Search results

The purpose of this study is to investigate the errors arising from the numerical treatment of model processes, paying particular attention to the impact of key system features including widely variable dispersion coefficients, spatiotemporal velocities of algal cells, and the aggregation of algae from single cells to large colonies. An advection–dispersion model has been presented to describe the vertical transport of colonial and motile harmful algae in a lake environment.

Model performance is examined for two different numerical treatments of the advective term: first-order upwind and quadratic upwind with a stability-preserving flux limiter (SMART). To determine how these schemes impact predictions, comparisons are made across a sequence of models with increasing complexity.

Using first-order upwinding for advection–dispersion calculations with a time oscillating velocity field leads to oscillatory numerical dispersion. Subjecting an initially uniform distribution of large-sized algal colonies to a spatiotemporal velocity creates a concentration pulse, which reaches a steady-state width at high-grid Peclet numbers when using the SMART scheme; the pulse exhibits contraction–expansion behavior throughout a velocity cycle at all Peclet numbers when using first-order upwinding. When aggregation dynamics are included with advection-dominated spatiotemporal transport, results indicate the SMART scheme predicts larger peak concentration values than those predicted by first-order upwind, but peak location and the time to large colony appearance remain largely unchanged between the two advective schemes.

To the best of the authors’ knowledge, this study is the first numerical investigation of a novel advection–dispersion model of vertical algal transport. In addition, a generalized expression for the effective dispersion coefficient of temporally variable flow fields is presented.

This paper aims to propose a new theoretical perspective on the organizational design of offshoring service organizations by adopting an information processing perspective which incorporates the factors of collaborative information technologies, task commoditization and global customer service delivery that are characteristic of modern-day knowledge-intensive service (KIS) organizations.

The authors analyze data from a large multiyear survey of offshoring service providers conducted in 12 countries.

The authors show how use of collaborative technology is significantly and positively related to spatial and configurational dispersion, task commoditization is significantly and positively related to spatial and temporal dispersion and need for global customer presence is not related to spatial, temporal or configurational dispersion.

The paper integrates concepts from management information system (MIS), operations management and international business to show how collaborative technology, task characteristics and customer service requirements affect the global dispersion of KISs.

The results show how use of collaborative technology, task characteristics and global customer service requirements need to be jointly considered in the global dispersion of activities by KIS providers.

The study sheds light on the effect of the key factors on different dimensions of global dispersion (i.e. spatial/temporal/configurational dispersion) in offshoring service provider organizations. Second, it shows how the traditional information processing perspective on organizations can be updated and applied to KIS organizations by incorporating the factors of global collaborative information technologies, task commoditization and global customer service.

The purpose of this paper is to develop the models of the dielectric permittivity dispersion of heterogeneous systems based on semiconductors to a level that would allow to apply effectively the method of broadband dielectric spectroscopy for the study of electronic processes in ceramic and composite materials.

The new approach for determining the complex dielectric permittivity of heterogeneous systems with semiconductor particles is used. It includes finding the analytical expression of the effective dielectric permittivity of the separate semiconductor particle of spherical shape. This approach takes into account the polarization of the free charge carriers in this particle, including capturing to localized electron states. This enabled the authors to use the known equations for complex dielectric permittivity of two-component matrix systems and statistical mixtures.

The presented dispersion equations establish the relationship between the parameters of the dielectric spectrum and electronic processes in the structures like semiconductor particles in a dielectric matrix in a wide frequency range. Conditions of manifestation and location of the different dispersion regions of the complex dielectric heterogeneous systems based on semiconductors in the frequency axis and their features are established. The most high-frequency dispersion region corresponds to the separation of free charge carriers at polarization. After this region in the direction of reducing of the frequency, the dispersion regions caused by recharge bulk and/or surface localized states follow. The most low-frequency dispersion region is caused by recharging electron traps in the boundary layer of the dielectric matrix.

