This thesis investigates the problem of strategic bias in discrete choice experiments using three approaches: simulations, a laboratory experiment, and a field experiment. Carson et al. (2007) state that choice experiments must be seen as consequential by respondents in order to provide useful information about preferences. To meet this requirement, surveys must exhibit two characteristics. First, the survey must be seen as influencing the provision of the good/service and second, the respondent must care about that provision outcome. However, the notion that the survey must be consequential, may also induce respondents to misrepresent their preferences in order to influence the decision making process. This is known as strategic bias. Using simulations, laboratory experiments and field studies, this thesis will investigate strategic bias in discrete choice experiments. To do so, we must assume that the discrete choice experiment will be used to influence a provisioning decision. Strategic behaviour is conceptualised as changes in choice behaviour that occurs when respondents have information on the relative likelihood of the provision outcomes. This information causes changes in choice strategies. In Chapter 1 we create a simulated environment that replicates when respondents may have incentive to bias their choice strategies. We explore the ramifications of biased choices through simulations. In Chapter 2 we replicate that environment in an induced value laboratory experiment. We present respondents with three possible `provision' outcomes, each of which was defined in terms of levels of arbitrary attributes. Each possible provision outcome was associated with a monetary payout to the respondent, therefore we know a respondents preference ordering over the possible outcomes. The monetary payouts varied such that there was a clear ranking between possible outcomes, such that respondents had a first, second and worst provision outcome. Respondents then completed a discrete choice experiment (DCE) that would decide which provision outcome is paid out. A respondent's payout was determined by which of the competing provision outcomes had the highest choice probability, based on their individual choice behaviour. As this was an unlabelled choice experiment, participants had to use choice strategies based on attributes in order to influence the provision outcome they hoped would get paid out. To introduce strategic bias, respondents were given information on the likelihood of the provision contenders being implemented. This information would affect which provision outcome would be chosen and hence paid out. In this respect, a respondent has incentive to act strategically if they believe (i) their first best outcome will lose in the final provision decision; (ii) their worst outcome is most likely to be paid out; and (iii) their choices can influence the provision to deliver the second best outcome. Strategic respondents are therefore those who chose to target their second best outcome to avoid worst outcome, which respondents are told is the most likely. We find approximately 27% of respondents exhibit strategic behaviour in the laboratory choice experiment. In Chapter 3 we implement the approach in the field. We administered a choice experiment about tidal energy development in Puget Sound, Washington. Local opposition to tidal energy has been strong in the past, with no project ever coming to fruition. As a result, we envision respondents to have strong sentiments towards the location of tidal energy development and potentially have incentives to behave strategically when location is a factor in their decision making process. We presented respondents with three possible site locations for tidal energy development in Puget Sound. Respondents can use the choice experiment as a means to reveal which site location they prefer (if any). As this was an unlabelled experiment, respondents must use choice strategies based on the attributes of tidal development in order to reveal preference for location. In order to identify strategic behaviour, rather than simply differences in preferences, half way through the DCE, we provide respondents with additional information on the likelihood of each of the tidal energy sites being chosen. Respondents whose first best location is revealed as the site least likely to be chosen, may seek to secure their second best location. Strategic bias is when respondents are trying to push preference away from their worst location site, when the set of provision outcomes has gone from three to two possible sites. Despite the complexity of the task, there is evidence of behavioural changes when the final set of possible locations changes. We find that 25% of respondents exhibit signs of strategic behaviour. These respondents are more likely to 1) believe their survey responses will affect future policy; and, 2) prefer the site which was revealed to be the unlikely site location and thus have strong motive to push development away from their worst location, and towards a second best site.