Relationship Between Privacy, Security and Trust in E-vendors
Info: 8497 words (34 pages) Dissertation
Published: 16th Dec 2019
Tagged: Cyber Security
Abstract
The development of online retailing has been hampered by a number of factors, the most noticeable being consumers’ lack of trust in the electric commerce environment. Examining two of trusts most important pre requisites, privacy and security may provide a solution or enable e-vendors to understand steps needed for progression. As a website is an information technology, intention to use is partially explained by the theory acceptance model (TAM ) which is taken into consideration in this study.
The purpose of this dissertation is to examine the relationship between privacy, security and trust and evaluate to what extent the factors affect user’s level of trust in e-vendors as distinct variables. In addition, a better understand of the relationship between the two identified factors is sought. Trust as a determinant for behavioural intention and actual usage is also investigated.
Data was collected from 67 millennials in the UK that participate in online commerce, the respondents were requested to fill in an online questionnaire. Results revealed that both perceived privacy and security significantly affected consumers’ and there was in fact a positive relationship between the two determinants. A significant strong positive relationship was also confirmed between consumer’s trust in the e- vendor and behavioural intention. Thus e-vendors must build a trustworthy market place in order to attract and retain consumer.
This studies main contribution is to develop and validate a theoretical framework of e-commerce adoption. The model comprises of TAM constructs, perceived privacy and security and trust beliefs.
Table of Contents
1.3 Outline of subsequent chapters
2.2 Importance of trust in E-commerce
2.3 Perceived security and privacy as determining trust factors
2.4 Technology Acceptance Model (TAM) and ecommerce
2.6 Research model and hypotheses development
2.6.2 Perceived privacy and security
3.2 Data collection and analysis
3.4 Sampling for Questionnaire
3.7 Validity, generalisability and reliability
4. Data Analysis and Discussion
4.1 Descriptive statistical analysis
4.5 Hypothesis testing results
5.1 Limitations and notes for future research
1. Introduction
The adoption and proliferation of digital technology during the twentieth century resulted in the digital revolution (NG, 2014). This evolved digital age provides a global platform over which businesses and individuals can digitally connect, thereby evading geographical limitations (Castells, 1999). Hence the introduction of internet retailing, a concept entailing electronic commerce (e-commerce): commercial transactions of selling or buying conducted online (Mesenbourg, 2001). This research focuses on Business-to-Consumer (B2C), a type of e-commerce that corresponds to the retail sector. B2C involves an electronic business relationship between businesses and final consumers (Fernandes, 2014).
The ability to obtain an extensive variety of online product information and make digital transactions via computing networks at the click of a button has catapulted the popularity of web-based services. The United Kingdom has the third largest e-commerce market worldwide, with 18% of all retail purchases expected to occur online this year. As the biggest demographic with disposable income, millennials account for over 59% of B2C e-commerce representing trillions in sales (Wilson, 2018). By 2040 it is predicted 95% of such purchases could be facilitated by e-commerce (Statista, 2018).
1.1 Rationale and Background
Though the industry is optimistic, as a newer form of shopping the potential of online retailing has not been fulfilled. Wilson (2018) reports almost 70% of online baskets are abandoned at checkout. This is due in part to consumers’ lack of trust in e-commerce, which is characterised with potential opportunism, uncertainty and anonymity. Studies have identified that consumers are hesitant to complete transactions or provide personal information to online sales channels (e-vendors), because of privacy and security concerns (Gurung, 2016). Since the introduction of e-commerce, privacy and security have been recognized as contributing factors to building trust online.
Due to the limited richness of a web-site, customers cannot gauge trust cues from an e-vendor in comparison with face-face interactions. Physical retail stores involve direct contact with a business’s employees and offer a ‘face’ to the company that can be held accountable. When customers can physically view merchandise and interact with sales associates, it encourages an increased sense of security. Conversely e-commerce does not allow the chance to inspect the quality of goods, or the opportunity to physically interact with a knowledgeable employee but, relies solely on the trust of consumers (McKnight and Chervany, 2001). Hence, consumers’ trust in e-vendors is crucial in an online setting and among the most important factors distinguishing online buyers from non-buyers (Hoffman et al., 1999). As pre-requisites for trust assuring security and privacy for consumers is crucial in the acceptance of e-commerce (Rupel et al., 2003).
