Factors That Affect Online Shopping Decision Making Marketing Essay

Published Date: 23 Mar 2015

Online shopping is the procedure that consumers directly buy goods and services from sell or services from a seller in real time, without an intermediary service such as supplier, through using the network for internet. Online retailing are similar as online shop, e-shop, e-store, internet shop, and web-shop, and web store, online store buying product or services at a shopping center. This marketing strategies is one of the process is called business to consumer (B2C) online shopping. The largest online retailing corporations such as E-bay and Amazon .com are one of the famous online businesses located in US based. At the moments, the internet based electronic commerce environment enables consumers to search for information and purchase products or services through direct interaction with the online store. That is, consumers' purchases are mainly based on cyberspace appearance such as pictures, image, quality information, and video clips of the product, not on the actual experience (Lohse and Spiller, 1998; Kolesar and Galbraith, 2000). Shopping depends, to a great extent, on user interfaces and how people interact with computers (Hoque and Lohse, 1999; Griffith et a., 2001). Moreover, the characteristics of information presentation, navigation, order fulfillment in an interactive shopping medium are considered a more important factor in building electronic commerce trust than in the traditional retailing (Alba et al., 1997; Reynolds, 2000).

In the literature on electronic commerce, there have been active on research on consumers' shopping experience and their evaluation based on perception about the online shopping website (Jarvenpaa and Todd, 1997; Szymanski and Hise, 2000; Griffith et al., 2001). This line of research considers consumers' information processing style, shopping patterns, storefront preferences, and related areas for insight into developing more attractive, user friendly, and successful internet stores. However, few studies provide empirical validation of consumer behaviors in the web based online shopping context. We adapt the theory of user information satisfaction and consumer purchase behaviour.

We investigated how the content and presentation product and services information affect consumers' willingness to patronize an online store. Finally, we identify and discuss several factors affecting consumers' purchase behavior as well as their perception and satisfaction.

Besides that, businesses with the most experience and success in using e-commerce are beginning to realize that the key determinants of success or failure are not merely website presence and low price but also include the electronic service quality (e-service quality) (Yang, 2001; Zeithaml, 2002). Santos (2003) defined e-service quality as overall customer assessment and judgment of e-service delivery in the virtual marketplace. Service quality is an elusive and abstract construct that is difficult to explain and measure (Cronin and Taylor, 1992).

The SERVQUAL model first developed by Parasuraman et al. (1988) has been widely tested as a means of measuring customer perceptions of service quality. The SERVQUAL model contains five dimensions: namely tangibles, reliability, responsiveness, assurance, and empathy. Research is required on the influence of e-services on all customer responses such as perceived service quality, customer satisfaction, and purchase intentions (Parasuraman and Grewal, 2000; Jeong et al., 2003). Understanding the determinants of service quality, customer satisfaction, and purchase intentions for online shopping are important for both marketing researchers and online stores managers. Moreover, previous studies have revealed that service quality in online environments is an important determinant of the effectiveness of e-commerce (Yang, 2001; Janda et al., 2002).

Background of Research and Research Question

In the recent year, online shopping is famous way whereby online shoppers using advanced technology such as internet directly purchase the goods and services they want from a seller without intermediary market. Online shopping provides variety goods and convenience. Customer can buy anything they want around the world through the internet.

In general, shopping has always targeted to middle class and upper class women. Nowadays, shopping has evolved with the growth of technology. Thus, online shopping becomes favourable for everyone if they able access with has a computer, a bank account and a debit card.

Many studies discuss about factors influences online shopping. Most of those studies have tended to measure variables of influence consumer purchase intention which included social, cultural, personal, psychology, and so on. However, compare with traditional shopping, the studies found that online shopper restrict with social, cultural environment, and psychological factors.

In order to achieve the objective of research, this study addresses the following research questions:

What factors are those affect consumers' online shopping decision making?

Research Objective

To determine whether trust affects online shopping decision making.

To determine whether personal involvement affects online shopping decision making.

To determine whether website design affects online shopping decision making.

To determine whether website quality affects online shopping decision making.

To determine whether website security affects online shopping decision making.

Significance and Justifications for the Study

Nowadays, there are more and more people prefer online shopping especially teenagers. This study is conducted on the student's decision making when purchased online. This study can provide some useful guidelines and tips to consumer who like to online shopping. Besides that, the study is also provides some potential guidelines to online sellers about consumer behaviors in the Web-based online shopping context. Consumer-purchased online are mainly based on the cyberspace appearance such as pictures, images, quality information, and video clips of the product, not on the actual experience (Lohse and Spiller, 1998; Kolesar and Galbraith, 2000). Decision making is the stage before consumers commit to online transaction or purchasing, and sometimes considered to be a behavioral stage. The study based on decision making of online shopping is becomes important because student more intend to buy things through internet. After a few successful transactions, a consumer starts to feel safe with the service provider or supplier (Ravald and Gronroos, 1996). When the consumers trust the online website, they know that this online seller is able to fulfill their needs and wants. Finally, they become committed to the specific website.

The study is tending to offer the factors and important ways for consumer on how to purchase things through internet wisely. On the other hands, this study is also provides some useful ways to online seller about consumer buying behavior. The distributor should identify his potential consumers and continuously try to understand them better than his competitors (Chetochine, 1992; Hallerman, 1994), which ultimately may favors the buyer's attitude towards the online website. Understanding the characteristics of potential online consumers can help businesses to target potential markets accurately.

Amichai-Hamburger (2002) indicated that the personality of Internet users plays an important role in their online behavior. This study can provide inputs for government to educate the young generations on spending their money wisely and effectively by considering the different aspects when they purchased online. Students and consumers should think twice and making decision from different aspect such as website quality when they purchased online.

Research Scope

The study was conducted in Multimedia University Melaka. The target population of the study was 100 students from MMU students. Set of question will be designed and those participants were asked to answer on their monthly allowance, gender, and other relevant factors that they will consider when they make decision to do online shopping. Each participants is required to answer from the aspects of personal involvement, trust, website design, website quality, and website security while they making decision in online shopping.

