Search results

A non‐local pseudopotential model is used to generate realistic bandstructure for InP and GaAs. This is used to calculate the thresholds for impact ionisation and ionisation rates in these materials as a function of direction in wavevector space. Results are presented for a range of transitions.

Numerically simulating the behavior of GaAs devices requires a model for the distorted densities of states, band edge shifts, ΔΕc and ΔΕv, and effective intrinsic carrier concentrations, nie. The subscripts c and v denote the conduction and valence bands, respectively. Klauder's self‐energy methods (third‐level and fifth‐level) are applied to calculate the effects of carrier‐dopant ion interactions on the densities of states for GaAs. The effects of carrier‐carrier interactions have been calculated according to the theory of Abram et al. modified for 300 K. These calculations span most of the range of densities encountered in GaAs devices. This range is 5 × 1016 cm−3 to 1019 cm−3 for n‐type GaAs and from 1018 cm−3 to 1020 cm−3 for p‐type GaAs. We present in this paper theoretical data on how ΔΕc, ΔΕv, and nie vary with dopant densities. The variations with dopant and/or carrier densities of the distorted densities of states, Fermi energies screening radii, and first Born shifts will be given in a future publication.

Combines the techniques of fast Fourier transforms, Buneman cyclic reduction and the capacity matrix in a finite difference Poisson solver specifically designed for modelling realistic electronic device structures. A solution may be determined on a number of connected rectangular regions which correctly accounts for continuity of the electric displacement at dielectric interfaces. Suggests the method is particularly well suited to problems requiring repeated solution with the same device structure and provides a self‐consistent Monte Carlo simulation as an example of such an application.

Dynamic advertising, including television and online video ads, demands new theory and tools developed to understand attention to moving stimuli. The purpose of this study is to empirically test the predictions of a new dynamic attention theory, Dynamic Human-Centred Communication Systems Theory, versus the predictions of salience theory.

An eye-tracking study used a sample of consumers to measure visual attention to potential areas of interest (AOIs) in a random selection of unfamiliar video ads. An eye-tracking software feature called intelligent bounding boxes (IBBs) was used to track attention to moving AOIs. AOIs were coded for the presence of static salience variables (size, brightness, colour and clutter) and dynamic attention theory dimensions (imminence, motivational relevance, task relevance and stability).

Static salience variables contributed 90% of explained variance in fixation and 57% in fixation duration. However, the data further supported the three-way interaction uniquely predicted by dynamic attention theory: between imminence (central vs peripheral), relevance (motivational or task relevant vs not) and stability (fleeting vs stable). The findings of this study indicate that viewers treat dynamic stimuli like real life, paying less attention to central, relevant and stable AOIs, which are available across time and space in the environment and so do not need to be memorised.

Despite the limitations of small samples of consumers and video ads, the results of this study demonstrate the potential of two relatively recent innovations, which have received limited emphasis in the marketing literature: dynamic attention theory and IBBs.

This study documents what does and does not attract attention to video advertising. What gets attention according to salience theory (e.g. central location) may not always get attention in dynamic advertising because of the effects of relevance and stability. To better understand how to execute video advertising to direct and retain attention to important AOIs, advertisers and advertising researchers are encouraged to use IBBs.

This study makes two original contributions: to marketing theory, by showing how dynamic attention theory can predict attention to video advertising better than salience theory, and to marketing research, showing the utility of tracking visual attention to moving objects in video advertising with IBBs, which appear underutilised in advertising research.

There has been much discussion regarding the necessity of moving away from precise (rules-based) standards toward less precise (principles-based) standards. This study examines the impact of the proposed shift by using a controlled experiment to evaluate the influence of rule precision and information ambiguity on reporting decisions in the presence of monetary incentives to report aggressively. Using motivated reasoning theory as a framework, we predict that the malleability inherent in both rule precision and information ambiguity amplify biased reasoning in a manner that is consistent with individuals’ pecuniary incentives. In contrast, consistent with research exploring ambiguity aversion we predict that high levels of ambiguity will actually attenuate aggressive reporting. Our results support these predictions. Specifically, we find an interactive effect between rule precision and information ambiguity on self-interested reporting decisions at moderate levels of ambiguity. However, consistent with ambiguity aversion, we find decreased self-interested reporting decisions at high levels of ambiguity relative to moderate ambiguity. This study should be of interest to preparers, auditors, and regulators who are interested in identifying situations which amplify and diminish aggressive reporting.

The idea that a significant portion of what consumers do, feel, and think is driven by automatic (or “implicit”) cognitive processes has sparked a wave of interest in the development of assessment tools that (attempt to) capture cognitive processes under automaticity conditions (also known as “implicit measures”). However, as more and more implicit measures are developed, it is becoming increasingly difficult for consumer scientists and marketing professionals to select the most appropriate tool for a specific research question. We therefore present a systematic overview of the criteria that can be used to evaluate and compare different implicit measures, including their structural characteristics, the extent to which (and the way in which) they qualify as “implicit,” as well as more practical considerations such as ease of implementation and the user experience of the respondents. As an example, we apply these criteria to four implicit measures that are (or have the potential to become) popular in marketing research (i.e., the implicit association test, the evaluative priming task, the affect misattribution procedure, and the propositional evaluation paradigm).

The learning outcomes sought by social studies educators emphasize critical thinking, deep content knowledge, and an understanding of how knowledge in the disciplines of social studies is created and changes. Achieving these outcomes, calls for a more active, collaborative, and student-centered pedagogy. The reported study seeks to better understand the nature of student engagement in this kind of pedagogy by closely examining student discourse during instruction. The study reveals while academic tasks were well thought out and, on the surface, constructivist in nature; student discourse was almost entirely oriented toward producing good products with little thinking aimed at exploring the meanings and relationships among content. The study also demonstrates that redesigning the nature of classroom tasks, by presenting students with problems that necessitate thinking about how content is inter-related, results in readily discernable deepening of student discourse.