User – Centered Hotel Website Design

Human – Computer Interaction theory proposes that user-centered design (UCD) is the most recognized approach to design successful hotel websites. UCD is ideal to design hotel websites following customers’ critical information requirements. UCD considers the user’s needs and involves the user throughout the design process (Dix, et al, 2004).

Figure 12: The principles and activities of UCD detailed in ISO 13407

NO

YES

COMPLETE

Source: Harrison, 2008

Figure 12 provides a step by step UCD process, with the first step being to plan the UCD process, step two is specifying the context of use, step three involves specifying the user characteristics, step four is to produce the design with step five being evaluation. If requirements are met then the user will proceed with the booking / checkout; if not designers are directed back to step two. Similarly, the online decision making process for a hotel booking, the user at the step of the “meet requirements” YES / NO, the user will stay or leave the webpage.

For the purposes of this study will be as follows:

1. Plan the User – Centered Hotel Website Design process 2. Specify CCIRs

1 .Plan the UCD process

2. Specify the context of use 3. Specify user requirements

4. Produce design solutions 5. Evaluate design against user requirements

Meet requirements

53 3. Specify website design

4. Produce a website design

5. Evaluate website design against CCIRs

6. If CCIRs are met, then the hotel will take the booking

7. If CCIRs are not met, then the hotel website should be (re)designed

4.9 Usability

According to Abran et al., (2003), usability is “the extent to which a product can be used by specified users to achieve specified goals with effectiveness, efficiency and satisfaction in the specified context of use”. An interesting definition comes from Quesenbery (2004), who states that usability means that people who use the product or service can achieve their tasks easily and quickly. Consequently, users who wish to book online should be provided by all these customers’ critical information requirements so as to successfully proceed with the booking.

Chappel and Huang (2007) differentiate the definition of usability of web-usability; they state that web-usability is “a quality attribute that assesses how easy user interfaces are to use”. Therefore, usability is a critical factor for a successful and smooth online decision making process. According to Roach (2007), usability describes the degree of ease in using a website to achieve a particular task by allowing users access and the ability to navigate smoothly. Following Lehtinen (2007) study, usability research focuses on users: how users find their way to use a product, do they find using it easy, and if the product can help them to achieve their preset goals. Usability studies focus on how the product can be more usable for users and not on the product itself.

According to Nielsen (1993), usability consists of five components: easy to learn (The system should be easy to learn and understand. It should be easy for the user to get their job or task executed using the software system), efficient to use (Efficiency of the system is directly related to its productivity. The more efficient a system is its throughput is correspondingly high), easy to remember (It is best suited for intermittent users. The user can return to the system’s previous state without starting away from the beginning), few errors (the prevention of catastrophic errors is relevant for applications such as process control or medical applications), and pleasant to use task (It is the

54 pleasant feeling that user gets while or after using the system. It can be observed as likeability for the system and fulfilment of specified).

The international organization of standardization (ISO 9214-11, 1998) gave a model consisting of three basic sub attributes, namely effectiveness (It is the performance measure of a system to complete a specified task or goal successfully within time), efficiency (It is the successful completion of a task by a system. It relates to accuracy and completeness of the specified goal), and satisfaction (It is acceptability of a system by the users, in a specified context of use). Then, ISO 9126 (2001) suggest the following sub attributes of usability namely understandability (The capability of the software product to enable the user to understand whether the software is suitable, and how it can be used for particular tasks and conditions of use), learnability (The capability of the software product to enable the user to learn its application), operability (The capability of the software product to enable the user to operate and control it), attractiveness (The capability of the software product to be attractive to the user), usability compliance (The capability of the software product to adhere to standards, conventions, style guides, or regulations related to usability).

4.9.1 Usability Testing and Eye Tracking Approach

Eye tracking is not a new method for usability testing. It is being used since 1950 (table below). However, nowadays it has become a key method for usability testing, especially of webpages. It is used in many areas of research as it provides indisputable, valid, objective and accurate data presenting usability problems and the user’s behaviour. For quantitative eye tracking analysis, Goldberg and Kotval (1999) summarize methods for analysing eye tracking data for computer-based usability studies, such as assessing the length of a scan path and comparing fixation durations. The below table is a summary of various usability studies incorporating eye tracking in chronological order from 1950 to 2012. It provides information about users recruited for the study, main tasks and eye tracking metrics observed and analyzed.

Table 2: Usability Studies incorporating eye tracking in chronological order

Authors / Date

Users and Tasks Eye Tracking Related Metrics

Fitts, Jones

• Gaze duration mean, on each area of interest

• Gaze % (proportion of time) on each area of interest

• Transition probability between areas of interest Harris and

Christhilf,

4 instrument-rated pilots.

Flying maneuvers in a

• Gaze % (proportion of time) on each area of interest

• Gaze duration mean, on each area of interest

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• Number of fixations on each area of interest (line of text)

• Number of words per fixation

• Fixation rate overall (fixations / S)

• Fixation duration mean, overall Card, 1984 3 PC users. Searching for

and selecting specified

• Fixation rate overall (fixations / S)

• Fixation duration mean, overall

• Number of fixations on each area of interest

• Fixation rate on each area of interest

• Fixation duration mean, on each area of interest

• Gaze duration mean, on each area of interest

• Gaze % (proportion of time) on each area of interest

• Transition probability between areas of interest Graf and

• Number of voluntary (>320 mS) fixations, overall

• Number of involuntary (<240 mS) fixations, overall

• Number of fixations on target Benel, Ottens

and Horst, 1991

7 PC users. Viewing web pages

• Gaze % (proportion of time) on each area of interest

• Scan path

• Fixation rate overall (fixations / S) Yamamoto

• Number of instances of backtracking

Svensson, et

• Gaze duration mean, on each area of interest

• Frequencies of long duration dwells on area of interest

Altonen, et al.,

• Sweep –scan path progressing in the same direction

• Number of fixations per sweep Ellis et al.,

• Number of fixations on each area of interest

• Time to 1^st fixation on target area of interest

• Gaze % (proportion of time) on each area of interest Kotval and

• First area of interest fixated

• Number of fixations on each area of interest

56

• Gaze % (proportion of time) on each area of interest

Redline and

• Number of fixations on each area of interest

• Fixation duration mean, on each area of interest

• Saccade length

• Fixation duration total, on each area of interest

• Number of areas of interest fixated

• Scan path length

• Scan path direction

• Transition probability between areas of interest Albert, 2002 24 intermediate to

• Number of fixations on area of interest (banner ad)

• Gaze % (proportion of time) on each area of interest

• Participant % fixating on each area of interest

Cooke, 2006 10 people from Department of Technical

30 participants • Mean response time

• Fixation filter values (radius of 50 pixels)

• Fixation duration (min 100ms)

Following Table 2, most commonly used eye tracking metrics are number of fixations overall, the proportion of time (Gaze %) on every area of interest, fixation and gaze duration on each area of interest, and fixation rate overall. All eye tracking statistics metrics are discussed in Chapter 5, Methodological Review under the 5.14 Eye tracking metrics.

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