1.6 Operational Definition

Key Terms

Definitions

Sources

Online Shopping Decision Making

Online shopping decision-making includes information seeking, comparison of alternatives, and choice making.

(Na Li and Ping Zhang, 2002)

Personal Characteristic - Trust

Trust is characterised in terms of the expectations and willingness of the trusting party in a transaction, the risks associated with acting on such expectations, and the contextual factors that either enhance or inhibit the development and maintenance of trust.

(Lee and Turban, 2001)

Website Design

In the Internet market, retailers' websites have become a valuable channel for selling and interacting with customers, and an important medium for communicating with the general public as well as potential consumers.

(Hoque and Lohse 1999; Jarvenpaa and Todd 1996/97)

E-Service Quality

The e-service quality represents the trust cue that conveys the trustworthiness of the site and the system to customers.

(Corritore et al., 2003)

Product / Personal Involvement

Individual motivation regarding an object where that motivational state is activated by the relevance or importance of the object in question.

(Koufaris, 2002)

1.8 Organisational of Research

The research report is covered in five chapters. The chapter one in this study is included introduction, background of the study and research question, research objective, significance and justifications for the study, research scope, and operational definition.

Chapter two is comprised the introduction, journal analysis consists of dependent variable (online shopping decision making), personal characteristic (trust), personal involvement, website design, e-service quality, and e-service security which stated the findings of previous researchers. In addition, this study also show that the relationship between trust and online shopping decision making, the relationship between personal involvement and online shopping decision making, the relationship between web site design and online shopping decision making, the relationship between website quality and online shopping decision making, and the relationship between website security and online shopping decision making as well as the summary.

Furthermore, chapter three is comprised the introduction (theoretical frameworks, hypothesis development), research design, research instrument and sampling method, data collection method (literature review, questionnaire survey for quantitative data), data analysis method (what is the software to be used, frequency analysis, reliability analysis, quantitative analysis, mean analysis, Pearson correlation coefficient, and multiple regression analysis).

Next, chapter four is the results from the analysis that has matched with the hypothesis of study. This study is included introduction, descriptive statistics, reliability analysis, mean analysis, and multiple regression analysis.

Lastly, for chapter five is the summarization of research findings, which consists introduction, research findings, knowledge implications, managerial implications, limitations of the study, recommendations for the study, and conclusion.

Chapter2 Literature Review

2.1 Introduction

This chapter will cover the literature review of online shopping decision-making which is the dependent variable of our study. Our literature review will include the independent variables which are trust, personal involvement, website design, website quality, and website security. Besides, we will discuss about the relationship between dependent variable and independent variables.

2.2 Dependent Variable: Online Shopping Decision Making

Advances in internet technologies have grown tremendously over the years. Not surprisingly, one application of these Internet technologies that has grown right along with them is that of online shopping.

Xu, Y. and Paulins, V. A. (2005) found that more than half of college students in their study mentioned credit card security and return policy concerns. Limited social activities were also noted when shopping online for apparel products. About 30% of the participants were concerned about merchandise quality and customer service support. While about half of the respondents thought shopping online was convenient, only about 20% considered online item price as lower than that of items sold in traditional stores. About 50% of the respondents agreed that online shopping can offer more merchandise options than traditional shopping.

Other than these, Koufaris (2002) introduces the theory of Flow based on the theoretical frame TAM, and performs an empirical research on 300 consumers from certain online purchasing website. The results show that the pleasure and the utility of online purchasing have a great effect on the purchasing intention of consumers (Koufaris, 2002). Form the sequence of influences online shopping, web site design is rank 14th on the influencing factors of online consumers' purchasing behaviours. And result shows that influence the online shopping is 0.012209.

On the other hand, shopping at an online store is like shopping through a paper catalogue because both involve mail delivery of the purchases and in both cases customers cannot touch or smell the items (Spiller and Lohse, 1997). This study provides empirical validation of consumers behaviors in the web based online shopping context .We adopt the theory of user consumer purchase behavior to explain the consumers respond to online shopping services. Consumers tend to engage in relational behaviors to achieve greater efficiency in their decision making, to reduce information processing, to achieve more cognitive consistency in their decision, and to reduce the perceived risks associated with future choices (Sheth and Parvatiyar, 1995). After a few successful transactions, a consumers starts feel safe with the services provider or supplier (Ravald and Gronroos, 1996). When consumers trust a company, they know that this company is able to fulfil their needs and wants and eventually, they become committed to the company.

The online shopping environment enables consumers to reduce their decision -making efforts by providing vast selection, information screening, reliability, and product comparison (Alba et al., 1997). Since online shoppers mainly interact with the web-based computer system and cannot physically touch or feel actual products, they make decisions mainly with information provided electronically by the online store. Thus, consumers may reduce the cost of information search and the effort in making purchasing decisions since the Internet provides screened and comparison information for alternatives. The discussion about the critical factors in consumer purchase behavior in an electronic commerce environment needs to be focused on the availability of information (Wolfinbarger and Gilly, 2001).The availability of information but also convenience and personalization for retaining customers. It depends on the degree to which information can be employed by consumers to predict their probable satisfaction with subsequent purchases. Consequently, the success of online stores will be determined by the ability to tailor their information to meet the consumers' needs. But, several factors determine the predictive value of the information with no one type of information to be uniformly valued by all consumers (Kolesar and Galbraith, 2000).

Finally, although the consumers may receive a tangible good at the end of the online transaction, the benefits to the consumers are not in purchased good, which could have been obtained through alternative channels (Kolesar and Galbraith, 2000). Instead, the unique benefits to the consumer are in the performance of the online shopping transaction itself such as saved time, increased convenience and reduced risk of dissatisfaction (Wolfinbarger and Gilly, 2001). Thus customer service and promotion are also critical in designing an online store (Jarvenpaa and Todd, 1997; Lohse and Spiller, 1998).

