External orientation and business model adaptation in young and nascent firms : preliminary analysis from the CAUSSE project

Discovering factors that help or impede business model change is an important quest, both for researchers and practitioners. In this study we present preliminary findings based on the CAUSEE survey of young and nascent firms in Australia. In particular, we seek to determine an association between business model adaptation and external orientation among young and nascent firms within the random sample and amongst an oversample of high potential firms. The concept of external orientation is made operational by asking respondents whether, and to what extent, they rely on certain sources of advice and information. We find that high potential firms are more likely to have made at least some change to their business model, that greater use of external sources of advice is generally significantly associated with business model adaptation, but also that there appear to be different patterns of behaviour between the random sample and the over sample.

Numerical analysis of the time variable fractional order mobile-immobile advection-dispersion model

Many physical processes exhibit fractional order behavior that varies with time or space. The continuum of order in the fractional calculus allows the order of the fractional operator to be considered as a variable. In this paper, we consider the time variable fractional order mobile-immobile advection-dispersion model. Numerical methods and analyses of stability and convergence for the fractional partial differential equations are quite limited and difficult to derive. This motivates us to develop efficient numerical methods as well as stability and convergence of the implicit numerical methods for the fractional order mobile immobile advection-dispersion model. In the paper, we use the Coimbra variable time fractional derivative which is more efficient from the numerical standpoint and is preferable for modeling dynamical systems. An implicit Euler approximation for the equation is proposed and then the stability of the approximation are investigated. As for the convergence of the numerical scheme we only consider a special case, i.e. the time fractional derivative is independent of time variable t. The case where the time fractional derivative depends both the time variable t and the space variable x will be considered in the future work. Finally, numerical examples are provided to show that the implicit Euler approximation is computationally efficient.

Ability of modal analysis to detect osseointegration of implants in transfemoral amputees : a physical model study

Owing to the successful use of non-invasive vibration analysis to monitor the progression of dental implant healing and stabilization, it is now being considered as a method to monitor femoral implants in transfemoral amputees. This study uses composite femur-implant physical models to investigate the ability of modal analysis to detect changes at the interface between the implant and bone simulating those that occur during osseointegration. Using electromagnetic shaker excitation, differences were detected in the resonant frequencies and mode shapes of the model when the implant fit in the bone was altered to simulate the two interface cases considered: firm and loose fixation. The study showed that it is beneficial to examine higher resonant frequencies and their mode shapes (rather than the fundamental frequency only) when assessing fixation. The influence of the model boundary conditions on the modal parameters was also demonstrated. Further work is required to more accurately model the mechanical changes occurring at the bone-implant interface in vivo, as well as further refinement of the model boundary conditions to appropriately represent the in vivo conditions. Nevertheless, the ability to detect changes in the model dynamic properties demonstrates the potential of modal analysis in this application and warrants further investigation.

Model development and dynamic load-sharing analysis of longitudinal-connected air suspensions

The objective of this research was to investigate the effect of suspension parameters on dynamic load-sharing of longitudinal-connected air suspensions of a tri-axle semi-trailer. A novel nonlinear model of a multi-axle semi-trailer with longitudinal-connected air suspension was formulated based on fluid mechanics and thermodynamics and was validated through test results. The effects of suspension parameters on dynamic load-sharing and road-friendliness of the semi-trailer were analyzed. Simulation results indicate that the road-friendliness metric DLC (Dynamic Load Coefficient), is generally in accordance with the load-sharing metric - DLSC (Dynamic Load Sharing Coefficient). When the static height or static pressure increases, the DLSC optimization ratio declines monotonically. The effect of employing larger air lines and connectors on the DLSC optimization ratio gives varying results as road roughness increases and as driving speed increases. The results also indicate that if the air line diameter is always assumed to be larger than the connector diameter, the influence of air line diameter on load-sharing is more significant than that of the connector.

Modification of advanced programmatic risk analysis and management model for the whole project life cycle’s risks

The advanced programmatic risk analysis and management model (APRAM) is one of the recently developed methods that can be used for risk analysis and management purposes considering schedule, cost, and quality risks simultaneously. However, this model considers those failure risks that occur only over the design and construction phases of a project’s life cycle. While it can be sufficient for some projects for which the required cost during the operating life is much less than the budget required over the construction period, it should be modified in relation to infrastructure projects because the associated costs during the operating life cycle are significant. In this paper, a modified APRAM is proposed, which can consider potential risks that might occur over the entire life cycle of the project, including technical and managerial failure risks. Therefore, the modified model can be used as an efficient decision-support tool for construction managers in the housing industry in which various alternatives might be technically available. The modified method is demonstrated by using a real building project, and this demonstration shows that it can be employed efficiently by construction managers. The Delphi method was applied in order to figure out the failure events and their associated probabilities. The results show that although the initial cost of a cold-formed steel structural system is higher than a conventional construction system, the former’s failure cost is much lower than the latter’s

Towards a compendium of process technologies : the jBPT library for process model analysis

This paper presents the idea of a compendium of process technologies, i.e., a concise but comprehensive collection of techniques for process model analysis that support research on the design, execution, and evaluation of processes. The idea originated from observations on the evolution of process-related research disciplines. Based on these observations, we derive design goals for a compendium. Then, we present the jBPT library, which addresses these goals by means of an implementation of common analysis techniques in an open source codebase.

