TOPIC: EFFECTS OF CUSTOMERS TRUST AND PRIVACY CONCERNS TOWARDS ONLINE BUSINESSES.

1.0 INTRODUCTIONThe internet conceivably is the most important technology as it allows people to carry out their daily activities such as communication, businesses and personal life. Indeed, people have found advantages in using the internet and these advantages may include having access to a wide range of information, convenience and more choice for goods and services. Probably, companies can also be grateful for the innovation of the internet as it provides them with the means of extending their services outside their physical environment. However, the many advantages that the internet technology brings with transacting online may be countered with concerns such as privacy concerns. Due to the fact that there is no presence of a physical sales personnel during online transactions, people are usually faced with the unwillingness to transact online.Customers acceptance of online transactions relies not just on the benefits online transactions bring but also on the trust they have in online transactions. The inability of customers to trust online transactions has been argued to be one of the major reasons why customers do not engage in any form of online transaction (Hoffman et al., 1999). The aspect of trust that will be employed in this paper is online trust, as online trust differs from offline trust. Online trust can be defined as customers trust directed towards businesses or organizations that conduct transactions online (Wang and Emurian, 2005). Online trust is vital for every online transaction and building this trust is a difficult task. For online businesses to continue to grow, they need to be trustworthy. Online businesses also need to understand their customers so as to build a long-term relationship with them. An online business in this paper is defined as a business or an organization that uses the internet as a medium to carry out online transactions. Many online businesses collect information from customers through order and/or registration forms. They also collect information from customers through the use of cookies which enable them to track the online activities of their customers in order to acquire information about the preferences of their customers. This information acquired by online businesses is always beneficial to them as it allows them to sell their goods and services according to the preferences of their customers. Moreover, online businesses can increase their revenue by selling advertising space on their websites to advertisers because they believe that personal information or preferences of customers can be used by advertisers to bring more customers (Mangalindan, 2003). Although customers find it interesting when online businesses provide them with their preferences (Liu et al., 2005), concerns about their privacy has become a critical issue and this stands as an obstacle to the development of electronic commerce (Gefen, 2000; Scalet, 2001; Wu et al., 2012). For instance, a study conducted by Hoffman et al., (1999) reported that almost 95% of the people they surveyed refused to submit personal information to online businesses when they asked for it. It can therefore be ascertained that many customers may not actually trust an online business because of their concerns over privacy.1.1 Research questionDoes the degree of trust and privacy concerns customers have with online businesses generate an effect on their behavioural intentions for online transactions? 1.2 Research objectivesThe objectives of this research are as follows: To understand what influences a customer to trust an online business. To understand the effects of customers trust and privacy concerns towards online businesses.1.3 Research outlineThis paper began with a brief overview of customers trust and privacy concerns towards online businesses. The next chapter (chapter two) will review existing literatures on customers trust and privacy concerns towards online businesses. Chapter three will focus on the adopted methodology used in the course of this research. Chapter four will report the findings obtained from the analysis of data. Chapter five will discuss the findings, the limitations of the research and the implications of the research to both academic and business practitioners. The last chapter (Chapter six) will conclude the research and recommendations will be suggested in this chapter. LITERATURE REVIEW2.0 OverviewThis chapter reviews relevant literatures to gain an insight on customers trust and privacy concerns towards online businesses.2.1 Definition of trustAccording to Mayer et al. (1995) trust is the willingness of a party to be vulnerable to the actions of another party based on the expectation that the other will perform a particular action important to the trustor, irrespective of the ability to monitor or control that other party (p. 712). This definition covers two important areas of trust which includes the willingness of individuals to be vulnerable and the presence of confident expectations. Moreover, Barber (1983) argues that the notion of trust is perceived as the expectation that exchange partners (partners involved in a transaction process) will carry out the responsibilities required of them. Trust can also be conceptualized as a belief that embodies depending on a person or group under uncertain environmental and risky conditions.Trust, according to the Oxford English Dictionary (1971) is defined as the confidence in or reliance on some quality or attribute of a person or thing, or the truth of a statement (p. 3423). In as much as humans interact with one another, there must be some form of trust. Trust has been studied from different perspectives by various researchers. Whitener et al. (1998), for example, defined trust as a concept that involves the conviction or expectation about the anticipated actions of an exchange partner. From this definition, one can say that a trustor (an individual placing his or her trust in an online business) must be ready to accept the risk that what they are expecting from an online business might not be fulfilled. Similarly, Yoon (2002) defined trust as an element that is required for building relationships between a trustor and trustee. Trustee is defined as a person or a party to whom legal title to property is entrusted to. In the build-up of exchange relationships, trust normally plays a crucial role. Bradach and Eccles (1989) argued that trust is a type of expectation that an online business may not act accordingly to the rules or policies stipulated on its website. Moreover, trust guides exchanges between an online business and its customers in anticipation of establishing a long-term relationship. Trust is regarded as an antecedent for transactions or exchanges (Pruitt, 1981). Furthermore, saying that trust is needed for transactions or exchanges would mean that trust results from collaboration and coordination between exchange partners. In the marketing literature, trust is been regarded as a central link between buyer-seller relationship and customer loyalty and retention. Trust is important in starting relationships with customers. For example, Frazier et al. (1988) argued that trust is strengthened by means of keeping to ones promises, keeping to ones personal integrity and not betraying or cheating the other party even if the opportunity to do so presents itself. However, these variables can only be attained after satisfactory transactions have been carried out. Trust changes with time. If a customer already trusts an online business then after sometime finds out reasons to doubt this online business, there is the possibility that the customer will no longer trust the online business. The growth of an online business can be influenced by their trustworthiness towards their customers. 2.2 The significance of trustEngaging in interaction with people that cannot be fully depended on joined with an inner desire to understand how these people act, presents individuals with an overpowering difficulty or complexity. The impossibility to have power over how people act or the impossibility of trying to understand their incentives allows this complexity to look more difficult that it can somehow reduce individuals intentions to carry out various tasks. However, since people do need to interact constantly, they therefore use various means to reduce these complexities. These complexity reduction methods are important because without them, people will probably not interact with others more than once. Trust has been argued to be one of the most effective means of reducing these complexities (Luhmann, 1979).As stated earlier, trust is defined as a concept that shows conviction or expectation about the anticipated actions of an exchange partner in (Whitener et al. 1998). Trust is also the confidence an individual has in his or her favourable anticipations of what another individual or individuals will do based in most situations, on prior interactions (Gefen, 2000). The previous behaviour of a party (a person or an organization) cannot guarantee that the party would act as one would expect. However, if the party behaved as expected, the party will be seen as trustworthy, thus increasing the belief that that party will behave accordingly in future interactions. The inability to trust others will make a party consider possible behaviours of other parties before deciding on what actions to take. These complexities will be too much that people will become reluctant to do anything. Trust can be conceptualized as an effective means of reducing complexities. However, it is not the only method, as rules and regulations are also methods used in reducing complexities (Gefen, 2000). Nonetheless, with the availability of rules, trust is still necessary because there is no assurance that other people will abide by these rules and regulations (Fukuyama, 1995). Trust makes it feasible for a person to create an understanding of their interactions with others, however, it does not actually allow one to predict or even control the behavioural intentions of others.The significance that trust brings is however dependent on the complexity and the type of interaction between people. The more a person depends on other people, the more the need to trust (Rousseau et al. 1998; Deutsch, 1958). Research on online business has used a more definite approach, defining trust as the expectation that parties involved in online transactions will behave amicably (Kumar, 1996) and will keep to their promises (Rotter, 1971; Schurr, 1985) under conditions of