2.3 Journal Analyse

2.3.1 Personal characteristic-Trust

Worchel (1979) has classified trust into three categories based on the perspectives of personality theorists, sociologists and economists, as well as social psychologists. Trust is an expectation of the occurrence of an event or a relationship (Deutsch, 1960). The decision to trust is a personal decision dependent on the individual's expectation of the outcome (Zand, 1972). Trust is characterised in terms of the expectations and willingness of the trusting party in a transaction, the risks associated with acting on such expectations, and the contextual factors that either enhance or inhibit the development and maintenance of trust (Lee and Turban, 2001).

Next to satisfaction of customer, trust has been brought forward as a precondition for patronage behavior (Pavlou, 2003) and the development of long-term customer relationships (Doney and Cannon, 1997; Papadopoulou et al., 2001; Singh and Sirdeshmukh, 2000). The role of trust could be even more important in an e-commerce setting, since e-customers do not deal directly with the company, or its staff (Papadopoulou et al., 2001; Urban et al.2000).

Besides, the trust concept has been studied in a number of disciplines, and various definitions have been proposed (Lewicki et al., 1998). Trust is consistently related to the vulnerability of the trust or (Bigley and Pearce, 1998; Singh and Sirdeshmukh, 2000), because without vulnerability of the trust or upon the trustee, trust becomes irrelevant. Trust also has been found to be important for building and maintaining long-term relationships (e.g. Geyskens et al., 1996; Rousseau et al., 1998; SinghandSirdeshmukh, 2000).

Moreover, trust appears to be especially important for creating loyalty when the perceived level of risk is high (Anderson and Srinivasan, 2003). E-trust is expected to affect customers' willingness to purchase online (Reichheld and Schefter, 2000). According to Corritore et al. (2003), risk is sparsely studied in the online literature. The need for trust presupposes inherent risks in taking the action and, therefore the effects of different types of risk on e-trust need further investigation.

Trust is vital to online settings (Collier and Bienstock, 2006; Gefen and Straub, 2003) and trust has been identified as a key factor in online shopping (Gefen et al., 2003b; Gefen and Straub, 2003; Grabner-Kraeuter, 2002; Pavlou, 2003). More specifically trust is a key enabler in relations between geographically dispersed people in the virtual community (Gefen et al., 2003b; McKnight and Chervany, 2001; Swan and Nolan, 1985).

2.3.2 Personal Involvement

The concept of personal involvement was first proposed by Zaichkowsky (1985, 1994) as "individual perceptions of the relevance of an object based on inherent needs, values and interests (p.342). Koufaris (2002) used the term "product involvement" as a substitute for personal involvement and proposed the following as its generally accepted definition: "individual motivation regarding an object where that motivational state is activated by the relevance or importance of the object in question (p.211)". The same method was employed by Chaudhuri (2000) and Wang et al. (2006), both using the term "product involvement" to indicate the same concept. Chaudhuri (2000) identified a correlation between information search and product involvement. That is, consumers with high product involvement also have high levels of intention to collect related information online.

Personal values provide the motivation that ultimately determines an individual's online shopping behavior. These personal values do this by providing motivation to seek certain type's benefits by assessing certain types of attributes. The consumer's assessment of these attributes affects shopping behavior such as re-patronage. Besides that, Shim, Eastlick, Lotz, and Warrington (2001) found that individuals who frequently search for information online have high acceptance of online shopping. Similarly, Koufaris (2002) indicated that individuals with higher product involvement have more positive shopping experiences and greater interest in specific products.

Last but not least, Wang et al. (2006) identified consumer product involvement as one of the determinants of online financial service purchases. Thus, we hypothesized that: H1: High levels of product involvement positively affect user attitudes toward online shopping.

2.3.3 Website- website design

Web design elements are defined as the features, components, and information used in developing e-commerce websites, which may influence customers purchase behavior through the reinforcement of their positive beliefs.In the Internet market, retailer's websites have become a valuable channel for selling and interacting with customers, and an important medium for communicating with the general public as well as potential consumers (Hoque and Lohse 1999; Jarvenpaa and Todd 1996/97). Moreover, Gwo-Guang Lee and Hsiu-Fen Lin (2005) noted that although web site design had only a minor effect on online shopping, its importance should not be underestimated. Online stores should pay careful attention to this aspect. In particularly, web site design should be readable, and the user interface should be visually appealing and tidy, allowing customers to use the web site easily.

A company's website design and content reflect its business strategy as well as its operational policies, such as pricing and service. Hence, design of a company's website can have a critical impact on the firm's success in the Internet market. Since the ultimate goal of an e-commerce website is the customer's purchase action, insight into how a website's design impacts potential customers' purchase behavior could be of great value. Web design elements that provide facilitating resources, such as product customization or facilities for payment, may reduce the mental efforts and increase the customer's sense of control and power regarding the availability of resources, thus reinforcing the behavior intention (Taylor and Todd 1995; Triandis 1977).

The connection between web elements and beliefs provides us with a theoretical foundation in that web design elements could be grouped into five categories, as promotion, service, informational interpersonal influence, self-efficacy, and resource facilitation (Alba et al. 1997; Jarvenpaa and Todd 1996/97; Keeney 1999; Lohse and Spiller 1998).Web site design quality is crucial for online stores (Than and Grandon, 2002). Web site design describes the appeal that user interface design presents to customers (Kim and Lee, 2002). The influence of web site design on e-service performance has been studied extensively. For instance, Cho and Park (2001) conducted an empirical research of a sample of 435 internet users to examine the e-commerce user-consumer satisfaction index (ECUSI) for internet shopping. They found that the customer satisfaction is assessed using the quality of web site design.

