G.R. Boer s1916963 28-12-2011
Supervisor: Dr. Ig. M.C. Achterkamp Second supervisor: Dr. D. Trampe Faculty of Economics and Business University of Groningen
The influence of user-experience and price on perceived credibility in an
online shopping environment.
ABSTRACT
This research examines how consumer perceive an e-vendors’ website in terms of credibility and includes factors as; user-experience, price and trust-assuring factors. It tests theories from prior research, which predominantly focused on the variables in an offline environment.
The main findings are that whenever there is an increase in price the perceived credibility declines. Whenever trust-assuring factors are available on the e-vendors’ website, the perceived credibility significantly increases.
Furthermore, the extent to which consumers are experienced in conducting e-commerce did not proof to have a significant moderating role in the relationship between the trust-assuring factors and perceived credibility. However, the level of user-experience did have a significant moderating effect on the relationship between price-level and the perception of credibility. Indicating that the negative effect of a higher price on perceived credibility is smaller whenever user-experience in higher, in contrast to when user-experience is lower.
Moreover, the level of user-experience does not have a direct effect on the way consumers perceive the credibility of an e-vendor.
TABLE OF CONTENTS 1. Introduction 4 1.1 Trust 4 1.2 Shopping online 5 1.3 User-experience 6 1.4 Price 6 1.5 Trust-assuring factors 6 1.6 Research question 7 2. Theoretical underpinnings 8
2.1 Earlier research on trust 9
2.1.1 Measurements of trust 10 2.1.2 Credibility 14 2.2 User-experience 14 2.3 Trust-assuring factors 16 2.4 Risk 18 2.5 Intent to purchase 19 2.6 Conceptual model 20 3. Research design 21 3.1 Methodology 21 3.1.1 Participants 21 3.1.2 Sampling methods 21 3.1.3 Experimental procedures 22 3.1.4 Experimental design 23
3.2 Design of the questionnaires 25
3.3 Data analysis 26 4. Results 28 4.1 Descriptive results 28 4.2 Main results 29 5. Discussion 34 5.1 Conclusion 37
6. Recommendations for further research 39
1. INTRODUCTION
Electronic commerce (E-commerce) is growing at a staggering rate. Ever since the beginning of the Internet, E-commerce has shown an increase in revenue. According to the Economist, electronic commerce around 1996 accounted for $500 to $600 million in global revenue. Nowadays, e-commerce accounts for more than $600 billion dollars and is expected to grow over the years to come (J.P. Morgen, 2011).
Despite this tremendous growth in global revenue over the last ten to fifteen years, E-commerce entails a range of debates. One of the main discussions regarding electronic commerce is about consumer trust in an online retail environment. Consumers’ trust in an online retail environment refers to the willingness to engage in an Internet shopping transaction with an online vendor / Internet store (McKnight et al, 2002).
Several scholars have examined the relationship between trust and the intent to buy in an online environment. Gefen (2000) found that trust was a worthy indicator of a consumers’ intent to purchase. Moreover, according to the empirical research by Ku et al. (2002), trust has an important effect on the consumer intention to buy in an online setting. In which they find that whenever trust increases, so does the intention to purchase. This was also in line with the findings of Doney and Cannon (1997).
Therefore, understanding the process of how consumers build trust online can be of high value for every e-vendor. With an increased understanding of the process, e-vendors will be better able to adjust their online shopping environment to the needs and wishes of their customers.
During the review of existing literature it became clear that whenever these relationships were tested, they were not tested in an online shopping environment. Hence, to elaborate on prior research this research will emphasize on the perceived credibility of an e-vendor from a consumers’ perspective. Moreover, it will delve into important elements that consumers are confronted with when intending to shop in an online environment and that are likely to have an effect on the process.
1.1 Trust
According to the findings of Egger (2000), ‘difficult use and lack of trust with respect to online payment, privacy and customer service have been found to constitute a real psychological barrier to E-commerce’. Trust is of critical importance when it comes to motivating initial purchases over the Internet, as well as during the online payment process (Reichheld & Schefter, 2000). Moreover, lack of trust has been identified as a major obstacle to consumer acceptance of E-ecommerce by Kivijärvi et al. (2007), stating that consumers are worried about theft of their identity and transaction fraud. Clearly, trust is an important factor determining whether or not consumers will consider making a purchase at a particular online vendor. However, creating consumer-trust on the Internet is facing difficulties through a variety of factors; for example, the increasing stories about Internet frauds keep raising questions about the trustworthiness of E-commerce (Economist, 2001). Additionally, strong factors that influence online shoppers are fears about risk, and online security (Parasuraman & Zinkhan, 2002).
Building consumer trust in an online shopping environment is therefore of critical importance for online businesses. Several scholars found that by building trust, online businesses can significantly stimulate the willingness of customers to make purchases in an E-commerce environment (MacInnes, 2005; Saini and Johnson, 2005).
1.2 Shopping online
Theory defines two stages in the online shopping process. During the exploratory-stage ‘the user has not yet directly experienced a specific web site and is still trying to decide whether or not to explore the web site to see what it offers. Trusting intention at this stage, therefore, refers to the willingness to pursue the experience, that is, to explore the web site further’.
During the commitment-stage ‘the user interacts with the vendor through the web site and must decide “Shall I do business with this vendor?” Deciding to do business (trusting intention) may include intent to purchase the product and/or to exchange personal information with the vendor’ (Mayer et al. 1995).
1.3 User-experience
Within this commitment-stage of the online shopping process user-experience can have an influence on the way consumer are processing the website, after all experience tends to make things more familiar. ‘Familiarity is a precondition for trust, and trust is prerequisite of social behavior, especially with regards to important decisions’ (Luhman, 1979). Clearly, at the time this statement was made electronic commerce was far from operational. Nevertheless, it seems plausible that it holds for online shopping as well. The difference in user-experience might play an important role in the way consumers perceive a website; this might also include the way consumers build their trust in an online vendor.
However, the level of consumer-experience in relationship with the way a consumer perceives an online vendor and builds its trust is a topic hardly dealt with in literature.
