Listerine – for the bridesmaid who’s never a bride: disparaging humour increases brand attitude and recall among the powerless

Purpose: While the potential benefits of integrating humour into advertisements are widely understood, the reasons why these effects emerge are not. Drawing on literature about the impact of psychological feelings of power, this research aims to examine how power motivation interacts with the presence of disparaging humour in ads to influence ad-related outcomes.

Design/methodology/approach: Following the measurement (Study 1) or manipulation (Study 2) of power motivation, participants viewed an ad featuring either disparaging humour or one of the following alternatives: no humour (Study 1) or non-disparaging humour (Study 2). Sense of superiority, brand attitude, ad claim recall and the perceived humorousness of the ad were then assessed.

Findings: Featuring disparaging humour in an ad increased participants’ sense of superiority, but only among those with high power motivation. Among such participants, this heightened sense of superiority increased the perceived humorousness of the disparaging humour (Studies 1 and 2), induced more favourable attitudes towards the brand featured in the ad (Studies 1 and 2) and enhanced ad claim recall (Study 2). These effects did not, however, extend to ads featuring non-disparaging humour (Study 2), indicating that it was the presence of disparaging humour, and not humour per se, that was responsible for these effects.

Originality/value: These findings break open the “black box” of humour by identifying why consumers perceive disparaging humorous content to be funny, when this effect will occur and what impact this will have on advertising-related outcomes.

SAMPLING BIAS IN EVALUATING THE PROBABILITY OF SEISMICALLY INDUCED SOIL LIQUEFACTION WITH SPT & CPT CASE HISTORIES

Several deterministic and probabilistic methods are used to evaluate the probability of seismically induced liquefaction of a soil. The probabilistic models usually possess some uncertainty in that model and uncertainties in the parameters used to develop that model. These model uncertainties vary from one statistical model to another. Most of the model uncertainties are epistemic, and can be addressed through appropriate knowledge of the statistical model. One such epistemic model uncertainty in evaluating liquefaction potential using a probabilistic model such as logistic regression is sampling bias. Sampling bias is the difference between the class distribution in the sample used for developing the statistical model and the true population distribution of liquefaction and non-liquefaction instances. Recent studies have shown that sampling bias can significantly affect the predicted probability using a statistical model. To address this epistemic uncertainty, a new approach was developed for evaluating the probability of seismically-induced soil liquefaction, in which a logistic regression model in combination with Hosmer-Lemeshow statistic was used. This approach was used to estimate the population (true) distribution of liquefaction to non-liquefaction instances of standard penetration test (SPT) and cone penetration test (CPT) based most updated case histories. Apart from this, other model uncertainties such as distribution of explanatory variables and significance of explanatory variables were also addressed using KS test and Wald statistic respectively. Moreover, based on estimated population distribution, logistic regression equations were proposed to calculate the probability of liquefaction for both SPT and CPT based case history. Additionally, the proposed probability curves were compared with existing probability curves based on SPT and CPT case histories.

BIAS-CORRECTED MAXIMUM LIKELIHOOD ESTIMATION OF THE PARAMETERS OF THE WEIGHTED LINDLEY DISTRIBUTION

This report discusses the calculation of analytic second-order bias techniques for the maximum likelihood estimates (for short, MLEs) of the unknown parameters of the distribution in quality and reliability analysis. It is well-known that the MLEs are widely used to estimate the unknown parameters of the probability distributions due to their various desirable properties; for example, the MLEs are asymptotically unbiased, consistent, and asymptotically normal. However, many of these properties depend on an extremely large sample sizes. Those properties, such as unbiasedness, may not be valid for small or even moderate sample sizes, which are more practical in real data applications. Therefore, some bias-corrected techniques for the MLEs are desired in practice, especially when the sample size is small. Two commonly used popular techniques to reduce the bias of the MLEs, are ‘preventive’ and ‘corrective’ approaches. They both can reduce the bias of the MLEs to order O(n−2), whereas the ‘preventive’ approach does not have an explicit closed form expression. Consequently, we mainly focus on the ‘corrective’ approach in this report. To illustrate the importance of the bias-correction in practice, we apply the bias-corrected method to two popular lifetime distributions: the inverse Lindley distribution and the weighted Lindley distribution. Numerical studies based on the two distributions show that the considered bias-corrected technique is highly recommended over other commonly used estimators without bias-correction. Therefore, special attention should be paid when we estimate the unknown parameters of the probability distributions under the scenario in which the sample size is small or moderate.

