the second part of the questionnaire because "scaling permits measurement of the intensity of respondents' answers" (Churchill and Brown, 2004, p.329).The third part of the questionnaire identifies demographic profile of the respondents.
The items of the questionnaire in this research were adopted from different sources of the extant literature.
The items for the independent variables "impulse purchase orientation", "quality orientation", and "brand orientation" are adapted from Gehrt, et. al. (2007) and Seock (2003).The items for the independent variable "online trust" are adapted from Chen and Barnes (2007).The items for the independent variable "prior online purchase intention" are adapted from Brunelle and Lapierre (2008).The items for the dependent variable "online purchase intention" are adapted from Chen and Barnes (2007).A 5-point Likert scale anchored by "strongly disagree" (1) to "strongly agree" (5) was used as the attitude measurement for the independent and dependent variables.Solomon, Dann, Dann and Russell-Bennett (2007, p.477) define Generation Y as "kids born between 1979 and 1994 (the younger siblings of Gen Xers)".Since the study focused on Generation Y, the target population covered all the undergraduate students enrolled in University 'A' and the sampling unit included all the current full-time undergraduate information technology students in University 'A'.All of these undergraduate students are born between 1986 and 1990.The university is one of the largest private universities in Malaysia; with an estimated student population of 18,000 pursuing 84 programs in nine faculties spread over four campuses.Students who had actual online purchase experience were targeted.The respondents were selected through the filtering question in the questionnaire.The targeted sample size was 250 and convenience-sampling technique was used to select potential respondents in this survey.Convenience sampling technique was adopted because the research looks for cross-cultural differences in consumer behaviour (ie., customer online purchase intention) (Zikmund, Babin, Carr and Griffin, 2010) and "convenience samples are best used for exploratory research when additional research will subsequently be conducted with a probability sample" (Zikmund, et al., 2010, p.396;Sekaran and Bougie, 2010).Respondents were instructed to answer the questions based on their most recent online purchase experience with one of the web-retailer via the Internet.

Administration of Survey
Self-administered survey method in the form of drop-off surveys technique was used to ensure the confidentiality and non-obligation aspects of participating in the survey.The survey was conducted in the lecture hall where respondents could return the questionnaires immediately into the box allocated.The voluntary nature of the participation was explained verbally as well as being indicated in the survey questionnaire.Students were invited to complete an anonymous survey questionnaire that took approximately 15 minutes of their time to complete.
A total of 250 sets of questionnaires were distributed and 248 questionnaires were collected.Out of that, 8 sets of questionnaires were considered unusable because they were incomplete.It was assumed that the respondents were either unwilling to cooperate or not serious with the survey.Therefore, subsequently only 242 usable questionnaires (96.8 percent) were used for data analysis using SPSS software version 14.

Respondents' Demographic Profile and Online Purchasing Behaviour
Based on the survey, male respondents represented 52.07 percent of the total respondents while female respondents 47.93 percent.In the case of age distribution, the majority of the respondents were between the ages of 21 to 23 (76.86 percent).In terms of ethnic compositions, the respondents were mainly Chinese ethnic group (91.74 percent).In the category of current year of study, most of the respondents study in year 3 (62.81%).Based on the survey, all the respondents (100%) have the experience of purchasing products and services via the online mode.Movie tickets (33.34%) and technology gadgets (21.43%) were the two most common items purchased by the respondents.At least half of the respondents (53.72%) use credit card as a mode of payment in the online purchasing process.

Reliability Test
The reliability of a measure indicates the stability and consistency with which the instrument measures the concept and helps to assess the 'goodness' of a measure (Cavana, Delahaye and Sekaran, 2001).All the constructs were tested for the consistency reliability of the items within the constructs by using the Cronbach Alpha reliability analysis.In Table 1, the results indicated that the Cronbach alpha for all the constructs were well above 0.7 as recommended by Cavana, et. al. (2001).Cronbach alpha for the constructs ranged from the lowest of 0.797 (prior online purchase experience) to 0.880 (online trust).In conclusion, the results showed that the scores of the Cronbach alpha for all the constructs used in this research exceeded the preferable scores of 0.70 and this indicated that the measurement scales of the constructs were stable and consistent.

Validity Test
Construct validity was adopted as validity measurement and factor analysis was used to measure the construct validity (Cavana, et. al., 2001).The details of the factor analysis were presented in Table 1.Based on the output shown, factor analysis was appropriate because the value of Kaiser-Meyer-Olkin (KMO) was 0.867 (between 0.5 and 1.0) and the statistical test for Bartlett test of sphericity was significant (p = 0.000; d.f.= 325) for all the correlations within a correlation matrix (at least for some of the constructs).Based on the principal components analysis and VARIMAX procedure in orthogonal rotation, the results also showed that the Eigenvalues for all the constructs were greater than 1.0, ranging from the lowest 8.210 (online purchase intention) to the highest of 18.131 (online trust).In terms of convergent validity, the factor loadings for all items within a construct were more than 0.50.Discriminant validity indicated that all items were allocated according to the different constructs.Therefore, the items were not overlapping and they supported the respective constructs.

Multiple Regression Analysis
Before employing regression analysis, there are six assumptions to be addressed.The assumptions include: (1) normality; (2) linearity; (3) independence of error term; (4) free from multicollinearity; (5) free from heterocedasticity; and (6) free from outlier and influential observations (Field, 2005).Based on the normally distributed histogram that was generated from the SPSS analysis, the normality assumption was met because the distribution of the residuals appeared to be unimodal and symmetric.From the scatterplot diagram, both the conditions of linearity and free from heterocedasticity were met because the residuals appeared to be randomly scattered and showed no patterns or clumps when plotted against the predicted values.The independence of error term was also met because the value of Durbin-Watson was 1.886, which was close to 2 (the closer to the value to 2, the better the independence of error) (Field, 2005, p.189).From the multicollinearity statistics generated, VIF values were all well below 10 and the tolerance statistics were all well above 0.2; therefore the data was free from multicollinearity.Lastly, the normal p-p plot analysis indicated that the data was free from outlier and influential observations because the normal probability plot was seen to be a straight line and the spread of the residuals were uniformed when plotted against the predicted values.
The result of the multiple regression analysis was presented in Table 2.The p value of the impulse purchase orientation (p = 0.000) is less than the alpha value of 0.05.Therefore, the research concludes that an impulse purchase orientation is positively related to the customer online purchase intention.Hypothesis 1 is supported.This finding supports the existing literature which states that the shopping orientations in term of impulse purchase will positively affect the online purchase intention (Zhang, et. al., 2007).
The p value for the quality orientation (p = 0.034) is also less than the alpha value of 0.05.Therefore, it can be suggested that quality orientation is positively related to the customer online purchase intention.Hypothesis 2 is therefore supported.This finding supports the existing literature that quality orientations will positively influence the customer online purchase intention (Gehrt, et. al., 2007).
The result from the research also postulated that the brand orientation is positively related to the customer online purchase intention, as the alpha value is less than 0.05 (p value = 0.001).Hypothesis 3 is therefore supported.According to Jayawardhera, et. al. (2007), brand orientation is positively related to the customer online purchase intention.
Hypothesis 4 is supported in this research.The p value of the online trust (p = 0.000) is less than the alpha value of 0.05.Therefore the hypothesis that indicates the positive relationship between online trust and the customer online purchase intention is supported.According to McCole and Palmer (2001), online purchasing necessitates online trust.
Finally, the result from the research also indicated that the prior online purchase experience is positively related to the customer online purchase intention, as the alpha value is less than 0.05 (p value = 0.000).Hypothesis 5 is therefore supported.According to Shim and Drake (1990), customers with strong online purchase intention in web-shopping usually have prior purchase experiences that assist in reducing their uncertainties.
Based on the SPSS output, the following multiple regression equation was formed: Customer Online Purchase Intention= -0.546 + 0.170 (Impulse Purchase Orientation) + 0.100 (Quality Orientation) + 0.130 (Brand Orientation) + 0.091 (Online Trust) + 0.279 (Prior Online Purchase Experience) The values of the un-standardized Beta coefficient among the independent variables ranges from the weakest relationship of 0.091 (online trust) to the strongest relationship of 0.279 (prior online purchase experience).Therefore, "prior online purchase experience" is the most important antecedent in affecting the customer online purchase intention."Impulse purchase orientation" (0.170), "brand orientation" (0.130), and "quality orientation" (0.100) are ranked second, third and fourth most important antecedents affecting the customer online purchase intention.In addition, the customer online purchase intention is explained 48.2 percent by the combination of the five independent variables (r square = 0.694), which includes impulse purchase orientation, quality orientation, brand orientation, online trust and prior online purchase experience.Table 3 shows the summary of the five hypotheses and its outcomes.

