Exploring the Application of Multiple Intelligences Theory to Career Counseling

This article demonstrates the practical value of applying H. Gardner's (1993) theory of multiple intelligences (MI) to the practice of career counseling. An overview of H. Gardner's MI theory is presented, and the ways in which educational and vocational planning can be augmented by the integration of MI theory in career counseling contexts are discussed. The Multiple Intelligences Developmental Assessment Scales (C. B. Shearer, 2007), a research‐based self‐report measure of intellectual disposition, is introduced, and a case study illustrating the effective application of H. Gardner's MI theory to career counseling is presented.     

Revisiting multi-tier wage structures: Equity,employment mobility,and tier effects

This study considers the competing conclusions reached by Martin and Peterson (1987) and Cappelli and Sherer (1990) regarding two-tier wage systems and examines how worker perceptions of their own employment mobility affect attitudes about two-tier systems. Findings from a hybrid multi-tier wage system in the retail food industry containing both permanent and merging or temporary tiers indicates that workers on the permanently lower B tier possessed more negative attitudes than their A-tier counterparts, with some evidence that the effects of permanent and temporary plans differ. Employment mobility moderates these attitudes, for low mobility workers report more positive attitudes than do high mobility workers.     

Leader–member exchange and empowerment: Direct and interactive effects on job satisfaction,turnover intentions,and performance

This study examined the moderating impact of empowerment on the relationships between leader–member exchange (LMX) quality and the self-rated outcomes of job satisfaction and turnover intentions, as well as the supervisor-rated outcomes of job performance and organizational citizenship behaviors. Two samples, with 244 and 158 employees respectively, were used to test our hypotheses. Our results provided evidence that in general, empowerment moderates the relationships between LMX and job outcomes. These findings are important as previous research has only tested these variables as independent predictors, but our results suggest the relationships these constructs have with important consequences are dependent on both variables. Practical implications and directions for future research are offered.     

Overcoming Confirmation Bias in Causal Attribution: A Case Study of Antibiotic Resistance Risks

When they do not use formal quantitative risk assessment methods, many scientists (like other people) make mistakes and exhibit biases in reasoning about causation, if‐then relations, and evidence. Decision‐related conclusions or causal explanations are reached prematurely based on narrative plausibility rather than adequate factual evidence. Then, confirming evidence is sought and emphasized, but disconfirming evidence is ignored or discounted. This tendency has serious implications for health‐related public policy discussions and decisions. We provide examples occurring in antimicrobial health risk assessments, including a case study of a recently reported positive relation between virginiamycin (VM) use in poultry and risk of resistance to VM‐like (streptogramin) antibiotics in humans. This finding has been used to argue that poultry consumption causes increased resistance risks, that serious health impacts may result, and therefore use of VM in poultry should be restricted. However, the original study compared healthy vegetarians to hospitalized poultry consumers. Our examination of the same data using conditional independence tests for potential causality reveals that poultry consumption acted as a surrogate for hospitalization in this study. After accounting for current hospitalization status, no evidence remains supporting a causal relationship between poultry consumption and increased streptogramin resistance. This example emphasizes both the importance and the practical possibility of analyzing and presenting quantitative risk information using data analysis techniques (such as Bayesian model averaging (BMA) and conditional independence tests) that are as free as possible from potential selection, confirmation, and modeling biases.     

Determinants of Bureaucratic Turnover Intention: Evidence from the Department of the Treasury

This study employs a novel statistical strategy to examine thedeterminants of turnover intention in government service. Toappropriately measure a main determinant of turnover intention—functionalpreferences—I estimate an ordinal item response modelusing data from the Federal Human Capital Survey. The sampleis selected to facilitate an important comparison: the InternalRevenue Service (IRS) has undergone significant performance-basedpay reforms for supervisors, but not for nonsupervisors, whereasthe Office of the Comptroller of the Currency (OCC), also asubunit of the U.S. Treasury, has not. Inferential models ofturnover intention reveal among other things that functionaland friendship solidary preferences are important determinantsof turnover intention, but increased accountability is associatedwith greater turnover among subordinates. IRS supervisors, whoface paybanding, are significantly less likely to consider leavingthan their counterparts in the OCC, who do not face such incentives.     

On the measurement of unemployment

This paper investigates how alternative measures of unemployment may be derived from information on unemployment duration. It begins by listing various properties that unemployment indices should satisfy, and shows how ‘duration profiles’ can usefully represent unemployment data. Theorem 1 establishes that unemployment indices are unanimous iff the duration profiles do not intersect. Two families of unemployment indices are examined in detail. Both allow unemployment to be decomposed across population subgroups. In addition, they can be expressed as the product of three components reflecting the contributions of the unemployment rate, mean unemployment duration, and differences in duration among the unemployed.     

Some Limitations of “Risk = Threat × Vulnerability × Consequence” for Risk Analysis of Terrorist Attacks

Several important risk analysis methods now used in setting priorities for protecting U.S. infrastructures against terrorist attacks are based on the formula: Risk=Threat×Vulnerability×Consequence. This article identifies potential limitations in such methods that can undermine their ability to guide resource allocations to effectively optimize risk reductions. After considering specific examples for the Risk Analysis and Management for Critical Asset Protection (RAMCAP?) framework used by the Department of Homeland Security, we address more fundamental limitations of the product formula. These include its failure to adjust for correlations among its components, nonadditivity of risks estimated using the formula, inability to use risk‐scoring results to optimally allocate defensive resources, and intrinsic subjectivity and ambiguity of Threat, Vulnerability, and Consequence numbers. Trying to directly assess probabilities for the actions of intelligent antagonists instead of modeling how they adaptively pursue their goals in light of available information and experience can produce ambiguous or mistaken risk estimates. Recent work demonstrates that two‐level (or few‐level) hierarchical optimization models can provide a useful alternative to Risk=Threat×Vulnerability×Consequence scoring rules, and also to probabilistic risk assessment (PRA) techniques that ignore rational planning and adaptation. In such two‐level optimization models, defender predicts attacker's best response to defender's own actions, and then chooses his or her own actions taking into account these best responses. Such models appear valuable as practical approaches to antiterrorism risk analysis.     

Chaos: But Not in Both Directions!

This paper will informally explore the reversal of some stochastic autoregressive processes, which lead to deterministically chaotic processes. Correspondingly, the stochastic reversal of map models is shown to lead to a new class of invariant distribution. Finally, some connections between congruential recursions and independence in discretized chaotic processes are illustrated.     

A Staged Service Innovation Model*

Drawing from the new product development (NPD) literature, service quality literature (SERVQUAL), and empirically grounded research with 53 service innovation decision makers, we develop a staged service innovation model (SIM) for decision makers. We tested the model using empirical data from 329 firms across five industries. The empirical results show that integrating prelaunch service quality training into new service development process leads to successful service innovation. The model developed in this article can be used as a decision support tool and diagnostic model for assessing service innovation ideas, evaluating performance of ongoing service innovations, allocating resources, and improving success rate of service innovations. Decision makers can use the measures developed in this study as a checklist to identify their strengths in delivering service quality to their own customers as well as areas of improvement. This article extends service innovation research by combining NPD and service quality development into a single study and opens the door to further work that could help improve the success rate of service innovations. The model can serve as a base model for future research extensions in service innovation research. A major takeaway for the academic reader is that the SIM demonstrates the value of using the SERVQUAL literature to understand how best to provide excellent quality that results in more fully satisfied customers and, ultimately, improved service performance.