The primary interface of e-commerce is a web site: a type of information technology used to communicate, and to exchange information that consequently leads to a transaction (Thaw et al, 2009). Studies of technology adoption have proposed an explanation of the relationship between user actions, behavioural intention to use and acceptance (Davis, 1989; Gefen and Straub, 1997). The technology acceptance model (TAM) proposed by Davis (1989) has become the bona fide model of IT acceptance. The basic premise in TAM is that user acceptance of any new technology is determined by two factors: perceived ease of use (PEOU) and perceived usefulness (PU). In the context of e -commerce the theory posits that users PEOU and PU of retail websites determine behavioural intention towards accepting and using the technology. Thus, in addition to trust technological attributes of IT must be considered as a partial set of explanatory variables in understanding consumer behaviour towards e-commerce.
Extensive research (Cheskin Reasearch, 1999; Florian, 2001; Gefen, 2003) confirms that consumer trust positively affects the PU of e-vendors and therefore intention to use. These studies conclude that trust is as important to e-commerce adoption as the widely accepted TAM antecedents. Together the complementary variable sets explain a substantial proportion of variance in behavioural intention and actual usage of new technology. The effects of trust on TAM constructs has been widely studied and will not be directly investigated in this dissertation. However, there is little published research on perceived privacy and security as joint trust pre-requisites and predictors of future IT usage. Both factors are recognised as important elements of a consumer’s e-commerce experience, however, there is a lack of academic literature that provides a clear delineation of the impact of privacy and security on consumers’ trust in e-vendors as two distinct concepts as well as their joint effect. Gaps in this literature indicate further research needs to be done to investigate the relationship between privacy and security, to fully understand their impact on consumer trust and therefore how to obtain and sustain trust in e-vendors.
The lack of physical interaction and clues associated with the online environment make consumer trust in e-vendors difficult to establish. This constitutes a major challenge for e-vendors. Evaluating privacy and security as determining factors can help gain insights on their combined effects on trust and therefore how to establish it. This study is undertaken to evaluate the extent to which consumers’ perceived privacy and security effect consumer trust in e- vendors as distinct variables. In addition, this research will shed light on how behavioural intentions are influenced by said factors through trust jointly with traditional TAM constructs: PU and PEOU. The research outcome is an important contribution to e-commerce knowledge. It will pinpoint areas that online retailers can improve on to effectively communicate their trustworthiness and significantly change consumer attitude towards e-commerce.
1.2 Aim and Objective
The research aim is to examine the influence of privacy and security on consumers trust in e-vendors.
The objectives are:
To evaluate how perceived privacy and security affect user’s level of trust in e-vendors as distinct variables
To identify if there is a relationship between the identified determining factors
To expand on the theoretical model: TAM to include perceived privacy and security as pre-requisites for trust.
1.3 Outline of subsequent chapters
Following the introduction, this dissertation is broken down into the following chapters:
Chapter 2: Literature review
This chapter reviews the current literature regarding trust, perceived privacy and security as determining factors and the theoretical framework of this research. The findings and conclusions are discussed.
Chapter 3: Research methodology
the choice of methodology and research strategy is presented. Following this, data collection, analysis and questionnaire design are described. The chapter ends with a discussion about validity, reliability and generalisability.
Chapter 4: Data analysis and Discussion
This chapter contains results from detailed data analysis and hypothesis testing. The chapter ends with a discussion of the results obtained.
Chapter 5: Conclusion
In this chapter the dissertation is summarised, and limitations are discussed. Direction for possible related research in the future is suggested.
2. Literature Review
This section reviews the current literature regarding trust and its importance in ecommerce. Thereafter, literature and conclusion on determining factors of trust and the theoretical model this research is based on are discussed. The chapter ends with the modified theoretical model this research assesses.
2.1 The concept of trust
Trust can be defined as ‘firm belief in the reliability, truth or ability of someone or something’ (Oxford English dictionary, 2017). The concept has been examined in numerous disciplines, including social psychology, sociology, and e-commerce which all view trust from unique perspectives (Roca et al., 2009). Sociologist refer to trust as a social structure. On the other hand, psychologists see trust as a personal trait; individuals cognitively choose whom they will trust, in which respects and under which circumstances, their chose is based on what they believe to be good reason (Lewis & Weigert, 1985 p. 98). From the social psychologist perspective, “trust is characterised in terms of the expectation and willingness of the trusting party engaging in a transaction” (Roca et al., 2009). The definitions stated are relatable to circumstances in the discipline they represent, inferring trust is situation- specific.
There are considerable variations of the definition of trust across literature, implying trust is a complex concept to explain. McKnight and Chervany (2001) argue although the concept is multi-dimensional, as a vital relationship researched across several fields clarification is needed. The scholars propose an interdisciplinary typology consisting of three trust types: Dispositional trust (stems from psychology); institutional trust (from sociology) and interpersonal trust (from social psychology).