Implications of the Research
The research findings have brought managerial implications to the various stakeholders.In terms of managerial implication, the research findings do provide some insights and feedbacks for the e-retailers to formulate and implement various business strategies to increase the customer online purchase intention.The research finding discovered that the antecedents of the customer online purchase intention could be applied in both low uncertainty avoidance countries and high uncertainty avoidance countries (especially in Malaysia), particularly among Generation Y.To create the condition for prior online purchasing experience, e-retailers can provide free samples or free subscription for the potential web shoppers to test the products or services.To increase the customer impulse purchase, e-retailers can provide e-mail updates on product development or offer special discounts for a limited time to the potential online customers.E-retailers may offer loyalty programmes or club memberships for those online customers who exhibit strong brand orientation.For targeting quality-orientated customers, e-retailers can provide full online version of product quality information and product search information through the website to them.To increase the level of online trust, e-retailers must provide honest and trustworthy information to the potential web shoppers at all time.

Limitations of the Research
Although the research findings provide some new insights to researchers, these findings should be viewed in light of some limitations.The study in this research is focusing on those respondents who have some experiences in engaging online purchase intention.Therefore, the study does not cover those potential customers who do not have experienced in online transaction but have the intention to engage in online purchase activities.By incorporating the potential online customers in the study, this will enhance the generalisability of the subsequent research.In addition, the study does not explore the impact of gender differences in moderating the relationship between shopping orientations and customer online purchase intention.The finding from Jayawardhena, et. al. (2007) discovered that gender has a significant influence on online purchase intention.By incorporating the gender construct in studying the relationship between shopping orientations, and customer online purchase intention may able to enrich the extant literature.Lastly, the adoption of convenience sampling technique may limit how well the research represents the intended population (Zikmund, et al., 2010, p.396).Consequently, the respondents may not be representative and the study not generalisable.

Recommendations for Further Research
Due to the limitations of this research, three recommendations are suggested for further research for the purpose of enhancing the study of the customer online purchase intention.It is proposed to evaluate the impacts of shopping orientations, online trust and prior online purchase experience on the customer online purchase intention among the potential customers who have strong intention to engage in online purchasing activities.Besides, it is recommended to evaluate the relationship between shopping orientations and customer online purchase intention based on gender differences as well as the role of gender in mediating the relationship between shopping orientations and customer online purchase intention.Lastly, it is suggested to utilize probability sampling technique to evaluate customer online purchase intention in the future research., D.A. (1991).Managing brand equity: Capitalizing on the value of brand name, New York: Free Press.

Table 1 .
Factors Identified by the Principal Components Factor Analysis products/services from a web-retailer that I am familiar with, I would prefer to buy well-known brand name.It is important for me to buy products/services from the web-retailer with well-known brand names.Once I find a brand I like through web-shopping, I stick with it.The web site of this web-retailer wants to keep promises and obligations.The information provided by the web-retailer is plentiful and of sufficient quality.The infrastructure of the web site of this web-retailer is dependable.The web site of this web-retailer offers secure personal privacy.The web site of this web-retailer keeps my best interests in mind.Compared to other web site offered, the web site of this web-retailer is secure and reliable.The web site of this web-retailer would not behave opportunistically (e.g., gaining money illegally).The performance of the web site of this web-retailer fulfills my expectation.