acceptance and exposure to vulnerability (Rousseau et al. 1998). This further means that parties expose themselves to the vulnerability based on the belief that other parties will not betray or cheat them even if they have the ability to do so.Trust is vital to business relationships. With trust, the need for negotiating for a long period of time can be reduced. Trust reduces resolution of details (Gulati, 1995; Fukuyama, 1995) and it also reduces the need for compulsory regulation and complete legislation (Fukuyama, 1995). Trust builds and encourages long-term relationship. Fukuyama (1995) argues that trust is important as it reduces risk perception, privacy and security concerns. In addition, In any agreement that involves the use of contracts, trust can be very vital in such situations due to the fact that people can go ahead to make agreements with the assurance that there will be no form of opportunistic behaviour. On the contrary, if there is no trust in a contractual agreement, people would have to watch out for any opportunistic behaviour such as cheating that can be carried out on them.Trust is important in any business relationship as it can go a long way to determine the quality of the relationship. Consequently, trust in a business context is the salient factor in determining the effectiveness of many relations (Zand 1972: 229) and it also a determinant of the wide-ranging behaviours of individuals (Konovsky and Pugh, 1994; Schurr, 1985). Lack of trust has been argued to be the cause of having important information twisted in order to suit some people and it creates situations. Lack of trust also leads to the unwillingness to take risks (Fukuyama, 1995; Luhmann, 1979). The willingness to engage in activities that involves ones exposure to risks without being able to control other peoples behaviour is an effect of trust and this makes trust very important to the development of electronic commerce.2.3 Online trustElectronic commerce can be characterized as transaction carried out on the internet which is usually conducted between two or more entities through various types of online-linking media such as portals or websites. According to a study conducted by Cheskin Research (1999) as cited by Yoon (2002), online trust is built or formed from the following factors: Presentation: this entails the design characteristics of the website of an online business. Technology: this entails attributes showing technical skills and advantage. Search: the ability to provide customers with the convenience of looking for what they want. Brand: the brand of an online business allows customers predict the reputation and the credibility of online businesses. Security and privacy assurance: the attribute of an online business showing adequate security measures and privacy protection measures.

Trust strengthens or weakens the relationship between a person and an online business. The factors presented above reflect on the honesty and integrity of an online business. Individuals visiting the website of an online business for the first time may be worried over the privacy and security of their personal details that would be submitted during the online transaction. Also, they may be worried when search results fail to show what they (first-time customers) would like to purchase. This results to having reasons to doubt the trustworthiness of that online business. However, if these individuals see features such as the presence of a privacy policy assuring them of the privacy of their personal information, their trust towards that online business begins to grow. After having series of transactions with an online business that has proven to be trustworthy, these individuals then place their trust in that online business. It is then left for the online business to maintain the relationship. Online businesses can maintain relationships by updating their security and privacy measures (Aiken and Bousch, 2006; Lauer and Deng, 2007). Also, online businesses can maintain trust relationships by updating their information - that is being current (Kim et al. 2005). At this point, one may begin to wonder on what makes online trust different from offline trust. The absence of sales personnel and the fact that the buyer will not be able to physically view the product that he or she wants to purchase are the main reasons why online trust is different from offline trust. It has been argued that the non-availability of human network features such as visual features, audio features and sensual features threatens the development of customers trust towards an online business (Nohria and Eccles 1992). Using the internet as a medium for online transactions create concerns related to privacy and security among exchange partners. As a result of this, online businesses are forced to create a kind of trust relationship that is stronger than the kind of trust relationship experienced offline. Organizations with no offline availability would have to show more evidence in order to gain customers trust. Furthermore, organizations with no offline availability can proof to be trustworthy by having up-to-date security and privacy measures implemented on their websites (Aiken and Bousch, 2006). Just like offline trust influences customers to purchase goods and services, online trust will also function as a determinant to purchase goods and services too. Not only that trust facilitates purchase intention, it also facilitates customers to purchase again from an online business that has proven to be trustworthy.Gefen (2002) argued that integrity, benevolence and ability are essential for general trust formation. From an e-commerce perspective, integrity is the belief that personnel behind an online business will stick to their stated policies and rules. Benevolence is the belief that online businesses will not betray or cheat their customers in order to make more sales. Ability is the belief that online businesses have the necessary skills and competence to provide good quality products and services to their customers (Gefen, 2002). In addition, Ang et al. (2001) suggested that the ability of online businesses to deliver goods and services as expected combined with the presence of a privacy policy on the website of online businesses and the readiness of an online businesses to accept to work on the goods or services purchased if they do not meet the customers contentment, would facilitate a customers trust towards online businesses.Hemphill (2002) in his research conceptualized the basis of online trust in terms of fair information standards. He argues that online businesses should have policies on the disclosure of personal details, provide information on the purpose of collecting customers personal details and allow customers to view and access their personal data. More importantly, Hemphill (2002) argues that without an enforcement and redress mechanism, a fair information practice code is merely a suggested set of guidelines rather than a prescriptive mechanism, and does not ensure compliance with the fair information practice principles (p. 2). Hemphill (2002) was one of the few researchers who considered and examined the need for legislation to create civil solutions for customers in the occurrence of untrustworthy interactions with an online business. Furthermore, he noted that there are enforcement agencies that sanction individuals that violate privacy policies. For example, the Federal Trade Commission sanctioned several online businesses (e.g. toysmart.com) for violating privacy regulations (Hemphill, 2002).The aforementioned studies offer vital insights into the factors of online trust. The terms antecedent, element, dimension, principle and determinant are sometimes used interchangeably due to the lack of agreement among researchers on a definite meaning for what each term means to trust. Shankar et al. (2002) made a similar observation concerning trust studies in the e-business and information systems literature. Additionally, researchers often offer a list of trust determinants in their various studies without providing empirical facts on what each feature stands for to the formation of trust. 2.4 Antecedents of online trustThis section will review the antecedents of trust. Antecedents in this context are the criteria that can determine customers trust towards an online business.2.4.1 Customers web experienceCustomers trust towards an online business can be attributed to their experience in using the internet (Metzger, 2006). According to a study conducted by Corbitt et al. (2003), the degree or extent of customers web experience affects customers level of trust towards an online business. From this assertion, the level of experience customers have in using the internet influences their trust towards the internet which in turn could build their trust towards online businesses.. Aiken and Bousch (2006) stated that customers trust increases in the preliminary stages of using the internet. However, when these customers become more experienced, their trust declines when they get to know about things that could go wrong which such as the misuse of their personal details.2.4.2 Ease in using the website of an online businessThe ability of customers to use the website of an online business easily, especially during their first use of the website, influences their trust towards that online business. Ease of use in this context is specifically about the structure and the design of the website. Lohse and Spiller (1998) argue that the overall design of a website which includes product types, search functions, quality information and the absence of errors such as spelling errors influences customers trust towards online businesses. Therefore, customers are more likely to trust any online business that has its website free from all kinds of errors and also they are more likely to trust an online business if its website contains correct and complete information. Additionally, Bart et al. (2005) stated that online businesses whose websites are easy to use and have the ability to direct their customers to what they (customers) want quickly, can easily get the trust of their customers. Chau et al. (2007) argues that using a website easily is critical to the formation of trust. From this, one can argue that when a customer experiences difficulties in using the website of an online business, there is the tendency that their trust towards that online business will decrease as they would believe that if using the website proves to be difficult, then they (the online business) cannot be capable to carry out transactions.