1.4 Price
Another factor that is likely to have an effect on the trust building process of consumers while shopping online is price. Nowadays, almost everything is for sale online resulting in major price differences between the different goods and services sold over the Internet. It does not seem odd that when buying a t-shirt online other trust-assuring factors come into play then when shopping for a LED-television. In relation to that, Beatty et al. (1987) found that consumers are likely to search for more information when the price of a product or service is relatively high.
Besides, ‘price is closely related to perceived risk, which refers to customers’ perception of the uncertainty and the adverse consequences of purchasing a product and/or service’ (Dowling & Staeling, 1997). This relates to the fact that when uncertainty is meeting a certain threshold the customer is likely to abandon the website and to do his/her purchase elsewhere.
1.5 Trust-assuring factors
This wide range of trust-assuring factors can play a distinctive role in a business-to-consumer online shopping environment, but until now have barely been experimentally tested.
1.6 Research question
What makes this research different from earlier research is that it combines the issue of perceived credibility on the Internet with two additional factors. Previous research showed that the two additional factors showed to have a close relationship with trust (building), being; user-experience and price.
Based on the mentioned variables, the following research question will be examined in this paper; does the price level of a product and/or trust-assuring factors influence the consumer-perception of credibility and to what extent does user-experience moderates this process?
The outcomes of this research will broaden the understanding of the online shopping process, and will particularly be useful for online vendors aiming to increase the intent to purchase of their potential customers.
2. THEORETICAL UNDERPINNINGS
This research has both a theoretical and an experimental nature. In the following part the variables playing a key role in this research will be discussed in terms of previous research and their possible relationships. The conceptual model (figure 1.) displays all the variables and transforms the research question at stake into a graphical representation.
When having a closer look at the formulated research question, it is expected that whenever the price level of a product rises, consumers are likely to have a closer look at the e-vendor (website) in terms of its credibility.
Moreover, user-experience might have its effect on this relationship. Whenever a user is more experienced in buying products and/or services over the Internet he/she might feel more comfortable in doing so and therefore less focused on certain trust-elements in contrast to less-experienced consumers. This might also work the other way around, because of the fact that consumers are more experienced they know what to look for, when it comes to credibility. Hence, whenever certain elements are not available they might decide to move away from their intent to purchase.
The question is, does the consumer trust the e-vendor enough in order to move from an ‘intent to purchase’ to an actual purchase. Therefore, from the viewpoint of the consumer, the e-vendor has to meet a certain level of perceived credibility in order to gain (online) trust. This also emphasizes the close bond between trust and credibility.
External Factor: Perception of:
Trust-assuring factors
User-experience Credibility
Online-trust Intent to purchase
2.1 EARIER RESEARCH ON TRUST
One could state that trust can occur in a wide variety of dimensions. Due to the fact that credibility is one the dimensions of trust, and is the dependent variable of this study, this part will delve into some of the earlier research performed on trust in general.
The issue of trust can come into play in the widest variety of events. For instance, over the phone, in a private setting, during a business meeting, et cetera. This might well be the reason that, over time, theorists have defined trust in many different ways. Within marketing literature trust is mostly defined in way in which it describes the relationship between businesses and consumers, and acts as a key component of this relationship. According to Czpiel (1990), trust has the ability to facilitate relationships and to make them evolve over time. Moreover, he states that by taking the customer’s best interest at heart it increases sales.
Clearly, there is much more to say about in an offline environment, as it has been a topic for research for decennia’s long. Nonetheless, reviewing the wide-ranging literature on offline trust is beyond the scope and time limitations of this paper.
Online-trust on the other hand is a key variable of this research, and will therefore be discussed into more depth. Online-trust is different in many ways from its offline equivalent. With regards to a shopping environment, probably the largest difference between a bricks-and-mortar store and an online store are the physical benefits that the former has opposed to the latter. This means that trust needs to be solely built on the interaction that the customer has on the e-vendors’ website. Therefore, one can state that trust in electronic commerce is (mostly) impersonal in nature compared to the traditional way of building (offline) trust (Culnan and Armstrong, 1999). In order to limit the scope of this research, this paper will focus on e-vendors that are merely operating online and do not have bricks-and-mortar stores.
Additionally, this paper focused on the commitment-stage of trust, in which consumers are deciding whether or not to do business with a certain vendor.
This means that during this stage consumers are actively processing the intent to purchase, in which factors like price and user-experience are expected to play an influencing role.
In the definition of Corritore et al. this stage of the process could be explained as; ‘…the risk that one’s vulnerabilities will not be exploited’.
Apart from the research conducted by Corritore et al., the vast majority of prior research focused on building trust in the offline environment. This is not remarkable since many scholars identified trust as a vital variable with regards to ‘the intent to purchase’ (Kivijärvi et al., 2007; Morgan and Hunt, 1990; Reichheld and Schefter, 2000). Clearly, the need for building trust online from the e-vendor’s perspective is crucial for its long-term success, as theory shows that without meeting a certain level of (offline) trust, the intent to purchase will decline.
For example, Hampton-Sosa et al. (2004) performed a questionnaire-based field-study in which they found that giving consumers the possibility to customize their products or services online it increases trust. Likewise, their empirical research showed that perceived company reputation, especially with regards to a bricks-and-mortar store of the company, could significantly affect initial online-trust. Perceived reputation from previous visits to the website or based on visits to a shop in the offline environment appear to play an important role in the trust building process. However, many research papers investigating online-trust use existing websites and/or companies as a foundation, which makes it impossible to deny the possible influence of perceived reputation. This research used fictional e-vendors in order to exclude the likeliness of influence by perceived reputation and previous store visits. Reason for doing so, is to maintain an unbiased focus on the factors at hand, being; price, user-experience, trust and intent to purchase. Moreover, there are many e-vendors that solely have an online presence and are unable to use reputation from the offline environment.
2.1.1. MEASUREMENTS OF TRUST
Mayer et al. (1995) conceptualized trust by means of an extensive literature research, in which they focused on trust in an organizational setting.
Even though, this might not seem directly related to the research question dealt with in this paper, the first part of their proposed conceptual model does seem relevant to address.
Mayer et al. mention the antecedents of trust, which they captured in a framework of ‘factors of perceived trustworthiness’ (Figure 2.).
First of all, they state that trust evolves out of antecedents which they define as; ability, benevolence and integrity.
