MLT 7 v1.1

ANDY LETTING STUDENT NUMBER: 12109095

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A study to determine the implication on the consumer for a brand serving a 404 page error during the research phase of an online electronic

product purchase.

ANDY LETTING

STUDENT NUMBER: 12109095

MSc Digital Marketing

UNIT 1: MASTERS LEVEL THINKING

TUTOR: Ruth McQuater


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Table of Contents 1 Introduction ................................................................................................................... 3

1.1 What is a HTTP:// 404 error .................................................................................................. 3

2 Critical literature review ................................................................................................. 4 2.1 Introduction ......................................................................................................................... 4 2.2 The Online Consumer and Customer Loyalty ......................................................................... 6 2.4 The expectancy disconfirmation model ................................................................................ 6 2.5 Unified Theory of Acceptance and Use of Technology 2 ........................................................ 7

2.5.a Personal Characteristics, Habit & Experience ....................................................................... 9 2.6 Turning a 404 page into potential sales, and retaining customers: ....................................... 11 2.7 Literature Review Conclusion .............................................................................................. 11

3 Methodology: .............................................................................................................. 12 3.1 Philosophical stance: ........................................................................................................... 12 3.2 Research design: .................................................................................................................. 13 3.3 Bias: .................................................................................................................................... 14 3.4 Data analysis: ...................................................................................................................... 14 3.5 Pilot & Pretest: .................................................................................................................... 14 3.6 Ethical Considerations: ........................................................................................................ 15 3.7 Limitations: ......................................................................................................................... 15 3.8 Other possible areas of study: ............................................................................................. 16

4 Conclusion: .................................................................................................................. 16

5 References ................................................................................................................... 17

6 Appendix 1 ................................................................................................................... 24

7 Appendix 2 .................................................................................................................. 29 i


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1 Introduction

Today, more than three billion people are linked to the Internet, with a sharp increase in the number of internet users around the world since 2012 from 35.5 to 46 percent. (Internet World Stats' statistics, 2015; Internet live stats; no date). Consequently, the Internet forms new competitive advantage for online businesses and gives them new ways to outperform competitors (Porter and Millar, 1985)

Consumers are attracted to digital commerce as it offers convenience, ease of use, and agility in finding information in a shorter amount of time compared to offline shopping. (Doolin et al, 2005 cited in Lucian, 2014). Consumers favour their intended purchases and shop more online as they receive product recommendations (Aljukhadar et al, 2013).

According to Ofcom’s Adults’ media use and attitude report 2015, media use has increased by 27 percentage compared to 2005, and nearly nine in ten adults now go online at any location (compared to 6 in 10 in 2005). The past ten years has also seen weekly time spent online doubling from around 10 to 20 hours, and an increase in the amount of 65-‐74 year olds going online at any location (from 56% to 70%).

Previous studies have approximated that there is an average shopping cart abandonment rate of 68.3 percent (Baymard Institue, January 2016). McGlaughlin (2001) suggests that shopping cart abandonment represents approximately more than $6.5billion in lost sales per year.

The above statement assumes that if a customer has added items to the cart, it is reasonable to assume the revenue loss would be higher if consumers are forced to abandon their online journey before selecting products to purchase due to a 404 error page.

The purpose of this research proposal is to help businesses explore the implications of 404 error page interruption on the consumer experience, and potentially, retailers website. The research will be based on the expectancy / disconfirmation model and an adapted Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) model.

1.1 What is a HTTP:// 404 error

Various types of errors can occur when users attempt to access a webpage that prevent the page from being displayed. If there is no response from a host at the target address when a page is requested, a default message will be shown by the web browser indicating that the requested page cannot be displayed, or the web browser may “hang” until the user performs some action. Another reason can be that valid URLs may become unsupported due to reasons such as if the developers deletes or moves certain web pages, or if the whole website is hosted at another address. (Manber et al., no date)

Other causes for 404 errors found by Manber et al. (no date) is due to users attempting to reach a webpage which is currently unresponsive, or if users mistype the URL (Uniform


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Resource Locator), and so the page request is directed to a valid host but to an invalid URL, and the host may return an “error 404: page not found” error message.

They also found that sometimes, a web page can be retrieved, but not displayed, because of unsupported data formats, script execution errors, and page load errors. For instance a given URL that is valid at one time may become invalid. (Manber et al., no date).