2.4.3 Technology trustworthinessThe technical advantage of an online business is important to the development of customers trust. Customers can choose not to trust an online business that lacks the necessary technical skills required to carry out online transactions. Corbitt et al. (2003) argues that technology trustworthiness is critical to customers trust. They further add that online businesses with poor IT (information technology) operations tend not to be seen as trustworthy. A psychological state of trust can be conceptualized as attributes of benevolence and credibility (Doney and Cannon, 1997). An online business with quality technology or strong IT operations helps to build customers trust. Also, since customers accepting to conduct online transactions shows their willingness to accept the risks that comes with it (Corbitt et al. 2003), risk perceptions about the technology that is used to engage in online transactions becomes important to customers trust.2.4.4 Risk perceptionsTrust is interlinked with risk (McAllister, 1995). In the context of online transactions, customers may be exposed to the risk of opportunism or expectation. According to Williamson (1975), opportunism is defined as self interest with guile (p. 6) and it includes behaviours such as twisting information and failing to keep to ones obligations and promises (John, 1984). However, trust can be formed without the existence of risk perception. From a theoretical standpoint, one does not have to risk anything before placing his or her trust in another person. Studies have shown that risk perceptions are important for the development of trust towards online businesses (Fram and Grady, 1997; Jarvenpaa et al. 2000). Mayer et al. (1995) argue that in an organizational context, activities that involve taking risks may depend on trust. Trust can be conceptualized as the willingness of an individual to take risks and risk perception can be conceptualized as the possibility of getting both negative and positive outcomes. Stewart (1999) investigated the effects of customers trust and risk perceptions in an online business and their (customers) willingness to transact or purchase online. She further argued that perceived risk is a moderating antecedent that exists between customers trust and their willingness to transact with or purchase from an online business. Also, Mitchell (1999) argues that perceived risk is an antecedent of trust and the relationship that exists between the trust and perceived risk is not recursive.With the interlinked relationship between trust and risk perception, should two of them be disjointedly separated? It is obvious that risk perceptions and trust are closely related and as such they affect a customers behavioural intention towards online business. However, trust is more restrictive than risk perception because trust involves two different parties namely the trustee and the trustor. In transacting or purchasing online, customers can choose not to trust or trust an online business. 2.4.5 Perceived SecuritySince the internet is a global phenomenon (Wu et al. 2012), security of customers personal details become a global phenomenon too. Personal details of individuals can be intercepted and used for fraudulent activities. Furthermore, transacting in an online environment involves greater security concerns than transacting in an offline environment. Therefore customers need to be assured of the security of their personal details. Security concern is still one of the major obstacles to the development of e-commerce (Wang et al. 1998; Gefen, 2000). Perceived security is defined as a threat that creates a circumstance, condition or event with the potential to cause economic hardship to data or network resources in the form of destruction, disclosures, modification of data, denial of service and/or fraud, waste and abuse (Kalakota and Whinston, 1997: 853).An online business having security measures that involves the use of advanced technologies such as digital signatures, certificates and cryptography directed at protecting customers from fraudulent activities will positively influence customers behavioural intention to purchase from or transact with that online business. Therefore, when an online business has security measures, people have the tendency to trust that online business. In light of this, online businesses are employed to enforce security mechanisms that would include encryption, verification, protection and authentication of customers personal information (Chellappa and Sin, 2005). These mechanisms ensure that customers data cannot be viewed or modified by third-parties. Moreover, enforcing these principles or mechanisms make customers believe that their security is guaranteed which in turn contributes to their development of trust towards online transactions.2.5 Privacy concernsPrivacy is not a new concept and it has generally been conceptualized as the ability of an individual to control the terms by which his or her personal data is obtained and used (Westin, 1967, Galanxhi-Janagi and Fui-Hoon Nah, 2004). Privacy affects aspects such as the acquisition, distribution and the non-authorized use of a customers personal details (Wang et al. 1998). Privacy has been an interesting subject long before computers were invented. Privacy has been defined as the desire of individuals to choose freely under what situations and to what extent they will expose themselves, their behaviour and attitudes to others (Westin, 1967). These days, the wide use of the internet limits the ability of internet users to remain unidentified. Internet users leave lots of electronic footprints showing their preferences which can easily be retrieved, shared or used by unknown people (Zviran, 2008). Due to the fast development of new web technologies, the privacy of online users can be raided in numerous ways. In 2004, more than 50% of well-known US firms monitored the e-mail of their employees (Conley, 2004). Finishing an online transaction without revealing some personal information is very difficult, in some cases impossible. With the advent of new technologies for information processing, privacy concerns have become a very important issue in e-commerce. Privacy concerns are concerns that individuals have over the possibility that online business will use the data collected from them inappropriately or without their authorization. This inappropriate use of customers personal information may include disclosing customers personal information to third parties without customers consent and using customers personal information for purposes not stated in the privacy policy of an online business (Jarvenpaa and Toad, 1996). There are increasing concerns regarding security issues and the purpose of data submitted online in terms of the privacy of customers personal data and the unauthorized use of these data (Roca et al. 2009). Customers are sometimes unwilling to submit their personal information when these online businesses ask for them because they have concerns that the information they submit over the internet might be intercepted by hackers and used for fraudulent purposes. Therefore, customers often waver to submit personal information to online businesses because they have the feelings that these online businesses could make use of it inappropriately or they may disclose it to third parties without their consent (Lim, 2003). At other times, customers give falsified information to online business or they go to a physical store to get what they want. Trust determines the behavioural intention of a customer towards online businesses. It sums up concerns regarding privacy and the consequent use of customers information by an online business (Liu et al. 2005). Therefore, when security measures and privacy policies are taken serious by an online business, customers increase their trust towards that online business which in turn influences their behavioural intentions towards that online business.Online businesses place privacy policies on their websites to reduce customers privacy concerns. Privacy policies are policies that inform customers on what data is to be collected from them, how these data will be used, the purpose of the data collected and the recipients of the data collected (Westin, 1967). Online businesses place their privacy policy on their websites to build the trust of customers (Wu et al. 2012). Moreover, online privacy policies are aimed at decreasing the fear customers have over the disclosure of their personal details (Westin, 1967). Privacy policies have become very important in respect to reducing customers privacy concerns because these policies provide customers with information about how online businesses utilize customers personal details. Furthermore, Culnan and Milberg (1998) argue that privacy policies help customers decide whether or not to give out personal details online or whether or not to even transact with the online business at any level. Laufer and Wolfe (1977) argue that individuals carry out a simple risk-benefit calculation when deciding whether or not to provide their personal details to online businesses. They