Assumptions, interviewing

If you do not listen to people, you cannot expect them to listen to you. Communication is a two-way activity. Do not make assumptions about what people know, think, or want done about risks. Take the time to find out what people are thinking. Often, people are more concerned about issues such as trust, credibility, competence, control, voluntariness, fairness, and compassion than about mortality statistics and the details of QRA. Use techniques such as interviews, focus groups, and surveys to gauge what people are thinking. 

The mecin WTP estimates presented hitherto are valid only for the respondents who answered WTP questions in the interviews. However, there are also respondents who rejected the Fund payment vehicle and said that they would accept another payment vehicle, hut none the less did not give any answer to the final WTP question. There were also respondents who rejected all suggested payment vehicles, and there were persons in the sample who refused to participate in the survey altogether. It is important to study the sensitivity of the mean WTP for assumptions regarding the WTP of such groups. Some assumptions that result in a conservative mean WT P estimate for the total sample will he used here. 

F 47 persons were non-respondents. A common conservative assumption in CV studies is to assign a zero WTP to all nonrespondents. However, as was mentioned earlier, this assumption is hardly valid for 30 of the non-respondents, since they refused to he interviewed before they were told the subject of the study. A zero WTP will consequently be assumed to be valid for only 17 of the non-respondents. The mean WTP estimate will be assumed for the remainingSO persons. 

In this type of case, your job is to work through a series of estimations to produce a numerical answer to the question. As the interview proceeds on, you will need to interact with your interviewer, obtain infor-mahon, and check your thinking. Explain your logic at each stage of the problem, and ask your interviewer whether your assumptions are correct. In all likelihood, your interviewer won t provide you with the hard numbers you need for intermediate steps instead, the case asks you to make a few assumptions and devise them yourself. 

The assumption of self-similarity often is applied, almost as a matter of course, when one uses inductive reasoning to predict the properties of a large system on the basis of studies performed on relatively small subsystems thereof. This holds true not only in the physical sciences but for other areas of research as well. For example, statisticians obviously are only able to interview very limited samples of human populations. To generalize such findings to an entire population it is assumed that testimony elicited from the small sample accurately reflects opinions held by all members. Thus, the (response distribution of the) population is assumed to be self-similar, on the scale set by the sample size. This assumption can be tested by interviewing several samples, each consisting of a different number of participants. If the distributions of opinions are identical for all samples beyond a certain threshold size, it then is concluded that results based on the larger samples accurately represent the population as a whole, that is, the distribution is asymptotically self-similar . 

A stmctured employment interview could also be used to measure knowledge which is required to work in a safe manner. Obviously this knowledge will be idiosyncratic to the job in question. The job-relevant knowledge which an applicant has is often inferred based on their work and education history. While there should, for example, be a relationship between education and what an applicant s knows, it is not always wise to make this assumption. Furthermore, employees are going to expect (assume) that new employees do have the knowledge necessary to perform their job in safe manner. 

The inclusion of external use/need knowledge is also one of the main issues of marketing science (Hauser et al. 2006), and remains a remarkable challenge for research and practice (Marketing Science Institute 2010). This task can be attributed to marketing research in organizations (McDaniel and Gates 2008). Many different methods have been developed to assess customer needs, which can be broadly divided Into quantitative (conjoint analysis, quality function deployment) and qualitative techniques (focus interviews, consumer workshops). All of these methods rely on the assumption that users or consumers have the ability to articulate or express their needs. Yet this is only possible for those needs, of which customers are aware themselves. Latent needs, which are crucial for the development of new product, cannot be acquired via these techniques, as they cannot be made explicit by users (Narver et al. 2004). 

The date of the intake may be definitely known if an incident occurred that resulted in the bioassay measurement(s) being made. Otherwise, a review of records and an interview of the individual should be performed. A review of radiation work permits may indicate when an individual had the potential for an intake of the material of concern even if no intake was suspected at the time, or an interview of the individual may reveal a particular occurrence that could have resulted in the intake. If multiple bioassay measurements are made over a period of time, it may be possible to fit a plot of the data and back-calculate the date of the intake. If none of these are possible, the default assumption is to assume the intake occurred at the midpoint between the positive measurements and any previous bioassay measurements that would have detected the material. Use of the midpoint strikes a balance between conservatively estimating the intake and overconservatism. 

See for example Tilli and Trevelyan (2007) An underlying assumption that has informed our thinking about engineering work is that training and experience is an essential component of the first few years of an engineering career. This assumption is based on data from the framework study interviews in which all participants said that it took between two and five years for a novice to become competent . While each participant had a different interpretation of competence, all identified this early career period as important . 

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