The reasons identified above may lead to frustration and abandonment of the page, potentially having a direct impact on customer loyalty to a particular website, which is primarily determined by the usability of the application and the customers’ opportunity cost of waiting for the page to load.

The rapid growth of the internet means web applications are constantly evolving and development cycles of web applications are becoming shorter, making assurance of the quality and reliability the products and services available online more difficult. (Offutt, 2002).

Offutt (2002) also suggests there is a common theme occurring from usability of applications and customer loyalty to these applications, while Dobolyi (2010) acknowledges that not much attention is given to consumer retention during the development process of web applications, and high development costs along with insufficient resources mean some applications are inadequately tested.

This research proposal is intended for commercial UK online retailers who have traditionally sold their products via the high street and have been forced to move online to compete with the online only retailers. The proposal’s focus is to determine key online behaviours and the perception when a user is faced with a 404 error.

Therefore the objectives of the research are:

• Explore customer buying behaviour when faced with error page disruption • What impact can a 404 error have on a customer’s perceptions of a website?

2 Critical literature review

2.1 Introduction While numerous studies have focused on the impact of complex checkout procedures, ease of payment, and other issues impacting shopping cart abandonment and customers’ shopping experience (Pavlou, 2003; Oliver and Shor, 2003; Rajamaa, Paswan, and Hossain; 2009, Kukar-‐Kinney and Close, 2010) there is scarce research on 404 error page interruptions and their potential impact on the consumers’ motivation to return to the site.

Based on a ten year study conducted by Kumar and Kumar (2012), HTTP error 404 (not found) accounted for 70.15% of all inactive URLs in their research, as shown in Figure 1 and figure 2.


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Figure 1 HTTP errors associated with missing URL citations (Kumar and Kumar, 2012)

Figure 2 Errors associated with missing URL's (Kumar and Kumar, 2012)

Minimal data is available on the impact of a 404 error page on a transactional website, therefore understanding the behaviour of an online consumer across e-‐commerce will be drawn on to understand the potential impact 404 error pages have on an online business.

Online consumer characteristics will be explored in regards to their motivations to better understand the impact of a 404 error page, with reference to the expectancy disconfirmation model to measure brand expectancy and its role when consumers are faced with a 404 error page, as well as the use of an adapted Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) model to measure behavioural intentions and technology use of consumers.


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2.2 The Online Consumer and Customer Loyalty It is reasonable to assume that for online retailers, sales are critical for the online business. Therefore analysing consumers' behaviours is crucial for driving online activity (Deaton and Muellbauer, 1980, Solomon et al., 2006). The Internet has increased the competitive landscape, therefore understanding online consumers' behavioural traits has become very important (Turan, 2011, p. 78) to secure sales.

No face to face interaction online, makes understanding key consumer behaviour features crucial. Rogan (2007, cited in Nazir, et al., 2012) focuses on the importance of the relationship between the business strategy and the behaviour of consumer, and that business strategy as a key approach to understanding the consumer’s needs and wants, to positively increase probability and frequency of online behaviour.

Much has been researched on the subject of customer loyalty both online and offline, (Srinivasan, Anderson & Ponnavolu, 2002) identified that consumers can compare rival products and services quickly and easily with just a few clicks, and so rival businesses are at risk. They also identify eight factors (customization, contact interactivity, care, community, convenience, cultivation, choice and character) that can potentially affect e-‐loyalty and develop scales to measure these factors.

Seen as the success and growth of customer-‐centric businesses, customer loyalty is key to increasing online revenue and profit. Satisfied customers are more likely to return to the website and engagement with the brand and share experiences with other. (Ernst & Young, 2013)

Online stores need to work on the best strategies to ensure customer loyalty, as customers can easily move between rival retailers within seconds and so retailers need to secure that when customers are faced with a 404 error page, they do not completely back away from the business, and are guaranteed to return for future purchases.

2.4 The expectancy disconfirmation model Consumer satisfaction / dissatisfaction (CD/D) has been extensively studied and extensive literature has published (Hunt 1991; laTour and Peat, 1979; Oliver and Bearden, 1985; Divett, 2002)

According to the expectancy disconfirmation model, consumer knowledge regarding a products’ performance will form their expectations, (Liu et al., 2013) and expectation and disconfirmations are moderators for satisfaction or dissatisfaction of the consumer (i.e. the difference between consumer expectations and actual experience) (Oliver, 1980; Oliver and DeSabro, 1988, Liu et al., 2013), and so “consumer’s expectations serve as a base line for satisfaction assessment” (Szymanski and Henard, 2001). Therefore expectations are either highly reaffirmed when the experience exceeds expectations, confirmed when experience equals expectation and are negatively disconfirmed when the experience falls below expectations (Swan, Trawick, and Carroll 1981).