further argue that if the benefits of disclosing their personal information overshadow the risks, customers will be more likely to disclose their personal details to the online business. Privacy policy is a vital means of reducing customers privacy concerns. This policy enables customers to make a decision whether or not they want to provide personal details or to choose not to have anything to do with the online business at all (Culnan and Milberg, 1998).Customers are concerned about losing control over the ways in which online businesses handle their personal data (Wu et al. 2012). It has been argued that customers who disclosed false personal details would be willing to provide their genuine details if the online business provided a policy about how their personal details will be used (Westin, 1999). This therefore suggests that privacy concerns could be reduced if online businesses provide understandable privacy policies. However, privacy policies will reduce privacy concerns only if customers read and utilize the information disclosed in these policies. Furthermore, if the policy is not perceived as one that is understandable, then it is less likely to be considered by customers. On the other hand, if customers perceive that the privacy policies of online businesses are comprehensible, then the chances of the customers reading and utilizing the policy will be high. This further leads to customers placing their trust in that particular online business.Wu et al. (2012) argue that online businesses should provide customers with the control over all aspects of information collected from them. They further stated five principles that online businesses should follow in order to gain customers trust. These principles are: Notice: Notice requires that online businesses should give customers notification or notice about the information to be collected from them, how these information will be collected and the purpose of the information to be collected. Access: Access requires that online businesses should provide customers with the opportunity of accessing their personal information to check for completeness and accuracy. Choice: Choice requires that customers should have a choice about how their personal information will be used and to which parties it will be revealed to. It also requires that customers should be given the choice to opt-in or opt-out from a transaction. Security: Security requires that adequate security mechanisms are implemented to protect customers personal details from unauthorized use. Enforcement: Enforcement requires that there should be an enforcement authority to enforce privacy policies and also to sanction individuals who violate them. It can be suggested that if an online business complies with them, then customers privacy concerns will be limited or removed. This then influence customers trust towards online businesses.2.6 Trust and privacy concern in e-commerceIndividuals that do carry out online transactions frequently measure the risks of revealing their personal information and the misuse of this information (Milne and Culnan, 2004). Customers must have the feelings that an online business is trustworthy before revealing personal details (Schoenbachler and Gordon, 2002). Studies have proposed that concerns over customers privacy acts as an obstacle to the development of trust (Wu et al. 2012; Liu et al. 2005). While the sales force in an offline business plays an important role in customer interaction in building customers trust (Doney and Cannon, 1997), trust will play a more crucial part in an e-commerce context where there is absence of physical sales personnel. Odom et al. (2002) argued that organizations can gain a large amount of money if concerns such as privacy can be addressed appropriately (Odom et al. 2002). The internet has created lots of opportunities for organizations to put their businesses on the global map and it has also supported organizations to carry out their businesses online (Wu et al. 2012). E-commerce presents numerous benefits for online users including online services, fast and easy communication. Also, large amounts of personal details about customers are usually collected and used by organizations through registration and order forms or through the use of cookies. Furthermore, the information gathered by these organizations enables them to track customers online activities in order to get their (customers) preferences and interests. These information become useful to organizations as they help discover the demands of their customers, it also helps online businesses to create effective advertising programs and in some cases, it helps them sell advertising space on their websites better (Liu et al. 2005). In the offline environment, the physical effort of collecting, archiving and analyzing such information acts as a restraint which in a way helps to protect privacy to a reasonable extent (Blanchette and Johnson, 2002). However, the development of new web technologies does not only change the quality and the quantity of what can be collected, but also enables it to be analyzed and explored in different ways (OConnor, 2006). Because of the dramatic increase of online businesses, customers are usually worried over concerns relating to their privacy.Customers having online privacy concerns leads to their unwillingness to provide personal details, rejection of online businesses or sometimes, it could lead to them not using the internet. With privacy concerns, customers tend to distrust online businesses. Privacy concerns do not only limit the development of e-commerce but may also have an effect on the validity and completeness of customers databases which could lead to imprecise targeting, frustrated customers and wasted efforts (Wu et al. 2012). To avoid these problems, online businesses should assure users that their privacy is secure and safe. However, this comes down to the degree of trust between the online business and the customer. Because of this, many researchers view trust and privacy concerns as major barriers to the growth of e-commerce, specifically as less experienced internet users are less capable of differentiating the media propaganda from the valid threats that privacy may bring (Grabner-Kraeuter, 2002). Developing trust becomes a key aspect in reducing the concerns customers have over privacy and to improve the relationships between customers and online businesses (Milne and Boza, 2000). With the growth of e-commerce, some customers have concerns about the disclosure, transfer and sale of their personal details. Rubin and Lenard (2002) argue that these concerns are relatively slowing the growth of e-commerce. Creating a privacy policy reduces customers concerns over privacy which in turn influences their trust towards online businesses. 2.7 Behavioural intentionBehavioural intentions can be defined as the behaviours customers exhibit before or after engaging in online transactions. Trust influences behavioural intentions including the willingness to provide personal information to an online business (Liu et al. 2005). Some customers are more willing to trust an online business even if they have limited knowledge about them while others need more information before they can trust an online business. This further shows variations in individuals willingness to trust. Factors such as internet usage and previous interactions of customers have been argued to affect the behavioural intentions of customers to engage in online transactions (Salam et al. 2005). For instance, Customers who have had pleasant interactions or experiences with an online business are more likely to develop favourable behavioural intentions towards that online business. Also, pleasant internet usage such as the ease in using the website of an online business combined with its trustworthiness influences customers behavioural intention to either purchase from or visit that online business again. Salam et al. (2005) stated that continued pleasant experiences with an online business can result to a long-term relationship with the online business. They further suggested that online businesses can bring about long-term relationship with customers by improving the interface of their website making it easy for customers to use. Previous interactions influence customers behavioural intentions and decisions towards online businesses. For instance, if a customer successfully purchased goods from an online business in the past, there is the possibility of that customer wanting to transact with or purchase from that online business again. On the other hand, if the purchase or interaction was not successful in the past, customers are more likely not to purchase from that online business again. Customers learn about an online business through various ways including communication with others, recommendation from others, product promotions and advertising. Individuals visiting an online business for the first time, tend to rely on this information when deciding whether or not to transact with or purchase from that online business.2.8 Privacy, trust and behavioural intentions of customersTrust is important