Dispositional trust refers to an induvial trust in general others and is built on an individual’s belief that others are reliable and mean well (McKnight and Chervany, 2001). Pennanen et al, (2008) add that disposition to trust is a personality-driven trait. That is, an individual’s inherent qualities influences their tendency to trust. Additionally, an individual’s disposition to trust is shaped by particular childhood-derived attributes that become less or more stable over time as well as cultural background. McKnight and Chervany’s (2001) theoretical work notes trust in general, is likely the result of a disposition to trust. When a new relationship is formed, before people have the chance to determine whether the other party is trustworthy, their disposition is the leading determinant of their trust. Institution-based trust refers to an individual’s trust in an environment or structure. In this instance, trust is not determined by an individual’s innate features but by the situation. Interpersonal trust refers to an individual’s trust in another specific party or the trustworthiness of a third party. Pennanen et al, (2008, p.110) define it “as the perception you have that other people will not do anything that will harm your interest; the individual is giving the willingness to accept vulnerability or risk based on expectations regarding another person’s behaviour.” Gefen et al. (2003) posit familiarity is a prerequisite of trust, as it creates an understanding of what is happening. The more familiar one is with a circumstance or individual, the more (or less) likely we trust them.
A clear deduction from this literature is that trust is crucial to building any relationship and has the ability to affect interactions with others.
2.2 Importance of trust in E-commerce
As more consumers look to the web for products and services, e-commerce presents a large threat to the more traditional brick and mortar retailers (Entrepreneur 2017). Although online websites are available almost anywhere and at any time, as a newer form of purchasing goods consumers’ trust is low as there are more risks involved than traditional retail shopping. Risks include security and privacy threats that could compromise consumers personal information (Kohli 2016).
Gefen et al., (2003) define trust in relation to e-commerce as:
“The expectation that companies with whom one interacts will not take undue advantage of a dependence upon them. It is a belief the trusted party will behave in an ethical, dependable and socially appropriate manner and will fulfil their expected commitments in conditions of interdependence and potential vulnerability.” (vol. 50, no. 3, p. 308)
Considering this perception, trust is central to a B2C online relationship as it is crucial wherever uncertainty, interdependence or risk exist (Ruppel et al., 2003). In support of this belief McKnight and Chervany (2001) propose their typology of trust types is central to interpreting consumer trust in e-commerce. Trust is a necessity in such an environment as there is no real guarantee that the e-vendor will not partake in offensive opportunistic activities, such as privacy violation and unlawful use of consumers financial information. In traditional offline settings an in-person transaction allows an individual to exercise judgement about the retailer. In comparison, there is a higher degree of uncertainty associated with online transactions. In a virtual environment it is difficult to connect an identity to an actual individual or have any direct control over the e-vendors actions. Additional studies (Hoffman et al., 1999; Lee and Turban, 2002; Pavlou, 2003) acknowledge the lack of trust in online transactions is the foremost reason reason for consumers not engaging in e-commerce.
Considering consumers who trust are more likely to engage in online transactions, its importance as a significant facilitator of e-commerce has become progressively recognised in relevant academic literature. Scholars have studied how consumers’ trust is developed toward online businesses without any face-face interaction. Jarvenpaa et al., (2000) propose positive online interactions with an e-vendors web-site develops consumers’ trust. Understandably trust is more likely to flourish when consumers feel at more at ease using a web site. (Roca et al., 2009). Gefen et al., (2003) explore this narrative and investigate experienced and inexperienced consumer trust in e-vendors. The study concludes repeat consumers trusted the e-vendor more and were therefore more likely to take part in e-commerce. On the other hand, inexperienced consumers trusted the e-vendor less and were therefore less likely to take part in e-commerce. From these results, one can assume consumers’ trust is somewhat influenced by previous positive interactions with e-vendors and is a deciding factor as to whether consumers participate in ecommerce. Both studies conclude the impact of trust on e-commerce adoption is significant. Therefore, in order to improve purchase intentions it is vital to investigate significant trust determining factors.
In the current study, I consider McKnight and Chervany’s (2001) typology when discussing trust. Dispositional refers to consumer trust in others, shaped from personal experience with e-vendors. Interpersonal trust refers specifically to the e-commerce consumer trusting the e-vendor and, institutional trust refers to consumer trust in the web itself. McKnight and Chervany’s (2001) study originally involved an in-depth analysis of existing trust definitions from over 80 articles and books across different fields. Thus, the classification system accurately simplifies the complexity of trust, without losing meanings associated with original definitions. In addition, the trust types are interrelated which is particularly valuable for this study.