Dielectric dispersion models are developed that are associated with: electronic processes of separation of free charge carriers in the semiconductor component, recapture of free charge carriers in the localized electronic states in bulk and on the surface of the semiconductor and also boundary layers of the dielectric at the polarization. The authors have analyzed to situations that correspond applicable and promising materials: varistor ceramics and composite structure with conductive and semiconductor fillers. The modelling results correspond to the existing level of understanding of the electron phenomena in matrix systems and statistical mixtures based on semiconductors. It allows to raise efficiency of research and control properties of heterogeneous materials by dielectric spectroscopy.

The objective of the present work was to perform a detailed numerical study of laminar forced convection in a three‐dimensional square duct packed with an isotropic granular material and saturated with a Newtonian fluid. Hydrodynamic and heat transfer results are reported for three different thermal boundary conditions. The flow in the porous medium was modeled using the semi‐empirical Brinkman‐Forchheimer‐extended Darcy model which also included the effects of variable porosity and thermal dispersion. Empirical models for variable porosity and thermal dispersion were determined based on existing three‐dimensional experimental measurements. Parametric studies were then conducted to investigate the effects of particle diameter, Reynolds number, Prandtl number and thermal conductivity ratio. The results showed that channeling phenomena and thermal dispersion effects are reduced considerably in a three‐dimensional duct compared with previously reported results for a two‐dimensional channel. It was found that the Reynolds number affects mainly the velocity gradient in the flow channeling region, while the particle diameter affects the width of the flow channeling region. As the Reynolds number increases or as the particle diameter decreases (i.e., when the inertia and thermal dispersion effects are enhanced), the Nusselt number increases. The effects of varing the Prandtl number on the magnitude of the Nusselt number were found to be more significant than those of the thermal conductivity ratio. Finally, the effects of varing the duct aspect ratio on the friction factor can be neglected for small particle diameter (D_p ≤ 0.01) or for high particle Reynolds number (Re_d ≥ 1000) due to the dominant bulk damping resistance from the porous matrix (Darcy term) or strong inertia effects (Forchheimer term), respectively.

Cross-border e-commerce in China has been booming in recent years. This paper aims to study pricing in Chinese cross-border e-commerce companies and focuses on the baby food market, which is simply examined as a case study to highlight broader implications. In this intensely competitive sector, the biggest challenge faced by such companies is ensuring that they are in a position to be able set prices in the short-term to maximize their competitive advantage and profitability. The study of pricing will help management to make correct operational decisions.

This study utilizes transaction data, which were obtained from the Taobao e-commerce platform. Taobao is the largest e-commerce retail platform in the world. We analyzed factors, including business models, homogeneity, reputation ratings and sales volumes, which may affect pricing.

This study found that consumers in the baby food sector of Chinese cross-border e-commerce are not price-sensitive. Consumers are reputation-rating-sensitive. The reputation ratings of sellers affect the price dispersion in e-commerce markets. The Core Price Dispersion Rate Model not only considers the prices but also takes sales volumes into account in the calculations. Finally, based on Gaussian processes, a model was developed for price forecasting in the area of cross-border e-commerce. The experimental results show that the proposed method is highly valuable for price forecasting.

This study provides a novel understanding of the baby food sector in the Chinese cross-border e-commerce market by examining the business model, price dispersion, reputation rating and correlation between the reputation of sellers, prices and sales volume. Furthermore, a model for price forecasting is proposed.

This paper aims to investigate the association between analyst forecast dispersion and investors’ perceived uncertainty toward earnings.

A new measure for investors’ expectations of earnings announcement uncertainty is constructed, using changes in implied volatility of option contracts prior to earnings announcements. Unlike other proxies of uncertainty, this measure isolates the incremental uncertainty regarding the upcoming earnings announcement and is a forward-looking measure.

Using this new proxy, this paper finds a significant negative correlation between analyst forecast dispersion and investors’ uncertainty regarding the upcoming earnings announcements. Further tests show that this negative correlation is driven by analysts’ private information acquisition rather than analysts; uncertainty toward upcoming earnings announcements. Additional cross-sectional tests show that this negative relationship is more pronounced in the subsample with lower earnings quality.

This paper helps to further the understanding of the information content of analyst forecast dispersion, particularly the ways in which they gather and produce private information and their incentives for so doing.