in an online environment (Fukuyama, 1996). Without trust, online businesses probably would exist without reliabilities. Hoffman et al. (1999) argue that the primary motive why many individuals do not transact online is due to the lack of trust and concerns over the disclosure of their personal details.As business organizations put in efforts on building long-term relationships with customers, trust has assumed a more central role (Doney and Cannon, 1997; Dwyer et al. 1987, Garbarino and Johnson, 1999; Viega et al. 2001). A successful customer relationship would require online businesses from its inception to describe the way they collect information from individuals and how those information will be used or shared. The behavioural intentions of a customer depend on the trust a customer has towards an online business (Liu et al. 2005). More particularly, a customers attitude and perception will influence the actions that customer would take when he or she thinks that certain behaviours will be connected to a specific result. In addition, social pressures and subjective customs to carry out or not to carry out a specific behaviour influences behavioural intentions, determined by the positive or negative assessment the individual has on that behavioural intention. Heijden and Verhagen (2002) proposed that the image of an online store or an online business is a vital predictor for the intention of purchasing or transacting online. They further developed dependable and accurate measures which would include usefulness of an online business and its trustworthiness. Furthermore, the result of their research showed that that trust is an important element needed for transacting online. A related result can be found from the study carried out by Jarvenpaa et al. (2000). Several studies have researched privacy and trust in the field of e-commerce (Cheung and Lee, 2006; Kim, 2001, Martin et al. 2001; McKnight et al. 2000; Nagai and Wat, 2002). However, only a handful of studies have included privacy as a prerequisite of trust (Liu et al. 2005; Wu et al. 2012). Furthermore, only few researches have been done to investigate the relationship among trust, privacy concerns and behavioural intentions. Hence, the need for research to investigate how customers trust and privacy concerns influences their behavioural intentions towards online businesses.2.9 Proposed research hypothesisOnline businesses use various ways to build customers trust in their websites such as providing online privacy policies and evidences of security measures. Liu et al., (2005) in their research found out that a successful relationship between a seller and a buyer depends on the degree of trust the buyer has in the seller. They further stated that trust is influenced by privacy which in turn influences the behavioural intentions of customers to engage in online transactions. The results of the study conducted by Liu et al., (2005) showed that there was a positive relationship between privacy and trust. Privacy has been argued to be a major criterion in building trust in electronic commerce (Liu et al., 2005; Wu et al., 2012). If customers have the assurance that their privacy is protected, the possibility of them placing their trust in online businesses will be high. Privacy influences customers trust towards online businesses. In light of this, the following hypothesis is proposed:H1= Privacy is positively related to the trust a customer has in an online business.Ocass and Fenech (2003) and Vijayasarathy (2004) empirically tested the positive relationship between security and customers behavioural intentions towards online businesses. Furthermore, Lian and Lin (2008) and Ranganathan and Ganapathy (2002) reported that in other constructs that were tested such as innovativeness; security was reported to have a greater impact on the acceptance of online transactions by customers. Also Flavin and Guinaliu (2006) reported that the formation of trust affected the behavioural intention to purchase, but that trust was particularly influenced by the security perceptions a customer has towards the handling of his or her personal information by an online business. In the study carried out by Mukherjee and Nath (2007), it was found out that security features (such as security seals) on the websites of online businesses is the key prerequisite of trust which in turn positively influences customers behavioural intention to purchase online. In light of this, the following hypothesis is proposed:H2= Security is positively related to the trust a customer has in an online businessOne of the outcomes of trust is that trust decreases the perception that an online business will cheat or betray a customer (Ganesan, 1994). Increased level of customers trust has been argued to positively influence customers behavioural intention to engage in online transactions. Ganesan (1994) reported that low perceptions of risks towards online transactions increases customers trust which in turn influences their behavioural intentions. One can therefore say that trust reduces the risk perceptions customers have toward online businesses. Also, low perception of risk will influence customers behavioural intentions towards an online business. Similarly, during a transaction process, the level of trust a customer has towards an online business is a function of the level of risk that is taking place during the transaction (Koller, 1988). Andrade (2000) posits that customers conceptualize transacting online to be of higher risk than transacting in an offline environment. Trust is interlinked with risk (McAllister, 1995). Since trust has been argued to have an effect on the behaviours of customers, Jarvenpaa and Todd (1996) posits that customers trust in online businesses will reduce their risk perceptions of being cheated or betrayed by online businesses. A low perception of risk will negatively influence customers behavioural intentions towards the online business. Thus, the following hypothesis is proposed:H3= Customers risk perceptions towards an online business is negatively related to their trust towards that online business. According to a study conducted by Chen and Barnes (2007), trust influences behavioural intentions of customers to transact with an online business. Trust in e-commerce is important to online transactions because the level of uncertainty or ambiguity in an online environment exposes the user/customer to vulnerability because he or she cannot physically see whom he or she is transacting with. Therefore, customers trust in online businesses will determine their behavioural intentions to conduct online transactions. Moreover, some researchers have carried out research to show that trust in online businesses increases behavioural intention to engage in online transactions (George, 2002; Bhuttacherjee, 2002; Mukherjee and Nath, 2007). Bhuttacherjee (2002) reported that trust positively affects the behavioural intention of customers to transact with an online business. On the other hand, George (2002) showed that the more customers believe an online business to be trustworthy, the higher their behavioural intentions towards transacting with that online business will be. It can therefore be argued that trust will influence intentions to transact online. Thus, the following hypothesis is proposed:H4= Trust is positively related to the behavioural intentions a customer has towards online business.George (2002) reported that negative behavioural intentions toward online transactions are associated with privacy concerns. Privacy concerns have been pointed out as a significant factor that prevents consumers from engaging in online transactions (Hoffman et al., 1999). These concerns may include customers receiving spam mails, customers being tracked for their history in using the internet and customers having their personal details being accessed by third parties without authorization (Wang et al., 1999). However, customers may find it beneficial when online businesses remember basic information about them and use this information to provide them with what they (customers) want. Although such customization is beneficial to both parties, if its use is leaked, it becomes a threat to customers privacy. Studies have shown that customers are increasingly concerned about the absence of privacy protection during online transactions (Wu et al., 2012; Liu et al., 2005). According to a web survey of internet users, almost 95% of users refused to transact online when asked to provide personal details (Hoffman et al., 1999). Another web survey showed that 92% of web users are concerned about their privacy and 61% declined to transact online (Ryker et al., 2002). It is obvious that privacy concerns have an influence over the behavioural intention of a person to purchase online. People who are concerned with their privacy could be unwilling to go ahead with transacting with an online business as most of it requires them disclosing personal information. Therefore the following hypothesis is proposed:H5= Privacy is negatively related to the behavioural intentions of a customer has towards an online business.