Following the literature on the concept of trust and its application to e-commerce, the next section discusses determining factors of trust in e-commerce.
2.3 Perceived security and privacy as determining trust factors
Trust has been identified as a major barrier to the development of e‐commerce. Six ‘critical’ factors affecting the level of trust in online transactions were identified in Cheskin and Sapient ‘s (1999) ground breaking report: company brand, website navigation, process fulfilment, web site presentation, web site function and seals of approval. The research concluded though trust is affected by a number of factors, in privacy and security were prevalent in producing a sense of trustworthiness. The researchers reinforce the narrative that without trust in online sites, e-commerce cannot reach its full potential. The validity of Cheskin and Sapient’s (1999) research conclusions in today’s society is questionable as the study was conducted well over a decade ago. It is wise to consider whether the level of trust in e-commerce has developed with the constantly evolving digital economy. However, as Cheskin and Sapient posit, success of the online environment today still depends heavily on gaining and maintaining the trust of users. More recently, Gurung (2016) confirm security and privacy as current influencers of behavioural intention and e-commerce usage.
For the purposes of this research, perceived privacy is defined as users’ perception of how they are protected from risks related to unauthorised sharing of personal after it is collected (Roca et al., 2009). Perceived security refers to a users’ precipitation about how secure an online transaction is in regard to protection from unauthorized access of their financial information.
The web threatens the privacy of user’s personal information in extreme and new ways. Thus, numerous consumers choose not to partake in any manner of online transaction activity, to avoid giving out their information to online businesses (Hoffman et al.,1999). According to Forrester Research 43% of participants cited fears over data privacy issues regarding the personal information required by e-vendors. Dolatabadi and Ebrahimi (2010) report that privacy has a positive and significant influence on consumers’ online trust. This suggests e-vendors that employ advanced data protection and secured access will successfully increase consumers’ readiness to use online payment systems and reduce consumer privacy concerns.
Security threats are also a leading hurdle in the growth of e-commerce. Forrester Research found that the primary reason for young buyers (59%) not conducting online transactions was their concern about using credit cards for online transactions (McQuivey & Ham, 2000). Their study revealed a very small fraction of participants, only 10%, felt the risk associated with online transactions was little to none. Kim et al. (2008) and Gurung’s (2016) study identified similar findings. They posit enhanced security, has a positive and significant effect on consumers’ intention to purchase online. consumers were more trusting of e-vendors online payment systems when security mechanisms were implemented. Online companies need to ensure financial and personal information is protected from unauthorized third party’s or persons with fraudulent intentions. This assurance will increase consumers’ sense of security, when conducting financial transactions.
The following researchers, Bart et al. (2005); Dolatabadi; Kim et al. (2008) and Ebrahimi (2010) all found perceived privacy or security had a significant impact on consumers’ online trust. When comparing the literature, it appears the effect of security on consumer’s trust in e-vendors is stronger than the effect of privacy. However, the studies reviewed examined different demographics, which could account for the variation in the extent consumers perceived privacy and security. The studies suggest optimum use of e-commerce can be reached through taking both privacy and security into consideration. In contrast, opposing studies do not find a significant impact of security (Lee and Turban, 2001) or privacy (Gurung et al. 2008) in online trust, and posit other unidentified variables are influencers.
All of the preceding studies conclude online transactions are still an uncertain avenue for some shoppers, that find comfort in exchanging cash in hand or inserting their credit card into a machine. For some of these individuals online transaction complexity and anonymity make conditions more uncertain, triggering privacy and security concerns. Thus, for e-vendors to maintain a competitive edge over traditional retailers, they must provide consumers with a high level of transaction security and data protection services. Trust can be gained by meeting consumer needs, assuring that information is only shared amongst authorised persons. In addition, implementing security measures such as authentication methods (e.g IDs and passwords) will minimise the risk of online shopping and therefore remove uncertainty (Ratnasingam, 2005). Kyösti et al, (2006) add protection against malware, spyware, spam and other attacks are also critical to increase sing users’ sense of security.