Ability refers to a group of skills that enable a person to have influence within a specific domain. With regards to an online shopping environment this does not directly have a relationship. However, ‘internet-skills’ of the customer might make a difference in the way they perceive trust, but it is not likely that they will give the consumer a certain degree of skills that they will become able to influence the shopping domain. Therefore, this might be an interesting antecedent, but the current definition does not hold for the online environment.
Factor of Perceived Trustworthiness
Figure 2. (Antecedents of trust).
Benevolence covers the extent to which ‘the trustee is believed to want to do good to the trustor, aside from an egocentric profit motive’. When transferring this to online shopping environment, it could well be seen as the overall appearance of an e-vendors’ website. To what extent does the e-vendor portray a honest/reliable image?
The last antecedent of trust, which Mayer et al. defined, is ‘Integrity’. With integrity the focus is on whether or not the words of the trustee are congruent with its actions. With regards to an e-vendor (trustee), this could be the return-policy that is mentioned on the website and that he needs to live up to in order to maintain its integrity. Although, this is an interesting topic for discussion, it fell beyond the scope of this research.
Integrity Benevolence
Ability
Reason for this was, that this research focused on the commitment-stage of the online shopping process, an actual evaluation of promises made would include the ‘after-sales-stage’.
Mayer et al. gathered antecedent factors of trust, such as; openness, past interactions and competence, which they subsequently grouped into the three previously mentioned antecedents of trust which altogether determined the level of trust in an organizational setting.
Whereas Mayer et al. discussed the antecedents of trust in an organizational setting; Corritore et al. (2003) proposed a model, which presented three perceptual factors that impact on online-trust. The model covers online-trust between users and websites. In line with Mayer et al. this model also originates from literature. Additionally, the model has been tested in an experiment in a controlled setting (Chandran et al., 2005).
The model (figure 3.) divides trust into three perceptual factors that directly impact online-trust. The first defined factor is credibility, which, according to earlier research, can be subdivided into three dimensions. The three main dimensions of credibility that could be subtracted from earlier research are; reliability, honesty and competence (Earle et al. 2010; Patton, 1999; Silva et al. 2002) these will be discussed further in the next subchapter.
Figure 3. (Model of online-trust).
The second perceptual factor of online-trust, as defined by Corritore et al., is the ‘ease of use’. Ease of use is described as how simple the website is to use, e.g. how simple is it to navigate the website? With regards to this research, ease of use of the website is a factor which will not be included due to limitations in time and tools available.
As this research will investigate whether there is a relationship between the price-level of a product and the perception of online-trust, the perception of risk might well be playing an important role. Several studies found that price has a direct effect on risk in an offline environment (Dowling & Staeling, 1997; Dodds et al.,1991). Nevertheless, this has not been investigated in an online environment with regards to building trust. Therefore, this research elaborates on the model of Corritore et al., and includes price as a substitute for risk (figure 1.), in order to gather more specific results.
The three perceptual factors discussed above, can on their turn be affected by external factors. These external factors can consist of characteristics of the trustor, in this case the customer, or out of characteristics of the object of trust, in this case the e-vendor. The degree of experience with a comparable situation, and the experience with web technology are characteristics of the customer that could directly influence the perception of trust factors, and subsequently the overall trust in an e-vendor (McKnight and Chervany, 2002). However, of the studies conducted this far, most of them focused on the features of the website, such as navigational architecture, or interface design, and are likely to be outdated, as the internet has undergone major changes over the last ten to fifteen years (Kim and Moon, 1997; Milne and Boza, 1999).
Corritore at al.’s model shows an overlap with the variables addressed in this research. The degree of user-experience could be perceived as the external factor, the price-level as the perceptual risk factor and the trust-assuring factors (Table 1.) can be part of determining perceived credibility.
Nonetheless, the research did not include a manipulated fixed variable such as price-level and it included ‘reputation’ as they made use of existing websites.
Additionally, the conceptual model addresses online-trust at an abstract instead of an operational level, which grants the possibility to use it in a wider variety of contexts.
On the other hand, Corritore et al.’s model does proof that credibility can be perceived as a key factor when it comes to building online trust. One can understand that the term trust is a very broad term and does not, in itself, narrow down to the essence of this research. However, prior research by Corritore at al. shows that (perceived) credibility can be seen as an important element of trust. This grants the opportunity to become more specific and to narrow down to a particular element of trust, which is in line with the scope of this research.
2.1.2 CREDIBILITY
Marketing literature defines two different types of trust. First there is benevolence, which is mainly affected by familiarity, and experience in a certain action. Second there is credibility. Credibility focuses on the expectation that the trustee (e-vendor) is a reliable source and whether it can accurately fulfill promises made. In other words, the belief of the consumer that the e-vendor is reliable, honest and competent (Earle et al. 2010; Patton, 1999; Silva et al. 2002), and is able to meet a certain amount of trust which sustains/increases the intent to buy. These three dimensions taken together make it possible to measure credibility.
Moreover, credibility is a type of trust, which is mainly impersonal and depends on information, experience and economic reasoning (Doney and Canon, 1997; Ganesan S. 1994), which is in line with shopping in an online environment. Whenever one or more of the three dimensions is lacking or not meeting a certain level of expectation, from the consumers’ point of view, it is likely that this will have its effect on the trust that consumers have in the particular e-vendor. Subsequently, a decrease in trust is expected to lead to a direct decrease in intent to buy. This allows the perception of credibility to fulfill the central (dependent) role in this research.
2.2 USER-EXPERIENCE
As mentioned earlier, the effect of user-experience on online-trust is a topic hardly dealt with in literature. Additionally, this research goes into more depth as it focuses on a specific element of trust, being perceived credibility, which is on its turn sub-divided as well.
User-experience in this paper refers to the degree of experience a customer has in shopping online. For instance, did the customer do any shopping online before taking part in this research?
On the other hand, it might also be that the customer is well experienced in the online shopping process but never bought anything from an e-vendor due to a variety of reasons, e.g. trust-issues.
Finally, Hoffman et al. (1999) found that the level of consumer concerns decreases with an increase in experience.