A recent empirical study found that web site design factors are strong predictors of customer quality judgments, satisfaction, and loyalty for internet retailers (Wolfinbarger and Gilly, 2003).From the angle of website technology, Swami Nathan studies the factors that influence consumers' online purchasing based on characteristics of consumers, and results show that the competitive price and the quick cancel of orders are the key for consumers' online purchasing (Swami Nathan. E. Lepkowska - White & B.P Rao, 1999). The rapid explosion of e-commerce and the growth of online sales have changed consumers purchasing behavior (Bellman et al. 1999). In the Internet market, retailer's websites have become a valuable channel for selling and interacting with customers, and an important medium for communicating with the general public as well as potential consumers (Hoque and Lohse 1999; Jarvenpaa and Todd 1996/97). Based on the TAM model, Lin & Lu (2001) performs an empirical study on 139 online consumers, from the angle of website quality affecting consumers' online purchasing intention, and results show that the quality of website influences the effects of TAM model's main variables PEOU and PU on the purchasing attitudes and intentions (Lin, Chuan-chuan J & Lu H., 2000).

2.3.4 Website- website quality

E-service quality is commonly defined as how well a delivered service level matches customer expectations. In another study, Song &Zahedi (2001) tested the model using lab experiments. The experimental design was a full factorial combination of five web design categories (promotion, service, self-efficacy, resource facilitation and informational interpersonal influence). They created 32 different websites that contained different combinations of web design features in particular category of web design elements could be present or absent from a website. For example, website number 2 contained web design elements for promotion, service, informational interpersonal influence, and self-efficacy, but lacked the web design elements for resource facilitation. Most experienced and successful online vendors are beginning to realise that the key determinants of success or failure are not merely a web presence or low price but rather delivering a high quality electronic service (e-service) (Zeithaml et al., 2000).

The e-service quality represents the trust cue that conveys the trustworthiness of the site and the system to customers (Corritore et al., 2003). According to Bart et al. (2005), the dimensions of e-service quality can be considered as website-related determinants of trust. In response, a number of studies have developed scales for measuring online service quality in a variety of industry and product settings (Francis, 2009; Loiacono et al., 2007; Parasuraman et al., 2005; Wolfinbarger and Gilly, 2003; Yoo and Donthu, 2001; Zeithaml et al., 2000).Research over the past two decades has indicated that e-service quality will influences consumption decisions, but only recently these findings have been applied in the online setting (Yang and Jun, 2002; Wolfinbarger and Gilly, 2003). The concept of e-service quality was first introduced by Parasuraman, Zeithaml and Berry (1985, 1988) whereby researchers measured e-service quality (SERVQUAL) in five (5) phases: i) tangibility, ii) reliability, iii) responsiveness, iv) assurance and v) empathy. Three major quality constructs that are critical to web site success in e-commerce: information quality, system quality, and service quality (Liu and Arnett, 2000). Lai, Chen and Lin (2007) suggested that when customers perceive better quality service website, such as special treatment benefits, they will have greater online satisfaction. Hence, the satisfaction of the consumer on the particular website will influence the customers' purchase intention.

2.3.5 Website-website security

The internet based electronic commerce environment enables consumers to search for information and purchase products or services through direct transaction with the online store. That is, consumers purchase are mainly based on the cyberspace appearance such as pictures, image, quality information, and video clip of the product, not on the actual experience (Lohse and Spiller,1998;Kolesar and Galbraith,2000).Shooping at an online store is like shooping through a paper catalog because both involve mail delivery of the purchases and in both cases customers cannot touch or smell the items (Spiller and Lohse,1997).This study provides empirical validation of consumers behaviors in the web based online shopping context .We adopt the theory of user consumer purchase behavior to explain the consumers respond to online shopping services. Consumers tend to engage in relational behaviors to achieve greater efficiency in their decision making, to reduce information processing, to achieve more cognitive consistency in their decision, and to reduce the perceived risks associated with future choices (Sheth and Parvatiyar, 1995).After a few successful transactions, a consumers starts to feel safe with the services provider or supplier (Ravald and Gronroos, 1996).

When consumers trust a company, they know that this company is able to fulfill their needs and wants and eventually, they become committed to the company. The online shopping environment enables consumers to reduce their decision -making efforts by providing vast selection, information screening, reliability, and product comparison (Alba et al.,1997).Since the Internet provides screened and comparison information for alternatives, consumers may reduce the cost of information search and the effort in making purchasing decisions .However, since online shoppers mainly interact with the Web-based computer system and cannot physically touch or feel actual products , they make decisions mainly with information provided electronically by the online store. Thus, the discussion about the critical factors in consumer purchase behavior in an electronic commerce environment needs to be focused on the availability of information (Wolfinbarger and Gilly,2001).The availability of information but also convenience and personalization for retaining customers. It depends on the degree to which information can be employed by consumers to predict their probable satisfaction with subsequent purchases. Consequently, the success of online stores will be determined by the ability to tailor their information to meet the consumers' needs. But, several factors determine the predictive value of the information with no one type of information to be uniformly valued by all consumers (Kolesar and Galbraith, 2000). The basic requirement for inducing a consumer to become a customer of an online store and increasing his/her switching cost is to reduce the cost of information to consumers (Bakos,1991,1997).Although the consumers may receive a tangible good at the end of the of the online transaction , the benefits to the consumers are not in purchased good, which could have been obtained through alternative channels (Kolesar and Galbraith,200).Instead , the unique benefits to the consumer are in the performance of the online shopping transaction itself such as saved time, increased convenience and reduced risk of dissatisfaction (Wolfinbarger and Gilly,2001) .Thus customer service and promotion are also critical in designing an online store (Jarvenpaa and Todd,1997;Lohse and Spiller,1998)

2.4 The relationship between independent variable and dependent variable.

2.4.1 Relationship between trust and online shopping

Trust is vital for online shopping because trust in a shopping website can affect attitude toward, and willingness to engage in, online shopping (Jarvenpaa et al., 2000; Lee and Turban, 2001). Besides, in an e-commerce setting, since e-customers do not dealdirectly with the company, or its staff (Papadopoulou et al., 2001; Urban et al., 2000). Various relationships have been proposed between trust, satisfaction and loyalty in an online context (Reichheld and Schefter, 2000). Moreover, trust is proposed as another important antecedent of loyalty (Reichheld et al., 2000). E-trust will therefore be defined as the degree of confidence customers have in online exchanges, or in the online exchange channel. Dispositional trust plays a particularly important role in the interaction between unfamiliar actors (Bigley and Pearce, 1998) and is therefore essential for the initial use of electronic retailers (Grabner-Kra¨uter and Kalusha, 2003), as well as for purchases of goods and services that score high on credence and experience qualities.