In spite of the general agreement among researchers that privacy and security are key determinants of online trust the academic literature still presents inconsistent findings about the conceptualization of privacy and security and their effects on online trust. Belanger et al. (2002), cite privacy and security should be theorised as distinct variables. It is appropriate for privacy and security to signify two distinct constructs, researchers clustering them into one dimension may account for some of the inconsistences across research. Studies that have considered these factors as distinct constructs have examined their effect in separate investigations (Jarvenpaa et al., 2000; Pavlou, 2002; Riquelme and Roman, 2014). This demonstrates a lack of understanding of how privacy and security are related to each other. It is important to study the influence of both factors and their effects together to gain insights on their combined effects and interactions. This study attempts to provide a delineation of the impact of privacy and security concerns as two distinct constructs. In addition, their relation to each other and combined effect on trust is examined by integrating these factors in a single study. In doing so the technology acceptance model is adopted. This is explained in the section that follows.
2.4 Technology Acceptance Model (TAM) and ecommerce
Scholars concerned with reasons for information technology acceptance proposed multiple theories which analysed user’s behavioural intentions towards systems. Fishbein and Ajzen, (1975) proposed Theory of reasoned action (TRA) a social psychology construct which theorises an individual’s action is a function of their behavioural intention. The theory of planned behaviour (TPB) (Ajzen, 1988) is considered an extension of the TRA with an addition of perceived behavioural control. It posits that behavioural intention is jointly determined by the individuals attitude.
An alternative theory base for explaining intention to use is the renowned technology acceptance model TAM (Davis, 1989), which makes considerate adjustments to TRA and TPB. TAM posits perceived ease of use (PEOU) and perceived usefulness (PU) are the major determinants of information system acceptance, as they influence an individual’s behavioural intention to use a particular technology. PEOU is defined as “the degree to which the prospective user expects the target system to be free of effort’’. Perceived usefulness is defined as “the prospective user’s subjective probability that using a specific application system will increase his or her job performance within an organizational context” (Davis, 1989). The model also posits PU and attitude predict the individual’s behavioural intention to use the IT and that PEOU mostly influences intention to use through its effect on PU (Davis, 1989). This could be due to users directly relating PU to the primary envisioned outcome of using the IT. Lastly, behavioural intention is expected to lead to actual usage of an information system.
TAM is a robust model that offers an explanation of the factors of technology acceptance and is capable of explaining consumer behaviours across a wide variety of technologies. Prior technology acceptance studies validate the model empirically (Mathieson, 1991; Venkatesh, 2000; Davis, 1996). As its constructs are theoretically justified and applicable to e-commerce acceptance TAM is the most suitable theoretical model for this study. The effect of PEOU and PU directly on behavioural intention will not be investigated as the concept has been widely studied and cohesively understood by scholars.
2.5 TAM and trust
Given that a web site is both an information technology and the platform through which consumers and e-vendors communicate with, it makes sense that trust pre requisites and technology based antecedents both influence consumers decision to accept e-commerce (Pennanen et al, 2008). Gefen et al., (2003) proposed a modified TAM that integrates trust, and excludes the original attitude constructs arguing a large portion of the variance for behavioural intention and actual IT usage can be explained by PEOU and PU alone.
Extensive research has shown consumer trust is as important to e-commerce as the TAM antecedents. Gefen et al., (2003) investigate and integrate specific trust-based antecedents into the TAM. The study examines the effect of trust antecedents on consumers who had prior continuous experience with an e-vendor. Shortly after Gefen et. al (2003) conduct a study that expands TAM to include familiarity and disposition to trust components. Both studies concluded trust increased PU of a web site. PU is dependent on the web sites technological effectiveness. However, the study determines when the e-vendor is viewed as trustworthy the web site is more beneficial, thus PU is also dependent on trust.
It is vital to take into consideration that the importance of consumer trust, PU and PEOU change with experience. Gefen et al. (2003) found experienced consumers not only trusted e-vendors more than inexperienced consumers but perceived the website to be easier to use as well as more useful. Initially, whether a business or person can be trusted is dependent on an individual’s disposition to trust. Inexperienced consumers have little else to base trust on. However, once a relationship is established and matures disposition diminishes, and trust is influenced by previous interactions (McKnight and Chervany, 2001). Similarly, as users get familiar with a new information technology and grasp more of its capabilities , the relative importance of PU and PEOU will change. Frequent or continued use will increase user’s familiarity with a technology, thus ease of use perceptions also increase due to better understanding of the web site.
Multiple studies discussed argue trust is crucial to starting a B2C relationship. It has been widely researched that trusts influence on PEOU and PU contribute to consumers decision process and is a significant predictors of IT usage (Dolatabadi and Ebrahimi 2010; Gefen 2003; Kim et al. 2008). Therefore, this study will not assess whether trust directly affects the TAM antecedents. However, perceived privacy and security as determining factors for consumer trust, conjoint with TAM constructs have not been widely researched. This identifies a clear gap in subject knowledge. To understand actual usage, it is necessary to examine the effect of trust on behavioural intention with privacy and security as focal trust prerequisites.