They state that; ‘consumer concerns over control of personal information actually decreases with Internet experience’, and find that 70 per cent of newcomers are concerned about credit card theft in contrast to 46 per cent of the more experienced users. This might seem logical, as more experience in general leads to lower concerns. However, the research does not exclude the fact that it might also work the other way around in which higher user-experience will lead to a higher degree of awareness of risk. Which subsequently leads to a lower intent to buy when an e-vendors’ credibility is low.
Based on these earlier findings it is expected that whenever the level of user-experience increases, the level of perceived credibility increases with it. For example, familiarity with the process of shopping online is likely to increase (online) trust. Also, the decline in concerns whenever the user-experience increases leads us to the following hypothesis to address;
H1: Among consumers with prior user-experience in conducting e-commerce there will be a higher level of perceived credibility.
Due to the scarce findings on the effect of user-experience on the perception of credibility, the outcome of this hypothesis will broaden the existing knowledge of its effect.
2.3 TRUST-ASSURING FACTORS
Apart from measuring credibility based on the three dimensions discussed above, theory defines additional factors that can be closely related to (building) credibility.
Theory defined many more factors that can increase credibility of an online shopping environment, such as number of pages that consumers need to go through before making the actual payment.
However, due to methodological reasons only factors that are displayed on one page of the website are included. In this case the page on which the product at stake was displayed (Appendices 1a-d).
Seals of Approval Testimonials User-Reviews Contact Opportunities Visa, MasterCard Guarantee
information Product-Reviews User-requested Chat seals of approval Shipping information Shop-Reviews Contact Information and product support Third-party payment
system
Table 1. Trust-assuring Factors
The trust-assuring factors are divided into four separate groups, and are defined by a variety of prior researches. Not all of the trust-assuring factors are likely to be provided directly on the landing-page but the availability of links to this information increases the trustworthiness of an e-vendor (Bradley S. 2011; Cheskin, 1999 and Hoffman et al. 1999).
This research paper addresses these, in theory defined, trust-assuring factors and examines them in a business-to-consumer setting in an online shopping environment. As prior research found, the trust-assuring factors are likely to enhance the perceived credibility of an e-vendor. Therefore, the following hypothesis is constructed;
H2: The availability of trust-assuring factors on the e-vendors’ website will have a positive influence on the perceived credibility of the consumers.
However, prior research predominantly focused on trust in general, whereas this study focuses on particular trust-assuring factors and narrowed down on trust, which led to credibility. Yet, the following hypotheses was formulated:
H3: Among consumers with prior user-experience in conducting e-commerce there will be a lower need for trust-assuring factors.
2.4 RISK
It does not require a rocket scientist to understand that the price level of a product will undoubtedly have its effect on consumer-decision making. Beatty et al. (1987) showed in their study that whenever the price of a product rises, consumer tend to search for more information before making the purchase. This could be explained as the need for increased credibility, due to an increase in risk, by ‘searching’ for more trust-assuring factors afore making the purchase. In line with these findings is the study of Dowling & Staelin (1994), which empirically tested the hypothesis and indicated that ‘the intended use of risk-handling activity increases with higher price levels.’ ‘Risk-handling activities’ could be explained as the need for credibility, or at least the search for some form of trust that decreases the feeling of risk.
Extending the view of Beatty et al., an experiment-based study of perceived risk (Gotlieb et al., 1994) showed that the price of a product affects consumers’ perception of risk.
Furthermore, the paper suggests that ‘the influence of price on consumers’ perception of risk is greater when the credibility of the source is low’. When relating this to the conceptual model proposed in figure 4, the findings of Gotlieb et al. (1994) claims that there is a direct one-sided relationship between the two factors, price and credibility.
All of the above mentioned research papers, with regards to the relationship between price and credibility, were conducted in an offline environment in which e-commerce did not fulfill any role.
Whenever the price-level is high, consumers are expected to have a lower perception of credibility then when the price-level is low.
In short this means that, whenever the price-level increases, the perceived credibility decreases. This leads us to the following hypothesis:
H4: A higher level of price leads to a lower perception of credibility.
Furthermore, the study addresses the moderating effect of user-experience on several relationships with credibility. ‘H5’ examines the moderating effect of the level of user-experience on the relationship between the level of price and credibility. Even though past research did not address this effect, due to earlier findings on the effects of user-experience the following hypothesis is constructed:
H5: Among consumers with more user-experience in conducting e-commerce there is a lower effect on the perceived credibility whenever the price is higher.
2.5 INTENT TO PURCHASE
Even though the intent to purchase does not fulfill a central role in this research, the outcomes of this research (Chapter 5) will be closely related to the intent to purchase. For this reason, some of the prior researches on the relationship between trust and the intent to purchase are discussed. Increasing the consumers’ intention to purchase should be one of the main goals of every (e-) vendor. Obviously, by increasing intent to purchase, sales will rise and subsequently the revenue of the e-vendor. There are many factors that influence the process of the intent to purchase from a consumer point of view. One, which is in line with this paper, is the level of credibility that consumers perceive with regards to the selling party.
Whenever there is a low level of trust in a certain e-vendor, the intent to purchase is likely to be negatively influenced. More importantly, the reversed is true as well.
Several scholars have examined the relationship between trust and the intent to buy in an online environment. Gefen (2000) found that trust was a worthy indicator of a consumers’ intent to purchase.
In which they find that whenever trust increases, so does the intention to purchase. This was also in line with the findings of Doney and Cannon (1997).
Therefore, understanding the process of how consumers build trust online can be of high value for every e-vendor. With an increased understanding of the process, e-vendors will be better able to adjust their portal to the needs and wishes of their customers.
2.6 CONCEPTUAL MODEL
By finding answers to the five hypotheses formulated above, this research will be able to find answers to the main research question; ‘does the price level of a product and/or trust-assuring factors influence the consumer-perception of credibility and to what extent does user-experience moderates this process?’.
Figure 4 captures the variables, hypotheses and their expected effects in one graphical representation.
