A Course Project Designed to Aid Students’ Understanding of the Structure of Advertisements: An Application of the Who Says What to Whom over What Channel with What Effect Model

The author describes a project using a classic communication and attitude-change model and explains how instructors teaching a course in promotional strategy, advertising, or integrated marketing communications can use it to help students better understand the critical elements of an effective advertisement. The author provides an overview of the research on the classic model and describes how the model is still useful today. One benefit for the instructor who adopts this project in their respective course is that students are required to synthesize knowledge of the model with information provided in the current advertising literature and then use this knowledge to analyze components of an advertisement. Another benefit is the project provides instructors with an assignment to help students learn about how communication and attitude-change models can be both relevant and applicable regarding decisions on the usage of promotional strategy and tactics

Revisiting Cognitive Dissonance Theory:Pre-Decisional Influences and the Relationship to the Consumer Decision-Making Model

This paper examines pre-decisional dissonance as a motivating factor in consumer decisional-making. A review of the marketing literature found the majority of research studies were limited to post-decisional influences. Several studies including measures of pre-decisional activity linked the construct to post-decision situations. The author provides evidence regarding the popularity and resurgence of research on cognitive dissonance theory and asserts that researchers in the field of consumer behavior may gain a better understanding of consumer decision-making when studying pre-decisional consonance and dissonance as separate entities and independent of post-decisions

Grey-box Modelling of a Household Refrigeration Unit Using Time Series Data in Application to Demand Side Management

This paper describes the application of stochastic grey-box modeling to identify electrical power consumption-to-temperature models of a domestic freezer using experimental measurements. The models are formulated using stochastic differential equations (SDEs), estimated by maximum likelihood estimation (MLE), validated through the model residuals analysis and cross-validated to detect model over-fitting. A nonlinear model based on the reversed Carnot cycle is also presented and included in the modeling performance analysis. As an application of the models, we apply model predictive control (MPC) to shift the electricity consumption of a freezer in demand response experiments, thereby addressing the model selection problem also from the application point of view and showing in an experimental context the ability of MPC to exploit the freezer as a demand side resource (DSR).Comment: Submitted to Sustainable Energy Grids and Networks (SEGAN). Accepted for publicatio

An Analysis of Perceptual Gaps among Chamber Management, Chamber Member Contacts, and a Proxy Sample of Chamber Member Employees: An Attempt to Improve Marketing Efficacy

Decreases in membership for a local chamber of commerce led the authors to conduct research to assist them in determining why they have been experiencing difficulty with business organization memberships within the last few years. This paper presents findings from an exploratory study that examined perceptual gaps on a series of factors that the authors believe when identified, may lead to improved marketing efficacy. Chamber management, chamber member contacts, and a proxy sample of chamber member employees for a local chamber of commerce completed surveys to assess the level of consistency among their perceptions of value added benefits of chamber membership. The authors believe the results of this study may be useful for other chambers of commerce and organizations when their long-term survival is dependent on active memberships

Recurring patterns in stationary intervals of abdominal uterine electromyograms during gestation

Abdominal uterine electromyograms (uEMG) studies have focused on uterine contractions to describe the evolution of uterine activity and preterm birth (PTB) prediction. Stationary, non-contracting uEMG has not been studied. The aim of the study was to investigate the recurring patterns in stationary uEMG, their relationship with gestation age and PTB, and PTB predictivity. A public database of 300 (38 PTB) three-channel (S1-S3) uEMG recordings of 30 min, collected between 22 and 35 weeks' gestation, was used. Motion and labour contraction-free intervals in uEMG were identified as 5-min weak-sense stationarity intervals in 268 (34 PTB) recordings. Sample entropy (SampEn), percentage recurrence (PR), percentage determinism (PD), entropy (ER), and maximum length (L MAX) of recurrence were calculated and analysed according to the time to delivery and PTB. Random time series were generated by random shuffle (RS) of actual data. Recurrence was present in actual data (p<0.001) but not RS. In S3, PR (p<0.005), PD (p<0.01), ER (p<0.005), and L MAX (p<0.05) were higher, and SampEn lower (p<0.005) in PTB. Recurrence indices increased (all p<0.001) and SampEn decreased (p<0.01) with decreasing time to delivery, suggesting increasingly regular and recurring patterns with gestation progression. All indices predicted PTB with AUC≥0.62 (p<0.05). Recurring patterns in stationary non-contracting uEMG were associated with time to delivery but were relatively poor predictors of PTB

Application of NASTRAN/COSMIC in the analysis of ship structures to underwater explosion shock

The application of NASTRAN/COSMIC in predicting the transient motion of ship structures to underwater, non-contact explosions is discussed. Examples illustrate the finite element models, mathematical formulations of loading functions and, where available, comparisons between analytical and experimental results