On the other hand, lack of trust is frequently cited as a reason for not purchasing from online merchants (Lee and Turban, 2001). More recently trust has been applied in marketing contexts (Moorman et al., 1992, 1993) to explain exchange relationships between parties and how they affect decision making (Doney and Cannon, 1997). Trusting intention means that a potential online shopper is willing to expose themselves to the possibility of loss and transact with the shopping website, that is, willing to purchase from it (McKnight and Chervany, 2001).

2.4.2 Relationship between personal involvement and online shopping

Involvement is the concept that has acquired importance, due to the relationship between it and other aspects such as online shopping decision making. For this reasons many authors have investigated this subject with the aim of reaching a consensus about its meaning and how to measure it (See Krugman, 1966; Mitchell, 1979; Petty and Cacioppo, 1981; Bloch, 1982; Zaichkowsky, 1985, 1994; Laurent and Kapferer, 1985; Andrew et al., 1990; Day et al., 1995). This is certain agreement as to the definition of the concept, thus we can define involvement with the products as a personal's perceived relevance of the objects based on inherent interests, needs and values (Mitchell, 1979; Zaichkowsky, 1985; Solomon, 1997). Besides that, Shim, Eastlick, Lotz, and Warrington (2001) found that individuals who frequently search for information online have high acceptance of online shopping. Similarly, Koufaris (2002) indicated that individuals with higher product involvement have more positive shopping experiences and greater interest in specific products.

2.4.3 Relationship between web site design and online shopping

Website is the main connection between online merchants and its online shoppers. In the Internet market, retailers' websites have become a valuable channel for selling and interacting with customers, and an important medium for communicating with the general public as well as potential consumers (Hoque and Lohse 1999; Jarvenpaa and Todd 1996/97). Effective website design plays an important role in maintaining and attracting potential online shoppers' intention and interest. Bellman et al. (1999) also mention that the rapid explosion of e-commerce and the growth of online sale have influencing consumers' purchasing behavior. Furthermore, the influence of web site design on online shopping has been studied extensively. For instance, Cho and Park (2001) conducted an empirical research of a sample of 435 internet users to examine the e-commerce user-consumer satisfaction index (ECUSI) for internet shopping. A recent empirical study found that web site design factors are strong predictors of customer quality judgments, satisfaction, and loyalty for internet retailers (Wolfinbarger and Gilly, 2003). Hence, the analytical results showed that online store web site design positively affect overall service quality (β= 0:21; p < 0:01) and customer satisfaction (β= 0:22; p < 0:01).

2.4.4 Relationship between Website Quality and Online Shopping

Customer satisfaction is particularly important to the success of online stores as it is posited as a major driver of post-purchase phenomena, such as repurchase intentions. More recently, web site quality has become essential for improving customer satisfaction and creating customer loyalty (Parasuraman et al., 2005). In traditional service research and in emerging research on electronic service (e-service) (Collier and Bienstock, 2006), several antecedents of customer satisfaction have been proposed.

Among these, web site quality figures prominently. Several researchers have developed conceptual models for measuring B2C website success (Liu and Arnett, 2000). They identified three major quality constructs that are critical to website success in e-commerce: information quality, system quality, and service quality. Those models are consistent with the updated information systems (IS) success model (DeLone and McLean, 2003), a research framework theorizing that information quality, system quality, and service quality are fundamental determinants of an individual's satisfaction, which in turn is the determinant of repurchase intention.

2.4.5 Relationship between Website Security and Online Shopping Decision Making

Electronic commerce environment enables consumers to search for information and purchase products or services through direct interaction with the online store. That is, consumer-purchases are mainly based on the cyberspace appearance such as pictures, images, quality information, and video clips of the product, not on the actual experience (Lohse and spiller,1998;Kolesar and Galbraith,2000).Shopping at an online store is like shopping through a paper catalogue because both involve mail delivery of the purchases and in both cases customers cannot touch or smell the items (Spiller and Lohse,1997).Another factor affecting information satisfaction in the web environment is security .Consumers are concerned about online payment security , reliability, and privacy policy of the online store (Gefen ,2000).Basically, security concerns in electronic commerce can be divide into concerns about users. Basically, security concerns in electronic commerce can be dividing into concerns about data and transaction security (Rowley, 1996; Ratnasingham, 1998).

Chapter3 Research Methodology

3.1 Development of Research Framework and Hypotheses

In chapter 3, we describe the research method that is used in this research. It is important to support the research which is being done. Besides, we will also explain in details the development of research framework, hypothesis, research design, research instrument, sampling plan, methods of data collection and data analysis. The main objective is to provide a clear picture to readers about the overall study.

3.1.1 Research Framework

TrustThe following structure is a theoretical framework that can support the theory of research work. The figure below illustrates the relationship between a dependent variable, online shopping decision making and independent variables namely gender, personal involvement, trust and website.

Personal Involvement

Online shopping decision making

Website Design

Website Security

Website Quality

3.1.2Hypotheses Development

The hypothesis statements are described in this part. Hypotheses can be defined as a specific, testable prediction for the relationship between variables. The hypotheses developed for testing the relationship between independent and dependent variables are as follows:

H1: There is a relationship between personal involvement and online shopping decision making.