External Factor: Perception of: Trust-assuring factors
H3 (-)
H2 (+) H1 (+)
User-experience Credibility
Online-trust Intent to purchase (H5+) H4 (-)
3. RESEARCH DESIGN 3.1 METHODOLOGY
The purpose of this research is to examine whether the price level of a product influences the consumer-perception of credibility (online trust) and to what extent user-experience influences this process. In order to be able to do so the five constructed hypotheses need to be tested. The consumer-perception will be measured with the assistance of four online questionnaires (Appendices 2a-b). These questionnaires will be distributed amongst four random samples (n30). All four questionnaires will consist out of three components. The first component measures the user-experience, the second component integrates price, and the third and final part focuses on credibility. The questionnaires will be identical, with the exception of the price-level and presence of trust-assuring factors. The participants will be randomly assigned to one of the four questionnaires. When all the participants have completed their questionnaire, a between-participants comparison can be made, meaning that between-participants are allowed to serve in only one experimental condition (one questionnaire). This between-participants design will emphasize on the difference in price-level and on whether or not there were trust-assuring factors present. Moreover, a comparison between the other variables, level of user-experience and the need for credibility, are tested. The results will be displayed in chapter four and discussed in chapter five. 3.1.1 PARTICIPANTS
A total of one hundred and twenty participants were included in this online questionnaire experiment, subdivided in a total of thirty participants per questionnaire. The participants were randomly assigned, and were primarily approached online by e-mail, Facebook, or Twitter. Additionally, participants were approached at public social gatherings, e.g. coffee shops and sport clubs. No incentives were used in order to stimulate participation.
3.1.2. SAMPLING METHODS
This led to the fact that initially the participants originated from a personal network. However, social media has the advantage of a ‘snowballing-effect’, which led to a rapid expansion of that same personal network. In less that one-week time, all one hundred and twenty participants were questioned and the data set was complete and ready for analysis.
3.1.3. EXPERIMENTAL PROCEDURES
A short written introduction to the questionnaire was the beginning of the survey. However, the introduction did no reveal anything about what was going be asked and what the main research topic was about, in order to maintain unbiased response. In other words, the cover story of the questionnaire was limited to revealing the fact that it was an academic research for the University of Groningen. Hence, it did not share its research topic with the participants.
Before answering questions on perceived credibility participants were told in the questionnaire (by means of a text) that they were shopping online for a new mobile phone, and that the one displayed on the website was the one they were looking for. In order to do so, they were to ‘visit’ an Internet store and were asked to indicate to what extent they would prefer to buy the mobile phone at the projected store (Appendices 1a-d). Additionally, they were told that the store was chosen randomly. The e-vendor stores that were used in the questionnaires were created by a professional web designer1 who was aware of the research’ goal, and was profoundly instructed by the researcher.
As mentioned before, there were four questionnaires, which differed in price-level and the presence of trust-assuring factors. One questionnaire included a mock e-vendor, which offered a mobile phone at a low price and without any trust-assuring factors (Appendix 1a). On the other hand, the other questionnaire included the same mock e-vendor offering the same low-priced mobile phone but with all the trust-assuring factors (Appendix 1b).
Furthermore, the other two questionnaires took the same approach, in which only the mobile phone was a different, more expensive model, of the same brand in order to manipulate the price-level (Appendices 1c-d).
A total of thirty participants were included in the low-priced questionnaire version without the trust-assuring factors, another thirty participants in the low-priced questionnaire, but this time with the trust-assuring factors. For the higher-priced version the approach was exactly the same, resulting in a total of one-hundred-and-twenty participants.
The majority of the participants were approached over the Internet with the help of thesis tools2, a website which is specialized in conducting online questionnaires and gathering the data.
Using an online questionnaire is in line with the recommendations of Pitkow and Recker (1995), who suggested lower overheads, ease of use, and reliability as the main advantages of online questionnaires. The respondents received an invitation by e-mail to join a survey. Subsequently, they were redirected to the questionnaire by clicking a hyperlink. After going through all the components of questionnaire, the results were sent to a database by a simple click on a button, and gathered in an Excel-file.
Next to the online approach, some participants were also randomly approached in daily live while being at a social gathering such as a coffee shop or at sport clubs. All of these places were situated in the proximity of the city center of Groningen, the Netherlands.
These participants were asked to fill out the questionnaire on a laptop, which was brought by the researcher. Subsequently, they went through the exact same questionnaires. The reason for doing so was to stimulate the equal probability of selection, since it could not be expected that everyone had an Internet connection. Moreover, this also granted the opportunity to approach less internet-active users, since the majority of invitations to the questionnaires were sent by means of Internet-channels (Facebook, Twitter and e-mail).
3.1.4. EXPERIMENTAL DESIGN
A 2 (low user-experience and high user-experience) x2 (Low price-level and high price-level) x 2 (Without trust-assuring factors and with trust-assuring factors) between-participants factorial design was used (Table 5). The perception of credibility functioned as the dependent variable in this research.
Independent variables
Level of user-experience functioned as an independent variable in this research. The variable will not be a manipulated like the other independent variables, yet the level of user-experience is expected to influence consumers’ perception of credibility (dependent variable).
More specifically, the effects of user-experience on the relationships with credibility were measured as well in terms of its moderating effect (figure 4).
The variable was measured with regards to; the number of times that products were bought online over the past year, the average price (in Euros, without decimals) of the products bought online (if applicable) and the approximate time between the previous product was bought online (if applicable) and the moment the participant fills out the questionnaire. The questions were asked with regards to the previous year in order to keep the gathered information up-to-date. The first question acted as the main indicator of the level of user-experience of the participant. The additional questions enriched the information on the participants of this study.
Price-level was the first independent variable of this research. The variable was manipulated by varying the mobile phones and their price.
For the lower price-level version of the questionnaires a very basic Samsung mobile (Samsung e1170) phone at the price of €13,95 was used (Appendices 1a-b). The participants were confronted with both the price of the phone, as well as a displayed picture of the phone itself. For the higher price-level in the other questionnaires, a Samsung smartphone (Samsung c3500) was used at the price of €119,95 (Appendices 1c-d). Same as with the lower-priced version, both the phone itself and the price of the phone were shown to the participant (See Appendix for the questionnaires).
The research included mobile phones as the product that participants were shopping for, because mobile phones are widely adopted in the Netherlands (72 phones per 100 people)3. Therefore, the experimental setting that was created in the questionnaire was likely to be a common situation in which the participant could easily identify him/herself. Moreover, mobile phones tend to be less influenced by gender-differences in taste.
