Expert leaders in a fast-moving environment

This longitudinal study explores the influence of leaders on performance in the iconic, high-technology, turbulent industry of Formula One. The evidence is evaluated through the emerging theory of expert leadership which proposes the existence of a first-order requirement: it is that leaders should have expert knowledge in the core-business of the organizations they are to lead (holding constant management and leadership experience). The study's findings provide strong support for the ‘expert leader’ hypothesis. The most successful F1 principals are disproportionately those who started their careers as drivers. Moreover, within the sub-sample of former drivers, it is those who had the longest driving careers who went on to become the most effective leaders. The study's expert-leader findings are consistent with the hypothesis that longitudinal performance improves when a leader's knowledge and expertise correlate with an organization's core-business activity.     

Assessing global leadership competencies: the critical role of assessment centre methodology

The purpose of this conceptual paper is to examine the use of assessment centre (AC) methodology for addressing the ever-increasing demand for effective talent management of global leaders. Research is reviewed on the most commonly used questionnaire tools for assessing global leadership competencies, which lack the AC’s ability to provide behavioural evidence of leadership competency. A literature search is conducted to identify the extent to which scholarly research to date has examined the use of ACs to measure global leadership competencies. Based on the findings from the review of the literature, the authors recommend further exploration of a leadership AC approach as a ‘best practice’ talent management tool for measuring global leadership competencies. A framework is provided for designing ACs to evaluate and provide developmental feedback on the competencies identified as critical for successful leadership performance in an organization’s global environment.     

Expert system for production manager recruitment

Abstract

Production manager recruitment poses a three-fold problem: finding a broad-knowtedged recruiter; obtaining an objective evaluation of the candidate; and the ever present risk of accepting unqualified candidates and rejecting qualified candidates A prototype expert system (ES) was developed for the purpose of testing the technical potential for computer assisted recruiting. The ES embodied a three-fold strategy: probing the candidate's past; asking questions from a business case study; and from several human-behaviour, video-taped episodes. The candidate's responses are graded, rated for competency (excellent, good, fair, poor), and weighted. A hiring action is recommended based on the composite weight. The prototype effectively demonstrated thit potential for expert system-conducted recruiting.     

Engaging Expert Peers in the Development of Risk Assessments

The participation of external technical experts in the development of risk assessment documents and methodologies has expanded and evolved in recent years. Many government agencies and authoritative organizations have experts peer review important works to evaluate the scientific and technical defensibility and judge the strength of the assumptions and conclusions (OMB, 2004; IPCS, 2005; IARC, 2006; Health Canada, 2007; U.S. EPA, 2006). Expert advice has been solicited in other forms of peer involvement, including peer consultation in, for example, the U.S. EPA's Voluntary Children's Chemical Evaluation Program (VCCEP). This article discusses how the principles and practices of peer review can be extended to other types of peer involvement activities (i.e., peer input and peer consultation) to develop high-quality risk assessment work products. A comprehensive process for incorporating peer input, peer consultation, and peer review into risk assessment science is outlined. Four key principles for peer involvement-independence, inclusion of appropriate experts, transparency, and a robust scientific process-are discussed. Recent examples of peer involvement in the development of Health Canada's Priority Substances and Domestic Substance List (DSL) programs under the Canadian Environmental Protection Act (CEPA) serve to highlight the concepts.     

Judgment Error and Expert Critics in Forecasting Tasks*

This paper presents an approach to elicit and critique intuitive forecasts. It attempts to retain the valid component of experts' judgments while correcting some biases. Decision science and expert system techniques were unified with the design of an expert critiquing system. A real world application of the resulting critic verifies the approach. A discussion addresses how to create a similar critic for other forecast settings.     