H2: There is a relationship between trust and online shopping decision making.

H3: There is a relationship between website design and online shopping decision making.

H4: There is a relationship between website quality and online shopping decision making.

H5: There is a relationship between website security and online shopping decision making.

3.2 Research Design

Research design is the overall plan for connecting the conceptual research problems to the related empirical research. In other words, the research design articulates what data is required, what methods are going to be used to collect and analyse this data, and how all of this is going to answer the research question. According to Rohrer (2008), "qualitative methods are much better suited for answering questions about why or how to fix a problem, whereas quantitative methods do a much better job answering how many and how much type of questions." Our research was designed to use quantitative research as it generates numerical data for statistical review. Quantitative approach is one in which the investigator primarily uses post positivist claims for developing knowledge, employ strategies of inquiry such as experiments and surveys, and collects data on predetermined instruments that yield statistical data (Creswell, 2003). Quantitative research designs are either descriptive or experimental. In our research, we will mainly focus on descriptive study as it establishes only associations between variables.

We used the questionnaire survey to collect the quantitative data. In order to obtain valid results it was necessary to collect data from a sufficiently large sample and this could only be done efficiently by means of a questionnaire survey. A questionnaire survey can be completed anonymously which protects the privacy of respondents and may encourage more to respond. The results of the questionnaires can usually be quickly and easily quantified by either a researcher or through the use of a software package.

3.3 Research Instrument and Sampling Method

This research is using survey questionnaires as research instruments. Our questionnaire was divided into three parts. Part A was proposed to collect the respondents' demographic information such as gender, age, ethnicity, nationality, major course and monthly allowances of the respondent. A total of six questions were included in this part. Part B was intended to identify the dependent variable about the customer's online shopping decision making. In this section, some questions were asked about student's opinion towards online shopping such as is online shopping saving their time and more easier compared to physical shopping. A total of four questions were included in this part. Part C included twenty-five questions, which were separated into five categories in terms of the independent variable. In this part, students have to answer whether the five main factors influence them when they are shopping online. The factors included personal involvement when their shopping online, trust, website design, website security and website quality. The respondents were required to provide their rating on their perception using a five-point Likert Scale measurement, which the scales are 1 = strongly disagree, 2 = disagree, 3 = neutral, 4 = agree and 5 = strongly agree. The targeted respondents will be given the survey questionnaires that related to our research topic. Reliability analysis is used to test how good the items in sample set are linked to each other. This is important to use in measuring the reliability and the strength of data collected from the questionnaires and will bring the impact to the findings part. Sampling is a process to select an individual from a general population to examine the characteristic of whole populations. We used the simple random sampling method to choose our target population. We targeted 100 students from Multimedia University in Malacca Campus and most of the participants are students from Faculty of Business and Law. They are our target population is because we are conducting the research on identifying the factors affecting the online shopping decision making among the Multimedia University students. The target respondents will return back the questionnaires after they have completed it.

3.4 Data collection method

The methods that used in this research to collect data and information were discussed. The quantitative method helps us to gather the key data and information from our respondents. A questionnaire survey was used to collect the necessary data and information. It serves as the primary data to answer the questionnaire pertaining to online shopping decision making. The method used was personally administrated questionnaires for the purpose of gathering information from respondents, and designed to extract specific information. Some factors that influence online shopping decision making were found after reading some previous studies and journals. These factors had helped to guide us in designing for the questionnaire which included factors such as trust, personal involvement, website design, website quality, and website security in Part C.

Questionnaires have advantages over other types of surveys in that they are inexpensive to administer, easy to compare and analyses and it allows the researchers to collect lots of data from all the respondents in a very short period of time. Besides that, questionnaire survey can collect the appropriate data from the respondents and make data comparable and amenable to analysis. The other advantage of the questionnaire is that it can minimize bias in formulating and asking question.

3.5 Data Analysis Method

3.5.1 What is the software to be used?

In order to accomplish the data analysis, software is important tools in particular matters. SPSS also called Statistical Package for the Social Sciences can be used to make predict on the outcome of the analysis. This software can predict with confidence what will occur for the next so that predictor can make smarter decisions in order to replace it with the correct method. This SPSS is also helpful for managing data and calculating a wide variety of statistics. For instance, students allow taking classes that use SPSS Statistics or public who is totally new to the SPSS software.

3.5.2 Frequency Analysis

Frequency analysis is used for the study of the frequency of letter or groups of letters in a cipher text. The method is used as an aid to breaking classical ciphers. Frequency analysis is based on the fact that, in any given stretch of written language, certain letters and combinations of letter occur with varying frequencies.

3.5.3 Reliability analysis

The reliability analysis is one of the instruments concerns the extent to which the instrument yields the same results on repeated trials. Although unreliability is always present to a certain extent, there will generally be a good deal of consistency in the result of a quality instruments gathered at different times. The tendency toward consistency and dependability found in repeated measurements is referred to as reliability (Carmines & Zeller. 1979). It is very important for accuracy for any research we related. For instance, online purchasing can measure many times numerical assessments to come out the mental attributes of human being accepted specific types of purchase.

3.5.4 Quantitative analysis

Quantitative analysis is the process of presenting and interpreting numerical data. It contains descriptive statistics and inferential statistics. Descriptive statistics are a set of descriptive coefficients that summarizes a given data set. It helps researchers to measure central tendency (mode, median, mean) and a measure of variability about the average (range and standard deviation). Inferential statistics are the outcomes of statistical tests. It's helping researches provide valuable information through deductions to be made from the data collected, to test hypotheses set and finding from sample to population.

3.5.5 Mean analysis

Mean analysis is an average of the number. It means the sum all the number divided by the count of the number. The purpose is to measure the arithmetic average of a range of values or quantities in the research, and then computed by dividing the total of all values by the number of values.