The Trust-assuring factors were the second independent variable. Although the variable consisted out of nine factors (Table 1.), the variable was manipulated as a whole. Participants either saw a website with all the trust-assuring factors or without all of them. Subsequently, they were tested in six groups instead of nine, due to the fact that some factors are hard to distinguish. Dependent variable
The dependent variable in this research was perceived credibility. The perception of credibility will be tested against the two independent variables mentioned earlier, as well as to the direct effect of user-experience.
The key components of perceived credibility that were tested were to what extend the e-vendors’ website emits reliability, honesty and competence. A five-point Likert scale (1= not at all, 5= very much) was used to indicate to what extent the participants perceived the e-vendor reliable, honest and competent. The collection of scores allowed the opportunity to determine the degree of perceived credibility per participant.
3.2 DESIGN OF THE QUESTIONNAIRES
The obtained data from the questionnaires was used for quantitative analysis. The research can be defined as a descriptive and conclusive analysis as it determined the change in perception of users of an e-vendor.
All the gathered data came from the four questionnaires. The questions posed in the questionnaires were well prepared and their order was prearranged, making it a structured data collection.
The purpose of the questionnaires was not explained beforehand to the participants for the sake of the experimental process. For that same reason, this research included four separate questionnaires to lessen biased answers due to the fact that participants could start to recognize the differences between the e-vendors used.
This discussion led to few alternations of the questionnaire, primarily in terms of phrasing, and to some extent providing some extra information before asking the question.
All the questionnaires were conducted in Dutch (English blueprint; appendix 2b), as this researched focused on the Dutch market.
3.3 DATA ANALYSIS
A total of 120 participants were active in this research. These participants generated the raw data that needed to be analyzed in order to find answers to the constructed hypothesis and subsequently the main research question. The results are presented in two parts. First of all, some descriptive results (4.1) are presented which present additional information about the participants in terms of their mean scores on age, level of education, level of user-experience et cetera. Additionally, a comparison of means will be performed in order to make sure that there are no significant differences between the two groups (high experience vs. low user-experience) that can interfere the outcomes.
Second, the main results (4.2) will delve into testing the formulated hypotheses in order to find answers to the main research question.
Each type of the four questionnaires was analyzed with similar analysis-tools and in the same order as the gathered data resulted in one dataset.
First of all, the dataset will be examined on its normal distribution. In order to find out whether the data is distributed normally a ‘Shapiro-Wilk’ test will be performed.
Second, the level of experience will be determined in order to rank the level of user-experience as ‘low’ or as ‘high’. Univariate analysis in combination with ranking cases (tertiles) allows the opportunity to determine three groups, two of these three groups meet the requirements of either low user-experience, or high user-experience, being the first and the last tertile.
In order to examine perceived credibility the ‘Likert-scale scores’ per participants on (perceived) reliability, honesty and competence were computed. By doing so, a total score for credibility was created which could be considered as the dependent variable.
4. RESULTS
The results that are presented below are divided into two parts; descriptive results (Ch. 4.1) and the main results (Ch. 4.2). First of all, the focus will be on providing additional information about the participants of this research. The description of the participants will not directly answer the formulated hypotheses but will enhance the general picture of the participants and their characteristics.
Thereafter, the main results will examine the (possible) relationships between the key variables at stake. Hence, chapter 4.2 will address the formulated hypotheses. Subsequently, the gathered information will lead to answering the main research question (chapter 5).
4.1 DESCRIPTIVE RESULTS
The mean scores presented below illustrate the composition of the entire sample (N=120) in this research. Out of the 120 participants, 65 (≈ 54, 2%) were male and 55 (≈45, 8%) were female. The mean scores of their age were for the former 33,98 (SD= 15,38) and the latter 27,65 (SD= 8,95). The youngest male participating in the research was 20 years old and the oldest was 87 years old. Whereas the youngest female was 20 years old as well, but the oldest female participating was 69 years old. Moreover, 80 percent of the participants were below the age of 40 years old. In general, the largest group of participants (35,8 %) had HBO as their highest level of education, whereas another 26,7 percent had a university degree. When addressing user-experience in terms of the samples’ characteristics the following findings can be presented. A mean score of 9,24 (SD= 9,47) products/services were bought over the last year by the participants. The average price of the products/services bought (rounded to full euros) was € 42,- euros (SD= 43,15), and the mean score on the time (in weeks) since the participants’ previous online purchase was approximately 4 weeks (SD= 5,35).
When delving into more detail on the entire sample, a distinction can be made that is in line with this research.
Low-experienced users High-experienced users Significance level Gender 20 Male / 17 Female 25 Male /16 Female .737
Age M= 33,31 M= 32,60 .831
Education M= 3,37 M = 3,81 .186
Table 2. Sample characteristics.
Moreover, when comparing the two defined samples in terms of their user-experience characteristics, the following can be concluded (Table 3). Clearly, the number of products/services bought over the last year significantly (.00) differ between the two groups. The low-experienced users had a mean score of 1,89 products/services (SD= 1,586), whereas the high-experienced users had a mean score of 18,33 products/services (SD= 10,537). Furthermore, there was no significant difference (.619) between the average price of the products/services bought. Low-experienced users had a mean score of € 39,43 euros, and high-experienced users a mean score of € 44,47 euros a product/service. Finally, the time since the participants’ last purchase did not significantly differ (.079), for low-experienced users this was 5,5 (SD≈ 7,47) weeks and for the high-experienced users approximately 3,5 (SD≈ 3,79) weeks.
4.2 MAIN RESULTS
In order to find answers to the hypotheses, this chapter will present the results of the examined hypotheses step by step.
First of all, it is important to address the ranking of user-experience. The participants do not share an equal level of user-experience in conducting e-commerce. Therefore, their rank, in terms level of experience, needs to be determined in order to be able to answer the formulated hypotheses of chapter 2.5.
The ‘Shapiro-Wilk’ score can conclude whether or not the data is distributed normally. Whenever, the sig. value of the ‘Shapiro-Wilk’ Test is greater then 0.05 the data is distributed normally. The test in this research showed a sig. value of .763, indicating a normally distributed dataset with regards to user-experience.