Hierarchical multiscale model for biomechanics analysis of microfilament networks

The mechanisms of force generation and transference via microfilament networks are crucial to the understandings of mechanobiology of cellular processes in living cells. However, there exists an enormous challenge for all-atom physics simulation of real size microfilament networks due to scale limitation of molecular simulation techniques. Following biophysical investigations of constitutive relations between adjacent globular actin monomers on filamentous actin, a hierarchical multiscale model was developed to investigate the biomechanical properties of microfilament networks. This model was validated by previous experimental studies of axial tension and transverse vibration of single F-actin. The biomechanics of microfilament networks can be investigated at the scale of real eukaryotic cell size (10 μm). This multiscale approach provides a powerful modeling tool which can contribute to the understandings of actin-related cellular processes in living cells.

A comprehensive dual-scale wood torrefaction model : application to the analysis of thermal run-away in industrial heat treatment processes

A dual-scale model of the torrefaction of wood was developed and used to study industrial configurations. At the local scale, the computational code solves the coupled heat and mass transfer and the thermal degradation mechanisms of the wood components. At the global scale, the two-way coupling between the boards and the stack channels is treated as an integral component of the process. This model is used to investigate the effect of the stack configuration on the heat treatment of the boards. The simulations highlight that the exothermic reactions occurring in each single board can be accumulated along the stack. This phenomenon may result in a dramatic eterogeneity of the process and poses a serious risk of thermal runaway, which is often observed in industrial plants. The model is used to explain how thermal runaway can be lowered by increasing the airflow velocity, the sticker thickness or by gas flow reversal.

Integration of sentiment analysis into customer relational model : the importance of feature ontology and synonym

Online business or Electronic Commerce (EC) is getting popular among customers today, as a result large number of product reviews have been posted online by the customers. This information is very valuable not only for prospective customers to make decision on buying product but also for companies to gather information of customers’ satisfaction about their products. Opinion mining is used to capture customer reviews and separated this review into subjective expressions (sentiment word) and objective expressions (no sentiment word). This paper proposes a novel, multi-dimensional model for opinion mining, which integrates customers’ characteristics and their opinion about any products. The model captures subjective expression from product reviews and transfers to fact table before representing in multi-dimensions named as customers, products, time and location. Data warehouse techniques such as OLAP and Data Cubes were used to analyze opinionated sentences. A comprehensive way to calculate customers’ orientation on products’ features and attributes are presented in this paper.

Spatial prediction of N2O emissions in pasture : a Bayesian model averaging analysis

Nitrous oxide (N2O) is one of the greenhouse gases that can contribute to global warming. Spatial variability of N2O can lead to large uncertainties in prediction. However, previous studies have often ignored the spatial dependency to quantify the N2O - environmental factors relationships. Few researches have examined the impacts of various spatial correlation structures (e.g. independence, distance-based and neighbourhood based) on spatial prediction of N2O emissions. This study aimed to assess the impact of three spatial correlation structures on spatial predictions and calibrate the spatial prediction using Bayesian model averaging (BMA) based on replicated, irregular point-referenced data. The data were measured in 17 chambers randomly placed across a 271 m(2) field between October 2007 and September 2008 in the southeast of Australia. We used a Bayesian geostatistical model and a Bayesian spatial conditional autoregressive (CAR) model to investigate and accommodate spatial dependency, and to estimate the effects of environmental variables on N2O emissions across the study site. We compared these with a Bayesian regression model with independent errors. The three approaches resulted in different derived maps of spatial prediction of N2O emissions. We found that incorporating spatial dependency in the model not only substantially improved predictions of N2O emission from soil, but also better quantified uncertainties of soil parameters in the study. The hybrid model structure obtained by BMA improved the accuracy of spatial prediction of N2O emissions across this study region.