3.5.6 Independent sample t-test

Independent sample t-test is the hypothesis testing procedure that uses separate samples for each treatment condition. It used for analysis and compare the values of the means from two independent variable as well as tests whether it is likely that the independent variable are from populations having different mean values such as compared web site design and website quality which one influence more on online shopper's decision making.

3.5.7 Pearson correlation coefficient, r

Correlation is a technique for showing the relationship between two quantitative and continuous variables. Pearson's correlation coefficient (r) is a measure of the strength of the association between the two independent variables. Its values for continuous (interval level) data ranges from -1 to +1. The nearer the scatter of points is to straight line, the higher the strength of association between the independent variables. If two independent variables are not linear, the correlation coefficient should not be calculated.

3.5.8 Multiple regression analysis

Multiple regression analysis is a powerful technique used for predicting the unknown value of a variable from the known value of two or more variables also called the predictors. (Amit & Choudhury, 2009).Multiple regression analysis is helping to predict outcome the value of A given by B. While the dependent variable the online purchasing. Multiple Linear Regression analysis is conducted to check the significant difference among the independent variables such as security, gender, and website design and e-services quality.

Chapter4 Research Findings and Discussion

4.0 Introduction

Various types of statistics technique are common used in the data analysis. Frequency distribution analysis is one of the techniques used to determine demographic profile of the respondents. It used to determine quartiles, percentiles. Descriptive statistics will be used to measures of central tendency (means, median, and mode) and measure of dispersion (standard deviation and variance of the variables).

Besides that, factors analysis will used to reduce number of variables to a meaningful, interpretable, and manageable set of factors. After that, Cronbach alpha values are employed for variables' reliability .Final, multiple regression analysis are conducted.

4.1 Descriptive statistics

Table 4.1 Gender

Frequency

Percent

Valid Percent

Cumulative Percent

Valid

Male

28

28.0

28.0

28.0

Female

72

72.0

72.0

100.0

Total

100

100.0

100.0

There are total 100 respondents of Multimedia University student's conducts to the survey. 28 of them are Male and the other 72 respondents are female.

Table 4.2 Age

Frequency

Percent

Valid Percent

Cumulative Percent

Valid

18-20

49

49.0

49.0

49.0

21-23

49

49.0

49.0

98.0

Above 23

2

2.0

2.0

100.0

Total

100

100.0

100.0

The majority of the students are 18-20 and 21-23 respective years old. The total of categories for 18-20 and 21-23 years old are 98 students. Besides that, there are only 2 students is above 23 years old.

Table 4.3 Ethnicity

Frequency

Percent

Valid Percent

Cumulative Percent

Valid

Malay

9

9.0

9.0

9.0

Chinese

79

79.0

79.0

88.0

India

5

5.0

5.0

93.0

Other

7

7.0

7.0

100.0

Total

100

100.0

100.0

The students are come from variety of races which are Malay, Chinese, India and other race. In this study, 79 students are mainly formed by Chinese students. For race Malays are 9 students to conducts the study. The other 5 students are come from India students. The rest of the students may come from other races that seldom in the Malaysia. Only 7 students are conduct in this study.

Table 4.4 Nationality

Frequency

Percent

Valid Percent

Cumulative Percent

Valid

Malaysian

93

93.0

93.0

93.0

Non-Malaysian

7

7.0

7.0

100.0

Total

100

100.0

100.0

Based on the result above, there are total 93 of students are Malaysian while the other 7 non-Malaysian who come from other countries to conduct this study in Multimedia University.

Table4.5 Course

Frequency

Percent

Valid Percent

Cumulative Percent

Valid

FBL

70

70.0

70.0

70.0

FET

20

20.0

20.0

90.0

FIST

2

2.0

2.0

92.0

CDP

8

8.0

8.0

100.0

Total

100

100.0

100.0

After the researcher had distributed the questionnaire at Multimedia University and collect the data, 70 students who are hold Bachelor's degree of FBL's students. Besides that, there are 20 of students who are course in FET Faculty. 8 of them are course of CDP Faculty in Multimedia University. The rest of the students may from FIST faculty to conducts in the study.

Table 4.6 Allowance

Frequency

Percent

Valid Percent

Cumulative Percent

Valid

less than RM300

48

48.0

48.0

48.0

RM301-500

28

28.0

28.0

76.0

RM501-800

12

12.0

12.0

88.0

RM801-1000

6

6.0

6.0

94.0

more than RM1000

6

6.0

6.0

100.0

Total

100

100.0

100.0

The table above shows the allowance of student. The source of allowance may come from PTPTN, their parent's pocket money or doing part time job. There are 48 out of the total 100 student' reply that they normally spend less than RM 300 for spending their daily expenses. 28 of them are hold RM 301-500 for their allowance. Besides that, 12 students had spent RM 501-800 per month's allowance. 6 of them had spent their allowance at RM 801-RM1000 while 6 of them are spend their allowance more than RM1000.

4.2 Reliability Analysis

Variable

N of Item

Item Deleted

Alpha

Online shopping decision making

4

-

0.671

Personal Involvement

5

-

0.814

Website Design

5

-

0.753

Website Quality

5

-

0.790

Website Security

5

-

0.850

From the table above, it shows that all the independent variables are reliable because alpha is more than 0.7. Only dependent variable which is online shopping decision making is below alpha 0.7. All four independent variable are internally consistent. The independent variable of website security has the highest value in alpha which is 0.850. However, website design has alpha 0.753 lowest alphas between all independent variable.

4.3 Mean Analysis

N

Mean

Standard Deviation

Online Shopping Decision Making

100

3.5375

.59605

Personal Involvement

100

2.9600

.69573

Trust

100

3.1280

.63534

Website Design

100

3.5560

.62770

Website Quality

100

3.2160

.62324

Website Security

100

2.6280

.74184

Based on the table showed above, the mean of the dependent variable (online shopping decision making) was 3.5375 and the standard deviation was 0.59605. Furthermore, the mean of the personal involvement was 2.96 and has the standard deviation of 0.69573. The accumulated average mean for trust dimension was 3.128 and the standard deviation was 0.63534. By seeing the mean of website design, it has the highest mean which are 3.556 while the standard deviation of website design was 0.6277. Compare to other factor, it is concluded that most of the respondents are agree that website design is most important factor in online shopping decision making. The average mean value of website quality was 3.216 and the standard deviation was 0.62324. Last but not least, the mean of website security was 2.628 and the standard deviation was 0.74184. Since the mean value of website security was the lowest, this means that the respondents agree website security is not main factor in influence the respondents' online shopping decision making.