The following chapter discusses the theoretical model for this research.
2.6 Research model and hypotheses development
After reviewing related literature, I propose two additional variables: perceived privacy and perceived security to the Trust and TAM (Gefen et al., 2003). Figure 1 represent the modified conceptual model.
Figure 2.1: Effect of perceived privacy and security on trust and behavioural intentions jointly with TAM constructs.
2.6.1 Trust
Based on the literature reviewed in the previous chapter heightened level of trust is associated with heightened behavioural intention and intention to use. According to the trust and familiarity model proposed by Gefen et al. (2003), amongst other factors consumer trust is the product of a disposition to trust others and familiarity with the e-vendor. Disposition to trust is recognised as especially important in the formation of initial trust, that is, trust before any actual interaction occurs. Trust is a significant precursor of participation in e-commerce because of the greater ease with which e-vendors can behave in an opportunistic manner. Accordingly, the following is proposed:
H1: Increased trust will positively influence consumers behavioural intentions
2.6.2 Perceived privacy and security
Similar to Belanger et al. (2002) this research views security and privacy as two different, yet related constructs. In particular, privacy refers to the uncertainty associated with providing personal information on a website and the risk of such information being exposed (Bart et al. 2005). Privacy
issues on the Internet include but are not limited to, usage tracking, spam and the sharing of information with third parties (Riquelme and Román, 2014). Accordingly, in this study perceived privacy refers to consumers’ perceptions about the protection of individually identifiable information on the Internet (Kim et al., 2008). Security, on the other hand, refers to the uncertainty of incurring monetary losses while interacting on a website (Riquelme and Román, 2014). This may happen, for example, as a result of online credit card fraud (Kohli, 2016).
Perceived privacy protection on the website helps to reduce consumers’ perceptions of risk that stems from online disclosure of personal information and thus encourage online transaction by increasing the perceived trustworthiness of the website (Gurung et al. 2008). Several previous studies. A substantial body of research(Bart et al. 2005; Dolatabadi and Ebrahimi 2010; Kim et al. 2008) has already shown that perceived privacy positively influences consumer trust in online transactions. Accordingly, the following is proposed:
H2: A consumers perceived privacy positively contributes to their trust in an e-vendor
the uncertainty of a threat that creates a circumstance, condition, or event with the potential to cause monetary losses. Perceived security, then, refers to consumers’ perceptions about the
Perceived security, then, refers to consumers’ perceptions about the security of the online transaction (i.e., the safety of the payment methods) along with the protection of financial information from unauthorized access (Ruppel et al., 2003). Consumer trust in the online retailer is conceptualized in this study as the consumer’s subjective belief that the e-vendor will fulfil its transactional obligations as the consumer understands them ( Kim et al. 2008).
In order to address consumers’ concerns about the security of online transactions, online retailers employ several security enforcement principles, such as encryption, protection, verification
and authentication (Riquelme and Román, 2014). These mechanisms protect consumer data from being viewed or modified and ensure that only the appropriate entities (e.g., vendor, credit
card authorizer – visa, bank) have access to consumer data. Consumer perceptions of these security enforcement principles positively contribute to their trusting perceptions regarding online transactions. Kim et al. 2008 previously concluded perceived security has a positive influence on online trust, and the effect is in fact stronger than that of privacy. Accordingly, the following is proposed:
H3: A consumers perceived security positively contributes to their trust in an e-vendor
Although privacy and security are accepted to be two clearly distinct constructs, there is strong evidence that they interactively influence each other (Belanger et al. 2002; Schlosser et al.
2006; Hu et al. 2010). For example, a high concern for personal privacy would directly produce negative attitudes toward web security, and consumers who lack knowledge about online security and the third-party security identification would worry about disclosing personal information during the process of online shopping. Accordingly, the following is proposed:
H4: Perceived privacy is positively correlated to perceived security
The literature reviewed has provided insight and understanding into studies already completed on trust in an e-commerce environment and its determining factors. Conclusions proposed by scholars assisted in forming the hypotheses of this study.
3. Research Methodology
This chapter presents the methodology of this research. The research approach and strategy is described. Following this, the method for data collection and analysis, sampling and questionnaire design are explained. Finally, validity, reliability and generalisability are discussed.