RESEARCH METHODOLOGY3.0 OverviewAccording to Easterby-Smith et al., (2008), a research methodology can be defined as the combination of different techniques used to enquire about a particular situation. This chapter aims to discuss the techniques that were employed to enquire about the effects of customers trust and privacy concerns towards online businesses. Specifically, this chapter will discuss the epistemological considerations of this research, the ontological considerations of this research, the ethics employed during the course of this research and the strategy that was employed during the course of this research. This chapter would also describe the various statistical techniques used for this research. 3.1 Epistemological considerationsEpistemological considerations relates to the question of what is considered to be acceptable knowledge in a particular area of study (Bryman, 2012). This research employed positivism as its epistemological approach. This is because it describes the philosophical position that can be determined by research. Further, it describes how trust and privacy concerns influence an individuals behavioural intention to engage in online transactions. Positivism also entails generating hypothesis or hypotheses that can be tested, thereby paving the way for further explanations about relevant theories or literatures. This relates with the deductive theoretical approach. Since, this research involved deducing and testing hypotheses thereby allowing explanations to be assessed, one can therefore say that it followed a positivism epistemological approach. Furthermore, positivism entails that only knowledge that is confirmed by the senses can truly be regarded as knowledge. This research involves the acquisition of acceptable knowledge on the effects of customers trust and privacy concerns towards online businesses. According to Easterby-Smith et al., (2008), positivism can cover a wide range of situations and can be used when a sample size is large. In light of this, positivism can further be justified as the epistemological approach for this research since this research covers a wide range of situations which would include the various behavioural intentions customers have towards online businesses.

3.2 Ontological considerationsOntological considerations are concerned with the character of social entities (Bryman, 2012). Basically, ontology concerns how a researcher sees the world. Easterby-Smith et al., (2008) argues that different researchers have different viewpoint about a research area. Collins (1983) stated what counts for truth can vary from place to place and from time to time (p.88). Similarly, the underlying assumption of this research is that a customers willingness or behavioural intentions to engage in online transactions is dependent on/upon the levels of trust and the degree of privacy concerns he or she has towards online businesses. The researcher in this context is of the opinion that individuals have different views about online transactions. Therefore, facts related to this research were gathered through consensus based on different perspectives.3.3 Research ethicsResearch ethics refers to the proper code of conduct researchers exhibit towards their research subjects (Saunders et al., 2011). Bryman (2012) highlighted that a research should follow the following ethics: Provide an informed consent to the research subjects stating the objectives of the research. Ensure that the research subjects are protected from any form of harm. Ensure that the data of the research subjects are kept strictly confidential and used only for the purpose of the research. Ensure that no form of deception is used on the research subjects.The ethical principles highlighted above were duly observed by the researcher. Also, the researcher ensured that participants data were not publicized or circulated. The research subjects were duly informed of the research objective as this was stated on the first page of the questionnaire. Participation was voluntary, participants were allowed to either accept or reject the offer to participate in the survey.

3.4 Research strategyResearch strategy according to Bryman (2012) is the broad orientation to the conduct of a social research. Bryman (2012) stated that a research that entails a deductive quantifiable approach to investigate the relationships between a particular research area and the research that is to be conducted can be referred to as a quantitative research. This research can be justified as a quantitative research since it involved quantifying the collected data before analyzing them. Basically, the steps that were involved in this research (quantitative) would be discussed in this section.3.4.1 TheoryThis research employed a deductive theoretical approach. According to Bryman (2012), deductive theory shows the nature of the relationship between what is known about a particular research area and the research that is to be carried out. In the context of this research, the researcher on the basis of what is already known about customers trust and privacy concerns towards online businesses, deduced hypotheses that were subjected to analysis. These hypotheses were either confirmed or rejected. Thus, agreeing with Brymans (2012) argument where he stated that deductive theoretical approach involves confirming or rejecting a hypothesis in order to enable a researcher to compare them with what is already known about a particular research area.3.4.2 Deducing hypothesesAfter going through relevant literatures on the effects of customers trust and privacy concerns towards online businesses, some hypotheses were deduced. These hypotheses were to be tested to find out the relationship or significance between variables related to this research.3.4.3 Research designAccording to Bryman (2012), a research design provides an outline for the collection and analyses of data. Furthermore, a research design shows what data is to be collected, how these data would be collected and where these data would be collected from. This is done for the purpose of data analysis. This research employed a cross-sectional design and the use of questionnaire was the method that was employed to collect information from the research subjects. This agrees with Brymans (2012) argument where he argued that in a cross-sectional design, information may be collected either by structured interviews or questionnaires. Moreover, items on the questionnaire were collected simultaneously. This also agrees with Brymans (2012) argument where he stated that in any cross-sectional design research, data on the variables that are of interest to a researcher are mostly collected at the same time. Furthermore, when a person completes a questionnaire, the responses to the items are submitted at the same time. During the course of this research, it was possible to investigate relationships that exist between variables. This further agrees with the argument by Bryman (2012) where he stated that it is feasible to examine relationships between variables in a cross-sectional research design. He added that in most cases, there is nothing like time ordering to the variables because the information on these variables is usually collected more or less simultaneously.3.4.4 SamplingThis involves selecting a section of a specific population for research purposes (Bryman, 2012). This section will describe the sample used for this research and the sampling design used.3.4.4.1 Choice of sample/ survey sampleIt would be difficult to reach or survey all the individuals that engage in online transactions. The postgraduate students of Lancaster University were used as the survey sample for this research. However, it is of importance to state here that arriving at this choice of survey sample was not done without basis. According to Walczuch and Lundgren (2004), using students for any research study in the field of e-commerce and e-retailing, is appropriate as they have the opportunity of accessing the internet for communication and transaction purposes. They further stated that students also represent the sample for studies like this, since they are also customers of online businesses. Moreover, students frequently buy products from online businesses. In most cases, these products are sold at a lower price online compared to businesses operating in an offline environment. Furthermore, this gives a good reason for students to engage in online transactions (Walczuch and Lundgren, 2004). In addition, the overall control of the research was essential, differences due to time and place of the research would be overpowering. Hence, the need to use the postgraduate students of Lancaster University as survey sample.Using students as survey sample in research is often criticized (Liu et al., 2005). However, they are both appropriate and acceptable for studies that involve certain relationship patterns (Dickson, 1989). Furthermore, this