State-of-the-Art Developments in Expert Systems and Strategic Marketing Planning

This paper describes a case history of the development of an Expert System in Strategic Marketing Planning codenamed EXMAR. It traces the evolution of the system from the formation of the DTI club two years ago to the launch of the prototype model. The paper outlines the technical and domain–specific obstacles encountered en route and how these were overcome. A number of conclusions are drawn from the project. The principal one is that there is a bright future for expert systems in the field of strategic management. Professor Malcolm McDonald is the principal expert to the club. Hugh Wilson is a senior consultant with Artificial Intelligence Ltd. He was also the knowledge engineer and the project manager. For readers who would like a simple explanation of Expert Systems, please refer to Professor McDonald's paper ‘Marketing Planning and Expert Systems: an Epistemology of Practice’, Marketing Intelligence and Planning, 7, 7/8, 1989.     

Validating Expert Systems: A Demonstration Using Personal Choice Expert,A Flexible Employee Benefit System*

A method for validating expert systems, based on validation approaches from psychology and Turing's “imitation game,” is demonstrated using a flexible employee benefits expert system. Psychometric validation has three aspects: the extent to which the system and expert decisions agree (criterionrelated validity), the inputs and processes used by experts compared to the system (content validity), and differences between expert and novice decisions (construct validity). If these criteria are satisfied, then the system is indistinguishable from experts for its domain and satisfies the Turing Test. Personal Choice Expert (PCE) was designed to help employees of a Fortune 500 firm choose benefits in their flexible benefits system. Its recommendations do not significantly differ from those given by independent experts. Hence, if the system-independent expert agreement (criterion-related validity) were the only standard, PCE could be considered valid. However, construct analysis suggests that re-engineering may be required. High intra-expert agreement exists only for some benefit recommendations (e.g., dental care and long-term disability) and not for others (e.g., short-term disability, accidental death and dismemberment, and life insurance). Insights offered by these methods are illustrated and examined.     

Choosing the Right Expert System Building Approach

The analytical hierarchy process (AHP) is used to systematically examine the relative appropriateness of contending expert system building approaches—algorithmic programming languages, symbolic programming languages, expert system shells, and knowledge engineering environments based upon characteristics of application domains and development environments. Two expert system projects, Back Expert, and R&D Expert, illustrate the value of this methodology. Domain and development environment characteristics identified in the AHP approach are then used to construct rule-based and Lotus 1-2-3 expert systems for selecting the right expert system building approach.     

Expert Review on Poliovirus Immunity and Transmission

Successfully managing risks to achieve wild polioviruses (WPVs) eradication and address the complexities of oral poliovirus vaccine (OPV) cessation to stop all cases of paralytic poliomyelitis depends strongly on our collective understanding of poliovirus immunity and transmission. With increased shifting from OPV to inactivated poliovirus vaccine (IPV), numerous risk management choices motivate the need to understand the tradeoffs and uncertainties and to develop models to help inform decisions. The U.S. Centers for Disease Control and Prevention hosted a meeting of international experts in April 2010 to review the available literature relevant to poliovirus immunity and transmission. This expert review evaluates 66 OPV challenge studies and other evidence to support the development of quantitative models of poliovirus transmission and potential outbreaks. This review focuses on characterization of immunity as a function of exposure history in terms of susceptibility to excretion, duration of excretion, and concentration of excreted virus. We also discuss the evidence of waning of host immunity to poliovirus transmission, the relationship between the concentration of poliovirus excreted and infectiousness, the importance of different transmission routes, and the differences in transmissibility between OPV and WPV. We discuss the limitations of the available evidence for use in polio risk models, and conclude that despite the relatively large number of studies on immunity, very limited data exist to directly support quantification of model inputs related to transmission. Given the limitations in the evidence, we identify the need for expert input to derive quantitative model inputs from the existing data.     

Expert and Layperson Perceptions of Ecosystem Risk

This research examines and compares perceptions held by laypeople and ecologists about risks to ecosystems, particularly risk from global climate change (GCC). A survey elicited perceptions of 31 risk characteristics for 13 GCC and 12 non-GCC risks to ecosystems. Factor analysis was used to examine the structure of layperson and expert risk perceptions. Both experts and laypeople tend to perceive GCC risks to ecosystems as less avoidable and more acceptable than risks from other causes. Compared to laypeople's perceptions, though, experts perceived GCC risks to have slightly lower impacts, be less avoidable, more acceptable, and less understandable than non-GCC risks to ecosystems. These findings may help guide efforts to communicate with laypeople about ecological risks from climate change.     