Burn healing is dependent on burn site : a quantitative analysis from a porcine burn model

This retrospective review examines healing in different sites on a porcine burn model; 24 pairs of burns on 18 pigs from other animal trials were selected for analysis. Each pair of burns was located on the either the cranial or the caudal part of the thoracic ribs region, on the same side of the animal. The burns were 40-50 cm(2) in size and of uniform deep-dermal partial thickness. Caudal burns healed significantly better than cranial burns, demonstrated by earlier closure of wounds, less scar formation and better cosmesis. To our knowledge, this is the first detailed study reporting that burn healing is affected by location on a porcine burn model. We recommend that similar symmetrical burns should be used for future comparative assessments of burn healing.

A simple model for the establishment of tick-borne pathogens of Ixodes scapularis : a global sensitivity analysis of R0

The basic reproduction number of a pathogen, R 0, determines whether a pathogen will spread (R0>1R 0>1), when introduced into a fully susceptible population or fade out (R0<1R 0<1), because infected hosts do not, on average, replace themselves. In this paper we develop a simple mechanistic model for the basic reproduction number for a group of tick-borne pathogens that wholly, or almost wholly, depend on horizontal transmission to and from vertebrate hosts. This group includes the causative agent of Lyme disease, Borrelia burgdorferi, and the causative agent of human babesiosis, Babesia microti, for which transmission between co-feeding ticks and vertical transmission from adult female ticks are both negligible. The model has only 19 parameters, all of which have a clear biological interpretation and can be estimated from laboratory or field data. The model takes into account the transmission efficiency from the vertebrate host as a function of the days since infection, in part because of the potential for this dynamic to interact with tick phenology, which is also included in the model. This sets the model apart from previous, similar models for R0 for tick-borne pathogens. We then define parameter ranges for the 19 parameters using estimates from the literature, as well as laboratory and field data, and perform a global sensitivity analysis of the model. This enables us to rank the importance of the parameters in terms of their contribution to the observed variation in R0. We conclude that the transmission efficiency from the vertebrate host to Ixodes scapularis ticks, the survival rate of Ixodes scapularis from fed larva to feeding nymph, and the fraction of nymphs finding a competent host, are the most influential factors for R0. This contrasts with other vector borne pathogens where it is usually the abundance of the vector or host, or the vector-to-host ratio, that determine conditions for emergence. These results are a step towards a better understanding of the geographical expansion of currently emerging horizontally transmitted tick-borne pathogens such as Babesia microti, as well as providing a firmer scientific basis for targeted use of acaricide or the application of wildlife vaccines that are currently in development.

Fluid-structure interaction analysis by coupled FE-SPH model based on a novel searching algorithm

Fluid–Structure Interaction (FSI) problem is significant in science and engineering, which leads to challenges for computational mechanics. The coupled model of Finite Element and Smoothed Particle Hydrodynamics (FE-SPH) is a robust technique for simulation of FSI problems. However, two important steps of neighbor searching and contact searching in the coupled FE-SPH model are extremely time-consuming. Point-In-Box (PIB) searching algorithm has been developed by Swegle to improve the efficiency of searching. However, it has a shortcoming that efficiency of searching can be significantly affected by the distribution of points (nodes in FEM and particles in SPH). In this paper, in order to improve the efficiency of searching, a novel Striped-PIB (S-PIB) searching algorithm is proposed to overcome the shortcoming of PIB algorithm that caused by points distribution, and the two time-consuming steps of neighbor searching and contact searching are integrated into one searching step. The accuracy and efficiency of the newly developed searching algorithm is studied on by efficiency test and FSI problems. It has been found that the newly developed model can significantly improve the computational efficiency and it is believed to be a powerful tool for the FSI analysis.

A Bayesian hurdle model for analysis of an insect resistance monitoring database

Motivated by the analysis of the Australian Grain Insect Resistance Database (AGIRD), we develop a Bayesian hurdle modelling approach to assess trends in strong resistance of stored grain insects to phosphine over time. The binary response variable from AGIRD indicating presence or absence of strong resistance is characterized by a majority of absence observations and the hurdle model is a two step approach that is useful when analyzing such a binary response dataset. The proposed hurdle model utilizes Bayesian classification trees to firstly identify covariates and covariate levels pertaining to possible presence or absence of strong resistance. Secondly, generalized additive models (GAMs) with spike and slab priors for variable selection are fitted to the subset of the dataset identified from the Bayesian classification tree indicating possibility of presence of strong resistance. From the GAM we assess trends, biosecurity issues and site specific variables influencing the presence of strong resistance using a variable selection approach. The proposed Bayesian hurdle model is compared to its frequentist counterpart, and also to a naive Bayesian approach which fits a GAM to the entire dataset. The Bayesian hurdle model has the benefit of providing a set of good trees for use in the first step and appears to provide enough flexibility to represent the influence of variables on strong resistance compared to the frequentist model, but also captures the subtle changes in the trend that are missed by the frequentist and naive Bayesian models.