In order to determine these two groups an analysis of the frequency of the data was performed. The key in this analysis is to maintain a significant difference in products/services bought over the last year between the two groups, while limiting the loss of respondents. Best-case scenario, in terms of minimizing data loss, would be to split the dataset at the median. However, this will lead to marginal difference at the scores around the median between the two groups.
Therefore, this research split the dataset into tertiles (33,3 % - 66,6 % - 99,9 %), where the first tertile becomes the low user-experience group, the second the medium user-experience group, and the last tertile the high user-experience group. As the scope of this research is on the difference between low and high user-experience, the middle group will be neglected in this research.
Table 3 displays the distribution of the groups and the average number of products/services bought online over the last year.
Tertiles (Rank) Mean score (M) Participants (N) Standard Deviation (SD)
1 (≤ 33,3 %) 1,89 37 (47,7 %) 1,586
3 (≥ 66,6 %) 18,33 41 (52,3 %) 10,537
Total: 10,95 78 (100 %) 11,375
Table 3. Distribution of ranked cases
Now that there are two distinctive groups based on their level of user-experience it is possible to examine the five hypotheses of this research.
Level of user-experience Trust-assuring factors Price
Low High Without With Low High
Perceived Credibility M= 9,97 (2,770) M=9,60 (2,830) 8,53 (2,892) 10,95 (2,124) 10,58 (2,447) 9,07 (2,883) Table 4. Main effects per experimental condition (Note: standard deviations are in parentheses)
Low price High price
With TAF Without
TAF With TAF
Without TAF Total User-experience LOW M=11,43 (SD=1,618) M=11,83 (SD=2,229) M=10,46 (SD=1,713) M=6,89 (SD= 2,759) M=9,97 (SD=2,770) HIGH M=11,08 (SD=2,811) M=8,82 (SD=1,888) M=11,13 (SD=2,167) M=7,83 (SD=2,887) M=9,60 (SD=2,830) Table 5. Experimental design (TAF = trust-assuring factors)
All five hypotheses can be tested with the help of one single test, the ‘Univariate General Linear Model (GLM)’. The univariate GLM is a technique that can conduct analysis of variance for an experiment with more factors. In this research there are now three independent variables; level of user-experience, price-level and the availability of trust-assuring factors. Moreover, the dependent variable stays the same all the time, being (perceived) credibility. The study strives for a confidence level of 95 percent; therefore a significant value of .05 accepts the hypothesis. The univariate GLM creates output that emphasizes on three different aspects; the main effects, the two-way interactions and a three-way interaction. This research is especially interested in the main effects on perceived credibility and the two-way interactions, which assesses the moderating role of user-experience.
There was no significant main effect of the level of user-experience on perceived credibility (.428), which indicated that there is no significant difference between high and low user-experienced participants on the degree of perceived credibility.
The second main effect that was tested in this experiment was availability of trust-assuring factors in the online environment. H2 claims that the availability of trust-trust-assuring factors on an e-vendors’ website has a positive influence on the perceived credibility of consumers. The test found a highly significant main effect of the availability or unavailability of trust-assuring factors on perceived credibility (.000), which indicated that perceived credibility was increased when trust-assuring factors were present (M=10,95; SD=2,124) versus absent (M=8,53; SD=2,892).
The third and last main effect that this research assessed was the effect of the price-level on perceived credibility. H4 states that, a higher level of price leads to a lower perception of credibility. The outcomes of the test show a significant effect of the level of price on the participants’ perception of credibility (.003), which indicated that perceived credibility was decreased when the price-level was high (M=9,07, SD=2,883) versus low (M=10,58; SD=2,447).
Within this research two two-way interactions were tested with regards to its effect on perceived credibility. With these tests the moderating role of the independent variable, level of user-experience, is examined (H3, H5).
The first two-way interaction that was addressed was the expected moderating effect of the level of user-experience on the relationship between the presence of trust-assuring factors and perceived credibility (H3). The results of the test show that there is no significant moderating effect (.281) of the level of user-experience on the relationship between the presence of trust-assuring factors on the perception of credibility. Which indicated that the effect of trust-trust-assuring factors on perceived credibility does not depend on the level of user-experience.
The second two-way interaction and the final hypothesis that was examined, was the expected moderating effect of level of user-experience on the relationship between the level of price and the perception of credibility. H5 claims that among consumers with more user-experience in conducting e-commerce there is a lower effect on the perceived credibility whenever the price is higher.
Indicating that perceived credibility was increased whenever the level of user-experience was high (M=9,15; SD=3,048) and the price was high, versus low (M=9,00; SD=2,770) with a high price. On the other hand, perceived credibility decreased whenever the level of user-experience was high (M=10,00; SD=2,629) and the price low, versus (M=11,62; SD=1,850) with a low price. The mean scores mentioned originate from the totals of the low-experienced users and a high price-level, and the high-experienced users and a high price-level. Even though, the total scores do not show significance levels per condition in this interaction, table 5 grants the opportunity to see which way the effect works.
The following table (Table 6) represents a summary of the outcomes of the tests performed to examine the hypotheses.
The effect of…. Mean
Square F. Sig. Reject/Accepted
User-experience on Credibility (H1) 3,489 .636 .428 Rejected
Trust-assuring factors on Credibility (H2) 86,487 15,776 .000 Accepted
User-experience on the relationship between trust-assuring factors and
credibility (H3)
6,484 1,183 .281 Rejected
Level of price on Credibility (H4) 53,385 9,738 .003 Accepted
User-experience on the relationship between the level of price and Credibility
(H5)
28,449 5,189 .027 Accepted
Table 6. Summary of results
5. DISCUSSION
In this research, five hypotheses played a central role. The results confirm several (significant) findings. However, other not significant findings also came to light.
The first results showed that the level of user-experience does not have a significant effect on the consumers’ perception of credibility of an e-vendor. In fact, a lower level of user-experience led to a slightly higher perception of credibility in contrast to a higher level of user-experience. This study confirms that trust-assuring factors have a strong significant effect on the perception of credibility in an online environment. Whenever trust-assuring factors were present, participants of this research perceived the e-vendors’ website as more credible than when the trust-factors were absent.
