The over-optimism among experts in assessment and foresight

It is still disputed whether foresight exercises should be based on top-expert assessments or on a broader base of less specialised experts, and whether the self-rating of experts is an acceptable method. Using the German 1993 and the Austrian 1998 Technology Delphis, this study addresses both questions. Self-rating is, in fact, an appropriate method for selecting experts. But the assessment of self-rated top experts tend to suffer from an optimism bias due to the experts' involvement and their underestimation of realisation and diffusion problems. The degree of optimism is positively correlated with the degree of self-rated knowledge, and it is more pronounced for the least pioneering and for organizational innovations. Experts with top self-ratings working in business have a stronger optimism bias than those working in the academia or in the administration: Consistent with the insider hypothesis, they are most optimistic with regard to realisation, innovativeness, and potential leadership in economic exploitation. Given the optimism bias, foresight exercises should base their panels on a fair mixture of experts of different grades, with different types of knowledge and affiliation, and not only on top specialists of the respective field. Delphi-type exercises, therefore, offer an advantage relative to forum groups or small panels of specialists.     

Classical meets modern in the IDEA protocol for structured expert judgement

Expert judgement is pervasive in all forms of risk analysis, yet the development of tools to deal with such judgements in a repeatable and transparent fashion is relatively recent. This work outlines new findings related to an approach to expert elicitation termed the IDEA protocol. IDEA combines psychologically robust interactions among experts with mathematical aggregation of individual estimates. In particular, this research explores whether communication among experts adversely effects the reliability of group estimates. Using data from estimates of the outcomes of geopolitical events, we find that loss of independence is relatively modest and it is compensated by improvements in group accuracy.     

基于AHP法的建筑公司财务风险评价

针对建筑公司财务管理的现状,提出了在财务管理中应用AHP法进行财务风险评价,同时结合模糊数学理论,构建了一个财务风险评价定性化与定量化结合的指标体系,并基于AHP法对建筑公司进行了财务风险评价。     

从以专家为主导到以农民为主导的实地研究

参与式理念已经成功地应用于许多农业发展项目,在农业研究项目中我们尝试应用以农民为主导的实地研究方法。在外来者的参与下,由农民讨论和制定研究计划,由农民实施和管理研究项目。实践证明,以农民为主导的实地研究,完全符合当地的自然和社会条件,产生了良好的社会经济效益。     

Reining in auditors: On the dynamics of power surrounding an “innovation” in the regulatory space

In the aftermath of Enron and the collapse of Arthur Andersen, new “independent” institutions were created to oversee financial auditing. Based on a modified version of Lukes’ multidimensional model of power, we first investigate how the creation of the Canadian Public Accountability Board (CPAB) has affected the dynamics of power among the main players enlisted in Canada’s regulation of public accounting. Our findings strengthen the view that a “form of allegiance” was, at the time of data collection, developing between CPAB and the largest Canadian accounting firms. Through a second analytical movement, we extend the boundaries of our argument, showing that patterns of resistance against the logic of arm’s length regulation operate in a variety of audit regulatory sites. Our conclusion points, in particular, to the spatial gap - and incidentally the limitations - of any attempt to control and supervise a globalized industry from a national or regional perspective.     

Mixture of MLP-experts for trend forecasting of time series: A case study of the Tehran stock exchange

A new method for forecasting the trend of time series, based on mixture of MLP experts, is presented. In this paper, three neural network combining methods and an Adaptive Network-Based Fuzzy Inference System (ANFIS) are applied to trend forecasting in the Tehran stock exchange. There are two experiments in this study. In experiment I, the time series data are the Kharg petrochemical company’s daily closing prices on the Tehran stock exchange. In this case study, which considers different schemes for forecasting the trend of the time series, the recognition rates are 75.97%, 77.13% and 81.64% for stacked generalization, modified stacked generalization and ANFIS, respectively. Using the mixture of MLP experts (ME) scheme, the recognition rate is strongly increased to 86.35%. A gain and loss analysis is also used, showing the relative forecasting success of the ME method with and without rejection criteria, compared to a simple buy and hold approach. In experiment II, the time series data are the daily closing prices of 37 companies on the Tehran stock exchange. This experiment is conducted to verify the results of experiment I and to show the efficiency of the ME method compared to stacked generalization, modified stacked generalization and ANFIS.     

专家对19世纪上半期德国交通政策的影响分析

19世纪上半期,德国的一批专家对政府的交通政策产生了较大的影响。他们给当时奋发向上的市民提供了社会舆论支持,同时他们自己又在更高的舞台上表演。他们在“是否采纳铁路作为交通工具”、“大技术体系”等方面进行了充分的讨论,给政府提供了富有建设性的意见,并由此创造了学者政治的模式。专家们并不谋求直接在政治上发展,而是把自己看成超党派的公众的良心;而政府听取他们的意见,则体现了政府尊重科学的明智之举。     

Bound by Gravity or Living in a ‘Post Geography Trading World’?* Expert Knowledge and Affective Spatial Imaginaries in the Construction of the UK’s Post-Brexit Trade Policy

A key battle has been fought within the UK cabinet on the direction of post-Brexit trade policy. The opposing sides have favoured either continued alignment or a ‘hard’ break with the European Union’s (EU’s) regulatory and customs regime, in the latter case to allow the UK to pursue an independent and ambitious trade policy agenda. Contrary to much commentary on ‘post-truth’ politics, both sides have relied on rival forms of expertise to support their claims. I argue for the need to not only re-emphasise the malleability and political nature of expert knowledge, but also appreciate its emotional bases. The Treasury has led the charge in favour of a softer Brexit by drawing on econometric (‘gravity’) models that emphasise the economic costs of looser association with the EU. In contrast to this attempt at technocratic legitimation, the specific legal expertise drawn upon by cabinet advocates of ‘hard’ Brexit has appealed to an emotive political economy of bringing the UK, and its (in this imaginary) overly regulated economy, closer to its ‘kith and kin’ in the Anglosphere, deepening the UK ‘national business model’. I conclude by calling for more explicitly emotive and values-based argumentation in the public debate on the UK’s future trade policy to improve the quality of democratic deliberation.     

Experts' Views on Societal Risk Attention1

The search for a process by which agencies, whether at the national or the local level, might either rank or prioritize disparate risks has been on the minds if not the agenda of policy makers for some decades at least. In the absence of an agreed methodology, risk management practitioners in government, industry, and other walks of life have, through necessity, developed their own. Inspection reveals, however, that many of these are grounded in particular ideologies which may be associated with discrete professional world views or systems of working. It is apparent, however, that even subtle differences in methodologies can generate radically different rankings and, ultimately, actions. Thus, while the ranking of risks as a means of setting goals and prioritizing actions is a crucial activity, the process by which it is conducted may have an overwhelming influence upon the outcome, which in turn might bear little resemblance to the aspirations of stakeholders. It is suggested that more attention needs to be devoted to the assumptions and values inherent in ranking procedures, even those previously regarded as 'objective,' and to the ways in which these, together with artefacts of the ranking procedure itself, may affect outcomes. In the longer term, a shift towards a more holistic prioritization process is seen as highly desirable. Failure to achieve this could mean that neither local nor societal goals are properly accommodated.