3.1 Research strategy
The type of research being conducted is analytical as it aims to evaluate and explain how perceived privacy and security affect consumer trust in e-vedors. The quantitative approach to research concentrates attention on a limited number of variables and allows the researcher to examine the relationship between said variables. As this research also attempts to identify if there is a relationship between the determining factors, quantitative techniques were chosen to collect, analyse and summarise the data.
Quantitative research is more commonly associated with a deductive approach and quantifies a problem by generating numerical data or data that can be converted into usable statistics (Saunders and Thornhill, 2009). Deductive research moves from existing general theories which are tested to deduce a particular conclusion. The objective of quantitative research is to quantify the behaviours, opinions, and theories of usually a larger sample population. As such, in retrospect this approach was the most suitable, to collect participants opinions and beliefs in e-commerce. The data produced from quantitative methods is measurable and can be in any type of numerical form. This allows the data to be analysed to expose patterns that can be generalised to some larger population (Glesne, 2011). Quantitative methods are very structured and produce reliable data, however, there are limitations. One of which is, the research will not provide reasoning behind participants’ responses (Diriwächter and Valsiner, 2006).
Based on this study’s characteristics a questionnaire is be used to collect data from a sample of individuals that may or may not participate in online retailing. To limit time and costs an online questionnaire is used for this survey. This method allows useful standardised data to be collected quickly for easy comparison (Saunders and Thornhill, 2009). The questionnaire contains a list of carefully constructed questions that collect participants feelings and opinions of privacy and security in relation to e-commerce. 100+ participants were anticipated; however, 67 valid questionnaires were collected. Some responses collected were incomplete or did not fit the sample requirements which contributed to the shortfall.
3.2 Data collection and analysis
As previously mentioned, based on the research aims and objective, quantitative techniques are used to collect primary data in the form of a questionnaire. The questionnaire designed in Qualtrics consists of closed questions specifically scale and category types, to assess the behaviour and opinion of consumers. Mutually exclusive responses were used where appreciate. For example, the age category consisted of three groups 18 or below, 19-32 and 33 or above. These options mitigate the chance for confusion. The questions focus on how the identified determined factors affect consumers’ level of trust and in turn behavioural intention. Raw data is produced that is directly relevant to the research topic.
Secondary data such as published journals, books and articles on consumer trust in e-commerce environments are used to help interpret and support the primary data. Secondary data is easy to access and increases ones understating of related research.
This study uses the software SPSS to conduct statistical analysis. The type of data produced from the questionnaire is multivariate and is analysed using quantitative measures. First SPSS is used to provide descriptive statistical analysis of the data. Then, Spearman’s Correlation Coefficient is used to investigate the relationship between perceived privacy, perceived security, trust and behavioural intention. Linear regression tests are then used to quantify the relationship between perceived privacy, perceived security and trust. To avoid data quality issues, all the questionnaires distributed will be exactly the same, with questions that reflect the research aim.
3.3 Questionnaire design
The questionnaire (Appendix 1) design consisted of five sections: Personal information (PI), behavioural intention (BI), trust (TRU), privacy (PRI) and security (SEC). Validated measures for BI, TRU, PRI and SEC were adopted from Riquelme and Román (2014) and Gefen et al. (2003).
Section 1 consisted of three questions to collect respondents’ personal information (PI) (i.e., gender, age group,) and one question to asses consumer attitude towards e-commerce. This data was used to filter valid from non -valid responses in relation to the selected study sample. Section 2 consisted of three questions intended to measure behavioural intention and actual usage of e-commerce. These questions were designed to collect information on intention to purchase, intention to continue online purchasing and frequency of online purchases. Section 3 consisted of four questions intended to measure variables related to consumers’ trust in e-vendors. Section 4 consisted of three questions intended to measure variables related to privacy perceptions. Section 5 consisted of three questions intended to measure variables related to security perceptions. Questions in sections 3-5 collected information related to trustworthiness of e- vendors, attitudes towards privacy of personal data online and security of online transaction processing systems.
Category items were used to collect data for PI 1-3, as gender, sex and residency are attribute variables. All the other questions required respondent’s opinion. To collect this data in a quantitative manner rating questions are often used (Saunders and Thornhill, 2009). The items in section 2 to 5 were set in a seven point Likert scale with endpoints ranging from 1 (strongly agree) to 7 (strongly disagree). The questionnaire consists of closed questions only. Respondents were given a number of alternative answers from which the could chose the most applicable. This method meant the answers are predetermined making them easier to compare. In addition, closed questions are quicker and easier for respondents to answer as they do not require the respondent to create an answer or write additional responses.