research is aimed at understanding how trust and privacy concerns relate to the behavioural intention of customers to carry out online transactions. Thus, this agrees with Dicksons (1989) argument since this research has a pattern of relationship. In addition, using students may be even more suitable, since their demographics suit parts of the customer profile of various online businesses.3.4.4.2 Sampling designThe sampling design employed in this research is the probability sampling design. Easterby-Smith et al., (2008) argues that employing the use of probability sampling allows the researcher to get accurate and precise information about the population from which the sample is taken. Specifically, this research employed the use of a stratified random sampling which is a type of probability sampling design. Therefore, the survey sample used in this research was divided into homogenous groups to ensure the representativeness of the sample in the given population. Homogenous group in the context of this research refers to the various postgraduate departments of Lancaster University. Some of these departments include project management, environmental sciences, and engineering. The questionnaire was sent to all the postgraduate students of Lancaster University. Since all postgraduate students in each department study or take the same module, they can be referred to as a homogenous group. Easterby-Smith et al., (2008) argued that using a probability sampling design would enable a researcher to gather accurate information about the relationship that exists between a sample and the population from which that sample is drawn. Furthermore, the researcher would be able to make a concrete judgement between the characteristics of the population from which a particular sample is drawn and the sample itself, if only the relationship that exists between them is understood. Given the investigative nature of this research, probability sampling method suits the purpose of this research. 3.4.5 Administering the research instrumentQuestionnaires were used to collect information from the surveyed sample. A questionnaire is a list of questions usually administered to the selected sample for the purpose of collecting information (Bryman, 2012). In the context of this research, the questionnaire was administered to the respondents online. It was distributed to the postgraduate students of Lancaster University through the ITMOC programme coordinator.3.4.5.1 Questionnaire designThe questionnaire was designed using Google forms. The measures used in the questionnaire were mostly adapted from related prior studies. Most of the items or questions were measured using a seven point likert-type scale with anchors from Strongly disagree to Strongly agree. Other items had response options such as Yes or No. Items for trust were adapted from prior research by Corbitt et al., (2013) and Pan and Zinkhan (2006). Items for perceived security were adapted from Liu et al., (2005). Items for privacy concerns were adapted from Liu et al., (2005) and Corbitt et al., (2003). Items for behavioural intentions were adapted from Wu et al., (2012) and Liu et al., (2005). Items for perceived risks were adapted from Corbitt et al., (2003). Other items were questions that would enable the researcher know the characteristics of the respondents. 3.4.6 Processing the dataThis stage involved transforming the collected information into data. In the context of this research, the data was processed so that it can be quantified. The quantification process involved coding the collected information. In other words, the quantification process involved transforming the collected information into numbers to aid the quantitative analysis of the data. Codes acts as labels placed on data about individuals to allow information to be processed by a computer (Bryman, 2012).3.5 PretestingThe questionnaire was pretested to identify any problem that the research subjects might face when answering the questionnaire. This agrees with Grfs (2000) argument where he said that by carrying out pre-tests, researchers would be able to identify any problem associated with the questionnaire. Furthermore, pretesting allows researchers to improve questionnaires if problems are identified.During the course of this research, the researcher pre-tested the questionnaire by sending it to some individuals that are part of the survey sample. There was a low response as only nine (5) responses were received within three (3) weeks. Given the duration of the research (3 months), this was seen as a very low response. This was in a way attributed to the fact that the questionnaire did not provide participants with anonymity. Esposito et al., (1984) argued that providing respondents with anonymity decreases the outcomes of social desirability as well as increasing response rate. The researcher corrected this and provided participants with anonymity. This improved the response rate.3.6 Statistical techniquesStatistical Package for the Social Science (SPSS) 20 is the statistical tool that was used for analysis carried out in this research. Various tests were conducted in order to generate findings. Before these tests were conducted, some of the items in the questionnaire were combined into single constructs. These items include those that have their responses anchoring from Strongly disagree to Strongly agree. This agrees with Likert (1932) where he stated that to create an attitudinal measurement scale, responses from series of questions or items that are related should be combined into a single composite score. Each item with anchors from Strongly disagree to Strongly agree is a likert-type data but when series of these likert-type data items are combined, they form a likert-scale data (Boone Jr and Boone, 2012). They added that when related items are combined into single composite scores, they would facilitate the data analysis process by providing a quantitative measure of a personality attribute or character. Moreover, a score is created by calculating the sum of series of items that are related to a particular construct (Boone Jr and Boone). The constructs used in this research are: trust, security, privacy concerns, behavioural intentions and risk perceptions. The questionnaire has four (4) items for trust, two (2) items for security perceptions, five (5) items for behavioural intentions and seven (7) items for risk perceptions. Therefore, responses to the items on trust were combined to give a single composite score for trust. Also, responses to the items on security perceptions, privacy concerns, behavioural intentions and risk perceptions were combined to give a single composite score for security perceptions, privacy concerns, behavioural intentions and risk perceptions respectively. Take the case of trust for example; trust has four (4) items. For each of these items respondents can select any response within the range of Strongly disagree to Strongly agree which were coded as 1 to 7. Supposing a respondent selects strongly disagree (1) for the first item on trust, strongly agree (7) for the second item on trust, agree (6) for the third item on trust and mildly agree (5) for the fourth item on trust; the trust score for this particular respondent would be the combination (sum) of all the responses he or she answered for the trust items. In other words, it would be 1 + 7 + 6 + 5 which is 19. This example is shown in the table below.Trust item 1Trust item 2Trust item 3Trust item 4Trust score

Respondent 176519

This was not done only for trust. It was also done for security, privacy concerns, behavioural intentions and risk perceptions. Furthermore, the score for each of these single variables was calculated for all the respondents.The questionnaire is made up of 29 items. Out of these 29 items, 6 of them do not have anchors ranging from Strongly disagree to Strongly agree, rather, they have response options such as Yes or No. The response options for these 6 items were coded with numbers but these numbers only served as labels. These are referred to as nominal scale items. Ary et al., (2010) stated that nominal scale items can be coded into numbers however, these numbers only serve as labels. They further stated that there is no form of ranking in nominal scale items. An example of this would be what is your gender? With response options as male or female A respondent can select either male or female depending on his or her gender. Male can come before female and female can come before male. Therefore, male can be coded as 1 and female can be coded as 2. Also, female can be coded as 1 and male can be coded as 2. In this case, there is no form of ranking. The numbers are only serving as labels for the purpose of analysis. Out of the 29 items in the questionnaire, 23 items have anchors ranging from Strongly disagree to Strongly agree. Numbers (codes) assigned to these response options were within the