Bias of damage awards and free options in securities litigation

Damage measures in securities fraud cases are very imprecise because they are based on security price changes that reflect both the correction of previous misrepresentation and other independent information. Consequently, potential plaintiffs have a valuable “free option” to decide whether or not to file suit, and average damage awards are greater than actual damages, much greater when markets are volatile. The “Private Securities Litigation Reform Act of 1995” was intended to curb abusive litigation and to address the problem of excessive damage awards. Motivated by a misdiagnosis that excess awards are due to temporary price drops, the Act limits damages to the difference between the purchase price and the time-averaged trading price from the release of the corrective information until 90 days later or until the sale of the security, whichever is first. Unfortunately, the Act's modified measure of damages suffers from a more severe free-option problem than did the traditional measure. Also, the Act introduced an additional new option to time the sale of the security; the effects of these options may be mitigated by the impact of the positive drift in stock prices over time, if the time-averaged price is not adjusted for market movements. As a result, the bias can be larger or smaller under the new Act, depending on how severe the free-option problem is. We propose an alternative approach to addressing the issue of excessive damages: courts should adopt a threshold of measured damages below which no damage would be awarded. The threshold would depend on several factors, most notably the volatility of the stock in the period under question. That is, damages will be awarded only if measured damages exceed the threshold, and awards would be capped by the formula presented in the Reform Act.

Prejudicial evaluation: bias in self-and-peer-assessments of teamwork contributions to design

This chapter considers a simple but important question: can students fairly assess each other’s individual contribution to team designs? The chapter focuses on a key problem when using online self-and-peerassessment to individualising design grades for team assignments, namely rater bias – the possibility of students being biased when assessing their own and their peers’ contributions. Three rater-bias issuesare considered in depth: (1) self-overmarking; (2) gender bias and gender differences; and (3) out-group bias in the peer assessment of international students in multicultural cohorts. Each issue is explored viathe analysis of eight years of quantitative data from the use of an online self-and-peer assessment tool. Evidence is found of self-overmarking and of out-group bias in nonhomogeneous cohorts. However, no evidence is found of gender bias. The chapter concludes with recommendations for design teachers around the assessment of individual contributions to teamwork using self-and-peer assessment.

Examining interview techniques to assist children’s recall of repeated events.

This thesis tested interview techniques expected to assist children reporting on repeated events, such as ongoing abuse. The quality and quantity of information children provided was improved by several techniques that rehearsed children in key cognitive tasks. Developmental trends were found whereby techniques often assisted older children more than younger children.

Assemblage, size and abundance bias in a novel sandy shore macro-infaunal sampling technique

Sampling sandy shore macro-invertebrate fauna is critical in enhancing our understanding of beach ecology and conservation, and is a common monitoring approach. The traditional, and almost universal, method of sampling involves sieving sand to locate infauna, but here we describe a novel Hydraulic Sampling Device (HSD), a candidate method for future macro-invertebrate sampling, which has the potential to be faster and more effective at sampling invertebrates. We compared the results obtained by these two methods. Macro-invertebrate fauna of six beaches on Phillip Island, southern Victoria, Australia were sampled in the upper and lower beach. On average, the HSD sampled a smaller size range of fauna than the sieving method, perhaps because of longer handling times and escape of larger individuals. The sieving method found more individuals and a higher species richness. The methods we describe do not produce directly comparable results. On balance, the sieving method is simpler, apparently not as prone to ‘escape bias’, and reports higher abundances and richness of beach infauna.

Reptile responses to fire and the risk of post-disturbance sampling bias

Altered fire regimes are a driver of biodiversity decline. To plan effective management, we need to know how species are influenced by fire and to develop theory describing fire responses. Animal responses to fire are usually measured using methods that rely on animal activity, but animal activity may vary with time since fire, potentially biasing results. Using a novel approach for detecting bias in the pit-fall trap method, we found that leaf-litter dependent reptiles were more active up to 6 weeks after fire, giving a misleading impression of abundance. This effect was not discovered when modelling detectability with zero-inflated binomial models. Two species without detection bias showed early-successional responses to time since fire, consistent with a habitat-accommodation succession model. However, a habitat specialist did not have the predicted low abundance after fire due to increased post-fire movement and non-linear recovery of a key habitat component. Interactions between fire and other processes therefore must be better understood to predict reptile responses to changing fire-regimes. We conclude that there is substantial bias when trapping reptiles after fire, with species that are otherwise hard to detect appearing to be abundant. Studies that use a survey method based on animal activity such as bird calls or animal movements, likely face a similar risk of bias when comparing recently-disturbed with control sites.

Detectability of migrating raptors and its effect on bias and precision of trend estimates

Annual counts of migrating raptors at fixed observation points are a widespread practice, and changes in numbers counted over time, adjusted for survey effort, are commonly used as indices of trends in population size. Unmodeled year-to-year variation in detectability may introduce bias, reduce precision of trend estimates, and reduce power to detect trends. We conducted dependent double-observer surveys at the annual fall raptor migration count at Lucky Peak, Idaho, in 2009 and 2010 and applied Huggins closed-capture removal models and information-theoretic model selection to determine the relative importance of factors affecting detectability. The most parsimonious model included effects of observer team identity, distance, species, and day of the season. We then simulated 30 years of counts with heterogeneous individual detectability, a population decline (λ = 0.964), and unexplained random variation in the number of available birds. Imperfect detectability did not bias trend estimation, and increased the time required to achieve 80% power by less than 11%. Results suggested that availability is a greater source of variance in annual counts than detectability; thus, efforts to account for availability would improve the monitoring value of migration counts. According to our models, long-term trends in observer efficiency or migratory flight distance may introduce substantial bias to trend estimates. Estimating detectability with a novel count protocol like our double-observer method is just one potential means of controlling such effects. The traditional approach of modeling the effects of covariates and adjusting the index may also be effective if ancillary data is collected consistently.