4.4 Multiple Regression Analysis

Multiple regression analysis (enter method) is used to identify the predictors of the dependent variable and to see how well the model fits.

The variables tested are online shopping decision making, personal involvement, trust, website design, and website quality and website security. The R2 value obtained in the analysis is 0.46. This means that 46% in online shopping decision making is explained by the independent variables.

The ANOVA table shows a significant value 0.000.

Model Summary

Model

R

R Square

Adjusted R Square

Std. Error of the Estimate

1

.678a

.460

.431

.44960

a. Predictors: (Constant), Wes, Wed, Per, Weq, Tru

ANOVAa

Model

Sum of Squares

df

Mean Square

F

Sig.

1

Regression

16.171

5

3.234

16.000

.000b

Residual

19.001

94

.202

Total

35.172

99

a. Dependent Variable: Osdm

b. Predictors: (Constant), Wes, Wed, Per, Weq, Tru

Coefficientsa

Model

Unstandardized Coefficients

Standardized Coefficients

t

Sig.

B

Std. Error

Beta

1

(Constant)

1.135

.290

3.914

.000

Per

.227

.093

.264

2.430

.017

Tru

.212

.112

.226

1.898

.061

Wed

.147

.091

.154

1.605

.112

Weq

.169

.100

.176

1.685

.095

Wes

.002

.082

.003

.026

.979

a. Dependent Variable: Osdm

H1: There is a significant relationship between personal involvement and online shopping decision making.

The beta value of personal involvement is 0.264. (t = 2.430, p = 0.017). Since the p-value is lower than 0.05, the hypothesis is therefore supported. This means that there is a relationship between personal involvement and online shopping decision making. This result is in line with the study by Chaudhuri (2000) who has identified a correlation between information search and product involvement. That is, consumers with high product involvement also have high levels of intention to collect related information online.

H2: There is a significant relationship between trust and online shopping decision making.

The beta value of trust is 0.226. (t = 1.898, p = 0.061). Since the p-value is more than 0.05, therefore the hypothesis is not supported. This result contradicts with previous findings such as by Collier and Bienstock, 2006; Gefen and Straub (2003), which has been found that, trust is vital to online settings and trust has been identified as a key factor in online shopping.

H3: There is a significant relationship between website design and online shopping decision making.

The beta value of website design is 0.154. (t = 1.605, p = 0.112). Since the p-value is more than 0.05, therefore the hypothesis is not supported. This result contradicts with previous findings such as by (Koufaris, 2002). The findings show that the pleasure and the utility of online purchasing have a great effect on the purchasing intention of consumers and result show that influence the online shopping is 0.012209.

H4: There is a significant relationship between website quality and online shopping decision making.

The beta value of website quality is 0.176. (t = 1.685, p = 0.095). Since the p-value is more than 0.05, therefore the hypothesis is not supported. This result contradicts with previous findings such as by DeLone and McLean (2003). A research framework theorizing that information quality, system quality, and service quality are fundamental determinants of an individual's satisfaction, which in turn is the determinant of repurchase intention.

H5: There is a significant relationship between website security and online shopping decision making.

The beta value of website security is 0.003. (t = 0.026, p = 0.979). Since the p-value is more than 0.05, therefore the hypothesis is not supported. This result contradicts with previous findings such as by Gefen (2000), which consumers are concerned about online payment security, reliability, and privacy policy of the online store.

Chapter 5 Discussion and Conclusions

5.1 Introduction

In this chapter, we are going to clarifies the discussion of the each of the hypotheses testing which are discuss in the data analysis part of this research. Moreover, the discussion of the hypotheses testing will be compared with the previous studies to increase the validity of the information. Besides that, this chapter also includes the implication of study research which toward other studies in the future based on the results which was found. On the other hand, this chapter also comprises of various suggestions and recommendations for future research regarding the study of references group influence of online shopping affect buying decision.

5.2 Research Findings

According to our findings in chapter 4, based on the mean analysis, we can conclude that most of the respondents agree website design is the main in online shopping decision making. Besides, the hypotheses testing shows that personal involvement, trust, website design, website quality and website security have a strong relationship with online shopping decision making.

5.3 Knowledge Implications

The proposed research study was to examine the online shopping making decision was according to the 6 variables which are trust, personal involvement, website quality, website security, website design and gender. In this part, a number of contributions of this study have been acknowledged towards future researches. The findings of this study are very important because it would enhance and inspire the knowledge in the social studies area. In addition, the results that we obtained from this thesis would help future researcher to get additional information which covered in this research. Besides that, researches who are doing their study in related field would notice that this report would be constructive and it can also be their reference. Finally, this research would be useful as there are few studies available in the related area.

5.4 Managerial Implications

This study had tested on some new variables and other variables that rarely tested in the previous study. This study had consisted six variables about online shopping decision making. The variables that had tested in this study are personal involvement during consumer online shopping decision making, trust towards the online website, gender towards online shopping decision making, website design, and website quality and website security. Throughout the research, our mainly focus is on online shopping decision making among consumer and also aim to provide the consumer a better understanding while they purchasing online. This research had consisted of six perspectives which consumer can take it as references while they want to online shopping.

Furthermore, most of the time people might not think and consider so many while they purchasing things online. Thus, this research could share and provide more useful information for those people who are facing decision making problem in online shopping. This research is very important to the marketer and is essential for future academic study. All of the variables and attr