An official pilot test was not conducted. However, a draft of the questionnaire was analysed and approved by Professor Niki Panteli, an established published author in the field.
3.4 Sampling for Questionnaire
The study aims at investigating millennials’ trust in B2C web sites in the UK. Therefore, the population of interest is all UK millennial consumers that have access to e-commerce. In this study millennials are defined as any person born between the years 1986 – 1999, and currently between the ages 19-to-32. In 2017, there was an estimated total of 12 million people between ages of 19 and 32 in the United Kingdom (Statista, 2018). As the population is vast and dispersed, this research studies a sample of those individuals in order to draw valid conclusions about the opinions of a larger population. It is challenging to produce an unbiased, representative sample. Consequently, this project will use convenience snowballing sampling. The questionnaire is distributed by an anonymous link posted on the social platforms Whatsapp and Facebook. To increase the sample diversity and size, as directed the link was further distributed by participants to their contacts. There will always be sampling error or variation due to sampling as only part of the population is being studied.
3.5 Validity, generalisability and reliability
Validity is “concerned with whether the findings are really about what they appear to be about” (Saunders et al., 2007, p.150). Constructing questions specific to the research and entirely understandable to participants is challenging. A pilot study was not conducted which may affect the validity of this research. However, the findings of this research are believed to be valid and credible, as the method being used to evaluate perceived privacy and security as determining factors for users’ level of trust in e-vendors are specifically tailored to unbiasedly measure said constructs.
Generalisability is defined as an ability to generalise research results to a bigger population (Saunders, et al.,2009). Most qualitative research such as this study, investigate a specific subject in a particular group or population, hence generalisability is not usually not a likely attribute. However, similar literature reviewed suggests if there is a positive correlation between the identified determining factors and trust in e-vendors, the data collected is valid and can be generalised beyond this study to some degree.
Reliability is defined as “the extent to which your data collection techniques or analysis procedures will yield consistent findings” (Saunders et al., 2007, p.150). This study investigates online transaction services. As Web-based services continue to develop it is likely consumers perception of privacy and security in regard to the e-environment will change. Multiple researchers reviewed in the previous chapter (Literature review) have investigated similar aims and deduced similar results to each other. In addition, all participants of the questionnaire complete it with an anonymous link. This reduces the likelihood of untruthful answers and thus, strengthens the reliability of the data. Currently, the findings of this research are repeatable and therefore reliable.
3.6 Ethical Aspect
As the questionnaire will be distributed online it is difficult to ensure all participants are of a reasonable age, however, the questions will not deal with particularly sensitive issues and is low risk. The aim of this project will not be disclosed on the questionnaire, but the subject area will. All participants have the option to withdrawal at any time. To ensure privacy all respondents will remain anonymous and personal details will not be shared.
4. Data Analysis and Discussion
In this chapter, the data from the questionnaire is analysed. Results from test run in SPSS statistics software are presented and explained. The chapter ends with a discussion of the results.
| Code | Item | Strongly agree Strongly disagree |
| PI4 | I have a positive attitude towards using the internet, to purchase products/services | 1 2 3 4 5 6 7 |
| Assessing the e-vendor | ||
| BI1 | I intend to make purchases online often | 1 2 3 4 5 6 7 |
| BI2 | I make purchases online often | 1 2 3 4 5 6 7 |
| BI3 | I intend to continue purchasing products/services online | 1 2 3 4 5 6 7 |
| TRU1 | I would use my credit/debit card to purchase online | 1 2 3 4 5 6 7 |
| TRU2 | Even if not monitored I trust online businesses to do the job right | 1 2 3 4 5 6 7 |
| TRU3 | Online businesses are trustworthy | 1 2 3 4 5 6 7 |
| TRU4 | I am certain what to expect from online businesses | 1 2 3 4 5 6 7 |
| PRI1 | I am not concerned that online businesses will use my personal information for other purposes without my authorization | 1 2 3 4 5 6 7 |
| PR2 | I am not concerned about the privacy of my personal and financial information during a transaction | 1 2 3 4 5 6 7 |
| PR3 | I believe my personal and financial information will not be shared with other entities without my authorization | 1 2 3 4 5 6 7 |
| SEC1 | Online businesses have sufficient technical capacity to ensure secure payment systems | 1 2 3 4 5 6 7 |
| SEC2 | Online businesses have enough security measures to protect my personal and financial information | 1 2 3 4 5 6 7 |
| SEC2 | I am sure my personal data will not be intercepted by unauthorised third parties | 1 2 3 4 5 6 7 |
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