Clinical Accuracy of the MedGem Indirect Calorimeter for Measuring Resting Energy Expenditure in Cancer Patients

OBJECTIVE: To compare, in patients with cancer and in healthy subjects, measured resting energy expenditure (REE) from traditional indirect calorimetry to a new portable device (MedGem) and predicted REE. DESIGN: Cross-sectional clinical validation study. SETTING: Private radiation oncology centre, Brisbane, Australia. SUBJECTS: Cancer patients (n = 18) and healthy subjects (n = 17) aged 37-86 y, with body mass indices ranging from 18 to 42 kg/m(2). INTERVENTIONS: Oxygen consumption (VO(2)) and REE were measured by VMax229 (VM) and MedGem (MG) indirect calorimeters in random order after a 12-h fast and 30-min rest. REE was also calculated from the MG without adjustment for nitrogen excretion (MGN) and estimated from Harris-Benedict prediction equations. Data were analysed using the Bland and Altman approach, based on a clinically acceptable difference between methods of 5%. RESULTS: The mean bias (MGN-VM) was 10% and limits of agreement were -42 to 21% for cancer patients; mean bias -5% with limits of -45 to 35% for healthy subjects. Less than half of the cancer patients (n = 7, 46.7%) and only a third (n = 5, 33.3%) of healthy subjects had measured REE by MGN within clinically acceptable limits of VM. Predicted REE showed a mean bias (HB-VM) of -5% for cancer patients and 4% for healthy subjects, with limits of agreement of -30 to 20% and -27 to 34%, respectively. CONCLUSIONS: Limits of agreement for the MG and Harris Benedict equations compared to traditional indirect calorimetry were similar but wide, indicating poor clinical accuracy for determining the REE of individual cancer patients and healthy subjects.

Capabilities : describing what services can do

The ability of agents and services to automatically locate and interact with unknown partners is a goal for both the semantic web and web services. This, \serendipitous interoperability", is hindered by the lack of an explicit means of describing what services (or agents) are able to do, that is, their capabilities. At present, informal descriptions of what services can do are found in \documentation" elements; or they are somehow encoded in operation names and signatures. We show, by ref- erence to existing service examples, how ambiguous and imprecise capa- bility descriptions hamper the attainment of automated interoperability goals in the open, global web environment. In this paper we propose a structured, machine readable description of capabilities, which may help to increase the recall and precision of service discovery mechanisms. Our capability description draws on previous work in capability and process modeling and allows the incorporation of external classi¯cation schemes. The capability description is presented as a conceptual meta model. The model supports conceptual queries and can be used as an extension to the DAML-S Service Pro¯le.

Property cash flow studies : focusing on model consistency and data accuracy

The high degree of variability and inconsistency in cash flow study usage by property professionals demands improvement in knowledge and processes. Until recently limited research was being undertaken on the use of cash flow studies in property valuations but the growing acceptance of this approach for major investment valuations has resulted in renewed interest in this topic. Studies on valuation variations identify data accuracy, model consistency and bias as major concerns. In cash flow studies there are practical problems with the input data and the consistency of the models. This study will refer to the recent literature and identify the major factors in model inconsistency and data selection. A detailed case study will be used to examine the effects of changes in structure and inputs. The key variable inputs will be identified and proposals developed to improve the selection process for these key variables. The variables will be selected with the aid of sensitivity studies and alternative ways of quantifying the key variables explained. The paper recommends, with reservations, the use of probability profiles of the variables and the incorporation of this data in simulation exercises. The use of Monte Carlo simulation is demonstrated and the factors influencing the structure of the probability distributions of the key variables are outline. This study relates to ongoing research into functional performance of commercial property within an Australian Cooperative Research Centre.

Perceptions of Integration: What the Literature Says and What Stakeholders See

This paper compares perceptions of integrated marketing communication (IMC) to establish whether consumers perceive integration in the same way as the literature. It begins by reviewing the literature to identify shared assumptions about integration and factors thought to contribute to the integration of marketing communication and, in an experiment, compares these with the perceptions of consumers. Many of the shared assumptions in the literature have been supported by the findings of this study. Integration has been demonstrated to be both a strategy and a tactic. The strategic side is part of a management process and is unable to be observed by consumers from the marketing communication output. Consumers can, however, identify the tactics and are able to recall a number of integration factors such as logo, corporate colours and image. Consumers in the total message integration groups perceived the messages they received as more integrated than those in partial integration or no integration groups.