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The mixed method is not, however, without disadvantages or detractors. Critics of this methodology often cite the risk of the ‘incompatibility paradox’; the probability that one data type will be inadequately analysed compared to the other. A prominent example of this risk is known as ‘pragmatism’, or the perception that researchers who use the mixed method value ‘experiential data’ (. self-reports recorded from respondents) at the expense of quantitative data. The use of the mixed method may also be subject to preconceptions, judgement or other forms of observer bias that a researcher may impose on qualitative data in the course of its collection. These risks can be ameliorated, mainly through the skill and training of the individual researcher. Under these conditions, the mixed-method technique can be applied to generating full, comprehensive conclusions for non-standard research questions.
Data mining is another area that has tremendous applications for e-commerce. Because a huge amount of information is made available through digital systems, and this information can be collated from various sources to glean more information than the individual would expect, customer privacy issues have come to the fore. Legislation such as the Data Protection Act 1998 and the Freedom of Information Act 2000 are aimed at protecting the interests of the lay citizen. Technology such as RFID tagging has further enabled data mining in an unprecedented scale. Some e-commerce dissertation topics in this area are: