Currently, there are no commonly accepted standard measurements for website success in the tourism industry (Gupta and Utkarsh 2014; Estêvão et al. 2014), leading most DMOs to simply track visits or measure basic forms of conversion
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(online brochure requests, or actual travel after visiting the website). Although these kinds of evaluation measures are valuable to an extent, they give little insight into what aspects of the website have encouraged certain attitudes or behaviours, and how the web design, structure and content, could be improved. Scholars have not reached a consensus on the construct of a comprehensive and standardised website evaluation measurement, for website effectiveness.
Wang and Fesenmaier (2006) have suggested that the key ingredients to successful web-based destination marketing, include identifying, developing, and analysing the factors that can influence, or even shape, customer needs, thus suggesting that website development and evaluation efforts. Mena (2002) proposed that the success or failure of any website evaluation framework, is largely reliant on the quality and depth of its information (Mena 2002). Therefore, it is important to firstly identify the evaluation dimensions and criteria that need to be included in the evaluation framework (Law and Cheung 2005). The necessity of identifying checklists, or evaluation dimensions and criteria, is essential for the construction of a comprehensive and standardised evaluation framework.
Previous studies of website evaluations, provided checklists or criteria, in order to compare and rank them. The checklists or evaluation criteria factors in previous evaluation studies have been labelled in many ways, such as website evaluation, e-satisfaction, website quality, e-quality, e-loyalty, etc. (Park and Gretzel 2007; Gupta and Utkarsh 2014). The evaluation checklists or criteria have been adopted or modified from existing models or evaluation instruments, in order to evaluate selected websites. They have been identified according to their importance to the success of a website (Daniele and Frew 2008). In their study, Park and Gretzel (2007) adopted a qualitative meta-analysis methodology, to synthesise the diverse findings from previous studies, in order to find the commonly used website success factors. The evaluation factors that emerged from the analysis included a total of nine factors: information quality; ease of use; responsiveness; security/privacy;
visual appearance; trust; interactivity; personalisation; and fulfilment.
The number of dimensions and criteria considered in the previous website evaluation studies, has varied dramatically (Johnson et al. 2012; Fernández-Cavia et al. 2013; Gupta and Utkarsh 2014; Del Vasto-Terrientes etl. 2015), making it difficult to compare the findings and identify factors that have consistently been used to evaluate websites. This situation has also led to a great deal of replication, and
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little progress in understanding the key factors that should be included in website evaluation frameworks. Therefore, there is a need to identify a comprehensive, standardised set of dimensions and criteria for website evaluation, and house them in a comprehensive evaluation framework.
There is also a need to weight the identified dimensions and criteria, accordingly.
Weightings are essential for two reasons; firstly, they are an indicator of the importance of individual features and areas; and secondly, they are a means to evaluate the overall effectiveness of a web ’ L w C 2005).
Dimensions and criteria should not be of equal importance (Lu et al. 2002). For B ’ w regarded as a more important factor than content. Therefore, not all website dimensions and criteria have the same level of importance, and, so there is a definite need for the appropriate weighting to be attributed to them (Welling and White 2006).
Once the weighting of the dimensions and criteria have been determined within the identified evaluation framework, the next stage of a website evaluation process should be to decide upon how to measure these weighted evaluation dimensions and criteria. More often, previous website evaluation studies relied either on expert assessments or consumer opinions, to measure these identified evaluation dimensions and criteria. The information required to measure these effectiveness factors has often been taken from customers, either without their knowledge or consent (from the analysis of web server logs), or with their consent, through a variety of methods including direct feedback, online and offline surveys, and focus groups (Horan 2001; Young Hoon and Mincheol 2010). Although these methods are very useful for informing management of what is happening on the website, the nature of an effective evaluation methodology must be comprehensive. This means that the inclusion of a variety of stakeholder viewpoints in assessing the effectiveness, is essential (DeLone and McLean 2003). The stakeholders should include the customers, the suppliers, and the systems management. Unfortunately, the majority of previous studies lacks a comprehensive framework for website evaluations.
It is crucial that a comprehensive evaluation framework of this nature, which combines a set of weighted evaluation dimensions and criteria, should handle a statistical variability between the metrics, whilst remaining effective. The lack of a
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robust, comprehensive methodology that houses a set of weighted dimensions, assessed by different stakeholders, is a critical limitation of the previous evaluation studies.
Another important issue that should be taken into consideration when developing a comprehensive evaluation framework, is what exactly the website performance should be measured against. Firstly, if we assess the dimensions and criteria against the optimum effectiveness, this means that each of them will be evaluated against the maximum performance that could be achieved. However, this could be suitable for some criteria, but not at all, for others. For example, in the case of website conversion, it is unrealistic to expect a website to achieve a 100%
conversion rate. Therefore, it is illogical to set website aims that are too high.
Secondly, if we benchmarked against peer, DMS websites, it would ancillary approach used once an internal performance measurement approach has already taken place, and it is beyond the scope of developing a standardised and comprehensive evaluation framework, once this evaluation is conduced. Thirdly, if we mea w ’ DMO would provide the most appropriate set of results for a specific website under investigation, and would be the best option for an effective evaluation to take place.
A standardised website measurement instrument, which addresses the website strategy as a guideline for developing websites, means that organisations will be able to measure how successful their website strategies are, with respect to their goals. The consistency between website strategy and website presence can help w w w w fi fi ’ objectives, in the virtual marketplace.
Although it is possible to adopt standard syntactic models to evaluate destination w “ ” k account the semantics of the website under assessment (Mich et al. 2005). There were very few attempts to construct such a standardised evaluation framework for websites, and the early attempts only started in 2010. The following section examines two of these attempts, which moved towards a comprehensive evaluation framework view of website evaluations.
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