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Figure 3 The expectation-‐disconfirmation model (Liu et al., 2013)

Based on this model, it is reasonable to assume that if the consumers’ online store experiences fall short of their expectations, they will experience dissatisfaction and intentions to repurchase will fall. (Cronin and Taylor, 1992; Oliver, 1980; Liu et al., 2013).

Consumers may have different feelings regarding different aspects of the shopping environment, and may be satisfied with some aspects, and dissatisfied with others, and so it can argued that if retailers exceed customers expectations ‘(Rajamma et al., 2009) though out their shopping experience, any minor mishaps such as encountering a 404 error page may mean that customers are less likely to be disappointed, and their overall level of satisfaction will be enough to overcome this.

It is evident that negative emotions experienced by customers directly influence their post-‐purchase behaviors (Laros & Steenkamp 2005; Mattila & Ro 2008; Harmeling et al., 2015) in terms of repurchasing, and word of mouth, as well as sparking brand switching intentions (Sánchez-‐García and Currás-‐Pérez, 2011). Negative emotional service experiences are likely to harmfully influence customer’s intentions on establishing or maintaining a loyal relationship (Tronvoll 2010), whereas positive experiences of exceeded expectations help to raise customer loyalty, thus significantly enhancing repeat purchases and positive word of mouth marketing.

The expectancy disconfirmation model implies that if expectations are not met, a 404 error page could potentially cause dissatisfaction, causing the consumer not to return to the website.

Hypothesis 1: A brand exceeding expectation when a 404 error page is served, has a greater chance of retaining the customer based on the expectancy disconfirmation model

2.5 Unified Theory of Acceptance and Use of Technology 2 The only way for productivity to improve in technologies is if technologies are accepted and used by individuals. (Venkatesh et al., 2003)


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Figure 4 Basic concept explaining user acceptance models (Venkatesh et al., 2003)

A unified theory of individual acceptance of technology was proposed from the eight current prominent user acceptance models called the Unified Theory of Acceptance and Use of Technology (Venkatesh et al., 2003) This model was later updated to UTAUT2. This research paper shall use an adapted UTAUT2 model to explore the behavioural intentions of consumers when faced with a 404 error page. In UTAUT three key components of performance expectancy, social influence and effort expectancy influence behavioural intention to use a technology, while facilitating conditions and behavioural intentions determine technology use (because facilitating conditions are believed to be freely available within organisation) (Venkatesh et al., 2003), however in UTAUT2 which is tailored to consumer technology use, facilitating conditions differ across different technological platforms and environments etc, and so facilitating conditions are added as a key stimulant of behaviour intention (Venkatesh et al., 2012).

UTAUT2 has improved the variance explained in behavioral intention from 56 to 74%, and explained 52% of the variance in technology use (up from 40%) compared to the original model. It also added 3 core components of hedonic motivation, price value, and habit. The influences of the same individual differences (age, gender, experience) are tested to investigate the effect of the components on consumer behaviour intentions and use of technology (Venkatesh et al., 2012). (For original, please see Appendix 2)

Figure 5 adapted UTAUT2 model

Effort expectancy is “the degree of ease associated with consumers’ use of technology” (Venkatesh et al., 2012) and involves three parameters; perceived ease of use, complexity and ease of use. (Venkatesh et al., 2003)


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In the effort expectancy component of the Unified Theory of Acceptance and Use of Technology model (UTAUT), researches found that effort-‐orientated components are more prominent as individuals face new things, where processes take longer to complete, (greater in women and the elderly) but as experience grows, effort expectancy diminishes and becomes irrelevant (Venkatesh et al., 2003) This is in line with other literature such as Sharma, 2012, p. 189) where it was found that with experience, the intention to continue a behaviour was not significantly influenced by perceived ease of use. This insinuates that if new customers don’t find it easy to return to what they were doing when interrupted by a 404 error page, then they may potentially leave the site and businesses will not be able to retain them.