The Value of Performance Weights and Discussion in Aggregated Expert Judgments

In risky situations characterized by imminent decisions, scarce resources, and insufficient data, policymakers rely on experts to estimate model parameters and their associated uncertainties. Different elicitation and aggregation methods can vary substantially in their efficacy and robustness. While it is generally agreed that biases in expert judgments can be mitigated using structured elicitations involving groups rather than individuals, there is still some disagreement about how to best elicit and aggregate judgments. This mostly concerns the merits of using performance‐based weighting schemes to combine judgments of different individuals (rather than assigning equal weights to individual experts), and the way that interaction between experts should be handled. This article aims to contribute to, and complement, the ongoing discussion on these topics.     

A Model-Based Approach to Investigate Performance Improvements in Rule-Based Expert Systems

One of the major issues in the development of large, rule-based expert systems is related to improving their performance efficiency. One way to address this issue is by reducing the number of unsuccessful tries a system goes through before executing a rule to establish a goal or an intermediary fact. On the average, the number of unsuccessful tries can be reduced if the rules that are tried first are those that are expected to execute most frequently, and this can be established by extracting information on the probability distributions of the input parameters. In this paper, a rule base is modeled as a network and simulated to investigate potential performance improvements by changing the order used to test the rules. The model of the rule base is also used to investigate performance gains achieved by parameter factorization and premise clause reordering.     

Expert knowledge,expert systems and commercial interests

Experience to date in building expert systems has brought a general realization of the complexity of the effort required for producing systems capable of operating on ‘real-world’ problems. The most successful knowledge-based/expert systems built to date, e.g. DENDRAL, MYCIN, PROSPECTOR and R1 have demonstrated that a considerable investment in time and dedication on the part of systems designers and experts is required to create a fully operational system. The great majority of development projects attempting to harness this new programming technology do not extend beyond creation of a prototype system largely due to lack of necessary resources, i.e. time, money and know-how. The purpose of this paper is to discuss some of the more important issues associated with development of expert systems and to provide an overview of the commercial and industrial efforts of putting expert systems to work. This paper should be of interest to those who have gained their knowledge of expert systems from the reading of non-specialist publications and thus may have been exposed to somewhat over enthusiastic accounts of the subject.     

Expert and Public Perception of Risk from Biotechnology

Risk perceptions of a series of biotechnology applications were examined in a public (nonexpert) sample and an expert sample. Compared with the experts, the public perceived all biotechnology applications as more risky. Both groups perceived food-related applications to be riskier than medical applications. Compared with the public, experts perceived both food and medical applications as less harmful and more useful. Experts also judged the risks posed from medical biotechnology applications as more familiar and acknowledged by people and science. Lay estimates of the risk of food applications were predicted by potential harm, potential benefits, science knowledge, and familiarity; experts' estimates were predicted only by harm and benefits. Lay estimates of the risk of medical applications were predicted by potential harm; experts' estimates were predicted by potential benefits, number and type of people exposed, and science knowledge. We discuss the implications of the results for risk communication about and management of different types of biotechnologies.     

神经网络生产作业计划专家模拟系统研究

综合人神经网络、遗传算法、计算机模粗及生产作业计划方法等技术,研究集成人神经网络的生产作业计划专家模拟系统功能及构成,探讨其实现机理和工作流程．     

Lay and Expert Interpretations of Cancer Cluster Evidence

Conflict frequently occurs between community members and environmental/public health officials when an unusual number of cancer cases is reported. This conflict may result from different ways in which laypeople and experts interpret facts to judge whether there is an environmental cause of the cancer cases, but little is known about this issue. Volunteer laypeople (N= 551) and epidemiologists (N= 105) read a hypothetical scenario about cases of cancer on one neighborhood block. Participants judged whether each of the 23 facts about the situation made it “much more likely” to “much less likely” that something in town was causing the cancer cases (7‐point scale). The facts were designed to be “alarming,”“reassuring,” or “neutral” (i.e., according to epidemiological principles, should increase, decrease, or have no impact on the likelihood of an environmental cause). The laypeople were alarmed by most of the facts (mean response significantly greater than the scale midpoint), including all of the neutral facts and over half of the reassuring facts. The experts were more balanced: they were alarmed by none of the neutral or reassuring facts. Their responses showed significantly less alarm than the laypeople's responses (p < 0.0001 for all comparisons). This study reveals that laypeople are not reassured by information that substantially lowers the chance of an environmental cause for cancer cases. Lay responses differ significantly and systematically from experts who are far less alarmed by relevant facts. These findings may help explain the conflicts between the two groups in situations where concern about cases of cancer arises in a community.     