Moreover, it also finds significant evidence that price-level has a significant effect on the perception of credibility. Whenever the price of the product was high, the perception of credibility was significantly lower than when the price of the product was low.
The assumption that the level of user-experience moderates the relationship between trust-assuring factors and the perception of credibility does not find significant evidence.
On the other hand, the level of user-experience does significantly influence the relationship between the level of price and the perception of credibility. Hence, whenever the level of user-experience was high and the price was high as well, the level of perceived credibility was significantly higher than when the level of user-experience was low in combination with a high price.
This research had the same approach, in terms of experience, however it did address a more specific element of trust, being the perception of credibility.
Hence, the outcomes of this research delve into more detail in relation to trust. It also indicates that even though consumers are more experienced in buying products/services online, they still are almost evenly aware of the level of credibility, which might have to do with increasing information available on online fraud, which makes consumers more distrustful regardless of their experience. In addition to that, this study finds a slightly lower perception of credibility whenever the level of user-experience was high.
Furthermore, there was barely any prior research on this specific relationship in an online environment, therefore the findings of this study can be perceived as an elaboration on previous findings by Gefen (2000).
The finding that user-experience does not have an effect on perceived credibility could be explained in a way that consumers maintain reluctant in easily perceiving a website as credible even when their experience is increasing. Even though, the slight difference between the two mean scores was not significant, the fact that higher-experienced consumer scored somewhat lower on perceived credibility could have to do with negative previous experience(s) or more easily recognizing the risks of purchasing online.
On the other hand, trust-assuring factors proved to have a strong significant effect on perceived credibility. Whenever the trust-assuring factors were available the perceived credibility increased significantly. This also worked to other way around, in which an absence of the trust-assuring factors led to a significant decrease in perceived credibility.
Earlier findings defined several types of trust-assuring factors, but these were never tested in an experiment. Therefore, the findings of this research are in line with the (in theory) defined trust-assuring factors (Table 1), and elaborates on it by experimentally testing them. It confirms the fact that it is of great importance to have the different types of trust-assuring factors on an e-vendors’ website in order to stimulate a higher consumer perception of credibility.
In relation to the finding on the importance of having trust-assuring factors on an e-vendors’ website in order to increase the perception of credibility, is the question to what extent user-experience moderates this significant difference?
For example, does an increase in user-experience decrease the negative effect of the unavailability of trust-factors on perceived credibility? Hoffman et al (1999) found that an increase in experience leads to a decrease in consumer concern in an offline environment. When relating their findings to this research it is expected that user-experience does have its effect on the relationship between trust-assuring factors and perceived credibility. However, the findings of this research are not in line with what Hoffman et al. found. This study finds that there is no significant moderating effect of the level of user-experience on this relationship. This might have to do with the strong significant effect between trust-assuring factors and the consumer perception of credibility. Thus, this could well be explained as another confirmation of the importance of having trust-assuring factors on an e-vendors’ website, and that even a consumer with high experience will not neglect absence of them. Furthermore, this indicates that theories on building trust in an offline environment cannot be transferred to the online environment.
Moreover, this research examined the direct relationship between the level of price and the perceived credibility of an e-vendor. Based on earlier research it was expected that whenever the price rises, the perception of credibility decreases. However, this earlier research was primarily performed in an offline environment.
The results of this study confirm earlier findings, and with a statistically significant difference the hypothesis is accepted. Indicating that whenever the price of a product increases, the perception of credibility decreases, and vice versa. However, earlier findings did not delve into specific elements of trust, but predominantly focused on the related aspect of risk.
For example, Gotlieb et al. (1994) found that price has a stronger influence on level of risk whenever the credibility of the source is low.
Therefore, the findings of the research enrich the earlier findings on the relationship between risk (price) and perceived credibility (trust). Besides, it proofs that the effects in an offline environment and in an online environment are comparable.
In addition to that, Beatty et al. (1987) found that whenever the price of a product rises, consumers tend to search for more information before making the purchase.
Even though, this research did not emphasize on this relationship, it seems plausible that the ‘search for information’ that Beatty et al. (1987) talked about (in an offline setting) might also hold for in an online setting in relation to an increased need for trust-assuring factors when the price is high.
Finally, this research addressed the moderating effect of user-experience on the relationship between price and perceived credibility. The outcomes showed a significant effect, indicating that whenever consumers had a higher level of experience the negative effect of a higher price on the perception of credibility was significantly moderated. The fact that this effect finds significant evidence is difficult to explain at this point in time. It might have to do with some way of building familiarity, however others findings in this research indicate differently (H1). Unfortunately, prior research did not address the moderating effect of user-experience on this relationship at all. However, the fact that this research shows a significant effect on this relationship does create food for thought.
5.1 CONCLUSION
From the findings of this research, one can draw the following conclusions with regards to the main research question (Ch. 1.6). Both price level and trust-assuring factors have a strong significant influence on the way consumers perceive an e-vendor with regards to credibility. Furthermore, the extent to which consumers are experienced in conducting e-commerce did not proof to have a significant moderating role the relation between the trust-assuring factors and perceived credibility. However, the level of user-experience did have a significant moderating effect on the relationship between price-level and the perception of credibility.
The findings of this study extent our knowledge on how consumers build trust online.
6. RECOMMENDATIONS FOR FURTHER RESEARCH
This research examined, and found evidence, on a wide range of topics. However, it also left some questions unanswered and raised new ones. As trust remains a very important variable in relation to the intent to purchase further research on this topic is recommended. Especially, since the outcomes of this research in many occasions are not in line with earlier findings on trust in an offline environment.
This study addressed the relationship between price and consumers’ perception of credibility and the moderating effect of user-experience on this relationship. Even though, this research found significant results, it was difficult to explain this effect, as no prior research was available and the scope of the research was much wider than addressing only this issue. Addressing this relationship could be done with a different sampling method, which in focused on either a high or low experience consumers. Further refinement of the experiment used might also lead to enrichment of the outcomes. Nonetheless, understanding how consumers build trust online remains an important topic of research. In relation to that, extended research on user-experience, as a dependent variable in an online environment would be helpful to better understand the process of building online trust.
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