Facilitating conditions are “consumers’ perceptions of the resources and support available to perform a behavior” (Venkatesh et al., 2012), with core components being: perceived behavioural control of the system, facilitating conditions (factors such as guidance and assistance that aid consumers in using technology and make the use easier), and compatibility (in relation to consumer’s preferences, lifestyle, needs, experience etc). (Venkatesh et al., 2003)

Cameron (1999) argued that customers left frustrated in their efforts to seek information, are less likely to comeback, with 30% of customers leaving the website without purchasing due to not being able to navigate their way around the site (Schaffer, 2000). Furthermore, Sinioukov (1999) suggested that a user friendly site, with accessible and visible information and the ability for consumers to search for information easily; is vital to creating a successful online business. This implies that unless the 404 error page informs the consumer of why they are arrived at 404 error page, with instructions to rectify the situation, and options to navigate to different areas of the website, then the consumer will be left frustrated and abandon the web page.

Research has also shown that receiving help and assistance places a huge importance for the elderly in the context of difficult IT usage, (Morris and Venkatesh, 2000) and so there is a greater need for making technology easy to learn and use (Venkatesh et al., 2012). Venkatesh et al., (2012) also shows that when customers have more experience, the need for facilitating conditions for learning (influenced by gender and age) will be less significant, with Sharma’s study (2012, p. 189) adding that facilitating conditions are only important as individuals face new things but become less important as consumers gain more experience.

2.5.a Personal Characteristics, Habit & Experience Personal characteristics such as age, gender, education, income and lifestyle are important factors affecting the behavior of an online consumer when faced with an error page.

Sun and Zhang (2006) and Hernandez et al. (2011) studies on consumer’s demographic characteristics (age, gender and income), and their effects on online shopping behaviour reveals that when consumers are more proficient at online shopping, their behaviour become analogous and so demographic factors no longer influence experienced online shoppers’ behaviour.

Rodgers and Harris (2003) found that men are more emotionally satisfied with Internet shopping, and found it more convenient than women. (Sun and Zhang, 2006) found that women experience anxiety when faced with new things, unlike men who are more


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pragmatic. Women also care more about others opinions towards them and so social influences play a big role in behavioral intentions when trying new things (Venkatesh et al., 2000; Sun and Zhang, 2006)

Habit is a “perceptual” component that reflects the outcomes of prior experiences with technology (Venkatesh et al., 2012) and has been defined by Nilsen et al. (2012) as a “behaviour that has been repeated until it has become more or less automatic, enacted without purposeful thinking, largely without any sense of awareness”.

The difference between habit and experience is that experience is essential but not enough for establishing a habit. Also, in ”the passage of chronological time (i.e. experience), different levels of habit can be formed depending on the specific technology individuals’ intent to learn and use (Venkatesh et al., 2012).

There has been extensive research into the relationship of habit and behavioural intention and technology usage (Howell, 2007, pp. 28-‐29; Van Winkle et al., no date; Peijian et al., no date; Limayem et al., 2007; Kim et al., 2005; Venkatesh et al., 2012). Kim et al. (2005) compared two perspectives of Habit/automaticity perspective (HAP) and Instant Activation Perspective (IAP), with IAP indicating that well established attitudes and intentions can be formed if a behaviour is performed repeatedly, but is still a function of evaluations and intention, whereas with HAP, no evaluation, thinking process, decision making or intentions are needed to doing a behaviour (Kim et al., 2005; Pro-‐Quest, 2007, p. 27-‐29; Venkatesh et al., 2012). Both perspectives depend on information and cue processing as surroundings change, and as experience increases and time passes, the response to changes will become faster and so habit will have a stronger influence on behavioural intention and technology use for more experienced consumers (Venkatesh et al., 2012)

This may mean that experienced customers who are used to seeing a 404 error page, might have a habit of without thinking, automatically exiting the page and moving on to continue their shopping or exit the site.

Experience: As seen above, consumers who have gained more experience tend to act automatically and are guided by cues, and so the effect of behavioural intentions on technology use diminish, as experienced customers form habits and so actions become spontaneous (Kim et al., 2005; Vankatesh, et al., 2012) and are no longer moderated by demographic factors.

Using the above literature review, we can hypothesize that effort expectancy and facilitating conditions when moderated by experience can define whether or not customers will return back to the retailer’s site.

