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Information Needs Analysis
If you want to provide an information service that truly fulfils your users' needs, this book is essential reading. The book supports practitioners in developing an information needs analysis strategy and offers the necessary professional skills and techniques to do so.
eBook
How much is new information worth? Evaluating the financial benefit of resolving management uncertainty
Conservation decision‐makers face a trade‐off between spending limited funds on direct management action, or gaining new information in an attempt to improve management performance in the future. Value‐of‐information analysis can help to resolve this trade‐off by evaluating how much management performance could improve if new information was gained. Value‐of‐information analysis has been used extensively in other disciplines, but there are only a few examples where it has informed conservation planning, none of which have used it to evaluate the financial value of gaining new information. We address this gap by applying value‐of‐information analysis to the management of a declining koala Phascolarctos cinereus population. Decision‐makers responsible for managing this population face uncertainty about survival and fecundity rates, and how habitat cover affects mortality threats. The value of gaining new information about these uncertainties was calculated using a deterministic matrix model of the koala population to find the expected population growth rate if koala mortality threats were optimally managed under alternative model hypotheses, which represented the uncertainties faced by koala managers. Gaining new information about survival and fecundity rates and the effect of habitat cover on mortality threats will do little to improve koala management. Across a range of management budgets, no more than 1·7% of the budget should be spent on resolving these uncertainties. The value of information was low because optimal management decisions were not sensitive to the uncertainties we considered. Decisions were instead driven by a substantial difference in the cost efficiency of management actions. The value of information was up to forty times higher when the cost efficiencies of different koala management actions were similar. Synthesis and applications. This study evaluates the ecological and financial benefits of gaining new information to inform a conservation problem. We also theoretically demonstrate that the value of reducing uncertainty is highest when it is not clear which management action is the most cost efficient. This study will help expand the use of value‐of‐information analyses in conservation by providing a cost efficiency metric by which to evaluate research or monitoring.
Journal Article
Rough set-based rule generation and Apriori-based rule generation from table data sets: a survey and a combination
The authors have been coping with new computational methodologies such as rough sets, information incompleteness, data mining, granular computing, etc., and developed some software tools on association rules as well as new mathematical frameworks. They simply term this research Rough sets Non-deterministic Information Analysis (RNIA). They followed several novel types of research, especially Pawlak's rough sets, Lipski's incomplete information databases, Orłowska's non-deterministic information systems, Agrawal's Apriori algorithm. These are outstanding researches related to information incompleteness, data mining, and rule generation. They have been trying to combine such novel researches, and they have been trying to realise more intelligent rule generator handling data sets with information incompleteness. This study surveys the authors’ research highlights on rule generators, and considers a combination of them.
Journal Article
The Value of Value of Information
Value of information (VOI) methods have been proposed as a systematic approach to inform optimal research design and prioritization. Four related questions arise that VOI methods could address. (i) Is further research for a health technology assessment (HTA) potentially worthwhile? (ii) Is the cost of a given research design less than its expected value? (iii) What is the optimal research design for an HTA? (iv) How can research funding be best prioritized across alternative HTAs?
Following Occam’s razor, we consider the usefulness of VOI methods in informing questions 1–4 relative to their simplicity of use. Expected value of perfect information (EVPI) with current information, while simple to calculate, is shown to provide neither a necessary nor a sufficient condition to address question 1, given that what EVPI needs to exceed varies with the cost of research design, which can vary from very large down to negligible. Hence, for any given HTA, EVPI does not discriminate, as it can be large and further research not worthwhile or small and further research worthwhile. In contrast, each of questions 1–4 are shown to be fully addressed (necessary and sufficient) where VOI methods are applied to maximize expected value of sample information (EVSI) minus expected costs across designs.
In comparing complexity in use of VOI methods, applying the central limit theorem (CLT) simplifies analysis to enable easy estimation of EVSI and optimal overall research design, and has been shown to outperform bootstrapping, particularly with small samples. Consequently, VOI methods applying the CLT to inform optimal overall research design satisfy Occam’s razor in both improving decision making and reducing complexity. Furthermore, they enable consideration of relevant decision contexts, including option value and opportunity cost of delay, time, imperfect implementation and optimal design across jurisdictions.
More complex VOI methods such as bootstrapping of the expected value of partial EVPI may have potential value in refining overall research design. However, Occam’s razor must be seriously considered in application of these VOI methods, given their increased complexity and current limitations in informing decision making, with restriction to EVPI rather than EVSI and not allowing for important decision-making contexts. Initial use of CLT methods to focus these more complex partial VOI methods towards where they may be useful in refining optimal overall trial design is suggested. Integrating CLT methods with such partial VOI methods to allow estimation of partial EVSI is suggested in future research to add value to the current VOI toolkit.
Journal Article
The Limits of Price Discrimination
We analyze the welfare consequences of a monopolist having additional information about consumers' tastes, beyond the prior distribution; the additional information can be used to charge different prices to different segments of the market, i.e., carry out \"third degree price discrimination.\" We show that the segmentation and pricing induced by the additional information can achieve every combination of consumer and producer surplus such that: (i) consumer surplus is nonnegative, (ii) producer surplus is at least as high as profits under the uniform monopoly price, and (iii) total surplus does not exceed the surplus generated by efficient trade.
Journal Article