This paper introduces a new market-based and forward-looking proxy of earnings announcement uncertainty that should be useful in future research. This paper also provides original empirical evidence that analysts gather and produce an additional private information to the market when facing noisy signals and that their information reduces investors’ uncertainty toward upcoming earnings announcements.

The classical advection-dispersion equation (ADE) model cannot accurately depict the gas transport process in natural geological formations. This paper aims to study the behavior of CO₂ transport in fractal porous media by using an effective Hausdorff fractal derivative advection-dispersion equation (HFDADE) model.

Anomalous dispersion behaviors of CO₂ transport are effectively characterized by the investigation of time and space Hausdorff derivatives on non-Euclidean fractal metrics. The numerical simulation has been performed with different Hausdorff fractal dimensions to reveal characteristics of the developed fractal ADE in fractal porous media. Numerical experiments focus on the influence of the time and space fractal dimensions on flow velocity and dispersion coefficient.

The physical mechanisms of parameters in the Hausdorff fractal derivative model are analyzed clearly. Numerical results demonstrate that the proposed model can well fit the history of gas production data and it can be a powerful technique for depicting the early arrival and long-tailed phenomenon by incorporating a fractal dimension.

To the best of the authors’ knowledge, first time these results are presented.

This paper aims to investigate the informativeness of rhetorical impression management patterns of CEO letters and examines whether these rhetorical features affect financial analysts’ forecasting behaviour.

The authors use textual analysis on a sample of 526 CEO letters of US firms and apply factor analysis on individual linguistic style measures to identify co-occurrence patterns of style features.

The authors identify three holistic style patterns (assertive acclaiming, cautious plausibility-based framing and logic-based rationalizing) and find that assertive rhetorical feature in CEO letters is negatively related with the dispersion of financial analysts’ earnings forecasts and positively associated with earnings forecast accuracy. CEOs’ use of a rationalizing rhetorical pattern tends to decrease the dispersion of financial analysts’ earnings, whereas a cautious plausibility-based rhetorical position is only marginally instrumental in getting more accurate earnings predictions.

Whilst impression management communication is often theorized as manipulative and void of real information content, the findings suggest that impression management serves both self-presentation and information-sharing purposes.

This paper elaborates on the co-occurrence of style characteristics in management communication and is a first attempt to validate the external ramifications of holistic style profiles of corporate narratives by focusing on an economic target audience.

In the “dry” state, pigment particles are held together by attraction forces of various physical chemical natures including the van der Waals force and the “liquid bridge” force. These attraction forces must be overcome in order to disperse pigment particles into liquid media. Dispersion machinery is designed to generate energy required to overcome, to various extents, such attraction forces. On the other hand, the efficiency of dispersion operation is significantly dependent upon the effectiveness of the transfer of energy from the dispersion tools/dispersion charges to the oversized pigment particles, as a result of the presence of the adhesion and cohesion within the dispersion system. This paper explores the nature and the significance of various forces between pigment particles and of the adhesion and cohesion phenomena associated with pigment dispersion, from a practical point of view. Principles relevant to improving the efficiency of pigment dispersion via minimisation of the adhesion between pigment particles and via maximisation of the adhesion and cohesion within the dispersion system are also discussed.

The variable porosity and thermal dispersion effects on natural convection in an inclined porous cavity are investigated numerically. The wall effect on porosity is approximated by an exponential function and its effect on thermal dispersion is modeled in terms of a dispersive length. Numerical results show that both variable porosity and thermal dispersion effects increase the temperature gradient adjacent to the wall resulting in the enhancement of surface heat flux. These effects become important when the dimensionless particle diameter is increased. The variable porosity effect increases the fluid velocity near the wall, consequently enhancing convective heat transfer. The Prandtl number effect on the Nusselt number is small for Prandtl number greater than one, but increases as the Prandtl number decreases below one. The effect of thermal conductivity ratio on the Nusselt number is greater at low Rayleigh numbers where conduction heat transfer is predominant. A comparison between theoretical and experimental results shows that the calculated Nusselt numbers which take into account variable porosity and thermal dispersion effects have the best agreement with experimental data.