Hypothesis 2: New customers are more likely to return to the retailers website if online retailers understand these users and help navigate them back to the site from a 404 error page


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2.6 Turning a 404 page into potential sales, and retaining customers: 404 pages are over looked and not seen as crucial to getting customers back on tract towards a potential sale and consequently, revenue.

If a 404 page has the same theme, and look as the website, and also contains the company logo, then people are more likely to stay than if it was a random white page as they are more attached and familiar with the company website. (Adam, 2015).

When customers are interrupted by a 404 page, they will request some explanation as to why as retailers will gain customer trust and satisfaction when they show a message on the 404 error page notifying customers of the situation and even an apology can sit well with customers. In addition, an option to report the page is an important tool to prevent and minimise the occurrence of landing on a 404 page. (Adam, 2015)

Retailers should engage readers who have landed on a 404 page, and use this as a sales opportunity, with many ways to return customers to the website. There should be links to certain pages, such as key selling pages (e.g. TV’s, Phones, Gaming Consoles etc.), and a search bar for customers to quickly look for what they need. The more information on the 404 page the better. (Adam, 2015)

Kumaragu, Cranor and Mather (2009) recognized that some error page provide no feedback to the user about what has just happened. Providing immediate feedback at the “teachable moment” enhances learning (JR Anderson, Rules of the mind, lawerance Erlbaum 1993), and can also provide the viewer with options on how to solve the error or report it.

(Kumaragu 2009) tested a landing page approach, convinced it enables user to be educated without taking time out of their schedules for the purpose of getting trained on falling for phishing scams, and substitutes an impractical 404 error page with educational information

This is a logical approach to educate the users at times when a 404 error would occur, however the volume of content and type of messaging is critical if a consumer is going to take advantage of the content presented to them, otherwise this approach is no more beneficial than serving a standard non-‐informative 404 error page.

2.7 Literature Review Conclusion One of the key conclusions is the need for greater evaluation and refinement of the consumer journey at a 404 error page. It would appear that there are a number of potential factors that have the ability to influence a customer’s decision whether or not to proceed from a 404 error page. However this is an issue that needs to be considered in greater detail in order to determine the best approach to return consumers back to the website they were originally navigating. As a result, the web-‐based questionnaire developed for this proposed research should incorporate questions to help explore customer perceptions about the issues of, retailer expectations, online experience, 404 navigation and ease of use, and the impact on brand loyalty, in order to establish the impact error pages have on behavioural intentions and customer’s decision to return to the site.

There is a lack of academic research into the impact of 404 error pages on consumers and the best approach to return these consumers to the site. The literature studied in this


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review suggests there are a number of factors leaving consumers frustrated with their online experience, with 404 error pages adding to this experience. However, this idea will need to be further investigated in the proposed research in order to determine whether an obvious and clearly observable relationship exists between the messaging of a 404 error page and the the conversion back to the website. To test this idea further, questions specifically related to customer attitudes towards 404 error pages and there perception of the organization would need to be incorporated in the web base questionnaire.

3 Methodology:

3.1 Philosophical stance: This research proposes a deductive approach to gather quantitative data, with the need for the adequate amount of samples in order to predict behaviours of the whole population. (Saunders et al., 2009, p.127) based on our hypotheses (Hyde, 2000). Retailers are only surveying consumers when interrupted by a 404 error page on their customer journey, and are not analysing customers’ change over time, and so this is a cross-‐sectional study. (Levin, 2007; Saunders et al., 2009, p. 155; Smith and Albaum, 2010, p. 164) There are many forms of data collection. This research proposal shall collect primary data in the form of an online survey to test the hypotheses acknowledged in the literature review. The research population is anyone affected by a 404 error page when trying to view a product page. As only people reaching the 404 page will have the chance of filling in the survey, non-‐probability convenience sampling paradigm will be used. (Pew Research Centre, no date: A)

The past 10 years have seen a sharp increase in the number of Internet surveys (Baker et al., 2013) due to many factors including the fact that online surveys are more continent for participants who can complete them at a time a place convenient to them. There also comes the fact that respondents are not effected by the social desirability bias (Holbrook and Krosnick, 2012) as they would be if they were being surveyed over the phone or face to face (Pew Research Centre, no date: B). Other advantages for businesses are the low cost of online surveys compared to other methods and that fact that the internet is more widely available and so a more diverse range of samples can be reached. (Pew Research Centre, no date: B)

This method was also chosen as large amounts of information can be collected from a large number of people in a short period of time. (Pew Research Centre, methodology, no date: B; Saunders et al., 2009, p. 144)

When customers land on a 404 error page, they should be faced with, amongst other elements, an option to take part in a questionnaire studying consumer perceptions of a 404 error page and its implications. An explanatory introduction will be added to explain the purpose of the study to customers, with an email address should respondents want to know more information.