range of 1-7 with 1 representing Strongly disagree and 7 representing Strongly agree. In these cases, there is a form of rank; the numbers are ranked in measures of magnitude. These are referred to as ordinal scale items. Ary et al., (2010) stated that ordinal scale items are ranked in order of magnitudes. Moreover, numbers assigned or coded to ordinal scale items show a greater than relationship, though, how much greater is not inferred. These numbers or codes only specify the order of ranks (Ary et al., 2010).As stated earlier, composite scores were generated for each of the five (5) constructs. According to Boone Jr and Boone (2012), composite scores are referred to as interval scales. The composite scores generated, were analyzed as interval measurement scales. This further agrees with Boone Jr and Boones (2012) argument where they stated that for the purpose of analysis, composite scores should be analyzed as interval measurement scales. The following tests were carried out using SPSS 20.3.6.1 Descriptive statistics According to Greasley (2008), descriptive statistics provide the summary information about a given data. The descriptive statistics that were carried out on the items with response options other than Strongly disagree to Strongly agree are:3.6.1.1 FrequenciesThis was done to enable the researcher know the number and percentages of respondents that responded to these items. This agrees with Greasleys (2008) argument where he stated that a researcher has to run frequencies to enable him or her know the number and the percentage of respondents that responded to a particular question.3.6.1.2 ModeThe mode was carried out on these items to enable the researcher know the value that occurred most frequently. This also agrees with Greasleys (2008) argument where he stated that modes would enable the researchers to know the most frequently occurring value.For the other items, because they were converted to composite scores (interval measurement scale), the descriptive statistics that were carried out are:

3.6.1.3 MeanThis was carried out to enable the researcher know the average score for each construct. Easterby-Smith et al., (2008) stated that the mean allows a researcher to know the average value for a particular construct or item. This justifies the reason for calculating the mean.3.6.1.4 Standard deviationThis was carried out to enable the researcher to know the average spread around the mean score of each construct. This agrees with the argument by Easterby-Smith et al., (2008) where they stated that the standard deviation enables the researcher to know the most typical distance of scores from the mean.3.6.1.5 Reliability analysisA reliability analysis was carried out to ensure that the items or variables in each construct were internally consistent. It was carried out using Cronbachs . Bryman (2012) stated that when respondents responses are combined to form scores, there will be the possibility of having items in a construct that are not related to that particular construct. They may be related to another construct. Therefore, there was the need to carry out a reliability test to make sure that the items in a construct are related to that particular construct. 3.6.2 Further analyses These tests which include correlation analysis, regression analysis, t-tests were carried out to enable the researcher generate findings that would help in answering the research question. Also, further analyses were carried out to test the already postulated hypotheses. 3.6.2.1 Correlation analysisThis analysis was used to test hypotheses. In other words, it was used to analyze the relationships between the constructs stipulated in each hypothesis. It was also carried out to check for any significance between two constructs. This agrees with Brymans (2012) argument where he stated that to find the relationships between variables, researchers should carry out correlation analysis. In the context of this research, Pearsons correlation was used to assess the level of relationship between variables.3.6.2.2 Regression analysisThis analysis was conducted to estimate the relationships that exist among constructs. Specifically, it was carried out to estimate the relationship among behavioural intention (dependent variable), trust (independent variable) and privacy concerns (independent variable). This agrees with Sykess (1993) where he stated that regression analysis enables a researcher to ascertain the effect of one or more independent variables on a dependent variable. The researcher is trying to investigate how the effects of customers trust and privacy concerns influence the behavioural intentions of customers towards online businesses. As a result, behavioural intention is depending on trust and privacy concerns. Thus, behavioural intention is the dependent variable while both trust and privacy concerns are the independent variables. 3.6.2.3 T-testThe t-test was carried out to compare the mean scores of two constructs. This agrees with the argument by Easterby-Smith et al., (2012) where they stated that it is necessary for researchers to carry out t-tests to allow them compare the mean values of two variables.

ANALYSIS AND FINDINGS4.0 OverviewThis chapter presents the results of the data analyzed. The next section will focus on the characteristics of the respondents. The third section will focus on the hypotheses testing. These analyses were done to enable the researcher answer the research question.4.1 Characteristics of respondentsDescriptive statistics were carried out to know the characteristics of the respondents. A total of 131 respondents completed the questionnaire. Table 1 shows the characteristics of the respondents.4.1.1 Gender51 males completed the questionnaire and this represents 38.9% of the total number of respondents that participated in the questionnaire survey. 80 females completed the questionnaire representing 61.1% of the total number of respondents that participated in the questionnaire survey. 4.1.2 Age groupThe item on age group shows that 57 respondents are within the age group of 21-25 representing 43.5% of the total number of respondents that completed the questionnaire. 34 respondents are within the age group of 26-30 representing 26% of the total number of respondents that completed the questionnaire. 15 respondents are within the age group of 31-35 representing 11.5% of the total number of respondents that completed the questionnaire. 5 respondents are within the age group of 36-40 representing 3.8% of the total number of respondents that completed the questionnaire. 8 respondents are within the age group of 41-45 representing 6.1% of the total number of respondents that completed the questionnaire. 12 respondents are within the age group of 46 and above representing 9.2% of the total number of respondents that completed the questionnaire. The modal age group is 21-25. This means that majority of the respondents are within the age group of 21-25.4.1.3 Web experience5 respondents reported that they have used the internet a few times before the survey representing 3.8% of the total number of respondents that completed the questionnaire. 4 respondents reported that they do use the internet a few times a month representing 3.1% of the total number of respondents that completed the questionnaire. 3 respondents reported that they do use the internet every week representing 2.3% of the total number of respondents that completed the questionnaire. 112 respondents reported that they do use the internet almost every day representing 85.5% of the total number of respondents that completed the questionnaire. 7 respondents reported other times when they use the internet representing 5.3% of the total number of respondents that completed the questionnaire. The modal web or internet experience is I do use the internet/world wide web almost every day. This means that majority of the respondents use the internet almost every day.4.1.4 Buying goods/services onlineAll 131 respondents reported that they do buy goods/services online. 2 respondents reported that they do buy goods/services daily representing 1.5% of the total number of respondents that completed the questionnaire. 27 respondents reported that they do buy goods/services weekly representing 20.6% of the total number of respondents that completed the questionnaire. 26 respondents reported that they do buy goods/services once in two weeks representing 19.8% of the total number of respondents that completed the questionnaire. 67 respondents reported that they do buy goods/services monthly representing 51.1% of the total number of respondents that completed the questionnaire. 9 respondents reported other times when they buy goods/services representing 6.9% of the total number of respondents that completed the questionnaire. Majority of the respondents buy goods/services online monthly.4.1.5 Average amount7 respondents reported that they spent an average of