Explosion Probability of Unexploded Ordnance: Expert Beliefs

This article reports on a study to quantify expert beliefs about the explosion probability of unexploded ordnance (UXO). Some 1,976 sites at closed military bases in the United States are contaminated with UXO and are slated for cleanup, at an estimated cost of $15–140 billion. Because no available technology can guarantee 100% removal of UXO, information about explosion probability is needed to assess the residual risks of civilian reuse of closed military bases and to make decisions about how much to invest in cleanup. This study elicited probability distributions for the chance of UXO explosion from 25 experts in explosive ordnance disposal, all of whom have had field experience in UXO identification and deactivation. The study considered six different scenarios: three different types of UXO handled in two different ways (one involving children and the other involving construction workers). We also asked the experts to rank by sensitivity to explosion 20 different kinds of UXO found at a case study site at Fort Ord, California. We found that the experts do not agree about the probability of UXO explosion, with significant differences among experts in their mean estimates of explosion probabilities and in the amount of uncertainty that they express in their estimates. In three of the six scenarios, the divergence was so great that the average of all the expert probability distributions was statistically indistinguishable from a uniform (0, 1) distribution—suggesting that the sum of expert opinion provides no information at all about the explosion risk. The experts' opinions on the relative sensitivity to explosion of the 20 UXO items also diverged. The average correlation between rankings of any pair of experts was 0.41, which, statistically, is barely significant (p= 0.049) at the 95% confidence level. Thus, one expert's rankings provide little predictive information about another's rankings. The lack of consensus among experts suggests that empirical studies are needed to better understand the explosion risks of UXO.     

Rapid Benefit-Risk Assessments: No Escape from Expert Judgments in Risk Management

The "human health impacts assessment" described by Cox and Popken (this issue) is intended to be a benefit-risk tool that avoids pitfalls of using expert judgments for policy analysis or during strict application of the precautionary principle in risk management. The proposed benefit-risk calculation uses numerous assumptions and suppositions to calculate a ratio of quality-adjusted life years (QALYs) lost for the number of human illness days prevented by the use of a food-animal antimicrobial drug, to the number of human illness days caused by the use of the antimicrobial drug. Assumptions about data--e.g., expert judgments on the representativeness of parameter estimates--are commonly used in risk assessment and risk management, including Cox and Popken's method. Cox and Popken apply the technique to specific examples of enrofloxacin and macrolides antimicrobial drugs, sometimes used in broiler chickens for human food. Although enthusiastically portrayed as a straightforward calculation of QALYs lost for two decision alternatives, Cox and Popken were silent on the pivotal expert judgment subsumed in their method: quality weights for illnesses caused by antimicrobial-resistant and antimicrobial-sensitive microbes are tacitly assumed to be equal. Yet, the costs in terms of prolonged illness, additional medications, repeat medical visits, and dread of more serious sequelae are expected to differ substantially for antimicrobial-resistant versus antimicrobial-sensitive illnesses. Despite their enthusiasm to the contrary, the "human health impacts assessment" by Cox and Popken is not immune from expert judgments in risk management.     

A Learning Curve Analysis of Expert System Use*

In this article, we study how an expert system affects novice problem solving in a financial risk analysis domain. We demonstrate that novice performance is improved after exposure to an expert system. Further, we show that novice performance continues to improve when the system is withdrawn. By comparing learning curves for people with exposure to those without, we can assess how much the system has benefitted its users. We demonstrate a quantitative methodology to measure the increment of learning due to the use of an information technology. We also explore the issue of how expertise is transferred from the system to the user.