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3.2 Research design:

The hypotheses to be tested are:

Hypothesis 1: A brand exceeding expectation when a 404 error page is served, has a greater chance of retaining the customer based on the expectancy disconfirmation model

Hypothesis 2: New customers are more likely to return to the retailers website if online retailers understand these users and help navigate them back to the site from a 404 error page

The questionnaire will contain 5 mandatory sections, with a mixture of forced-‐choice, list, and category questions, as well as rating questions using the Likert-‐style scale (Saunders et al., 2009, pp. 374-‐378). There will also be a final section for any additional comments respondents might have.

The first three sections contain questions related to 404 error page perceptions and behaviour intentions and use an adaptation of the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) to test the second hypothesis relating to effort expectancy, facilitating conditions, habit and experience, and their influence on behavioural intention of continued usage of the retailer’s site. The UTAUT2 model has been applied to many areas of research such as ecommerce and has shown to be a valid model for understanding consumers’ acceptance and successful use of technology (Escobar-‐Rodríguez and Carvajal-‐Trujillo, 2013; Martin, 2013; Albugami and Bellaaj, 2014; Arenas-‐gaitán et al., 2015)

The fourth section contains questions relating to the respondents’ demographic factors, frequency of online shopping, online activity, and spending habits and shall be used in conjunction with the first three sections.

The fifth section of the questionnaire incorporates the expectancy disconfirmation model to test the first hypothesis and contains questions relating to brand expectancy and perceived performance. The expectancy disconfirmation model has also been a key model in ecommerce research. (Elkhani and Bakr, no date; Liao et al., 2011; Liu et al., 2013).

Assuming that retailers have guest check-‐ins, respondents can be differentiated by those who hold accounts and those who don’t. Businesses need to assume that if customers believe that the brand exceeds expectations, they hold an account with the retailer, otherwise they can shop via guest check-‐ins. To validate these assumptions, the following questions shall be asked:

“Do you hold an account with this retailer” and “Are you thinking of making an account with this retailer?”

As all questions are mandatory, and businesses need to ask for demographic questions, they have been placed later in the questionnaire and engaging and interesting questions have been placed at the start to motivate respondents to continue participating in the questionnaire. (Pew Research Centre, no date: c)


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Answers to questions holding more than 2 response options should be spread randomly due to the concerns of the effects that category order has on responses of participants (Pew Research Centre, no date: c ; Foddy, 1994, p. 7; Schoenherr et al., no date)

3.3 Bias: To remove any bias and to reach as many respondents as possible, the questionnaire should be available for a long period of time. (FluidSurveys Team, 2013) Large-‐scale samples are needed to get more reliable population estimates for each variable.

To eradicate any form of cognitive bias, the same number of opposing independent variables needs to collected when analysing each hypothesis, i.e. for the first hypothesis; (A brand exceeding expectation when a 404 error page is served, has a greater chance of retaining the customer based on the expectancy disconfirmation model), the same number of respondents confirming that the brand exceeds or does not exceed expectations needs to be randomly collected and analysed to test the hypothesis of who is more likely to return to the retailer’s site.

For the second hypothesis; (New customers are more likely to return to the retailers website if online retailers understand these users and help navigate them back to the site from a 404 error page), the same number of inexperienced verses experienced customers need to be randomly selected for analysis of this hypothesis.

This is not a study of which of these groups is more likely to take part in the questionnaire, and so to eliminate any bias that may affect the research results, the same number of respondents from each group should be chosen randomly for analysis and review.

The ways for assessors to know the type of consumer has been mentioned above in the research design section.

3.4 Data analysis: The research will use appropriate tools within an embedded TypeForm platform to analyse data for useful information to help in conclusive decision-‐making, and can later be connected to Google Spreadsheets and analysed using SPSS if needed.

Businesses shall use statistical inference when analysing the questionnaire answers. (make assumptions about the population based on data given from the sample, with the conclusion being the acceptance or rejection of each of the hypotheses) (Saunders et al., 2009, p. 218)

3.5 Pilot & Pretest: Questionnaire can be adjusted and improved by running a pilot test to understand what respondents will think of filling in the survey, and open ended questions can be asked in the questionnaire for the pilot test, and respondents should be encouraged to comment so researchers can analyse and include the most appropriate closed-‐ended answers adapted from the most common answers for people to chose from. (Pew Research Centre, no date: C ). A pilot test should run on a large group of people so that differences within the population can be analysed.

During the pilot test reviewed for face validity this research proposal, 32 questions needed editing for clarity. There was confusion regarding question 3.2 “Are you more likely to return


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to a website after encountering a 404 page if you think the retailer exceeds expectations?” with a Yes or No answer. This lead to confusion, and so more detailed answers were provided.

The other issue was 5.1 “To what extent do you believe this retailer exceeds expectations?” where respondents felt forced to choose one of the 3 answers which were not enough to choose from, and so the question was changed to include more response options.

A Pretest can be taken by retailers on a small sample of the population to determine respondents’ interpretation and understanding of the questionnaire. Respondents give feedback on the questionnaire and so any necessary changes to the survey are made before it is published on the 404 error page (Pew Research Centre, no date: C ).

3.6 Ethical Considerations: As well as the explanatory introduction to the survey and it’s purpose, potential respondents will be given information on the content of the questionnaire along so they can make the decision to opt in or not.

For customers to participate in the questionnaire, they need to give consent for their answers to be used in primary and secondary research, and know that data collected is anonymous and will not be used other than for the purpose of 404 error page research. After agreeing to the terms and conditions of the survey which include the ethical consideration, respondents will be able to start the survey.

3.7 Limitations: Although surveys are a quick and affective way to gather information, lengthily questionnaire tend to push away respondents if there are no incentives attached (Saunders et al., 2009, p. 144), and so the response rate is generally lower than telephone and structured interviews (Saunders et al., 2009, p. 364). Although this proposals’ questionnaire is lengthily, and did not take too long for respondents to complete in the pilot test, a higher incentive may be needed for consumers to be engaged and complete the survey. Another limitation is that researchers can not follow up the questionnaire with respondents. (Beiske, 2002).

A key question is that there may be a low response rate to complete the survey, and so generally, online surveys incentivize respondents in order to increase cooperation and completion of the survey (Pedersen and Nielsen, 2016; Deutskens et al., 2004). A 15% discount on a future purchases can be given, but the question still remains as to is it enough, as some customers might have landed on the 404 page by mistake or without continued intentions to use the website or are doing a one off purchase, and so might not be willing to do the questionnaire

The Questionnaire element on the 404 error page needs to be noticeable to consumers so they see it before closing the page or going back to the page there were on in order to get a higher co-‐operation rate. One could assume that loyal customers are more likely to do the survey even without the incentive coupon and so, if retailers choose not to include a promotional code incentive, it may be found that a higher number of loyal customers are participating survey.


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3.8 Other possible areas of study: This questionnaire can be applied to other areas and not just on the 404 page itself. It can be offered on relevant research locations chosen associated with the site (e.g. pop up when entering site and also on social media pages).

If 404 error pages are well managed and have buttons for users to get back to the site then there are other possible areas of study to know the effect of a 404 page on retaining customers, such as measuring the amount of outward traffic coming from a 404 page, and the results can be more trustworthy than customers filled surveys, where honesty and reliability are not always confirmed.

To know if this traffic is coming from a loyal customer or not, companies can compare the traffic of those who have an account to the traffic coming from a 404 page of those holding no account (i.e. new customers)

Response rate and completion rates should be reported in order to improve future studies.

The findings from this study, if undertaken, can also be used to test other hypotheses such as testing to see if demographic factors do not play a role in behavioural intentions as experience increases.

4 Conclusion:

Companies requiring a competitive advantage need to quickly adapt and change to retain consumers. Technological advancements have paved the way for consumers to gain product information, recommendations, reviews effortlessly and so businesses need to design new strategies to engage and retain customers.

While this review has contributed potential research approaches for further understanding of customers reactions to a 404 error page, and its potential sales, there are some limitations in knowledge as there is currently insufficient research regarding 404 error page interruptions and their potential impact on the consumers’ shopping current and future shopping experiences, as well as the consequent effects on retailers.

This study proposal hypothesizes brand expectations and the level of consumer experience as key moderators of continued store browsing after being faced with a 404 error page.

Using an adapted UTAUT2 model, experience is hypothesized to moderate the effort of expectancy and facilitating conditions when customers are faced with a 404 error page. If the appropriate facilitating conditions are available to enable customers to continue their store browsing, then effort expectancy should, in agreement with past researches, decrease as customers find it easier to return to the main website after the 404 error page interruption

The questionnaire needs to be clearly advertised on the 404 page for customers to see it, and interact with it if they please. If there is no incentive for consumers to take part in the survey, retailers may find the majority of respondents to be loyal customers, and so the response rate from new and inexperienced user will be low and may impact the


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interpretations of our finding. To reduce this bias, a promotional code notice will be visible to everyone landing on the 404 error page, regardless of if they hold shopping accounts with the retailer, and regardless of their loyalty to the company and experience with the internet.

If retailers want to increase completion rates of the survey, they need to manage load times for the survey, make sure the survey window is compatible and fully responsive on all devices. (FluidSurveys Team, 2013)

Retailers also need to enhance the survey and make it more appealing and fun to the user in order to limit the non-‐response rate. (Deutskens et al., 2004).

This proposal raises important areas for further investigation through the presented research models. Retailers need to further understand consumer intentions in order to know the current and future implications of a 404 error page interruption on the business, and be able to tailor the page layout to be more informative and user-‐friendly to both new and experienced users.

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6 Appendix 1 QUESTIONNAIRE

1. 404 page error perception

1.1 Do you know what a 404 page is?

O Yes

O No

1.2 Have you ever been redirected to a 404 error page before?

O Yes

O No

1.3 Have you been made aware of why you have arrived a 404 page error?

O Yes

O No

1.4 How would you describe your reaction to a 404 error page?

O Frustration

O Angry

O Concerned

O Unconcerned

O Undecided

1.5 What do you do when faced with a 404 page?

O Exit the page

O Refresh

O Go back to the page I was on

O Other (please state)


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2. Ease of use and complexity of a 404 page

2.1 I find the navigation back to site from a 404 error page easy

O Strongly disagree

O Disagree

O Undecided

O Agree

O Strongly agree

2.2 I find that navigation back to site from a 404 page does not require much mental effort

O Strongly disagree

O Disagree

O Undecided

O Agree

O Strongly agree

2.3 I find that the messaging of the 404 error page informative

O Strongly disagree

O Disagree

O Undecided

O Agree

O Strongly agree


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3 Behavioural intention

3.1 A 404 error page will not stop me from returning to the online site

O Strongly disagree

O Disagree

O Undecided

O Agree

O Strongly agree

3.2 Are you more likely to return to a website after encountering a 404 page if you think the retailer exceeds expectations?

O Yes, I am more likely to return to the website if I think the retailer exceeds expectations O No, my expectations regarding the retailer do not affect my chances of continuing my shopping. I.e. my decision to going back is not effected by my perceptions of the retailer.

3.3 I would prefer the brand to automatically redirect to the homepage without a 404 error notification page.

O Strongly disagree

O Disagree

O Undecided

O Agree

O Strongly agree

3.4 Is the look of the page important when considering to return to the website

O Yes

O No

3.5 How many times will you attempt to access the branded page before giving up?

0 1-‐3 4-‐5 6+


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4. Personal data 4.1. What is your gender?

O Male

O Female

4.2. How old are you?

Under 21 22-‐35 36-‐45 46-‐55 56+

4.3 How frequently do you use the Internet?

O Daily

O Weekly

O More than weekly

4.4. How frequently do you browse online for products?

O Daily

O Weekly

O More than weekly

4.5. What is your salary bracket per month?

£0-‐1k £1-‐3k £3-‐5k £5k+

4.6. How much do you spend on fitness related products per annum?

O Under £100

O £100 -‐ £500

O £500 -‐ £1000

O £1000 -‐ £2000

O £2000+


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5. Retailer Expectations:

5.1 To what extent do you believe this retailer exceeds expectations?

O Extremely

O Very much

O Moderately

O Slightly

O Not at all

5.2 Do you hold an account with this retailer?

O Yes

O No

5.3 Are you thinking of making an account with this retailer?

O Yes

O No

6. Any additional comments (optional)

Thank you for your time


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7 Appendix 2

Figure 6 Original UTAUT2 Model (Venkatesh et al., 2012)

MLT 7 v1.1

Documents

Transcript of MLT 7 v1.1